Playing with Lattice Structure Simulations

OpenMNN is a Python-based framework for lattice structure design and optimization. The project provides tools for creating, solving, and optimizing 2D lattice patterns using computational methods combined with genetic algorithms.

The framework consists of three core components:

1. Lattice Generation - Creates 2D lattice patterns including hexagonal grid structures with configurable parameters for mesh density and element sizing.

2. Structural Analysis - Implements finite element analysis using PyNite for analyzing lattice structures under load, providing efficient computation of structural responses.

3. Genetic Algorithm Optimization - Uses PyGAD to optimize elastic modulus values across lattice elements, minimizing mean squared error between target and achieved structural behavior. The optimization uses 20 generations with 8 solutions per population.

Testing demonstrates fitness improvements through genetic optimization, with the framework capable of handling various load configurations applied to lattice structures.