Multi-fidelity Surrogates
Modeling, Optimization and Applications
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19 Result(s)
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Jiexiang Hu
Engineering Design
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Article
A multi-objective bayesian optimization approach based on variable-fidelity multi-output metamodeling
Practical engineering problems are often involved multiple computationally expensive objectives. A promising strategy to alleviate the computational cost is the variable-fidelity metamodel-based multi-objectiv...
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Chapter
Sequential Multi-fidelity Surrogate Modeling
Under a limited computational budget, the quality of a multi-fidelity (MF) surrogate depends on the distributions of the sample points and sample size ratio between the low-fidelity (LF) and high-fidelity (HF)...
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Chapter
Multi-fidelity Surrogate Assisted Reliability Design Optimization
The structural reliability problem has received increasing attention with the increasing complexity of engineering structures. Failure probability is the main issue considered in structural reliability analyse...
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Multi-fidelity Surrogate Assisted Evolutional Optimization
Evolution algorithms, such as multi-objective genetic algorithms (MOGAs), require a large number of function evaluations to converge to global optima or near-optimal solutions (Sun et al. in IEEE Trans Cybern ...
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Book
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Chapter
Introduction
Physics-based simulation models from different disciplines are becoming indispensable in modern product design. In the preliminary design phase, these simulation models can help predict the performance of prod...
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Nonhierarchical Multi-fidelity Surrogate Modeling
The methods of constructing multi-fidelity (MF) surrogates can be divided into two categories: hierarchical and nonhierarchical methods. Several hierarchical methods have been described in Chap. 2
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Chapter
Multi-fidelity Surrogate Assisted Efficient Global Optimization
As reported in the previous literature, multi-fidelity (MF) surrogate assisted design optimization techniques can be classified into two types: offline and online techniques. In the offline technique, a prespe...
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Chapter
Multi-fidelity Surrogate Assisted Robust Design Optimization
Engineering product design optimization inevitably involves uncertainties, which may degrade the objective performance or render the optimal solution infeasible. To alleviate the sensitivity of the performance...
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Chapter
Engineering Applications
Multi-fidelity (MF) surrogates can balance the prediction accuracy and computational cost by augmenting a few expensive high-fidelity (HF) samples with many inexpensive low-fidelity (LF) data. Consequently, MF...
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Concluding Remarks
Chapter 1 introduces the concept of multi-fidelity surrogates, providing the readers with a general understanding of what such surrogates are and their expected use case...
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Hierarchical Multi-fidelity Surrogate Modeling
Most of the existing multi-fidelity (MF) surrogates assume that high-fidelity (HF) models are generally more accurate than low-fidelity (LF) models but LF models are less expensive than HF models. In other wor...
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Article
A multi-fidelity surrogate modeling method based on variance-weighted sum for the fusion of multiple non-hierarchical low-fidelity data
Multi-fidelity (MF) surrogate models have been widely adopted in simulation-based engineering design problems to reduce the computational cost by fusing data with diverse fidelity levels. Most of the MF modeli...
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Article
A conservative multi-fidelity surrogate model-based robust optimization method for simulation-based optimization
Multi-fidelity (MF) surrogate model-based robust optimization has been used to deal with engineering design and optimization problems that have uncertainty in their inputs. However, the MF surrogate model cons...
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Article
Multi-fidelity surrogate model-assisted fatigue analysis of welded joints
In this study, Kriging based multi-fidelity (MF) surrogate models are constructed to accelerate the fatigue analysis of welded joints. The influence of leg length, leg height, the width of the specimen, and lo...
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Article
A model validation framework based on parameter calibration under aleatory and epistemic uncertainty
Model validation methods have been widely used in engineering design to evaluate the accuracy and reliability of simulation models with uncertain inputs. Most of the existing validation methods for aleatory an...
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Article
Variable-fidelity probability of improvement method for efficient global optimization of expensive black-box problems
Variable-fidelity (VF) surrogate models have attracted significant attention recently in simulation-based design because they can achieve a desirable accuracy at a reasonable cost by making use of the data fro...
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Article
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 cost by augmenting the small nu...
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Article
A robust optimization approach based on multi-fidelity metamodel
Multi-fidelity (MF) metamodeling approaches have recently attracted a significant amount of attention in simulation-based design optimization due to their ability to conduct trade-offs between high accuracy an...
