Pub Date : 2023-09-20DOI: 10.1177/09544100231203404
Saleh Abuhanieh, Hasan U. Akay
In this work, the ability of open-source CFD tools to conduct store separation simulations from cavities is evaluated and validated using a generic test case from the literature. Firstly, the ability and accuracy of these tools for solving cavity flows at high speeds are evaluated. Secondly, their competence in predicting the trajectory of a generic store from a generic deep cavity is checked. Finally, and in order to reduce the associated computational costs, a release-time dependability factor from the recent literature is studied and evaluated. The obtained results using the selected open-source CFD tools matched quite well with the wind tunnel results. Furthermore, the results show that predicting the release-time dependability using a quantified index/factor can be a potential remedy for reducing the computational cost for this type of CFD simulations.
{"title":"Numerical investigation of store separation from cavity problems at high speeds","authors":"Saleh Abuhanieh, Hasan U. Akay","doi":"10.1177/09544100231203404","DOIUrl":"https://doi.org/10.1177/09544100231203404","url":null,"abstract":"In this work, the ability of open-source CFD tools to conduct store separation simulations from cavities is evaluated and validated using a generic test case from the literature. Firstly, the ability and accuracy of these tools for solving cavity flows at high speeds are evaluated. Secondly, their competence in predicting the trajectory of a generic store from a generic deep cavity is checked. Finally, and in order to reduce the associated computational costs, a release-time dependability factor from the recent literature is studied and evaluated. The obtained results using the selected open-source CFD tools matched quite well with the wind tunnel results. Furthermore, the results show that predicting the release-time dependability using a quantified index/factor can be a potential remedy for reducing the computational cost for this type of CFD simulations.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136373519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2023-09-20DOI: 10.1177/09544100231202930
Dongyu Xu, Zhaodi Wang, Biao Leng
Rain attenuation prediction of earth-space links is of vital significance for the application and development of satellite communication. Recently, most rain attenuation prediction methods are based on semi-empirical models or data-driven models, the former suffering from incompleteness problem, the latter faced with limited performance due to scarce data. In order to realize higher rain attenuation prediction performance, we propose a novel hybrid model ANN_ITU that combines advantages of the semi-empirical model and the artificial neural network. In ANN_ITU framework, the semi-empirical model ITU-R P.618-12 is leveraged to predict rain attenuation, and a six-layer artificial neural network is utilized to correct the rain attenuation predicted by ITU-R P.618-12, thus generating the final rain attenuation value. What’s more, we also present theories of two machine-learning based rain attenuation prediction methods, namely, random forest and support vector regression. Last but not least, we expound on processes of DBSG3 dataset filtering and data preprocessing. Experiments on DBSG3 dataset are carried out. Experimental results demonstrate that the hybrid ANN_ITU algorithm outperforms purely semi-empirical algorithms and data-driven algorithms. The evaluation indexes mean value, standard deviation, and root mean square value are 0.0355%, 19.63%, and 19.63%, respectively, which prove the effectiveness and precision of our rain attenuation prediction model ANN_ITU.
{"title":"ANN_ITU: Predicting rain attenuation with a hybrid model for earth-space links","authors":"Dongyu Xu, Zhaodi Wang, Biao Leng","doi":"10.1177/09544100231202930","DOIUrl":"https://doi.org/10.1177/09544100231202930","url":null,"abstract":"Rain attenuation prediction of earth-space links is of vital significance for the application and development of satellite communication. Recently, most rain attenuation prediction methods are based on semi-empirical models or data-driven models, the former suffering from incompleteness problem, the latter faced with limited performance due to scarce data. In order to realize higher rain attenuation prediction performance, we propose a novel hybrid model ANN_ITU that combines advantages of the semi-empirical model and the artificial neural network. In ANN_ITU framework, the semi-empirical model ITU-R P.618-12 is leveraged to predict rain attenuation, and a six-layer artificial neural network is utilized to correct the rain attenuation predicted by ITU-R P.618-12, thus generating the final rain attenuation value. What’s more, we also present theories of two machine-learning based rain attenuation prediction methods, namely, random forest and support vector regression. Last but not least, we expound on processes of DBSG3 dataset filtering and data preprocessing. Experiments on DBSG3 dataset are carried out. Experimental results demonstrate that the hybrid ANN_ITU algorithm outperforms purely semi-empirical algorithms and data-driven algorithms. The evaluation indexes mean value, standard deviation, and root mean square value are 0.0355%, 19.63%, and 19.63%, respectively, which prove the effectiveness and precision of our rain attenuation prediction model ANN_ITU.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136306642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2023-09-19DOI: 10.1177/09544100231201215
Prashant Kumar, Sarvesh Kumar Sonkar, Riya Catherine George, Ajoy Kanti Ghosh, Deepu Philip
Aircraft system identification aims to estimate the aerodynamic force and moment coefficients utilizing intelligent modeling and parametric identification methodologies. Classical methods like output, filter, and equation error methods apply extensively as parametric approaches. In contrast, machine learning approaches like Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), etc., are alternatives to model-based methods. This work presents a novel aerodynamic parameters estimation technique that fuses two biologically inspired optimization techniques, (i) the Artificial Bee Colony (ABC) optimization and (ii) ANN for an actual aircraft while incorporating system and measurement uncertainty. The fusion of ABC and ANN imparts the ability to address sensor noise challenges associated with system identification and parameter estimation. Comparison of the proposed method’s results with the benchmark techniques like Least Square, Filter Error, and Neural Gauss Methods using recorded flight data of the ATTAS (DLR German Aerospace Centre) and HANSA-3 (IIT Kanpur) aircrafts established its adequacy and efficacy. Furthermore, the capability of the proposed hybrid method to extract stability and control variables from the stable aircraft kinematics is shown even with insufficient information in its data history.
{"title":"Estimation of aerodynamic parameters using neural artificial bee colony fusion algorithm for moderate angle of attack using real flight data","authors":"Prashant Kumar, Sarvesh Kumar Sonkar, Riya Catherine George, Ajoy Kanti Ghosh, Deepu Philip","doi":"10.1177/09544100231201215","DOIUrl":"https://doi.org/10.1177/09544100231201215","url":null,"abstract":"Aircraft system identification aims to estimate the aerodynamic force and moment coefficients utilizing intelligent modeling and parametric identification methodologies. Classical methods like output, filter, and equation error methods apply extensively as parametric approaches. In contrast, machine learning approaches like Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), etc., are alternatives to model-based methods. This work presents a novel aerodynamic parameters estimation technique that fuses two biologically inspired optimization techniques, (i) the Artificial Bee Colony (ABC) optimization and (ii) ANN for an actual aircraft while incorporating system and measurement uncertainty. The fusion of ABC and ANN imparts the ability to address sensor noise challenges associated with system identification and parameter estimation. Comparison of the proposed method’s results with the benchmark techniques like Least Square, Filter Error, and Neural Gauss Methods using recorded flight data of the ATTAS (DLR German Aerospace Centre) and HANSA-3 (IIT Kanpur) aircrafts established its adequacy and efficacy. Furthermore, the capability of the proposed hybrid method to extract stability and control variables from the stable aircraft kinematics is shown even with insufficient information in its data history.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135059464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A detailed numerical study of shock-wave interference on a cylindrical blunt leading edge in hypersonic flow is carried out to reveal the effect of shock-shock interaction on peak heating and blunt body aerodynamics. This study is unique in that it examines the effect of interactions on rear wake formation and aerodynamic forces acting on the blunt body. Six different shock wave interference patterns described by Edney are studied for a freestream Mach number of 6.5. Compressible Reynolds-averaged Navier–Stokes equations are solved using finite volume method to obtain accurate prediction of the flowfield and aerodynamic loads. Hugoniot jump conditions are imposed in the inlet boundary to realize oblique shock of desired strength to interact with the detached shock at specific location. Numerical predictions are in good agreement with reported experimental measurements. The results obtained in this study reveals that the type of shock-shock interaction pattern can significantly alter the characteristics of the rear wake. Comparisons to undisturbed flow conditions reveal that Type II to VI interactions lead to an increase in wake size, whereas Type I interaction shows a marginal reduction. These changes in wake size are attributed to modifications in the forebody boundary layer induced by the shock-shock interactions. In the case of Type I interaction, however, the transmitted wave interacting with the rear wake is found to be responsible for the marginal reduction in wake size. This study also shows that changes to the rear wake structure caused by the change in interaction type can affect aerodynamic loads. Type VI interaction recorded a maximum drag coefficient of 2.96, whereas Type IV interaction yielded a maximum lift coefficient of 0.992. These findings demonstrate the potential for dynamically adjusting the control forces of a flying body by manipulating shock interference.
{"title":"Aerothermodynamic analysis and rear wake assessment of shock wave interference over blunt leading edge at Mach 6.5","authors":"Gaurav Shivpratap Singh, Chirag Sharma, Siddhant Swaroop Padhy, Deepu Dinesan, Bibin John","doi":"10.1177/09544100231199859","DOIUrl":"https://doi.org/10.1177/09544100231199859","url":null,"abstract":"A detailed numerical study of shock-wave interference on a cylindrical blunt leading edge in hypersonic flow is carried out to reveal the effect of shock-shock interaction on peak heating and blunt body aerodynamics. This study is unique in that it examines the effect of interactions on rear wake formation and aerodynamic forces acting on the blunt body. Six different shock wave interference patterns described by Edney are studied for a freestream Mach number of 6.5. Compressible Reynolds-averaged Navier–Stokes equations are solved using finite volume method to obtain accurate prediction of the flowfield and aerodynamic loads. Hugoniot jump conditions are imposed in the inlet boundary to realize oblique shock of desired strength to interact with the detached shock at specific location. Numerical predictions are in good agreement with reported experimental measurements. The results obtained in this study reveals that the type of shock-shock interaction pattern can significantly alter the characteristics of the rear wake. Comparisons to undisturbed flow conditions reveal that Type II to VI interactions lead to an increase in wake size, whereas Type I interaction shows a marginal reduction. These changes in wake size are attributed to modifications in the forebody boundary layer induced by the shock-shock interactions. In the case of Type I interaction, however, the transmitted wave interacting with the rear wake is found to be responsible for the marginal reduction in wake size. This study also shows that changes to the rear wake structure caused by the change in interaction type can affect aerodynamic loads. Type VI interaction recorded a maximum drag coefficient of 2.96, whereas Type IV interaction yielded a maximum lift coefficient of 0.992. These findings demonstrate the potential for dynamically adjusting the control forces of a flying body by manipulating shock interference.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135396292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2023-09-07DOI: 10.1177/09544100231193133
Vidya Sumathy, Rakesh R. Warier, Debasish Ghose
The workspace analysis of a robotic arm coupled to an unmanned aerial vehicle executing close-to-target operations is significant. The workspace of a 3 degree-of-freedom manipulator mounted to the bottom of a quadcopter and having an extended workspace is analyzed in this research, along with a motion planning algorithm. The quadcopter manipulator system comprises a robotic arm attached to the quadcopter’s center of gravity at its bottom. The manipulator has an extended workspace as its end-effector can reach three-dimensional locations above and below the drone’s airframe. The arm’s workspace is determined by system kinematics. Certain factors like downwash from the drone, the robotic arm’s singularity, servo motor stall torques, and mechanical structure limit the arm’s workspace during real-time tasks. A detailed description of these factors and their impact on the arm’s reachable workspace is also provided. Based on these limitations, the motion planning algorithm verifies the viability of a specific arm configuration and, therefore, the feasibility of the task. A concept called the near-wall effect and strategies to limit its influence on aerial robots are presented to comprehend the effect of a wall on the system in tasks involving targets on a compound wall. The proposed research outcomes are evaluated using MATLAB and ROS/Gazebo simulations.
{"title":"Effect of constraints and vertical wall interaction on workspace of a quadcopter manipulator system","authors":"Vidya Sumathy, Rakesh R. Warier, Debasish Ghose","doi":"10.1177/09544100231193133","DOIUrl":"https://doi.org/10.1177/09544100231193133","url":null,"abstract":"The workspace analysis of a robotic arm coupled to an unmanned aerial vehicle executing close-to-target operations is significant. The workspace of a 3 degree-of-freedom manipulator mounted to the bottom of a quadcopter and having an extended workspace is analyzed in this research, along with a motion planning algorithm. The quadcopter manipulator system comprises a robotic arm attached to the quadcopter’s center of gravity at its bottom. The manipulator has an extended workspace as its end-effector can reach three-dimensional locations above and below the drone’s airframe. The arm’s workspace is determined by system kinematics. Certain factors like downwash from the drone, the robotic arm’s singularity, servo motor stall torques, and mechanical structure limit the arm’s workspace during real-time tasks. A detailed description of these factors and their impact on the arm’s reachable workspace is also provided. Based on these limitations, the motion planning algorithm verifies the viability of a specific arm configuration and, therefore, the feasibility of the task. A concept called the near-wall effect and strategies to limit its influence on aerial robots are presented to comprehend the effect of a wall on the system in tasks involving targets on a compound wall. The proposed research outcomes are evaluated using MATLAB and ROS/Gazebo simulations.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"126 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77263964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2023-09-05DOI: 10.1177/09544100231199856
G. Wang, Tianlai Gu, Shuai Zhang, Jifa Zhang, Yao Zheng
The inlet, isolation section, and other internal flow components are important parts of the aircraft propulsion system. Their performances affect the stability of the entire propulsion system. According to those components, complicated shock wave/boundary layer interaction (SBLI), flow separation, and secondary flow phenomena would occur. The commonly used turbulence models, SA and SST, cannot predict the anisotropy of turbulence. This deficiency makes the calculated results differ significantly from the experimental results and cannot accurately predict their aerodynamic performance. This paper validates the feasibility and effectiveness of the turbulence models based on quadratic constitutive relation (QCR) correction applied to the flow of square duct, compression corners, diffusing 3D S-Duct, and axisymmetric cylindrical isolator. This can support future calculations of complex flow fields with flow separation and secondary flow phenomena in the subsonic or supersonic inlet. The results show that the turbulence model with QCR correction is better than the original turbulence model. Among them, the SA-QCR2020 turbulence model is the best, which is able to predict the presence of secondary flows and large boundary layer separated flows well.
{"title":"Validation and analyses of QCR correction turbulence model in sub-/super-sonic inner flows","authors":"G. Wang, Tianlai Gu, Shuai Zhang, Jifa Zhang, Yao Zheng","doi":"10.1177/09544100231199856","DOIUrl":"https://doi.org/10.1177/09544100231199856","url":null,"abstract":"The inlet, isolation section, and other internal flow components are important parts of the aircraft propulsion system. Their performances affect the stability of the entire propulsion system. According to those components, complicated shock wave/boundary layer interaction (SBLI), flow separation, and secondary flow phenomena would occur. The commonly used turbulence models, SA and SST, cannot predict the anisotropy of turbulence. This deficiency makes the calculated results differ significantly from the experimental results and cannot accurately predict their aerodynamic performance. This paper validates the feasibility and effectiveness of the turbulence models based on quadratic constitutive relation (QCR) correction applied to the flow of square duct, compression corners, diffusing 3D S-Duct, and axisymmetric cylindrical isolator. This can support future calculations of complex flow fields with flow separation and secondary flow phenomena in the subsonic or supersonic inlet. The results show that the turbulence model with QCR correction is better than the original turbulence model. Among them, the SA-QCR2020 turbulence model is the best, which is able to predict the presence of secondary flows and large boundary layer separated flows well.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"44 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86584183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2023-08-31DOI: 10.1177/09544100231199239
Libao Wang, Min Xu
In this paper, we propose a regression-based nonlinear reduced-order model for nonlinear structural dynamics problems, called the Nonlinear Identification and Dimension-Order Reduction (NLIDOR) algorithm. We evaluate the algorithm using a simple toy model, a chain of coupled oscillators and an actual three-dimensional flat plate. The results show that NLIDOR can accurately identify the natural frequencies and modes of the system and capture the nonlinear dynamical features, while the linear Dynamic Mode Decomposition (DMD) method can only capture linear features and is influenced by nonlinear terms. Compared with the full-order model (FOM), NLIDOR can effectively reduce computational cost, while compared with DMD, NLIDOR significantly improves computational accuracy. The results demonstrate the effectiveness and potential of NLIDOR for solving nonlinear dynamic problems in various applications.
{"title":"Regression-based identification and order reduction method for nonlinear dynamic structural models","authors":"Libao Wang, Min Xu","doi":"10.1177/09544100231199239","DOIUrl":"https://doi.org/10.1177/09544100231199239","url":null,"abstract":"In this paper, we propose a regression-based nonlinear reduced-order model for nonlinear structural dynamics problems, called the Nonlinear Identification and Dimension-Order Reduction (NLIDOR) algorithm. We evaluate the algorithm using a simple toy model, a chain of coupled oscillators and an actual three-dimensional flat plate. The results show that NLIDOR can accurately identify the natural frequencies and modes of the system and capture the nonlinear dynamical features, while the linear Dynamic Mode Decomposition (DMD) method can only capture linear features and is influenced by nonlinear terms. Compared with the full-order model (FOM), NLIDOR can effectively reduce computational cost, while compared with DMD, NLIDOR significantly improves computational accuracy. The results demonstrate the effectiveness and potential of NLIDOR for solving nonlinear dynamic problems in various applications.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"10 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88586539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2023-08-30DOI: 10.1177/09544100231198150
Yang Hu, Xiaoyan Wang
Characterized by the wide use of advanced automation and the introduction of new operation concepts, the future air transportation system will be more complex. Advanced pilot behavior models with improved capability are required to support the design and analysis of the midair encounter situations in the future air transportation system. This paper first filters midair encounter data from Automatic Dependent Surveillance-Broadcast (ADS-B) observations. Based on the acquired midair encounter data, a comprehensive pilot behavior model is proposed based on a multi-layer Long Short-Term Memory (LSTM) network. The model is designed for the purpose of enhancing the predicting capability of pilot behaviors in both horizontal and vertical planes. Finally, the performance of the proposed model to predict pilot behavior in both horizontal and vertical planes is studied through evaluating against realistic midair encounter situations.
{"title":"Predicting pilot behavior during midair encounters using long short-term memory network","authors":"Yang Hu, Xiaoyan Wang","doi":"10.1177/09544100231198150","DOIUrl":"https://doi.org/10.1177/09544100231198150","url":null,"abstract":"Characterized by the wide use of advanced automation and the introduction of new operation concepts, the future air transportation system will be more complex. Advanced pilot behavior models with improved capability are required to support the design and analysis of the midair encounter situations in the future air transportation system. This paper first filters midair encounter data from Automatic Dependent Surveillance-Broadcast (ADS-B) observations. Based on the acquired midair encounter data, a comprehensive pilot behavior model is proposed based on a multi-layer Long Short-Term Memory (LSTM) network. The model is designed for the purpose of enhancing the predicting capability of pilot behaviors in both horizontal and vertical planes. Finally, the performance of the proposed model to predict pilot behavior in both horizontal and vertical planes is studied through evaluating against realistic midair encounter situations.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"42 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75088736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2023-08-29DOI: 10.1177/09544100231198160
S. Pourtakdoust, Amir H. Khodabakhsh
Most Aeronautical and Astronautical Systems (AAS) are inherently complex, multidisciplinary, nonlinear, and computationally intensive for design and analysis. Utilizing the Reliability-Based Multidisciplinary Design Optimization framework can address the multidisciplinary nature of these systems while accounting for inherent uncertainties. In this paper, an efficient methodology for Reliability-Based Multidisciplinary Design optimization of an aerial vehicle is developed. The computational burden of reliability assessment could make its integration within a Multidisciplinary Design Optimization cycle a formidable task. In this respect, a multilevel Multidisciplinary Design Optimization architecture is proposed in which the computational cost is reduced by considering the reliability analysis, as needed only for critical subsystems. To this end, a single-level Reliability-Based Multidisciplinary Design Optimization is derived using the Performance Measure Analysis and the Karush-Kuhn-Tucker condition. The work demonstrates the integration of this formulation into the proposed multilevel Reliability-Based Multidisciplinary Design Optimization architecture. The proposed design architecture is implemented for an aeroelastic Unpowered Guided Aerial Vehicle whose outcomes are compared with previous results obtained via a mono-level Uncertainty-Based Multidisciplinary Design Optimization architecture.
{"title":"Reliability-based multidisciplinary design optimization of an aeroelastic unpowered guided aerial vehicle","authors":"S. Pourtakdoust, Amir H. Khodabakhsh","doi":"10.1177/09544100231198160","DOIUrl":"https://doi.org/10.1177/09544100231198160","url":null,"abstract":"Most Aeronautical and Astronautical Systems (AAS) are inherently complex, multidisciplinary, nonlinear, and computationally intensive for design and analysis. Utilizing the Reliability-Based Multidisciplinary Design Optimization framework can address the multidisciplinary nature of these systems while accounting for inherent uncertainties. In this paper, an efficient methodology for Reliability-Based Multidisciplinary Design optimization of an aerial vehicle is developed. The computational burden of reliability assessment could make its integration within a Multidisciplinary Design Optimization cycle a formidable task. In this respect, a multilevel Multidisciplinary Design Optimization architecture is proposed in which the computational cost is reduced by considering the reliability analysis, as needed only for critical subsystems. To this end, a single-level Reliability-Based Multidisciplinary Design Optimization is derived using the Performance Measure Analysis and the Karush-Kuhn-Tucker condition. The work demonstrates the integration of this formulation into the proposed multilevel Reliability-Based Multidisciplinary Design Optimization architecture. The proposed design architecture is implemented for an aeroelastic Unpowered Guided Aerial Vehicle whose outcomes are compared with previous results obtained via a mono-level Uncertainty-Based Multidisciplinary Design Optimization architecture.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"37 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91210134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2023-08-27DOI: 10.1177/09544100231198152
Yaqiang Wei, X. Yang, Xinlin Bai, Zhigang Xu
Ground test for space berthing and docking mechanism plays crucial roles in their stable operation in orbit. In this paper, a hardware-in-the-loop based ground test system is presented for economic reliability test for space berthing and docking mechanism of small spacecraft. In the system, the support and adapter unit is employed to fix the active part of the berthing and docking mechanism, and the end-effector of the manipulator connects the passive part. The manipulator is driven according to the relative motion calculated by the hardware-in-the-loop model after gravity compensation, to simulate motion of space berthing and docking mechanism in space. A Smith predictor is introduced for control system delays compensation. A berthing and docking mechanism was employed in the experiment to evaluate the performance of the test system. The results validated the effectiveness of the test system. Since only one manipulator is exploited in the test system, compared with existing systems using two manipulators, the system cost can be greatly decreased.
{"title":"Hardware-in-the-loop based ground test system for space berthing and docking mechanism of small spacecraft","authors":"Yaqiang Wei, X. Yang, Xinlin Bai, Zhigang Xu","doi":"10.1177/09544100231198152","DOIUrl":"https://doi.org/10.1177/09544100231198152","url":null,"abstract":"Ground test for space berthing and docking mechanism plays crucial roles in their stable operation in orbit. In this paper, a hardware-in-the-loop based ground test system is presented for economic reliability test for space berthing and docking mechanism of small spacecraft. In the system, the support and adapter unit is employed to fix the active part of the berthing and docking mechanism, and the end-effector of the manipulator connects the passive part. The manipulator is driven according to the relative motion calculated by the hardware-in-the-loop model after gravity compensation, to simulate motion of space berthing and docking mechanism in space. A Smith predictor is introduced for control system delays compensation. A berthing and docking mechanism was employed in the experiment to evaluate the performance of the test system. The results validated the effectiveness of the test system. Since only one manipulator is exploited in the test system, compared with existing systems using two manipulators, the system cost can be greatly decreased.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"8 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83551077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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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