A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys
The design of materials and identification of optimal processing parameters constitute a
complex and challenging task, necessitating efficient utilization of available data. Bayesian …
complex and challenging task, necessitating efficient utilization of available data. Bayesian …
[LIBRO][B] Advanced reduced order methods and applications in computational fluid dynamics
Reduced order modeling is an important and fast-growing research field in computational
science and engineering, motivated by several reasons, of which we mention just a few …
science and engineering, motivated by several reasons, of which we mention just a few …
Dynamic Exploration–Exploitation Pareto Approach for high-dimensional expensive black-box optimization
Surrogate Optimization (SO) plays a vital role in optimizing performance parameters for
computationally expensive simulations. However, SO encounters significant challenges in …
computationally expensive simulations. However, SO encounters significant challenges in …
Multi-Objective Bayesian Optimization using an Active Subspace-based Approach
View Video Presentation: https://doi. org/10.2514/6.2023-2203. vid Multi-objective
optimization is often a difficult task owing to the need to balance competing objectives …
optimization is often a difficult task owing to the need to balance competing objectives …
Semi-Autonomous Problem Formulation Space Search for High Dimensional Multiobjective Optimization
View Video Presentation: https://doi. org/10.2514/6.2023-4260. vid In many design settings,
the number of quantities of interest under consideration is more than the usual two or three …
the number of quantities of interest under consideration is more than the usual two or three …