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Published in 2017 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-017-1655-y
Abstract: Multi-fidelity metamodeling provides an efficient way to approximate expensive black-box problems by utilizing the samples of multiple fidelities. While it still faces the challenge of “curse-of-dimensionality” when used in approximating high dimensional problems. On the…
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Keywords:
high dimensional;
fidelity;
dimensional problems;
multi fidelity ... See more keywords
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Published in 2019 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-019-02248-0
Abstract: 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 former. To take advantages of both HF and LF…
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Keywords:
fidelity surrogate;
basis function;
mfs rbf;
model ... See more keywords
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Published in 2020 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-020-02493-8
Abstract: Multi-fidelity surrogate (MFS) method is very promising for the optimization of complex problems. The optimization capability of MFS can be improved by infilling samples in the optimization process. Furthermore, once the gradient information is provided,…
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Keywords:
fidelity;
multi fidelity;
model;
infill sampling ... See more keywords
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Published in 2020 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-020-02575-7
Abstract: This paper presents a multi-fidelity RBF (radial basis function) surrogate-based optimization framework (MRSO) for computationally expensive multi-modal optimization problems when multi-fidelity (high-fidelity (HF) and low-fidelity (LF)) models are available. The HF model is expensive and…
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Keywords:
fidelity;
based optimization;
multi fidelity;
optimization ... See more keywords
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Published in 2020 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-020-02772-4
Abstract: Sampling efficiency is important for simulation-based design optimization. While Bayesian optimization (BO) has been successfully applied in engineering problems, the cost associated with large-scale simulations has not been fully addressed. Extending the standard BO approaches…
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Keywords:
fidelity;
bayesian optimization;
fidelity bayesian;
multi fidelity ... See more keywords
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Published in 2021 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-021-02895-2
Abstract: The multi-fidelity metamodeling method can dramatically improve the efficiency of metamodeling for computationally expensive engineering problems when multiple levels of fidelity data are available. In this paper, an efficient and novel adaptive multi-fidelity sparse polynomial…
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Keywords:
global approximation;
multi fidelity;
fidelity;
sparse polynomial ... See more keywords
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Published in 2019 at "Engineering with Computers"
DOI: 10.1007/s00366-019-00738-9
Abstract: With the significant growth of the world population, our cities are becoming more and more crowding. In this situation, any fire occurring would cause severe consequences, including property damage and human injuries or even deaths.…
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Keywords:
fidelity;
fire origin;
multi fidelity;
origin determination ... See more keywords
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Published in 2020 at "Engineering with Computers"
DOI: 10.1007/s00366-020-01084-x
Abstract: A new multi-fidelity modelling-based probabilistic optimisation framework for composite structures is presented in this paper. The multi-fidelity formulation developed herein significantly reduces the required computational time, allowing for more design variables to be considered early…
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Keywords:
fidelity;
multi fidelity;
composite structures;
reliability ... See more keywords
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Published in 2020 at "Engineering With Computers"
DOI: 10.1007/s00366-020-01203-8
Abstract: Multi-fidelity (MF) surrogate models have been widely used in engineering optimization problems to reduce the design cost by replacing computat ional expensive simulations. Ignoring the prediction uncertainty of the MF model that is caused by…
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Keywords:
engineering;
optimization;
multi fidelity;
method ... See more keywords
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Published in 2018 at "Computational Geosciences"
DOI: 10.1007/s10596-018-9770-4
Abstract: We propose a multi-fidelity system reduction technique that uses weighted graphs paired with three-dimensional discrete fracture network (DFN) modelling for efficient simulation of subsurface flow and transport in fractured media. DFN models are used to…
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Keywords:
reduction;
fidelity;
system;
dfn ... See more keywords
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Published in 2019 at "Acta Astronautica"
DOI: 10.1016/j.actaastro.2018.10.023
Abstract: Abstract To reduce computation time while limiting loss in accuracy when propagating an orbit state probability density function, this work seeks to develop an adaptive approach to multi-fidelity uncertainty propagation for applications in astrodynamics. Using…
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Keywords:
orbit;
uncertainty propagation;
multi fidelity;
fidelity ... See more keywords