State-of-the-art and comparative review of adaptive sampling methods for kriging
Metamodels aim to approximate characteristics of functions or systems from the knowledge
extracted on only a finite number of samples. In recent years kriging has emerged as a …
extracted on only a finite number of samples. In recent years kriging has emerged as a …
Recent advances in surrogate modeling methods for uncertainty quantification and propagation
C Wang, X Qiang, M Xu, T Wu - Symmetry, 2022 - mdpi.com
Surrogate-model-assisted uncertainty treatment practices have been the subject of
increasing attention and investigations in recent decades for many symmetrical engineering …
increasing attention and investigations in recent decades for many symmetrical engineering …
Design a J-type air-based battery thermal management system through surrogate-based optimization
Battery thermal management system is of great importance to the performance and safety of
electric vehicles. The conventional U-and Z-type air-based structures may fail to meet the …
electric vehicles. The conventional U-and Z-type air-based structures may fail to meet the …
Multidisciplinary design optimization of dynamic positioning system for semi-submersible platform
Y Yuan, Q Shen, W Xi, S Wang, J Ren, J Yu, Q Yang - Ocean Engineering, 2023 - Elsevier
The dynamic positioning system (DPS) is a complex mechatronic system consisting of
multiple sub-disciplines. For such highly coupled sub-disciplines and sub-systems within the …
multiple sub-disciplines. For such highly coupled sub-disciplines and sub-systems within the …
A suite of metrics for assessing the performance of solar power forecasting
Forecasting solar energy generation is a challenging task because of the variety of solar
power systems and weather regimes encountered. Inaccurate forecasts can result in …
power systems and weather regimes encountered. Inaccurate forecasts can result in …
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 …
Robust design optimization (RDO) of thermoelectric generator system using non-dominated sorting genetic algorithm II (NSGA-II)
The thermoelectric generator (TEG) is a promising technology for the exhaust heat recovery
of automobiles and TEG optimization has been widely studied. However, previous TEG …
of automobiles and TEG optimization has been widely studied. However, previous TEG …
Airfoil Shape Optimisation Using a Multi-Fidelity Surrogate-Assisted Metaheuristic with a New Multi-Objective Infill Sampling Technique.
This work presents multi-fidelity multi-objective infill-sampling surrogate-assisted
optimization for airfoil shape optimization. The optimization problem is posed to maximize …
optimization for airfoil shape optimization. The optimization problem is posed to maximize …
A data-driven modelling and optimization framework for variable-thickness integrally stiffened shells
The integrally stiffened shells possess the advantages of high specific strength, high specific
rigidity and excellent sealing performance, which have been widely used in the load …
rigidity and excellent sealing performance, which have been widely used in the load …
Smart sampling algorithm for surrogate model development
Surrogate modelling aims to reduce computational costs by avoiding the solution of rigorous
models for complex physicochemical systems. However, it requires extensive sampling to …
models for complex physicochemical systems. However, it requires extensive sampling to …