A radial-basis function mesh morphing and Bayesian optimization framework for vehicle crashworthiness design-Reference-Cited by-同舟云学术

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A radial-basis function mesh morphing and Bayesian optimization framework for vehicle crashworthiness design

Published:2023-03 Issue:3 Volume:66 Page:
ISSN:1615-147X
Container-title:Structural and Multidisciplinary Optimization
language:en
Short-container-title:Struct Multidisc Optim

Author:

Du Xianping^ORCID,Liang Jinbin,Lei Jianyin,Xu Jun,Xie Peng

Funder

Fundamental Research Funds for the Central Universities

Guangzhou Municipal Science and Technology Project

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,Computer Graphics and Computer-Aided Design,Computer Science Applications,Control and Systems Engineering,Software

Link

https://link.springer.com/content/pdf/10.1007/s00158-023-03496-x.pdf

Reference35 articles.

1. Biancolini ME, Chiappa A, Cella U, Costa E, Groth C, Porziani S (2020) Radial basis functions mesh morphing: A comparison between the bi-harmonic spline and the wendland c2 radial function. In: Computational Science–ICCS 2020: 20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part VI 20. Springer International Publishing, pp 294–308

2. Bletzinger KU (2014) A consistent frame for sensitivity filtering and the vertex assigned morphing of optimal shape. Struct Multidisc Optim 49 (6):873–895

3. Brujic D, Ristic M, Mattone M, Maggiore P, De Pol GP (2009) CAD based shape optimization for gas turbine component design. Struct Multidisc Optim 41(4):647–659

4. Carr JC, Fright WR, Beatson RK (1997) Surface interpolation with radial basis functions for medical imaging. IEEE Trans Med Imaging 16 (1):96–107

5. Deb K et al (2000) A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: International conference on parallel problem solving from nature. Springer, Berlin

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