Lorenzo Casalino, Andrea Ferrero, Lorenzo Folcarelli, F. Masseni, Luca Muscará, Dario Pastrone, Maria Luisa Frezzotti, A. Cretella, Rocco Carmine Pellegrini, Enrico Cavallini
{"title":"Multiphysics Modeling for Combustion Instability in Paraffin-Fueled Hybrid Rocket Engines","authors":"Lorenzo Casalino, Andrea Ferrero, Lorenzo Folcarelli, F. Masseni, Luca Muscará, Dario Pastrone, Maria Luisa Frezzotti, A. Cretella, Rocco Carmine Pellegrini, Enrico Cavallini","doi":"10.2514/1.a35758","DOIUrl":"https://doi.org/10.2514/1.a35758","url":null,"abstract":"The use of paraffin-based fuels is a promising approach to a low regression rate in hybrid rocket engines, and the capability to describe and predict combustion instability in the presence of liquefying fuels becomes an enabling step towards the application of hybrid rockets in a wide range of space transportation systems. In this work, a multiphysics model having this purpose is presented and discussed. The model is based on a network of submodels in which chamber gas dynamics is described by a quasi-1D Euler model for reacting flows while thermal diffusion in the grain is described by the 1D heat equation in the radial direction. An artificial neural network is introduced to reduce the computational cost required by the chemical submodel. A sensitivity analysis is performed to identify the key parameters, which have the largest influence on combustion instability and to evaluate the predictive capability of the model despite the uncertainty introduced with the necessary modeling simplifications. Results are presented considering two test cases with different oxidizers: hydrogen peroxide and gaseous oxygen. The procedure shows good agreement with the experimental results available in the literature.","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"75 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139840414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lorenzo Casalino, Andrea Ferrero, Lorenzo Folcarelli, F. Masseni, Luca Muscará, Dario Pastrone, Maria Luisa Frezzotti, A. Cretella, Rocco Carmine Pellegrini, Enrico Cavallini
{"title":"Multiphysics Modeling for Combustion Instability in Paraffin-Fueled Hybrid Rocket Engines","authors":"Lorenzo Casalino, Andrea Ferrero, Lorenzo Folcarelli, F. Masseni, Luca Muscará, Dario Pastrone, Maria Luisa Frezzotti, A. Cretella, Rocco Carmine Pellegrini, Enrico Cavallini","doi":"10.2514/1.a35758","DOIUrl":"https://doi.org/10.2514/1.a35758","url":null,"abstract":"The use of paraffin-based fuels is a promising approach to a low regression rate in hybrid rocket engines, and the capability to describe and predict combustion instability in the presence of liquefying fuels becomes an enabling step towards the application of hybrid rockets in a wide range of space transportation systems. In this work, a multiphysics model having this purpose is presented and discussed. The model is based on a network of submodels in which chamber gas dynamics is described by a quasi-1D Euler model for reacting flows while thermal diffusion in the grain is described by the 1D heat equation in the radial direction. An artificial neural network is introduced to reduce the computational cost required by the chemical submodel. A sensitivity analysis is performed to identify the key parameters, which have the largest influence on combustion instability and to evaluate the predictive capability of the model despite the uncertainty introduced with the necessary modeling simplifications. Results are presented considering two test cases with different oxidizers: hydrogen peroxide and gaseous oxygen. The procedure shows good agreement with the experimental results available in the literature.","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"69 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Postflight Assessment of Mars 2020 Entry, Descent, and Landing Simulation","authors":"S. Dutta, D. Way, C. Zumwalt, David Blette","doi":"10.2514/1.a35771","DOIUrl":"https://doi.org/10.2514/1.a35771","url":null,"abstract":"On 18 February 2021, the Mars 2020 Perseverance rover and Ingenuity helicopter successfully landed inside Jezero Crater. At 1026 kg, Perseverance is the largest, most sophisticated rover ever delivered to another planet. This event marked the ninth successful landing and fifth rover to be delivered at Mars. The Program to Optimize Simulated Trajectories II, a trajectory simulation tool, was the prime entry, descent, and landing performance simulation for Mars 2020. This paper presents comparisons between the flight telemetry and the simulation predictions. In general, approximately 90% of the as-flown values were within [Formula: see text] (standard deviations) of the preflight simulation predictions, and the anomalies are discussed in the paper. These comparisons are important in order to understand how each of the individual models and the integrated simulation as a whole performed. This information is fed forward to future missions, which benefit from knowing where additional resources or studies are needed and where uncertainties may be reduced to enable improved performance.","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"407 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139841550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Postflight Assessment of Mars 2020 Entry, Descent, and Landing Simulation","authors":"S. Dutta, D. Way, C. Zumwalt, David Blette","doi":"10.2514/1.a35771","DOIUrl":"https://doi.org/10.2514/1.a35771","url":null,"abstract":"On 18 February 2021, the Mars 2020 Perseverance rover and Ingenuity helicopter successfully landed inside Jezero Crater. At 1026 kg, Perseverance is the largest, most sophisticated rover ever delivered to another planet. This event marked the ninth successful landing and fifth rover to be delivered at Mars. The Program to Optimize Simulated Trajectories II, a trajectory simulation tool, was the prime entry, descent, and landing performance simulation for Mars 2020. This paper presents comparisons between the flight telemetry and the simulation predictions. In general, approximately 90% of the as-flown values were within [Formula: see text] (standard deviations) of the preflight simulation predictions, and the anomalies are discussed in the paper. These comparisons are important in order to understand how each of the individual models and the integrated simulation as a whole performed. This information is fed forward to future missions, which benefit from knowing where additional resources or studies are needed and where uncertainties may be reduced to enable improved performance.","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"52 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139781495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correction: Stagnation-Point Aeroheating Correlations for Mars Entry","authors":"Thomas K. West, A. Brandis","doi":"10.2514/1.a34602.c1","DOIUrl":"https://doi.org/10.2514/1.a34602.c1","url":null,"abstract":"","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"12 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139808535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joshua Aurand, Steven C. Cutlip, Henry Lei, Kendra A. Lang, Sean Phillips
{"title":"Deep Q-Learning for Decentralized Multi-Agent Inspection of a Tumbling Target","authors":"Joshua Aurand, Steven C. Cutlip, Henry Lei, Kendra A. Lang, Sean Phillips","doi":"10.2514/1.a35749","DOIUrl":"https://doi.org/10.2514/1.a35749","url":null,"abstract":"As the number of on-orbit satellites increases, the ability to repair or de-orbit them is becoming increasingly important. The implicitly required task of on-orbit inspection is challenging due to coordination of multiple observer satellites, a highly nonlinear environment, a potentially unknown or unpredictable target, and time delays associated with ground-based control. There is a critical need for autonomous, robust, decentralized solutions. To achieve this, we consider a hierarchical, learned approach for the decentralized planning of multi-agent inspection of a tumbling target. Our solution consists of two components: a viewpoint or high-level planner trained using deep reinforcement learning, and a low-level planner that will handle the point-to-point maneuvering of the spacecraft. Operating under limited information, our trained multi-agent high-level policies successfully contextualize information within the global hierarchical environment and are correspondingly able to inspect over 90% of nonconvex tumbling targets, even in the absence of additional agent attitude control.","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"22 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139868021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Payload Optimization for EnVision Mission Using an Electric Propulsion Module for Interplanetary Transfers","authors":"Sebastian Valencia","doi":"10.2514/1.a35923","DOIUrl":"https://doi.org/10.2514/1.a35923","url":null,"abstract":"This paper presents a study on the feasibility of using electric propulsion (EP) for interplanetary transfer in the context of an Earth–Venus mission. Extensive research has been conducted on EP modules for Mars missions, demonstrating their potential for faster mission times and greater flexibility compared to all-chemical propulsion (CP) systems. However, there is a notable gap in our understanding regarding EP systems for Venus missions, despite the unique and challenging environment that Venus presents. This study aims to bridge that gap by evaluating the performance of an EP module compared to a conventional all-CP spacecraft, which serves as the backup mission for the EnVision mission by the European Space Agency. The objectives of the study include identifying key drivers for the EP module’s preliminary design, analyzing tradeoffs and challenges associated with EP systems, and evaluating the feasibility of achieving payload mass delivery. The results reveal that the all-EP spacecraft delivers a higher payload mass compared to the all-CP EnVision mission, highlighting the superiority of EP over CP for interplanetary missions. This research provides valuable insights into the potential advantages of EP systems for future interplanetary missions and emphasizes the necessary design considerations when utilizing EP technology.","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"35 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139808130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Payload Optimization for EnVision Mission Using an Electric Propulsion Module for Interplanetary Transfers","authors":"Sebastian Valencia","doi":"10.2514/1.a35923","DOIUrl":"https://doi.org/10.2514/1.a35923","url":null,"abstract":"This paper presents a study on the feasibility of using electric propulsion (EP) for interplanetary transfer in the context of an Earth–Venus mission. Extensive research has been conducted on EP modules for Mars missions, demonstrating their potential for faster mission times and greater flexibility compared to all-chemical propulsion (CP) systems. However, there is a notable gap in our understanding regarding EP systems for Venus missions, despite the unique and challenging environment that Venus presents. This study aims to bridge that gap by evaluating the performance of an EP module compared to a conventional all-CP spacecraft, which serves as the backup mission for the EnVision mission by the European Space Agency. The objectives of the study include identifying key drivers for the EP module’s preliminary design, analyzing tradeoffs and challenges associated with EP systems, and evaluating the feasibility of achieving payload mass delivery. The results reveal that the all-EP spacecraft delivers a higher payload mass compared to the all-CP EnVision mission, highlighting the superiority of EP over CP for interplanetary missions. This research provides valuable insights into the potential advantages of EP systems for future interplanetary missions and emphasizes the necessary design considerations when utilizing EP technology.","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"13 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139867928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joshua Aurand, Steven C. Cutlip, Henry Lei, Kendra A. Lang, Sean Phillips
{"title":"Deep Q-Learning for Decentralized Multi-Agent Inspection of a Tumbling Target","authors":"Joshua Aurand, Steven C. Cutlip, Henry Lei, Kendra A. Lang, Sean Phillips","doi":"10.2514/1.a35749","DOIUrl":"https://doi.org/10.2514/1.a35749","url":null,"abstract":"As the number of on-orbit satellites increases, the ability to repair or de-orbit them is becoming increasingly important. The implicitly required task of on-orbit inspection is challenging due to coordination of multiple observer satellites, a highly nonlinear environment, a potentially unknown or unpredictable target, and time delays associated with ground-based control. There is a critical need for autonomous, robust, decentralized solutions. To achieve this, we consider a hierarchical, learned approach for the decentralized planning of multi-agent inspection of a tumbling target. Our solution consists of two components: a viewpoint or high-level planner trained using deep reinforcement learning, and a low-level planner that will handle the point-to-point maneuvering of the spacecraft. Operating under limited information, our trained multi-agent high-level policies successfully contextualize information within the global hierarchical environment and are correspondingly able to inspect over 90% of nonconvex tumbling targets, even in the absence of additional agent attitude control.","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"101 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139808244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correction: Stagnation-Point Aeroheating Correlations for Mars Entry","authors":"Thomas K. West, A. Brandis","doi":"10.2514/1.a34602.c1","DOIUrl":"https://doi.org/10.2514/1.a34602.c1","url":null,"abstract":"","PeriodicalId":508266,"journal":{"name":"Journal of Spacecraft and Rockets","volume":"47 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139868706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}