28 citations · 44 across the 11 of their papers we have counts for
5 papers · 1 filter
Multi-objective Bayesian Optimisation of Spinodoid Cellular Structures for Crush Energy Absorption
Hirak Kansara, Siamak F. Khosroshahi, Leo Guo +2
In the pursuit of designing safer and more efficient energy-absorbing structures, engineers must tackle the challenge of improving crush performance while balancing multiple confli…
Consistent machine learning for topology optimization with microstructure-dependent neural network material models
Harikrishnan Vijayakumaran, Jonathan B. Russ, Glaucio H. Paulino +1
Additive manufacturing methods together with topology optimization have enabled the creation of multiscale structures with controlled spatially-varying material microstructure. How…
Neural topology optimization: the good, the bad, and the ugly
Suryanarayanan Manoj Sanu, Alejandro M. Aragon, Miguel A. Bessa
Neural networks (NNs) hold great promise for advancing inverse design via topology optimization (TO), yet misconceptions about their application persist. This article focuses on ne…
Practical multi-fidelity machine learning: fusion of deterministic and Bayesian models
Jiaxiang Yi, Ji Cheng, Miguel A. Bessa
Multi-fidelity machine learning methods address the accuracy-efficiency trade-off by integrating scarce, resource-intensive high-fidelity data with abundant but less accurate low-f…
Gradient-free neural topology optimization: Towards effective fracture-resistant designs
Gawel Kus, Miguel A. Bessa
Gradient-free optimizers allow for tackling problems regardless of the smoothness or differentiability of their objective function, but they require many more iterations to converg…