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Aerospace
Special Issues
Aerodynamic and Multidisciplinary Design Optimization
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Aerodynamic and Multidisciplinary Design Optimization

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Aeronautics".

Deadline for manuscript submissions: 20 September 2024 | Viewed by 5092

Special Issue Editors

Dr. Zhonghua Han

E-Mail Website
Guest Editor
Professor, National Key Lab. of Science and Technology on Aerodynamic Design and Research, School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China
Interests: surrogate modeling and efficient global optimization algorithm; aerodynamic and multidisciplinary design optimization of aircraft; multi-fidelity data fusion and aerodynamic modeling; sonic-boom prediction and low-boom design for supersonic aircraft; aerodynamic design optimization of wide-speed-range aircraft configuration; transition prediction and natural-laminar-flow airfoil/wing design
Dr. Jiangtao Huang

E-Mail Website
Guest Editor
Researcher, China Aerodynamics Research and Development Center, Mianyang 621000, China
Interests: aerodynamic design and multidisciplinary optimization of aircraft; flight dynamics and control

Special Issue Information

Dear Colleagues,

The aerodynamic shape optimization and multidisciplinary design optimization methods have received increasing attention in the area of aerospace engineering. They can improve the aerodynamic and overall performance of an aircraft or spacecraft and significantly improve the design efficiency when compared with the traditional “cut and try” method. However, they still suffer from the difficulties and challenges associated with (a) the design of complex configuration parameterized with many design variables, (b）expensive numerical simulations and sensitivity analysis of coupled disciplines, (c) complicated engineering constraints, (d) multiple objectives and multiple design points, and (e) uncertainties relevant to flight conditions and manufacture error, etc. This Special Issue aims to provide an overview of recent advances in the aerodynamic shape optimization and multidisciplinary design optimization of aircraft or spacecraft. Authors are invited to submit full-length research articles or review manuscripts addressing (but not limited to) the following topics:

  • Geometric parameterization and mesh-deformation method
  • Design-oriented multidisciplinary numerical simulations 
  • Innovation and application of efficient global optimization algorithm
  • Innovation and application of single-discipline or coupled adjoint method 
  • Machine learning in aerodynamic and multidisciplinary design optimization
  • Design application of new-concept airfoil/wing/aircraft configurations
  • Low-boom design of supersonic aircraft.

Dr. Zhonghua Han
Dr. Jiangtao Huang
Guest Editors

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. 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 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

  • aerodynamic shape optimization
  • multidisciplinary design optimization
  • coupled adjoint method
  • new-concept aircraft
  • machine learning

Published Papers (3 papers)

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Research

32 pages, 7213 KiB  
Article
Extended Hierarchical Kriging Method for Aerodynamic Model Generation Incorporating Multiple Low-Fidelity Datasets
by Vinh Pham, Maxim Tyan, Tuan Anh Nguyen and Jae-Woo Lee
Aerospace 2024, 11(1), 6; https://doi.org/10.3390/aerospace11010006 - 20 Dec 2023
Cited by 1 | Viewed by 1002
Abstract
Multi-fidelity surrogate modeling (MFSM) methods are gaining recognition for their effectiveness in addressing simulation-based design challenges. Prior approaches have typically relied on recursive techniques, combining a limited number of high-fidelity (HF) samples with multiple low-fidelity (LF) datasets structured in hierarchical levels to generate [...] Read more.
Multi-fidelity surrogate modeling (MFSM) methods are gaining recognition for their effectiveness in addressing simulation-based design challenges. Prior approaches have typically relied on recursive techniques, combining a limited number of high-fidelity (HF) samples with multiple low-fidelity (LF) datasets structured in hierarchical levels to generate a precise HF approximation model. However, challenges arise when dealing with non-level LF datasets, where the fidelity levels of LF models are indistinguishable across the design space. In such cases, conventional methods employing recursive frameworks may lead to inefficient LF dataset utilization and substantial computational costs. To address these challenges, this work proposes the extended hierarchical Kriging (EHK) method, designed to simultaneously incorporate multiple non-level LF datasets for improved HF model construction, regardless of minor differences in fidelity levels. This method leverages a unique Bayesian-based MFSM framework, simultaneously combining non-level LF models using scaling factors to construct a global trend model. During model processing, unknown scaling factors are implicitly estimated through hyperparameter optimization, resulting in minimal computational costs during model processing, regardless of the number of LF datasets integrated, while maintaining the necessary accuracy in the resulting HF model. The advantages of the proposed EHK method are validated against state-of-the-art MFSM methods through various analytical examples and an engineering case study involving the construction of an aerodynamic database for the KP-2 eVTOL aircraft under various flying conditions. The results demonstrated the superiority of the proposed method in terms of computational cost and accuracy when generating aerodynamic models from the given multi-fidelity datasets. Full article
(This article belongs to the Special Issue Aerodynamic and Multidisciplinary Design Optimization)
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18 pages, 7192 KiB  
Article
Efficient Global Aerodynamic Shape Optimization of a Full Aircraft Configuration Considering Trimming
by Kai Wang, Zhonghua Han, Keshi Zhang and Wenping Song
Aerospace 2023, 10(8), 734; https://doi.org/10.3390/aerospace10080734 - 21 Aug 2023
Cited by 1 | Viewed by 1288
Abstract
Most existing aerodynamic shape optimization (ASO) studies do not take the balanced pitching moment into account and thus the optimized configuration has to be trimmed to ensure zero pitching moment, which causes additional drag and reduces the benefit of ASO remarkably. This article [...] Read more.
Most existing aerodynamic shape optimization (ASO) studies do not take the balanced pitching moment into account and thus the optimized configuration has to be trimmed to ensure zero pitching moment, which causes additional drag and reduces the benefit of ASO remarkably. This article proposes an efficient global ASO method that directly enforces a zero pitching moment constraint. A free-form deformation (FFD) parameterization combing Laplacian smoothing method is implemented to parameterize a full aircraft configuration and ensure sufficiently smooth aerodynamic shapes. Reynolds-averaged Navier–Stokes (RANS) equations are solved to simulate transonic viscous flows. A surrogate-based multi-round optimization strategy is used to drive ASO towards the global optimum. To verify the effectiveness of the proposed method, we adopt two design optimization strategies for the NASA Common Research Model (CRM) wing–body–tail configuration. The first strategy is to optimize the configuration without considering balance of pitching moment, and then manually trim the optimized configuration by deflecting the horizontal tail. The second one is to directly enforce the zero pitching moment constraint in the optimization model and take the deflection angle of the horizontal tail as an additional design variable. Results show that: (1) for the first strategy, about 4-count drag-reducing benefits would be lost when manually trimming the optimal configuration; (2) the second strategy can achieve 3.2-count more drag-reducing benefits than the first strategy; (3) compared with gradient-based optimization (GBO), surrogate-based optimization (SBO) is more efficient than GBO for ASO problems with around 80 design variables, and the benefit of ASO achieved by SBO is comparable to that obtained by GBO. Full article
(This article belongs to the Special Issue Aerodynamic and Multidisciplinary Design Optimization)
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28 pages, 4735 KiB  
Article
Aero-Engine Preliminary Design Optimization and Operability Studies Supported by a Compressor Mean-Line Design Module
by Alexios Alexiou, Ioannis Kolias, Nikolaos Aretakis and Konstantinos Mathioudakis
Aerospace 2023, 10(8), 726; https://doi.org/10.3390/aerospace10080726 - 20 Aug 2023
Viewed by 1841
Abstract
An approach for preliminary aero-engine design, incorporating a mean-line code for the design of axial-flow, multi-stage compressors, is presented. The compressor mean-line code is developed and integrated within a framework for the preliminary design and assessment of aero-engine concepts. It is then combined [...] Read more.
An approach for preliminary aero-engine design, incorporating a mean-line code for the design of axial-flow, multi-stage compressors, is presented. The compressor mean-line code is developed and integrated within a framework for the preliminary design and assessment of aero-engine concepts. It is then combined with modules for compressor map generation, multi-point engine design, steady-state and transient engine off-design performance and aircraft mission analysis. Implementation examples are presented, demonstrating the determination of the optimal combination of compressor and engine design parameters for achieving minimum fuel burn over a specific aircraft mission, while obeying constraints that guarantee operability over the entire flight envelope. Constraints related to compressor stability during transient maneuvers between idle and static take-off conditions and engine temperature limits at maximum take-off are respected by the final design. The results demonstrate the potential for design trade-offs between engine performance at the aircraft mission level and compressor aerodynamic stability. Full article
(This article belongs to the Special Issue Aerodynamic and Multidisciplinary Design Optimization)
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