The demand for transparent building envelopes, particularly glass facades, is rising in modern architecture. These facades are expected to meet multiple objectives, including aesthetic appeal, durability, quick installation, transparency, and both economic and ecological efficiency. At the heart of facade design, particularly for structural glass elements, lies the assurance of structural integrity for ultimate and serviceability limit states with a requisite level of reliability. However, current structural engineering assessments for glass and glass laminate designs, especially in the geometrically non-linear setting, are time-consuming and require significant expertise. This study develops a customized Mixture-of-Experts (MoE) neural network architecture to overcome current limitations. It calibrates it on synthetically generated stress and deformation data obtained via parametrized Finite-Element-Analysis (FEA) of glass and …
Strength Lab AI: A Mixture-of-Experts Deep Learning Approach for Limit State Analysis and Design of Monolithic and Laminate Structures made of Glass
Date
Authors
Michael Kraus, Rafael Bischof, Henrik Riedel, Leon Schmeiser, Alexander Pauli, Ingo Stelzer, Michael Drass
Conference / Journal
Challenging Glass Conference Proceedings