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Aerospace
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Multiscale Modelling in Aerospace Engineering
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Multiscale Modelling in Aerospace Engineering

A special issue of Aerospace (ISSN 2226-4310).

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 3909

Special Issue Editor

Dr. Gasser Abdelal

E-Mail Website
Guest Editor
School of Mechanical and Aerospace Engineering, Queen's University Belfast, Ashby Building, Stranmillis Road, Belfast BT9 5AH, UK
Interests: multiscale material modelling; simulation of manufacturing process using finite-element and multi-scale material constitutive modeling to optimize the process and to improve the product performance; composite materials design and manufacturing; aerospace thermal structures; surrogate models of nonlinear computational simulations

Special Issue Information

Dear Colleagues,

The state-of-the-art aerospace research studies biomaterials for aerospace applications, nanomaterials, and the use of plasma to improve material performance. The aerospace design depends on developing numerical methods that provide insight into the performance of materials, fluids, and fluid–structure interactions under standard and extreme load environments. This requires numerical modelling on atomic, molecular, meso, micro, and macro levels to capture the material performance and design optimization studies to study the impact of each scale under different load environments.

This Special Issue will cover multidisciplinary tools, including quantum mechanical methods, molecular dynamics, Monte Carlo simulations, coarse-grained simulations, dissipative particle dynamics, lattice Boltzmann, computational fluid dynamics, finite element, mathematical theory, and novel numerical methods to bridge material characterization between multiple scales. We expect the authors will use material characterization techniques (gas adsorption, microscopy, etc.) and a wide range of process analytics tools (tomography, rheometry, particle sizing, etc.) to validate their numerical studies.

Multiscale modelling often fails to efficiently combine large datasets from different sources and different levels of resolution. The journal acknowledges the emergence of machine learning in multiscale modelling to manage ill-posed problems and explore massive design spaces. The journal invites researchers to publish their studies using machine learning in multiscale modelling.

Dr. Gasser Abdelal
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. 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

  • multiscale modelling
  • biocomposites
  • nanomaterials
  • machine learning
  • finite element
  • molecular dynamics
  • Monte Carlo methods
  • experimental studies

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

27 pages, 8405 KiB  
Article
Fuzzy Control for Aircraft Engine: Dynamics Clustering Modeling, Compensation and Hardware-in-Loop Experimental Verification
by Muxuan Pan, Hao Wang, Chenchen Zhang and Yun Xu
Aerospace 2024, 11(8), 610; https://doi.org/10.3390/aerospace11080610 - 25 Jul 2024
Cited by 2 | Viewed by 767
Abstract
This paper presents an integrated framework for aircraft engines, which consists of three phases: modeling, control, and experimental testing. The engine is formulated as an uncertain T–S fuzzy model. By a hierarchical dynamical parameter clustering, the number and premise variables of fuzzy rules [...] Read more.
This paper presents an integrated framework for aircraft engines, which consists of three phases: modeling, control, and experimental testing. The engine is formulated as an uncertain T–S fuzzy model. By a hierarchical dynamical parameter clustering, the number and premise variables of fuzzy rules are optimized, which keeps the engine’s prime and representative dynamics. For each fuzzy rule, a global stability-guaranteed method is developed for the identification of the consequent uncertain dynamic model. The resulting stable T–S fuzzy model accurately approximates the actual engine dynamics in the operation space. Based on this fuzzy model, a new robust control is constructed with hierarchical compensators. The control parameters take advantage of the fuzzy blend of engine prime dynamics and uncertainty thresholds. Extensive hardware-in-loop (HIL) experimental tests in the flight envelope and a flight task cycle demonstrate the effectiveness and real-time performance of the proposed control. The settling times and overshoots of engine response are suppressed to be under 2.5 s and 10%, respectively. Full article
(This article belongs to the Special Issue Multiscale Modelling in Aerospace Engineering)
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25 pages, 10057 KiB  
Article
A Multisubstructure-Based Method for the Assessment of Displacement and Stress in a Fluid–Structure Interaction Framework
by Changchuan Xie, Kunhui Huang, Yang Meng, Nongyue Gao and Zhitao Zhang
Aerospace 2024, 11(6), 423; https://doi.org/10.3390/aerospace11060423 - 23 May 2024
Viewed by 830
Abstract
A multisubstructure-based method for assessing the deformation and stress of a fine-meshed model according to a coarse model was proposed. Integrating boundary conditions in a local fine-meshed model, a displacement mapping matrix from the coarse model to the fine-meshed model was constructed. The [...] Read more.
A multisubstructure-based method for assessing the deformation and stress of a fine-meshed model according to a coarse model was proposed. Integrating boundary conditions in a local fine-meshed model, a displacement mapping matrix from the coarse model to the fine-meshed model was constructed. The method was verified by a three-level panel in a fluid–structure interaction (FSI) framework by integrating the steady vortex lattice method (VLM). A comparison between the inner deformation distribution of the coarse model and that of the global fine-meshed model obtained from MSC.Nastran was carried out, and the results showed that the coarse model failed to demonstrate reliable strains and stresses. In contrast, the proposed method in this paper can effectively depict the inner deformation and critical stress distribution. The deformation error was lower than 8%, meeting engineering requirements. Moreover, the results of different working conditions can achieve a similar relative error of displacement for an identical position. The easy storage of the displacement mapping matrix and the convenience of the boundary information transformation among all substructure levels are prominent aspects. As a result, there is a solid foundation for addressing the time-dependent problem in spite of the simultaneity and region. Full article
(This article belongs to the Special Issue Multiscale Modelling in Aerospace Engineering)
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13 pages, 1059 KiB  
Article
Aeroelasticity Model for Highly Flexible Aircraft Based on the Vortex Lattice Method
by Mindaugas Dagilis and Sigitas Kilikevičius
Aerospace 2023, 10(9), 801; https://doi.org/10.3390/aerospace10090801 - 14 Sep 2023
Viewed by 1600
Abstract
With the increasing use of composite materials in aviation, structural aircraft design often becomes limited by stiffness, rather than strength. As a consequence, aeroelastic analysis becomes more important to optimize both aircraft structures and control algorithms. A low computational cost aeroelasticity model based [...] Read more.
With the increasing use of composite materials in aviation, structural aircraft design often becomes limited by stiffness, rather than strength. As a consequence, aeroelastic analysis becomes more important to optimize both aircraft structures and control algorithms. A low computational cost aeroelasticity model based on VLM and rigid-body dynamics is proposed in this work. UAV flight testing is performed to evaluate the accuracy of the proposed model. Two flight sections are chosen to be modeled based on recorded aerodynamic surface control data. The calculated accelerations are compared with recorded flight data. It is found that the proposed model adequately captures the general flight profile, with acceleration peak errors between −6.2% and +8.4%. The average relative error during the entire flight section is 39% to 44%, mainly caused by rebounds during the beginning and end of pull-up maneuvers. The model could provide useful results for the initial phases of aircraft control law design when comparing different control algorithms. Full article
(This article belongs to the Special Issue Multiscale Modelling in Aerospace Engineering)
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