Triya.io: Open-Source Strategic LCA Platform

Triya.io is a Life Cycle Assessment (LCA) instrument designed for open-source environmental engineering. It provides a bridge between visual product design and parametric modeling aligned with ISO 14044 standards.

The application is built on a React Flow and FastAPI stack. It includes interactive IDEF0 mapping, background sparse matrix solvers, and JRC EF 3.1 impact characterization.

Key Capabilities

• ISO 14040/44 Guardrails: Goal and Scope configurations for functional units, system boundaries, cut-off thresholds, and LCIA methodologies.
• IDEF0 Canvas: Standard-compliant workflow modeling using a drag-and-drop interface. Connections manage the mapping from Inputs and Resources to Processes and Outputs or Emissions.
• Parametric Monte Carlo Engine: Support for Lognormal, Normal, and Uniform distributions on physical exchanges for probabilistic modeling via the Python backend.
• AM_Pri Integration: Graph Neural Network hooks for analyzing .stl geometries to predict material efficiency and translate geometry into energy and material lifecycles.

Installation and Setup

Python 3.10 or higher and Node 18 or higher are required.

1. Backend Configuration (FastAPI)

Navigate to the backend directory to initialize the API and mathematical engine.

cd AutoLCA/backend

# Initialize environment
python -m venv venv
venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Start the service
python main.py

The API is served at http://localhost:8000.

2. Frontend Configuration (Next.js)

Navigate to the frontend directory to initialize the user interface.

cd AutoLCA/frontend

# Install dependencies
npm install

# Start the application
npm run dev

The dashboard is accessible at http://localhost:3000.

Architecture

Triya.io/
├── AutoLCA/
│   ├── frontend/        (Next.js 14, Zustand, React Flow)
│   │   ├── components/  (Goal & Scope, Canvas Nodes, 3D Dropzones)
│   │   └── lib/         (Zustand State, Matrix Data Sync)
│   ├── backend/         (FastAPI, Pydantic Validation)
│   │   ├── core/        (LCA Solvers, Monte Carlo Engines)
│   │   └── main.py      (Root Endpoints)
├── Database_Triya/      (SQLite / LCI Datasets)
└── docker-compose.yml   (Containerized environment)

Data Synchronization

1. Frontend: Zustand manages parametric changes and goal modifications, including allocation methodologies such as mass or economic ratios.
2. Validation: A Pydantic schema ensures ISO methodology rules are maintained during data transfer.
3. Backend Engine: Interprets cutoff thresholds and computes the Life Cycle Inventory matrix using allocation algorithms.

Project Standards

• Configuration files (.env) are excluded from version control.
• Machine learning weights and local databases are ignored to maintain repository efficiency.
• All project data and LCI databases are stored locally in the AutoLCA/backend/data directory using SQLite. No external cloud connection is required for operation.

Copyright 2026 Triya.io. Released under Open Source License.