Pub Date : 2026-02-05DOI: 10.1016/j.ast.2026.111849
Liu Zeya , Zhai Guang , Wei Shijun
Multi-Target tracking is significantly challenging due to the complicities of data association and trajectory correlation. Discontinuous observation sequences evidently cause interruptions on both data association and trajectory correlation, and finally resulting target tracking loss and missed alerts. The Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter is commonly used in multi-target tracking. Under the assumption of constant target detection probability, GM-PHD filter accurately estimates the number of targets and their motion states. However, when the sensor experiences stochastic missed detection of any target member, traditional GM-PHD filter immediately terminates the corresponding trajectory, and subsequently results in target loss and missed alert. To eliminate the risk of missed alerts caused by missed detections, a GM-PHD filter characterized by weight-redistribution is proposed by introducing a dynamic adjustment mechanism on target detection probability, this robust filter guarantees both the estimate accuracy on target number and the tracking stability even stochastic missed detection occurs. Simulation results across multiple scenarios are carried out to demonstrate the significance of the proposed filter.
{"title":"A Weight Redistributed GM-PHD filter Accounting for Stochastic Missed Detection","authors":"Liu Zeya , Zhai Guang , Wei Shijun","doi":"10.1016/j.ast.2026.111849","DOIUrl":"10.1016/j.ast.2026.111849","url":null,"abstract":"<div><div>Multi-Target tracking is significantly challenging due to the complicities of data association and trajectory correlation. Discontinuous observation sequences evidently cause interruptions on both data association and trajectory correlation, and finally resulting target tracking loss and missed alerts. The Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter is commonly used in multi-target tracking. Under the assumption of constant target detection probability, GM-PHD filter accurately estimates the number of targets and their motion states. However, when the sensor experiences stochastic missed detection of any target member, traditional GM-PHD filter immediately terminates the corresponding trajectory, and subsequently results in target loss and missed alert. To eliminate the risk of missed alerts caused by missed detections, a GM-PHD filter characterized by weight-redistribution is proposed by introducing a dynamic adjustment mechanism on target detection probability, this robust filter guarantees both the estimate accuracy on target number and the tracking stability even stochastic missed detection occurs. Simulation results across multiple scenarios are carried out to demonstrate the significance of the proposed filter.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111849"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-05DOI: 10.1016/j.ast.2026.111864
Zhengjie Liu, Wentao Huang, Yuhan Huang, Yu Zhang
As the core power system of aircraft, the fault prediction and health management of aircraft engines are of great significance in ensuring flight safety and optimizing maintenance strategies. Existing research faces the dual challenges of scarcity of real flight fault data and cross-domain feature differences. At present, most few-shot cross-domain fault diagnosis methods focus on efficient fault feature extraction and model structure optimization, while insufficiently leveraging diagnostic knowledge accumulated in the field over time. A key issue that remains unresolved in few-shot cross-domain fault diagnosis for aero-engine bearings is how to integrate valuable prior knowledge with effective cross-domain feature alignment methods into the diagnostic model. This study introduces a prior knowledge-informed multi-task collaborative learning (PKMTCL) approach. First, a cosine contrastive loss is introduced to implicitly embed prior diagnostic knowledge into the model, thereby reducing its dependence on large training datasets. Then, a novel information entropy-based prototype construction and cross-domain feature alignment strategy for the target domain is designed, effectively alleviating feature shift under varying working conditions. Finally, a multi-task collaborative learning framework is developed, where the inductive bias provided by auxiliary tasks guides the main task to learn more generalizable feature representations, thereby effectively improving the generalization performance of the main task. Experiments on two aero-engine bearing datasets demonstrate that, compared with state-of-the-art methods, the proposed method achieves higher fault identification accuracy and lower volatility in diagnostic results. The related code can be downloaded from https://github.com/LZJHIT/PKMTCL.
{"title":"Prior knowledge-informed multi-task collaborative learning for few-shot fault diagnosis of aero-engines","authors":"Zhengjie Liu, Wentao Huang, Yuhan Huang, Yu Zhang","doi":"10.1016/j.ast.2026.111864","DOIUrl":"10.1016/j.ast.2026.111864","url":null,"abstract":"<div><div>As the core power system of aircraft, the fault prediction and health management of aircraft engines are of great significance in ensuring flight safety and optimizing maintenance strategies. Existing research faces the dual challenges of scarcity of real flight fault data and cross-domain feature differences. At present, most few-shot cross-domain fault diagnosis methods focus on efficient fault feature extraction and model structure optimization, while insufficiently leveraging diagnostic knowledge accumulated in the field over time. A key issue that remains unresolved in few-shot cross-domain fault diagnosis for aero-engine bearings is how to integrate valuable prior knowledge with effective cross-domain feature alignment methods into the diagnostic model. This study introduces a prior knowledge-informed multi-task collaborative learning (PKMTCL) approach. First, a cosine contrastive loss is introduced to implicitly embed prior diagnostic knowledge into the model, thereby reducing its dependence on large training datasets. Then, a novel information entropy-based prototype construction and cross-domain feature alignment strategy for the target domain is designed, effectively alleviating feature shift under varying working conditions. Finally, a multi-task collaborative learning framework is developed, where the inductive bias provided by auxiliary tasks guides the main task to learn more generalizable feature representations, thereby effectively improving the generalization performance of the main task. Experiments on two aero-engine bearing datasets demonstrate that, compared with state-of-the-art methods, the proposed method achieves higher fault identification accuracy and lower volatility in diagnostic results. The related code can be downloaded from <span><span>https://github.com/LZJHIT/PKMTCL</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"174 ","pages":"Article 111864"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-05DOI: 10.1016/j.ast.2026.111859
Xin Liu, Song Ji, Mengmeng Sun, Dazhao Fan, Jiayang Lv, Mingze Suo, Rongrong Zhang, Zhen Yan, Yongjian Li
The exponential growth of remote sensing satellite deployments globally has exacerbated the imbalance between limited satellite-to-ground downlink capacity and the surging requirement for low-latency, mission-critical data transmission. This pressing issue is driving a transformative shift in remote sensing paradigms, transitioning from traditional “passive data collection with ground-based post-processing” to a novel model of “active sensing and real-time on-orbit processing” facilitated by intelligent satellites. However, there remains a significant deficiency in comprehensive surveys that systematically address on-orbit image processing technologies for intelligent remote sensing satellites, particularly those that provide integrative analyses of system architectures, cutting-edge advancements, and illustrative application scenarios. To address this shortfall, this paper systematically reviews research progress in on-orbit image data optimization and enhancement, as well as intelligent interpretation and thematic product generation technologies, from the perspective of the Layered Collaborative On-orbit Image Processing (LCOIP) framework. It elucidates the supporting role of these technologies in disaster response, national defense security, environmental protection, and agricultural remote sensing applications. Key technical challenges are identified. Furthermore, promising future development directions are explored, such as autonomous intelligent on-orbit processing by single satellites and collaborative on-orbit processing by functionally heterogeneous constellations. This aims to provide theoretical references and technical guidance for the development and application of next-generation intelligent remote sensing satellite systems.
{"title":"On-orbit image processing technology for intelligent remote sensing satellites: Progress, challenges, and opportunities","authors":"Xin Liu, Song Ji, Mengmeng Sun, Dazhao Fan, Jiayang Lv, Mingze Suo, Rongrong Zhang, Zhen Yan, Yongjian Li","doi":"10.1016/j.ast.2026.111859","DOIUrl":"10.1016/j.ast.2026.111859","url":null,"abstract":"<div><div>The exponential growth of remote sensing satellite deployments globally has exacerbated the imbalance between limited satellite-to-ground downlink capacity and the surging requirement for low-latency, mission-critical data transmission. This pressing issue is driving a transformative shift in remote sensing paradigms, transitioning from traditional “passive data collection with ground-based post-processing” to a novel model of “active sensing and real-time on-orbit processing” facilitated by intelligent satellites. However, there remains a significant deficiency in comprehensive surveys that systematically address on-orbit image processing technologies for intelligent remote sensing satellites, particularly those that provide integrative analyses of system architectures, cutting-edge advancements, and illustrative application scenarios. To address this shortfall, this paper systematically reviews research progress in on-orbit image data optimization and enhancement, as well as intelligent interpretation and thematic product generation technologies, from the perspective of the Layered Collaborative On-orbit Image Processing (LCOIP) framework. It elucidates the supporting role of these technologies in disaster response, national defense security, environmental protection, and agricultural remote sensing applications. Key technical challenges are identified. Furthermore, promising future development directions are explored, such as autonomous intelligent on-orbit processing by single satellites and collaborative on-orbit processing by functionally heterogeneous constellations. This aims to provide theoretical references and technical guidance for the development and application of next-generation intelligent remote sensing satellite systems.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"174 ","pages":"Article 111859"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-04DOI: 10.1016/j.ast.2026.111788
Yao Jiang , Meibao Yao , Xueming Xiao , Huanfeng Zhao , Hutao Cui , Zexu Zhang
In a microgravity environment, modular self-reconfigurable robots can perform a range of on-orbit missions including solar-array deployment, serial-arm assembly, and failed-subsystem replacement, owing to their modular scalability and morphological versatility, tailored to mission-specific constraints and extended across these tasks. However, conventional cubic modules have rotational blind spots and pose-dependent interfaces that inflate alignment burden and trigger collisions and local deadlocks, especially for large-scale deployment. Due to the tight coupling of local motion feasibility in modular robotic systems, coupled with the connectivity and reachability requirements during reconfiguration, task allocation and decision sequencing for large-scale architecture are often NP-hard. To address these issues, we present an integrated reconfigurable hardware-algorithmic solution. Structurally, the concentric, nested spherical design with isotropic geometry and unified locking mechanism reduces sensitivity to pose alignment, mitigates collisions and deadlocks, and expands the reachable workspace. Algorithmically, reconfiguration planning is formulated as an integer programming problem, incorporating penalties to enforce connectivity and reachability constraints within a hierarchical framework. The top level determines the matching and reconfiguration sequence by the proposed Cross-correlation BFS-Tree Genetic Algorithm with Gaussian mutation (CBGA), and the lower level aims at path planning using the designed kinematics-aware parallel A*. Extensive simulation and experiments are conducted with varied number of modular robots. The results demonstrate that the proposed system maintains full connectivity and reachability while achieving rapid convergence with low relocation steps even for large-scale architecture. Such capability thereby establishes its practical viability for autonomous modular reconfiguration in on-orbit missions.
{"title":"Towards scalable on-orbit assembly: Reconfigurable hardware and algorithm design","authors":"Yao Jiang , Meibao Yao , Xueming Xiao , Huanfeng Zhao , Hutao Cui , Zexu Zhang","doi":"10.1016/j.ast.2026.111788","DOIUrl":"10.1016/j.ast.2026.111788","url":null,"abstract":"<div><div>In a microgravity environment, modular self-reconfigurable robots can perform a range of on-orbit missions including solar-array deployment, serial-arm assembly, and failed-subsystem replacement, owing to their modular scalability and morphological versatility, tailored to mission-specific constraints and extended across these tasks. However, conventional cubic modules have rotational blind spots and pose-dependent interfaces that inflate alignment burden and trigger collisions and local deadlocks, especially for large-scale deployment. Due to the tight coupling of local motion feasibility in modular robotic systems, coupled with the connectivity and reachability requirements during reconfiguration, task allocation and decision sequencing for large-scale architecture are often NP-hard. To address these issues, we present an integrated reconfigurable hardware-algorithmic solution. Structurally, the concentric, nested spherical design with isotropic geometry and unified locking mechanism reduces sensitivity to pose alignment, mitigates collisions and deadlocks, and expands the reachable workspace. Algorithmically, reconfiguration planning is formulated as an integer programming problem, incorporating penalties to enforce connectivity and reachability constraints within a hierarchical framework. The top level determines the matching and reconfiguration sequence by the proposed Cross-correlation BFS-Tree Genetic Algorithm with Gaussian mutation (CBGA), and the lower level aims at path planning using the designed kinematics-aware parallel A*. Extensive simulation and experiments are conducted with varied number of modular robots. The results demonstrate that the proposed system maintains full connectivity and reachability while achieving rapid convergence with low relocation steps even for large-scale architecture. Such capability thereby establishes its practical viability for autonomous modular reconfiguration in on-orbit missions.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"174 ","pages":"Article 111788"},"PeriodicalIF":5.8,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Transpiration cooling is widely applied in hypersonic aircraft due to its high cooling effectiveness. However, shock impingement significantly degrades cooling effectiveness. Therefore, investigation on the influence of shock wave on transpiration cooling for porous flat plates under hypersonic conditions is essential. This study focuses on the effects of shock wave intensity and coolant injection rate on transpiration cooling effectiveness at Mach 6. The temperature of the porous plate is measured by infrared thermometry, while the flow-field is observed using schlieren and the Nano-tracer Planar Laser Scattering (NPLS) technology. Results indicate that the cooling effectiveness degrades with the increasing shock intensity. The coolant injection rate non-linearly influences cooling effectiveness, as higher rates enhance mainstream flow interaction and intensify heat exchange. With the injection rate increasing from 0.1% to 1.0%, the cost-effectiveness ratio drops by 88.5% and the thickness of turbulent boundary layer grows by 58.7%. The results indicate that the increased wall recovery temperature is the primary factor in the reduction of transpiration cooling effectiveness.
{"title":"Experimental investigation of shock wave effects on transpiration cooling for porous flat plate in hypersonic flow","authors":"Yishanchun Lu, Dundian Gang, Yuxin Zhao, Qi Mi, Yuan Feng, Zhiyao Yang, Shikang Chen","doi":"10.1016/j.ast.2026.111837","DOIUrl":"10.1016/j.ast.2026.111837","url":null,"abstract":"<div><div>Transpiration cooling is widely applied in hypersonic aircraft due to its high cooling effectiveness. However, shock impingement significantly degrades cooling effectiveness. Therefore, investigation on the influence of shock wave on transpiration cooling for porous flat plates under hypersonic conditions is essential. This study focuses on the effects of shock wave intensity and coolant injection rate on transpiration cooling effectiveness at Mach 6. The temperature of the porous plate is measured by infrared thermometry, while the flow-field is observed using schlieren and the Nano-tracer Planar Laser Scattering (NPLS) technology. Results indicate that the cooling effectiveness degrades with the increasing shock intensity. The coolant injection rate non-linearly influences cooling effectiveness, as higher rates enhance mainstream flow interaction and intensify heat exchange. With the injection rate increasing from 0.1% to 1.0%, the cost-effectiveness ratio drops by 88.5% and the thickness of turbulent boundary layer grows by 58.7%. The results indicate that the increased wall recovery temperature is the primary factor in the reduction of transpiration cooling effectiveness.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"174 ","pages":"Article 111837"},"PeriodicalIF":5.8,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-04DOI: 10.1016/j.ast.2026.111792
Muhammad Nasir , Dan Xie , Zijun Yi , Tamina Perveen , Adnan Maqsood
The design of Thermal Protection Systems (TPS) for hypersonic vehicles must simultaneously address extreme aerodynamic heating and ensure aerothermoelastic stability. Conventional approaches, as examined by Xie (2020), highlight that thickness distribution and material selection are critical to controlling flutter onset, stress evolution, and long-term structural safety. Yet, the performance of alternative advanced materials under fully coupled aerothermoelastic loading remains underexplored, leaving a gap in the development of next-generation TPS concepts. This study investigates the aerothermoelastic response of multilayer TPS panels by substituting the outer and insulation layers with three high-performance material combinations: (i) ZrBtwo/C/SiC with Silica Aerogel, (ii) C/SiC with AFRSI–2500, and (iii) Inconel 617 honeycomb with Cerrachrome Insulation, while retaining a Ti-6Al-2Sn-4Zr-2Mo structural panel. An aerothermoelastic MATLAB simulation framework, adapted from Xie (2020), was employed to evaluate baseline and selected thickness configurations (Cases 1, 2, and 7). Key outputs including transient deflection histories, temperature distributions, heat fluxes, thermal stresses, and flutter onset times are obtained and analyzed. The results indicate that the ZrBtwo/C/SiC + Silica Aerogel system provides the most favorable stability across cases, C/SiC + AFRSI–2500 offers intermediate performance, and Inconel 617 honeycomb + Cerrachrome Insulation tends to be least stable under the same loading, consistent with differences in thermal protection and temperature-dependent stiffness retention. Overall, the study highlights that while the emissivity of the outer radiation shield layer is important, the choice of insulation is decisive. Aerogel-based TPS shows strong potential for enhancing structural stability and thermal resilience in future hypersonic missions.
{"title":"Comparative aerothermoelastic performance assessment of advanced TPS materials for hypersonic vehicles","authors":"Muhammad Nasir , Dan Xie , Zijun Yi , Tamina Perveen , Adnan Maqsood","doi":"10.1016/j.ast.2026.111792","DOIUrl":"10.1016/j.ast.2026.111792","url":null,"abstract":"<div><div>The design of Thermal Protection Systems (TPS) for hypersonic vehicles must simultaneously address extreme aerodynamic heating and ensure aerothermoelastic stability. Conventional approaches, as examined by Xie (2020), highlight that thickness distribution and material selection are critical to controlling flutter onset, stress evolution, and long-term structural safety. Yet, the performance of alternative advanced materials under fully coupled aerothermoelastic loading remains underexplored, leaving a gap in the development of next-generation TPS concepts. This study investigates the aerothermoelastic response of multilayer TPS panels by substituting the outer and insulation layers with three high-performance material combinations: (i) ZrBtwo/C/SiC with Silica Aerogel, (ii) C/SiC with AFRSI–2500, and (iii) Inconel 617 honeycomb with Cerrachrome Insulation, while retaining a Ti-6Al-2Sn-4Zr-2Mo structural panel. An aerothermoelastic MATLAB simulation framework, adapted from Xie (2020), was employed to evaluate baseline and selected thickness configurations (Cases 1, 2, and 7). Key outputs including transient deflection histories, temperature distributions, heat fluxes, thermal stresses, and flutter onset times are obtained and analyzed. The results indicate that the ZrBtwo/C/SiC + Silica Aerogel system provides the most favorable stability across cases, C/SiC + AFRSI–2500 offers intermediate performance, and Inconel 617 honeycomb + Cerrachrome Insulation tends to be least stable under the same loading, consistent with differences in thermal protection and temperature-dependent stiffness retention. Overall, the study highlights that while the emissivity of the outer radiation shield layer is important, the choice of insulation is decisive. Aerogel-based TPS shows strong potential for enhancing structural stability and thermal resilience in future hypersonic missions.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111792"},"PeriodicalIF":5.8,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-04DOI: 10.1016/j.ast.2026.111853
Rui Liu , Siyu Liu , Zirui Fang , Jing Li , Lingfeng Zhong , Shen Xue
With the rapid development of the low-altitude economy and unmanned aerial vehicle (UAV) technology, aviation heavy-fuel rotary engines have re-emerged as a key power system, making the optimization of their control parameters crucial. This study established one-dimensional (1-D) and three-dimensional (3-D) numerical simulation models of an aviation heavy-fuel rotary engine, validated with experimental data, to investigate the effects of start of injection (SOI), injection pressure (Pinj), and trailing spark plug ignition timing (θign) on the mixture formation, combustion, and emission. Results show that retarding SOI improves mixture homogeneity and reduces soot, while higher Pinj concentrates fuel in the chamber front, creating an over-rich zone. Advancing θign causes a non-monotonic change in peak in-cylinder pressure (Pmax), underscoring the need for careful timing selection. Based on these findings, the entropy weight technique for order preference by similarity to ideal solution (EW-TOPSIS) was employed to identify the optimal control scheme: SOI = –500°EA ATDC, Pinj = 0.3 MPa, and θign = –10°EA ATDC. This configuration boosts Pmax by 11.08 %, increases indicated mean effective pressure (IMEP) by 14.69 %, and reduces soot emissions by 42.14 % compared to the original scheme.
{"title":"Comprehensive analysis and performance optimization of different control parameters on an aviation heavy-fuel rotary engine","authors":"Rui Liu , Siyu Liu , Zirui Fang , Jing Li , Lingfeng Zhong , Shen Xue","doi":"10.1016/j.ast.2026.111853","DOIUrl":"10.1016/j.ast.2026.111853","url":null,"abstract":"<div><div>With the rapid development of the low-altitude economy and unmanned aerial vehicle (UAV) technology, aviation heavy-fuel rotary engines have re-emerged as a key power system, making the optimization of their control parameters crucial. This study established one-dimensional (1-D) and three-dimensional (3-D) numerical simulation models of an aviation heavy-fuel rotary engine, validated with experimental data, to investigate the effects of start of injection (SOI), injection pressure (<em>P</em><sub>inj</sub>), and trailing spark plug ignition timing (<em>θ</em><sub>ign</sub>) on the mixture formation, combustion, and emission. Results show that retarding SOI improves mixture homogeneity and reduces soot, while higher <em>P</em><sub>inj</sub> concentrates fuel in the chamber front, creating an over-rich zone. Advancing <em>θ</em><sub>ign</sub> causes a non-monotonic change in peak in-cylinder pressure (<em>P</em><sub>max</sub>), underscoring the need for careful timing selection. Based on these findings, the entropy weight technique for order preference by similarity to ideal solution (EW-TOPSIS) was employed to identify the optimal control scheme: SOI = –500°EA ATDC, <em>P</em><sub>inj</sub> = 0.3 MPa, and <em>θ</em><sub>ign</sub> = –10°EA ATDC. This configuration boosts <em>P</em><sub>max</sub> by 11.08 %, increases indicated mean effective pressure (IMEP) by 14.69 %, and reduces soot emissions by 42.14 % compared to the original scheme.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111853"},"PeriodicalIF":5.8,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-04DOI: 10.1016/j.ast.2026.111851
Qiyun Cheng, Huihua Yang, Wei Ji
Accurate real-time forecasting of cryogenic tank behavior is essential for the safe and efficient operation of propulsion and storage systems in future deep-space missions. While cryogenic fluid management (CFM) systems increasingly require autonomous capabilities, conventional simulation methods remain hindered by high computational cost, model imperfections, and sensitivity to unanticipated boundary condition changes. To address these limitations, this study proposes an Adaptive Real-Time Forecasting Framework for Cryogenic Propellant Management in Space Systems, featuring a lightweight, non-intrusive method named ARCTIC (Adaptive Real-time Cryogenic Tank Inference and Correction). ARCTIC integrates real-time sensor data with precomputed nodal simulations through a data-driven correction layer that dynamically refines forecast accuracy without modifying the underlying model. Two updating mechanisms, auto-calibration and observation-correction, enable continuous adaptation to evolving system states and transient disturbances. The method is first assessed through synthetic scenarios representing self-pressurization, sloshing, and periodic operations, then validated using experimental data from NASA’s Multipurpose Hydrogen Test Bed and K-Site facilities. Results demonstrate that ARCTIC significantly improves forecast accuracy under model imperfections, data noise, and boundary fluctuations, offering a robust real-time forecasting capability to support autonomous CFM operations. The framework’s compatibility with existing simulation tools and its low computational overhead make it especially suited for onboard implementation in space systems requiring predictive autonomy.
{"title":"An adaptive real-time forecasting framework for cryogenic fluid management in space systems","authors":"Qiyun Cheng, Huihua Yang, Wei Ji","doi":"10.1016/j.ast.2026.111851","DOIUrl":"10.1016/j.ast.2026.111851","url":null,"abstract":"<div><div>Accurate real-time forecasting of cryogenic tank behavior is essential for the safe and efficient operation of propulsion and storage systems in future deep-space missions. While cryogenic fluid management (CFM) systems increasingly require autonomous capabilities, conventional simulation methods remain hindered by high computational cost, model imperfections, and sensitivity to unanticipated boundary condition changes. To address these limitations, this study proposes an Adaptive Real-Time Forecasting Framework for Cryogenic Propellant Management in Space Systems, featuring a lightweight, non-intrusive method named ARCTIC (Adaptive Real-time Cryogenic Tank Inference and Correction). ARCTIC integrates real-time sensor data with precomputed nodal simulations through a data-driven correction layer that dynamically refines forecast accuracy without modifying the underlying model. Two updating mechanisms, auto-calibration and observation-correction, enable continuous adaptation to evolving system states and transient disturbances. The method is first assessed through synthetic scenarios representing self-pressurization, sloshing, and periodic operations, then validated using experimental data from NASA’s Multipurpose Hydrogen Test Bed and K-Site facilities. Results demonstrate that ARCTIC significantly improves forecast accuracy under model imperfections, data noise, and boundary fluctuations, offering a robust real-time forecasting capability to support autonomous CFM operations. The framework’s compatibility with existing simulation tools and its low computational overhead make it especially suited for onboard implementation in space systems requiring predictive autonomy.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111851"},"PeriodicalIF":5.8,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-04DOI: 10.1016/j.ast.2026.111855
Xinyu Jia , Jingjun Zhong , Wanyang Wu
In response to the design imperatives of highly-loaded compressor stages, there is an urgent requirement to formulate a more exhaustive parametric methodology for tip winglets. This study introduces an autonomously designed subsonic axial compressor as its subject and develops a parametric model for the suction side tip winglet configuration using Non-Uniform Rational B-Splines (NURBS). This model is integrated with a Support Vector Regression (SVR) surrogate model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to establish a systematic parametric optimization design framework for tip winglets. Subsequent CFD simulations and flow field analyses of the optimized configurations were performed to explore the flow control mechanisms instigated by the winglet in the compressor tip region. The findings affirm that the optimization framework significantly enhances the design of tip winglet configurations, achieving a 9.13% improvement in the compressor’s stable operating margin while preserving the adiabatic efficiency and total pressure ratio nearly constant. Through a detailed comparative analysis of the flow fields associated with the optimized tip winglet configurations, the study elucidates the fundamental mechanism of stall margin enhancement facilitated by tip winglets in subsonic compressor stages. Specifically, the tip winglet structure not only mitigates the intensity of the leading edge tip leakage flow but also strengthens the wall-attached flow on the suction side near the leading edge, thereby improving flow conditions in this critical region.
{"title":"Parametric design for tip winglet in a subsonic compressor stage using SVR and NSGA-II","authors":"Xinyu Jia , Jingjun Zhong , Wanyang Wu","doi":"10.1016/j.ast.2026.111855","DOIUrl":"10.1016/j.ast.2026.111855","url":null,"abstract":"<div><div>In response to the design imperatives of highly-loaded compressor stages, there is an urgent requirement to formulate a more exhaustive parametric methodology for tip winglets. This study introduces an autonomously designed subsonic axial compressor as its subject and develops a parametric model for the suction side tip winglet configuration using Non-Uniform Rational B-Splines (NURBS). This model is integrated with a Support Vector Regression (SVR) surrogate model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to establish a systematic parametric optimization design framework for tip winglets. Subsequent CFD simulations and flow field analyses of the optimized configurations were performed to explore the flow control mechanisms instigated by the winglet in the compressor tip region. The findings affirm that the optimization framework significantly enhances the design of tip winglet configurations, achieving a 9.13% improvement in the compressor’s stable operating margin while preserving the adiabatic efficiency and total pressure ratio nearly constant. Through a detailed comparative analysis of the flow fields associated with the optimized tip winglet configurations, the study elucidates the fundamental mechanism of stall margin enhancement facilitated by tip winglets in subsonic compressor stages. Specifically, the tip winglet structure not only mitigates the intensity of the leading edge tip leakage flow but also strengthens the wall-attached flow on the suction side near the leading edge, thereby improving flow conditions in this critical region.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111855"},"PeriodicalIF":5.8,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-04DOI: 10.1016/j.ast.2026.111854
Resul Kurt , Hürrem Akbıyık
Understanding the flow characteristics and enhancing the aerodynamic characteristics of non-slender delta wings (NSDWs) is crucial for the design and performance of next generation unmanned aerial vehicles (UAVs). In this experimental study, the suction surface of a NSDW is modified with channels as a passive flow control technique. A 50-degree sweep angle and a 45-degree leeward bevel angle of the NSDW are chosen. The effects of the flow channels on the aerodynamic performance of the model were investigated at different angles of attack (AoA) and at various h/c ratios. Aerodynamic force measurements were performed for all models with a Re value of 1.5 × 10⁵, and surface oil flow visualization experiments based on titanium dioxide (TiO₂) were conducted. All experiments were conducted at the open suction wind tunnel for various attack angles between 0° and 40° with and increment of 5° and the distance (h/c) between the test model and ground is set as 0.1, 0.4, and out-of-ground effect (OGE) ratios. According to the experimental results, it is revealed that the channel structure as surface modification on the test models provides increase in lift coefficient (CL) and decrease in drag coefficient (CD). Thus, the improvement in aerodynamic performance of a non-slender delta wing is achieved. The lift-to-drag ratio (L/D) of the base model has been enhanced by about 17% with the surface modification, depending on the different h/c ratios. In the light of surface oil flow visualizations experiments, the flow structures on the modified delta wings are observed and monitored.
{"title":"Aerodynamic performance of a non-slender delta wing modified with passive flow channels under ground effect","authors":"Resul Kurt , Hürrem Akbıyık","doi":"10.1016/j.ast.2026.111854","DOIUrl":"10.1016/j.ast.2026.111854","url":null,"abstract":"<div><div>Understanding the flow characteristics and enhancing the aerodynamic characteristics of non-slender delta wings (NSDWs) is crucial for the design and performance of next generation unmanned aerial vehicles (UAVs). In this experimental study, the suction surface of a NSDW is modified with channels as a passive flow control technique. A 50-degree sweep angle and a 45-degree leeward bevel angle of the NSDW are chosen. The effects of the flow channels on the aerodynamic performance of the model were investigated at different angles of attack (AoA) and at various h/c ratios. Aerodynamic force measurements were performed for all models with a <em>Re</em> value of 1.5 × 10⁵, and surface oil flow visualization experiments based on titanium dioxide (TiO₂) were conducted. All experiments were conducted at the open suction wind tunnel for various attack angles between 0° and 40° with and increment of 5° and the distance (h/c) between the test model and ground is set as 0.1, 0.4, and out-of-ground effect (OGE) ratios. According to the experimental results, it is revealed that the channel structure as surface modification on the test models provides increase in lift coefficient (C<sub>L</sub>) and decrease in drag coefficient (C<sub>D</sub>). Thus, the improvement in aerodynamic performance of a non-slender delta wing is achieved. The lift-to-drag ratio (L/D) of the base model has been enhanced by about 17% with the surface modification, depending on the different h/c ratios. In the light of surface oil flow visualizations experiments, the flow structures on the modified delta wings are observed and monitored.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111854"},"PeriodicalIF":5.8,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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