Aerospace

21 pages, 827 KiB

Open AccessArticle

ELVO-Based Autonomous Satellite Collision Avoidance with Multiple Debris

by Ziyao Li, Hongchao Li and Chanying Li

Aerospace 2025, 12(5), 402; https://doi.org/10.3390/aerospace12050402 - 1 May 2025

The frequent occurrence of space debris collision incidents has made research on autonomous satellite avoidance necessary. Against this backdrop, the paper presents a short-term autonomous space debris avoidance algorithm based on the Equivalent Linear Velocity Obstacle (ELVO) paradigm, which addresses the challenges of [...] Read more.

The frequent occurrence of space debris collision incidents has made research on autonomous satellite avoidance necessary. Against this backdrop, the paper presents a short-term autonomous space debris avoidance algorithm based on the Equivalent Linear Velocity Obstacle (ELVO) paradigm, which addresses the challenges of multiple debris scenarios and real-time decision-making. Error analysis and compensating terms are provided to enhance the algorithm’s accuracy. Simulations are proposed to validate the algorithm, and the simplified design reduces the online computational load, demonstrating its feasibility for future on-orbit usage. Full article

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

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19 pages, 2432 KiB

Open AccessArticle

Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design Environment

by Dominik Eisenhut, Andreas Bender, Niclas Grüning, Jonas Mangold and Andreas Strohmayer

Aerospace 2025, 12(5), 401; https://doi.org/10.3390/aerospace12050401 - 1 May 2025

Abstract

To tackle climate change, aircraft designers envision new aircraft concepts which promise to reduce greenhouse gas emissions and enable greener flights. One option is hybrid-electric propulsion architectures. The University of Stuttgart has built and operates such an aircraft, called the e-Genius. This paper [...] Read more.

To tackle climate change, aircraft designers envision new aircraft concepts which promise to reduce greenhouse gas emissions and enable greener flights. One option is hybrid-electric propulsion architectures. The University of Stuttgart has built and operates such an aircraft, called the e-Genius. This paper aims to demonstrate how far a digital twin is able to replicate a real-world flight using a simplified mission definition and to estimate the range limit for a high-performance hybrid-electric aircraft, lifting the operational constraints faced in the real-world environment. First a digital twin is built and compared to actual flight data to calibrate the model. Next, a comparison with a full flight is performed, using a long-range flight of 2000 km for this purpose. Due to the duration of this flight, weather conditions like wind need to be considered. Validation is performed by comparison to two additional missions, one 500 km mission flown at faster speed and a 1000 km mission flown at a similar speed. To estimate the maximum range based on this calibrated model, operational constraints like daylight and maximum flight time are lifted to see the further potential of the aircraft. This allows the aircraft to fly more slowly, at best cruise speed, and thus estimate the maximum range of the aircraft. Results show good agreement with flight tests for fuel burnt, highlighting however a need to measure additional parameters in future flights. Overall, the model allows us to plan future flights and assess the feasibility of new projects. Full article

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24 pages, 1196 KiB

Open AccessArticle

Integrated Guidance and Control for Strap-Down Flight Vehicle: A Deep Reinforcement Learning Approach

by Qinglong Zhang, Bin Zhao, Yifu Jiang, Jingyan Zhang and Jiale Zhang

Aerospace 2025, 12(5), 400; https://doi.org/10.3390/aerospace12050400 - 1 May 2025

Abstract

This paper proposes a three-dimensional (3D) deep reinforcement learning-based integrated guidance and control (DRLIGC) method, which is restricted by the narrow field-of-view (FOV) constraint of the strap-down seeker. By leveraging the data-driven nature of the deep reinforcement learning (DRL) algorithm, this method mitigates [...] Read more.

This paper proposes a three-dimensional (3D) deep reinforcement learning-based integrated guidance and control (DRLIGC) method, which is restricted by the narrow field-of-view (FOV) constraint of the strap-down seeker. By leveraging the data-driven nature of the deep reinforcement learning (DRL) algorithm, this method mitigates the challenges associated with integrated guidance and control (IGC) method design arising from model dependencies, thereby addressing the inherent complexity of the IGC model. Firstly, according to different states and actions, the pitch and yaw channels of the six-degree-of-freedom (6-DOF) IGC model are modeled as Markov decision processes (MDPs). Secondly, a channel-by-channel progressive training method based on the twin delayed deep deterministic policy gradient (TD3) algorithm is proposed. The agents of the pitch and yaw channels are trained using the TD3 algorithm independently, which substantially alleviates the complexity of the training process, while the roll channel is stabilized through the application of the back-stepping method. Thirdly, a comprehensive reward function is designed to simultaneously address the narrow FOV constraint and enhance the target engagement capability. Additionally, this function mitigates the issue of sparse rewards to some extent. Through Monte Carlo (MC) and comparative simulation verification, it is shown that the DRLIGC method proposed in this paper can effectively approach the target while maintaining the narrow FOV constraint and also has good robustness. Full article

(This article belongs to the Special Issue Integrated Guidance and Control for Aerospace Vehicles)

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36 pages, 6529 KiB

Open AccessReview

A Review of Wavefront Sensing and Control Based on Data-Driven Methods

by Ye Zhang, Qichang An, Min Yang, Lin Ma and Liang Wang

Aerospace 2025, 12(5), 399; https://doi.org/10.3390/aerospace12050399 - 30 Apr 2025

Abstract

Optical systems suffer from wavefront aberrations due to complex atmospheric environments and system component errors, leading to systematic aberrations and significantly degrading optical field quality. Therefore, the detection and correction of optical aberrations are crucial for efficient and accurate observations. To fully utilize [...] Read more.

Optical systems suffer from wavefront aberrations due to complex atmospheric environments and system component errors, leading to systematic aberrations and significantly degrading optical field quality. Therefore, the detection and correction of optical aberrations are crucial for efficient and accurate observations. To fully utilize the capabilities of observation equipment and achieve high-efficiency, accurate imaging, it is essential to develop wavefront correction technologies that enable ultra-precise wavefront control. The application of data-driven techniques in wavefront correction can effectively enhance correction performance and better address complex environmental challenges. This paper elaborates on the research progress of data-driven methods in wavefront correction from three aspects: principles, current research status, and practical applications. It analyzes the performance of data-driven methods in diverse real-world scenarios and discusses future trends in the deep integration of data-driven approaches with optical technologies. This work provides valuable guidance for advancing wavefront correction methodologies. Full article

(This article belongs to the Special Issue Situational Awareness Using Space-Based Sensor Networks)

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29 pages, 1781 KiB

Open AccessArticle

Multi-Stand Grouped Operations Method in Airport Bay Area Based on Deep Reinforcement Learning

by Jie Ouyang, Changqing Zhu, Xiaowei Tang and Jian Zhang

Aerospace 2025, 12(5), 398; https://doi.org/10.3390/aerospace12050398 - 30 Apr 2025

Abstract

To address the trade-off between safety levels and operational efficiency in the Bay Area, this study proposes a Multi-Stand Grouped Operations method based on deep reinforcement learning under the consideration of the safety domain. The full-process operation of aircraft within the Bay Area [...] Read more.

To address the trade-off between safety levels and operational efficiency in the Bay Area, this study proposes a Multi-Stand Grouped Operations method based on deep reinforcement learning under the consideration of the safety domain. The full-process operation of aircraft within the Bay Area is analyzed to identify key operational spots. Safety domains are then established based on path conflicts arising from aircraft movements and safety conflicts caused by minimum separation distances and wake vortex effects. These domains are used to define corresponding safe operating spaces and construct an optimized operational model for the Bay Area. A multi-agent reinforcement learning algorithm is employed to solve the model, deriving an optimized stand allocation plan and Multi-Stand Grouped Operations strategy. To evaluate the effectiveness of the optimization, real flight data from the northwest Bay Area of Terminal 2 at Guangzhou Baiyun Airport are used for validation. Compared to the original stand allocation scheme, the optimized stand allocation and Multi-Stand Grouped Operations strategy reduce aircraft delay times by 62.45%, demonstrating that the proposed model effectively enhances operational efficiency in the Bay Area. Full article

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

16 pages, 1654 KiB

Open AccessArticle

A Deterministic-Stochastic Hybrid Integrator for Random Ordinary Differential Equations with Aerospace Applications

by Carmine Giordano

Aerospace 2025, 12(5), 397; https://doi.org/10.3390/aerospace12050397 - 30 Apr 2025

Abstract

High-fidelity propagation of dynamical systems can become a cumbersome task when dealing with uncertainties modeled as random processes. The random ordinary differential equations usually describing the uncertain dynamics can be numerically integrated, but they are challenging from the computational point of view. Traditional [...] Read more.

High-fidelity propagation of dynamical systems can become a cumbersome task when dealing with uncertainties modeled as random processes. The random ordinary differential equations usually describing the uncertain dynamics can be numerically integrated, but they are challenging from the computational point of view. Traditional methods usually require either the storage of a relevant amount of data or small integration steps. In this work, a hybrid method, embedding a stochastic integration method in a deterministic higher-order scheme, is conceived to obtain fast and stochastically correct results. The method is used for uncertainty propagation and quantification of aerospace problems. Results show a reduction of at least one order of magnitude for both computational time and memory usage with respect to state-of-the-art techniques, while it is able to provide statistically correct results. Full article

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

24 pages, 3314 KiB

Open AccessArticle

Safety Assessment Method for Parallel Runway Approach Based on MC-EVT for Quantitative Estimation of Collision Probability

by Yike Li, Honghai Zhang, Zongbei Shi, Jinlun Zhou and Wenqing Li

Aerospace 2025, 12(5), 396; https://doi.org/10.3390/aerospace12050396 - 30 Apr 2025

Abstract

The construction of parallel runways is an effective solution to address the constraints of urban land resources and mitigate flight delays caused by the increasing volume of air traffic. To ensure the safety of parallel approach operations and further enhance operational efficiency, this [...] Read more.

The construction of parallel runways is an effective solution to address the constraints of urban land resources and mitigate flight delays caused by the increasing volume of air traffic. To ensure the safety of parallel approach operations and further enhance operational efficiency, this study proposes a quantitative safety risk assessment method for parallel approaches based on Monte Carlo simulation (MCS) and extreme value theory (EVT). Taking a parallel runway at a major airport in Southwest China as a case study, historical Automatic Dependent Surveillance-Broadcast (ADS-B) trajectory data were processed and analyzed to derive traffic flow characteristics and the actual distribution of approach performance. Subsequently, we developed a collision probability estimation model for parallel approaches based on Monte Carlo–extreme value theory (MC-EVT). Monte Carlo simulation was employed to conduct simulation experiments on the parallel approach process, and the collision risk was quantitatively assessed by integrating experimental data with an analysis based on extreme value theory. Finally, taking the parallel runways of a major airport in southwest China as a case study, experiments were conducted under various parallel approach scenarios to quantitatively assess the collision risk between aircraft. The experimental results indicate that the MC-EVT-based safety risk assessment method for parallel approaches reduces the reliance on traffic flow assumptions. Compared to the conventional Monte Carlo method, it achieves a faster convergence rate, significantly reduces computational workload, and improves computational efficiency by a factor of ten, thus demonstrating that the proposed method is capable of accurately and effectively quantifying low-probability collision risks. Furthermore, the findings reveal a strong correlation between parallel runway width and collision risk. The approach risk under a mixed-aircraft-type configuration is higher than that of a single-aircraft-type configuration, while offset approaches can enhance approach safety. This study can provide valuable references for the construction of parallel runways and the development of regulatory frameworks for parallel approach operations in China. Full article

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

19 pages, 1289 KiB

Open AccessArticle

A Dynamic Multi-Graph Convolutional Spatial-Temporal Network for Airport Arrival Flow Prediction

by Yunyang Huang, Hongyu Yang and Zhen Yan

Aerospace 2025, 12(5), 395; https://doi.org/10.3390/aerospace12050395 - 30 Apr 2025

Abstract

In air traffic systems, aircraft trajectories between airports are monitored by the radar networking system forming dynamic air traffic flow. Accurate airport arrival flow prediction is significant in implementing large-scale intelligent air traffic flow management. Despite years of studies to improve prediction precision, [...] Read more.

In air traffic systems, aircraft trajectories between airports are monitored by the radar networking system forming dynamic air traffic flow. Accurate airport arrival flow prediction is significant in implementing large-scale intelligent air traffic flow management. Despite years of studies to improve prediction precision, most existing methods only focus on a single airport or simplify the traffic network as a static and simple graph. To mitigate this shortage, we propose a hybrid neural network method, called Dynamic Multi-graph Convolutional Spatial-Temporal Network (DMCSTN), to predict network-level airport arrival flow considering the multiple operation constraints and flight interactions among airport nodes. Specifically, in the spatial dimension, a novel dynamic multi-graph convolutional network is designed to adaptively model the heterogeneous and dynamic airport networks. It enables the proposed model to dynamically capture informative spatial correlations according to the input traffic features. In the temporal dimension, an enhanced self-attention mechanism is utilized to mine the arrival flow evolution patterns. Experiments on a real-world dataset from an ATFM system validate the effectiveness of DMCSTN for arrival flow forecasting tasks. Full article

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

25 pages, 2083 KiB

Open AccessArticle

Investigation of Heat and Drag Reduction Induced by Forward-Facing Cavity in Hypersonic Flow

by Ning Ding, Jianlong Chang and Junhui Liu

Aerospace 2025, 12(5), 394; https://doi.org/10.3390/aerospace12050394 - 30 Apr 2025

Abstract

The design of heat and drag reduction systems for hypersonic vehicles has garnered widespread global attention. In this study, the Navier–Stokes equations and the SST k-ω turbulence model are employed to establish a simulation model for heat and drag reduction induced by a [...] Read more.

The design of heat and drag reduction systems for hypersonic vehicles has garnered widespread global attention. In this study, the Navier–Stokes equations and the SST k-ω turbulence model are employed to establish a simulation model for heat and drag reduction induced by a forward-facing cavity. The numerical methods are validated using existing experimental results. The oscillation characteristics of the bow shock wave at the head and the shock inside the cavity in hypersonic flows are investigated. The heat and drag reduction mechanisms of the forward-facing cavity are discussed. The effects of the diameter and depth of the cavity on drag and heat reduction are comprehensively analyzed. The obtained results show that a reduction in drag and heat is achieved when a forward-facing cavity is added to the vehicle. The main reasons for this heat reduction are the cold ring mechanism and the energy conversion mechanism. The size of the cold ring is significantly affected by the cavity diameter, whereas the energy conversion mechanism is more sensitive to variations in diameter. The maximum reduction in heat load is 2.2%, and the maximum reduction in the Stanton number is 25.3%. Increases in both diameter and depth enhance drag reduction, achieving an average drag reduction of approximately 1.65%. Full article

(This article belongs to the Special Issue Thermal Protection System Design of Space Vehicles)

22 pages, 9118 KiB

Open AccessArticle

Fault-Tolerant Dynamic Allocation Strategies for Launcher Systems

by Diego Navarro-Tapia, Pedro Simplício and Andrés Marcos

Aerospace 2025, 12(5), 393; https://doi.org/10.3390/aerospace12050393 - 30 Apr 2025

Abstract

This article presents fault-tolerant dynamic allocation strategies designed to mitigate propulsion and actuation failures in launch vehicles using a clustered engine configuration. In particular, it addresses engine thrust loss and thrust vector control (TVC) jamming faults during the atmospheric ascent flight of a [...] Read more.

This article presents fault-tolerant dynamic allocation strategies designed to mitigate propulsion and actuation failures in launch vehicles using a clustered engine configuration. In particular, it addresses engine thrust loss and thrust vector control (TVC) jamming faults during the atmospheric ascent flight of a five-engine launch vehicle. Three different strategies are introduced: a fault-tolerant pseudo-inverse solution, a convex optimization-based approach, and a constrained nonlinear optimization one. These approaches are analyzed and compared at a linear design point and further evaluated using a nonlinear simulator of the launcher. The results demonstrate that these three dynamic allocation techniques are able to provide successful recovery from engine thrust loss failures (up to a certain level depending on the engine throttling capability), TVC actuator jamming failures, and simultaneous engine and actuator failures. Full article

(This article belongs to the Special Issue Modeling, Simulation, and Control of Launch Vehicles)

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25 pages, 2155 KiB

Open AccessArticle

Modeling, Altitude Control, and Trajectory Planning of a Weather Balloon Subject to Wind Disturbances

by Bruno Cândido, Catarina Rodrigues, Alexandra Moutinho and José Raul Azinheira

Aerospace 2025, 12(5), 392; https://doi.org/10.3390/aerospace12050392 - 30 Apr 2025

Abstract

Weather balloons are a popular tool to obtain atmospheric data. One of the biggest advantages of using this type of vehicle for scientific research is their inexpensiveness, as they are only composed of an inflated envelope, a parachute, and a sonde. However, their [...] Read more.

Weather balloons are a popular tool to obtain atmospheric data. One of the biggest advantages of using this type of vehicle for scientific research is their inexpensiveness, as they are only composed of an inflated envelope, a parachute, and a sonde. However, their flight is dependent on the atmospheric conditions, and their life cycle is short. Thus, altitude control for weather balloons, along with trajectory planning, is a major area of interest, as it would allow one to mitigate the disadvantages while maintaining the benefits. This article presents a novel, efficient, lightweight, and cost-effective framework for weather balloon control and path planning. The proposed solution integrates a P-D cascade controller for altitude control, adapted specifically to the dynamics and actuation constraints of weather balloons, with a wind-based trajectory planner built on the A* algorithm. To the best of the authors’ knowledge, this planner is the first to incorporate wind constraints in a grid-based search tailored for weather balloon navigation. By commanding the ballast release for ascent and helium venting for descent, the developed control solution proves efficient and robust in simulation, guiding the balloon to reach defined goals while traveling through predetermined waypoints. However, it demonstrates limitations in maintaining the balloon over a fixed area. Full article

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

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18 pages, 7618 KiB

Open AccessArticle

Assessment of Advanced Air Mobility Vehicle Integration at the Orlando International Airport

by Victor Fraticelli Rivera, Robert Thomas, Carlos Castro Peña and Sakurako Kuba

Aerospace 2025, 12(5), 391; https://doi.org/10.3390/aerospace12050391 - 30 Apr 2025

Abstract

This study aimed to assess the potential operational implications of integrating Advanced Air Mobility (AAM) traffic at the Orlando International Airport (MCO) Class Bravo airspace. Researchers developed corridor prototypes within MCO’s airspace to analyze potential traffic conflicts and wake turbulence risks between MCO’s [...] Read more.

This study aimed to assess the potential operational implications of integrating Advanced Air Mobility (AAM) traffic at the Orlando International Airport (MCO) Class Bravo airspace. Researchers developed corridor prototypes within MCO’s airspace to analyze potential traffic conflicts and wake turbulence risks between MCO’s commercial and AAM traffic. Furthermore, an AAM ecosystem at MCO was developed to enable the simultaneous integration of realistic MCO and AAM traffic paths. The ecosystem was created on a series of operational assumptions derived from the FAA’s AAM implementation plans and concepts of operation. The findings of this study revealed that the AAM ecosystem (corridor designs and operational schedule) had little to no impact on existing commercial air traffic operations based on the assumptions made for this analysis. Additionally, the assessment revealed that integrating 22 aircraft/airframes could result in an efficient operational infrastructure with no traffic or wake turbulence conflicts with existing commercial air traffic at MCO. This groundbreaking study marks one of the initial evaluations of AAM integration at a major international airport in the United States. Full article

(This article belongs to the Special Issue Operational Requirements for Urban Air Traffic Management)

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31 pages, 13096 KiB

Open AccessReview

The Data-Driven Performance Prediction of Lattice Structures: The State-of-the-Art in Properties, Future Trends, and Challenges

by Siyuan Yang, Ning Dai and Qianfeng Cao

Aerospace 2025, 12(5), 390; https://doi.org/10.3390/aerospace12050390 - 30 Apr 2025

Abstract

Lattice structures, with their unique design, offer properties like a programmable elastic modulus, an adjustable Poisson’s ratio, high specific strength, and a large specific surface area, making them the key to achieving structural lightweighting, improving impact resistance, vibration suppression, and maintaining high thermal [...] Read more.

Lattice structures, with their unique design, offer properties like a programmable elastic modulus, an adjustable Poisson’s ratio, high specific strength, and a large specific surface area, making them the key to achieving structural lightweighting, improving impact resistance, vibration suppression, and maintaining high thermal efficiency in the aerospace field. However, functional prediction and inverse design remain challenging due to cross-scale effects, extensive spatial freedom, and high computational costs. Recent advancements in AI have driven progress in predicting lattice structure functionality. This paper begins with an introduction to the lattice types, their properties, and applications. Then the development process for the performance-prediction methods of lattice structures is summarized. The current applications of performance-prediction methods, which are data-driven and related to material properties, structural properties, and performance under conditions of coupled multi-physical fields, are analyzed, and this analysis further extends to the data-driven methods in relation to their prediction of lattice structure functionality. This paper summarizes the application of data-driven methods in the prediction of the mechanical, energy absorption, acoustic, and thermal properties of lattice structures; elaborates on the application of these methods in the optimization design of lattice structures in the aerospace field; and details the relevant theory and references for the field of lattice structure performance analysis. Finally, the progress and problems in the functional prediction of lattice structures under the current research is demonstrated, and the future development direction of this field is envisioned. Full article

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23 pages, 2542 KiB

Open AccessArticle

End-to-End Deep-Learning-Based Surrogate Modeling for Supersonic Airfoil Shape Optimization

by Diogo Pereira, Frederico Afonso and Fernando Lau

Aerospace 2025, 12(5), 389; https://doi.org/10.3390/aerospace12050389 - 29 Apr 2025

Viewed by 66

Abstract

Aerodynamic shape design optimization faces challenges due to the computational demands and the vast design space, limiting its practicality and scalability. While progress has been made in subsonic and transonic regimes, the real-time optimization for supersonic conditions remains unexplored. To bridge this gap, [...] Read more.

Aerodynamic shape design optimization faces challenges due to the computational demands and the vast design space, limiting its practicality and scalability. While progress has been made in subsonic and transonic regimes, the real-time optimization for supersonic conditions remains unexplored. To bridge this gap, this work exploits knowledge learned from subsonic and transonic real-world data and introduces a rapid optimization framework tailored for the supersonic regime. A novel end-to-end multitask Convolutional Neural Network is proposed to predict the aerodynamic coefficients of an airfoil shape, extracting global and local features directly from the geometry. The surrogate model is thoroughly examined and validated, including an analysis of model explainability. The surrogate model achieves on par results with the state-of-the-art, with relative errors in aerodynamic coefficient predictions below 1.7%. Furthermore, a surrogate-based optimization strategy integrates the surrogate model with a Generative Adversarial Network to generate realistic airfoil shapes, thereby reducing the design space to a low-dimensional representation. This approach provides a robust solution that accelerates the optimization routine by over 3000 times when compared to simulation-based methods while achieving a deviation of less than 1.9% from their optimum performance. Overall, this work strikes a balance between efficiency and effectiveness without compromising reliability. Full article

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

25 pages, 5501 KiB

Open AccessArticle

Impact Analysis of Temperature Effects on the Performance of the Pick-Up Ion Analyzer

by Yu Cao, Yuzhu Zhang, Xiaodong Peng, Changbin Xue, Bin Su and Yiming Zhu

Aerospace 2025, 12(5), 388; https://doi.org/10.3390/aerospace12050388 - 29 Apr 2025

Viewed by 63

Abstract

In deep-space exploration, Pickup Ion Analyzers (PUIAs) operate under varying thermal environments in orbit, where thermally induced stress–deformation coupling may severely degrade their performance and long-term stability. To address temperature field analysis for in-orbit PUIAs, in this study, we propose a coupled simulation [...] Read more.

In deep-space exploration, Pickup Ion Analyzers (PUIAs) operate under varying thermal environments in orbit, where thermally induced stress–deformation coupling may severely degrade their performance and long-term stability. To address temperature field analysis for in-orbit PUIAs, in this study, we propose a coupled simulation framework integrating external heat flux, parallel temperature field calculation, and thermoelastic deformation analysis, establishing a systematic link from thermal inputs to performance analysis. Based on external heat flux results, a parallel LU decomposition algorithm reduced the computational time from 11.8 h to 2.9 h for rapid temperature field solutions. At 38 astronomical units (AUs), the instrument’s temperature distribution ranged from −45 °C to 51.13 °C, with simulation errors compared to COMSOL simulations meeting engineering accuracy requirements. Maximum thermoelastic deformation induced by thermal gradients reached 0.110 mm. Performance degradation due to deformation in key metrics—including ion energy resolution, angular resolution, detection field-of-view, geometric factor, and mass resolution—was below 7.2%. This research improves the computational efficiency of the temperature field and systematically quantifies temperature effects on PUIA performance in deep-space environments, and the proposed methodology could provide technical support for optimizing on-orbit thermal management strategies. Full article

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

28 pages, 33753 KiB

Open AccessArticle

Framework for the Multi-Objective Design Optimization of Aerocapture Missions

by Segundo Urraza Atue and Paul Bruce

Aerospace 2025, 12(5), 387; https://doi.org/10.3390/aerospace12050387 - 29 Apr 2025

Viewed by 53

Abstract

Developing spacecraft for efficient aerocapture missions demands managing extreme aerothermal environments, precise controls, and atmospheric uncertainties. Successful designs must integrate vehicle airframe considerations with trajectory planning, adhering to launcher dimension constraints and ensuring robustness against atmospheric and insertion uncertainties. To advance robust multi-objective [...] Read more.

Developing spacecraft for efficient aerocapture missions demands managing extreme aerothermal environments, precise controls, and atmospheric uncertainties. Successful designs must integrate vehicle airframe considerations with trajectory planning, adhering to launcher dimension constraints and ensuring robustness against atmospheric and insertion uncertainties. To advance robust multi-objective optimization in this field, a new framework is presented, designed to rapidly analyze and optimize non-thrusting, fixed angle-of-attack aerocapture-capable spacecraft and their trajectories. The framework employs a three-degree-of-freedom atmospheric flight dynamics model incorporating planet-specific characteristics. Aerothermal effects are approximated using established Sutton–Graves, Tauber–Sutton, and Stefan–Boltzmann relations. The framework computes the resulting post-atmospheric pass orbit using an orbital element determination algorithm to estimate fuel requirements for orbital corrective maneuvers. A novel algorithm that consolidates multiple objective functions into a unified cost function is presented and demonstrated to achieve superior optima with computational efficiency compared to traditional multi-objective optimization approaches. Numerical examples demonstrate the methodology’s effectiveness and computational cost at optimizing terrestrial and Martian aerocapture maneuvers for minimum fuel, heat loads, peak heat transfers, and an overall optimal trajectory, including volumetric considerations. Full article

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

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19 pages, 2317 KiB

Open AccessArticle

Incremental GA-Based 3D Trajectory Optimization for Powered Parachute Aerial Delivery Systems

by Hanafy M. Omar and Ayman Hamdy Kassem

Aerospace 2025, 12(5), 386; https://doi.org/10.3390/aerospace12050386 - 29 Apr 2025

Viewed by 57

Abstract

This paper presents an offline optimal trajectory planning method for powered parachutes (PPCs) using dynamic model simulations, emphasizing their potential in applications such as remote sensing and aerial delivery systems. A six-degrees-of-freedom (6-DOF) dynamic model of the PPC is developed, complemented by a [...] Read more.

This paper presents an offline optimal trajectory planning method for powered parachutes (PPCs) using dynamic model simulations, emphasizing their potential in applications such as remote sensing and aerial delivery systems. A six-degrees-of-freedom (6-DOF) dynamic model of the PPC is developed, complemented by a novel optimization technique called Incremented Genetic Algorithms (IGA). IGA improve the computational efficiency by dynamically increasing the number of variables only when optimization goals are unmet, eliminating the need to predefine input variable counts. This approach significantly reduces the computational time and CPU usage while maintaining cost-effectiveness for 3D trajectory planning. The proposed method was validated on three trajectories under diverse constraints, including the time, position, and predefined obstacles. The results demonstrate that IGA can effectively generate optimal trajectories using a single control parameter (the parachute steering angle) and a minimal number of control points, showcasing its practicality and efficiency. Full article

(This article belongs to the Section Aeronautics)

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27 pages, 6906 KiB

Open AccessArticle

Error Covariance Analyses for Celestial Triangulation and Its Optimality: Improved Linear Optimal Sine Triangulation

by Abdurrahim Muratoglu, Halil Ersin Söken and Uwe Soergel

Aerospace 2025, 12(5), 385; https://doi.org/10.3390/aerospace12050385 - 29 Apr 2025

Viewed by 59

Abstract

This study presents an improved methodology for celestial triangulation optimization in spacecraft navigation, addressing limitations in existing approaches. While current methods like Linear Optimal Sine Triangulation (LOST) provide statistically optimal solutions for position estimation using multiple celestial body observations, their performance can be [...] Read more.

This study presents an improved methodology for celestial triangulation optimization in spacecraft navigation, addressing limitations in existing approaches. While current methods like Linear Optimal Sine Triangulation (LOST) provide statistically optimal solutions for position estimation using multiple celestial body observations, their performance can be compromised by suboptimal measurement pair selection. The proposed approach, called the Improved-LOST algorithm, introduces a systematic method for evaluating and selecting optimal measurement pairs based on a Cramér–Rao Lower-Bound (CRLB) analysis. Through theoretical analysis and numerical simulations on translunar trajectories, this study demonstrates that geometric configuration significantly influences position estimation accuracy, with error variances varying by orders of magnitude depending on observation geometry. The improved algorithm outperforms conventional implementations, particularly in scenarios with challenging geometric configurations. Simulation results along a translunar trajectory using various celestial body combinations show that the systematic selection of measurement pairs based on CRLB minimization leads to enhanced estimation accuracy compared to arbitrary pair selection. The findings provide valuable insights for autonomous navigation system design and mission planning, offering a quantitative framework for assessing and optimizing celestial triangulation performance in deep space missions. Full article

(This article belongs to the Special Issue 14th EASN International Conference on Innovation in Aviation & Space towards Sustainability Today & Tomorrow)

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23 pages, 19131 KiB

Open AccessArticle

Experimental Study on the Icing of Rotating Intake Cones in Wind Tunnels Under Supercooled Large-Droplet Conditions

by Zhiqiang Zhang, Huanyu Zhao, Dongyu Zhu, Hao Dai and Zhengzhi Wang

Aerospace 2025, 12(5), 384; https://doi.org/10.3390/aerospace12050384 - 29 Apr 2025

Viewed by 116

Abstract

Supercooled droplets that collide with the windward surface of the aircraft will freeze, which results in icing on both stationary and rotating components. The ice accretion on rotating surfaces is physically different from those on stationary components. The icing phenomenon on the surface [...] Read more.

Supercooled droplets that collide with the windward surface of the aircraft will freeze, which results in icing on both stationary and rotating components. The ice accretion on rotating surfaces is physically different from those on stationary components. The icing phenomenon on the surface of a rotating intake cone was investigated in an icing wind tunnel, and the influence of icing conditions of supercooled large droplets on the experimental results was analyzed. In the experiments, the ice accretion of the intake cone was studied under various conditions, including rotational speed, wind speed, icing temperature, droplet diameter, and icing time. The ice shape on the surface of the intake cone is notably unique due to the influence of centrifugal force, which produces a longer feather-like ice structure that has a significant effect on the performance of the engine. The process of ice shedding caused by centrifugal force is also critical for the engine anti-icing process. Therefore, it is essential to study the icing characteristics under rotational effects during the design and verification process of engine anti-icing systems. Full article

(This article belongs to the Special Issue Aerospace Anti-icing Systems)

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17 pages, 6163 KiB

Open AccessArticle

Investigation of Skin–Stringer Assembly Made with Adhesive and Mechanical Methods on Aircraft

by Hacı Abdullah Tasdemir, Berke Alp Mirza and Yunus Hüseyin Erkendirci

Aerospace 2025, 12(5), 383; https://doi.org/10.3390/aerospace12050383 - 29 Apr 2025

Viewed by 115

Abstract

New assembly methods for aircraft structural parts, such as skins and stringers, are being investigated to address issues like galvanic corrosion, stress concentration, and weight. For this, many researchers are examining the mechanical and fracture properties of adhesively bonded parts through experimental testing [...] Read more.

New assembly methods for aircraft structural parts, such as skins and stringers, are being investigated to address issues like galvanic corrosion, stress concentration, and weight. For this, many researchers are examining the mechanical and fracture properties of adhesively bonded parts through experimental testing and numerical modelling methods, including Cohesive Zone Modelling (CZM), Compliance-Based Beam Method (CBBM), Double Cantilever Beam (DCB), and End Notched Flexural (ENF) tests. In this study, similarly, DCB and ENF tests were conducted on skin and beam parts bonded with AF163-2K adhesive using CBBM and then modelled and analysed in ABAQUS CAE 2018 software. Four different skin–stringer connection models were analysed, respectively, using only adhesive, only rivets, both adhesive and rivets, and also a reduced number of rivets in the adhesively bonded joint. This study found that adhesive increased initial strength, while rivets improved strength after the adhesive began to crack. Using a hybrid connection that combines both rivets and adhesive has been observed to enhance the overall strength and durability of the assembly. Then, experimental results were compared, and four numerical models for skin–stringer connections (adhesive only, rivets only, adhesive and rivets, and adhesive with reduced rivets) were analysed and discussed. In this context, the results were supported and reported with graphs, tables, and analysis images. Full article

(This article belongs to the Special Issue Advanced Aircraft Structural Design and Applications)

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21 pages, 822 KiB

Open AccessArticle

Variable Aircraft Spacing Quadratic Bézier Curve Trajectory Planning for Cascading Delay Mitigation

by Michael R. Variny, Travis W. Moleski and Jay P. Wilhelm

Aerospace 2025, 12(5), 382; https://doi.org/10.3390/aerospace12050382 - 29 Apr 2025

Viewed by 150

Abstract

Congested airspace conflict resolution during terminal operations is a common air traffic management issue that may produce cascading delays. Vehicles needing emergency clearance to land, at either traditional airports or vertiports, would require others on approach to move out of the way and, [...] Read more.

Congested airspace conflict resolution during terminal operations is a common air traffic management issue that may produce cascading delays. Vehicles needing emergency clearance to land, at either traditional airports or vertiports, would require others on approach to move out of the way and, in some instances, cause a wave of delay to propagate through all vehicles on approach. Specifically, uncrewed aerial systems utilizing near-maximum arrival rates would be greatly impacted when requested to move off their approach path and may interfere with others. Vertiports further complicate crowded approaches because vehicles can arrive from many different angles at the same time to maximize landing area usage. Traditional air traffic management techniques were studied for vertiport applications specific to high-capacity operations. This work investigated methods of uniformly re-directing vehicles on approach to a vertiport that would be impacted by an emergency vehicle to minimize or avoid cascading delays. A route of time-optimal Bézier curves as well as Dubins paths optimized for interception heading was generated and flown on as an alternate maneuver when an unaccounted-for emergency vehicle initiated a bypass of an air traffic fleet. A comparison to flight on a holding pattern showed that the Bézier and Dubins route improved delay times and mitigated a cascading delay effect. Full article

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

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31 pages, 8398 KiB

Open AccessArticle

Structural and Topological Optimization of a Novel Elephant Trunk Mechanism for Morphing Wing Applications

by Mir Hossein Negahban, Alexandre Hallonet, Marie Noupoussi Woumeni, Constance Nguyen and Ruxandra Mihaela Botez

Aerospace 2025, 12(5), 381; https://doi.org/10.3390/aerospace12050381 - 28 Apr 2025

Viewed by 109

Abstract

A novel mechanism for seamless morphing trailing edge flaps is presented in this paper. This bio-inspired morphing concept is derived from an elephant’s trunk and is called the Elephant Trunk Mechanism (ETM). The structural flexibility of an elephant’s trunk and its ability to [...] Read more.

A novel mechanism for seamless morphing trailing edge flaps is presented in this paper. This bio-inspired morphing concept is derived from an elephant’s trunk and is called the Elephant Trunk Mechanism (ETM). The structural flexibility of an elephant’s trunk and its ability to perform various types of deformations make it a promising choice in morphing technology for increasing the performance of continuous and smooth downward bending deformation at a trailing edge. This mechanism consists of a number of tooth-like elements attached to a solid wing box; the contractions of these tooth-like elements by external actuation forces change the trailing edge shape in the downwards direction. The main actuation forces are applied through wire ropes passing through tooth-like elements to generate the desired contractions on the flexible teeth. A static structural analysis using the Finite Element Method (FEM) is performed to examine this novel morphing concept and ensure its structural feasibility and stability. Topology optimization is also performed to find the optimum configuration with the objective of reducing the structural weight. The optimized mechanism is then attached to the flap section of a UAS-S45 wing. Finally, a skin analysis is performed to find its optimum skin material, which corresponds to the requirements of the morphing flap. The results of structural analysis and topology optimization reveal the reliability and stability of the proposed mechanism for application in the Seamless Morphing Trailing Edge (SMTE) flap. The optimization results led to significant improvements in the structural parameters, in addition to the desired weight reduction. The ETM maximum vertical displacement increased by 8.6%, while the von Mises stress decreased by 10.43%. Furthermore, the factor of safety improved from 1.3 to 1.5, thus indicating a safer design. The mass of the structure was reduced by 35.5%, achieving the primary goal of topology optimization. Full article

(This article belongs to the Special Issue Aircraft Design and System Optimization)

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17 pages, 6038 KiB

Open AccessArticle

Numerical Analysis of Ejector Flow Performance for High-Altitude Simulation

by Chae-Hyoung Kim and Chang-Su Park

Aerospace 2025, 12(5), 380; https://doi.org/10.3390/aerospace12050380 - 28 Apr 2025

Viewed by 132

Abstract

In this study we perform a computational numerical analysis to examine the flow characteristics of a system composed of a rocket engine, supersonic diffuser, and ejector system. When the nozzle expansion ratio of a rocket engine increases, it is necessary to maintain high-vacuum [...] Read more.

In this study we perform a computational numerical analysis to examine the flow characteristics of a system composed of a rocket engine, supersonic diffuser, and ejector system. When the nozzle expansion ratio of a rocket engine increases, it is necessary to maintain high-vacuum conditions during ground hot testing, which requires a supersonic diffuser and ejector system. The integrated model, consisting of multiple systems and a single-ejector system model, exhibits a difference in the initial volume to be evacuated. Although some differences are observed during the initial vacuum transition process, both models maintain the same final vacuum pressure (4 kPa). During the initial vacuum process, if the injection pressure of the ejector decreases below the design pressure, vacuum degradation occurs because of momentum deficiency, followed by pressure perturbations as the vacuum process resumes. Once the rocket engine ignites and flow is supplied to the suction region, two flow regions exist around the ejector nozzle exit. As these flows mix and move downstream, flow separation occurs in the expansion region. When the injection pressure of the ejector falls below the design pressure, the flow separation region moves forward, and this shift helps maintain the designed vacuum suction conditions. Full article

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

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43 pages, 5199 KiB

Open AccessArticle

An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration

by Junwei Zhang and Liangqing Lyu

Aerospace 2025, 12(5), 379; https://doi.org/10.3390/aerospace12050379 - 28 Apr 2025

Viewed by 87

Abstract

Traditional spacecraft task planning has relied on ground control centers issuing commands through ground-to-space communication systems; however, as the number of deep space exploration missions grows, the problem of ground-to-space communication delays has become significant, affecting the effectiveness of real-time command and control [...] Read more.

Traditional spacecraft task planning has relied on ground control centers issuing commands through ground-to-space communication systems; however, as the number of deep space exploration missions grows, the problem of ground-to-space communication delays has become significant, affecting the effectiveness of real-time command and control and increasing the risk of missed opportunities for scientific discovery. Adaptive Space Scientific Exploration requires that spacecraft have the ability to make autonomous decisions to complete known and unknown scientific exploration missions without ground control. Based on this requirement, this paper proposes an actor–critic-based hyper-heuristic autonomous mission planning algorithm, which is used for mission planning and execution at different levels to support spacecraft Adaptive Space Scientific Exploration in deep space environments. At the bottom level of the hyper-heuristic algorithm, this paper uses the particle swarm optimization algorithm, grey wolf optimization algorithm, differential evolution algorithm, and positive cosine optimization algorithm as the basic operators. At the high level, a reinforcement learning strategy based on the actor–critic model is used, combined with the network architecture, to construct a framework for the selection of advanced heuristic algorithms. The related experimental results show that the algorithm can meet the requirements of Adaptive Space Scientific Exploration, and exhibits a quality solution with higher comprehensive evaluation in the test. This study also designs an example application of the algorithm to a space engineering mission based on a collaborative sky and earth control system to demonstrate the usability of the algorithm. This study provides an autonomous mission planning method for spacecraft in the complex and ever-changing deep space environment, which supports the further construction of spacecraft autonomous capabilities and is of great significance for improving the exploration efficiency of deep space exploration missions. Full article

(This article belongs to the Special Issue Intelligent Perception, Decision and Autonomous Control in Aerospace)

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27 pages, 16010 KiB

Open AccessArticle

Rigid–Flexible Coupled Dynamics Modeling and Trajectory Compensation for Overhead Line Mobile Robots

by Guanghong Tao, Yan Li, Fen Wang, Wenlong Pan and Guoqiang Cao

Aerospace 2025, 12(5), 378; https://doi.org/10.3390/aerospace12050378 - 27 Apr 2025

Viewed by 145

Abstract

When a mobile robot on an overhead line carries out operations, the effects of the elastic deformation and vibration of the flexible overhead line on motion performance cannot be ignored. This study proposes a method for active compensation of the robot’s trajectory, based [...] Read more.

When a mobile robot on an overhead line carries out operations, the effects of the elastic deformation and vibration of the flexible overhead line on motion performance cannot be ignored. This study proposes a method for active compensation of the robot’s trajectory, based on the force–deformation characteristics of the overhead line. Overhead line mobile robot systems show a complex nonlinear coupled vibration problem. To simplify the flexible environment, it is modeled as a single-degree-of-freedom spring–damped system. A rigid–flexible coupled dynamics model is established using the sub-bar method and the Lagrangian method. A numerical simulation is used to compare and analyze the end trajectories of mobile robots using generalized coordinates when the overhead line is rigid and flexible, respectively, revealing the coupling mechanism between the flexible overhead line and the robot. Based on the force–deformation characteristics of the overhead line, an active robot trajectory compensation method is proposed. The experimental results show that the established rigid–flexible coupling dynamics model describes the dynamic characteristics of an overhead line mobile robot, and the active robot trajectory compensation method has certain feasibility. The proposed method provides a reference basis for the control of overhead line mobile robots and has some applicability in addressing motion compensation issues in flexible environments. Full article

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

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25 pages, 1174 KiB

Open AccessArticle

Parametric Study of a Liquid Cooling Thermal Management System for Hybrid Fuel Cell Aircraft

by Valentine Habrard, Valérie Pommier-Budinger, Ion Hazyuk, Joël Jézégou and Emmanuel Benard

Aerospace 2025, 12(5), 377; https://doi.org/10.3390/aerospace12050377 - 27 Apr 2025

Viewed by 84

Abstract

Hybrid aircraft offer a logical pathway to reducing aviation’s carbon footprint. The thermal management system (TMS) is often neglected in the assessment of hybrid aircraft performance despite it being of major importance. After presenting the TMS architecture, this study performs a sensitivity analysis [...] Read more.

Hybrid aircraft offer a logical pathway to reducing aviation’s carbon footprint. The thermal management system (TMS) is often neglected in the assessment of hybrid aircraft performance despite it being of major importance. After presenting the TMS architecture, this study performs a sensitivity analysis on several parameters of a retrofitted hybrid fuel cell aircraft’s performance considering three hierarchical levels: the aircraft, fuel cell system, and TMS component levels. The objective is to minimize CO₂ emissions while maintaining performance standards. At the aircraft level, cruise speed, fuel cell power, and ISA temperature were varied to assess their impact. Lowering cruise speeds can decrease emissions by up to

49 %

, and increasing fuel cell power from 200 kW to 400 kW cuts emissions by

18 %

. Higher ambient air temperatures also significantly impact cooling demands. As for the fuel cell, lowering the stack temperature from 80 °C to 60 °C increases the required cooling air mass flow by

49 %

and TMS drag by

40 %

. At the TMS component level, different coolants and HEX offset-fin geometries reveal low-to-moderate effects on emissions and payload. Overall, despite some design choice improvements, the conventional aircraft is still able to achieve lower CO₂ emissions per unit payload. Full article

(This article belongs to the Section Aeronautics)

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21 pages, 3806 KiB

Open AccessArticle

Research on the Method of Air Traffic Control Instruction Keyword Extraction Based on the Roberta-Attention-BiLSTM-CRF Model

by Sheng Chen, Weijun Pan, Yidi Wang, Shenhao Chen and Xuan Wang

Aerospace 2025, 12(5), 376; https://doi.org/10.3390/aerospace12050376 - 27 Apr 2025

Viewed by 116

Abstract

In recent years, with the increasing complexity of air traffic management and the rapid development of automation technology, efficiently and accurately extracting key information from large volumes of air traffic control (ATC) instructions has become essential for ensuring flight safety and improving the [...] Read more.

In recent years, with the increasing complexity of air traffic management and the rapid development of automation technology, efficiently and accurately extracting key information from large volumes of air traffic control (ATC) instructions has become essential for ensuring flight safety and improving the efficiency of air traffic control. However, this task is challenging due to the specialized terminology involved and the high real-time requirements for data collection and processing. While existing keyword extraction methods have made some progress, most of them still perform unsatisfactorily on ATC instruction data due to issues such as data irregularities and the lack of domain-specific knowledge. To address these challenges, this paper proposes a Roberta-Attention-BiLSTM-CRF model for keyword extraction from ATC instructions. The RABC model introduces an attention mechanism specifically designed to extract keywords from multi-segment ATC instruction texts. Moreover, the BiLSTM component enhances the model’s ability to capture detailed semantic information within individual sentences during the keyword extraction process. Finally, by integrating a Conditional Random Field (CRF), the model can predict and output multiple keywords in the correct sequence. Experimental results on an ATC instruction dataset demonstrate that the RABC model achieves an accuracy of 89.5% in keyword extraction and a sequence match accuracy of 91.3%, outperforming other models across multiple evaluation metrics. These results validate the effectiveness of the proposed model in extracting keywords from ATC instruction data and demonstrate its potential for advancing automation in air traffic control. Full article

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

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48 pages, 61162 KiB

Open AccessReview

Review of On-Orbit Assembly Technology with Space Robots

by Zhengwei Wang, Pengfei Wang, Jinjun Duan and Wei Tian

Aerospace 2025, 12(5), 375; https://doi.org/10.3390/aerospace12050375 - 27 Apr 2025

Viewed by 118

Abstract

With the accelerated pace of human space exploration and the progress of other related researches, there is an increasingly urgent demand for space infrastructure, equipment, and diversified spacecraft construction for space missions, and how to efficiently, intelligently, and autonomously build corresponding facilities and [...] Read more.

With the accelerated pace of human space exploration and the progress of other related researches, there is an increasingly urgent demand for space infrastructure, equipment, and diversified spacecraft construction for space missions, and how to efficiently, intelligently, and autonomously build corresponding facilities and equipment on orbit according to the functional requirements of different missions has become a great challenge in the field of space technology research. As an important means of automated manufacturing, the construction of on-orbit assembly systems centered on space robotics has become an emerging development trend. In view of its importance, space agencies and research institutes have successively proposed and developed a series of related programs. In order to comprehensively understand the progress of on-orbit assembly with space robots (OASR) and scientific problems involved, this paper investigates the current status of research and technological development in OASR. Firstly, the significance of OASR for space exploration and other space missions is analyzed. Secondly, the existing classification forms of on-orbit assembly are outlined and a classification idea is proposed from the point of view of the combination of space robot motion capability and assembly goals. Thirdly, the research and development status of OASR in the United States, Europe, Canada, Japan, and China is investigated. Then, based on a review of the literature on space robots to realize on-orbit assembly in space facilities, some of the key technologies involved are reviewed and discussed. Finally, this paper discusses and looks ahead to the future development trend and application prospect of the technology of OASR, reveals and explains the crucial position it occupies as well as the important role it can play in the process of human space exploration, and is expected to provide useful references for the in-depth research and development of future on-orbit assembly technology. Full article

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

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17 pages, 7946 KiB

Open AccessArticle

Optical Camera Characterization for Feature-Based Navigation in Lunar Orbit

by Pierluigi Federici, Antonio Genova, Simone Andolfo, Martina Ciambellini, Riccardo Teodori and Tommaso Torrini

Aerospace 2025, 12(5), 374; https://doi.org/10.3390/aerospace12050374 - 26 Apr 2025

Viewed by 195

Abstract

Accurate localization is a key requirement for deep-space exploration, enabling spacecraft operations with limited ground support. Upcoming commercial and scientific missions to the Moon are designed to extensively use optical measurements during low-altitude orbital phases, descent and landing, and high-risk operations, due to [...] Read more.

Accurate localization is a key requirement for deep-space exploration, enabling spacecraft operations with limited ground support. Upcoming commercial and scientific missions to the Moon are designed to extensively use optical measurements during low-altitude orbital phases, descent and landing, and high-risk operations, due to the versatility and suitability of these data for onboard processing. Navigation frameworks based on optical data analysis have been developed to support semi- or fully-autonomous onboard systems, enabling precise relative localization. To achieve high-accuracy navigation, optical data have been combined with complementary measurements using sensor fusion techniques. Absolute localization is further supported by integrating onboard maps of cataloged surface features, enabling position estimation in an inertial reference frame. This study presents a navigation framework for optical image processing aimed at supporting the autonomous operations of lunar orbiters. The primary objective is a comprehensive characterization of the navigation camera’s properties and performance to ensure orbit determination uncertainties remain below 1% of the spacecraft altitude. In addition to an analysis of measurement noise, which accounts for both hardware and software contributions and is evaluated across multiple levels consistent with prior literature, this study emphasizes the impact of process noise on orbit determination accuracy. The mismodeling of orbital dynamics significantly degrades orbit estimation performance, even in scenarios involving high-performing navigation cameras. To evaluate the trade-off between measurement and process noise, representing the relative accuracy of the navigation camera and the onboard orbit propagator, numerical simulations were carried out in a synthetic lunar environment using a near-polar, low-altitude orbital configuration. Under nominal conditions, the optical measurement noise was set to 2.5 px, corresponding to a ground resolution of approximately 160 m based on the focal length, pixel pitch, and altitude of the modeled camera. With a conservative process noise model, position errors of about 200 m are observed in both transverse and normal directions. The results demonstrate the estimation framework’s robustness to modeling uncertainties, adaptability to varying measurement conditions, and potential to support increased onboard autonomy for small spacecraft in deep-space missions. Full article

(This article belongs to the Special Issue Planetary Exploration)

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19 pages, 4234 KiB

Open AccessArticle

Introduction of a System Definition in the Common Parametric Aircraft Configuration Schema (CPACS)

by Tim Burschyk, Marko Alder, Andrea Mancini, Thimo Bielsky, Vivian Kriewall, Frank Thielecke and Björn Nagel

Aerospace 2025, 12(5), 373; https://doi.org/10.3390/aerospace12050373 - 25 Apr 2025

Viewed by 106

Abstract

The aircraft design process is a complex task that requires the collaboration of disciplinary experts from various fields. In practice, this complexity requires a large investment in setting up communication interfaces for the exchange of disciplinary data, and serious misinterpretations are not uncommon. [...] Read more.

The aircraft design process is a complex task that requires the collaboration of disciplinary experts from various fields. In practice, this complexity requires a large investment in setting up communication interfaces for the exchange of disciplinary data, and serious misinterpretations are not uncommon. To increase the efficiency and robustness of data exchange, a common language is essential. As such, the Common Parametric Aircraft Configuration Schema (CPACS) serves as a central data model, which currently includes detailed parametrizations of aircraft geometry and analysis results from traditional disciplines (e.g., aerodynamics, structure, etc.). However, with the recent interest in alternative propulsion and complex on-board system architectures, CPACS is proving to be too limited to meet the needs of the various disciplinary system experts. The particular challenge here is to enable different views on the same systems, i.e., a functional/logical as well as a geometric/physical representation, without violating the principle of unambiguous data. Therefore, this paper proposes an extension of CPACS which introduces an explicit system definition covering both representations. Its potential is demonstrated by two use cases from disciplinary experts in the field of on-board system design at the Hamburg University of Technology (TUHH), based on data provided by aircraft design experts. Through validation against the experts’ needs, the proposed system definition proves to bridge the gap between preliminary aircraft design and on-board system design, enabling a holistic, robust and efficient aircraft design process. Full article

(This article belongs to the Special Issue Aircraft Design and System Optimization)

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Aerospace, Volume 12, Issue 5 (May 2025) – 42 articles

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