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Generative AI design for building structures
Designing building structures presents various challenges, including inefficient design
processes, limited data reuse, and the underutilization of previous design experience …
processes, limited data reuse, and the underutilization of previous design experience …
Machine-learning assisted topology optimization for architectural design with artistic flavor
A machine-learning assisted topology optimization approach is proposed for architectural
design with artistic flavor. This work establishes a novel framework to systematically …
design with artistic flavor. This work establishes a novel framework to systematically …
Machine learning powered sketch aided design via topology optimization
Structural topology optimization is an important design tool in the conceptual design phase
of a product. However, the current topology optimization design is mostly driven strictly …
of a product. However, the current topology optimization design is mostly driven strictly …
cv-PINN: Efficient learning of variational physics-informed neural network with domain decomposition
We propose a novel approach for tackling scientific problems governed by differential
equations, based on the concept of a physics-informed neural networks (PINNs). The …
equations, based on the concept of a physics-informed neural networks (PINNs). The …
A Problem-Independent Machine Learning (PIML) enhanced substructure-based approach for large-scale structural analysis and topology optimization of linear …
Structural analysis for structures composed of highly heterogeneous materials which often
involves the solution of large-scale linear algebraic equations is very time-consuming even …
involves the solution of large-scale linear algebraic equations is very time-consuming even …
[PDF][PDF] Open-source codes of topology optimization: A summary for beginners to start their research
Topology optimization (TO), a numerical technique to find the optimal material layout with a
given design domain, has attracted interest from researchers in the field of structural …
given design domain, has attracted interest from researchers in the field of structural …
High fidelity FEM based on deep learning for arbitrary composite material structure
J Li, W Yao, Y Lu, J Chen, Y Sun, X Hu - Composite Structures, 2024 - Elsevier
Due to the outstanding performance, composite materials are widely used and analyzing
their properties and designing them based on performance has become a crucial task in the …
their properties and designing them based on performance has become a crucial task in the …