Multidisciplinary design optimization of engineering systems under uncertainty: a review

D Meng, S Yang, C He, H Wang, Z Lv… - International Journal of …, 2022 - emerald.com
Purpose As an advanced calculation methodology, reliability-based multidisciplinary design
optimization (RBMDO) has been widely acknowledged for the design problems of modern …

Modeling, analysis, and optimization under uncertainties: a review

E Acar, G Bayrak, Y Jung, I Lee, P Ramu… - Structural and …, 2021 - Springer
Abstract Design optimization of structural and multidisciplinary systems under uncertainty
has been an active area of research due to its evident advantages over deterministic design …

A novel Kriging-model-assisted reliability-based multidisciplinary design optimization strategy and its application in the offshore wind turbine tower

D Meng, S Yang, AMP de Jesus, SP Zhu - Renewable Energy, 2023 - Elsevier
Abstract In Reliability-based Multidisciplinary Design Optimization (RBMDO), the key
performance functions of wind turbine are usually implicit, which means the performance …

Application of state-of-the-art multiobjective metaheuristic algorithms in reliability-based design optimization: a comparative study

Z Meng, BS Yıldız, G Li, C Zhong, S Mirjalili… - Structural and …, 2023 - Springer
Multiobjective reliability-based design optimization (RBDO) is a research area, which has
not been investigated in the literatures comparing with single-objective RBDO. This work …

Uncertainty quantification and management in additive manufacturing: current status, needs, and opportunities

Z Hu, S Mahadevan - The International Journal of Advanced …, 2017 - Springer
One of the major barriers that hinder the realization of significant potential of metal-based
additive manufacturing (AM) techniques is the variation in the quality of the manufactured …

Surrogate model uncertainty quantification for reliability-based design optimization

M Li, Z Wang - Reliability Engineering & System Safety, 2019 - Elsevier
Surrogate models have been widely employed as approximations of expensive physics-
based simulations to alleviate the computational burden in reliability-based design …

Optimization of fused filament fabrication process parameters under uncertainty to maximize part geometry accuracy

P Nath, JD Olson, S Mahadevan, YTT Lee - Additive manufacturing, 2020 - Elsevier
This work presents a novel process design optimization framework for additive
manufacturing (AM) by integrating physics-informed computational simulation models with …

An uncertainty-based design optimization strategy with random and interval variables for multidisciplinary engineering systems

D Meng, T **e, P Wu, C He, Z Hu, Z Lv - Structures, 2021 - Elsevier
Generally, the traditional uncertainty-based multidisciplinary design optimization (UBMDO)
methods are based on the probability distribution information of random design variables …

Uncertainty quantification for additive manufacturing process improvement: Recent advances

S Mahadevan, P Nath, Z Hu - … -ASME Journal of …, 2022 - asmedigitalcollection.asme.org
This paper reviews the state of the art in applying uncertainty quantification (UQ) methods to
additive manufacturing (AM). Physics-based as well as data-driven models are increasingly …

Probabilistic digital twin for additive manufacturing process design and control

P Nath, S Mahadevan - Journal of Mechanical …, 2022 - asmedigitalcollection.asme.org
This paper proposes a detailed methodology for constructing an additive manufacturing
(AM) digital twin for the laser powder bed fusion (LPBF) process. An important aspect of the …