New fatigue example

doc/source/api/ply_wise_data.rst

@@ -6,7 +6,7 @@ Ply wise data
 .. autosummary::
     :toctree: _autosummary
 
-    ReductionStrategy
+    SpotReductionStrategy
     get_ply_wise_data
 
 

examples/006_filter_composite_data_example.py

@@ -31,7 +31,7 @@
 from ansys.dpf.composites.constants import Spot, Sym3x3TensorComponent
 from ansys.dpf.composites.example_helper import get_continuous_fiber_example_files
 from ansys.dpf.composites.layup_info import AnalysisPlyInfoProvider, get_all_analysis_ply_names
-from ansys.dpf.composites.ply_wise_data import ReductionStrategy, get_ply_wise_data
+from ansys.dpf.composites.ply_wise_data import SpotReductionStrategy, get_ply_wise_data
 from ansys.dpf.composites.select_indices import (
     get_selected_indices,
     get_selected_indices_by_analysis_ply,
@@ -82,7 +82,7 @@
         ply_name="P1L1__ud_patch ns1",
         mesh=composite_model.get_mesh(),
         component=Sym3x3TensorComponent.TENSOR11,
-        reduction_strategy=ReductionStrategy.MAX,
+        spot_reduction_strategy=SpotReductionStrategy.MAX,
         requested_location=dpf.locations.elemental,
     )
 

examples/012_fatigue_example.py

@@ -0,0 +1,156 @@
+"""
+.. _fatigue_plate_example:
+
+Evaluate fatigue for a composite plate
+--------------------------------------
+
+This example shows how to evaluate fatigue for a flat plate.
+It shows how you can use PyPDF Composites to select specific layers and define a custom
+combination method. For this example, the custom combination method is stress in fibre
+direction.
+
+A random load time series is created. Taking into account that the load is assumed
+proportional, rainflow counting is applied to the load time series.
+Load ranges are then applied on the stress combination method, and damage is evaluated
+by using a dummy S-N curve.
+
+Be aware that the fatpack package is not developed by Ansys, so it is the responsibility
+of the user to verify that it works as expected. For more information, see the
+`fatpack package <https://pypi.org/project/fatpack/>`_,
+
+"""
+
+
+# %%
+# Set up analysis
+# ~~~~~~~~~~~~~~~
+# Setting up the analysis consists of loading the required modules, connecting to the
+# DPF server, and retrieving the example files.
+#
+# Load Ansys libraries and numpy, matplotlib and fatpack
+import ansys.dpf.core as dpf
+import fatpack
+import matplotlib.pyplot as plt
+import numpy as np
+
+from ansys.dpf.composites.composite_model import CompositeModel
+from ansys.dpf.composites.constants import Sym3x3TensorComponent
+from ansys.dpf.composites.example_helper import get_continuous_fiber_example_files
+from ansys.dpf.composites.layup_info import AnalysisPlyInfoProvider
+from ansys.dpf.composites.select_indices import get_selected_indices_by_analysis_ply
+from ansys.dpf.composites.server_helpers import connect_to_or_start_server
+
+# %%
+# Start a DPF server and copy the example files into the current working directory.
+server = connect_to_or_start_server()
+composite_files_on_server = get_continuous_fiber_example_files(server, "fatigue")
+
+# %%
+# Create a composite model
+composite_model = CompositeModel(composite_files_on_server, server)
+
+# %%
+# Read stresses and define a specific layer and a component of stress tensor
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+#
+
+# %%
+# Read stresses
+stress_operator = composite_model.core_model.results.stress()
+stress_operator.inputs.bool_rotate_to_global(False)
+stress_fc = stress_operator.get_output(pin=0, output_type=dpf.types.fields_container)
+stress_field = stress_fc.get_field_by_time_id(1)
+
+# %%
+# Select layer P1L1__ModelingPly.2
+analysis_ply_info_provider = AnalysisPlyInfoProvider(
+    mesh=composite_model.get_mesh(), name="P1L1__ModelingPly.2"
+)
+
+# %%
+# Select Sigma11 as the combination method
+component = Sym3x3TensorComponent.TENSOR11
+
+
+# %%
+# Load time series and apply rainflow counting
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# A random time series is created. Load is assumed proportional, so rainflow counting
+# can be directly done on the load time series to get the load ranges.
+# No mean stress correction is applied.
+#
+number_of_times = 100
+load_factor_time_series = np.random.normal(-1, 2.5, size=number_of_times)
+x = np.linspace(1, number_of_times, number_of_times)
+plt.xlabel("Load Index")
+plt.ylabel("Load Factor")
+plt.plot(x, load_factor_time_series, color="red")
+
+
+# %%
+# Fatpack package is used for doing the rainflow counting
+load_range_factors = fatpack.find_rainflow_ranges(load_factor_time_series)
+
+
+# %%
+# S-N curve
+# ~~~~~~~~~
+# A dummy S-N curve is created. Note that this curve is not based on any
+# experimental data. Sc is chosen to be twice the orthotropic stress limit in the fiber direction.
+# and Nc is set to 1.
+#
+Sc = 2 * 1979
+Nc = 1
+s_n_curve = fatpack.LinearEnduranceCurve(Sc)
+# Value for UD materials
+s_n_curve.m = 14
+s_n_curve.Nc = Nc
+
+N = np.logspace(0, 9, 1000)
+S = s_n_curve.get_stress(N)
+line = plt.loglog(N, S)
+plt.grid(which="both")
+plt.title("Dummy Linear S-N curve")
+plt.xlabel("Cycles to failure")
+plt.ylabel("Stress range (MPa)")
+
+
+# %%
+# Damage evaluation
+# ~~~~~~~~~~~~~~~~~
+# Stress S11 at time 1 and layer P1L1__ModelingPly.2 are read
+# for each load range. Its damage is evaluated using the dummy S-N curve.
+#
+
+damage_result_field = dpf.field.Field(location=dpf.locations.elemental, nature=dpf.natures.scalar)
+
+with damage_result_field.as_local_field() as local_result_field:
+    element_ids = analysis_ply_info_provider.property_field.scoping.ids
+
+    for element_id in element_ids:
+        stress_data = stress_field.get_entity_data_by_id(element_id)
+        element_info = composite_model.get_element_info(element_id)
+        assert element_info is not None
+        selected_indices = get_selected_indices_by_analysis_ply(
+            analysis_ply_info_provider, element_info
+        )
+        # Load Range scaled by S11
+        s_11 = max(stress_data[selected_indices][:, component])
+        stress_ranges = load_range_factors * s_11
+        fatigue_damage = s_n_curve.find_miner_sum(stress_ranges)
+        local_result_field.append([fatigue_damage], element_id)
+
+
+# %%
+# Plot damage
+composite_model.get_mesh().plot(damage_result_field, text="Fatigue Damage")
+
+
+# %%
+# Identify the element with the maximum damage
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+#
+maximum_element_scoping = damage_result_field.max().scoping
+max_element_id = maximum_element_scoping[0]
+print(f"The element with highest damage is {max_element_id}.")
+print(f"The highest damage value is {damage_result_field.max().data[0]}.")