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Aerospace
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Aerospace Human–Machine and Environmental Control Engineering
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Aerospace Human–Machine and Environmental Control Engineering

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

Deadline for manuscript submissions: 31 December 2024 | Viewed by 6537

Special Issue Editors

Prof. Dr. Liping Pang

E-Mail Website
Guest Editor
School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
Interests: man–machine–environment system engineering; aircraft energy and thermal management; cockpit human–machine system evaluation; intelligent allocation of human–machine functions
Dr. Chen Ding

E-Mail Website
Guest Editor
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 10081, China
Interests: man–machine–environment system engineering; thermal management of aircraft and ground vehicles; thermal protection of hypersonic vehicles; heat and mass transfer in complex structure

Special Issue Information

Dear Colleagues,

Currently, human–machine–environment system engineering is considered the most important field in aerospace system engineering, and its aim is to promote and optimize aerospace engineering design to ensure safety, efficiency, and economy. Aerospace human–machine and environmental control engineering mainly focuses on the relationship between human, machines and the environment, and studies the optimization combination of human–machine and environmental systems.

Environmental control engineering and human–machine engineering are considered the two most important fields in the engineering of human–machine environmental systems. Aerospace environmental control includes aerospace thermal management and cabin environmental control. Its aims to meet the environmental parameter requirements of different flight stages of aerospace vehicles, dissipating the waste heat generated by the operation of aerospace equipment, and providing a suitable cabin environment for personnel. With the development of artificial intelligence, the field of aerospace human–machine engineering has exhibited new vitality. It is seeking novel technological approaches that maximize human–machine adaptability in controlled environments, enhance the efficiency of human–machine collaboration efficiency, and reduce cognitive load. This Special Issue of Aerospace covers recent research on environmental control and the human–machine performance of aerospace vehicles, including the related systems of spacecrafts, aerospace vehicles, and aircrafts. These human machine and environmental control systems pose significant challenges to the design and optimization of aerospace vehicle systems. Some of these challenges include optimizing environmental control, thermal management and energy utilization in aerospace flight, intelligent design and the evaluation of human–machine–environment systems, and flexible interaction between human and machine.

The editor of this Special Issue invites authors to submit papers addressing the challenges presented in the modeling and optimization of aerospace human machine and environmental control for aerospace vehicles, and in evaluating the capabilities of human–machine systems in aerospace vehicles.

Prof. Dr. Liping Pang
Dr. Chen Ding
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

  • aerospace man–machine–environment system engineering
  • aerospace environmental control
  • aerospace thermal management and energy utilization
  • aerospace human–machine–environment efficiency monitoring and evaluation
  • aerospace human–machine interaction and interface design
  • aerospace human machine function allocation

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Published Papers (7 papers)

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Research

14 pages, 3373 KiB  
Article
Optimization of Thermal Management for the Environmental Worthiness Design of Aviation Equipment Using Phase Change Materials
by Jianjun Zhang, Minwei Li, He Li, Yun Fu and Liangxu Cai
Aerospace 2024, 11(11), 943; https://doi.org/10.3390/aerospace11110943 - 15 Nov 2024
Viewed by 408
Abstract
A phase change materials (PCM)-based heat sink is an effective way to cool intermittent high-power electronic devices in aerospace applications such as airborne electronics and aircraft external carry. Optimizing the heat sink is significant in designing a compact and efficient system. This paper [...] Read more.
A phase change materials (PCM)-based heat sink is an effective way to cool intermittent high-power electronic devices in aerospace applications such as airborne electronics and aircraft external carry. Optimizing the heat sink is significant in designing a compact and efficient system. This paper proposes an optimization procedure for the PCM/expanded graphite (EG)-based heat sink to minimize the temperature of the heat source. The numerical model is built to estimate the thermal response, and a surrogate model is fitted using the Kriging model. An optimization algorithm is constructed to predict the optimum parameters of the heat sink, and the effects of heat sink volume, heat flux, and working time on the optimal parameters of the heat sink are investigated. This shows that the numerical results agree well with the experimental data, and the proposed optimization method effectively obtains the optimal EG mass fraction and the geometric dimensions of the PCM enclosure. The optimal EG mass fraction increases with the rise in heat sink volume and decreases with the increase in heat flux and working time. The optimal ratio of the height to the length of the heat sink is 0.43. This study provides practical guidance for the optimal design of a PCM/EG-based heat sink. Full article
(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)
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21 pages, 5794 KiB  
Article
Situation Awareness Discrimination Based on Physiological Features for High-Stress Flight Tasks
by Chunying Qian, Shuang Liu, Xiaoru Wanyan, Chuanyan Feng, Zhen Li, Wenye Sun and Yihang Wang
Aerospace 2024, 11(11), 897; https://doi.org/10.3390/aerospace11110897 - 31 Oct 2024
Viewed by 608
Abstract
Situation awareness (SA) discrimination is significant, allowing for the pilot to maintain task performance and ensure flight safety, especially during high-stress flight tasks. Although previous research has attempted to identify and classify SA, existing SA discrimination models are predominantly binary and rely on [...] Read more.
Situation awareness (SA) discrimination is significant, allowing for the pilot to maintain task performance and ensure flight safety, especially during high-stress flight tasks. Although previous research has attempted to identify and classify SA, existing SA discrimination models are predominantly binary and rely on traditional machine learning methods with limited physiological modalities. The current study aimed to construct a triple-class SA discrimination model for pilots facing high-stress tasks. To achieve this, a flight simulation experiment under typical high-stress tasks was carried out and deep learning algorithms (multilayer perceptron (MLP) and the attention mechanism) were utilized. Specifically, eye-tracking (ET), heart rate variability (HRV), and electroencephalograph (EEG) modalities were chosen as the model’s input features. Comparing the unimodal models, the results indicate that EEG modality surpasses ET and HRV modalities, and the attention mechanism structure has advantageous implications for processing the EEG modalities. The most superior model fused the three modalities at the decision level, with two MLP backbones and an attention mechanism backbone, achieving an accuracy of 83.41% and proving that the model performance would benefit from multimodal fusion. Thus, the current research established a triple-class SA discrimination model for pilots, laying the foundation for the real-time evaluation of SA under high-stress aerial operating conditions and providing a reference for intelligent cockpit design and dynamic human–machine function allocation. Full article
(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)
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20 pages, 4724 KiB  
Article
The Dynamic Prediction Method for Aircraft Cabin Temperatures Based on Flight Test Data
by He Li, Jianjun Zhang, Liangxu Cai, Minwei Li, Yun Fu and Yujun Hao
Aerospace 2024, 11(9), 755; https://doi.org/10.3390/aerospace11090755 - 13 Sep 2024
Viewed by 811
Abstract
For advanced aircraft, the temperature environment inside the cabin is very severe due to the high flight speed and the compact concentration of the electronic equipment in the cabin. Accurately predicting the temperature environment induced inside the cabin during the flight of the [...] Read more.
For advanced aircraft, the temperature environment inside the cabin is very severe due to the high flight speed and the compact concentration of the electronic equipment in the cabin. Accurately predicting the temperature environment induced inside the cabin during the flight of the aircraft can determine the temperature environment requirements of the onboard equipment inside the cabin and provide an accurate input for the thermal design optimization and test verification of the equipment. The temperature environment of the whole aircraft is divided into zones by the cluster analysis method; the heat transfer mechanism of the aircraft cabin is analyzed for the target area; and the influence of internal and external factors on the thermal environment is considered to establish the temperature environment prediction model of the target cabin. The coefficients of the equations in the model are parameterized to extract the long-term stable terms and trend change terms; with the help of the measured data of the flight state, the model coefficients are determined by a stepwise regression method; and the temperature value inside the aircraft cabin is the output by inputting parameters such as flight altitude, flight speed, and external temperature. The model validation results show that the established temperature environment prediction model can accurately predict the change curve of the cabin temperature during the flight of the aircraft, and the model has a good follow-up performance, which reduces the prediction error caused by the temperature hysteresis effect. For an aircraft, the estimated error is 2.8 °C at a confidence level of 95%. Engineering cases show that the application of this method can increase the thermal design requirements of the airborne equipment by 15 °C, increase the low-temperature test conditions by 17 °C, and avoid the problems caused by an insufficient design and over-testing. This method can accurately predict the internal temperature distribution of the cabin during the flight state of the aircraft, help designers determine the thermal design requirements of the airborne equipment, modify the thermal design and temperature test profile, and improve the environmental worth of the equipment. Full article
(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)
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27 pages, 12457 KiB  
Article
Heat Transfer Model Based on Flow Pattern during Flow Boiling in Rectangular Microchannels
by Jiamin Zhu, Peng Zhang, Sicong Tan, Tao Wang, Chaohong Guo and Yuyan Jiang
Aerospace 2024, 11(9), 733; https://doi.org/10.3390/aerospace11090733 - 6 Sep 2024
Viewed by 699
Abstract
In thermal management applications using two-phase flow boiling, rectangular microchannels hold significant promise due to their ease of manufacturing and effective heat transfer characteristics. In this work, we combined experimental and theoretical analyses to propose a theoretical model based on thin liquid film [...] Read more.
In thermal management applications using two-phase flow boiling, rectangular microchannels hold significant promise due to their ease of manufacturing and effective heat transfer characteristics. In this work, we combined experimental and theoretical analyses to propose a theoretical model based on thin liquid film evaporation for predicting heat transfer performance in rectangular cross-sectional microchannels. The heat transfer model is segmented into five zones based on two-phase flow patterns and transient liquid film thickness. These zones represent different flow boiling heat transfer mechanisms over time in microchannels: the liquid slug zone, elongated bubble zone, long-side wall dryout zone, corner liquid evaporation zone, and full dryout zone. The new model comprehensively explains experimental phenomena observed, including long-side wall dryout and thinning of the liquid film on the short-side wall. To validate our model, numerical solutions were computed to study the spatial and temporal variations in heat transfer coefficients. The results exhibited a consistent trend with experimental data regarding average heat transfer coefficients. We also analyzed factors influencing flow boiling characteristics, such as microchannel aspect ratio, hydraulic diameter, measurement location, fluid mass flux, and wall heat flux. Full article
(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)
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17 pages, 5200 KiB  
Article
Optimisation Design of Thermal Test System for Metal Fibre Surface Combustion Structure
by Bin Qi, Rong A, Dongsheng Yang, Ri Wang, Sujun Dong and Yinjia Zhou
Aerospace 2024, 11(8), 668; https://doi.org/10.3390/aerospace11080668 - 14 Aug 2024
Viewed by 821
Abstract
The metal fibre surface combustion structure has the characteristics of strong thermal matching ability, short response time, and strong shape adaptability. It has more advantages in the thermal test of complex hypersonic vehicle surface inlet, leading edge, etc. In this paper, a method [...] Read more.
The metal fibre surface combustion structure has the characteristics of strong thermal matching ability, short response time, and strong shape adaptability. It has more advantages in the thermal test of complex hypersonic vehicle surface inlet, leading edge, etc. In this paper, a method of aerodynamic thermal simulation test based on metal fibre surface combustion is proposed. The aim of the study was to create a uniform target heat flow on the inner wall surface of a cylindrical specimen by matching the gas jet flow rate and the geometry of the combustion surface. The research adopted the optimisation design method based on the surrogate model to establish the numerical calculation model of a metal fibre combustion jet heating cylinder specimen. One hundred sample points were obtained through Latin hypercube sampling, and a database of design parameters and heat flux was established through numerical simulation. The kriging surrogate model and the non-dominated sequencing genetic optimisation algorithm with elite strategy were adopted. A bi-objective optimisation design was carried out with the optimisation objective of the coincidence between the predicted and the target heat flux on the inner wall of the specimen. The results showed that the average relative errors of heat flow density on the specimen surface were 8.8% and 6% through the leave-one-out cross-validation strategy and the validation of six test sample points, respectively. The relative error values in most regions were within 5%, which indicates that the established kriging surrogate model has high prediction accuracy. Under the optimal solution conditions, the numerical calculation results of the heat flow on the inner wall of the specimen were in good agreement with the target heat flow values, with an average relative error of less than 5% and a maximum value of less than 8%. These results show that the optimisation design method based on the kriging surrogate model can effectively match the thermal test parameters of metal fibre combustion structures. Full article
(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)
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18 pages, 3418 KiB  
Article
Exploring the Psychological Well-Being of Flight Cadets through a Comprehensive Survey Analysis of Self-Awareness and Self-Acceptance
by Dan Miao, Xiaodong Cao, Bingxu Zhao, Yuan Shi and Yunze Shi
Aerospace 2024, 11(6), 441; https://doi.org/10.3390/aerospace11060441 - 30 May 2024
Viewed by 1050
Abstract
A robust level of self-awareness and self-acceptance is crucial for flight cadets. In this study, a total of 106 flight cadets from various grades and flight training sites were assessed using the self-awareness and self-acceptance scale. The scales were optimized through item analysis, [...] Read more.
A robust level of self-awareness and self-acceptance is crucial for flight cadets. In this study, a total of 106 flight cadets from various grades and flight training sites were assessed using the self-awareness and self-acceptance scale. The scales were optimized through item analysis, reliability, and validity assessments. The finalized scales demonstrated an acceptable level of reliability and validity. Upon analyzing the collected data, it was observed that the overall self-awareness and -acceptance levels among the evaluated pilot students fell within the normal range. However, identifying positive symptoms directly proved challenging. The tested flight cadets exhibited moderate symptoms across each factor, with instances of severe symptoms in academic self-awareness. Notably, flight cadets trained abroad exhibited a lower level of self-awareness and -acceptance compared to those trained in China. But this phenomenon was not reflected in grade difference. Regression analysis revealed that physical and emotional self-awareness dimensions accounted for 62% of the variations in the psychological dimension, while passive self-acceptance explained 72% of the changes in active self-acceptance. Finally, in view of the issues found in the research, corresponding management measures and recommendations are presented to enhance the self-awareness and -acceptance levels of flight cadets. Full article
(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)
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20 pages, 4497 KiB  
Article
Workload Measurement Method for Manned Vehicles in Multitasking Environments
by Chenyuan Yang, Liping Pang, Jie Zhang and Xiaodong Cao
Aerospace 2024, 11(5), 406; https://doi.org/10.3390/aerospace11050406 - 16 May 2024
Viewed by 984
Abstract
Workload (WL) measurement is a crucial foundation for human–machine collaboration, particularly in high-stress multitasking environments such as manned vehicle operations during emergencies, where operators often experience High Workload (HWL) levels, increasing the risk of human error. To address this challenge, this study introduces [...] Read more.
Workload (WL) measurement is a crucial foundation for human–machine collaboration, particularly in high-stress multitasking environments such as manned vehicle operations during emergencies, where operators often experience High Workload (HWL) levels, increasing the risk of human error. To address this challenge, this study introduces a novel WL measurement method that combines Task Demand Load (TDL) and Subject Load Capacity (SLC) to quantitatively assess operator workload. This method was validated through experiments with 45 subjects using the Environmental Control and Atmospheric Regeneration (ECAR) system. The statistical results showed that as the designed WL levels increased, the Average Workload (AWL), the NASA-TLX score, and the work time percentage increased significantly, while the task accuracy and the fixation duration decreased significantly. These results also revealed the impact of WL levels on human responses (such as subjective feeling, work performance, and eye movement). In addition, very strong correlations were found between AWL measurements and NASA-TLX scores (r = 0.75, p < 0.01), task accuracy (r = −0.73, p < 0.01), and work time percentage (r = 0.97, p < 0.01). Overall, these results proved the effectiveness of the proposed method for measuring WL. On this basis, this study defined WL thresholds by integrating task accuracy with AWL calculations, providing a framework for the dynamic management of task allocation between humans and machines to maintain operators within optimal WL ranges. Full article
(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)
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