Pub Date : 2026-02-05DOI: 10.1016/j.ast.2026.111844
Nihat Çabuk
This study presents a real-time geometry-aware control strategy and its experimental validation for quadrotor UAVs equipped with actively adjustable dihedral angles. By integrating a cascaded PID control architecture with dynamic dihedral modulation, the system adapts its aerodynamic configuration during flight to enhance stability and responsiveness. Unlike conventional fixed-geometry multirotors, this platform enables geometric tuning in flight via a centralized actuation mechanism. Nonlinear simulations and autonomous flight tests were conducted for five different dihedral configurations () under identical flight scenarios, including takeoff, hover and landing. Performance metrics such as altitude accuracy, attitude stability (roll, pitch, yaw), and structural vibration levels were analyzed. The findings validate the feasibility and effectiveness of geometry-aware control for multirotor systems. In addition, this work introduces a novel class of UAVs capable of real-time structural reconfiguration, enabling adaptation to changing flight conditions, payload variations, or mission profiles.
{"title":"Design and implementation of real-time dihedral angle control for enhanced flight stability of quadrotor UAV","authors":"Nihat Çabuk","doi":"10.1016/j.ast.2026.111844","DOIUrl":"10.1016/j.ast.2026.111844","url":null,"abstract":"<div><div>This study presents a real-time geometry-aware control strategy and its experimental validation for quadrotor UAVs equipped with actively adjustable dihedral angles. By integrating a cascaded PID control architecture with dynamic dihedral modulation, the system adapts its aerodynamic configuration during flight to enhance stability and responsiveness. Unlike conventional fixed-geometry multirotors, this platform enables geometric tuning in flight via a centralized actuation mechanism. Nonlinear simulations and autonomous flight tests were conducted for five different dihedral configurations (<span><math><mrow><mi>γ</mi><mo>=</mo><mo>−</mo><msup><mn>7</mn><mo>∘</mo></msup><mo>,</mo><mo>−</mo><mn>3</mn><mo>.</mo><msup><mn>5</mn><mo>∘</mo></msup><mo>,</mo><msup><mn>0</mn><mo>∘</mo></msup><mo>,</mo><mo>+</mo><mn>3</mn><mo>.</mo><msup><mn>5</mn><mo>∘</mo></msup><mo>,</mo><mo>+</mo><msup><mn>7</mn><mo>∘</mo></msup></mrow></math></span>) under identical flight scenarios, including takeoff, hover and landing. Performance metrics such as altitude accuracy, attitude stability (roll, pitch, yaw), and structural vibration levels were analyzed. The findings validate the feasibility and effectiveness of geometry-aware control for multirotor systems. In addition, this work introduces a novel class of UAVs capable of real-time structural reconfiguration, enabling adaptation to changing flight conditions, payload variations, or mission profiles.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111844"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134808","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.2026.111843
Dechuan Ma, Gaohua Li, Jiahao Liu, Can Liu, Fuxin Wang
Dynamic stall on helicopter retreating blades involves complex flow phenomena, particularly with the emergence of local supersonic regions and shock waves. This study investigates the force generation mechanisms of a pitching NACA0012 wing section in dynamic stall using improved delayed detached eddy simulations (IDDES). At a moderate Reynolds number of and reduced frequencies and 0.25, the compressibility effects are examined by varying the freestream Mach number (, 0.3, and 0.5). An extended force partitioning method (E-FPM) is proposed to establish a direct linkage between flow fields and aerodynamic forces in compressible flows. In all cases, the majority of force production is attributed to the second Galilean invariant of the velocity gradient tensor, while the remainder arises from nonzero velocity divergence and density fluctuations due to compressibility. Prior to stall onset, leading-edge suction dominates lift and drag production, and turbulent separation vortices (TSVs) also have a positive contribution. As M∞ increases, the leading-edge stagnation point moves upstream. The insufficient flow acceleration reduces fluid stretching and strain around the high-curvature leading edge, causing a loss in lift when M∞ reaches 0.5. Upon stall onset, the dynamic stall vortex (DSV) becomes the main force contributor. At higher M∞, the DSV forms earlier due to advanced stall onset, which leads to earlier drag divergence and increased drag. However, the DSV also sheds earlier and weakens with enhanced compressibility. The reduced vorticity and increased density fluctuations within the vortex core region of the DSV result in lower peak lift and drag. With the DSV shedding, its positive contribution from the vortex core region diminishes without vorticity feed. The negative contribution from the vortex-induced stretching and strain becomes dominant and leads to lift stall. This work provides new insights into compressible dynamic stall physics and demonstrates the E-FPM’s effectiveness in identifying the physical origins of aerodynamic forces in such compressible, vortex-dominated flows.
{"title":"Correlation between aerodynamic forces and vortex dynamics of a NACA0012 wing section in compressible dynamic stall via IDDES","authors":"Dechuan Ma, Gaohua Li, Jiahao Liu, Can Liu, Fuxin Wang","doi":"10.1016/j.ast.2026.111843","DOIUrl":"10.1016/j.ast.2026.111843","url":null,"abstract":"<div><div>Dynamic stall on helicopter retreating blades involves complex flow phenomena, particularly with the emergence of local supersonic regions and shock waves. This study investigates the force generation mechanisms of a pitching NACA0012 wing section in dynamic stall using improved delayed detached eddy simulations (IDDES). At a moderate Reynolds number of <span><math><mrow><mi>R</mi><msub><mi>e</mi><mi>c</mi></msub><mo>=</mo><mn>500</mn><mo>,</mo><mn>000</mn></mrow></math></span> and reduced frequencies <span><math><mrow><mi>k</mi><mo>=</mo><mn>0.15</mn></mrow></math></span> and 0.25, the compressibility effects are examined by varying the freestream Mach number (<span><math><mrow><msub><mi>M</mi><mi>∞</mi></msub><mo>=</mo><mn>0.1</mn></mrow></math></span>, 0.3, and 0.5). An extended force partitioning method (E-FPM) is proposed to establish a direct linkage between flow fields and aerodynamic forces in compressible flows. In all cases, the majority of force production is attributed to the second Galilean invariant of the velocity gradient tensor, while the remainder arises from nonzero velocity divergence and density fluctuations due to compressibility. Prior to stall onset, leading-edge suction dominates lift and drag production, and turbulent separation vortices (TSVs) also have a positive contribution. As <em>M</em><sub>∞</sub> increases, the leading-edge stagnation point moves upstream. The insufficient flow acceleration reduces fluid stretching and strain around the high-curvature leading edge, causing a loss in lift when <em>M</em><sub>∞</sub> reaches 0.5. Upon stall onset, the dynamic stall vortex (DSV) becomes the main force contributor. At higher <em>M</em><sub>∞</sub>, the DSV forms earlier due to advanced stall onset, which leads to earlier drag divergence and increased drag. However, the DSV also sheds earlier and weakens with enhanced compressibility. The reduced vorticity and increased density fluctuations within the vortex core region of the DSV result in lower peak lift and drag. With the DSV shedding, its positive contribution from the vortex core region diminishes without vorticity feed. The negative contribution from the vortex-induced stretching and strain becomes dominant and leads to lift stall. This work provides new insights into compressible dynamic stall physics and demonstrates the E-FPM’s effectiveness in identifying the physical origins of aerodynamic forces in such compressible, vortex-dominated flows.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111843"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134810","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.2026.111863
Jintao Hu , Min Chen , Jiyuan Zhang , Yihao Xu , Hailong Tang
Accurate state estimation is critical for performance optimization and reliability enhancement in modern turbine systems. Although traditional filtering methods have demonstrated strong performance in various applications, their effectiveness is limited in the presence of component performance dispersion, high-dimensional system dynamics, performance degradation and uncertain control inputs. This study proposes a variational inference-based state estimation framework for aero-engine systems to address challenges arising from multi-source uncertainty. Under the assumption of a known state-space model, a loss function based on the stochastic variational lower bound is constructed to enable joint optimization of state variables and model parameters. This allows for precise inference of component health states and reliable identification of fault-related features. In cases where the aero-engine system model is partially or completely unknown, a hierarchical variational framework is further introduced, incorporating stochastic differential equations to simultaneously infer system states and uncover underlying control dynamics. Simulation results demonstrate that the proposed method consistently outperforms traditional filtering algorithms under varying noise levels and model uncertainties. It effectively distinguishes between modeling errors and actual performance deviations of engine components, leading to improved diagnostic accuracy and robustness.
{"title":"State estimation and system model correction of aero-engines under multi-source uncertainty: A hierarchical variational inference approach","authors":"Jintao Hu , Min Chen , Jiyuan Zhang , Yihao Xu , Hailong Tang","doi":"10.1016/j.ast.2026.111863","DOIUrl":"10.1016/j.ast.2026.111863","url":null,"abstract":"<div><div>Accurate state estimation is critical for performance optimization and reliability enhancement in modern turbine systems. Although traditional filtering methods have demonstrated strong performance in various applications, their effectiveness is limited in the presence of component performance dispersion, high-dimensional system dynamics, performance degradation and uncertain control inputs. This study proposes a variational inference-based state estimation framework for aero-engine systems to address challenges arising from multi-source uncertainty. Under the assumption of a known state-space model, a loss function based on the stochastic variational lower bound is constructed to enable joint optimization of state variables and model parameters. This allows for precise inference of component health states and reliable identification of fault-related features. In cases where the aero-engine system model is partially or completely unknown, a hierarchical variational framework is further introduced, incorporating stochastic differential equations to simultaneously infer system states and uncover underlying control dynamics. Simulation results demonstrate that the proposed method consistently outperforms traditional filtering algorithms under varying noise levels and model uncertainties. It effectively distinguishes between modeling errors and actual performance deviations of engine components, leading to improved diagnostic accuracy and robustness.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"174 ","pages":"Article 111863"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135571","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.2026.111860
Ayushmaan Singh
This study experimentally investigates fluidic thrust vectoring (FTV) in a Mach 1.6 axisymmetric jet using pulsed transverse air injection located 3.57 mm upstream of the nozzle exit. The influence of actuation frequency, duty cycle, and momentum ratio on jet deflection and vectoring efficiency is systematically examined, with direct comparison between steady and pulsed injection modes. Experiments were conducted using a precision-machined converging–diverging nozzle, employing wall-pressure measurements, total-pressure rake diagnostics, and Schlieren visualisation. Results show that pulsed injection consistently achieves higher mass-specific vectoring efficiency than steady injection at identical supply pressures, producing comparable jet deflection with reduced secondary mass flow. Maximum efficiency is observed at low duty cycles (20–25%) and forcing frequencies near 200 Hz. Numerical characterisation using a convective timescale and corresponding Strouhal number indicates that this frequency range aligns with dominant supersonic shear-layer instability modes. Analytical scaling relations and symbolic manipulation reveal a nonlinear dependence of vectoring efficiency on duty cycle and frequency, explaining the observed transition between efficient unsteady forcing and quasi-steady behaviour. Schlieren images confirm periodic bow-shock oscillations and transient asymmetry under pulsed actuation, demonstrating the effectiveness of unsteady fluidic control for supersonic jet vectoring.
{"title":"Experimental investigation of pulsed fluidic thrust vectoring in a Mach 1.6 axisymmetric jet using transverse air injection for enhanced vectoring efficiency","authors":"Ayushmaan Singh","doi":"10.1016/j.ast.2026.111860","DOIUrl":"10.1016/j.ast.2026.111860","url":null,"abstract":"<div><div>This study experimentally investigates fluidic thrust vectoring (FTV) in a Mach 1.6 axisymmetric jet using pulsed transverse air injection located 3.57 mm upstream of the nozzle exit. The influence of actuation frequency, duty cycle, and momentum ratio on jet deflection and vectoring efficiency is systematically examined, with direct comparison between steady and pulsed injection modes. Experiments were conducted using a precision-machined converging–diverging nozzle, employing wall-pressure measurements, total-pressure rake diagnostics, and Schlieren visualisation. Results show that pulsed injection consistently achieves higher mass-specific vectoring efficiency than steady injection at identical supply pressures, producing comparable jet deflection with reduced secondary mass flow. Maximum efficiency is observed at low duty cycles (20–25%) and forcing frequencies near 200 Hz. Numerical characterisation using a convective timescale and corresponding Strouhal number indicates that this frequency range aligns with dominant supersonic shear-layer instability modes. Analytical scaling relations and symbolic manipulation reveal a nonlinear dependence of vectoring efficiency on duty cycle and frequency, explaining the observed transition between efficient unsteady forcing and quasi-steady behaviour. Schlieren images confirm periodic bow-shock oscillations and transient asymmetry under pulsed actuation, demonstrating the effectiveness of unsteady fluidic control for supersonic jet vectoring.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111860"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134789","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.2026.111861
Xiaohu Chen , Ziheng Hong , Mingtao Zang , Ziyu Jia , Lianfeng Yang , Yanhua Wang , Zhongyi Wang , Yuzhang Wang
To address the challenge of predicting particle deposition characteristics on high-temperature air-cooled turbine in aero-engines, this work develops a high-temperature particle collision and deposition criterion based on the Weber number of molten particles. The effects of film cooling blowing ratio, hole geometry, particle diameter, and thermal barrier coatings (TBCs) on particle deposition behavior near film cooling holes are analyzed. The proposed model accurately predicts particle transport and deposition under large thermal gradients within air-cooled turbine cascade passages across a wide temperature range. Results show that particles are mainly deposited at the exits of the film cooling holes, in the leading-edge stagnation regions, and between the downstream cooling zones, forming pronounced internal blockage, horseshoe-shaped accumulation region, and ridge-like deposition band, respectively. With increasing blowing ratio, both deposition efficiency and deposition rate decrease nonlinearly, and the downstream ridge-like deposition becomes more prominent. When the blowing ratio increases from M = 0.5 to M = 3, particle deposition efficiency decreases by approximately 67 %. Compared with cylindrical holes, fan-shaped holes reduce total particle deposition by 5 %-42 % and suppress the downstream ridge deposition pattern, but increase deposition inside the holes. Applying TBCs increases the overall particle deposition rate by 14 %-27 %, enhances surface deposition, and accentuates the downstream ridge-like deposition structures. The particle diffusion deposition mechanism (St < 0.1), particle diffusion-collision deposition mechanism (0.1 < St < 1), and particle inertial buffering deposition mechanism (St > 1) are the main causes of the aforementioned deposition characteristics. Different blowing ratios, hole geometries, and TBCs all change the spatial scale and intensity of the counter-rotating vortex pairs, which dominate the two basic transport physics of particle ejection and entrainment, thereby determining the particle deposition characteristics. This study provides theoretical insights and quantitative data to support an understanding of particle deposition, film hole blockage, cooling performance degradation, TBCs failure, and blade erosion in turbine environments.
{"title":"Mechanisms of particle deposition around film cooling holes on nozzle guide vanes in aero-engines","authors":"Xiaohu Chen , Ziheng Hong , Mingtao Zang , Ziyu Jia , Lianfeng Yang , Yanhua Wang , Zhongyi Wang , Yuzhang Wang","doi":"10.1016/j.ast.2026.111861","DOIUrl":"10.1016/j.ast.2026.111861","url":null,"abstract":"<div><div>To address the challenge of predicting particle deposition characteristics on high-temperature air-cooled turbine in aero-engines, this work develops a high-temperature particle collision and deposition criterion based on the Weber number of molten particles. The effects of film cooling blowing ratio, hole geometry, particle diameter, and thermal barrier coatings (TBCs) on particle deposition behavior near film cooling holes are analyzed. The proposed model accurately predicts particle transport and deposition under large thermal gradients within air-cooled turbine cascade passages across a wide temperature range. Results show that particles are mainly deposited at the exits of the film cooling holes, in the leading-edge stagnation regions, and between the downstream cooling zones, forming pronounced internal blockage, horseshoe-shaped accumulation region, and ridge-like deposition band, respectively. With increasing blowing ratio, both deposition efficiency and deposition rate decrease nonlinearly, and the downstream ridge-like deposition becomes more prominent. When the blowing ratio increases from M = 0.5 to M = 3, particle deposition efficiency decreases by approximately 67 %. Compared with cylindrical holes, fan-shaped holes reduce total particle deposition by 5 %-42 % and suppress the downstream ridge deposition pattern, but increase deposition inside the holes. Applying TBCs increases the overall particle deposition rate by 14 %-27 %, enhances surface deposition, and accentuates the downstream ridge-like deposition structures. The particle diffusion deposition mechanism (<em>St</em> < 0.1), particle diffusion-collision deposition mechanism (0.1 < <em>St</em> < 1), and particle inertial buffering deposition mechanism (<em>St</em> > 1) are the main causes of the aforementioned deposition characteristics. Different blowing ratios, hole geometries, and TBCs all change the spatial scale and intensity of the counter-rotating vortex pairs, which dominate the two basic transport physics of particle ejection and entrainment, thereby determining the particle deposition characteristics. This study provides theoretical insights and quantitative data to support an understanding of particle deposition, film hole blockage, cooling performance degradation, TBCs failure, and blade erosion in turbine environments.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111861"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135559","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.2026.111827
Yujie Gan , Huan Zhao , Zhengang Zhang , Keyao Gan
Natural laminar flow (NLF) design offers significant potential for reducing aerodynamic drag in green aviation to reduce fuel consumption, emissions, and noise. However, as the Mach number increases, it’s difficult for the current aerodynamic optimization method to balance maintaining an extended laminar flow region and weakening shockwaves for a lower drag coefficient, due to the multimodal characteristic of NLF design. Surrogate-based optimization is a promising solution meeting this requirement, but it encounters the serious curse of dimensionality, hindering its application for complex NLF design. To resolve this issue, a novel Partial Least Squares-based multi-level multi-fidelity sparse polynomial chaos-kriging (PLS-MLMF-PCK) surrogate model-assisted global optimization method for high-dimensional NLF design is proposed. PLS-MLMF-PCK enables more rapid and accurate prediction for high-dimensional problems by introducing PLS to modify the model’s kernel function of each level of fidelity in MLMF-PCK. This method selects the effective dimensionality for hyperparameters and builds the new kernel function in the covariance matrix to enhance the ability of creating the optimal MLMF-PCK. Further, a PLS-MLMF-PCK-assisted global optimization method with an adaptive multi-fidelity in-filling criterion is proposed. Results show that the new PLS-MLMF-PCK reduces computational costs by 60–95 % while improving prediction accuracy by 40–75 % in high-dimensional scenarios compared to the original MLMF-PCK. Further, it is validated that the advantages of this method scale with problem dimensionality, demonstrating robust performance for designs involving more than fifty variables. More importantly, the proposed method effectively alleviates dimensionality challenges and avoids getting stuck in a local optimum in high-dimensional global optimization for NLF or aerodynamic/multidisciplinary design.
{"title":"Novel partial least squares-based multi-level multi-fidelity polynomial chaos-Kriging for high-dimensional surrogate and optimization of natural laminar flow shape","authors":"Yujie Gan , Huan Zhao , Zhengang Zhang , Keyao Gan","doi":"10.1016/j.ast.2026.111827","DOIUrl":"10.1016/j.ast.2026.111827","url":null,"abstract":"<div><div>Natural laminar flow (NLF) design offers significant potential for reducing aerodynamic drag in green aviation to reduce fuel consumption, emissions, and noise. However, as the Mach number increases, it’s difficult for the current aerodynamic optimization method to balance maintaining an extended laminar flow region and weakening shockwaves for a lower drag coefficient, due to the multimodal characteristic of NLF design. Surrogate-based optimization is a promising solution meeting this requirement, but it encounters the serious curse of dimensionality, hindering its application for complex NLF design. To resolve this issue, a novel Partial Least Squares-based multi-level multi-fidelity sparse polynomial chaos-kriging (PLS-MLMF-PCK) surrogate model-assisted global optimization method for high-dimensional NLF design is proposed. PLS-MLMF-PCK enables more rapid and accurate prediction for high-dimensional problems by introducing PLS to modify the model’s kernel function of each level of fidelity in MLMF-PCK. This method selects the effective dimensionality for hyperparameters and builds the new kernel function in the covariance matrix to enhance the ability of creating the optimal MLMF-PCK. Further, a PLS-MLMF-PCK-assisted global optimization method with an adaptive multi-fidelity in-filling criterion is proposed. Results show that the new PLS-MLMF-PCK reduces computational costs by 60–95 % while improving prediction accuracy by 40–75 % in high-dimensional scenarios compared to the original MLMF-PCK. Further, it is validated that the advantages of this method scale with problem dimensionality, demonstrating robust performance for designs involving more than fifty variables. More importantly, the proposed method effectively alleviates dimensionality challenges and avoids getting stuck in a local optimum in high-dimensional global optimization for NLF or aerodynamic/multidisciplinary design.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"173 ","pages":"Article 111827"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134809","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.2026.111838
Sirui Yang , Chengwen Zhong , Hao Jin , Sha Liu , Congshan Zhuo
A simplified unified wave-particle method is adopted to analyze how the freestream Mach number, jet Mach number, jet temperature, angle of jet, and jet pressure ratio affect the flow field characteristics, aerodynamic forces, and aerothermal effects of the interaction between the jet and the freestream flow over a three-dimensional blunt cone model in rarefied nitrogen flow. The numerical results obtained using the present method are validated against those from the DSMC method. Some of the trends summarized from the parametric study are consistent with the literature. The influence of molecular internal energy of diatomic gases under rarefied gas effects on three-dimensional jet interactions is also presented. Significant differences are observed between three-dimensional jets of diatomic gases and those of monoatomic gases. The findings reveal that: 1) At a constant momentum ratio, the interference zone and barrel shock remain nearly unchanged, while higher freestream Mach numbers reduce the jet’s influence on the flow field; 2) At constant freestream conditions, lower jet Mach numbers increase the jet’s influence on the blunt cone wall, with the jet pressure ratio having a stronger effect than the jet Mach number; 3) When the jet temperature is sufficiently high, comparable control effectiveness can be achieved with a smaller amount of jet gas. 4) Reducing the angle of jet increases the control efficiency, and in the rarefied regime, a smaller angle of jet does not readily lead to flow instabilities. 5) As the jet pressure ratio increases, the jet momentum ratio also rises, thereby intensifying the interaction between the jet and the freestream flow and influencing a larger region of the flow field. This research will provide valuable references for the application of jet-control devices in near-space flight vehicles.
{"title":"Parametric study of lateral jet interaction in diatomic gas non-equilibrium flows using wave-particle method","authors":"Sirui Yang , Chengwen Zhong , Hao Jin , Sha Liu , Congshan Zhuo","doi":"10.1016/j.ast.2026.111838","DOIUrl":"10.1016/j.ast.2026.111838","url":null,"abstract":"<div><div>A simplified unified wave-particle method is adopted to analyze how the freestream Mach number, jet Mach number, jet temperature, angle of jet, and jet pressure ratio affect the flow field characteristics, aerodynamic forces, and aerothermal effects of the interaction between the jet and the freestream flow over a three-dimensional blunt cone model in rarefied nitrogen flow. The numerical results obtained using the present method are validated against those from the DSMC method. Some of the trends summarized from the parametric study are consistent with the literature. The influence of molecular internal energy of diatomic gases under rarefied gas effects on three-dimensional jet interactions is also presented. Significant differences are observed between three-dimensional jets of diatomic gases and those of monoatomic gases. The findings reveal that: 1) At a constant momentum ratio, the interference zone and barrel shock remain nearly unchanged, while higher freestream Mach numbers reduce the jet’s influence on the flow field; 2) At constant freestream conditions, lower jet Mach numbers increase the jet’s influence on the blunt cone wall, with the jet pressure ratio having a stronger effect than the jet Mach number; 3) When the jet temperature is sufficiently high, comparable control effectiveness can be achieved with a smaller amount of jet gas. 4) Reducing the angle of jet increases the control efficiency, and in the rarefied regime, a smaller angle of jet does not readily lead to flow instabilities. 5) As the jet pressure ratio increases, the jet momentum ratio also rises, thereby intensifying the interaction between the jet and the freestream flow and influencing a larger region of the flow field. This research will provide valuable references for the application of jet-control devices in near-space flight vehicles.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"174 ","pages":"Article 111838"},"PeriodicalIF":5.8,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134812","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.2026.111849
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}
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