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 …
represent the solutions (or at least approximations) to partial differential equations that are …
Advances in bayesian probabilistic modeling for industrial applications
Industrial applications frequently pose a notorious challenge for state-of-the-art methods in
the contexts of optimization, designing experiments and modeling unknown physical …
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 …
miniaturization of hydraulic power unit in quadruped robot. In this work, a rectangular …
Industrial applications of intelligent adaptive sampling methods for multi-objective optimization
Multi-objective optimization is an essential component of nearly all engineering design.
However, for industrial applications, the design process typically demands running …
However, for industrial applications, the design process typically demands running …
Data-Driven Optimization of Carbon Electrodes for Aqueous Supercapacitors
Doping carbon electrodes with heteroatoms such as nitrogen and oxygen proves effective in
improving the performance of aqueous supercapacitors. However, the optimal conditions of …
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 …
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 …
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 …
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 …
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 …
(ML) is exploding, and a large variety of complex algorithms are being developed. One …