(Click the video thumbnail above to watch the demonstration on YouTube!)

Source-Available Engineering Simulation & Optimization Platform

Visual Modeling · Parametric CAD · Topology Optimisation · FEA · Solution Spaces · Sensitivity Analysis · Surrogate AI · Multi-Objective Optimization

PyLCSS (Python Low-Code System Solutions) is a professional engineering design platform. It allows engineers to model complex multidisciplinary systems through a node-based visual interface, run parametric CAD and FEA simulations, explore high-dimensional Solution Spaces, and optimise designs using 7 different algorithms — all within a single desktop application.

Built for real-world engineering workflows, PyLCSS features a crash-free multi-threaded architecture, vectorised computation kernels, comprehensive file I/O, and an integrated AI coding assistant.

PyLCSS implements the Solution Space approach for robust design: instead of seeking a single optimal point (which may be sensitive to tolerances), it identifies box-shaped regions of valid designs, enabling decoupled subsystem development.

Markus Zimmermann, Johannes Edler von Hoessle, "Computing solution spaces for robust design", Int. J. Numer. Meth. Engng., 2013. DOI: 10.1002/nme.4450

• 70+ Node Types — Primitives, Booleans, Fillets, Chamfers, Sweeps, Lofts, Shells, Patterns, Imports
• Topology Optimisation — SIMP with MMA/OC solvers, density/sensitivity filtering, Heaviside projection, symmetry constraints, shape recovery with marching cubes, and direct STL/OBJ export of optimised shapes
• Advanced Nodes — Thicken, Pipe, Split, Text emboss, Math Expression evaluator, Import STEP/STL
• Real-Time 3D Viewer — VTK-based with density cutoff preview during optimisation
• Measurement — Distance, surface area, and volume nodes

• scikit-fem + Netgen meshing — Tetrahedral/triangular elements
• Linear Elasticity — Displacement, von Mises stress, compliance
• FEA Results Nodes — Stress extraction, displacement, reaction forces
• Remeshing — Surface-to-solid conversion for topology-optimised shapes (up to 20 000 faces)

• Batch analysis across all outputs, convergence study, importance ranking (Critical / Important / Minor / Negligible)

• 5 Algorithms — MLP Neural Network (PyTorch), Random Forest, Gradient Boosting, Gaussian Process, SVR
• Cross-Validation — K-Fold (2–20 folds) and Leave-One-Out
• Model Comparison — Automated comparison of all 5 algorithms on same dataset
• Feature Importance — Permutation-based and tree-based importance analysis
• Hyperparameter Optimisation — Grid search and random search with built-in search spaces

• Monte Carlo Sampling — Vectorised evaluation of thousands of design variants
• Visualisation — 2D scatter, parallel coordinates, feasibility maps
• Product Family Analysis — Common platform identification across product variants
• Step Analysis — Iterative box-size refinement

• Expression-Aware Inputs — Safe AST-based evaluation (sin, cos, sqrt, log, variables) in input fields
• Unit-Aware Inputs — Physical unit support via pint (SI, Imperial, CGS) in simulation nodes

• Natural Language Control — "Zoom in", "Create a helical gear", "Go to properties"
• Local STT — Faster-Whisper for real-time speech recognition
• Multi-Provider LLM — OpenAI, Claude, Gemini, LM-Studio
• Privacy-First — Optional fully local execution

• Python 3.8+
• OS Windows 10/11 (macOS and Linux: experimental)

# Clone
git clone <repository-url>
cd pylcss

# Virtual environment
python -m venv .venv
# Windows:
.venv\Scripts\activate
# Linux/Mac:
source .venv/bin/activate

# Dependencies
pip install -r requirements.txt

# Launch
python scripts/main.py

Or on Windows: double-click run_gui.bat.

1. Launch — python scripts/main.py
2. Load a Model — File → Open → select data/Gear Unit.json
3. Validate — Click "Validate" to check units and connections
4. Solution Space — Switch to Solution Space tab → "Compute"
5. Visualise — Plot Weight vs. Safety Factor
6. Optimise — Go to Optimisation tab → select objectives → Run

pylcss/
├── cad/                  # Parametric CAD kernel (CadQuery + OCC)
│   ├── nodes/            # 50+ node types (primitives, booleans, FEA, TopOpt)
│   ├── engine.py         # Graph execution engine
│   └── node_library.py   # Node registry
├── optimization/         # 7 solvers (SciPy, Nevergrad, NSGA-II, Multi-Start)
├── sensitivity/          # 4 methods (Sobol, Morris, FAST, Delta)
├── solution_space/       # Monte Carlo, step analysis, product families
├── surrogate_modeling/   # 5 ML algorithms + CV + HPO + feature importance
├── io_manager/           # CAD/mesh/data/project I/O (15+ formats)
├── system_modeling/      # Graph-based system model builder
├── assistant_systems/    # LLM voice assistant & tools
└── user_interface/       # PySide6 + VTK desktop application

Licensed under the PolyForm Shield License 1.0.0.

Allowed: Personal use, academic research, internal business use. Restricted: You cannot use this software to build a competing product or service.

See LICENSE for full details.