Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.0
2.2
Journals
Aerospace
Special Issues
New Results in Wind Tunnel Testing
share announcement

New Results in Wind Tunnel Testing

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

Deadline for manuscript submissions: 30 September 2025 | Viewed by 2411

Special Issue Editor

Prof. Dr. Bosko Rasuo

E-Mail Website
Guest Editor
Faculty of Mechanical Engineering, University of Belgrade, Belgrade, Serbia
Interests: computational and experimental aerodynamics; wind tunnel technology; flow control; flight mechanics and aircraft performance; aeroacoustics; aeroelasticity; composite materials/structures and fatigue; failure analysis; crashworthiness; fluid–structure interaction; experimental fracture mechanics; fatigue of aircraft materials and structures; bio-inspired aerodynamical and structural design; UAVs; artificial intelligence; wind energy

Special Issue Information

Dear Colleagues,

To successfully design the aerodynamics of new modern aircraft, it is necessary to know the accurate aerodynamic characteristics of the whole aircraft as well as of its individual constituent parts. Since there is still no completely accurate mathematical model of turbulent flows, we cannot completely solve the aerodynamic design problem by computer simulation and calculation only. We still have to solve many problems related to aerodynamic design by performing tests in wind tunnels. However, wind tunnel simulation is connected with many problems that cause distortions in the flow conditions around the tested models, which ultimately results in the inaccuracy of the measured aerodynamic values. There are many reasons for this, but it is quite understandable that even the best wind tunnels cannot provide conditions that accurately simulate flows around the model that are identical to the flows in the free air. Therefore, resolving the problem related to the definition and elimination of wind tunnel wall interference is a continuing task requiring experimental and theoretical research, either during the construction of new wind tunnels or during their use.

However, the fact is that wind tunnels are increasingly used today to calibrate CFD simulation codes and less and less to directly design new aircraft in order to reduce very expensive wind tunnel experiments. In the last three years, the role of wind tunnels in the field of aerospace has expanded even more, especially in the era of accelerated development and application of artificial intelligence and implementation of machine learning in aerodynamics and solving complex problems of aeroelasticity of sophisticated aircraft structures.

The focus of this special issue, called "New Results in Wind Tunnel Testing", will be the research and development of modern aircraft by testing in subsonic, transonic, supersonic, and hypersonic wind tunnels, covering a velocity range from 0.2 to 15 Mach.

Prof. Dr. Bosko Rasuo
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

  • subsonic/transonic/supersonic/hypersonic wind tunnel
  • measurement techniques
  • measurement systems
  • test methodology
  • innovative approaches

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

26 pages, 13044 KiB  
Article
FSN-PID Algorithm for EMA Multi-Nonlinear System and Wind Tunnel Experiments Verification
by Hongqiao Yin, Jun Guan, Guilin Jiang, Yucheng Zheng, Wenjun Yi and Jia Jia
Aerospace 2025, 12(8), 715; https://doi.org/10.3390/aerospace12080715 - 11 Aug 2025
Viewed by 316
Abstract
In order to improve mathematical model accuracy of electromechanical actuator (EMA) and solve the problems of low-frequency response and large overshoot for nonlinear systems by using traditional proportional integral derivative (PID) algorithm, a fuzzy single neuron (FSN)-PID algorithm is proposed. Firstly, a complete [...] Read more.
In order to improve mathematical model accuracy of electromechanical actuator (EMA) and solve the problems of low-frequency response and large overshoot for nonlinear systems by using traditional proportional integral derivative (PID) algorithm, a fuzzy single neuron (FSN)-PID algorithm is proposed. Firstly, a complete multi-nonlinear dynamic model of EMA is constructed, which introduces internal friction and current limiter of brushless direct current motors (BLDCMs), dead zone backlash of gear trains, and LuGre friction between output shaft and fin. Secondly, a FSN-PID controller is introduced into the automatic position regulator (APR) of EMA control system, where the gain coefficient K of SN algorithm is adjusted by fuzzy control, and the stability of the controller is proved. In addition, simulations are conducted on the response effect of different fin positions under different algorithms for the analysis of the 6° fin position response; it can be concluded that the rise time with FSN-PID algorithm can be reduced by about 4.561% compared to PID, about 1.954% compared to fuzzy (F)-PID, about 0.875% compared to single neuron (SN)-PID, and about 0.380% compared to back propagation (BP)-PID. For the 4°-2 Hz sine position tracking analysis, it can be concluded that the minimum phase error of FSN-PID algorithm is about 0.4705 ms, which is about 74.44% smaller than PID, about 73.43% smaller than F-PID, about 17.24% smaller than SN-PID, and about 10.81% smaller than BP-PID. Finally, wind tunnel experiments investigate the actual high dynamic flight environment and verify the excellent position tracking ability of FSN-PID algorithm. Full article
(This article belongs to the Special Issue New Results in Wind Tunnel Testing)
►▼ Show Figures

Figure 1

25 pages, 3472 KiB  
Article
Physical Information-Based Mach Number Prediction and Model Migration in Continuous Wind Tunnels
by Luping Zhao and Chong Wang
Aerospace 2025, 12(8), 701; https://doi.org/10.3390/aerospace12080701 - 7 Aug 2025
Viewed by 270
Abstract
In wind tunnel tests for aerospace and bridge engineering, the accurate prediction of Mach number remains a core challenge to ensure the reliability of airflow dynamics characterization. Pure data-driven models often fail to meet high-precision prediction requirements due to the lack of physical [...] Read more.
In wind tunnel tests for aerospace and bridge engineering, the accurate prediction of Mach number remains a core challenge to ensure the reliability of airflow dynamics characterization. Pure data-driven models often fail to meet high-precision prediction requirements due to the lack of physical mechanism constraints and insufficient generalization capability. This paper proposes a physical information-based long short-term memory network (P-LSTM), which constructs a physical loss function by embedding isentropic flow equations from gas dynamics, thereby constraining the Mach number prediction solution space within the physically feasible domain. This approach effectively balances the neural network’s ability to capture temporal features with the interpretability of physical mechanisms. Aiming at the scarcity of data in new wind tunnel scenarios, an adaptive weight transfer learning method (AWTL) is further proposed, realizing efficient knowledge transfer across different-scale wind tunnels via cross-domain data calibration, adaptive source-domain weight reweighting, and target-domain fine-tuning. Experimental results show that the P-LSTM method achieves a 50.65–62.54% reduction in RMSE, 48.00–54.05% in MAE, and 47.88–73.68% in MD compared with traditional LSTM for Mach number prediction in the 0.6 m continuous wind tunnel flow field. The AWTL model also outperforms the direct training model significantly in the 2.4 m continuous wind tunnel, with RMSE, MAE, and MD reduced by 85.26%, 95.12%, and 71.14%, respectively. These results validate that the proposed models achieve high-precision Mach number prediction with strong generalization capability. Full article
(This article belongs to the Special Issue New Results in Wind Tunnel Testing)
►▼ Show Figures

Figure 1

21 pages, 1303 KiB  
Article
A Multi-Mode Dynamic Fusion Mach Number Prediction Framework
by Luping Zhao, Weihao Li and Wentao Xu
Aerospace 2025, 12(7), 569; https://doi.org/10.3390/aerospace12070569 - 23 Jun 2025
Viewed by 246
Abstract
The precise control of Mach numbers in supersonic and hypersonic compressor wind tunnel systems is a critical challenge in aerodynamic research. Although existing studies have improved prediction accuracy to some extent through machine learning methods, they generally neglect the multi-mode characteristics of complex [...] Read more.
The precise control of Mach numbers in supersonic and hypersonic compressor wind tunnel systems is a critical challenge in aerodynamic research. Although existing studies have improved prediction accuracy to some extent through machine learning methods, they generally neglect the multi-mode characteristics of complex wind tunnel systems, limiting the generalizability of the models. To address this issue, the present study proposes a multi-mode dynamic fusion Mach number prediction framework that integrates strategies of segmented modeling and cross-modal information fusion. First, single-mode segmented prediction models are constructed on the basis of Multi-output Support Vector Regression (MSVR), with hyperparameters optimized to capture the characteristics of individual modes. Second, the Partial Least Squares (PLS) method is employed to explore the correlations between historical and new modes, dynamically selecting the optimal prediction model and updating the historical mode repository. Experimental results demonstrate that the multi-mode dynamic fusion framework reduces the Root Mean Square Error (RMSE) by 70.57%, 56.4%, and 63.64% compared to Support Vector Regression (SVR), PLS, and Long Short-term Memory (LSTM) networks across six operating conditions. The framework proposed in this paper enhances Mach number prediction accuracy while improving model generalizability. Full article
(This article belongs to the Special Issue New Results in Wind Tunnel Testing)
►▼ Show Figures

Figure 1

15 pages, 7479 KiB  
Article
New Transonic Tests of HB-2 Hypersonic Standard Models in the VTI T-38 Trisonic Wind Tunnel
by Dijana Damljanović, Đorđe Vuković, Goran Ocokoljić and Boško Rašuo
Aerospace 2025, 12(2), 131; https://doi.org/10.3390/aerospace12020131 - 9 Feb 2025
Cited by 1 | Viewed by 1100
Abstract
Recent experience has shown that test results of standard wind tunnel models under off-design conditions could be a useful aid in preparations of some nonstandard wind tunnel tests. However, reference data for such conditions do not exist, or they are scarce. Therefore, off-design [...] Read more.
Recent experience has shown that test results of standard wind tunnel models under off-design conditions could be a useful aid in preparations of some nonstandard wind tunnel tests. However, reference data for such conditions do not exist, or they are scarce. Therefore, off-design transonic wind tunnel tests of the HB-2 standard models were executed in the VTI T-38 wind tunnel as a supplement to the supersonic tests of the same models under design-intent conditions, for which reference results were available. New tests were conducted so that test envelopes partially overlapped with those from available supersonic reference data. Good agreements of results with references were confirmed in the overlapped ranges, so it was assumed that, by implication, the obtained results were also valid in the transonic range of conditions, with an observation that the effects of sting diameter were much more pronounced in the transonic range than in the supersonic one. HB-2 models were tested in two sizes, using two different wind tunnel balances for each model, so that the results can be used with more confidence. Full article
(This article belongs to the Special Issue New Results in Wind Tunnel Testing)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop