Pub Date : 2024-10-16DOI: 10.1016/j.ast.2024.109667
Nikola Gavrilovic , Yuchen Leng , Jean-Marc Moschetta
The Drone Mermoz project aims to evaluate the feasibility of an uncrewed aircraft system powered by a hydrogen fuel cell, designed to traverse the Atlantic Ocean. The aircraft must complete a journey of 3000 km with a minimum endurance of 36 hours. In addition to ensuring sufficient onboard energy, a critical requirement is the stable operation of the entire propulsion system throughout the journey.
This paper outlines the developmental stages, theoretical modeling, and experimental testing of a thermal management system designed for a long-range uncrewed aircraft system equipped with hydrogen fuel cell-based propulsion. The 4-meter, sub-25 kg aircraft is engineered to undertake a 3000 km journey from Dakar, Senegal to Natal, Brazil.
A critical challenge in developing this hydrogen-powered drone is designing an efficient thermal management system to ensure continuous ventilation of the fuselage. While one side of the system involves the fuel cell generating electricity for aircraft propulsion, the other side must effectively dissipate a substantial amount of heat to ensure the stable operation of the entire system.
{"title":"Thermal control of a hydrogen-powered uncrewed aerial vehicle for crossing the Atlantic Ocean","authors":"Nikola Gavrilovic , Yuchen Leng , Jean-Marc Moschetta","doi":"10.1016/j.ast.2024.109667","DOIUrl":"10.1016/j.ast.2024.109667","url":null,"abstract":"<div><div>The Drone Mermoz project aims to evaluate the feasibility of an uncrewed aircraft system powered by a hydrogen fuel cell, designed to traverse the Atlantic Ocean. The aircraft must complete a journey of 3000 km with a minimum endurance of 36 hours. In addition to ensuring sufficient onboard energy, a critical requirement is the stable operation of the entire propulsion system throughout the journey.</div><div>This paper outlines the developmental stages, theoretical modeling, and experimental testing of a thermal management system designed for a long-range uncrewed aircraft system equipped with hydrogen fuel cell-based propulsion. The 4-meter, sub-25 kg aircraft is engineered to undertake a 3000 km journey from Dakar, Senegal to Natal, Brazil.</div><div>A critical challenge in developing this hydrogen-powered drone is designing an efficient thermal management system to ensure continuous ventilation of the fuselage. While one side of the system involves the fuel cell generating electricity for aircraft propulsion, the other side must effectively dissipate a substantial amount of heat to ensure the stable operation of the entire system.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109667"},"PeriodicalIF":5.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1016/j.ast.2024.109658
Changhui Wang, Wencheng Li, Mei Liang
In this article, an event-triggered finite-time adaptive neural network control tracking strategy is proposed for quadrotor unmanned aerial vehicle (UAV) with input saturation and error constraints. Firstly, the radial basis function neural networks (RBFNNs) are adopted to identify the unknown uncertainty of quadrotor UAV model from the installation errors, gyroscope errors and so on. An auxiliary equation is constructed to deal with input physical saturation from the actuator motors. Additionally, by combining the performance function and error transformation, the issue of error constraint is solved. Based on the Lyapunov stability theory and event-triggered mechanisms, a finite-time adaptive neural network scheme is developed to ensure that the closed-loop quadrotor UAV system is semi-globally practically finite-time stable, and save the computation, resources, and transmission load. Finally, the simulation results illustrate the good tracking performance of quadrotor UAV by using the proposed control strategy.
{"title":"Event-triggered finite-time adaptive neural network control for quadrotor UAV with input saturation and tracking error constraints","authors":"Changhui Wang, Wencheng Li, Mei Liang","doi":"10.1016/j.ast.2024.109658","DOIUrl":"10.1016/j.ast.2024.109658","url":null,"abstract":"<div><div>In this article, an event-triggered finite-time adaptive neural network control tracking strategy is proposed for quadrotor unmanned aerial vehicle (UAV) with input saturation and error constraints. Firstly, the radial basis function neural networks (RBFNNs) are adopted to identify the unknown uncertainty of quadrotor UAV model from the installation errors, gyroscope errors and so on. An auxiliary equation is constructed to deal with input physical saturation from the actuator motors. Additionally, by combining the performance function and error transformation, the issue of error constraint is solved. Based on the Lyapunov stability theory and event-triggered mechanisms, a finite-time adaptive neural network scheme is developed to ensure that the closed-loop quadrotor UAV system is semi-globally practically finite-time stable, and save the computation, resources, and transmission load. Finally, the simulation results illustrate the good tracking performance of quadrotor UAV by using the proposed control strategy.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109658"},"PeriodicalIF":5.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441361","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 : 2024-10-13DOI: 10.1016/j.ast.2024.109668
Jian Li , Chenyu Ding , Tianwei Yang , Genghao Lin , Jianguo Ning
The present study focuses on fundamental research about the transition from a planar detonation to a cylindrical detonation and the propagation of the diverging cylindrical detonation. We aim to figure out the mechanism of the transition and propagation of the diverging cylindrical detonation by analyzing the cellular pattern and critical initial pressure. The findings highlight that the successful detonation in a cylindrical chamber via transition through a straight channel is predominantly influenced by diffraction at the corners and the successive continuous reflections between the front and rear walls. Depending on the initial pressure, the initiation modes exhibit characteristics of subcritical, critical, and supercritical three-stage processes. Sustained propagation of cylindrical detonations necessitates increasing the number of cells to match the growth rate in the front region. Experimental investigations reveal two distinct modes of cell number increase: mild and violent. In the case of the former, cell number increase predominantly occurs on a scale of two to three times the characteristic cell size of the Chapman-Jouguet detonation. In contrast, a decaying Mach stem undergoes twisting and evolves into local kinks, leading to the development of new triple-wave points. The latter mode typically occurs near the limit, where cell increase primarily arises from randomly occurring local explosions, and operates on a scale of ten times the characteristic cell size or the chamber diameter. In addition, a numerical study of two-dimensional fundamental problems abstracted from the experiment is conducted to help interpret experimental results and reveal more about the physics of the problem.
{"title":"Research on the initiation and wavefront evolution of diverging cylindrical detonations of acetylene and oxygen mixtures","authors":"Jian Li , Chenyu Ding , Tianwei Yang , Genghao Lin , Jianguo Ning","doi":"10.1016/j.ast.2024.109668","DOIUrl":"10.1016/j.ast.2024.109668","url":null,"abstract":"<div><div>The present study focuses on fundamental research about the transition from a planar detonation to a cylindrical detonation and the propagation of the diverging cylindrical detonation. We aim to figure out the mechanism of the transition and propagation of the diverging cylindrical detonation by analyzing the cellular pattern and critical initial pressure. The findings highlight that the successful detonation in a cylindrical chamber via transition through a straight channel is predominantly influenced by diffraction at the corners and the successive continuous reflections between the front and rear walls. Depending on the initial pressure, the initiation modes exhibit characteristics of subcritical, critical, and supercritical three-stage processes. Sustained propagation of cylindrical detonations necessitates increasing the number of cells to match the growth rate in the front region. Experimental investigations reveal two distinct modes of cell number increase: mild and violent. In the case of the former, cell number increase predominantly occurs on a scale of two to three times the characteristic cell size of the Chapman-Jouguet detonation. In contrast, a decaying Mach stem undergoes twisting and evolves into local kinks, leading to the development of new triple-wave points. The latter mode typically occurs near the limit, where cell increase primarily arises from randomly occurring local explosions, and operates on a scale of ten times the characteristic cell size or the chamber diameter. In addition, a numerical study of two-dimensional fundamental problems abstracted from the experiment is conducted to help interpret experimental results and reveal more about the physics of the problem.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109668"},"PeriodicalIF":5.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444671","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 : 2024-10-12DOI: 10.1016/j.ast.2024.109637
Yulin Ma , Zhou Du , Quanyong Xu , Jiaheng Qi
In the design process of compressors, calculating the S1 flow surface involves solving the Navier-Stokes equations, which results in slow convergence and makes determining cascade characteristics time-consuming. However, deep learning offers significant advantages in flow field reconstruction by not only automatically extracting complex flow features and reducing prediction time but also providing high accuracy in reconstruction. This paper implements the rapid reconstruction of the compressor S1 flow surface cascade flow field using two deep learning models: U-Net and 1D-CNN. Using a double-circular arc airfoil as an example, we selected four key design parameters that define the geometry and position of the airfoil, ultimately designing 5,292 sets of cascade geometries. By performing batch meshing and CFD simulations, we built a cascade flow field dataset. The U-Net neural network uses design parameters as input and outputs the aerodynamic distribution of the cascade flow field. After training, it can directly predict the flow field based on the design parameters. Since the U-Net model cannot directly obtain the aerodynamic parameter distribution and flow field aerodynamic coefficients on the airfoil surface, a 1D-CNN model is used as a complementary approach. The 1D-CNN model takes the design parameters as input and outputs the aerodynamic parameter distribution on the airfoil surface and the flow field aerodynamic coefficients. The prediction results show that the U-Net model achieves an average relative error of <1% in cascade flow field reconstruction, while the 1D-CNN model achieves an average relative error of <1% in predicting the pressure recovery coefficient and <2% in predicting the total pressure loss coefficient. This study presents a method for the rapid reconstruction of compressor blade cascade flow fields, which helps improve design efficiency and shorten the design cycle.
{"title":"Flow field reconstruction of compressor blade cascade based on deep learning methods","authors":"Yulin Ma , Zhou Du , Quanyong Xu , Jiaheng Qi","doi":"10.1016/j.ast.2024.109637","DOIUrl":"10.1016/j.ast.2024.109637","url":null,"abstract":"<div><div>In the design process of compressors, calculating the S1 flow surface involves solving the Navier-Stokes equations, which results in slow convergence and makes determining cascade characteristics time-consuming. However, deep learning offers significant advantages in flow field reconstruction by not only automatically extracting complex flow features and reducing prediction time but also providing high accuracy in reconstruction. This paper implements the rapid reconstruction of the compressor S1 flow surface cascade flow field using two deep learning models: U-Net and 1D-CNN. Using a double-circular arc airfoil as an example, we selected four key design parameters that define the geometry and position of the airfoil, ultimately designing 5,292 sets of cascade geometries. By performing batch meshing and CFD simulations, we built a cascade flow field dataset. The U-Net neural network uses design parameters as input and outputs the aerodynamic distribution of the cascade flow field. After training, it can directly predict the flow field based on the design parameters. Since the U-Net model cannot directly obtain the aerodynamic parameter distribution and flow field aerodynamic coefficients on the airfoil surface, a 1D-CNN model is used as a complementary approach. The 1D-CNN model takes the design parameters as input and outputs the aerodynamic parameter distribution on the airfoil surface and the flow field aerodynamic coefficients. The prediction results show that the U-Net model achieves an average relative error of <1% in cascade flow field reconstruction, while the 1D-CNN model achieves an average relative error of <1% in predicting the pressure recovery coefficient and <2% in predicting the total pressure loss coefficient. This study presents a method for the rapid reconstruction of compressor blade cascade flow fields, which helps improve design efficiency and shorten the design cycle.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109637"},"PeriodicalIF":5.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142534782","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 : 2024-10-11DOI: 10.1016/j.ast.2024.109648
Dong Jiang , Meisheng Zhang , Yongjie Xu , Hui Qian , Yichao Yang , Dahai Zhang , Qinghua Liu
The deep learning method provides an effective alternative to numerical simulations for establishing the nonlinear input-output relationship and calculating dynamic responses of rotor systems. To overcome the low generalization capability of pure data-driven long short-term memory (LSTM) networks when predicting dynamic responses to out-of-distribution inputs, a dynamic response prediction method using physics-informed multi-LSTM networks is proposed. This approach incorporates required physical constraints into the deep LSTM network, allowing the model training process to optimize the network parameters within the feasible solution space that adheres to physical laws. Consequently, this enhances the physical interpretability of the deep learning model. Specifically, two physics-informed multi-LSTM network architectures are introduced, and physical laws of equation of motion, state dependency and hysteretic constitutive relationship are considered to construct the physics loss. The feasibility of the proposed method is verified by a Bouc-Wen hysteresis model and a simulated gas generator rotor. The response prediction performance of the two networks is validated on a constructed fault rotor dataset with significant sample differences, along with cross-speed and cross-node prediction validation for the rotor system. The results demonstrate that the trained networks exhibit strong robustness and generalization capabilities, making them suitable as surrogate models for rotor systems.
{"title":"Rotor dynamic response prediction using physics-informed multi-LSTM networks","authors":"Dong Jiang , Meisheng Zhang , Yongjie Xu , Hui Qian , Yichao Yang , Dahai Zhang , Qinghua Liu","doi":"10.1016/j.ast.2024.109648","DOIUrl":"10.1016/j.ast.2024.109648","url":null,"abstract":"<div><div>The deep learning method provides an effective alternative to numerical simulations for establishing the nonlinear input-output relationship and calculating dynamic responses of rotor systems. To overcome the low generalization capability of pure data-driven long short-term memory (LSTM) networks when predicting dynamic responses to out-of-distribution inputs, a dynamic response prediction method using physics-informed multi-LSTM networks is proposed. This approach incorporates required physical constraints into the deep LSTM network, allowing the model training process to optimize the network parameters within the feasible solution space that adheres to physical laws. Consequently, this enhances the physical interpretability of the deep learning model. Specifically, two physics-informed multi-LSTM network architectures are introduced, and physical laws of equation of motion, state dependency and hysteretic constitutive relationship are considered to construct the physics loss. The feasibility of the proposed method is verified by a Bouc-Wen hysteresis model and a simulated gas generator rotor. The response prediction performance of the two networks is validated on a constructed fault rotor dataset with significant sample differences, along with cross-speed and cross-node prediction validation for the rotor system. The results demonstrate that the trained networks exhibit strong robustness and generalization capabilities, making them suitable as surrogate models for rotor systems.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109648"},"PeriodicalIF":5.0,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538116","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 : 2024-10-11DOI: 10.1016/j.ast.2024.109656
Ruilin Huang , Linhao Cheng , Zhengjiang Ji , Guang Cui , Maoyuan Li , Leilei Yan , Yuexuan Li , Xitao Zheng
In this work, a novel multifunctional polymethacrylimide (PMI) foam sandwich structure with enhanced electromagnetic (EM) wave transmissivity and compressive properties is proposed aiming at the demand of high-performance radome structures for aeronautic industry. A double-parabolic-shaped copper arrays is designed and formed a spoof surface plasmon polaritons (SSPPs) structure, which was embedded into the traditional PMI foam sandwich to enhance its microwave transmission property. The simulation and experimental results indicated that the average transmissivity can be increased by 20.9% due to SSPPs structure involvement, which can restrain and regulate the propagation path of EM wave. At the same time, the polytetrafluoroethylene (PTFE) boards plated with the proposed SSPPs structure are inserted into the PMI foam core in the form of interlocking square honeycomb. The coupling effect between honeycomb and PMI foam where the buckling of honeycomb wall is restrained, leading to a significant improvement of compressive strength and energy absorption by 95% and 72%, respectively. Overall, present simultaneous enhancement design of PMI foam sandwich structure with EM wave transmission and compressive properties can provide a novel and practical design scheme of radome structure.
{"title":"Simultaneous enhancement design of polymethacrylimide foam sandwich structure with EM wave transmission and compressive properties","authors":"Ruilin Huang , Linhao Cheng , Zhengjiang Ji , Guang Cui , Maoyuan Li , Leilei Yan , Yuexuan Li , Xitao Zheng","doi":"10.1016/j.ast.2024.109656","DOIUrl":"10.1016/j.ast.2024.109656","url":null,"abstract":"<div><div>In this work, a novel multifunctional polymethacrylimide (PMI) foam sandwich structure with enhanced electromagnetic (EM) wave transmissivity and compressive properties is proposed aiming at the demand of high-performance radome structures for aeronautic industry. A double-parabolic-shaped copper arrays is designed and formed a spoof surface plasmon polaritons (SSPPs) structure, which was embedded into the traditional PMI foam sandwich to enhance its microwave transmission property. The simulation and experimental results indicated that the average transmissivity can be increased by 20.9% due to SSPPs structure involvement, which can restrain and regulate the propagation path of EM wave. At the same time, the polytetrafluoroethylene (PTFE) boards plated with the proposed SSPPs structure are inserted into the PMI foam core in the form of interlocking square honeycomb. The coupling effect between honeycomb and PMI foam where the buckling of honeycomb wall is restrained, leading to a significant improvement of compressive strength and energy absorption by 95% and 72%, respectively. Overall, present simultaneous enhancement design of PMI foam sandwich structure with EM wave transmission and compressive properties can provide a novel and practical design scheme of radome structure.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109656"},"PeriodicalIF":5.0,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142534778","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 : 2024-10-11DOI: 10.1016/j.ast.2024.109655
Shengjun Zeng, Wei Fan, Hui Ren
In this work, a novel orbital-attitude coupled control framework is developed for the electric solar wind sail (E-sail) spacecraft, aiming to handle the orbital transformation and attitude maneuver simultaneously. In the framework, the desired attitude parameters and the slow-varying voltage component are provided by the orbital control strategy, while the current attitude parameters and the fast-varying voltage component are manipulated by the attitude control strategy to approach their desired values. The orbital-attitude coupled characteristics of the E-sail spacecraft, including the flexibility-induced coupling effect, are fully described by the referenced nodal coordinate formulation. Considering the input saturation conditions, the governing equation for the orbital control strategy is then derived, in which the in-plane and out-of-plane displacement and velocity errors are prescribed as the state variables to be eliminated. An integral sliding mode control (ISMC) scheme is proposed to improve the robustness against the unmeasurable disturbance term. A model predictive control (MPC) scheme is introduced to enhance the convergence efficiency, where a quadratic optimization is performed to plan the desired attitude parameters and voltage components within the prediction horizon. To evaluate the control performance in the orbital transformation and attitude maneuver missions on the displaced non-Keplerian orbit, a series of scenarios with complex initial conditions are simulated under different control schemes, including the ISMC-MPC compound scheme. The results show that the control strategy designed under the rigid-body assumptions may not be feasible for the flexible E-sail spacecraft, while the investigated control strategy realizes the accurate and efficient convergence of the orbital and attitude variables on both the rigid and flexible E-sail spacecraft with the tether deformation stabilized.
{"title":"An orbital-attitude coupled control framework for a full-scale flexible electric solar wind sail spacecraft in orbital transformation missions","authors":"Shengjun Zeng, Wei Fan, Hui Ren","doi":"10.1016/j.ast.2024.109655","DOIUrl":"10.1016/j.ast.2024.109655","url":null,"abstract":"<div><div>In this work, a novel orbital-attitude coupled control framework is developed for the electric solar wind sail (E-sail) spacecraft, aiming to handle the orbital transformation and attitude maneuver simultaneously. In the framework, the desired attitude parameters and the slow-varying voltage component are provided by the orbital control strategy, while the current attitude parameters and the fast-varying voltage component are manipulated by the attitude control strategy to approach their desired values. The orbital-attitude coupled characteristics of the E-sail spacecraft, including the flexibility-induced coupling effect, are fully described by the referenced nodal coordinate formulation. Considering the input saturation conditions, the governing equation for the orbital control strategy is then derived, in which the in-plane and out-of-plane displacement and velocity errors are prescribed as the state variables to be eliminated. An integral sliding mode control (ISMC) scheme is proposed to improve the robustness against the unmeasurable disturbance term. A model predictive control (MPC) scheme is introduced to enhance the convergence efficiency, where a quadratic optimization is performed to plan the desired attitude parameters and voltage components within the prediction horizon. To evaluate the control performance in the orbital transformation and attitude maneuver missions on the displaced non-Keplerian orbit, a series of scenarios with complex initial conditions are simulated under different control schemes, including the ISMC-MPC compound scheme. The results show that the control strategy designed under the rigid-body assumptions may not be feasible for the flexible E-sail spacecraft, while the investigated control strategy realizes the accurate and efficient convergence of the orbital and attitude variables on both the rigid and flexible E-sail spacecraft with the tether deformation stabilized.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109655"},"PeriodicalIF":5.0,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142437751","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 : 2024-10-10DOI: 10.1016/j.ast.2024.109660
Ming Yan , Ye Tian , Zhijian Ding , Yi Zhang , Fuyu Zhong , Wenyan Song , Jialing Le
As the flight Mach number increases, scramjet engines struggle to achieve stabilized combustion. In the present investigation, a reliable combustion strategy is developed for a kerosene-fueled supersonic combustor. Assisted by air throttling, this enables the combustor to operate efficiently at a flight Mach number of 7. Various experimental measurement techniques are used to capture the combustion process and flow characteristics. A three-dimensional numerical method based on the Reynolds-averaged Navier–Stokes equations is employed to analyse the effects of air throttling on the non-reacting and reacting flow fields. The whole combustion test is effectively divided into five processes covering the establishment of non-reacting flow, ignition, flame stabilization, and flameout. Analysis of the experimental and numerical flow fields indicates that, as the origin of the initial flame in the combustor, the aerodynamic compression induced by air throttling promotes the kerosene/air sub-mixing region. The main mixing process is enhanced by the arrangement of ramps and cavity, which contribute to effective multi-channel injection. Two combustion modes are observed, namely combined cavity shear-layer/recirculation stabilized combustion and jet-wake stabilized combustion. In the reacting flow field, the additional injection of throttling gas improves the thrust augmentation at the cost of reduced combustion intensity. The outlet combustion efficiency and total pressure recovery coefficient are found to decrease by 8.49% and 28.79%, respectively.
{"title":"A reliable combustion strategy for a throttling-assisted supersonic combustor with flight Mach 7","authors":"Ming Yan , Ye Tian , Zhijian Ding , Yi Zhang , Fuyu Zhong , Wenyan Song , Jialing Le","doi":"10.1016/j.ast.2024.109660","DOIUrl":"10.1016/j.ast.2024.109660","url":null,"abstract":"<div><div>As the flight Mach number increases, scramjet engines struggle to achieve stabilized combustion. In the present investigation, a reliable combustion strategy is developed for a kerosene-fueled supersonic combustor. Assisted by air throttling, this enables the combustor to operate efficiently at a flight Mach number of 7. Various experimental measurement techniques are used to capture the combustion process and flow characteristics. A three-dimensional numerical method based on the Reynolds-averaged Navier–Stokes equations is employed to analyse the effects of air throttling on the non-reacting and reacting flow fields. The whole combustion test is effectively divided into five processes covering the establishment of non-reacting flow, ignition, flame stabilization, and flameout. Analysis of the experimental and numerical flow fields indicates that, as the origin of the initial flame in the combustor, the aerodynamic compression induced by air throttling promotes the kerosene/air sub-mixing region. The main mixing process is enhanced by the arrangement of ramps and cavity, which contribute to effective multi-channel injection. Two combustion modes are observed, namely combined cavity shear-layer/recirculation stabilized combustion and jet-wake stabilized combustion. In the reacting flow field, the additional injection of throttling gas improves the thrust augmentation at the cost of reduced combustion intensity. The outlet combustion efficiency and total pressure recovery coefficient are found to decrease by 8.49% and 28.79%, respectively.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109660"},"PeriodicalIF":5.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434168","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 : 2024-10-09DOI: 10.1016/j.ast.2024.109650
Viktar Beliautsou, Aleksandra Beliautsou
Vertical take-off and landing (VTOL) unmanned aircrafts are the newest and rapidly developing topic which is not only capable of improving Unmanned Aerial Vehicles (UAV) potential but also to create new use cases. This paper proposes a new convertible VTOL concept designed to obtain optimum flight characteristics for monitoring or flying over long objects. The distinctive feature of the proposed design is a combination of a flying wing with a longitudinal bicopter. The aircraft folds the wings down along the main axis of the aircraft during vertical take-offs and landings to descend the center of gravity and increase stability in bicopter mode. The convertible plane maximizes performance during horizontal flight while maintaining vertical take-off and landing capabilities.
The design has been implemented in prototype, and the internal systems and the airframe have been designed and manufactured. As a result, the calculated technical characteristics of the UAV including wind resistance capability were described, the principal elements and components of the design were discussed, and the flight tests of the prototype created were conducted and results presented. Furthermore, the advantages and disadvantages of the concept are reviewed and further development of the project is discussed. The conducted work allows us to confirm the assumption that the developed concept can be used for real-world monitoring missions and to continue developing the concept for a full-scale UAV.
{"title":"Prop-plane — New convertible VTOL UAV as a combination of a longitudinal bicopter and a flying wing with a tilt-rotor powertrain","authors":"Viktar Beliautsou, Aleksandra Beliautsou","doi":"10.1016/j.ast.2024.109650","DOIUrl":"10.1016/j.ast.2024.109650","url":null,"abstract":"<div><div>Vertical take-off and landing (VTOL) unmanned aircrafts are the newest and rapidly developing topic which is not only capable of improving Unmanned Aerial Vehicles (UAV) potential but also to create new use cases. This paper proposes a new convertible VTOL concept designed to obtain optimum flight characteristics for monitoring or flying over long objects. The distinctive feature of the proposed design is a combination of a flying wing with a longitudinal bicopter. The aircraft folds the wings down along the main axis of the aircraft during vertical take-offs and landings to descend the center of gravity and increase stability in bicopter mode. The convertible plane maximizes performance during horizontal flight while maintaining vertical take-off and landing capabilities.</div><div>The design has been implemented in prototype, and the internal systems and the airframe have been designed and manufactured. As a result, the calculated technical characteristics of the UAV including wind resistance capability were described, the principal elements and components of the design were discussed, and the flight tests of the prototype created were conducted and results presented. Furthermore, the advantages and disadvantages of the concept are reviewed and further development of the project is discussed. The conducted work allows us to confirm the assumption that the developed concept can be used for real-world monitoring missions and to continue developing the concept for a full-scale UAV.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":"155 ","pages":"Article 109650"},"PeriodicalIF":5.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.ast.2024.109649
Ma Qiyue , Gao Chuanqiang , Xiong Neng , Zhang Weiwei
Transonic shock buffet is a significant self-excited shock oscillations and aerodynamic instability phenomenon induced by shock-boundary layer interaction, which limits the flight envelope and even causes flight accidents. The aviation industry has a significant interest in accurately predicting the shock buffet onset boundary, defined by a specific combination of Mach number and angle of attack. While the current methods of steady and unsteady numerical simulation suffer from a contradiction of efficiency and accuracy. In the current paper, a flow feature-informed neural network (FINN) model is constructed to predict the buffet onset boundary over airfoils. Typical features associated with buffet onset are extracted from the steady base flow and subsequently integrated into the hidden layer of the neural network to impose physical constraints. With the test cases of the NACA0012 airfoil at various Mach numbers, the FINN model can accurately predict the damping representing the unsteady instability margin. Compared to the direct mapping input-output neural network (NN) model, the proposed method with shock wave feature-informed has enhanced accuracy, with an average relative error decreased by 70% at extrapolated Mach numbers. This research demonstrates the effectiveness of the FINN model in predicting the buffet onset, which leverages physics features derived from the more economical steady solution far from the onset boundary at a given predicted Mach number.
跨音速冲击缓冲是由冲击边界层相互作用诱发的一种显著的自激冲击振荡和气动不稳定现象，它限制了飞行包线，甚至导致飞行事故。航空业对准确预测由特定马赫数和攻角组合定义的冲击缓冲起始边界非常感兴趣。而目前的稳定和非稳定数值模拟方法存在效率和精度的矛盾。本文构建了一个流动特征信息神经网络（FINN）模型，用于预测机翼上的缓冲区起始边界。从稳定的基本流中提取与缓冲区开始相关的典型特征，然后将其集成到神经网络的隐层中，以施加物理约束。通过 NACA0012 机翼在不同马赫数下的测试案例，FINN 模型可以准确预测代表非稳定不稳定性边缘的阻尼。与直接映射输入输出神经网络（NN）模型相比，带有冲击波特征信息的拟议方法提高了准确性，在推算马赫数时平均相对误差减少了 70%。这项研究证明了 FINN 模型在预测缓冲区开始时的有效性，该模型在给定的预测马赫数下利用了从远离开始边界的更经济的稳定解中得出的物理特征。
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