State-of-the-art and comparative review of adaptive sampling methods for kriging

JN Fuhg, A Fau, U Nackenhorst - Archives of Computational Methods in …, 2021 - Springer
Metamodels aim to approximate characteristics of functions or systems from the knowledge
extracted on only a finite number of samples. In recent years kriging has emerged as a …

Data‐Driven Design for Metamaterials and Multiscale Systems: A Review

D Lee, W Chen, L Wang, YC Chan… - Advanced …, 2024 - Wiley Online Library
Metamaterials are artificial materials designed to exhibit effective material parameters that
go beyond those found in nature. Composed of unit cells with rich designability that are …

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

V Nemani, L Biggio, X Huan, Z Hu, O Fink… - … Systems and Signal …, 2023 - Elsevier
On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …

Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques

R Bostanabad, Y Zhang, X Li, T Kearney… - Progress in Materials …, 2018 - Elsevier
Building sensible processing-structure-property (PSP) links to gain fundamental insights and
understanding of materials behavior has been the focus of many works in computational …

A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design

H Liu, YS Ong, J Cai - Structural and Multidisciplinary Optimization, 2018 - Springer
Metamodeling is becoming a rather popular means to approximate the expensive
simulations in today's complex engineering design problems since accurate metamodels …

Perspectives on the integration between first-principles and data-driven modeling

W Bradley, J Kim, Z Kilwein, L Blakely… - Computers & Chemical …, 2022 - Elsevier
Efficiently embedding and/or integrating mechanistic information with data-driven models is
essential if it is desired to simultaneously take advantage of both engineering principles and …

Design of computer experiments: A review

SS Garud, IA Karimi, M Kraft - Computers & Chemical Engineering, 2017 - Elsevier
In this article, we present a detailed overview of the literature on the design of computer
experiments. We classify the existing literature broadly into two categories, viz. static and …

Special section on multidisciplinary design optimization: metamodeling in multidisciplinary design optimization: how far have we really come?

FAC Viana, TW Simpson, V Balabanov, V Toropov - AIAA journal, 2014 - arc.aiaa.org
The use of metamodeling techniques in the design and analysis of computer experiments
has progressed remarkably in the past 25 years, but how far has the field really come? This …

Review of metamodeling techniques in support of engineering design optimization

GG Wang, S Shan - … Design Engineering Technical …, 2006 - asmedigitalcollection.asme.org
Computation-intensive design problems are becoming increasingly common in
manufacturing industries. The computation burden is often caused by expensive analysis …

Kriging metamodeling in simulation: A review

JPC Kleijnen - European journal of operational research, 2009 - Elsevier
This article reviews Kriging (also called spatial correlation modeling). It presents the basic
Kriging assumptions and formulas—contrasting Kriging and classic linear regression …