Special Issue "Uncertainty Quantification in Aerospace Engineering"
A special issue of Aerospace (ISSN 2226-4310).
Deadline for manuscript submissions: closed (31 May 2019).
Interests: non-probabilistic set theory; computational solid mechanics; aeroelastic mechanics; random vibration; structural reliability design; durability/damage tolerance design; non-linear problems in mechanics; intelligent material structure and composites mechanics
With the development of science and technology, engineers have been devoted to developing advanced aerospace vehicles and systems with more functions and higher performances. As a practical matter, real aerospace systems are inevitably confronted with multiple sources of uncertainty arising from modeling errors, material discrepancy, machining tolerance and environmental variations during the processes of design, manufacture and service. Hence, Uncertainty Quantification (UQ) is a crucial aspect in the reliability or robust design of aerospace structures and systems. However, the lack of knowledge or experimental data, the coupling between different physical fields and the expensive computational cost of high-fidelity simulation make UQ and model validation extremely challenging. A series of problems of interest are expected to be well solved, such as rational modeling of uncertain parameters based on limited experience and experimental data, compatibility and consistency between different uncertain models, importance measure of uncertain variables, estimation of uncertainty propagation in multidisciplinary systems, reliability evaluation of structures and systems with uncertainties, optimization performed in the context of uncertainty, model calibration, verification and validation, etc.
This Special Issue welcomes papers on the following topics: 1) uncertainty characterization, 2) compatibility and consistency of different uncertain models, 3) uncertainty quantification and model validation in aerospace engineering, 4) global sensitivity analysis of uncertain variables, 5) uncertainty propagation in single disciplinary/multidisciplinary systems (including perturbation method, optimization approach, surrogate model method, sampling approach, hybrid algorithm, etc.), and 6) reliability/robust analysis and optimization of aerospace structures and systems. We hope this Special Issue will keep inspiring scholars and engineers to develop more effective and efficient UQ technologies for improving the credibility and consistency of simulation-based analyses and designs in aerospace engineering.
Prof. Dr. Zhiping Qiu
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 papers will be 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. Aerospace is an international peer-reviewed open access monthly 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 1400 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.
- Uncertainty quantification
- Uncertainty propagation
- Sensitivity analysis
- Model verification and validation
- Reliability analysis and optimization
- Robust analysis and optimization
- Aerospace engineering