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Applied Sciences
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Novel Methods for Structural Analysis and Optimization under Multi-Source Uncertainties
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Novel Methods for Structural Analysis and Optimization under Multi-Source Uncertainties

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 5144

Special Issue Editor

Dr. Lei Wang

E-Mail Website
Guest Editor
Institute of Solid Mechanics, School of Aeronautic Science and Engineering, Beihang University, Beijing 100083, China
Interests: computational solid mechanics; aircraft structural dynamics; structural reliability; structural topology optimization; dynamic load identification for aircraft structures; structural damage identification and health monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, alongside the growing complexity of engineering structures and the severity of the service environments, uncertainties related to material properties, external loads, boundary conditions, measurement noises, etc., have extensively increased. Uncertainty greatly influences structural safety and applicability, which nevertheless is challenging and expensive to investigate experimentally. Besides, practical cases of complicated computing modeling and limited sample information may also lead to unsatisfactory results in theoretical and validation research. It is therefore necessary to develop advanced methodology and strategy to completely recognize the uncertainties involved when tackling with structural analysis and design optimization issues.

The purpose of this Special Issue is to report and discuss recent progress in various aspects of uncertainty-oriented theoretical modeling, numerical methods, and engineering applications in different specific areas, such as aeronautics and astronautics, and mechanical and civil engineering. Original research and review articles on all relative aspects are welcome. 

Dr. Lei Wang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • new theories of uncertainty quantification and propagation
  • robust/reliable assessment for practical engineering problems
  • uncertainty-based design optimization policies
  • inverse problems in mechanics with multisource uncertainties
  • robust/reliable control in engineering vibratory systems
  • model verification and validation under uncertainty issues
  • reliability test and inverse optimization schemes
  • software or algorithm programming of uncertainty-based methods

Published Papers (3 papers)

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Research

14 pages, 7882 KiB  
Article
Analysis of Temperature and Thermal Stress for a Solar Power Tower Molten Salt Receiver under Multi-Source Uncertainties
by Yan Luo, Gen Li, Zhiyuan Wang and Tao Lu
Appl. Sci. 2022, 12(21), 10740; https://doi.org/10.3390/app122110740 - 23 Oct 2022
Cited by 2 | Viewed by 1457
Abstract
Although uncertainties such as solar radiation and material properties are generally involved in the solar receiver design process, current studies in the solar receiver field are based on deterministic models and do not incorporate these uncertainties into the design process. In this paper, [...] Read more.
Although uncertainties such as solar radiation and material properties are generally involved in the solar receiver design process, current studies in the solar receiver field are based on deterministic models and do not incorporate these uncertainties into the design process. In this paper, based on a coupled deterministic thermal–structural model and an uncertainty analysis model, an analysis of temperature and thermal stress was conducted for a solar power tower (SPT) molten salt receiver under multi-source uncertainties to investigate the dispersions of responses. The results demonstrated that the maximum temperature inside the tube wall under multi-source uncertainties ranged from 847 K to 895 K, with an expectation of 871 K and a standard deviation of 8 K, and the maximum thermal stress ranged from 173 MPa to 245 MPa, with an expectation of 204 MPa and a standard deviation of 12 MPa, both of which had severer probabilities than the deterministic results (871 K and 204 MPa) and may cause failure in the receiver. Furthermore, the results of the global sensitivity analysis indicated that the peak incident solar flux was the most sensitive, and the specific heat of the tube material was the least sensitive to the maximum temperature and thermal stress of the tube wall. These results are beneficial to provide additional reliability and confidence in the temperature and thermal stress evaluation process of solar receiver tubes. Full article
(This article belongs to the Special Issue Novel Methods for Structural Analysis and Optimization under Multi-Source Uncertainties)
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19 pages, 6081 KiB  
Article
Uncertainty-Based Comprehensive Optimization Design for the Thermal Protection System of Hypersonic Wing Structure
by Ruixing Wang and Yan Luo
Appl. Sci. 2022, 12(21), 10734; https://doi.org/10.3390/app122110734 - 23 Oct 2022
Cited by 2 | Viewed by 1377
Abstract
Due to the inherent uncertainties in material properties, loads, geometric dimensions, et al., the uncertainty-based optimization design method has become increasingly important for the design of the thermal protection system (TPS) by carefully considering the influences of uncertainties. In this study, an uncertainty-based [...] Read more.
Due to the inherent uncertainties in material properties, loads, geometric dimensions, et al., the uncertainty-based optimization design method has become increasingly important for the design of the thermal protection system (TPS) by carefully considering the influences of uncertainties. In this study, an uncertainty-based comprehensive optimization design method, which sequentially performs the robust design of aerodynamic shape and structure size for the TPS of a hypersonic wing is proposed, on the presence of uncertain-but-bounded parameters. The robust design of the TPS’s aerodynamic shape is firstly carried out. The results show that the proposed method decreases the fluctuation of the lift-to-drag ratio by 5.7%, with a small increase of heat flux on the stagnation point by only 0.13% when compared with the conventional deterministic optimization method. After that, based on the optimized aerodynamic shape and heating loads, the robust design of the multilayer TPS tile is conducted. The results show that the mass of the TPS tile efficiently deceased from 2.713 kg to 2.445 kg by 9.89%, and the robustness of the optimized design is better than the initial design. Finally, the effectiveness of the proposed optimization method is validated by the heat insulting experiment of the typical multilayer TPS tiles. Full article
(This article belongs to the Special Issue Novel Methods for Structural Analysis and Optimization under Multi-Source Uncertainties)
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25 pages, 13307 KiB  
Article
Dynamic Uncertainty Quantification and Risk Prediction Based on the Grey Mathematics and Outcrossing Theory
by Lei Wang and Jiaxiang Liu
Appl. Sci. 2022, 12(11), 5389; https://doi.org/10.3390/app12115389 - 26 May 2022
Cited by 2 | Viewed by 1422
Abstract
Embarked from the practical conditions of small samples in time-invariant and time-variant uncertainties, a complete non-probabilistic analysis procedure containing uncertainty quantification, uncertainty propagation, and reliability evaluation is presented in this paper. Firstly, the Grey systematic approach is proposed to determine the boundary laws [...] Read more.
Embarked from the practical conditions of small samples in time-invariant and time-variant uncertainties, a complete non-probabilistic analysis procedure containing uncertainty quantification, uncertainty propagation, and reliability evaluation is presented in this paper. Firstly, the Grey systematic approach is proposed to determine the boundary laws of static intervals and dynamic interval processes. Through a combination of the policies of the second-order Taylor expansion and the smallest parametric interval set, the structural response histories via quantitative uncertainty results are further confirmed. Additionally, according to the first-passage idea from classical random process theory, the study on the time-dependent reliability measurement on the basis of the interval process model is carried out to achieve a more elaborate estimation for structural safety during its whole life cycle. A numerical example and one experimental application are eventually discussed for demonstration of the usage and reasonability of the methodology developed. Full article
(This article belongs to the Special Issue Novel Methods for Structural Analysis and Optimization under Multi-Source Uncertainties)
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