A machine learning-based surrogate model for optimization of truss structures with geometrically nonlinear behavior

HT Mai, J Kang, J Lee - Finite Elements in Analysis and Design, 2021 - Elsevier
Abstract Design optimization of geometrically nonlinear structures is well known as a
computationally expensive problem by using incremental-iterative solution techniques. To …

Development of a standard calibration procedure for the DEM parameters of cohesionless bulk materials–Part II: Efficient optimization-based calibration

C Richter, T Rößler, G Kunze, A Katterfeld, F Will - Powder Technology, 2020 - Elsevier
The numerical complexity of Discrete Element Method (DEM) simulations generally forces
an idealisation of DEM models, making the calibration process the key to realistic simulation …

Understanding the effect of hyperparameter optimization on machine learning models for structure design problems

X Du, H Xu, F Zhu - Computer-Aided Design, 2021 - Elsevier
To relieve the computational cost of design evaluations using expensive finite element (FE)
simulations, surrogate models have been widely applied in computer-aided engineering …

Defect-Driven topology optimization for fatigue design of additive manufacturing structures: Application on a real industrial aerospace component

CB Niutta, A Tridello, G Barletta, N Gallo… - Engineering Failure …, 2022 - Elsevier
In this paper, a generalized formulation of defect-driven topology optimization (TO) for
fatigue design, named TopFat, is proposed, where the first principal stress, that causes the …

A boundary identification approach for the feasible space of structural optimization using a virtual sampling technique-based support vector machine

H Cao, H Li, W Sun, Y Xie, B Huang - Computers & Structures, 2023 - Elsevier
To improve the computational efficiency of structural optimization, this study treats the
feasibility evaluation of the solutions as a two-class classification problem and proposes a …

Design space exploration and optimization using self-organizing maps

SP Thole, P Ramu - Structural and Multidisciplinary Optimization, 2020 - Springer
Identifying regions of interest (RoI) in the design space is extremely useful while building
metamodels with limited computational budget. Self-organizing maps (SOM) are used as a …

Multidisciplinary design optimization for hybrid electric vehicles: component sizing and multi-fidelity frontal crashworthiness

PG Anselma, CB Niutta, L Mainini… - Structural and …, 2020 - Springer
The electrification of road vehicle powertrains has recently gained growing interest
worldwide as an effective solution to comply tightening regulations on CO2 emissions. In …

Data-driven feasibility analysis for the integration of planning and scheduling problems

LS Dias, MG Ierapetritou - Optimization and Engineering, 2019 - Springer
A framework for the integration of planning and scheduling using data-driven methodologies
is proposed. First, the constraints at the planning level related to the scheduling problem are …

Escaping unknown discontinuous regions in blackbox optimization

C Audet, A Batailly, S Kojtych - SIAM Journal on Optimization, 2022 - SIAM
The design of key nonlinear systems often requires the use of expensive blackbox
simulations presenting inherent discontinuities whose positions in the variable space cannot …

Robust design optimization for enhancing delamination resistance of composites

S Singh, L Pflug, J Mergheim… - International Journal for …, 2023 - Wiley Online Library
Recent developments in the field of computational modeling of fracture have opened up
possibilities for designing structures against failure. A special case, called interfacial fracture …