Metamodeling for high dimensional design problems by multi-fidelity simulations
Sign Up to like & getrecommendations! 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… read more here.
Keywords: high dimensional; fidelity; dimensional problems; multi fidelity ... See more keywords
A radial basis function-based multi-fidelity surrogate model: exploring correlation between high-fidelity and low-fidelity models
Sign Up to like & getrecommendations! 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… read more here.
Keywords: fidelity surrogate; basis function; mfs rbf; model ... See more keywords
Adaptive infill sampling criterion for multi-fidelity gradient-enhanced kriging model
Sign Up to like & getrecommendations! 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,… read more here.
Keywords: fidelity; multi fidelity; model; infill sampling ... See more keywords
A multi-fidelity RBF surrogate-based optimization framework for computationally expensive multi-modal problems with application to capacity planning of manufacturing systems
Sign Up to like & getrecommendations! 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… read more here.
Keywords: fidelity; based optimization; multi fidelity; optimization ... See more keywords
A multi-fidelity Bayesian optimization approach based on the expected further improvement
Sign Up to like & getrecommendations! 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… read more here.
Keywords: fidelity; bayesian optimization; fidelity bayesian; multi fidelity ... See more keywords
Adaptive multi-fidelity sparse polynomial chaos-Kriging metamodeling for global approximation of aerodynamic data
Sign Up to like & getrecommendations! 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… read more here.
Keywords: global approximation; multi fidelity; fidelity; sparse polynomial ... See more keywords
A novel multi-fidelity cokriging model assisted by multiple non-hierarchical low-fidelity datasets
Sign Up to like & getrecommendations! Published in 2024 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-024-03744-8
Abstract: Multi-fidelity (MF) surrogate models for incorporating multiple non-hierarchical low-fidelity (LF) datasets, whose rank of fidelity level is unknown, have attracted much attention in engineering problems. However, most of existing approaches either need to build extra… read more here.
Keywords: multi fidelity; non hierarchical; fidelity; multiple non ... See more keywords
Vehicle suspension recommendation system: multi-fidelity neural network-based mechanism design optimization
Sign Up to like & getrecommendations! Published in 2024 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-024-03957-x
Abstract: Mechanical mechanisms are designed to perform specific functions in a variety of fields. In most cases, there is not a unique mechanism that performs a well-defined function. For example, vehicle suspensions are designed to improve… read more here.
Keywords: multi fidelity; vehicle; analysis; fidelity ... See more keywords
Multi-fidelity surrogate algorithm for fire origin determination in compartment fires
Sign Up to like & getrecommendations! 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.… read more here.
Keywords: fidelity; fire origin; multi fidelity; origin determination ... See more keywords
A novel multi-fidelity modelling-based framework for reliability-based design optimisation of composite structures
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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… read more here.
Keywords: fidelity; multi fidelity; composite structures; reliability ... See more keywords
An ensemble weighted average conservative multi-fidelity surrogate modeling method for engineering optimization
Sign Up to like & getrecommendations! 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… read more here.
Keywords: engineering; optimization; multi fidelity; method ... See more keywords