Aerospace

22 pages, 2456 KiB

Open AccessArticle

An Ensemble of Heuristic Adaptive Contract Net Protocol for Efficient Dynamic Data Relay Satellite Scheduling Problem

by Manyi Liu, Guohua Wu, Yi Gu and Qizhang Luo

Aerospace 2025, 12(8), 749; https://doi.org/10.3390/aerospace12080749 - 21 Aug 2025

Task scheduling in data relay satellite networks (DRSNs) is subject to dynamic disruptions such as resource failures, sudden surges in task demands, and variations in service duration requirements. These disturbances may degrade the performance of pre-established scheduling plans. To improve adaptability and robustness [...] Read more.

Task scheduling in data relay satellite networks (DRSNs) is subject to dynamic disruptions such as resource failures, sudden surges in task demands, and variations in service duration requirements. These disturbances may degrade the performance of pre-established scheduling plans. To improve adaptability and robustness under such uncertainties, this paper presents a dynamic scheduling model for DRSN that integrates comprehensive task constraints and link connectivity requirements. The model aims to maximize overall task utility while minimizing deviations from the original schedule. To efficiently solve this problem, an ensemble heuristic adaptive contract net protocol (EH-ACNP) is developed, which supports dynamic scheduling strategy adaptation and efficient rescheduling through iterative negotiations. Extensive simulation results show that, in scenarios with sudden task surges, the proposed method achieves a 3.1% improvement in yield compared to the state-of-the-art dynamic scheduling algorithm HMCNP, and it also outperforms HMCNP in scenarios involving resource interruptions. Sensitivity analysis further indicates that the algorithm maintains strong robustness when the disposal rate parameter exceeds 0.2. These results highlight the practical potential of the EH-ACNP for dynamic scheduling in complex and uncertain DRSN environments. Full article

(This article belongs to the Section Astronautics & Space Science)

► Show Figures

Figure 1

23 pages, 8922 KiB

Open AccessArticle

Research on Parameter Prediction Model of S-Shaped Inlet Based on FCM-NDAPSO-RBF Neural Network

by Ye Wei, Lingfei Xiao, Xiaole Zhang, Junyuan Hu and Jie Li

Aerospace 2025, 12(8), 748; https://doi.org/10.3390/aerospace12080748 - 21 Aug 2025

Abstract

To address the inefficiencies of traditional numerical simulations and the high cost of experimental validation in the aerodynamic–stealth integrated design of S-shaped inlets for aero-engines, this study proposes a novel parameter prediction model based on a fuzzy C-means (FCM) clustering and nonlinear dynamic [...] Read more.

To address the inefficiencies of traditional numerical simulations and the high cost of experimental validation in the aerodynamic–stealth integrated design of S-shaped inlets for aero-engines, this study proposes a novel parameter prediction model based on a fuzzy C-means (FCM) clustering and nonlinear dynamic adaptive particle swarm optimization-enhanced radial basis function neural network (NDAPSO-RBFNN). The FCM algorithm is applied to reduce the feature dimensionality of aerodynamic parameters and determine the optimal hidden layer structure of the RBF network using clustering validity indices. Meanwhile, the NDAPSO algorithm introduces a three-stage adaptive inertia weight mechanism to balance global exploration and local exploitation effectively. Simulation results demonstrate that the proposed model significantly improves training efficiency and generalization capability. Specifically, the model achieves a root mean square error (RMSE) of

3.81 \times 10^{- 8}

on the training set and

8.26 \times 10^{- 8}

on the test set, demonstrating robust predictive accuracy. Furthermore,

98.3 %

of the predicted values fall within the

y = x \pm 3 β

confidence interval (

β = 1.2 \times 10^{- 7}

). Compared with traditional PSO-RBF models, the number of iterations of NDAPSO-RBF network is lower, the single prediction time of NDAPSO-RBF network is shorter, and the number of calls to the standard deviation of the NDAPSO-RBF network is lower. These results indicate that the proposed model not only provides a reliable and efficient surrogate modeling method for complex inlet flow fields but also offers a promising approach for real-time multi-objective aerodynamic–stealth optimization in aerospace applications. Full article

(This article belongs to the Section Aeronautics)

► Show Figures

Figure 1

23 pages, 5093 KiB

Open AccessArticle

Reentry Trajectory Online Planning and Guidance Method Based on TD3

by Haiqing Wang, Shuaibin An, Jieming Li, Guan Wang and Kai Liu

Aerospace 2025, 12(8), 747; https://doi.org/10.3390/aerospace12080747 - 21 Aug 2025

Abstract

Aiming at the problem of poor autonomy and weak time performance of reentry trajectory planning for Reusable Launch Vehicle (RLV), an online reentry trajectory planning and guidance method based on Twin Delayed Deep Deterministic Policy Gradient (TD3) is proposed. In view of the [...] Read more.

Aiming at the problem of poor autonomy and weak time performance of reentry trajectory planning for Reusable Launch Vehicle (RLV), an online reentry trajectory planning and guidance method based on Twin Delayed Deep Deterministic Policy Gradient (TD3) is proposed. In view of the advantage that the drag acceleration can be quickly measured by the airborne inertial navigation equipment, the reference profile adopts the design of the drag acceleration–velocity profile in the reentry corridor. In order to prevent the problem of trajectory angle jump caused by the unsmooth turning point of the section, the section form adopts the form of four multiple functions to ensure the smooth connection of the turning point. Secondly, considering the advantages of the TD3 dual Critic network structure and delay update mechanism to suppress strategy overestimation, the TD3 algorithm framework is used to train multiple strategy networks offline and output profile parameters. Finally, considering the reentry uncertainty and the guidance error caused by the limitation of the bank angle reversal amplitude during lateral guidance, the networks are invoked online many times to solve the profile parameters in real time and update the profile periodically to ensure the rapidity and autonomy of the guidance command generation. The TD3 strategy networks are trained offline and invoked online many times so that the cumulative error in the previous guidance period can be eliminated when the algorithm is called again each time, and the online rapid generation and update of the reentry trajectory is realized, which effectively improves the accuracy and computational efficiency of the landing point. Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

24 pages, 8138 KiB

Open AccessArticle

Design Methodology for Fishtailed Pipe Diffusers and Its Application to a High-Pressure Ratio Centrifugal Compressor

by Junnan Liu, Dingxi Wang and Xiuquan Huang

Aerospace 2025, 12(8), 746; https://doi.org/10.3390/aerospace12080746 - 21 Aug 2025

Abstract

A high-performance diffuser is crucial for a high-pressure ratio centrifugal compressor to achieve high efficiency. Pipe diffusers have been proven effective in enhancing the performance of such compressors. However, detailed design methodologies for pipe diffusers are scarcely covered in the existing literature. Thus, [...] Read more.

A high-performance diffuser is crucial for a high-pressure ratio centrifugal compressor to achieve high efficiency. Pipe diffusers have been proven effective in enhancing the performance of such compressors. However, detailed design methodologies for pipe diffusers are scarcely covered in the existing literature. Thus, this paper provides a comprehensive design methodology specifically for fishtailed pipe diffusers. This methodology begins by defining the throat and outlet areas using gas-dynamic functions and then establishes the centerline by choosing the angle distributions. Finally, various cross-sectional profiles are defined along the centerline, completing the diffuser’s design. To demonstrate the proposed methodology, a fishtailed pipe diffuser is designed to contrast with the original diffuser of the National Aeronautics and Space Administration’s High-Efficiency Centrifugal Compressor (NASA HECC). Numerical analysis shows that the fishtailed pipe diffuser increases the compressor’s total pressure ratio and isentropic efficiency over its whole operating range. At the design operating point, the isentropic efficiency and the total pressure ratio are increased by 2.4 percentage points and 2.7%, respectively. This demonstrates the effectiveness of the proposed design methodology for fishtailed pipe diffusers. Full article

(This article belongs to the Special Issue Progress in Turbomachinery Technology for Propulsion (2nd Edition))

► Show Figures

Figure 1

26 pages, 2825 KiB

Open AccessArticle

Towards a Unified Modeling and Simulation Framework for Space Systems: Integrating Model-Based Systems Engineering with Open Source Multi-Domain Simulation Environments

by Serena Campioli, Giacomo Luccisano, Davide Ferretto and Fabrizio Stesina

Aerospace 2025, 12(8), 745; https://doi.org/10.3390/aerospace12080745 - 21 Aug 2025

Abstract

The increasing complexity of modern space systems requires a more integrated and scalable approach to their design, analysis, and verification. Model-Based Systems Engineering (MBSE) has emerged as a powerful methodology for managing the complexity of systems through formalized modeling practices, but its integration [...] Read more.

The increasing complexity of modern space systems requires a more integrated and scalable approach to their design, analysis, and verification. Model-Based Systems Engineering (MBSE) has emerged as a powerful methodology for managing the complexity of systems through formalized modeling practices, but its integration with dynamic and domain-specific simulations remains limited. This paper presents the first version of the unified Modeling and Simulation (M&S) framework MOSAiC (Modeling and Simulation Architecture for integrated Complex systems), which connects MBSE with open source, multi-domain simulation environments, with the goal of improving traceability, reusability, and fidelity in the system lifecycle. The architecture proposed here leverages ARCADIA-based models as authoritative sources, interfacing with simulation tools through standardized data exchanges and co-simulation strategies. Using a representative space mission scenario, the framework ability to align functional and physical models with specialized simulations is demonstrated. Results show improved consistency between system models and simulation artifacts, reduced integration costs, and improved early validation of design choices. This work supports the broader vision of digital engineering for space systems, suggesting that a modular, standards-based approach to unifying MBSE and simulation can significantly improve system understanding and development efficiency. Full article

(This article belongs to the Special Issue On-Board Systems Design for Aerospace Vehicles (2nd Edition))

► Show Figures

Figure 1

23 pages, 4182 KiB

Open AccessArticle

A Long Sequence Time-Series Forecasting Method for Early Warning of Long Landing Risks with QAR Flight Data

by Zeyuan Zhou, Xiaolei Chong, Zhenglei Chen, Jicheng Zhou, Jichao Zhang and Pengshuo Guo

Aerospace 2025, 12(8), 744; https://doi.org/10.3390/aerospace12080744 - 21 Aug 2025

Abstract

Long landings can reduce runway utilization and increase the probability of runway incursions and excursions. Previous studies on long landings often lacked support from actual operational data and primarily relied on event-triggering logic established by airlines for parameter exceedance detection and retrospective analysis. [...] Read more.

Long landings can reduce runway utilization and increase the probability of runway incursions and excursions. Previous studies on long landings often lacked support from actual operational data and primarily relied on event-triggering logic established by airlines for parameter exceedance detection and retrospective analysis. In response, a comprehensive risk prediction framework for aircraft long landings, supported by Quick Access Recorder (QAR) data, was constructed. The framework includes a data analysis pipeline, a sequence prediction model, and performance evaluation metrics for accident warning efficiency. Specifically, approximately 3 million rows of real QAR data were collected, and reasonable landing intervals were extracted based on pilots’ correct landing sightlines, attention allocation, and actual visual scenarios at departure heights. Gradient Boosting Decision Trees (GBDT) were employed to develop a method for extracting landing interval feature data, based on monitored parameters and ranges of landing distance. Additionally, the GBDT-Informer long-sequence time series prediction model was developed to forecast landing distance, accompanied by the construction of effective metrics for evaluating prediction performance. The results indicate that the GBDT-Informer model effectively models the temporal dimensions of landing intervals, accurately predicting ground speed (GS), radio altitude (RALT), and landing distance sequences. Compared to other prediction models, the GBDT-Informer model consistently achieved the smallest RMSE, MAE, and MAPE values, demonstrating high prediction accuracy. This predictive framework allows for the analysis of the coupling relationships among multiple parameters in flight data and their interrelations with exceedance anomalies. The findings can be applied in actual flight landings to promptly assess whether landing distances exceed limits, providing quick references for flight crews during landing or go-around decisions, thereby enhancing operational safety margins during the landing phase. Full article

(This article belongs to the Section Air Traffic and Transportation)

► Show Figures

Figure 1

19 pages, 3937 KiB

Open AccessArticle

Numerical Method for Chemical Non-Equilibrium Plume Radiation Characteristics of Solid Rocket Motors

by Ruitao Zhang, Yang Liu, Yuxuan Zou, Moding Peng, Zilong Wang and Xiaojing Yu

Aerospace 2025, 12(8), 743; https://doi.org/10.3390/aerospace12080743 - 21 Aug 2025

Abstract

The research objectives of engine plume radiation calculation primarily encompass two aspects: (1) addressing the additional heating induced by plume radiation on rocket thermal protection systems and (2) elucidating the variation patterns of spectral radiation intensity for infrared signature identification and tracking. Focusing [...] Read more.

The research objectives of engine plume radiation calculation primarily encompass two aspects: (1) addressing the additional heating induced by plume radiation on rocket thermal protection systems and (2) elucidating the variation patterns of spectral radiation intensity for infrared signature identification and tracking. Focusing on the thermal effects of radiation, this study first calculates the radiative properties of high-temperature combustion gases and particles separately. Subsequently, the radiative properties of mixed droplets with alumina caps are computed and analyzed. Building upon this and incorporating empirical formulas for aluminum droplet combustion, the engine’s radiative properties are calculated, accounting for the presence of mixed droplets. Ultimately, an integrated computational method for engine radiative properties (both internal and external flow fields) is established, which considers the non-equilibrium processes during droplet transformation. The radiative property parameters are then embedded into the fluid dynamics software via multidimensional interpolation. The radiation transfer equation is solved using the discrete ordinates method (DOM) to obtain the radiation intensity distribution within the plume flow field. This work provides technical support for investigating the radiative characteristics of solid rocket engine plumes. Full article

(This article belongs to the Special Issue Flow and Heat Transfer in Solid Rocket Motors)

► Show Figures

Figure 1

16 pages, 1350 KiB

Open AccessArticle

Orbit Prediction Methods for ONEWEB Constellation

by Junyu Chen, Zhangyi Wen, Kaihui Hu and Xiangxu Lei

Aerospace 2025, 12(8), 742; https://doi.org/10.3390/aerospace12080742 - 20 Aug 2025

Abstract

This study aims to enhance Low Earth Orbit (LEO) satellite orbit prediction accuracy. We propose the Precise Orbit Determination with Optimized Perturbations (PODOP) method, considering Earth’s non-spherical gravity, atmospheric drag, etc., and a Long Short-Term Memory (LSTM)-based approach for orbital element time series. [...] Read more.

This study aims to enhance Low Earth Orbit (LEO) satellite orbit prediction accuracy. We propose the Precise Orbit Determination with Optimized Perturbations (PODOP) method, considering Earth’s non-spherical gravity, atmospheric drag, etc., and a Long Short-Term Memory (LSTM)-based approach for orbital element time series. Validation shows that PODOP’s 10-day median error is 8.1 km (19% larger than Simplified General Perturbations (SGP4)’s 10.1 km) and LSTM’s 10-day median error is 5.3 km, outperforming SGP4 (48.5 km) and PODOP and improving constellation management and collision prevention. Full article

(This article belongs to the Section Astronautics & Space Science)

► Show Figures

Figure 1

37 pages, 18414 KiB

Open AccessArticle

Clearance Analysis of Rotor–Stator Coupled Structures Under Maneuver Flight Conditions Considering Multi-Physical Fields

by Dongxu Du, Shihao Ma, Yu Zhang, Kunpeng Xu, Junzhe Lin, Shang Lv, Xuedong Sun and Wei Sun

Aerospace 2025, 12(8), 741; https://doi.org/10.3390/aerospace12080741 - 20 Aug 2025

Abstract

In the previous studies on the clearance between rotors and stators, only a single physical field or part of the physical fields are considered. In fact, multi-physical fields (inertial moment, temperature, centrifugal, and aerodynamic load) significantly affect the clearance analysis results, especially the [...] Read more.

In the previous studies on the clearance between rotors and stators, only a single physical field or part of the physical fields are considered. In fact, multi-physical fields (inertial moment, temperature, centrifugal, and aerodynamic load) significantly affect the clearance analysis results, especially the inertial load caused by maneuver flight. However, few studies have been found in clearance studies that can comprehensively consider the influence of various loads. To reflect the actual service environment and accurately calculate the clearance, a clearance analysis method is proposed which can consider the inertia moment, temperature, centrifugal, and aerodynamic load simultaneously. Firstly, the dynamic model of the rotor–stator coupled structure is created by using the finite element method. The coupling between blade tenons and disk grooves is realized based on the friction contact way. The bolt connection at the stator flange is simulated by the beam element, and the bearing supports at the rotor are simulated by the spring element. Furthermore, the clearance experiment platform of the rotor–stator coupled structure is constructed, and the validity of the proposed method is verified based on the clearance test results. Finally, the influence of multi-physical fields on the clearance of the rotor–stator coupled structure is investigated, and some new clearance variation rules are found. Full article

(This article belongs to the Section Aeronautics)

► Show Figures

Figure 1

19 pages, 3793 KiB

Open AccessArticle

Assessment of Oscillating Wings to Deliver Air Mass Flow Under Power and Thrust Constraints

by Emin Burak Ozyilmaz and Mustafa Kaya

Aerospace 2025, 12(8), 740; https://doi.org/10.3390/aerospace12080740 - 20 Aug 2025

Abstract

An oscillating wing was evaluated for its ability to deliver air mass flow. The evaluation was based on exploring the oscillation parameters that provide a given mass flow rate at the least power requirement with the highest possible thrust generation. Wing oscillation was [...] Read more.

An oscillating wing was evaluated for its ability to deliver air mass flow. The evaluation was based on exploring the oscillation parameters that provide a given mass flow rate at the least power requirement with the highest possible thrust generation. Wing oscillation was defined as coupled pitch and plunge motions. The support vector regression algorithm was implemented as a machine learning tool to link the oscillation parameters to power and thrust values. The required power and generated thrust values were computed by solving the unsteady turbulent flows around the wings. The results were also compared to the performance of an axial flow fan that delivered the same amount of air mass flow. It was found that an oscillating wing is compatible with an axial fan in terms of power requirement and thrust generation. Full article

(This article belongs to the Special Issue Recent Advances in Applied Aerodynamics (2nd Edition))

► Show Figures

Figure 1

25 pages, 6919 KiB

Open AccessArticle

Research on the Vibration Characteristics of Non-Axisymmetric Exhaust Duct Under Thermal Environment

by Jintao Ding and Lina Zhang

Aerospace 2025, 12(8), 739; https://doi.org/10.3390/aerospace12080739 - 19 Aug 2025

Viewed by 103

Abstract

The exhaust duct of aero-engine exhibits complex vibration response characteristics under the influence of temperature fields and vibration loads. Taking the non-axisymmetric exhaust duct of turboshaft engine as the object of study, a finite element model of the exhaust duct was established using [...] Read more.

The exhaust duct of aero-engine exhibits complex vibration response characteristics under the influence of temperature fields and vibration loads. Taking the non-axisymmetric exhaust duct of turboshaft engine as the object of study, a finite element model of the exhaust duct was established using three-dimensional finite element analysis methods to analyze the thermal modal and random vibration response characteristics under axial loading for large thin-walled non-axisymmetric exhaust ducts. The simulation analysis method was validated through thermal vibration experiments on the scaled model. In a thermal environment, the shape of the power spectral density curves for displacement and stress of the exhaust duct remains largely unchanged in the low-frequency range; however, the response frequencies exhibit a significant forward shift. When subjected to Y-axial loading, the amplitude of the X- and Z-direction displacement response at 1st order (12.96 Hz) and the stress response at 6th order (30.92 Hz) significantly increase. Random vibration loads excite multiple modes of the exhaust duct, with lower-order modes being more easily stimulated. When subjected to X- and Z-axial loading, 1st order (12.96 Hz) has the greatest impact on the X- and Z-direction displacement responses, while 2nd order (16.93 Hz) and 13th order (82.79 Hz) frequencies have the greatest impact on the displacement response in the Y-direction and equivalent stress response. When subjected to Y-axial loading, the 5th order (22.35 Hz) and 12th order (81.69 Hz) modes have the most significant effects on the displacement responses in the X, Y, and Z directions and equivalent stress responses. Attention to these orders is essential during the design process, along with implementing certain stiffness reinforcement measures to reduce response amplitudes. Full article

(This article belongs to the Section Aeronautics)

► Show Figures

Figure 1

22 pages, 4646 KiB

Open AccessArticle

Analysis on Characteristics of Mixed Traffic Flow with Intelligent Connected Vehicles at Airport Two-Lane Curbside Based on Traffic Characteristics

by Xin Chang, Weiping Yang, Yao Tang, Zhe Liu and Zheng Liu

Aerospace 2025, 12(8), 738; https://doi.org/10.3390/aerospace12080738 - 19 Aug 2025

Viewed by 89

Abstract

With the growing adoption of connected and autonomous vehicles (CAVs), their market penetration is expected to rise. This study investigates the mixed traffic flow dynamics of human-driven vehicles (HDVs) and CAVs at airport terminal curbsides. A two-lane parking simulation model is developed, integrating [...] Read more.

With the growing adoption of connected and autonomous vehicles (CAVs), their market penetration is expected to rise. This study investigates the mixed traffic flow dynamics of human-driven vehicles (HDVs) and CAVs at airport terminal curbsides. A two-lane parking simulation model is developed, integrating the intelligent driver model, PATH-calibrated cooperative adaptive cruise control, and a degraded adaptive cruise control model to capture different driving behaviors. The model accounts for varying time headways among HDV drivers based on their information acceptance levels and imposes departure constraints to enhance safety. Simulation results show that the addition of CAVs can significantly increase the average speed of vehicles and reduce the average delay time. Two metrics are inversely proportional. Specifically, as illustrated by a curbside length of 400 m and a parking demand of 1300 pcph, when the CAV penetration rate p is 10%, 30%, 50%, 70%, and 100%, respectively, compared to p = 0, the average traffic flow speed increases by 1.7%, 6.4%, 15.0%, 27.2%, and 48.7%, respectively. The average delay time decreases by 2.8%, 6.4%, 10.5%, 13.5%, and 20.0%, respectively. Meanwhile, CAVs and HDVs exhibit consistent patterns in terms of parking space utilization: the first stage (0–30% of parking spaces) showed a stable and concentrated trend; the second stage (30–70% of parking spaces) showed a slow downward trend but remained at a high level; the third stage (70–100% of parking spaces) showed a rapid decline at a steady rate. Full article

(This article belongs to the Section Air Traffic and Transportation)

► Show Figures

Figure 1

20 pages, 10047 KiB

Open AccessArticle

Thermal Environment for Lunar Orbiting Spacecraft Based on Non-Uniform Planetary Infrared Radiation Model

by Xinqi Li, Liying Tan, Jing Ma and Xuemin Qian

Aerospace 2025, 12(8), 737; https://doi.org/10.3390/aerospace12080737 - 19 Aug 2025

Viewed by 77

Abstract

Accurate computation of external heat flux is critical for spacecraft thermal analysis and thermal control system design. The traditional method, which adopted the uniform planetary infrared radiation model (UPIRM), is inadequate for lunar orbital missions due to the extreme planetary surface temperature variations. [...] Read more.

Accurate computation of external heat flux is critical for spacecraft thermal analysis and thermal control system design. The traditional method, which adopted the uniform planetary infrared radiation model (UPIRM), is inadequate for lunar orbital missions due to the extreme planetary surface temperature variations. This study proposes an external heat flux calculation method for lunar orbits by integrating a non-uniform lunar surface temperature model derived from Lunar Reconnaissance Orbiter (LRO) Diviner radiometric data. Specifically, the lunar surface temperature data were first fitted as functions of latitude (

ψ

) and position angles (

ζ

) through data regression analysis. Then, a comprehensive mathematical framework is established to analyze solar radiation, lunar albedo, and lunar infrared radiation components, incorporating orbital parameters such as beta angle (

β

), orbital inclination (

i

) and so on. Coordinate transformations and numerical integration techniques are employed to evaluate heat flux distributions across cuboidal orbiter surfaces. It is found that the lunar infrared radiation heat flux manifests pronounced fluctuation, peaking at 1023 W/m² near the lunar noon region while plummeting to 20 W/m² near the midnight region under the orbital parameters investigated in this study. This study demonstrates the essential role of the non-uniform planetary infrared radiation model (NUPIRM) in enhancing prediction accuracy by contrast, offering foundational references for thermal management in future lunar and deep-space exploration spacecraft. Full article

(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)

► Show Figures

Figure 1

38 pages, 22596 KiB

Open AccessArticle

Parameter Tuning of Detached Eddy Simulation Using Data Assimilation for Enhancing the Simulation Accuracy of Large-Scale Separated Flow Around a Cylinder

by Kyosuke Nomoto and Shigeru Obayashi

Aerospace 2025, 12(8), 736; https://doi.org/10.3390/aerospace12080736 - 19 Aug 2025

Viewed by 112

Abstract

In this study, data assimilation using PIV measurement data of the cylinder wake obtained from wind tunnel tests was applied to tune the simulation model parameters of Detached Eddy Simulation (DES) to improve the accuracy of large-scale separated flow simulations around a cylinder. [...] Read more.

In this study, data assimilation using PIV measurement data of the cylinder wake obtained from wind tunnel tests was applied to tune the simulation model parameters of Detached Eddy Simulation (DES) to improve the accuracy of large-scale separated flow simulations around a cylinder. The use of DES enables more accurate simulation of large-scale separation flows than RANS. However, it increases computational costs and makes parameter tuning using data assimilation difficult. To reduce the computational time required for data assimilation, the conventional data assimilation method was modified. The background values used for data assimilation were constructed by extracting only velocity data from locations corresponding to observation points. This approach reduced the computational time for background error covariance and Kalman gain, thereby significantly reducing the execution time of the filtering step in data assimilation. As a result of tuning,

C_{d e s}

significantly increased, while

C_{b 1}

decreased. This adjustment extended the length of the recirculation bubble, bringing the time-averaged velocity distribution closer to the PIV measurement data. However, the peak frequency in the PSD obtained from the FFT analysis of velocity fluctuations in the wake shifted slightly toward lower frequencies, slightly increasing the discrepancy with the measurement data. Verifying the relationship between parameter values and flow, it was found that parameter tuning stabilized the separation shear layer generated at the leading edge of the cylinder and enlarged the size of the recirculation bubbles. On the other hand, frequency variations did not show consistent changes in response to parameter value changes, indicating that the effect of parameter tuning was limited under the simulation conditions of this study. To bring the frequency fluctuations closer to experimental results, it is suggested that other methods, such as higher-order spatial and temporal accuracy, should be combined. Full article

(This article belongs to the Special Issue Fluid Flow Mechanics (4th Edition))

► Show Figures

Figure 1

20 pages, 3475 KiB

Open AccessArticle

Numerical Simulation of Gliding Arc Plasma-Assisted Ignition and Combustion in Afterburner Combustor

by Zecheng Li, Yong Liang, Xing Zheng, Zhibo Zhang and Yun Wu

Aerospace 2025, 12(8), 735; https://doi.org/10.3390/aerospace12080735 - 19 Aug 2025

Viewed by 141

Abstract

The ignition and combustion characteristics of the afterburner directly affect the engine performance. In this study, a numerical simulation model was created for both the novel gliding arc assisted combustion system and the conventional spark plug system. The ignition and combustion characteristics of [...] Read more.

The ignition and combustion characteristics of the afterburner directly affect the engine performance. In this study, a numerical simulation model was created for both the novel gliding arc assisted combustion system and the conventional spark plug system. The ignition and combustion characteristics of the afterburner were then numerically investigated. Results indicate that gliding arc can enhance ignition and combustion compared to traditional spark plug. In terms of ignition characteristics, gliding arc extends the lean ignition limit by 50% and reduces ignition delay time by up to 33.8%. Regarding combustion performance, gliding arc improves combustion efficiency by up to 7.6% and increases combustor outlet temperature by up to 7%. However, due to more intense combustion dynamics within the chamber, gliding arc reduces the total pressure recovery coefficient by approximately 8% compared to baseline. Full article

► Show Figures

Figure 1

20 pages, 4152 KiB

Open AccessArticle

Fault Detection and Distributed Consensus Fault-Tolerant Control for Multiple Quadrotor UAVs Based on Nussbaum-Type Function

by Kun Yan, Jinxing Fan, Jianing Tang and Chuchao He

Aerospace 2025, 12(8), 734; https://doi.org/10.3390/aerospace12080734 - 19 Aug 2025

Viewed by 124

Abstract

In this work, a fault detection method and a distributed consensus fault-tolerant control (FTC) scheme are proposed for multiple quadrotor unmanned aerial vehicles (multi-QUAVs) with actuator faults. In order to identify the actuator faults in time, an auxiliary state observer is constructed first. [...] Read more.

In this work, a fault detection method and a distributed consensus fault-tolerant control (FTC) scheme are proposed for multiple quadrotor unmanned aerial vehicles (multi-QUAVs) with actuator faults. In order to identify the actuator faults in time, an auxiliary state observer is constructed first. Subsequently, a fault detection scheme based on the observer error is presented, which can improve the early warning ability of the multi-QUAVs. Meanwhile, to handle unknown sudden faults, the Nussbaum function approach is combined with the consensus theory to design a distributed consensus FTC strategy for multi-QUAVs. Compared with the traditional direct fault estimation method using the projection function technique, the proposed Nussbaum-based FTC method can avoid the singularity problem of the controller in a simple way. Moreover, all error signals of the closed-loop system are proved to be uniformly ultimately bounded via Lyapunov stability theory and the consensus control algorithm. Finally, simulation comparison results indicate the early warning capability of the fault detection method and the formation maintenance performance of the developed fault-tolerant controller. Full article

(This article belongs to the Section Aeronautics)

► Show Figures

Figure 1

20 pages, 966 KiB

Open AccessCommunication

Microwave-Assisted Tunnel Boring for Lunar Subsurface Development: Integration of Rock Weakening and Strength Prediction

by Tae Young Ko

Aerospace 2025, 12(8), 733; https://doi.org/10.3390/aerospace12080733 - 19 Aug 2025

Viewed by 175

Abstract

This study presents an integrated approach for lunar subsurface excavation by combining Tunnel Boring Machine (TBM) technology with microwave-assisted rock weakening and machine learning-based strength prediction methods. Through comprehensive analysis of lunar environmental conditions and geological characteristics, we address the key challenges of [...] Read more.

This study presents an integrated approach for lunar subsurface excavation by combining Tunnel Boring Machine (TBM) technology with microwave-assisted rock weakening and machine learning-based strength prediction methods. Through comprehensive analysis of lunar environmental conditions and geological characteristics, we address the key challenges of subsurface construction on the Moon. Our machine learning models, trained on terrestrial rock data and calibrated with Apollo mission samples, provide reliable predictions of lunar rock strength. Laboratory experiments demonstrate that microwave irradiation can reduce rock strength by 19% within three minutes, significantly enhancing excavation efficiency. The integration of these techniques with TBM technology offers practical solutions for developing lunar habitats while effectively managing challenges posed by extreme temperatures, vacuum conditions, and abrasive regolith. The demonstrated 19% reduction in rock strength through microwave treatment indicates significant potential for enhancing lunar excavation efficiency, though operational implementation requires further development. Our findings indicate that this combined approach of rock weakening and strength prediction methods can substantially improve the technical and economic feasibility of lunar subsurface construction. Full article

(This article belongs to the Special Issue The (Near) Future of Space Resources)

► Show Figures

Figure 1

22 pages, 5391 KiB

Open AccessArticle

Comparative Study of Hybrid Electric Distributed Propulsion Aircraft Through Multiple Powertrain Component Modeling Approaches

by Baptiste Legrand, Arnaud Gaillard and David Bouquain

Aerospace 2025, 12(8), 732; https://doi.org/10.3390/aerospace12080732 - 19 Aug 2025

Viewed by 281

Abstract

Aircraft design is an ever-expanding field of research. Disruptive aircraft architectures and the long-standing need for fast design processes are the main drivers behind the domain growth. Novel concepts like distributed propulsion, Vertical Take-Off and Landing, electrification, hybridization, etc., require new models and [...] Read more.

Aircraft design is an ever-expanding field of research. Disruptive aircraft architectures and the long-standing need for fast design processes are the main drivers behind the domain growth. Novel concepts like distributed propulsion, Vertical Take-Off and Landing, electrification, hybridization, etc., require new models and design strategies to achieve a significant degree of fidelity at every stage of the design. This paper proposes a framework targeting key techniques and assumptions to improve the accuracy of the preliminary aircraft design stage. Based on a review of modern design strategies, a model-based method has been developed. Two distinct approaches to component modeling have been compared for a hybrid-electric distributed propulsion aircraft. To complement this comparative study, the second modeling approach has been tested for three different hybrid electric architectures. The results showcase the feasibility of the three architectures, with promising results for the hydrogen powertrain system. Full article

(This article belongs to the Special Issue Aircraft Design (SI-7/2025))

► Show Figures

Graphical abstract

34 pages, 6708 KiB

Open AccessArticle

Unmanned Aerial Vehicle Tactical Maneuver Trajectory Prediction Based on Hierarchical Strategy in Air-to-Air Confrontation Scenarios

by Yuequn Luo, Zhenglei Wei, Dali Ding, Fumin Wang, Hang An, Mulai Tan and Junjun Ma

Aerospace 2025, 12(8), 731; https://doi.org/10.3390/aerospace12080731 - 18 Aug 2025

Viewed by 339

Abstract

The prediction of the tactical maneuver trajectory of target aircraft is an important component of unmanned aerial vehicle (UAV) autonomous air-to-air confrontation. In view of the shortcomings of low accuracy and poor real-time performance in the existing maneuver trajectory prediction methods, this paper [...] Read more.

The prediction of the tactical maneuver trajectory of target aircraft is an important component of unmanned aerial vehicle (UAV) autonomous air-to-air confrontation. In view of the shortcomings of low accuracy and poor real-time performance in the existing maneuver trajectory prediction methods, this paper establishes a hierarchical tactical maneuver trajectory prediction model to achieve maneuver trajectory prediction based on the prediction of target tactical maneuver intentions. First, extract the maneuver trajectory features and situation features from the above data to establish the classification rules of maneuver units. Second, a tactical maneuver unit prediction model is established using the deep echo-state network based on the auto-encoder with attention mechanism (DeepESN-AE-AM) to predict 21 basic maneuver units. Then, for the above-mentioned 21 basic maneuver units, establish a maneuver trajectory prediction model using the gate recurrent unit based on triangle search optimization with attention mechanism (TSO-GRU-AM). Finally, by integrating the above two prediction models, a hierarchical strategy is adopted to establish a tactical maneuver trajectory prediction model. A section of the confrontation trajectory is selected from the air-to-air confrontation simulation data for prediction, and the results show that the trajectory prediction error of the combination of DeepESN-AE-AM and TSO-GRU-AM is small and meets the accuracy requirements. The simulation results of three air-to-air confrontation scenarios show that the proposed trajectory prediction method helps to assist UAV in accurately judging the confrontational situation and selecting high-quality maneuver strategies. Full article

(This article belongs to the Special Issue Application of Multidisciplinary Optimization and Artificial Intelligence Techniques to Aerospace Engineering (Volume II))

► Show Figures

Figure 1

24 pages, 8239 KiB

Open AccessArticle

Experimental and Numerical Analysis of Wrinkling Behaviors of Inflated Membrane Airship Structures

by Yu Hu, Rongyan Guo and Wujun Chen

Aerospace 2025, 12(8), 730; https://doi.org/10.3390/aerospace12080730 - 18 Aug 2025

Viewed by 208

Abstract

In this paper, the wrinkling behavior of an inflated cantilever beam is presented. An analytical solution for the load-bearing capacity of an inflated beam is proposed to predict the ultimate wrinkling force and critical wrinkling force of the inflated beam, and an iterative [...] Read more.

In this paper, the wrinkling behavior of an inflated cantilever beam is presented. An analytical solution for the load-bearing capacity of an inflated beam is proposed to predict the ultimate wrinkling force and critical wrinkling force of the inflated beam, and an iterative membrane properties method is used to simulate the wrinkling of membrane structures. The load-bearing capacities of an inflated beam, numerically simulated based on these two methods, are compared with experimental results. Good agreement between wrinkling using UMAT-modified M3D4 elements based on the IMP method and experiments was obtained. The effect of wrinkling on the stress distribution of the airship envelope under internal pressure is also explored based on a practice airship. Full article

► Show Figures

Figure 1

36 pages, 8958 KiB

Open AccessArticle

Dynamic Resource Target Assignment Problem for Laser Systems’ Defense Against Malicious UAV Swarms Based on MADDPG-IA

by Wei Liu, Lin Zhang, Wenfeng Wang, Haobai Fang, Jingyi Zhang and Bo Zhang

Aerospace 2025, 12(8), 729; https://doi.org/10.3390/aerospace12080729 - 17 Aug 2025

Viewed by 366

Abstract

The widespread adoption of Unmanned Aerial Vehicles (UAVs) in civilian domains, such as airport security and critical infrastructure protection, has introduced significant safety risks that necessitate effective countermeasures. High-Energy Laser Systems (HELSs) offer a promising defensive solution; however, when confronting large-scale malicious UAV [...] Read more.

The widespread adoption of Unmanned Aerial Vehicles (UAVs) in civilian domains, such as airport security and critical infrastructure protection, has introduced significant safety risks that necessitate effective countermeasures. High-Energy Laser Systems (HELSs) offer a promising defensive solution; however, when confronting large-scale malicious UAV swarms, the Dynamic Resource Target Assignment (DRTA) problem becomes critical. To address the challenges of complex combinatorial optimization problems, a method combining precise physical models with multi-agent reinforcement learning (MARL) is proposed. Firstly, an environment-dependent HELS damage model was developed. This model integrates atmospheric transmission effects and thermal effects to precisely quantify the required irradiation time to achieve the desired damage effect on a target. This forms the foundation of the HELS–UAV–DRTA model, which employs a two-stage dynamic assignment structure designed to maximize the target priority and defense benefit. An innovative MADDPG-IA (I: intrinsic reward, and A: attention mechanism) algorithm is proposed to meet the MARL challenges in the HELS–UAV–DRTA problem: an attention mechanism compresses variable-length target states into fixed-size encodings, while a Random Network Distillation (RND)-based intrinsic reward module delivers dense rewards that alleviate the extreme reward sparsity. Large-scale scenario simulations (100 independent runs per scenario) involving 50 UAVs and 5 HELS across diverse environments demonstrate the method’s superiority, achieving mean damage rates of 99.65% ± 0.32% vs. 72.64% ± 3.21% (rural), 79.37% ± 2.15% vs. 51.29% ± 4.87% (desert), and 91.25% ± 1.78% vs. 67.38% ± 3.95% (coastal). The method autonomously evolved effective strategies such as delaying decision-making to await the optimal timing and cross-region coordination. The ablation and comparison experiments further confirm MADDPG-IA’s superior convergence, stability, and exploration capabilities. This work bridges the gap between complex mathematical and physical mechanisms and real-time collaborative decision optimization. It provides an innovative theoretical and methodological basis for public-security applications. Full article

(This article belongs to the Special Issue Application of Multidisciplinary Optimization and Artificial Intelligence Techniques to Aerospace Engineering (Volume II))

► Show Figures

Figure 1

31 pages, 4893 KiB

Open AccessArticle

Improvements in Robustness and Versatility of Blade Element Momentum Theory for UAM/AAM Applications

by Myungsik Tai, Wooseung Lee, Dahye Kim and Donghun Park

Aerospace 2025, 12(8), 728; https://doi.org/10.3390/aerospace12080728 - 15 Aug 2025

Viewed by 184

Abstract

This study proposes an improved formulation of the blade element momentum theory (BEMT) to enhance its robustness and versatility for urban/advanced air mobility (UAM/AAM) applications. A new velocity factor was introduced to eliminate numerical singularity issue under low inflow velocity conditions. The BEMT [...] Read more.

This study proposes an improved formulation of the blade element momentum theory (BEMT) to enhance its robustness and versatility for urban/advanced air mobility (UAM/AAM) applications. A new velocity factor was introduced to eliminate numerical singularity issue under low inflow velocity conditions. The BEMT framework was further extended and modified to account for non-axial inflow and descent flight conditions. The proposed approach was validated for an isolated propeller case by comparing the results with wind tunnel test data and the computational fluid dynamics (CFD) based on both the overset mesh and sliding mesh methods. The improved BEMT provided reliable accuracy even in low inflow velocity conditions where basic BEMT fails to converge, and yielded reasonable performance predictions with respect to the sliding mesh results. The practicality of the method was confirmed through further application studies such as analyzing on the tilt propeller of single-seated UAM along its mission profile and constructing a propeller performance database for the lift and propulsion propellers of a lift and cruise type 5-seated UAM. The improved BEMT exhibited satisfactory engineering-level accuracy for various flight conditions, with prediction errors within 14% of the CFD results. The results and observations indicate that the proposed BEMT framework is suitable for use in the early design stages, performance analysis, and construction of a performance database, for distributed propulsion aircraft, such as eVTOL and UAM/AAM. Full article

(This article belongs to the Special Issue Numerical Modelling of Aerospace Propulsion)

► Show Figures

Figure 1

24 pages, 3659 KiB

Open AccessArticle

An Improved Climbing Strategy for High-Altitude Fast-Deploy Aerostat Systems

by Jun Li, Yonglin Deng, Zheng Chen, Jun Liao and Yi Jiang

Aerospace 2025, 12(8), 727; https://doi.org/10.3390/aerospace12080727 - 15 Aug 2025

Viewed by 201

Abstract

Due to the restrictions associated with the actual deployment time, the flight performance of traditional aerostat systems in the climbing process needs to be improved to reduce the climbing time and the horizontal movement. This paper presents a scheme comprising a dual-balloon system, [...] Read more.

Due to the restrictions associated with the actual deployment time, the flight performance of traditional aerostat systems in the climbing process needs to be improved to reduce the climbing time and the horizontal movement. This paper presents a scheme comprising a dual-balloon system, including an assisting system and a station-keeping system. In this study, a thermal and dynamic model for an aerostat system in the climbing course was established. To verify the theoretical model, flight experiments including traditional and improved aerostat systems were conducted. The performance of the improved aerostat system was compared with that of the traditional aerostat system. In addition, in this paper, the effects of helium mass in the tow balloon and payload mass on the climbing performance and equilibrium height of the improved aerostat system are discussed in detail. The results demonstrate that larger tow balloon volume does not guarantee better performance. With a fixed payload mass, equilibrium height initially rises sharply with helium mass but soon plateaus. Compared to traditional zero-pressure balloons, the dual-balloon system cuts ascent time by two-thirds. The proposed conceptual design and theoretical model could be a pathway towards achieving rapid deployment in high-altitude dual-balloon systems. Full article

(This article belongs to the Special Issue Design, Characterization and Operations of Lighter-than-Air Flying Vehicles)

► Show Figures

Figure 1

22 pages, 2608 KiB

Open AccessArticle

Fast Buckling Analysis of Stiffened Composite Structures for Preliminary Aerospace Design

by Dimitrios G. Stamatelos and George N. Labeas

Aerospace 2025, 12(8), 726; https://doi.org/10.3390/aerospace12080726 - 14 Aug 2025

Viewed by 180

Abstract

Predicting buckling in large-scale composite structures is hindered by the need for highly detailed Finite Element (FE) models, which are computationally expensive and impractical for early-stage design iterations. This study introduces a macromodelling buckling framework that reduces those models to plate-level size without [...] Read more.

Predicting buckling in large-scale composite structures is hindered by the need for highly detailed Finite Element (FE) models, which are computationally expensive and impractical for early-stage design iterations. This study introduces a macromodelling buckling framework that reduces those models to plate-level size without sacrificing accuracy. An equivalent bending stiffness matrix is derived from strain–energy equivalence, rigorously retaining orthotropic in-plane terms, bending–extensional coupling, and—crucially—the eccentricity of compressive loads about an unsymmetrically stiffened mid-plane, effects overlooked by conventional Parallel-Axis smearing. These stiffness terms contribute to closed-form analytical solutions for homogeneous orthotropic plates, providing millisecond-level evaluations ideal for gradient-based design optimisation. The method is benchmarked against detailed FE simulations of panels with three to ten stringers under longitudinal and transverse compression, showing less than 5% deviation in critical load prediction. Its utility is demonstrated in the sizing optimisation of the upper cover of a scaled Airbus A330 composite wing-box, where the proposed model explores the design space in minutes on a standard workstation, orders of magnitude faster than full FE analyses. By combining analytical plate theory, enhanced smearing, and rapid optimisation capability, the framework provides an accurate, ultra-fast tool for buckling analysis and the preliminary design of large-scale stiffened composite structures. Full article

(This article belongs to the Section Aeronautics)

► Show Figures

Figure 1

26 pages, 8392 KiB

Open AccessArticle

A Framework for an ML-Based Predictive Turbofan Engine Health Model

by Jin-Sol Jung, Changmin Son, Andrew Rimell and Rory J. Clarkson

Aerospace 2025, 12(8), 725; https://doi.org/10.3390/aerospace12080725 - 14 Aug 2025

Viewed by 362

Abstract

A predictive health modeling framework was developed for a family of turbofan engines, focusing on early detection of performance degradation. Turbine Gas Temperature (TGT) was employed as the primary indicator of engine health within the model, due to its strong correlation with core [...] Read more.

A predictive health modeling framework was developed for a family of turbofan engines, focusing on early detection of performance degradation. Turbine Gas Temperature (TGT) was employed as the primary indicator of engine health within the model, due to its strong correlation with core engine performance and thermal stress. The present research uses engine health monitoring (EHM) data acquired from in-service turbofan family engines. TGT is typically measured downstream of the high-pressure turbine stage and is regarded as the key thermodynamic variable of the gas turbine cycle. Three new training approaches were proposed using data segmentation based on time between major overhauls and compared with the conventional train–test split method. Detrending was employed to effectively remove trends and seasonality, enabling the ML-based model to learn more intrinsic relationships. Large generalized models based on the entire engine family were also investigated. Prediction performance was evaluated using selected machine learning (ML) models, including both linear and nonlinear algorithms, as well as a long short-term memory (LSTM) approach. The models were compared based on accuracy and other relevant performance metrics. The prediction accuracies of ML models depend on the selection of data size and segmentation for training and testing. For individual engines, the proposed training approaches predicted TGT with the accuracy of 4 ^∘C to 6 ^∘C in root mean square error (RMSE) by utilizing 65% less data than the train (80%)–test (20%) split method. Utilizing the data of each family engine, the large generalized model achieved similar prediction accuracy in RMSE with a smaller interquartile range. However, the amount of data required was 45–300 times larger than the proposed approaches. The sensitivity of prediction accuracy to the size of the training dataset offers valuable insights into the framework’s applicability, even for engines with limited data availability. Uncertainty quantification showed a coverage width criterion (CWC) between 29 ^∘C and 40 ^∘C, varying with different family engines. Full article

(This article belongs to the Section Aeronautics)

► Show Figures

Figure 1

24 pages, 3805 KiB

Open AccessArticle

Digital Transformation in Aircraft Design and Certification: Developing Requirements for Modeling Regulatory Documentation

by Andréa Cartile, Catharine Marsden and Susan Liscouët-Hanke

Aerospace 2025, 12(8), 724; https://doi.org/10.3390/aerospace12080724 - 13 Aug 2025

Viewed by 203

Abstract

Aircraft design and development is complex and regulated by increasingly stringent regulatory documentation. While many disciplines manage design complexity with well-established digital tools, digital transformation of the certification process remains in the early stages of implementation. Models are often used to provide explicit [...] Read more.

Aircraft design and development is complex and regulated by increasingly stringent regulatory documentation. While many disciplines manage design complexity with well-established digital tools, digital transformation of the certification process remains in the early stages of implementation. Models are often used to provide explicit structures to facilitate digital transformation. While several modeling approaches have been applied to regulatory documentation, a gap remains for an established list of requirements for developing effective models in the context of digital transformation. This paper proposes a list of requirements using a requirements elicitation framework adapted from the International Council on Systems Engineering (INCOSE) Needs and Requirements Manual. The adapted research methodology includes problem identification, needs assessment, and requirements development processes. The resulting requirements are validated against needs statements and verified against selected INCOSE requirement statement criteria. Four requirements are selected for a detailed feasibility assessment, which compares the efficacy of process mapping, Unified Modeling Language (UML), and ontological modeling methods to realize the requirements. Full article

(This article belongs to the Special Issue Airworthiness, Safety and Reliability of Aircraft)

► Show Figures

Figure 1

20 pages, 13166 KiB

Open AccessArticle

Flow and Flame Stabilization in Scramjet Engine Combustor with Two Opposing Cavity Flameholders

by Jayson C. Small, Liwei Zhang, Bruce G. Crawford and Valerio Viti

Aerospace 2025, 12(8), 723; https://doi.org/10.3390/aerospace12080723 - 13 Aug 2025

Viewed by 195

Abstract

Scramjet operation requires a comprehensive understanding of the internal flowfield, encompassing fuel–air mixing and combustion. This study investigates transient flow and flame development within a HIFiRE-2 scramjet engine combustor, which features two opposing cavities and dual sets of fuel injectors—the upstream (primary) and [...] Read more.

Scramjet operation requires a comprehensive understanding of the internal flowfield, encompassing fuel–air mixing and combustion. This study investigates transient flow and flame development within a HIFiRE-2 scramjet engine combustor, which features two opposing cavities and dual sets of fuel injectors—the upstream (primary) and downstream (secondary) injectors. These cavities function as flameholders, creating circulating flows with elevated temperatures and pressures. Shock waves form both ahead of fuel plumes and at the diverging and converging sections of the flowpath. Special attention is given to the interactions among these shock waves and the shear layers along the supersonic core flow as the system progresses towards a quasi-steady state. Driven by increased backpressure, bow shocks and disturbances induced by the normal, secondary fuel injection and the inclined, primary fuel injection move upstream, amplifying the cavity pressure. These shocks generate adverse pressure gradients, causing near-wall flow separation adjacent to both injector sets, which enhances the penetration and dispersion of fuel plumes. Once a quasi-steady state is achieved, a feedback loop is established between dynamic wave motions and combustion processes, resulting in sustained entrainment of reactive mixtures into the cavities. This mechanism facilitates stable combustion in the cavities and near-wall separation zones. Full article

(This article belongs to the Special Issue Advances in Thermal Fluid, Dynamics and Control)

► Show Figures

Figure 1

19 pages, 951 KiB

Open AccessArticle

Interpreting Decision-Making Behavior in AI-Piloted Aircraft in Aerial Combat Scenarios: An Approach to Enhance Human-AI Trust

by Zhouwei Lou, Weiyi Ge and Ke Xie

Aerospace 2025, 12(8), 722; https://doi.org/10.3390/aerospace12080722 - 13 Aug 2025

Viewed by 185

Abstract

With the continuous advancement of artificial intelligence (AI) technology, AI algorithms have demonstrated exceptional aircraft control capabilities in highly dynamic and complex scenarios such as aerial combat. However, the inherent lack of explainability in AI algorithms poses a significant challenge to gaining sufficient [...] Read more.

With the continuous advancement of artificial intelligence (AI) technology, AI algorithms have demonstrated exceptional aircraft control capabilities in highly dynamic and complex scenarios such as aerial combat. However, the inherent lack of explainability in AI algorithms poses a significant challenge to gaining sufficient trust, presenting potential safety risks that could lead to aircraft loss of control. This limitation hinders the widespread adoption of AI in practical applications. To enhance human–AI trust, improve system stability and safety, and advance the deployment of AI algorithms in practical settings, this study proposes an approach to describe and explain AI decision-making behaviors using natural language. Natural language is a straightforward medium for expressing information, which avoids the need for additional decoding or interpretation, particularly in rapidly changing battlefield environments, enabling pilots to quickly comprehend the intentions of AI algorithms and thereby fostering trust in AI systems. This study constructs a dataset of AI decision behavior description and interpretation based on adversarial temporal data in an aerial combat scenario and introduces an encoder–decoder framework that integrates an attentional mechanism. Findings from the experiments suggest that this approach effectively delineates and elucidates the AI decision-making behaviors, thereby facilitating mutual trust between humans and AI. Full article

(This article belongs to the Section Aeronautics)

► Show Figures

Figure 1

17 pages, 1922 KiB

Open AccessArticle

A Road-Level Transport Network Model with Microscopic Operational Features for Aircraft Taxi-Out Time Prediction

by Xiaowei Tang, Wenjie Zhang, Shengrun Zhang and Cheng-Lung Wu

Aerospace 2025, 12(8), 721; https://doi.org/10.3390/aerospace12080721 - 13 Aug 2025

Viewed by 200

Abstract

For aircraft departure, which is a process of multi-resource coordination, strict time limitations, and complex condition constraints, the optimization of taxi-out time prediction is critical for enhancing airport surface operational efficiency, optimizing runway slot utilization, and reducing aircraft ground delay and fuel consumption. [...] Read more.

For aircraft departure, which is a process of multi-resource coordination, strict time limitations, and complex condition constraints, the optimization of taxi-out time prediction is critical for enhancing airport surface operational efficiency, optimizing runway slot utilization, and reducing aircraft ground delay and fuel consumption. By combining aircraft taxi path and network traffic flow features, a refined airport road-level transport network model is constructed to accurately characterize the taxi path topology and node-edge attributes. On this basis, two new micro-features are introduced: estimated taxi time and the number of handovers. Experimental results show that after the introduction of the micro-features, the prediction accuracy of the taxi-out time prediction model within the error of 1 min increases from 49.29% to 54.41%, and the prediction accuracy within the error of 5 min reaches 99.42%. This method effectively addresses the limitations of traditional models that focus solely on the overall taxiing process while neglecting microscopic airfield network dynamics and time consumption during control handover procedures. The method can be integrated into the Airport Collaborative Decision Making (A-CDM) system to provide minute-level support for departure taxi-out time prediction, thereby providing a more precise and operationally aligned temporal benchmark for intelligent apron operations scheduling, aircraft sequencing optimization, and other collaborative decision making processes. Full article

(This article belongs to the Collection Air Transportation—Operations and Management)

► Show Figures

Figure 1

29 pages, 40314 KiB

Open AccessArticle

Efficient Uncertainty Quantification for Satellite Antenna Pointing: A GSA-PEM Framework Integrating Multi-Source Disturbances

by Shiyu Tan, Ning Zhang, Yingyong Shen, Cong Wang and Jingbo Gao

Aerospace 2025, 12(8), 720; https://doi.org/10.3390/aerospace12080720 - 13 Aug 2025

Viewed by 269

Abstract

Space-borne antenna pointing is affected by uncertain disturbances like satellite attitude, structural flexibility, and manufacturing/installation errors. Understanding the effect of these uncertainties is crucial for antenna performance. The main contribution of this paper is the proposal of an uncertainty quantification (UQ) framework for [...] Read more.

Space-borne antenna pointing is affected by uncertain disturbances like satellite attitude, structural flexibility, and manufacturing/installation errors. Understanding the effect of these uncertainties is crucial for antenna performance. The main contribution of this paper is the proposal of an uncertainty quantification (UQ) framework for antenna pointing performance that integrates the Global Sensitivity Analysis (GSA) method and Point Estimate Method (PEM), named the GSA-PEM Integrated Framework (GSA-PEM in short). This framework enables systematic analysis of how uncertain parameters (satellite attitude, manufacturing/installation errors, joint rotation, structural deformation, feed displacement, etc.) impact antenna pointing. It establishes a pointing model via coordinate transformation, utilizes the total-effect of the Sobol method to prioritize the key parameters for reliability analysis, and computes pointing performance statistics characteristic via PEM to evaluate pointing reliability. Two case studies are presented to validate the accuracy and efficiency of the proposed framework. Monte Carlo Simulation (MCS) and the Maximum Entropy method using the Fractional-order Moments (ME-FMs) are comparison methods. Results demonstrate that the proposed framework achieves a trade-off between accuracy and efficiency in assessing antenna pointing performance under parameter uncertainty. Full article

(This article belongs to the Section Astronautics & Space Science)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Aerospace, Volume 12, Issue 8 (August 2025) – 102 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI