A survey of Bayesian calibration and physics-informed neural networks in scientific modeling

FAC Viana, AK Subramaniyan - Archives of Computational Methods in …, 2021 - Springer
Computer simulations are used to model of complex physical systems. Often, these models
represent the solutions (or at least approximations) to partial differential equations that are …

Advances in bayesian probabilistic modeling for industrial applications

S Ghosh, P Pandita, S Atkinson… - … -ASME Journal of …, 2020 - asmedigitalcollection.asme.org
Industrial applications frequently pose a notorious challenge for state-of-the-art methods in
the contexts of optimization, designing experiments and modeling unknown physical …

[HTML][HTML] Weight and performance optimization of rectangular staggered fins heat exchangers for miniaturized hydraulic power units using genetic algorithm

Y Zhang, J Peng, R Yang, L Yuan, S Li - Case Studies in Thermal …, 2021 - Elsevier
The compact, lightweight, and energy-efficient heat exchanger is significant for the
miniaturization of hydraulic power unit in quadruped robot. In this work, a rectangular …

Industrial applications of intelligent adaptive sampling methods for multi-objective optimization

J Kristensen, W Subber, Y Zhang… - Design and …, 2019 - books.google.com
Multi-objective optimization is an essential component of nearly all engineering design.
However, for industrial applications, the design process typically demands running …

Data-Driven Optimization of Carbon Electrodes for Aqueous Supercapacitors

R Pan, M Gu, J Wu - Journal of Chemical & Engineering Data, 2024 - ACS Publications
Doping carbon electrodes with heteroatoms such as nitrogen and oxygen proves effective in
improving the performance of aqueous supercapacitors. However, the optimal conditions of …

Assessing the sources of uncertainty in supply chain management

M Vinogradova, R Rogulin, M Ermakova… - Strategic …, 2021 - Wiley Online Library
Supply chains are prone to unpredictable events that negatively impact their ability to
function effectively. The study shows that worldwide rankings may be used to determine the …

Gaussian Processes enabled model calibration in the context of deep geological disposal

L Paul, JH Urrea-Quintero, U Fiaz, A Hussein… - arXiv preprint arXiv …, 2024 - arxiv.org
This work introduces a surrogate modeling approach for an emplacement drift of a deep
geological repository based on Gaussian Processes (GPs). The surrogate model is used as …

Intelligent product-gene acquisition method based on K-means clustering and mutual information-based feature selection algorithm

P Li, Y Ren, Y Yan, G Wang - AI EDAM, 2019 - cambridge.org
Conceptual design is a key stage of product design and has received increasing attention in
recent years. However, this stage is characterized by limited information, large uncertainty …

Sensitivity analysis and its role in expert judgment

B Handoko - 2022 - etheses.whiterose.ac.uk
Sensitivity analysis has become an essential tool for assessing the importance of inputs in
mathematical models or computer models. The models could be simple or complex and …

An application of Gaussian processes for analysis in chemical engineering

A Yeardley - 2023 - etheses.whiterose.ac.uk
Industry 4.0 is transforming the chemical engineering industry. With it, machine learning
(ML) is exploding, and a large variety of complex algorithms are being developed. One …