From 769ded71a9ff931699400372a03fb8c1d40f30b4 Mon Sep 17 00:00:00 2001 From: jenzenho <46580415+jenzenho@users.noreply.github.com> Date: Wed, 24 Sep 2025 13:38:57 -0700 Subject: [PATCH 1/2] Renamed the dataset URLs to be more descriptive. --- _datasets/brouzet2021.md | 43 -------- _datasets/chung2022.md | 28 ----- _datasets/chung2024.md | 34 ------ _datasets/coulon.md | 29 ----- _datasets/gauding2022.md | 91 ---------------- _datasets/guo2022.md | 33 ------ _datasets/ho2024.md | 95 ----------------- _datasets/jiang2021.md | 36 ------- _datasets/jung2021.md | 32 ------ _datasets/mklee2025.md | 212 ------------------------------------- _datasets/pkyeung2025.md | 121 --------------------- _datasets/poludnenko.md | 33 ------ _datasets/quentin2024.md | 148 -------------------------- _datasets/roshan2024.md | 180 ------------------------------- _datasets/savard.md | 181 ------------------------------- _datasets/shantanu.md | 223 --------------------------------------- _datasets/sharma2024.md | 117 -------------------- _datasets/wang2024.md | 156 --------------------------- 18 files changed, 1792 deletions(-) delete mode 100644 _datasets/brouzet2021.md delete mode 100644 _datasets/chung2022.md delete mode 100644 _datasets/chung2024.md delete mode 100644 _datasets/coulon.md delete mode 100644 _datasets/gauding2022.md delete mode 100644 _datasets/guo2022.md delete mode 100644 _datasets/ho2024.md delete mode 100644 _datasets/jiang2021.md delete mode 100644 _datasets/jung2021.md delete mode 100644 _datasets/mklee2025.md delete mode 100644 _datasets/pkyeung2025.md delete mode 100644 _datasets/poludnenko.md delete mode 100644 _datasets/quentin2024.md delete mode 100644 _datasets/roshan2024.md delete mode 100644 _datasets/savard.md delete mode 100644 _datasets/shantanu.md delete mode 100644 _datasets/sharma2024.md delete mode 100644 _datasets/wang2024.md diff --git a/_datasets/brouzet2021.md b/_datasets/brouzet2021.md deleted file mode 100644 index cc05a53..0000000 --- a/_datasets/brouzet2021.md +++ /dev/null @@ -1,43 +0,0 @@ ---- -layout: datapage -excerpt: (2 cases) -title: Reacting Jet Flows -description: Turbulent Round Jet Premixed COFFEE CH4-air Premixed Flame DNS -header: - teaser: /assets/img/ico_brouzet2021.png -categories: - - reacting - - turbulent - - jet - - numerical ---- - -
- Image 1 -
- -## Description - -The DNS configurations by Brouzet et al. involve two parametric variations of 3D reacting turbulent premixed methane/air round-jet flames with high-fidelity acoustics to investigate the effect of different chemical mechanisms on flame dynamics. The setup is initialized with methane/air combustion products at adiabatic flame temperature and at atmospheric pressure. The jet Reynolds and Mach numbers are 5300 and 0.36, respectively. A schematic representation of the DNS configuration is shown in Figure 10. The two variations of the reacting jet correspond to two different chemical mechanisms: (i) a semi-global CH4-BFER mechanism with 2 reactions, and (ii) a skeletal COFFEE mechanism with 14 species and 38 reactions. In both configurations, the domain size is 20D×16D×16D. The grid sizes are 1811×721×721 and 1546×676×676 for the BFER and COFFEE cases, respectively. These meshes correspond to 10 and 12 grid points per unit thermal flame thickness in the streamwise direction, and 12 and 16 points in the transverse and spanwise directions. - -The DNS is performed using the code NTMIX-CHEMKIN, which solves fully compressible Navier-Stokes equations along with energy and species conservation equations in Cartesian coor- dinates. The solver uses an eight-order explicit central spatial difference scheme and a third-order Runge-Kutta time integration scheme. Ideal gas law and mixture-averaged species-specific properties are used for the simulations. Further details of the DNS configuration and solver are provided in Brouzet et al. - -## Quick Info -* Contributors: Davy Brouzet, Mohsen Talei -* DOI -* .bib - -## BFER Case -* Kaggle Link
-* Nx = 1832, Ny = 721, Nz = 721, Nɸ = 6 + 6 -* Size = 58 GB -info.json - -## COFFEE Case -* Kaggle Link -* Nx = 1235, Ny = 676, Nz = 676, Nɸ = 6 + 14 -* Size = 52 GB -* info.json - - - diff --git a/_datasets/chung2022.md b/_datasets/chung2022.md deleted file mode 100644 index 0fe3d52..0000000 --- a/_datasets/chung2022.md +++ /dev/null @@ -1,28 +0,0 @@ ---- -layout: datapage -title: Non-reacting HIT -excerpt: (1 case) -header: - teaser: /assets/img/ico_chung2022.png -description: Compressible Inert CH4-O2 Homogeneous Isotropic Turbulence DNS -categories: -- nonreacting -- numerical -- turbulent -- hit ---- - -![image](./assets/img/chung2022.png) - -## Description - -The HIT DNS simulation is performed on a 3D cubic domain of length L, where a spherical gaseous-oxygen core of radius r = 0.25L at 300 K is initialized in gaseous methane environment of 300 K at 1 atm pressure, providing an idealized representation of an inert gaseous fuel-air mixture in a rocket engine. Periodic boundary conditions are used at all boundaries. A synthetic turbulence generator by Saad et al. based on von Kármán-Pao energy spectrum with zero mean velocity is used to generate the initial velocity profile. Ideal gas law is used as the equation of state (EoS) to relate pressure, temperature and density. The simulation is performed in an unstructured compressible finite-volume solver [64]. The solver uses a fourth-order accurate central spatial finite difference scheme. For the time integration, a stable third-order Runge-Kutta scheme is employed. Mixture-averaged transport properties are used in the DNS. - -## Quick Info -* Kaggle Link
-* Contributors: Wai Tong Chung, Matthias Ihme -* Nx = 129, Ny = 129, Nz = 129, Nɸ = 6 + 2 -* Size = 6 GB -* DOI
-* .bib
-* info.json diff --git a/_datasets/chung2024.md b/_datasets/chung2024.md deleted file mode 100644 index 23a2b3b..0000000 --- a/_datasets/chung2024.md +++ /dev/null @@ -1,34 +0,0 @@ ---- -layout: datapage -title: BLASTNet Momentum128 3D SR Dataset -excerpt: -header: - teaser: /assets/img/ico_chung2022.png -description: Collection of BLASTNet Simulations -categories: -- numerical -- nonreacting -- turbulent -- hit -- pipe -- channel -- jet -- benchmark ---- - -![image](./assets/img/diversity.png) - -## Description -The BLASTNet Momentum128 3D SR Dataset is a benchmark dataset for developing and evaluating 3D super-resolution (SR) methods on turbulent flow data. It is a curated subset of the larger BLASTNet datasets, specifically designed to facilitate high-fidelity reconstruction of velocity fields from low-fidelity fields. This dataset includes 2,000 volumetric samples of 128$$^3$$ grid points, each containing the three components of the velocity field (u, v, w) and the density. The sub-volumes were extracted from high-resolution direct numerical simulations (DNS) which span a range of flow regimes and statistical variations. - -Each sample is accompanied by pre-computed low-resolution inputs at multiple downsampling ratios (e.g., 8×, 16×, and 32×), enabling the evaluation of SR models under different reconstruction challenges. Data is provided in binary .dat format using single-precision floating point (little-endian) ordering. The dataset is split into training, validation, and test sets, with metadata stored in accompanying CSV. These include physical statistics summary (e.g., skewness, kurtosis, variance). - - -## Quick Info -* Kaggle Link
-* Contributors: Wai Tong Chung, Bassem Akoush, Matthias Ihme -* Nx = 128, Ny = 128, Nz = 128, Nɸ = 4 -* Size = 75.15 GB -* DOI
-* .bib
- diff --git a/_datasets/coulon.md b/_datasets/coulon.md deleted file mode 100644 index 0685a1e..0000000 --- a/_datasets/coulon.md +++ /dev/null @@ -1,29 +0,0 @@ ---- -layout: datapage -title: Premixed Flame NH3-H2-Air -description: NH3-H2-Air Premixed Flame DNS -excerpt: (1 case) -header: - teaser: /assets/img/ico_coulon2023.png -categories: -- reacting -- turbulent -- jet -- numerical ---- - -
- Image 1 -
- -## Description -This DNS corresponds to a slot burner turbulent flame, where burnt gases at equilibrium surround a rectangular slot injecting fresh premixed gases. All calculations are performed with the compressible solver AVBP3 for solving the conservation of mass, momentum, energy and species equations. A third-order accurate in space and time Taylor-Galerkin finite-element scheme is used for the discretization of the convective terms, while a second-order Galerkin scheme is used for diffusion terms. Axial dimensions have been chosen using preliminary estimations of flame brush lengths to avoid interference with lateral boundaries, and to average in the transverse direction. A central jet injects a flow of fresh turbulent gases. Turbulence in this central jet is homogeneous and isotropic (HIT) with obtained by a synthetic generation method built from a Fourier series decomposition. Two slow laminar coflows of burnt gases are imposed on both sides of the central jet. Their composition corresponds to the burnt gas states of the central mixture. Ammonia-hydrogen/air mixtures are at stoichiometry whereas the. Simulations are initialized with burnt conditions inside the domain before beginning the injection of fresh gases at the inlet boundary. In the fresh-burnt transition region, species mass fraction and temperature profiles are set to follow the unstretched laminar flames profiles, and a smooth transition is enforced through a hyperbolic tangent function. The domain is periodic in the spanwise direction (z), no-slip conditions are specified in the crosswise direction (y) and static pressure is imposed at the outlet. Both inlet and outlet boundary conditions are treated with the Navier–Stokes Characteristic Boundary Conditions (NSCBC). - -## Quick Info -* Kaggle1, Kaggle2, Kaggle3, Kaggle4 -* Contributors: Victor Coulon and Corentin Lapeyre -* Nx = 2191, Ny = 627, Nz = 314, Nɸ = 6 + 15 -* Size = 257 GB -* DOI
-* .bib
-* info.json1 , info.json2 , info.json3 ,info.json4 diff --git a/_datasets/gauding2022.md b/_datasets/gauding2022.md deleted file mode 100644 index 6204ad4..0000000 --- a/_datasets/gauding2022.md +++ /dev/null @@ -1,91 +0,0 @@ ---- -layout: datapage -excerpt: (6 cases) -title: Forced HIT (Re$$_\lambda$$ = 88-331) -description: Passive Scalar HIT DNS -header: - teaser: /assets/img/ico_gauding2022.png -categories: -- nonreacting -- hit -- numerical -- turbulent ---- - -
- Image 1 -
- -# Description -This DNS configuration simulates non-reacting forced homogeneous isotropic turbulence with a passive scalar. The DNS solver utilizes the analytical framework developed by Gauding et al., which is designed to investigate the structure and kinematics of iso-scalar fields. This approach involves a two-point statistical analysis of the phase indicator field to track a specified iso-scalar volume. The scalar field is represented as ξ̃ =Gξ y + ξ with the mean scalar gradient Gξ assumed to be unity. The first term represents the mean scalar field while the second term is the fluctuations. To maintain a statistically steady state, external stochastic forcing is applied to the velocity field, as described by Eswaran and Pope (1988). This forcing is statistically isotropic and restricted to low wavenumbers to minimize its impact on small scales. The BLASTNet dataset includes five parametric variations of this configuration, differing by (i) Reynolds number based on the Taylor microscale, and (ii) grid size. Each configuration contains four variables: the velocity components (u, v, w) and the scalar fluctuation field ξ. - - -# Quick Info -* Contributors: Michael Gauding -* Nɸ = 4 -* DOI -* .bib - -# Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IDConditionsGridSize (GB)Links
0 Reλ = 88512325.23 - Kaggle, - info.json, -
1 Reλ = 12110243131.14 - Kaggle, - info.json, -
2 Reλ = 18410243133.14 - Kaggle, - info.json, -
3 Reλ = 21820483137.44 - Kaggle, - info.json, -
4 Reλ = 33120483137.44 - Kaggle, - info.json, -
diff --git a/_datasets/guo2022.md b/_datasets/guo2022.md deleted file mode 100644 index 3e52f70..0000000 --- a/_datasets/guo2022.md +++ /dev/null @@ -1,33 +0,0 @@ ---- -layout: datapage -title: Non-Reacting N$$_2$$ Channel Flow -excerpt: (6 cases) -header: - teaser: /assets/img/ico_guo2022.png -categories: -- nonreacting -- channel -- turbulent -- numerical -description: Transcritical Channel Flow N2 Turbulence DNS ---- - -
- Image 5 -
- -## Description - -The study by Guo et al. involves six different configurations of wall-bounded DNS in the transcritical regime. The schematic of the DNS setup is shown in Figure 11. They used nitrogen N2 as the working fluid with a critical pressure and temperature of pc = 3.39 MPa and Tc = 126.19 K. These studies consider the flow of N2 inside a channel with a hot top and a cold bottom wall with temperatures Thot and Tcold, respectively. The six variations correspond to different temperature ratio (TR) between the two walls. The channel is periodic in streamwise and spanwise direction, while the wall boundary conditions are enforces at two walls. The domain dimensions are Lx × 2Ly × Lz , where Lx/Ly = 2π, Lz/Ly = 4π/3 and the channel height is 2Ly = 9.0132×10−5 m. A Cartesian grid (with mesh size 384 × 256 × 384) is used for all six configurations. - -A compressible finite-volume solver is used for these DNS. The governing equations are solved using a strong stability-preserving Runge-Kutta scheme with third-order accuracy in time step- ping, and a fourth-order accurate central spatial finite difference, which reduces to third-order for non-uniform meshes. As the conditions of these simulations are in the transcritical regime, the Peng-Robinson EoS is used, which provides better accuracy in predicting thermodynamic variables than ideal gas in the investigated regime. To avoid the pressure oscillations and to obtain physically realizable solutions, an entropy-stable double-flux model is used along with second-order accurate essentially non-oscillatory (ENO) scheme and Harten-Lax-Van Leer contact (HLLC) Riemann flux computations. - - -## Quick Info -* Kaggle Link -* Contributors: Jack Guo, Matthias Ihme -* Nx = 385, Ny = 257, Nz = 257, Nɸ = 6 -* Size = 93 GB -* DOI
-* .bib
-* info.json diff --git a/_datasets/ho2024.md b/_datasets/ho2024.md deleted file mode 100644 index b49c06b..0000000 --- a/_datasets/ho2024.md +++ /dev/null @@ -1,95 +0,0 @@ ---- -layout: datapage -excerpt: (4 cases) -title: H2/CH4 Turbulent Jet Flows -description: H2/CH4 Fuel Mixtures, Turbulent Round Jet Premixed Flame DNS -header: - teaser: /assets/img/ho2024_ico.png -categories: -- reacting -- jet -- turbulent -- numerical ---- - -
- Image 1 -
- -## Description - -The DNS configurations by Ho et al. [1] investigates four turbulent round jet flames fueled by 0, 10, 50, and 80% hydrogen by volume, with the rest by methane, while maintaining the jet Reynolds number at 10,300. The jet is preheated to 450 K and the coflow is set to the adiabatic combustion products. The setup is initialized with combustion products at adiabatic flame temperature and at atmospheric pressure. A reduced mechanism with Quasi-Steady State chemistry is used, resulting in 16 transported species and 7 QSS species. The original simulation domain size is 25D×16D×16D, though note that the sponge layer data has been removed from this dataset, resulting in a 19.3D×5D×5D domain. After removal of the sponge layer, the grid sizes are 1739×620×620, 1749×486×486, 1730×571×571, and 1831×654×654 for the H0, H10, H50, and H80 cases, respectively. Five snapshots of each case is provided. - -The DNS is performed using the code NTMIX-CHEMKIN, which solves fully compressible Navier-Stokes equations along with energy and species conservation equations in Cartesian coordinates. The solver uses an eight-order explicit central spatial difference scheme and a third-order Runge-Kutta time integration scheme. Ideal gas law and mixture-averaged species-specific properties are used for the simulations. Further details of the DNS configuration and solver are provided in Ho et al. [1]. - -## Quick Info -* Contributors: Jen Zen Ho, Mohsen Talei -* DOI -* .bib - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IDConditionsSize (GB)Links
0 0% H2 100% CH4790 - Kaggle1, info.json1
- Kaggle2, info.json2
- Kaggle3, info.json3
- Kaggle4, info.json4
- Kaggle5, info.json5
-
1 10% H2 90% CH4490 - Kaggle1, info.json1
- Kaggle2, info.json2
- Kaggle3, info.json3
- Kaggle4, info.json4
- Kaggle5, info.json5
-
2 50% H2 50% CH4654 - Kaggle1, info.json1
- Kaggle2, info.json2
- Kaggle3, info.json3
- Kaggle4, info.json4
- Kaggle5, info.json5
-
3 80% H2 20% CH4878 - Kaggle1, info.json1
- Kaggle2, info.json2
- Kaggle3, info.json3
- Kaggle4, info.json4
- Kaggle5, info.json5
-
- -## References -[1]. J. Z. Ho, M. Talei, and R. L. Gordon. Direct numerical simulation of stoichiometric hydrogen/methane premixed jet flames. International Journal of Hydrogen Energy 81, pp. 831-841 (2024). diff --git a/_datasets/jiang2021.md b/_datasets/jiang2021.md deleted file mode 100644 index 74ee92c..0000000 --- a/_datasets/jiang2021.md +++ /dev/null @@ -1,36 +0,0 @@ ---- -layout: datapage -title: Reacting Channel Flow -excerpt: (1 case) -header: - teaser: /assets/img/ico_jiang2021.png -description: Premixed Flame-wall Interaction CH4-Air DNS -categories: -- reacting -- channel -- numerical -- turbulent ---- - -
- Image 1 -
- -## Description - -This DNS configuration by Jiang et al. investigates the flame-wall interaction for methane/air flames diluted by hot combustion products in a 3D turbulent V-flame configuration inside a channel with isothermal hot and cold walls. At the inlet of the channel, the reactant mixture consists of a mixture of cold reactants (30%) and hot combustion products from 1D premixed freely-propagating flame simulation (70%), resulting in an inlet temperature of Tin = 1705 K at 2 atm pressure. The hot and cold wall temperatures are fixed at 1200 and 400 K, respectively. The inlet turbulence is generated with a non-reacting simulation of the same channel. Then, the results collected at a sampling plane of x/H = 4 are fed into the reacting simulation. This turbulence generation allows coupling of the velocity and temperature fluctuations at the inlet. - -Velocity fluctuations are first produced using the Passot-Pouquet spectrum for the turbulent kinetic energy. The inlet turbulence for the non-reacting simulation was then generated by rescaling these fluctuations with the RMS profiles of a fully developed channel flow at a Reynolds number of 3200. Next, this is fed into the domain with a convection velocity 25% lower than the mean inlet velocity at the centerline. This accounts for a correction to the Taylor’s hypothesis due to the high near-wall shear stress. Non-reflecting Navier-Stokes Characteristic Boundary Condition (NSCBC) is used for the outlet boundary, and a periodic boundary condition is used in the z-direction. For the reacting case to ignite, a cylindrical hot patch is imposed at y/H = 0 and x/H = 1 with a diameter of 0.03H, which creates two branches of the V-flame that interact with two walls. - -The domain size is 12H × 2H × 3H, with a grid size of 1000 × 250 × 250, which stretches from 5 μm at the wall to 30 μm at the centerline in the y-direction, and 30 μm uniform grid in both x- and z-direction, and ensures at least one grid point within one wall unit and a mean grid size less than 1.4 times the Kolmogorov length scale. There are around 20 grid points inside the flame thickness as well. - -The numerical solver used for the DNS study is NTMIX-CHEMKIN. This solver features an eighth-order central finite difference scheme for spatial derivatives and a third-order Runge-Kutta time integrator. A tenth-order explicit filter is also used to eliminate spurious oscillations at high wave numbers. Ideal gas law is used as the EoS. A reduced mechanism for methane/air combustion with 23 species, 12 quasi-steady species and 205 reactions is developed for this study. - -## Quick Info -* Kaggle Link
-* Contributors: Bin Jiang, Mohsen Talei -* Nx = 1001, Ny = 251, Nz = 251, Nɸ = 6 + 23 -* Size = 89 GB -* DOI
-* .bib
-* info.json diff --git a/_datasets/jung2021.md b/_datasets/jung2021.md deleted file mode 100644 index 8372ce7..0000000 --- a/_datasets/jung2021.md +++ /dev/null @@ -1,32 +0,0 @@ ---- -layout: datapage -title: Slot Burner -excerpt: (1 case) -header: - teaser: /assets/img/ico_jung2021.png -description: Slot Burner Diluted Partially-Premixed H2-air Lifted Flame DNS -categories: -- numerical -- reacting -- jet -- turbulent ---- - -
- Image 1 -
- -## Description - -This DNS configuration involves a turbulent lifted hydrogen jet flame in heated co-flow air. A diluted fuel mixture (65% H2 and 35% N2 by volume) is issued from the central slot at an inlet temperature of 400 K. This central jet is surrounded on either side by co-flowing heated air streams with an inlet temperature of 850 K, at atmospheric pressure. The jet width at the inlet is 2 mm. The jet Reynolds number is 8000. Velocity fluctuations, u′, which is 10% of Ujet, is obtained by generating an auxiliary homogeneous isotropic turbulence field. These fluctuations are then fed from the inlet using Taylor’s hypothesis. This 2000 × 1600 × 400 computational domain is 15H × 20H × 3H in the streamwise x-, transverse y-, and spanwise z- directions, respectively, resulting in a total of 1.28 billion cells. A uniform grid size of 15 μm is placed in the x- and z-directions, while the y-directional grid is algebraically stretched outside the flame and shear zones. Improved non-reflecting boundary conditions are adopted in the x- and y-directions, while periodic boundary conditions are applied in the z-direction. The data is collected after four jet flow-through times after the flame becomes statistically stationary. - -The Sandia DNS code, S3D, is employed for solving the compressible Navier–Stokes, species conservation, and total energy equations. Spatial derivatives are approximated with an eighth-order central difference scheme, and a tenth-order filter is used to remove any spurious high-frequency fluctuations in the solution. For time integration, a fourth-order explicit Runge-Kutta method is used. The employed detailed hydrogen-air chemical mechanism composed of 9 species and 21 elementary reaction steps was developed by Li et al. - -## Quick Info -* Kaggle Link
-* Contributors: Ki Sung Jung, Jacqueline H. Chen -* Nx = 2000, Ny = 1600, Nz = 400, Nɸ = 6 + 9
-* Size = 93 GB -* DOI
-* .bib
-* info.json diff --git a/_datasets/mklee2025.md b/_datasets/mklee2025.md deleted file mode 100644 index c5a3bad..0000000 --- a/_datasets/mklee2025.md +++ /dev/null @@ -1,212 +0,0 @@ ---- -layout: datapage -excerpt: (2 cases) -title: Non-Reacting Channel Flow -description: Non-Reacting Channel Flow DNS -header: - teaser: /assets/img/ico_mklee2015.png -categories: -- nonreacting -- channel -- turbulent -- numerical ---- - - -## Description -These snapshots are from a Direct Numerical Simulation (DNS) of incompressible turbulent channel flow at friction Reynolds number $$Re_\tau = 544$$ and bulk Reynolds number $$Re_b = 10,000$$ [1]. The computational domain has dimensions $$L_x = 8\pi$$ and $$L_z = 3\pi$$ in the streamwise and spanwise directions respectively, with periodic boundary conditions applied in both directions. The channel width is set to $$L_y = 2$$. No-slip/no-penetration boundary conditions are enforced at the walls. The flow is driven by a uniform pressure gradient that varies in time to maintain constant mass flux through the channel. -The numerical methods employ a Fourier-Galerkin approach in the streamwise and spanwise directions. The wall-normal direction is represented using a B-spline collocation method. Time advancement employs a low-storage implicit-explicit scheme based on third-order Runge-Kutta for nonlinear terms and Crank-Nicolson for viscous terms. Each snapshot captures the complete three-dimensional flow field including all three velocity components (u, v, w) at a given time. - -## Quick Info -* Contributors: Myoungkyu Lee -* Nx = 1536, Ny = 384, Nz = 1024 -* Nɸ = 4 -* DOI -* .bib - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - -
IDRe$_{\tau}$DescriptionSize (TB)Links
0 544One Flow Through Time4.5 -
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- Kaggle357-377, info.json357-377, -
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- Kaggle378-398, info.json378-398, -
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- Kaggle441-461, info.json441-461, -
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- Kaggle462-482, info.json462-482, -
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- Kaggle483-503, info.json483-503, -
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- Kaggle504-509, info.json504-509, -
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1 544Collection of snapshots at different time4.5 -
- Kaggle000-020, info.json000-020, -
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- Kaggle021-041, info.json021-041, -
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- Kaggle042-062, info.json042-062, -
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- Kaggle084-104, info.json084-104, -
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- Kaggle105-125, info.json105-125, -
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- Kaggle126-146, info.json126-146, -
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- Kaggle315-335, info.json315-335, -
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- Kaggle378-398, info.json378-398, -
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- Kaggle420-440, info.json420-440, -
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- Kaggle441-461, info.json441-461, -
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- Kaggle462-482, info.json462-482, -
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- Kaggle483-503, info.json483-503, -
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- Kaggle504-509, info.json504-509, -
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- -## References -[1] Lee, M., & Moser, R. D. (2015). Direct numerical simulation of turbulent channel flow up to Reτ ≈ 5200. Journal of Fluid Mechanics, 774, 395-415. diff --git a/_datasets/pkyeung2025.md b/_datasets/pkyeung2025.md deleted file mode 100644 index e618c8c..0000000 --- a/_datasets/pkyeung2025.md +++ /dev/null @@ -1,121 +0,0 @@ ---- -layout: datapage -excerpt: (2 cases) -title: Forced HIT (Re$$_\lambda$$ = 390, 650) -description: Forced Homogeneous Isotropic Turbulence DNS with 3 Passive Scalars -header: - teaser: /assets/img/ico_pkyeung2025.png -categories: -- numerical -- nonreacting -- hit -- turbulent ---- -
- Image 1 -
- -## Description -These snapshots are from a series of Direct Numerical Simulations (DNS) of passive scalar mixing in three-dimensional homogeneous isotropic turbulence, at grid resolution up to $$16384^3$$ [1], performed using the exascale supercomputer named Frontier at Oak Ridge National Laboratory. The velocity fluctuations evolve according to the incompressible Navier-Stokes equations, while the scalar fluctuations follow an advection-diffusion equation, with a source term representing an imposed mean scalar gradient. The numerical methods employed are standard Fourier pseudo-spectral in space, second order in time, with aliasing errors controlled by a combination of phase shifting and truncation [2]. The velocity field is forced by keeping the values of the energy spectrum in the three lowest wavenumber shells constant [3]. - -The simulations begin from previously evolved velocity fields and are first run at a modest resolution of $$k_{max}\eta \approx 1.4$$ (where $$k_{max} = \sqrt 2 N/3$$ is the highest wavenumber resolved on an $$N^3$$ grid and $$\eta$$ is the Kolmogorov length scale) until the scalar fields reach statistical stationarity. The grid is then -refined to a higher resolution of $$k_{max} η \approx 2.8$$, and the simulation proceeds until the smallest scales fully adjust. Snapshots at this highest resolution have been collected for Taylor-scale Reynolds -numbers $$Re_\lambda \approx 390, 650, 1000 \text{ and } 1600$$. The Schmidt number is $$1.0$$ in all cases. Each snapshot captures the complete flow field — including velocity, pressure, and three passive -scalars — at a single instant in time. The three scalars are each subjected to a uniform mean gradient along a different coordinate direction. - - -## Quick Info -* Contributors: P.K Yeung, Daniel Dotson -* Nɸ = 4 + 3 - -* DOI -* .bib - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IDRe$_{\lambda}$GridSize (GB)Links
0 39020483225` -
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- -## References -[1] D. L. Dotson, P. K. Yeung, and K. R. Sreenivasan. A Study of passive scalar turbulence at high Reynolds numbers enabled by exascale computing. Bull. Am. Phys. Soc. -https://meetings.aps.org/Meeting/DFD24/Session/R37.00003, 2024. -[2] R. S. Rogallo. Numerical experiments in homogeneous turbulence. NASA TM 81315, NASA Ames Research Center, Moffett Field, CA., 1981. -[3] D. A. Donzis and P. K. Yeung. Resolution effects and scaling in numerical simulations of passive -scalar mixing in turbulence. Physica D, 239:1278–1287, 2010. diff --git a/_datasets/poludnenko.md b/_datasets/poludnenko.md deleted file mode 100644 index 83f691e..0000000 --- a/_datasets/poludnenko.md +++ /dev/null @@ -1,33 +0,0 @@ ---- -layout: datapage -title: Reacting Forced HIT -excerpt: (1 case) -description: CH4-Air Flame Interaction With Forced HIT DNS -header: - teaser: /assets/img/ico_poludnenko.png -categories: -- reacting -- hit -- turbulent -- numerical ---- - -![image](./assets/img/poludnenko.png) - -## Description - -TThe DNS study involves a statistically steady, isotropic, and homogeneous turbulent flow in an unconfined space. The flame is initialized by a planar surface separating half of the domain containing methane/air mixture at 700 K and 3.04 × 107 erg cm−3 pressure, and another half with hot products, and is immersed in a high-intensity turbulent flow field with Kolmogorov type spectrum. The idea is to investigate the process of flame interaction with steady homogeneous isotropic turbulence. However, the flow needs to be constantly stirred at the largest scale to ensure a steady energy cascade to smaller scales so that the turbulence-flame interaction at the quasi-steady state can be studied. A spectral turbulence- driving method is used in the study, the details of which are available in Poludnenko and Oran. This driving method produces statistically steady forced-HIT flows with arbitrarily complex energy spectra. In particular, it is possible to achieve Kolmogorov type turbulence with inertial range of energy cascade extending up to energy injection scale. The other advantage of this method is that it does not introduce any artificial large-scale anisotropy, compression, or rarefaction. Prior to ignition, all domain boundaries are periodic. At ignition, boundary conditions along the left and right z-boundaries (as shown in Figure 9) are switched to zero-order extrapolation to prevent any non-physical pressure build-up in the domain and the formation of artificial large-scale rarefaction waves at the boundaries. - -The computational domain aspect ratio is 1 × 1 × 16, with a grid size of 257 × 257 × 4097, including 16 grid points per unit laminar flame thermal thickness. The cell size is 2.62 × 10−4 cm. The turbulent velocity at energy injection scale (L = 0.067 cm) length scale is 213.92 cms−1 with turbulent root-mean-squared (RMS) velocity of 245.83 cms−1, resulting in an eddy turnover time of 3.14×10−4 s. The same velocity quantities corresponding to the integral length scale (l = 0.0196 cm) are 141.93 cms−1 and 132.2 cms−1. The ignition delay time of the mixture is three times the eddy turn-over time, and the total simulation runtime is 16 times the eddy turn-over time. The Damköhler and Karlovitz numbers are 0.66 and 9.97, respectively. - -The DNS calculation is performed using the code Athena-RFX, which implements higher-order fully conservative Godunov-type methods for integration of fluid equations. The numerics in this work are third-order accurate in space and second-order accurate in time. More details are available in the original paper. The foundational fuel chemistry model (FFCM-1) with 22 species and 107 reactions is used as the chemical mechanism. - - -## Quick Info -* Kaggle Link -* Contributors: Alexei Y. Poludnenko -* Nx = 257, Ny = 257, Nz = 4097, Nɸ = 6 + 21 -* Size = 30 GB -* DOI
-* .bib
-* info.json diff --git a/_datasets/quentin2024.md b/_datasets/quentin2024.md deleted file mode 100644 index ac795ca..0000000 --- a/_datasets/quentin2024.md +++ /dev/null @@ -1,148 +0,0 @@ ---- -layout: datapage -excerpt: (5 cases) -title: Premixed Flame H2-Air -description: Premixed Flame H2-Air DNS in Slot Burner -header: - teaser: /assets/img/ico_quentin2024.png -# image: /assets/img/quentin2024.png -categories: -- reacting -- jet -- turbulent -- numerical ---- -
- Image 1 -
- -## Description -The configuration is a slot burner at constant pressure $$P = 1$$ atm and fresh gas temperature $$T_u = 300$$ K used to generate a training database for the modeling of subfilter-scale features in lean premixed H$$_2$$-air reacting flows using a CNN [1]. The physical domain consists of a central inlet where a premixed H2-air mixture flows at a bulk velocity $$U_b = 24$$ m/s with velocity fluctuation $$u′= 2.4$$ m/s, surrounded by two laminar coflows where burnt gas flows at a bulk velocity $$U_c = 3.6$$ m/s. The injection of turbulence at the central inlet corresponds to homogeneous and isotropic turbulence using a Passot-Pouquet turbulence spectrum [2] with an integral length scale $$l_t = 2$$ mm. The domain is rectangular with periodic boundary conditions in the z-direction. Adiabatic walls are specified in the y-direction. Both inlets and outlet are specified in the x-direction. This configuration is computed for five different global equivalence ratios $$\phi_g = $$ 0.35, 0.4, 0.5, 0.6 and 0.7. All other parameters are kept constant. The Reynolds number of the central inlet is about 10,000 for all cases. -DNS of the slot burner cases are performed using the AVBP [3] massively parallel code solving the -compressible multi-species Navier-Stokes equations. A third order accurate Taylor–Galerkin scheme is adopted -for discretization of the convective terms [4]. NSCBC [5] are imposed at the inlets (relaxation factor of 1000 -s−1) and at the outlet (relaxation factor of 200 s−1). Dynamic viscosity µ follows a power law function of -temperature $$T$$ - - -$$\mu = \mu_0 \left(\frac{T}{T_0}\right)^\gamma$$ - -with $$\mu_0 = 8.062 × 10−5$$ kg/m.s, $$T_0 = 2.645 \times 10^3$$ K and $$γ = 6.481 \times 10^{−1}$$. Thermal diffusivity is computed -from the viscosity using a constant Prandtl number: $$Pr = 0.66$$. Species diffusivities are computed using -a constant Schmidt number specific for each species. This approach takes into account non-unity -Lewis numbers and preferential diffusion between the different species. It was verified that the errors made by -the simplified transport description are negligible by comparing the results with simulations using a mixture- -averaged transport model [1]. Soret and Dufour transport processes are ignored in the simulations of the present -work. Hydrogen chemical kinetics relies on the San Diego mechanism [6], already successfully used for H2-air -premixed combustion in Coulon et al. [7]. This mechanism comprises 9 species and 21 reactions. - -The mesh is a homogeneous Cartesian grid with constant element size $\Delta_x = 80 \mu m$ for $$\phi_g = 0.35, 0.4$$ and -$$0.6$$, and $$\Delta_x = 50 \mu m$$ for $$\phi_g = 0.6\ \mathrm{and}\ 0.7$$. The length of the domain in the x-direction $$L_x$$ is adapted to the length of turbulent the flame brush. It varies from 76 mm for $$\phi_g = 0.35$$ to $$36$$ mm for $$\phi_g= 0.7$$. - -## Application -This database was generated to train a CNN to infer H$$_2$$-air burning rates. The data-driven, supervised learning -methodology is described in Malé et al. [1]. It involves using the database, filtered to emulate LES solutions, to train a -CNN to approximate burning rates based on relevant input variables. The emulated LES database comprises the -five different global equivalence ratios of the present DNS database and three different filter sizes. Random crops, -rotations and flips are performed to ensure that the CNN is invariant to translation [8] and has no preferential -orientation. Once trained, the CNN-based model is shown to infer burning rates on full LES solutions never -seen during training with high accuracy. In addition to this, the model is found to infer burning rates on filter -sizes and equivalence ratios other than those used for training. More details can be found in Malé et al. [1]. Code for -training and inference is available via GitLab at https://gitlab.com/male.quentin/cnn_h2flame. - -
- Image 1 -
- -## Quick Info -* Contributors: Quentin Malé -* Nɸ = 6 + 9 - -* DOI -* .bib - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
ID$$\phi_g$$GridSize (GB)Links
0 0.35951×401×20116 - Kaggle, info.json
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1 0.4901×401×20115 - Kaggle, info.json
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2 0.5651×401×20111 - Kaggle, info.json
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3 0.61041×641×32131 - Kaggle, info.json
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4 0.7721×641×32145 - Kaggle, info.json
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- -## References -[1] Malé, Q., Lapeyre, C. J., and Noiray, N. (2024). Hydrogen reaction rate modeling based on convolutional -neural network for large eddy simulation. Accepted for publication in Data-Centric Engineering, to appear. -arXiv:2408.16709 [cs.CE]. -[2] Passot, T. and Pouquet, A. (1987). Numerical simulation of compressible homogeneous flows in the turbulent -regime. Journal of Fluid Mechanics, 181:441–466. -[3] Gicquel, L. Y., Gourdain, N., Boussuge, J.-F., Deniau, H., Staffelbach, G., Wolf, P., and Poinsot, T. (2011). -High performance parallel computing of flows in complex geometries. Comptes Rendus M´ecanique, 339(2- -3):104–124. -[4] Colin, O. and Rudgyard, M. (2000). Development of High-Order Taylor–Galerkin Schemes for LES. Journal -of Computational Physics, 162(2):338–371. -[5] Poinsot, T. and Lelef, S. (1992). Boundary conditions for direct simulations of compressible viscous flows. -Journal of Computational Physics, 101(1):104–129. -[6] Saxena, P. and Williams, F. A. (2006). Testing a small detailed chemical-kinetic mechanism for the -combustion of hydrogen and carbon monoxide. Combustion and Flame, 145(1-2):316–323. -[7] Coulon, V., Gaucherand, J., Xing, V., Laera, D., Lapeyre, C., and Poinsot, T. (2023). Direct numerical -simulations of methane, ammonia-hydrogen and hydrogen turbulent premixed flames. Combustion and Flame, -256:112933. -[8] Biscione, V. and Bowers, J. S. (2021). Convolutional neural networks are not invariant to translation, but -they can learn to be. Journal of Machine Learning Research, 22(229):1–28. - - - - diff --git a/_datasets/roshan2024.md b/_datasets/roshan2024.md deleted file mode 100644 index ec7e2ca..0000000 --- a/_datasets/roshan2024.md +++ /dev/null @@ -1,180 +0,0 @@ ---- -layout: datapage -excerpt: (5 cases) -title: Rayleigh-Bénard Convection -description: Rayleigh-Bénard Convection DNS -header: - teaser: /assets/img/ico_roshan2024.png - image: /assets/img/roshan2024.png -categories: -- nonreacting -- channel -- pipe -- turbulent -- numerical ---- - - - -## Description -Rayleigh Benard Convection (RBC) is a benchmark fluid-dynamics problem for simulating natural thermal -convection. It consists of a thin layer of fluid confined between a pair of parallel horizontal plates. The top plate is -cooler than the bottom plate, and when this temperature difference is sufficiently high, a convective flow arises.This phenomenon can be simulated numerically by solving the incompressible Navier-Stokes equations under the -Boussinesq approximation: - -$$ -\frac{\partial \mathbf{u}^*}{\partial t^*} + \mathbf{u}^* \cdot \nabla \mathbf{u}^* = -\frac{1}{\rho_0} \nabla p^* + \nu \nabla^2 \mathbf{u}^* + \alpha g T^* \hat{\mathbf{z}} -$$ - -$$\frac{\partial T^*}{\partial t^*} + \mathbf{u}^* \cdot \nabla T^* = \kappa \nabla^2 T^* $$ - -$$\nabla \cdot \mathbf{u}^* = 0$$ - -Here, $$\mathbf{u}^*$$, $$p^*$$ and $$T^*$$ are the velocity, pressure and temperature fields respectively. These quantities are in the dimensional form (including time, $$t^*$$). The length scales are non-dimensionalized with respect to the height of the domain, $$𝐻$$. Similarly, the temperature field is non-dimensionalized by the temperature difference between the bottom and top plates, $$\Delta = 𝑇_𝑏 − 𝑇_𝑡$$. This gives the free-fall velocity, $$𝑈_𝑓 = \sqrt{\alpha g \Delta 𝐻}$$, which is used to non- -dimensionalize the velocity field. The non-dimensional variables can therefore be written as: - -$$\mathbf{u} = \frac{\mathbf{u}^*}{U_f} \quad ,\quad T = \frac{T^*}{\Delta} \quad ,\quad t = \frac{U_f t^*}{H} \quad ,\quad p = \frac{p^*-p_0}{\rho _0 U_f^2}$$ - -where $$p_0$$ and $$\rho _0$$ are the reference pressure and density respectively. Since the DNS is performed with non-dimensional variables, the values of 𝑝0 and 𝜌0 are not set explicitly in the code. If necessary, they can be assumed to be 101.3 kPa and 1.2 kg/m3 respectively, as prescribed by the International Standard Atmosphere (ISA) at sea- -level. Finally, we obtain the following non-dimensional equations for velocity and temperature which are solved in the DNS of RBC: - -$$\frac{\partial \mathbf{u}}{\partial t} + \mathbf{u} \cdot \nabla \mathbf{u} = -\nabla p + \sqrt{Ra / Pr} \nabla^2 \mathbf{u} + T \hat{\mathbf{z}}$$ - -$$\frac{\partial T}{\partial t} + \mathbf{u} \cdot \nabla T= \frac{1}{\sqrt{Ra Pr}} \nabla^2 T $$ - -$$\nabla \cdot \mathbf{u} = 0$$ - -The non-dimensional parameter, Rayleigh number ($$Ra$$), quantifies the degree of forcing imparted by buoyancy, -whereas the Prandtl number ($$Pr$$) is the dimensionless ratio between the viscous and thermal diffusivities of the fluid: - -$$Ra = \frac{\alpha g \Delta H^3}{\nu \kappa} \quad,\quad Pr = \frac{\nu}{\kappa}$$ - -The present dataset is generated from DNS of RBC within a periodically extended Cartesian -box of aspect ratio $$\Gamma = L/H =4$$, where L is the length of the box. All the simulations are performed with these fixed dimensions of 4 × 4 × 1. The DNS are performed using the GPU accelerated spectral element solver, NekRS [1], at a fixed $$Pr = 0.7$$ and at $$10^5 \leq Ra \leq 10^9$$. -Although the original simulations were performed on grids of increasingly finer resolutions [2], all fields have been interpolated to a uniform grid of size 2049 × 2049 × 1025 with a grid-spacing of 2h × 2h × h, where h is the grid spacing along the vertical 𝑧-axis. This -axis has a higher resolution to resolve the boundary layers properly. The interpolation was performed using spectral -element routines of NekRS itself to ensure maximum accuracy. There are 20 snapshots for each case. - -## Quick Info -* Contributors: Roshan Samuel, Mathis Bode -* Nx = 2049, Ny = 2049, Nz = 1025, Nɸ = 5 - -* DOI -* .bib - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IDConditionsSize (TB)Links
0 Ra = 1051.44 - Kaggle0, info.json0
- Kaggle1, info.json1
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1 Ra = 1061.44 - Kaggle0, info.json0
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2 Ra = 1071.44 - Kaggle0, info.json0
- Kaggle1, info.json1
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3 Ra = 1081.44 - Kaggle0, info.json0
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4 Ra = 1091.44 - Kaggle0, info.json0
- Kaggle1, info.json1
- Kaggle2, info.json2
- Kaggle3, info.json3
- Kaggle4, info.json4
- Kaggle5, info.json5
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- Kaggle7, info.json7
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-
- -## References -[1]. P. F. Fischer, S. Kerkemeier, M. Min, Y.-H. Lan, M. Phillips, T. Rathnayake, E. Merzari, A. Tomboulides, A. Karakus, N. Chalmers, and T. Warburton. a GPU-accelerated spectral element Navier–Stokes solver. Parallel Computing 114, 102982 (2022). -[2]. R. J. Samuel, M. Bode, J. D. Scheel, K. R. Sreenivasan and J. Schumacher. No sustained mean velocity in the boundary region of plane thermal convection. Journal of Fluid Mechanics 996, A49 (2024). - - - diff --git a/_datasets/savard.md b/_datasets/savard.md deleted file mode 100644 index dd5f881..0000000 --- a/_datasets/savard.md +++ /dev/null @@ -1,181 +0,0 @@ ---- -layout: datapage -title: Freely-Propagating Flame -excerpt: (22 cases) -header: - teaser: /assets/img/ico_savard2019.png -description: Vitiated H2-air Freely Propagating Flame DNS -categories: -- reacting -- turbulent -- numerical ---- - -
- Image 1 -
- -## Description - -This DNS configuration presents a statistically-planar, freely-propagating flame. BLASTNet contains 22 parametric variations of this configuration that differ by three essential parameters involving turbulence: (i) turbulence intensity, characterized by the RMS velocity u′, (ii) inflow velocity, Uin , and (iii) integral length scale, lI. These configurations represent a series of hydrogen-premixed turbulent flames in autoignitive reheat combustion conditions that provide rich information on regimes of turbulent spontaneous ignition and turbulent deflagration. - -The turbulent flames are initialized with an ignition front. For the initial flat spontaneous ignition front, the thermo-chemical conditions are chosen to be representative of those at the end of the first stage of a heavy-duty gas turbine sequential combustor, but at a lower pressure of 1 atm for all configurations. The mixture of fuel and products of first stage hydrogen-air combustion at an equivalence ratio of 0.43 and initial temperature of 773 K is used at the inlet of the domain. This mixture is equivalent to an equivalence ratio of 0.35 and Tu = 990 K, and its ignition delay time (τign,0) and laminar flame speed (SL) are identified to be 0.55 ms and 14.7 ms−1, respectively. The reference laminar flame thickness, lf , is evaluated to be 0.66 mm. After initialization, the ignition front is superimposed on a turbulent flow-field using a one-to-one correspondence in x-space (Figure 14). Depending on varying Uin and u′, the flame may stabilize at a position far away from the inlet (a turbulent spontaneous ignition front) or the introduction of turbulence may trigger the transition to a deflagration, where the flame front propagates towards the inlet. - -The width of the domain in the y- and z-directions is Ly = Lz = 5.26lI, and the length in the streamwise direction is Lx, which is different for individual configuration. For all configurations, the simulations are run until a statistically steady state is achieved. -The low Mach number form of the governing equations is solved using the energy conservative, finite difference code NGA and high turbulence simulations are enabled by the linear velocity forcing method. NGA is second-order accurate in both space and time, and it uses a semi-implicit Crank-Nicolson time integration scheme. A third-order bounded QUICK scheme, BQUICK, is used for scalar transport. Ideal gas law is used as the EoS for a mixture of perfect gases. A detailed chemical mechanism for hydrogen combustion with 9 species and 21 reactions is used for all configurations. - - -## Quick Info -* DOI -* .bib -* Contributor: Bruno Savard - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Kau= 2.4, Uin/SL = 2.4570 - Kaggle
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Kau= 6.8, Uin/SL = 2.4532Kaggle
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Kau= 13, Uin/SL = 2.4535Kaggle
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Kau= 2.4, Uin/SL = 3.6765Kaggle
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Kau= 6.8, Uin/SL = 3.6746Kaggle
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Kau= 13, Uin/SL = 3.6765Kaggle
- info.json
Kau= 19, Uin/SL = 3.6759Kaggle
- info.json
Kau= 36, Uin/SL = 3.67111Kaggle
- info.json
Kau= 2.4, Uin/SL = 4.6339Kaggle
- info.json
Kau= 6.8, Uin/SL = 4.6391Kaggle
- info.json
Kau= 13, Uin/SL = 4.63118Kaggle
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Kau= 2.4, Uin/SL = 5.5135Kaggle
- info.json
Kau= 6.8, Uin/SL = 5.51118Kaggle
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Kau= 19, Uin/SL = 5.51118Kaggle
- info.json
Kau= 1.7, Uin/SL = 3.67111Kaggle
- info.json
Kau= 4.8, Uin/SL = 3.67118Kaggle
- info.json
Kau= 8.9, Uin/SL = 3.6780Kaggle
- info.json
Kau= 1.7, Uin/SL = 4.63118Kaggle
- info.json
Kau= 4.8, Uin/SL = 4.63118Kaggle
- info.json
Kau= 8.9, Uin/SL = 4.63110Kaggle
- info.json
Kau= 1.7, Uin/SL = 5.51110Kaggle
- info.json
Kau= 8.9, Uin/SL = 5.51110Kaggle
- info.json
- - - - diff --git a/_datasets/shantanu.md b/_datasets/shantanu.md deleted file mode 100644 index 05ce944..0000000 --- a/_datasets/shantanu.md +++ /dev/null @@ -1,223 +0,0 @@ ---- -layout: datapage -excerpt: (1 case) -title: Canonical Decaying HIT -description: Decaying homogeneous isotropic turbulence DNS -header: - teaser: /assets/img/ico_shantanu2022.png -categories: -- numerical -- nonreacting -- hit -- turbulent ---- - -
- Image 1 -
- -## Description -A DNS decaying homogeneous isotropic turbulence simulation is developed by Wang et al. and runs on Tensor Processing Unit (TPU) platform. The Computational Fluid Dynamics (CFD) framework is employed to solve the variable-density Navier-Stokes equation under a low-Mach approximation. The governing equations are discretized using a finite-difference method on a collocated structured mesh within a cubic computational domain with a side length of 10.24 m. The discretization involves a total of N = 2048 grid points in each direction, resulting in a homogeneous grid spacing of Δ = 5 × 10 -3 m. The simulation is initialized with specific turbulence parameters, including an initial Reynolds number Re λ = 309, initial turbulent kinetic energy k0 = 24.42 m2/s2, and initial ratios of Taylor length scale λ0/L = 7.49 × 10-3 and integral length scale l0/L = 2.84 × 10-1. Here, λ and l represent the Taylor length scale and integral length scale, respectively. These initial condition set the stage for investigating the temporal evolution and decay characteristics of homogeneous isotropic turbulence within the computational domain. - -## Quick Info -* Contributors: Qing Wang, Shantanu Shahane, Yifan Chen -* Nx = 2040, Ny = 2040, Nz = 2048, Nɸ = 4 -* DOI -* .bib - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IDConditionsSize (GB)Links
0 TKE = 25.8844, ε = 65.7053120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
1 TKE = 21.2626, ε = 39.3486120 - KaggleV, KaggleP
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2 TKE = 17.1823, ε = 37.9396120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
3 TKE = 13.7007, ε = 30.2196120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
4 TKE = 9.3180, ε = 16.4062120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
5 TKE = 5.8251, ε = 7.4214120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
6 TKE = 3.4790, ε = 3.2468120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
7 TKE = 1.9369, ε = 1.2832120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
8 TKE = 1.0627, ε = 0.5080120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
9 TKE = 0.6658, ε = 0.2389120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
10 TKE = 0.4521, ε = 0.1295120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
11 TKE = 0.3339, ε = 0.0789120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
12 TKE = 0.2596 ε = 0.0518120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
13 TKE = 0.2119, ε = 0.0375120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
14 TKE = 0.1765, ε = 0.0283120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
15 TKE = 0.1488, ε = 0.0215120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
16 TKE = 0.1268, ε = 0.0167120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
17 TKE = 0.1090, ε = 0.0131120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
18 TKE = 0.0953, ε = 0.0107120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
19 TKE = 0.0843, ε = 0.0089120 - KaggleV, KaggleP
- info.jsonV, info.jsonP -
- - - - diff --git a/_datasets/sharma2024.md b/_datasets/sharma2024.md deleted file mode 100644 index 556d9d3..0000000 --- a/_datasets/sharma2024.md +++ /dev/null @@ -1,117 +0,0 @@ ---- -layout: datapage -excerpt: (10 cases) -title: Lifted hydrogen jet flame -description: Circular Burner Diluted Partially-Premixed H2-air Lifted Flame in 2D configuration -header: - teaser: /assets/img/ico_sharma2024.png -categories: -- reacting -- jet -- laminar -- numerical ---- - -
- Image 1 -
- -## Description - -This configuration involves 8 parametric variations of lifted hydrogen jet flame in heated co-flow air. The central circular jet with D = 1.92mm consists of a mixture of 65% of hydrogen and 35% of nitrogen by volume with an inlet temperature of 400K. The jet is surrounded by a co-flow of heated air at 1100K and 1 bar pressure. -The jet Reynolds number is varied between 5000 to 11000. The computational domain size is 12.5D x 15.6D. A detailed hydrogen-air chemical mechanism composed of 9 species and 21 elementary reactions is employed in this study. -A uniform grid size of 15 μm is placed in both axial and spanwise direction, resulting in a grid size of 1600 x 2000. Two additional inert mixing cases are also added corresponding to jet Reynolds number of 5000 and 10000. - -A compressible unstructured finite-volume solver is used to numerically solve the conservation laws for mass, momentum, total energy, and chemical species. -The convective fluxes are discretized using a sensor-based hybrid scheme, where a high-order, non-dissipative scheme is combined with a low-order scheme to describe interfaces and flow field discontinuities. -A central scheme, which is 4th-order accurate on uniform meshes, is used along with a 2nd-order accurate ENO scheme. -We apply a second-order accurate simpler balanced-splitting scheme to separate the convection, diffusion, and reaction operators. -The stiff chemical source terms are integrated in time using a semi-implicit fourth-order accurate Rosenbrock-Krylov scheme. -For all other non-stiff operators, we utilize a strong stability preserving third-order Runge-Kutta (SSP-RK3) scheme. - -## Quick Info -* DOI -* .bib -* ML model source code -* Contributor: Pushan Sharma, Wai Tong Chung and Matthias Ihme - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Reynolds numberLinks
Rejet= 5000 - Kaggle
- info.json -
Rejet= 6000 - Kaggle
- info.json -
Rejet= 7000 - Kaggle
- info.json -
Rejet= 7500 - Kaggle
- info.json -
Rejet= 8000 - Kaggle
- info.json -
Rejet= 9000 - Kaggle
- info.json -
Rejet= 10000 - Kaggle
- info.json -
Rejet= 11000 - Kaggle
- info.json -
Rejet= 5000 (inert mixing) - Kaggle
- info.json -
Rejet= 10000 (inert mixing) - Kaggle
- info.json -
- diff --git a/_datasets/wang2024.md b/_datasets/wang2024.md deleted file mode 100644 index 4c8eeb2..0000000 --- a/_datasets/wang2024.md +++ /dev/null @@ -1,156 +0,0 @@ ---- -layout: datapage -excerpt: (117 cases) -title: FireBench data above ground level -description: LES of an ensemble of wildfire spread -header: - image: /assets/img/wang2024.png - teaser: /assets/img/ico_wang2024.png -categories: -- reacting -- environmental -- turbulent -- numerical -- benchmark ---- - - - -## Description -The propagation of wildfires is a complex, dynamic process that is influenced by various factors, such as fuel, wind, terrain, and other environmental conditions. Accurately and reliably predicting the rate-of-spread of wildfires is of critical importance for fire management, rapid fire response, and fire mitigation. The [Google FireBench dataset](https://sites.research.google/gr/wildfires/firebench/) [1] aims to provide high-fidelity data to tackle these issues by providing an ensemble of large-eddy simulations that capture the three-dimensional wildfire-spread behavior and coupling with the atmospheric environment. - -The spatial and temporal evolution of the combustion of solid fuel coupled with the -atmospheric flow is described by a two-phase model [2]. The gas-phase is described by -the Favre-filtered conservation equations for mass, momentum, oxygen-fraction, and potential temperature [3]: -{::nomarkdown} -$$ -\partial_t \overline{\rho} + \nabla \cdot (\overline{\rho} \widetilde{\boldsymbol{u}}) = S_\rho, -$$ -$$ -\partial_t (\overline{\rho} \widetilde{\boldsymbol{u}} ) + \nabla \cdot (\overline{\rho} \widetilde{\boldsymbol{u}} \otimes \widetilde{\boldsymbol{u}}) = - \nabla \overline{p_d} + \nabla \cdot \overline{\tau} + [\overline{\rho} - \rho(z)] g \boldsymbol{\hat{k}_z} + \boldsymbol{f}_D + \boldsymbol{f}_C, -$$ -$$ -\partial_t (\overline{\rho} \widetilde{Y_O}) + \nabla \cdot (\overline{\rho} \widetilde{\boldsymbol{u}} \widetilde{Y_O}) = \nabla \cdot \overline{\boldsymbol{j}_O} + \overline{\rho} \widetilde{\dot{\omega}_O}, -$$ -$$ -\partial_t (\overline{\rho} \widetilde{\theta}) + \nabla \cdot (\overline{\rho} \widetilde{\boldsymbol{u}} \widetilde{\theta}) = \nabla \cdot \overline{\boldsymbol{q}} + \frac{\overline{\rho} \widetilde{\theta}}{c_p \widetilde{T}} [h a_v (T_s - \widetilde{T}) + \dot{q}_r + (1-\Theta) H_f \widetilde{\dot{\omega}}], -$$ -where $\widetilde{\cdot}$ denotes Favre-filtering and $\overline{\cdot}$ denotes Reynolds filtering. $\rho$ is the density, $\boldsymbol{u}$ is the velocity vector, $p_d$ is the hydrodynamic pressure, $\tau$ is the shear stress tensor, $g$ is the gravitational acceleration, $\boldsymbol{\hat{k}_z}$ is the unit vector along the gravitational direction, $f_D = - \overline{\rho} c_d a_v \boldsymbol{|\widetilde{u}| \widetilde{u}}$ is the drag force due to surface vegetation, $\boldsymbol{f}_C = f \boldsymbol{\hat{k}_z} \times \overline{\rho} (\widetilde{\boldsymbol{u}} - \boldsymbol{U}_\infty)$ is the Coriolis force, $Y_O$, $\boldsymbol{j}_O$, and $\dot{\omega}_O$ are the mass fraction, species diffusion, and source term of the oxidizer, $\theta$ is the potential temperature, $\boldsymbol{q}$ is the heat flux vector, $T$ is the gas-phase temperature, and $H_f$ is the heat of combustion. -The heat exchange between the solid and gas phase is modeled with $h$ as the convective heat transfer coefficient, $a_v$ as the bulk fuel area-to-volume ratio, and $\dot{q}_r$ is the radiation source term. $\Theta = 1 - \rho_f/\rho_{f,0}$ is the fraction of the heat release that contributes to the increase of the solid phase temperature. -$\dot{\omega}$ is the gas-phase combustion source term. -{:/} - -The dataset consists of 117 cases with 9 velocities and 13 slopes with data extracted 1.5 m and 10 m above ground level. In addition, data was extracted at a streamwise location of 100 m < x < 1000 m. -Specifically, the cases span a range of mean inlet velocity at 10 m above ground level of 2 to 10 m/s with a step of 1 m/s, and a range of slopes from 0 to 30 degrees with steps of 2.5 degrees. - -## Quick Info -* Contributors: Qing Wang, Matthias Ihme, Cenk Gazen, Yi-Fan Chen, John Anderson, Jen Zen Ho, Bassem Akoush -* Nx = 900, Ny = 252 -* DOI -* .bib - -## Links to different cases - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IDConditionsSize (GB)Links
0 u10 = 2 m/s68 - Kaggle
-
1 u10 = 3 m/s42 - Kaggle
-
2 u10 = 4 m/s42 - Kaggle
-
3 u10 = 5 m/s42 - Kaggle
-
4 u10 = 6 m/s42 - Kaggle
-
5 u10 = 7 m/s42 - Kaggle
-
6 u10 = 8 m/s60 - Kaggle
-
7 u10 = 9 m/s42 - Kaggle
-
8 u10 = 10 m/s51 - Kaggle
-
- -## References -[1]. Q. Wang, M. Ihme, C. Gazen, Y. F. Chen, J. Anderson. A high-fidelity ensemble simulation framework for interrogating wildland-fire behaviour and benchmarking machine learning models. International journal of wildland fire (2024). - -[2]. R. R. Linn. A transport model for prediction of wildfire behavior (No. LA-13334-T). PhD thesis. Los Alamos National Lab., NM, United States (1997). - -[3]. Q. Wang, M. Ihme, R. R. Linn, Y. F. Chen, V. Yang, F. Sha, C. Clements, J. S. McDanold, J. Anderson. A high-resolution large-eddy simulation framework for wildland fire predictions using TensorFlow. International journal of wildland fire (2023). From 39eea466c995b974a2102cf3b87c3fcf7ee47ccd Mon Sep 17 00:00:00 2001 From: jenzenho <46580415+jenzenho@users.noreply.github.com> Date: Wed, 24 Sep 2025 13:39:20 -0700 Subject: [PATCH 2/2] Renamed the dataset URLs to be more descriptive. --- _datasets/blastnet_momentum.md | 34 +++ _datasets/ch4air_forced_hit_flame.md | 33 +++ _datasets/compressible_inert_ch4o2_hit.md | 28 +++ _datasets/decaying_hit.md | 223 ++++++++++++++++++ ...d_partially_premixed_h2air_lifted_flame.md | 117 +++++++++ ...tially_premixed_h2air_lifted_slot_flame.md | 32 +++ _datasets/firebench_wildfire_les.md | 156 ++++++++++++ _datasets/forced_hit_passive_scalars.md | 121 ++++++++++ _datasets/h2ch4_turbulent_jet_flows.md | 95 ++++++++ _datasets/nh3h2air_premixed_slot_flame.md | 29 +++ _datasets/nonreacting_channel_flow.md | 33 +++ _datasets/nonreacting_channel_flow_2.md | 212 +++++++++++++++++ _datasets/passive_scalar_hit.md | 91 +++++++ .../premixed_flame_wall_interaction_ch4air.md | 36 +++ _datasets/premixed_slot_flame_h2air.md | 148 ++++++++++++ _datasets/rayleigh_benard_convection.md | 180 ++++++++++++++ .../turbulent_round_jet_premixed_ch4air.md | 43 ++++ _datasets/vitiated_h2air_flame.md | 181 ++++++++++++++ 18 files changed, 1792 insertions(+) create mode 100644 _datasets/blastnet_momentum.md create mode 100644 _datasets/ch4air_forced_hit_flame.md create mode 100644 _datasets/compressible_inert_ch4o2_hit.md create mode 100644 _datasets/decaying_hit.md create mode 100644 _datasets/diluted_partially_premixed_h2air_lifted_flame.md create mode 100644 _datasets/diluted_partially_premixed_h2air_lifted_slot_flame.md create mode 100644 _datasets/firebench_wildfire_les.md create mode 100644 _datasets/forced_hit_passive_scalars.md create mode 100644 _datasets/h2ch4_turbulent_jet_flows.md create mode 100644 _datasets/nh3h2air_premixed_slot_flame.md create mode 100644 _datasets/nonreacting_channel_flow.md create mode 100644 _datasets/nonreacting_channel_flow_2.md create mode 100644 _datasets/passive_scalar_hit.md create mode 100644 _datasets/premixed_flame_wall_interaction_ch4air.md create mode 100644 _datasets/premixed_slot_flame_h2air.md create mode 100644 _datasets/rayleigh_benard_convection.md create mode 100644 _datasets/turbulent_round_jet_premixed_ch4air.md create mode 100644 _datasets/vitiated_h2air_flame.md diff --git a/_datasets/blastnet_momentum.md b/_datasets/blastnet_momentum.md new file mode 100644 index 0000000..23a2b3b --- /dev/null +++ b/_datasets/blastnet_momentum.md @@ -0,0 +1,34 @@ +--- +layout: datapage +title: BLASTNet Momentum128 3D SR Dataset +excerpt: +header: + teaser: /assets/img/ico_chung2022.png +description: Collection of BLASTNet Simulations +categories: +- numerical +- nonreacting +- turbulent +- hit +- pipe +- channel +- jet +- benchmark +--- + +![image](./assets/img/diversity.png) + +## Description +The BLASTNet Momentum128 3D SR Dataset is a benchmark dataset for developing and evaluating 3D super-resolution (SR) methods on turbulent flow data. It is a curated subset of the larger BLASTNet datasets, specifically designed to facilitate high-fidelity reconstruction of velocity fields from low-fidelity fields. This dataset includes 2,000 volumetric samples of 128$$^3$$ grid points, each containing the three components of the velocity field (u, v, w) and the density. The sub-volumes were extracted from high-resolution direct numerical simulations (DNS) which span a range of flow regimes and statistical variations. + +Each sample is accompanied by pre-computed low-resolution inputs at multiple downsampling ratios (e.g., 8×, 16×, and 32×), enabling the evaluation of SR models under different reconstruction challenges. Data is provided in binary .dat format using single-precision floating point (little-endian) ordering. The dataset is split into training, validation, and test sets, with metadata stored in accompanying CSV. These include physical statistics summary (e.g., skewness, kurtosis, variance). + + +## Quick Info +* Kaggle Link
+* Contributors: Wai Tong Chung, Bassem Akoush, Matthias Ihme +* Nx = 128, Ny = 128, Nz = 128, Nɸ = 4 +* Size = 75.15 GB +* DOI
+* .bib
+ diff --git a/_datasets/ch4air_forced_hit_flame.md b/_datasets/ch4air_forced_hit_flame.md new file mode 100644 index 0000000..83f691e --- /dev/null +++ b/_datasets/ch4air_forced_hit_flame.md @@ -0,0 +1,33 @@ +--- +layout: datapage +title: Reacting Forced HIT +excerpt: (1 case) +description: CH4-Air Flame Interaction With Forced HIT DNS +header: + teaser: /assets/img/ico_poludnenko.png +categories: +- reacting +- hit +- turbulent +- numerical +--- + +![image](./assets/img/poludnenko.png) + +## Description + +TThe DNS study involves a statistically steady, isotropic, and homogeneous turbulent flow in an unconfined space. The flame is initialized by a planar surface separating half of the domain containing methane/air mixture at 700 K and 3.04 × 107 erg cm−3 pressure, and another half with hot products, and is immersed in a high-intensity turbulent flow field with Kolmogorov type spectrum. The idea is to investigate the process of flame interaction with steady homogeneous isotropic turbulence. However, the flow needs to be constantly stirred at the largest scale to ensure a steady energy cascade to smaller scales so that the turbulence-flame interaction at the quasi-steady state can be studied. A spectral turbulence- driving method is used in the study, the details of which are available in Poludnenko and Oran. This driving method produces statistically steady forced-HIT flows with arbitrarily complex energy spectra. In particular, it is possible to achieve Kolmogorov type turbulence with inertial range of energy cascade extending up to energy injection scale. The other advantage of this method is that it does not introduce any artificial large-scale anisotropy, compression, or rarefaction. Prior to ignition, all domain boundaries are periodic. At ignition, boundary conditions along the left and right z-boundaries (as shown in Figure 9) are switched to zero-order extrapolation to prevent any non-physical pressure build-up in the domain and the formation of artificial large-scale rarefaction waves at the boundaries. + +The computational domain aspect ratio is 1 × 1 × 16, with a grid size of 257 × 257 × 4097, including 16 grid points per unit laminar flame thermal thickness. The cell size is 2.62 × 10−4 cm. The turbulent velocity at energy injection scale (L = 0.067 cm) length scale is 213.92 cms−1 with turbulent root-mean-squared (RMS) velocity of 245.83 cms−1, resulting in an eddy turnover time of 3.14×10−4 s. The same velocity quantities corresponding to the integral length scale (l = 0.0196 cm) are 141.93 cms−1 and 132.2 cms−1. The ignition delay time of the mixture is three times the eddy turn-over time, and the total simulation runtime is 16 times the eddy turn-over time. The Damköhler and Karlovitz numbers are 0.66 and 9.97, respectively. + +The DNS calculation is performed using the code Athena-RFX, which implements higher-order fully conservative Godunov-type methods for integration of fluid equations. The numerics in this work are third-order accurate in space and second-order accurate in time. More details are available in the original paper. The foundational fuel chemistry model (FFCM-1) with 22 species and 107 reactions is used as the chemical mechanism. + + +## Quick Info +* Kaggle Link +* Contributors: Alexei Y. Poludnenko +* Nx = 257, Ny = 257, Nz = 4097, Nɸ = 6 + 21 +* Size = 30 GB +* DOI
+* .bib
+* info.json diff --git a/_datasets/compressible_inert_ch4o2_hit.md b/_datasets/compressible_inert_ch4o2_hit.md new file mode 100644 index 0000000..0fe3d52 --- /dev/null +++ b/_datasets/compressible_inert_ch4o2_hit.md @@ -0,0 +1,28 @@ +--- +layout: datapage +title: Non-reacting HIT +excerpt: (1 case) +header: + teaser: /assets/img/ico_chung2022.png +description: Compressible Inert CH4-O2 Homogeneous Isotropic Turbulence DNS +categories: +- nonreacting +- numerical +- turbulent +- hit +--- + +![image](./assets/img/chung2022.png) + +## Description + +The HIT DNS simulation is performed on a 3D cubic domain of length L, where a spherical gaseous-oxygen core of radius r = 0.25L at 300 K is initialized in gaseous methane environment of 300 K at 1 atm pressure, providing an idealized representation of an inert gaseous fuel-air mixture in a rocket engine. Periodic boundary conditions are used at all boundaries. A synthetic turbulence generator by Saad et al. based on von Kármán-Pao energy spectrum with zero mean velocity is used to generate the initial velocity profile. Ideal gas law is used as the equation of state (EoS) to relate pressure, temperature and density. The simulation is performed in an unstructured compressible finite-volume solver [64]. The solver uses a fourth-order accurate central spatial finite difference scheme. For the time integration, a stable third-order Runge-Kutta scheme is employed. Mixture-averaged transport properties are used in the DNS. + +## Quick Info +* Kaggle Link
+* Contributors: Wai Tong Chung, Matthias Ihme +* Nx = 129, Ny = 129, Nz = 129, Nɸ = 6 + 2 +* Size = 6 GB +* DOI
+* .bib
+* info.json diff --git a/_datasets/decaying_hit.md b/_datasets/decaying_hit.md new file mode 100644 index 0000000..05ce944 --- /dev/null +++ b/_datasets/decaying_hit.md @@ -0,0 +1,223 @@ +--- +layout: datapage +excerpt: (1 case) +title: Canonical Decaying HIT +description: Decaying homogeneous isotropic turbulence DNS +header: + teaser: /assets/img/ico_shantanu2022.png +categories: +- numerical +- nonreacting +- hit +- turbulent +--- + +
+ Image 1 +
+ +## Description +A DNS decaying homogeneous isotropic turbulence simulation is developed by Wang et al. and runs on Tensor Processing Unit (TPU) platform. The Computational Fluid Dynamics (CFD) framework is employed to solve the variable-density Navier-Stokes equation under a low-Mach approximation. The governing equations are discretized using a finite-difference method on a collocated structured mesh within a cubic computational domain with a side length of 10.24 m. The discretization involves a total of N = 2048 grid points in each direction, resulting in a homogeneous grid spacing of Δ = 5 × 10 -3 m. The simulation is initialized with specific turbulence parameters, including an initial Reynolds number Re λ = 309, initial turbulent kinetic energy k0 = 24.42 m2/s2, and initial ratios of Taylor length scale λ0/L = 7.49 × 10-3 and integral length scale l0/L = 2.84 × 10-1. Here, λ and l represent the Taylor length scale and integral length scale, respectively. These initial condition set the stage for investigating the temporal evolution and decay characteristics of homogeneous isotropic turbulence within the computational domain. + +## Quick Info +* Contributors: Qing Wang, Shantanu Shahane, Yifan Chen +* Nx = 2040, Ny = 2040, Nz = 2048, Nɸ = 4 +* DOI +* .bib + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
IDConditionsSize (GB)Links
0 TKE = 25.8844, ε = 65.7053120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
1 TKE = 21.2626, ε = 39.3486120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
2 TKE = 17.1823, ε = 37.9396120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
3 TKE = 13.7007, ε = 30.2196120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
4 TKE = 9.3180, ε = 16.4062120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
5 TKE = 5.8251, ε = 7.4214120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
6 TKE = 3.4790, ε = 3.2468120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
7 TKE = 1.9369, ε = 1.2832120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
8 TKE = 1.0627, ε = 0.5080120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
9 TKE = 0.6658, ε = 0.2389120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
10 TKE = 0.4521, ε = 0.1295120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
11 TKE = 0.3339, ε = 0.0789120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
12 TKE = 0.2596 ε = 0.0518120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
13 TKE = 0.2119, ε = 0.0375120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
14 TKE = 0.1765, ε = 0.0283120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
15 TKE = 0.1488, ε = 0.0215120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
16 TKE = 0.1268, ε = 0.0167120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
17 TKE = 0.1090, ε = 0.0131120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
18 TKE = 0.0953, ε = 0.0107120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
19 TKE = 0.0843, ε = 0.0089120 + KaggleV, KaggleP
+ info.jsonV, info.jsonP +
+ + + + diff --git a/_datasets/diluted_partially_premixed_h2air_lifted_flame.md b/_datasets/diluted_partially_premixed_h2air_lifted_flame.md new file mode 100644 index 0000000..556d9d3 --- /dev/null +++ b/_datasets/diluted_partially_premixed_h2air_lifted_flame.md @@ -0,0 +1,117 @@ +--- +layout: datapage +excerpt: (10 cases) +title: Lifted hydrogen jet flame +description: Circular Burner Diluted Partially-Premixed H2-air Lifted Flame in 2D configuration +header: + teaser: /assets/img/ico_sharma2024.png +categories: +- reacting +- jet +- laminar +- numerical +--- + +
+ Image 1 +
+ +## Description + +This configuration involves 8 parametric variations of lifted hydrogen jet flame in heated co-flow air. The central circular jet with D = 1.92mm consists of a mixture of 65% of hydrogen and 35% of nitrogen by volume with an inlet temperature of 400K. The jet is surrounded by a co-flow of heated air at 1100K and 1 bar pressure. +The jet Reynolds number is varied between 5000 to 11000. The computational domain size is 12.5D x 15.6D. A detailed hydrogen-air chemical mechanism composed of 9 species and 21 elementary reactions is employed in this study. +A uniform grid size of 15 μm is placed in both axial and spanwise direction, resulting in a grid size of 1600 x 2000. Two additional inert mixing cases are also added corresponding to jet Reynolds number of 5000 and 10000. + +A compressible unstructured finite-volume solver is used to numerically solve the conservation laws for mass, momentum, total energy, and chemical species. +The convective fluxes are discretized using a sensor-based hybrid scheme, where a high-order, non-dissipative scheme is combined with a low-order scheme to describe interfaces and flow field discontinuities. +A central scheme, which is 4th-order accurate on uniform meshes, is used along with a 2nd-order accurate ENO scheme. +We apply a second-order accurate simpler balanced-splitting scheme to separate the convection, diffusion, and reaction operators. +The stiff chemical source terms are integrated in time using a semi-implicit fourth-order accurate Rosenbrock-Krylov scheme. +For all other non-stiff operators, we utilize a strong stability preserving third-order Runge-Kutta (SSP-RK3) scheme. + +## Quick Info +* DOI +* .bib +* ML model source code +* Contributor: Pushan Sharma, Wai Tong Chung and Matthias Ihme + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Reynolds numberLinks
Rejet= 5000 + Kaggle
+ info.json +
Rejet= 6000 + Kaggle
+ info.json +
Rejet= 7000 + Kaggle
+ info.json +
Rejet= 7500 + Kaggle
+ info.json +
Rejet= 8000 + Kaggle
+ info.json +
Rejet= 9000 + Kaggle
+ info.json +
Rejet= 10000 + Kaggle
+ info.json +
Rejet= 11000 + Kaggle
+ info.json +
Rejet= 5000 (inert mixing) + Kaggle
+ info.json +
Rejet= 10000 (inert mixing) + Kaggle
+ info.json +
+ diff --git a/_datasets/diluted_partially_premixed_h2air_lifted_slot_flame.md b/_datasets/diluted_partially_premixed_h2air_lifted_slot_flame.md new file mode 100644 index 0000000..8372ce7 --- /dev/null +++ b/_datasets/diluted_partially_premixed_h2air_lifted_slot_flame.md @@ -0,0 +1,32 @@ +--- +layout: datapage +title: Slot Burner +excerpt: (1 case) +header: + teaser: /assets/img/ico_jung2021.png +description: Slot Burner Diluted Partially-Premixed H2-air Lifted Flame DNS +categories: +- numerical +- reacting +- jet +- turbulent +--- + +
+ Image 1 +
+ +## Description + +This DNS configuration involves a turbulent lifted hydrogen jet flame in heated co-flow air. A diluted fuel mixture (65% H2 and 35% N2 by volume) is issued from the central slot at an inlet temperature of 400 K. This central jet is surrounded on either side by co-flowing heated air streams with an inlet temperature of 850 K, at atmospheric pressure. The jet width at the inlet is 2 mm. The jet Reynolds number is 8000. Velocity fluctuations, u′, which is 10% of Ujet, is obtained by generating an auxiliary homogeneous isotropic turbulence field. These fluctuations are then fed from the inlet using Taylor’s hypothesis. This 2000 × 1600 × 400 computational domain is 15H × 20H × 3H in the streamwise x-, transverse y-, and spanwise z- directions, respectively, resulting in a total of 1.28 billion cells. A uniform grid size of 15 μm is placed in the x- and z-directions, while the y-directional grid is algebraically stretched outside the flame and shear zones. Improved non-reflecting boundary conditions are adopted in the x- and y-directions, while periodic boundary conditions are applied in the z-direction. The data is collected after four jet flow-through times after the flame becomes statistically stationary. + +The Sandia DNS code, S3D, is employed for solving the compressible Navier–Stokes, species conservation, and total energy equations. Spatial derivatives are approximated with an eighth-order central difference scheme, and a tenth-order filter is used to remove any spurious high-frequency fluctuations in the solution. For time integration, a fourth-order explicit Runge-Kutta method is used. The employed detailed hydrogen-air chemical mechanism composed of 9 species and 21 elementary reaction steps was developed by Li et al. + +## Quick Info +* Kaggle Link
+* Contributors: Ki Sung Jung, Jacqueline H. Chen +* Nx = 2000, Ny = 1600, Nz = 400, Nɸ = 6 + 9
+* Size = 93 GB +* DOI
+* .bib
+* info.json diff --git a/_datasets/firebench_wildfire_les.md b/_datasets/firebench_wildfire_les.md new file mode 100644 index 0000000..f1bbc15 --- /dev/null +++ b/_datasets/firebench_wildfire_les.md @@ -0,0 +1,156 @@ +--- +layout: datapage +excerpt: (117 cases) +title: FireBench data above ground level +description: LES of an ensemble of wildfire spread +header: + image: /assets/img/wang2024.png + teaser: /assets/img/ico_wang2024.png +categories: +- reacting +- environmental +- turbulent +- numerical +- benchmark +--- + + + +## Description +The propagation of wildfires is a complex, dynamic process that is influenced by various factors, such as fuel, wind, terrain, and other environmental conditions. Accurately and reliably predicting the rate-of-spread of wildfires is of critical importance for fire management, rapid fire response, and fire mitigation. The [Google FireBench dataset](https://sites.research.google/gr/wildfires/firebench/) [1] aims to provide high-fidelity data to tackle these issues by providing an ensemble of large-eddy simulations that capture the three-dimensional wildfire-spread behavior and coupling with the atmospheric environment. + +The spatial and temporal evolution of the combustion of solid fuel coupled with the +atmospheric flow is described by a two-phase model [2]. The gas-phase is described by +the Favre-filtered conservation equations for mass, momentum, oxygen-fraction, and potential temperature [3]: +{::nomarkdown} +$$ +\partial_t \overline{\rho} + \nabla \cdot (\overline{\rho} \widetilde{\boldsymbol{u}}) = S_\rho, +$$ +$$ +\partial_t (\overline{\rho} \widetilde{\boldsymbol{u}} ) + \nabla \cdot (\overline{\rho} \widetilde{\boldsymbol{u}} \otimes \widetilde{\boldsymbol{u}}) = - \nabla \overline{p_d} + \nabla \cdot \overline{\tau} + [\overline{\rho} - \rho(z)] g \boldsymbol{\hat{k}_z} + \boldsymbol{f}_D + \boldsymbol{f}_C, +$$ +$$ +\partial_t (\overline{\rho} \widetilde{Y_O}) + \nabla \cdot (\overline{\rho} \widetilde{\boldsymbol{u}} \widetilde{Y_O}) = \nabla \cdot \overline{\boldsymbol{j}_O} + \overline{\rho} \widetilde{\dot{\omega}_O}, +$$ +$$ +\partial_t (\overline{\rho} \widetilde{\theta}) + \nabla \cdot (\overline{\rho} \widetilde{\boldsymbol{u}} \widetilde{\theta}) = \nabla \cdot \overline{\boldsymbol{q}} + \frac{\overline{\rho} \widetilde{\theta}}{c_p \widetilde{T}} [h a_v (T_s - \widetilde{T}) + \dot{q}_r + (1-\Theta) H_f \widetilde{\dot{\omega}}], +$$ +where $\widetilde{\cdot}$ denotes Favre-filtering and $\overline{\cdot}$ denotes Reynolds filtering. $\rho$ is the density, $\boldsymbol{u}$ is the velocity vector, $p_d$ is the hydrodynamic pressure, $\tau$ is the shear stress tensor, $g$ is the gravitational acceleration, $\boldsymbol{\hat{k}_z}$ is the unit vector along the gravitational direction, $f_D = - \overline{\rho} c_d a_v \boldsymbol{|\widetilde{u}| \widetilde{u}}$ is the drag force due to surface vegetation, $\boldsymbol{f}_C = f \boldsymbol{\hat{k}_z} \times \overline{\rho} (\widetilde{\boldsymbol{u}} - \boldsymbol{U}_\infty)$ is the Coriolis force, $Y_O$, $\boldsymbol{j}_O$, and $\dot{\omega}_O$ are the mass fraction, species diffusion, and source term of the oxidizer, $\theta$ is the potential temperature, $\boldsymbol{q}$ is the heat flux vector, $T$ is the gas-phase temperature, and $H_f$ is the heat of combustion. +The heat exchange between the solid and gas phase is modeled with $h$ as the convective heat transfer coefficient, $a_v$ as the bulk fuel area-to-volume ratio, and $\dot{q}_r$ is the radiation source term. $\Theta = 1 - \rho_f/\rho_{f,0}$ is the fraction of the heat release that contributes to the increase of the solid phase temperature. +$\dot{\omega}$ is the gas-phase combustion source term. +{:/} + +The dataset consists of 117 cases with 9 velocities and 13 slopes with data extracted 1.5 m and 10 m above ground level. In addition, data was extracted at a streamwise location of 100 m < x < 1000 m. +Specifically, the cases span a range of mean inlet velocity at 10 m above ground level of 2 to 10 m/s with a step of 1 m/s, and a range of slopes from 0 to 30 degrees with steps of 2.5 degrees. + +## Quick Info +* Contributors: Qing Wang, Matthias Ihme, Cenk Gazen, Yi-Fan Chen, John Anderson, Jen Zen Ho, Bassem Akoush +* Nx = 900, Ny = 252 +* DOI +* .bib + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
IDConditionsSize (GB)Links
0 u10 = 2 m/s68 + Kaggle
+
1 u10 = 3 m/s42 + Kaggle
+
2 u10 = 4 m/s42 + Kaggle
+
3 u10 = 5 m/s42 + Kaggle
+
4 u10 = 6 m/s42 + Kaggle
+
5 u10 = 7 m/s42 + Kaggle
+
6 u10 = 8 m/s60 + Kaggle
+
7 u10 = 9 m/s42 + Kaggle
+
8 u10 = 10 m/s51 + Kaggle
+
+ +## References +[1]. Q. Wang, M. Ihme, C. Gazen, Y. F. Chen, J. Anderson. A high-fidelity ensemble simulation framework for interrogating wildland-fire behaviour and benchmarking machine learning models. International journal of wildland fire (2024). + +[2]. R. R. Linn. A transport model for prediction of wildfire behavior (No. LA-13334-T). PhD thesis. Los Alamos National Lab., NM, United States (1997). + +[3]. Q. Wang, M. Ihme, R. R. Linn, Y. F. Chen, V. Yang, F. Sha, C. Clements, J. S. McDanold, J. Anderson. A high-resolution large-eddy simulation framework for wildland fire predictions using TensorFlow. International journal of wildland fire (2023). diff --git a/_datasets/forced_hit_passive_scalars.md b/_datasets/forced_hit_passive_scalars.md new file mode 100644 index 0000000..e618c8c --- /dev/null +++ b/_datasets/forced_hit_passive_scalars.md @@ -0,0 +1,121 @@ +--- +layout: datapage +excerpt: (2 cases) +title: Forced HIT (Re$$_\lambda$$ = 390, 650) +description: Forced Homogeneous Isotropic Turbulence DNS with 3 Passive Scalars +header: + teaser: /assets/img/ico_pkyeung2025.png +categories: +- numerical +- nonreacting +- hit +- turbulent +--- +
+ Image 1 +
+ +## Description +These snapshots are from a series of Direct Numerical Simulations (DNS) of passive scalar mixing in three-dimensional homogeneous isotropic turbulence, at grid resolution up to $$16384^3$$ [1], performed using the exascale supercomputer named Frontier at Oak Ridge National Laboratory. The velocity fluctuations evolve according to the incompressible Navier-Stokes equations, while the scalar fluctuations follow an advection-diffusion equation, with a source term representing an imposed mean scalar gradient. The numerical methods employed are standard Fourier pseudo-spectral in space, second order in time, with aliasing errors controlled by a combination of phase shifting and truncation [2]. The velocity field is forced by keeping the values of the energy spectrum in the three lowest wavenumber shells constant [3]. + +The simulations begin from previously evolved velocity fields and are first run at a modest resolution of $$k_{max}\eta \approx 1.4$$ (where $$k_{max} = \sqrt 2 N/3$$ is the highest wavenumber resolved on an $$N^3$$ grid and $$\eta$$ is the Kolmogorov length scale) until the scalar fields reach statistical stationarity. The grid is then +refined to a higher resolution of $$k_{max} η \approx 2.8$$, and the simulation proceeds until the smallest scales fully adjust. Snapshots at this highest resolution have been collected for Taylor-scale Reynolds +numbers $$Re_\lambda \approx 390, 650, 1000 \text{ and } 1600$$. The Schmidt number is $$1.0$$ in all cases. Each snapshot captures the complete flow field — including velocity, pressure, and three passive +scalars — at a single instant in time. The three scalars are each subjected to a uniform mean gradient along a different coordinate direction. + + +## Quick Info +* Contributors: P.K Yeung, Daniel Dotson +* Nɸ = 4 + 3 + +* DOI +* .bib + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + +
IDRe$_{\lambda}$GridSize (GB)Links
0 39020483225` +
+ KaggleVP, info.jsonVP, +
+
+ KaggleY, info.jsonY +
+
+
1 650409631.8 TB +
+ KaggleP1, info.jsonP1, +
+
+ KaggleP2, info.jsonP2, +
+
+ KaggleU1, info.jsonU1, +
+
+ KaggleU2, info.jsonU2 +
+
+ KaggleV1, info.jsonV1, +
+
+ KaggleV2, info.jsonV2 +
+
+ KaggleW1, info.jsonW1, +
+
+ KaggleW2, info.jsonW2 +
+
+ KaggleY1,1, info.jsonY1,1, +
+
+ KaggleY1,2, info.jsonY1,2 +
+
+ KaggleY2,1, info.jsonY2,1, +
+
+ KaggleY2,2, info.jsonY2,2 +
+
+ KaggleY3,1, info.jsonY3,1, +
+
+ KaggleY3,2, info.jsonY3,2 +
+
+
+ +## References +[1] D. L. Dotson, P. K. Yeung, and K. R. Sreenivasan. A Study of passive scalar turbulence at high Reynolds numbers enabled by exascale computing. Bull. Am. Phys. Soc. +https://meetings.aps.org/Meeting/DFD24/Session/R37.00003, 2024. +[2] R. S. Rogallo. Numerical experiments in homogeneous turbulence. NASA TM 81315, NASA Ames Research Center, Moffett Field, CA., 1981. +[3] D. A. Donzis and P. K. Yeung. Resolution effects and scaling in numerical simulations of passive +scalar mixing in turbulence. Physica D, 239:1278–1287, 2010. diff --git a/_datasets/h2ch4_turbulent_jet_flows.md b/_datasets/h2ch4_turbulent_jet_flows.md new file mode 100644 index 0000000..b49c06b --- /dev/null +++ b/_datasets/h2ch4_turbulent_jet_flows.md @@ -0,0 +1,95 @@ +--- +layout: datapage +excerpt: (4 cases) +title: H2/CH4 Turbulent Jet Flows +description: H2/CH4 Fuel Mixtures, Turbulent Round Jet Premixed Flame DNS +header: + teaser: /assets/img/ho2024_ico.png +categories: +- reacting +- jet +- turbulent +- numerical +--- + +
+ Image 1 +
+ +## Description + +The DNS configurations by Ho et al. [1] investigates four turbulent round jet flames fueled by 0, 10, 50, and 80% hydrogen by volume, with the rest by methane, while maintaining the jet Reynolds number at 10,300. The jet is preheated to 450 K and the coflow is set to the adiabatic combustion products. The setup is initialized with combustion products at adiabatic flame temperature and at atmospheric pressure. A reduced mechanism with Quasi-Steady State chemistry is used, resulting in 16 transported species and 7 QSS species. The original simulation domain size is 25D×16D×16D, though note that the sponge layer data has been removed from this dataset, resulting in a 19.3D×5D×5D domain. After removal of the sponge layer, the grid sizes are 1739×620×620, 1749×486×486, 1730×571×571, and 1831×654×654 for the H0, H10, H50, and H80 cases, respectively. Five snapshots of each case is provided. + +The DNS is performed using the code NTMIX-CHEMKIN, which solves fully compressible Navier-Stokes equations along with energy and species conservation equations in Cartesian coordinates. The solver uses an eight-order explicit central spatial difference scheme and a third-order Runge-Kutta time integration scheme. Ideal gas law and mixture-averaged species-specific properties are used for the simulations. Further details of the DNS configuration and solver are provided in Ho et al. [1]. + +## Quick Info +* Contributors: Jen Zen Ho, Mohsen Talei +* DOI +* .bib + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
IDConditionsSize (GB)Links
0 0% H2 100% CH4790 + Kaggle1, info.json1
+ Kaggle2, info.json2
+ Kaggle3, info.json3
+ Kaggle4, info.json4
+ Kaggle5, info.json5
+
1 10% H2 90% CH4490 + Kaggle1, info.json1
+ Kaggle2, info.json2
+ Kaggle3, info.json3
+ Kaggle4, info.json4
+ Kaggle5, info.json5
+
2 50% H2 50% CH4654 + Kaggle1, info.json1
+ Kaggle2, info.json2
+ Kaggle3, info.json3
+ Kaggle4, info.json4
+ Kaggle5, info.json5
+
3 80% H2 20% CH4878 + Kaggle1, info.json1
+ Kaggle2, info.json2
+ Kaggle3, info.json3
+ Kaggle4, info.json4
+ Kaggle5, info.json5
+
+ +## References +[1]. J. Z. Ho, M. Talei, and R. L. Gordon. Direct numerical simulation of stoichiometric hydrogen/methane premixed jet flames. International Journal of Hydrogen Energy 81, pp. 831-841 (2024). diff --git a/_datasets/nh3h2air_premixed_slot_flame.md b/_datasets/nh3h2air_premixed_slot_flame.md new file mode 100644 index 0000000..0685a1e --- /dev/null +++ b/_datasets/nh3h2air_premixed_slot_flame.md @@ -0,0 +1,29 @@ +--- +layout: datapage +title: Premixed Flame NH3-H2-Air +description: NH3-H2-Air Premixed Flame DNS +excerpt: (1 case) +header: + teaser: /assets/img/ico_coulon2023.png +categories: +- reacting +- turbulent +- jet +- numerical +--- + +
+ Image 1 +
+ +## Description +This DNS corresponds to a slot burner turbulent flame, where burnt gases at equilibrium surround a rectangular slot injecting fresh premixed gases. All calculations are performed with the compressible solver AVBP3 for solving the conservation of mass, momentum, energy and species equations. A third-order accurate in space and time Taylor-Galerkin finite-element scheme is used for the discretization of the convective terms, while a second-order Galerkin scheme is used for diffusion terms. Axial dimensions have been chosen using preliminary estimations of flame brush lengths to avoid interference with lateral boundaries, and to average in the transverse direction. A central jet injects a flow of fresh turbulent gases. Turbulence in this central jet is homogeneous and isotropic (HIT) with obtained by a synthetic generation method built from a Fourier series decomposition. Two slow laminar coflows of burnt gases are imposed on both sides of the central jet. Their composition corresponds to the burnt gas states of the central mixture. Ammonia-hydrogen/air mixtures are at stoichiometry whereas the. Simulations are initialized with burnt conditions inside the domain before beginning the injection of fresh gases at the inlet boundary. In the fresh-burnt transition region, species mass fraction and temperature profiles are set to follow the unstretched laminar flames profiles, and a smooth transition is enforced through a hyperbolic tangent function. The domain is periodic in the spanwise direction (z), no-slip conditions are specified in the crosswise direction (y) and static pressure is imposed at the outlet. Both inlet and outlet boundary conditions are treated with the Navier–Stokes Characteristic Boundary Conditions (NSCBC). + +## Quick Info +* Kaggle1, Kaggle2, Kaggle3, Kaggle4 +* Contributors: Victor Coulon and Corentin Lapeyre +* Nx = 2191, Ny = 627, Nz = 314, Nɸ = 6 + 15 +* Size = 257 GB +* DOI
+* .bib
+* info.json1 , info.json2 , info.json3 ,info.json4 diff --git a/_datasets/nonreacting_channel_flow.md b/_datasets/nonreacting_channel_flow.md new file mode 100644 index 0000000..3e52f70 --- /dev/null +++ b/_datasets/nonreacting_channel_flow.md @@ -0,0 +1,33 @@ +--- +layout: datapage +title: Non-Reacting N$$_2$$ Channel Flow +excerpt: (6 cases) +header: + teaser: /assets/img/ico_guo2022.png +categories: +- nonreacting +- channel +- turbulent +- numerical +description: Transcritical Channel Flow N2 Turbulence DNS +--- + +
+ Image 5 +
+ +## Description + +The study by Guo et al. involves six different configurations of wall-bounded DNS in the transcritical regime. The schematic of the DNS setup is shown in Figure 11. They used nitrogen N2 as the working fluid with a critical pressure and temperature of pc = 3.39 MPa and Tc = 126.19 K. These studies consider the flow of N2 inside a channel with a hot top and a cold bottom wall with temperatures Thot and Tcold, respectively. The six variations correspond to different temperature ratio (TR) between the two walls. The channel is periodic in streamwise and spanwise direction, while the wall boundary conditions are enforces at two walls. The domain dimensions are Lx × 2Ly × Lz , where Lx/Ly = 2π, Lz/Ly = 4π/3 and the channel height is 2Ly = 9.0132×10−5 m. A Cartesian grid (with mesh size 384 × 256 × 384) is used for all six configurations. + +A compressible finite-volume solver is used for these DNS. The governing equations are solved using a strong stability-preserving Runge-Kutta scheme with third-order accuracy in time step- ping, and a fourth-order accurate central spatial finite difference, which reduces to third-order for non-uniform meshes. As the conditions of these simulations are in the transcritical regime, the Peng-Robinson EoS is used, which provides better accuracy in predicting thermodynamic variables than ideal gas in the investigated regime. To avoid the pressure oscillations and to obtain physically realizable solutions, an entropy-stable double-flux model is used along with second-order accurate essentially non-oscillatory (ENO) scheme and Harten-Lax-Van Leer contact (HLLC) Riemann flux computations. + + +## Quick Info +* Kaggle Link +* Contributors: Jack Guo, Matthias Ihme +* Nx = 385, Ny = 257, Nz = 257, Nɸ = 6 +* Size = 93 GB +* DOI
+* .bib
+* info.json diff --git a/_datasets/nonreacting_channel_flow_2.md b/_datasets/nonreacting_channel_flow_2.md new file mode 100644 index 0000000..c5a3bad --- /dev/null +++ b/_datasets/nonreacting_channel_flow_2.md @@ -0,0 +1,212 @@ +--- +layout: datapage +excerpt: (2 cases) +title: Non-Reacting Channel Flow +description: Non-Reacting Channel Flow DNS +header: + teaser: /assets/img/ico_mklee2015.png +categories: +- nonreacting +- channel +- turbulent +- numerical +--- + + +## Description +These snapshots are from a Direct Numerical Simulation (DNS) of incompressible turbulent channel flow at friction Reynolds number $$Re_\tau = 544$$ and bulk Reynolds number $$Re_b = 10,000$$ [1]. The computational domain has dimensions $$L_x = 8\pi$$ and $$L_z = 3\pi$$ in the streamwise and spanwise directions respectively, with periodic boundary conditions applied in both directions. The channel width is set to $$L_y = 2$$. No-slip/no-penetration boundary conditions are enforced at the walls. The flow is driven by a uniform pressure gradient that varies in time to maintain constant mass flux through the channel. +The numerical methods employ a Fourier-Galerkin approach in the streamwise and spanwise directions. The wall-normal direction is represented using a B-spline collocation method. Time advancement employs a low-storage implicit-explicit scheme based on third-order Runge-Kutta for nonlinear terms and Crank-Nicolson for viscous terms. Each snapshot captures the complete three-dimensional flow field including all three velocity components (u, v, w) at a given time. + +## Quick Info +* Contributors: Myoungkyu Lee +* Nx = 1536, Ny = 384, Nz = 1024 +* Nɸ = 4 +* DOI +* .bib + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + +
IDRe$_{\tau}$DescriptionSize (TB)Links
0 544One Flow Through Time4.5 +
+ Kaggle000-020, info.json000-020, +
+
+ Kaggle021-041, info.json021-041, +
+
+ Kaggle042-062, info.json042-062, +
+
+ Kaggle063-083, info.json063-083, +
+
+ Kaggle084-104, info.json084-104, +
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+ Kaggle105-125, info.json105-125, +
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+ Kaggle126-146, info.json126-146, +
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+ Kaggle147-167, info.json147-167, +
+
+ Kaggle168-188, info.json168-188, +
+
+ Kaggle189-209, info.json189-209, +
+
+ Kaggle210-230, info.json210-230, +
+
+ Kaggle231-251, info.json231-251, +
+
+ Kaggle252-272, info.json252-272, +
+
+ Kaggle273-293, info.json273-293, +
+
+ Kaggle294-314, info.json294-314, +
+
+ Kaggle315-335, info.json315-335, +
+
+ Kaggle336-356, info.json336-356, +
+
+ Kaggle357-377, info.json357-377, +
+
+ Kaggle378-398, info.json378-398, +
+
+ Kaggle399-419, info.json399-419, +
+
+ Kaggle420-440, info.json420-440, +
+
+ Kaggle441-461, info.json441-461, +
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+ Kaggle462-482, info.json462-482, +
+
+ Kaggle483-503, info.json483-503, +
+
+ Kaggle504-509, info.json504-509, +
+
+
1 544Collection of snapshots at different time4.5 +
+ Kaggle000-020, info.json000-020, +
+
+ Kaggle021-041, info.json021-041, +
+
+ Kaggle042-062, info.json042-062, +
+
+ Kaggle063-083, info.json063-083, +
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+ Kaggle084-104, info.json084-104, +
+
+ Kaggle105-125, info.json105-125, +
+
+ Kaggle126-146, info.json126-146, +
+
+ Kaggle147-167, info.json147-167, +
+
+ Kaggle168-188, info.json168-188, +
+
+ Kaggle189-209, info.json189-209, +
+
+ Kaggle210-230, info.json210-230, +
+
+ Kaggle231-251, info.json231-251, +
+
+ Kaggle252-272, info.json252-272, +
+
+ Kaggle273-293, info.json273-293, +
+
+ Kaggle294-314, info.json294-314, +
+
+ Kaggle315-335, info.json315-335, +
+
+ Kaggle336-356, info.json336-356, +
+
+ Kaggle357-377, info.json357-377, +
+
+ Kaggle378-398, info.json378-398, +
+
+ Kaggle399-419, info.json399-419, +
+
+ Kaggle420-440, info.json420-440, +
+
+ Kaggle441-461, info.json441-461, +
+
+ Kaggle462-482, info.json462-482, +
+
+ Kaggle483-503, info.json483-503, +
+
+ Kaggle504-509, info.json504-509, +
+
+
+ +## References +[1] Lee, M., & Moser, R. D. (2015). Direct numerical simulation of turbulent channel flow up to Reτ ≈ 5200. Journal of Fluid Mechanics, 774, 395-415. diff --git a/_datasets/passive_scalar_hit.md b/_datasets/passive_scalar_hit.md new file mode 100644 index 0000000..6204ad4 --- /dev/null +++ b/_datasets/passive_scalar_hit.md @@ -0,0 +1,91 @@ +--- +layout: datapage +excerpt: (6 cases) +title: Forced HIT (Re$$_\lambda$$ = 88-331) +description: Passive Scalar HIT DNS +header: + teaser: /assets/img/ico_gauding2022.png +categories: +- nonreacting +- hit +- numerical +- turbulent +--- + +
+ Image 1 +
+ +# Description +This DNS configuration simulates non-reacting forced homogeneous isotropic turbulence with a passive scalar. The DNS solver utilizes the analytical framework developed by Gauding et al., which is designed to investigate the structure and kinematics of iso-scalar fields. This approach involves a two-point statistical analysis of the phase indicator field to track a specified iso-scalar volume. The scalar field is represented as ξ̃ =Gξ y + ξ with the mean scalar gradient Gξ assumed to be unity. The first term represents the mean scalar field while the second term is the fluctuations. To maintain a statistically steady state, external stochastic forcing is applied to the velocity field, as described by Eswaran and Pope (1988). This forcing is statistically isotropic and restricted to low wavenumbers to minimize its impact on small scales. The BLASTNet dataset includes five parametric variations of this configuration, differing by (i) Reynolds number based on the Taylor microscale, and (ii) grid size. Each configuration contains four variables: the velocity components (u, v, w) and the scalar fluctuation field ξ. + + +# Quick Info +* Contributors: Michael Gauding +* Nɸ = 4 +* DOI +* .bib + +# Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
IDConditionsGridSize (GB)Links
0 Reλ = 88512325.23 + Kaggle, + info.json, +
1 Reλ = 12110243131.14 + Kaggle, + info.json, +
2 Reλ = 18410243133.14 + Kaggle, + info.json, +
3 Reλ = 21820483137.44 + Kaggle, + info.json, +
4 Reλ = 33120483137.44 + Kaggle, + info.json, +
diff --git a/_datasets/premixed_flame_wall_interaction_ch4air.md b/_datasets/premixed_flame_wall_interaction_ch4air.md new file mode 100644 index 0000000..74ee92c --- /dev/null +++ b/_datasets/premixed_flame_wall_interaction_ch4air.md @@ -0,0 +1,36 @@ +--- +layout: datapage +title: Reacting Channel Flow +excerpt: (1 case) +header: + teaser: /assets/img/ico_jiang2021.png +description: Premixed Flame-wall Interaction CH4-Air DNS +categories: +- reacting +- channel +- numerical +- turbulent +--- + +
+ Image 1 +
+ +## Description + +This DNS configuration by Jiang et al. investigates the flame-wall interaction for methane/air flames diluted by hot combustion products in a 3D turbulent V-flame configuration inside a channel with isothermal hot and cold walls. At the inlet of the channel, the reactant mixture consists of a mixture of cold reactants (30%) and hot combustion products from 1D premixed freely-propagating flame simulation (70%), resulting in an inlet temperature of Tin = 1705 K at 2 atm pressure. The hot and cold wall temperatures are fixed at 1200 and 400 K, respectively. The inlet turbulence is generated with a non-reacting simulation of the same channel. Then, the results collected at a sampling plane of x/H = 4 are fed into the reacting simulation. This turbulence generation allows coupling of the velocity and temperature fluctuations at the inlet. + +Velocity fluctuations are first produced using the Passot-Pouquet spectrum for the turbulent kinetic energy. The inlet turbulence for the non-reacting simulation was then generated by rescaling these fluctuations with the RMS profiles of a fully developed channel flow at a Reynolds number of 3200. Next, this is fed into the domain with a convection velocity 25% lower than the mean inlet velocity at the centerline. This accounts for a correction to the Taylor’s hypothesis due to the high near-wall shear stress. Non-reflecting Navier-Stokes Characteristic Boundary Condition (NSCBC) is used for the outlet boundary, and a periodic boundary condition is used in the z-direction. For the reacting case to ignite, a cylindrical hot patch is imposed at y/H = 0 and x/H = 1 with a diameter of 0.03H, which creates two branches of the V-flame that interact with two walls. + +The domain size is 12H × 2H × 3H, with a grid size of 1000 × 250 × 250, which stretches from 5 μm at the wall to 30 μm at the centerline in the y-direction, and 30 μm uniform grid in both x- and z-direction, and ensures at least one grid point within one wall unit and a mean grid size less than 1.4 times the Kolmogorov length scale. There are around 20 grid points inside the flame thickness as well. + +The numerical solver used for the DNS study is NTMIX-CHEMKIN. This solver features an eighth-order central finite difference scheme for spatial derivatives and a third-order Runge-Kutta time integrator. A tenth-order explicit filter is also used to eliminate spurious oscillations at high wave numbers. Ideal gas law is used as the EoS. A reduced mechanism for methane/air combustion with 23 species, 12 quasi-steady species and 205 reactions is developed for this study. + +## Quick Info +* Kaggle Link
+* Contributors: Bin Jiang, Mohsen Talei +* Nx = 1001, Ny = 251, Nz = 251, Nɸ = 6 + 23 +* Size = 89 GB +* DOI
+* .bib
+* info.json diff --git a/_datasets/premixed_slot_flame_h2air.md b/_datasets/premixed_slot_flame_h2air.md new file mode 100644 index 0000000..ac795ca --- /dev/null +++ b/_datasets/premixed_slot_flame_h2air.md @@ -0,0 +1,148 @@ +--- +layout: datapage +excerpt: (5 cases) +title: Premixed Flame H2-Air +description: Premixed Flame H2-Air DNS in Slot Burner +header: + teaser: /assets/img/ico_quentin2024.png +# image: /assets/img/quentin2024.png +categories: +- reacting +- jet +- turbulent +- numerical +--- +
+ Image 1 +
+ +## Description +The configuration is a slot burner at constant pressure $$P = 1$$ atm and fresh gas temperature $$T_u = 300$$ K used to generate a training database for the modeling of subfilter-scale features in lean premixed H$$_2$$-air reacting flows using a CNN [1]. The physical domain consists of a central inlet where a premixed H2-air mixture flows at a bulk velocity $$U_b = 24$$ m/s with velocity fluctuation $$u′= 2.4$$ m/s, surrounded by two laminar coflows where burnt gas flows at a bulk velocity $$U_c = 3.6$$ m/s. The injection of turbulence at the central inlet corresponds to homogeneous and isotropic turbulence using a Passot-Pouquet turbulence spectrum [2] with an integral length scale $$l_t = 2$$ mm. The domain is rectangular with periodic boundary conditions in the z-direction. Adiabatic walls are specified in the y-direction. Both inlets and outlet are specified in the x-direction. This configuration is computed for five different global equivalence ratios $$\phi_g = $$ 0.35, 0.4, 0.5, 0.6 and 0.7. All other parameters are kept constant. The Reynolds number of the central inlet is about 10,000 for all cases. +DNS of the slot burner cases are performed using the AVBP [3] massively parallel code solving the +compressible multi-species Navier-Stokes equations. A third order accurate Taylor–Galerkin scheme is adopted +for discretization of the convective terms [4]. NSCBC [5] are imposed at the inlets (relaxation factor of 1000 +s−1) and at the outlet (relaxation factor of 200 s−1). Dynamic viscosity µ follows a power law function of +temperature $$T$$ + + +$$\mu = \mu_0 \left(\frac{T}{T_0}\right)^\gamma$$ + +with $$\mu_0 = 8.062 × 10−5$$ kg/m.s, $$T_0 = 2.645 \times 10^3$$ K and $$γ = 6.481 \times 10^{−1}$$. Thermal diffusivity is computed +from the viscosity using a constant Prandtl number: $$Pr = 0.66$$. Species diffusivities are computed using +a constant Schmidt number specific for each species. This approach takes into account non-unity +Lewis numbers and preferential diffusion between the different species. It was verified that the errors made by +the simplified transport description are negligible by comparing the results with simulations using a mixture- +averaged transport model [1]. Soret and Dufour transport processes are ignored in the simulations of the present +work. Hydrogen chemical kinetics relies on the San Diego mechanism [6], already successfully used for H2-air +premixed combustion in Coulon et al. [7]. This mechanism comprises 9 species and 21 reactions. + +The mesh is a homogeneous Cartesian grid with constant element size $\Delta_x = 80 \mu m$ for $$\phi_g = 0.35, 0.4$$ and +$$0.6$$, and $$\Delta_x = 50 \mu m$$ for $$\phi_g = 0.6\ \mathrm{and}\ 0.7$$. The length of the domain in the x-direction $$L_x$$ is adapted to the length of turbulent the flame brush. It varies from 76 mm for $$\phi_g = 0.35$$ to $$36$$ mm for $$\phi_g= 0.7$$. + +## Application +This database was generated to train a CNN to infer H$$_2$$-air burning rates. The data-driven, supervised learning +methodology is described in Malé et al. [1]. It involves using the database, filtered to emulate LES solutions, to train a +CNN to approximate burning rates based on relevant input variables. The emulated LES database comprises the +five different global equivalence ratios of the present DNS database and three different filter sizes. Random crops, +rotations and flips are performed to ensure that the CNN is invariant to translation [8] and has no preferential +orientation. Once trained, the CNN-based model is shown to infer burning rates on full LES solutions never +seen during training with high accuracy. In addition to this, the model is found to infer burning rates on filter +sizes and equivalence ratios other than those used for training. More details can be found in Malé et al. [1]. Code for +training and inference is available via GitLab at https://gitlab.com/male.quentin/cnn_h2flame. + +
+ Image 1 +
+ +## Quick Info +* Contributors: Quentin Malé +* Nɸ = 6 + 9 + +* DOI +* .bib + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ID$$\phi_g$$GridSize (GB)Links
0 0.35951×401×20116 + Kaggle, info.json
+
1 0.4901×401×20115 + Kaggle, info.json
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2 0.5651×401×20111 + Kaggle, info.json
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3 0.61041×641×32131 + Kaggle, info.json
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4 0.7721×641×32145 + Kaggle, info.json
+
+ +## References +[1] Malé, Q., Lapeyre, C. J., and Noiray, N. (2024). Hydrogen reaction rate modeling based on convolutional +neural network for large eddy simulation. Accepted for publication in Data-Centric Engineering, to appear. +arXiv:2408.16709 [cs.CE]. +[2] Passot, T. and Pouquet, A. (1987). Numerical simulation of compressible homogeneous flows in the turbulent +regime. Journal of Fluid Mechanics, 181:441–466. +[3] Gicquel, L. Y., Gourdain, N., Boussuge, J.-F., Deniau, H., Staffelbach, G., Wolf, P., and Poinsot, T. (2011). +High performance parallel computing of flows in complex geometries. Comptes Rendus M´ecanique, 339(2- +3):104–124. +[4] Colin, O. and Rudgyard, M. (2000). Development of High-Order Taylor–Galerkin Schemes for LES. Journal +of Computational Physics, 162(2):338–371. +[5] Poinsot, T. and Lelef, S. (1992). Boundary conditions for direct simulations of compressible viscous flows. +Journal of Computational Physics, 101(1):104–129. +[6] Saxena, P. and Williams, F. A. (2006). Testing a small detailed chemical-kinetic mechanism for the +combustion of hydrogen and carbon monoxide. Combustion and Flame, 145(1-2):316–323. +[7] Coulon, V., Gaucherand, J., Xing, V., Laera, D., Lapeyre, C., and Poinsot, T. (2023). Direct numerical +simulations of methane, ammonia-hydrogen and hydrogen turbulent premixed flames. Combustion and Flame, +256:112933. +[8] Biscione, V. and Bowers, J. S. (2021). Convolutional neural networks are not invariant to translation, but +they can learn to be. Journal of Machine Learning Research, 22(229):1–28. + + + + diff --git a/_datasets/rayleigh_benard_convection.md b/_datasets/rayleigh_benard_convection.md new file mode 100644 index 0000000..ec7e2ca --- /dev/null +++ b/_datasets/rayleigh_benard_convection.md @@ -0,0 +1,180 @@ +--- +layout: datapage +excerpt: (5 cases) +title: Rayleigh-Bénard Convection +description: Rayleigh-Bénard Convection DNS +header: + teaser: /assets/img/ico_roshan2024.png + image: /assets/img/roshan2024.png +categories: +- nonreacting +- channel +- pipe +- turbulent +- numerical +--- + + + +## Description +Rayleigh Benard Convection (RBC) is a benchmark fluid-dynamics problem for simulating natural thermal +convection. It consists of a thin layer of fluid confined between a pair of parallel horizontal plates. The top plate is +cooler than the bottom plate, and when this temperature difference is sufficiently high, a convective flow arises.This phenomenon can be simulated numerically by solving the incompressible Navier-Stokes equations under the +Boussinesq approximation: + +$$ +\frac{\partial \mathbf{u}^*}{\partial t^*} + \mathbf{u}^* \cdot \nabla \mathbf{u}^* = -\frac{1}{\rho_0} \nabla p^* + \nu \nabla^2 \mathbf{u}^* + \alpha g T^* \hat{\mathbf{z}} +$$ + +$$\frac{\partial T^*}{\partial t^*} + \mathbf{u}^* \cdot \nabla T^* = \kappa \nabla^2 T^* $$ + +$$\nabla \cdot \mathbf{u}^* = 0$$ + +Here, $$\mathbf{u}^*$$, $$p^*$$ and $$T^*$$ are the velocity, pressure and temperature fields respectively. These quantities are in the dimensional form (including time, $$t^*$$). The length scales are non-dimensionalized with respect to the height of the domain, $$𝐻$$. Similarly, the temperature field is non-dimensionalized by the temperature difference between the bottom and top plates, $$\Delta = 𝑇_𝑏 − 𝑇_𝑡$$. This gives the free-fall velocity, $$𝑈_𝑓 = \sqrt{\alpha g \Delta 𝐻}$$, which is used to non- +dimensionalize the velocity field. The non-dimensional variables can therefore be written as: + +$$\mathbf{u} = \frac{\mathbf{u}^*}{U_f} \quad ,\quad T = \frac{T^*}{\Delta} \quad ,\quad t = \frac{U_f t^*}{H} \quad ,\quad p = \frac{p^*-p_0}{\rho _0 U_f^2}$$ + +where $$p_0$$ and $$\rho _0$$ are the reference pressure and density respectively. Since the DNS is performed with non-dimensional variables, the values of 𝑝0 and 𝜌0 are not set explicitly in the code. If necessary, they can be assumed to be 101.3 kPa and 1.2 kg/m3 respectively, as prescribed by the International Standard Atmosphere (ISA) at sea- +level. Finally, we obtain the following non-dimensional equations for velocity and temperature which are solved in the DNS of RBC: + +$$\frac{\partial \mathbf{u}}{\partial t} + \mathbf{u} \cdot \nabla \mathbf{u} = -\nabla p + \sqrt{Ra / Pr} \nabla^2 \mathbf{u} + T \hat{\mathbf{z}}$$ + +$$\frac{\partial T}{\partial t} + \mathbf{u} \cdot \nabla T= \frac{1}{\sqrt{Ra Pr}} \nabla^2 T $$ + +$$\nabla \cdot \mathbf{u} = 0$$ + +The non-dimensional parameter, Rayleigh number ($$Ra$$), quantifies the degree of forcing imparted by buoyancy, +whereas the Prandtl number ($$Pr$$) is the dimensionless ratio between the viscous and thermal diffusivities of the fluid: + +$$Ra = \frac{\alpha g \Delta H^3}{\nu \kappa} \quad,\quad Pr = \frac{\nu}{\kappa}$$ + +The present dataset is generated from DNS of RBC within a periodically extended Cartesian +box of aspect ratio $$\Gamma = L/H =4$$, where L is the length of the box. All the simulations are performed with these fixed dimensions of 4 × 4 × 1. The DNS are performed using the GPU accelerated spectral element solver, NekRS [1], at a fixed $$Pr = 0.7$$ and at $$10^5 \leq Ra \leq 10^9$$. +Although the original simulations were performed on grids of increasingly finer resolutions [2], all fields have been interpolated to a uniform grid of size 2049 × 2049 × 1025 with a grid-spacing of 2h × 2h × h, where h is the grid spacing along the vertical 𝑧-axis. This +axis has a higher resolution to resolve the boundary layers properly. The interpolation was performed using spectral +element routines of NekRS itself to ensure maximum accuracy. There are 20 snapshots for each case. + +## Quick Info +* Contributors: Roshan Samuel, Mathis Bode +* Nx = 2049, Ny = 2049, Nz = 1025, Nɸ = 5 + +* DOI +* .bib + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
IDConditionsSize (TB)Links
0 Ra = 1051.44 + Kaggle0, info.json0
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+ Kaggle2, info.json2
+ Kaggle3, info.json3
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+ Kaggle5, info.json5
+ Kaggle6, info.json6
+ Kaggle7, info.json7
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1 Ra = 1061.44 + Kaggle0, info.json0
+ Kaggle1, info.json1
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+ Kaggle5, info.json5
+ Kaggle6, info.json6
+ Kaggle7, info.json7
+ Kaggle8, info.json8
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2 Ra = 1071.44 + Kaggle0, info.json0
+ Kaggle1, info.json1
+ Kaggle2, info.json2
+ Kaggle3, info.json3
+ Kaggle4, info.json4
+ Kaggle5, info.json5
+ Kaggle6, info.json6
+ Kaggle7, info.json7
+ Kaggle8, info.json8
+ Kaggle9, info.json9
+
3 Ra = 1081.44 + Kaggle0, info.json0
+ Kaggle1, info.json1
+ Kaggle2, info.json2
+ Kaggle3, info.json3
+ Kaggle4, info.json4
+ Kaggle5, info.json5
+ Kaggle6, info.json6
+ Kaggle7, info.json7
+ Kaggle8, info.json8
+ Kaggle9, info.json9
+
4 Ra = 1091.44 + Kaggle0, info.json0
+ Kaggle1, info.json1
+ Kaggle2, info.json2
+ Kaggle3, info.json3
+ Kaggle4, info.json4
+ Kaggle5, info.json5
+ Kaggle6, info.json6
+ Kaggle7, info.json7
+ Kaggle8, info.json8
+ Kaggle9, info.json9
+
+ +## References +[1]. P. F. Fischer, S. Kerkemeier, M. Min, Y.-H. Lan, M. Phillips, T. Rathnayake, E. Merzari, A. Tomboulides, A. Karakus, N. Chalmers, and T. Warburton. a GPU-accelerated spectral element Navier–Stokes solver. Parallel Computing 114, 102982 (2022). +[2]. R. J. Samuel, M. Bode, J. D. Scheel, K. R. Sreenivasan and J. Schumacher. No sustained mean velocity in the boundary region of plane thermal convection. Journal of Fluid Mechanics 996, A49 (2024). + + + diff --git a/_datasets/turbulent_round_jet_premixed_ch4air.md b/_datasets/turbulent_round_jet_premixed_ch4air.md new file mode 100644 index 0000000..cc05a53 --- /dev/null +++ b/_datasets/turbulent_round_jet_premixed_ch4air.md @@ -0,0 +1,43 @@ +--- +layout: datapage +excerpt: (2 cases) +title: Reacting Jet Flows +description: Turbulent Round Jet Premixed COFFEE CH4-air Premixed Flame DNS +header: + teaser: /assets/img/ico_brouzet2021.png +categories: + - reacting + - turbulent + - jet + - numerical +--- + +
+ Image 1 +
+ +## Description + +The DNS configurations by Brouzet et al. involve two parametric variations of 3D reacting turbulent premixed methane/air round-jet flames with high-fidelity acoustics to investigate the effect of different chemical mechanisms on flame dynamics. The setup is initialized with methane/air combustion products at adiabatic flame temperature and at atmospheric pressure. The jet Reynolds and Mach numbers are 5300 and 0.36, respectively. A schematic representation of the DNS configuration is shown in Figure 10. The two variations of the reacting jet correspond to two different chemical mechanisms: (i) a semi-global CH4-BFER mechanism with 2 reactions, and (ii) a skeletal COFFEE mechanism with 14 species and 38 reactions. In both configurations, the domain size is 20D×16D×16D. The grid sizes are 1811×721×721 and 1546×676×676 for the BFER and COFFEE cases, respectively. These meshes correspond to 10 and 12 grid points per unit thermal flame thickness in the streamwise direction, and 12 and 16 points in the transverse and spanwise directions. + +The DNS is performed using the code NTMIX-CHEMKIN, which solves fully compressible Navier-Stokes equations along with energy and species conservation equations in Cartesian coor- dinates. The solver uses an eight-order explicit central spatial difference scheme and a third-order Runge-Kutta time integration scheme. Ideal gas law and mixture-averaged species-specific properties are used for the simulations. Further details of the DNS configuration and solver are provided in Brouzet et al. + +## Quick Info +* Contributors: Davy Brouzet, Mohsen Talei +* DOI +* .bib + +## BFER Case +* Kaggle Link
+* Nx = 1832, Ny = 721, Nz = 721, Nɸ = 6 + 6 +* Size = 58 GB +info.json + +## COFFEE Case +* Kaggle Link +* Nx = 1235, Ny = 676, Nz = 676, Nɸ = 6 + 14 +* Size = 52 GB +* info.json + + + diff --git a/_datasets/vitiated_h2air_flame.md b/_datasets/vitiated_h2air_flame.md new file mode 100644 index 0000000..dd5f881 --- /dev/null +++ b/_datasets/vitiated_h2air_flame.md @@ -0,0 +1,181 @@ +--- +layout: datapage +title: Freely-Propagating Flame +excerpt: (22 cases) +header: + teaser: /assets/img/ico_savard2019.png +description: Vitiated H2-air Freely Propagating Flame DNS +categories: +- reacting +- turbulent +- numerical +--- + +
+ Image 1 +
+ +## Description + +This DNS configuration presents a statistically-planar, freely-propagating flame. BLASTNet contains 22 parametric variations of this configuration that differ by three essential parameters involving turbulence: (i) turbulence intensity, characterized by the RMS velocity u′, (ii) inflow velocity, Uin , and (iii) integral length scale, lI. These configurations represent a series of hydrogen-premixed turbulent flames in autoignitive reheat combustion conditions that provide rich information on regimes of turbulent spontaneous ignition and turbulent deflagration. + +The turbulent flames are initialized with an ignition front. For the initial flat spontaneous ignition front, the thermo-chemical conditions are chosen to be representative of those at the end of the first stage of a heavy-duty gas turbine sequential combustor, but at a lower pressure of 1 atm for all configurations. The mixture of fuel and products of first stage hydrogen-air combustion at an equivalence ratio of 0.43 and initial temperature of 773 K is used at the inlet of the domain. This mixture is equivalent to an equivalence ratio of 0.35 and Tu = 990 K, and its ignition delay time (τign,0) and laminar flame speed (SL) are identified to be 0.55 ms and 14.7 ms−1, respectively. The reference laminar flame thickness, lf , is evaluated to be 0.66 mm. After initialization, the ignition front is superimposed on a turbulent flow-field using a one-to-one correspondence in x-space (Figure 14). Depending on varying Uin and u′, the flame may stabilize at a position far away from the inlet (a turbulent spontaneous ignition front) or the introduction of turbulence may trigger the transition to a deflagration, where the flame front propagates towards the inlet. + +The width of the domain in the y- and z-directions is Ly = Lz = 5.26lI, and the length in the streamwise direction is Lx, which is different for individual configuration. For all configurations, the simulations are run until a statistically steady state is achieved. +The low Mach number form of the governing equations is solved using the energy conservative, finite difference code NGA and high turbulence simulations are enabled by the linear velocity forcing method. NGA is second-order accurate in both space and time, and it uses a semi-implicit Crank-Nicolson time integration scheme. A third-order bounded QUICK scheme, BQUICK, is used for scalar transport. Ideal gas law is used as the EoS for a mixture of perfect gases. A detailed chemical mechanism for hydrogen combustion with 9 species and 21 reactions is used for all configurations. + + +## Quick Info +* DOI +* .bib +* Contributor: Bruno Savard + +## Links to different cases + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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