Modeling uncertainty of expert elicitation for use in risk-based optimization

Teter, Michael D.; Røyset, Johannes Ø.; Newman, Alexandra M.

doi:10.1007/s10479-018-3011-z

Cited by 4 publications

(1 citation statement)

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“…Vehicle performance evaluation and experimental research verified this research. Finally, this proven process was applied to the sport utility vehicle (SUV) under development, and its road noise reduction proved to be successful [4]. Teter used four different methods to estimate univariate distributions, namely, Beta and Gaussian distributions, standard Gaussian kernel estimation, and extra-exponential splines.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling and Multivariable Optimization Design of SUV Chassis Structure Based on SFE CONCEPT

Liu

Wang

2022

Security and Communication Networks

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The car chassis design concept is an important part of the car design process. Analyzing the car chassis structure in the conceptual design process is of great significance for improving the efficiency and accuracy of car chassis design. This paper takes SUV models as the research object and uses SFE CONCEPT software to realize the mathematical modeling and multivariate optimization of the SUV chassis structure. The concept of “implicit” parameterization and the concept of “CAE analysis-driven design” are adopted to quickly realize large-scale geometric transformation and consistency of interconnection, while achieving automated production and grid parameters. Through this research, it can be found that in the concept development stage of the vehicle chassis structure, the CAE performance analysis is introduced into the early development stage as soon as possible; combined with the implicit parametric design method, it can quickly and effectively realize the exploration and optimization of a larger range of structures. In addition, the SFE CONCEPT software used in this article can create parametric structural models, and combined with automatic meshing technology, it can realize continuous changes of topology variables, shape variables, size variables, and material variables, and compare the design results with the detailed design results to confirm the feasibility of the design. In addition, the experimental test shows that the success rate of SFE CONCEPT and other CAD software docking reaches 100%.

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Section: Introductionmentioning

confidence: 99%