Digital twin-based structural health monitoring by combining measurement and computational data: An aircraft wing example
Digital twin is a concept that utilizes digital technologies to mirror the real-time states of
physical assets and extract the hidden yet valuable information of physical assets for …
physical assets and extract the hidden yet valuable information of physical assets for …
Review of multi-fidelity models
MG Fernández-Godino - arxiv preprint arxiv:1609.07196, 2016 - arxiv.org
Multi-fidelity models provide a framework for integrating computational models of varying
complexity, allowing for accurate predictions while optimizing computational resources …
complexity, allowing for accurate predictions while optimizing computational resources …
Issues in deciding whether to use multifidelity surrogates
Multifidelity surrogates are essential in cases where it is not affordable to have more than a
few high-fidelity samples, but it is affordable to have as many low-fidelity samples as …
few high-fidelity samples, but it is affordable to have as many low-fidelity samples as …
Application of deep learning based multi-fidelity surrogate model to robust aerodynamic design optimization
J Tao, G Sun - Aerospace Science and Technology, 2019 - Elsevier
In the present work, a multi-fidelity surrogate-based optimization framework is proposed, and
then applied to the robust optimizations for airfoil and wing under uncertainty of Mach …
then applied to the robust optimizations for airfoil and wing under uncertainty of Mach …
A multi-fidelity surrogate model based on extreme support vector regression: Fusing different fidelity data for engineering design
Purpose Extreme support vector regression (ESVR) has been widely used in the design,
analysis and optimization of engineering systems of its fast training speed and good …
analysis and optimization of engineering systems of its fast training speed and good …
A radial basis function-based multi-fidelity surrogate model: exploring correlation between high-fidelity and low-fidelity models
In computational simulation, a high-fidelity (HF) model is generally more accurate than a low-
fidelity (LF) model, while the latter is generally more computationally efficient than the …
fidelity (LF) model, while the latter is generally more computationally efficient than the …
A multi-fidelity surrogate model based on support vector regression
Computational simulations with different fidelities have been widely used in engineering
design and optimization. A high-fidelity (HF) model is generally more accurate but also more …
design and optimization. A high-fidelity (HF) model is generally more accurate but also more …
Building a lightweight digital twin of a crane boom for structural safety monitoring based on a multifidelity surrogate model
Undetected fatigue and overload damages at the key locations of the crane boom are
among the biggest threats in construction, leading to structural failure. Thus, the structural …
among the biggest threats in construction, leading to structural failure. Thus, the structural …
Multi-fidelity Bayesian optimization in engineering design
Resided at the intersection of multi-fidelity optimization (MFO) and Bayesian optimization
(BO), MF BO has found a niche in solving expensive engineering design optimization …
(BO), MF BO has found a niche in solving expensive engineering design optimization …
A generalized hierarchical co-Kriging model for multi-fidelity data fusion
Multi-fidelity (MF) surrogate models have shown great potential in simulation-based design
since they can make a trade-off between high prediction accuracy and low computational …
since they can make a trade-off between high prediction accuracy and low computational …