Machine Learning-Enhanced Topology Optimization for Reliability-Based Structural Design

Széchenyi István Egyetem

Multidiszciplináris Műszaki Tudományi Doktori Iskola

Movahedi Rad Majid

Muayad Habashneh

építőmérnöki tudományok

This PhD research aims to pioneer the integration of machine learning (ML) into topology optimization (TO) methods for structural engineering, with a strong focus on reliability-based design under uncertainty. While existing TO approaches have achieved significant success, their performance typically relies on user-defined parameters and fixed heuristic rules. Such static configurations can restrict adaptability, slow down convergence, and reduce robustness when applied to complex engineering problems characterized by material nonlinearities, geometric imperfections, and uncertain loading conditions.

2026-08-31