EM
E. Mooij
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1
Rocket reusability is a key factor in enabling quicker and more cost-effective access to space. However, landing on Earth poses significant challenges due to the dynamic and highly uncertain environment. A robust guidance, navigation, and control system is essential to guide the vehicle to the landing site while fulfilling terminal constraints and minimizing fuel consumption. This research integrates meta-reinforcement learning with Gated Transformer XL neural networks to enhance the robustness of the powered guidance with respect to atmospheric and aerodynamic uncertainties, navigation and control errors, and dispersed initial conditions. By employing a 6-degree-of-freedom dynamics model and accurate vehicle and environmental simulations, the agent learns a higher-fidelity guidance policy compared to existing literature, demonstrating successful and robust performance in perturbed Monte Carlo campaigns. While all other terminal constraints are met using only the RL policy, a terminal patch can be included to reduce the violation of the vertical velocity constraint, achieving up to 99.7% of the simulations compliant with all terminal landing requirements.
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Rocket reusability is a key factor in enabling quicker and more cost-effective access to space. However, landing on Earth poses significant challenges due to the dynamic and highly uncertain environment. A robust guidance, navigation, and control system is essential to guide the vehicle to the landing site while fulfilling terminal constraints and minimizing fuel consumption. This research integrates meta-reinforcement learning with Gated Transformer XL neural networks to enhance the robustness of the powered guidance with respect to atmospheric and aerodynamic uncertainties, navigation and control errors, and dispersed initial conditions. By employing a 6-degree-of-freedom dynamics model and accurate vehicle and environmental simulations, the agent learns a higher-fidelity guidance policy compared to existing literature, demonstrating successful and robust performance in perturbed Monte Carlo campaigns. While all other terminal constraints are met using only the RL policy, a terminal patch can be included to reduce the violation of the vertical velocity constraint, achieving up to 99.7% of the simulations compliant with all terminal landing requirements.
This paper investigates the efficacy of Convolutional Neural Network (CNN) based methods to navigate autonomously around asteroids. The main contribution of this work is the successful development of a first-of-a-kind pose estimation pipeline, consisting of a CNN-based feature detector and a Perspective-n-Points (PnP) solver to allow accurate, safe, and autonomous distance estimation with respect to a target asteroid. A top-down CNN-based feature detector is developed, consisting of an object and keypoint detection network in sequence, which detects n pre-defined keypoints, designated on the target's 3D model, within the 2D image. The simulated target asteroid is Bennu, a subkilometer asteroid with a spinning top-shape and pronounced equatorial bulge. The networks have been trained and evaluated on synthetic datasets created in this work, consisting of 32,352 images with a variety of poses from 4.5 to 9 km from the asteroid, for different illumination conditions, asteroid orientations, and image corruptions that emulate real sensor artifacts. The pipeline could achieve a mean and median line-of-sight distance estimate of around 42 m and 30 m, respectively, at a confidence level of 90% for the large relative range, while satisfying the accuracy requirement of a maximum of 10% knowledge error for 99.979% of the cases.
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This paper investigates the efficacy of Convolutional Neural Network (CNN) based methods to navigate autonomously around asteroids. The main contribution of this work is the successful development of a first-of-a-kind pose estimation pipeline, consisting of a CNN-based feature detector and a Perspective-n-Points (PnP) solver to allow accurate, safe, and autonomous distance estimation with respect to a target asteroid. A top-down CNN-based feature detector is developed, consisting of an object and keypoint detection network in sequence, which detects n pre-defined keypoints, designated on the target's 3D model, within the 2D image. The simulated target asteroid is Bennu, a subkilometer asteroid with a spinning top-shape and pronounced equatorial bulge. The networks have been trained and evaluated on synthetic datasets created in this work, consisting of 32,352 images with a variety of poses from 4.5 to 9 km from the asteroid, for different illumination conditions, asteroid orientations, and image corruptions that emulate real sensor artifacts. The pipeline could achieve a mean and median line-of-sight distance estimate of around 42 m and 30 m, respectively, at a confidence level of 90% for the large relative range, while satisfying the accuracy requirement of a maximum of 10% knowledge error for 99.979% of the cases.
Ensuring the sustainability of future space missions requires addressing the space-debris issue proactively. Space debris threatens future space missions, making the need for collision avoidance manoeuvres essential. This research explores robust methods to perform such manoeuvres, focusing on guidance and control systems, using the Starlink constellation as a reference. A robust guidance system integrating convex optimisation enables autonomous, fuel-efficient collision avoidance of space debris. Testing across diverse conditions shows suitability for various satellite characteristics. Attitude-control requirements are analysed with a linear quadratic regulator controller. Low-thrust manoeuvres with constant capabilities are optimal for this specific mission, minimising fuel usage and achieving desired miss distances. The outcomes of this research represent a significant advancement in space-debris mitigation and contribute to enhancing space sustainability.
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Ensuring the sustainability of future space missions requires addressing the space-debris issue proactively. Space debris threatens future space missions, making the need for collision avoidance manoeuvres essential. This research explores robust methods to perform such manoeuvres, focusing on guidance and control systems, using the Starlink constellation as a reference. A robust guidance system integrating convex optimisation enables autonomous, fuel-efficient collision avoidance of space debris. Testing across diverse conditions shows suitability for various satellite characteristics. Attitude-control requirements are analysed with a linear quadratic regulator controller. Low-thrust manoeuvres with constant capabilities are optimal for this specific mission, minimising fuel usage and achieving desired miss distances. The outcomes of this research represent a significant advancement in space-debris mitigation and contribute to enhancing space sustainability.
Rocket reusability is a key factor in enabling quicker and more cost-effective access to space. However, landing on Earth poses significant challenges due to the dynamic and highly uncertain environment. A robust Guidance, Navigation, and Control system is essential to guide the vehicle to the landing site while meeting terminal constraints and minimizing fuel consumption. This research integrates Meta-Reinforcement Learning with Gated Transformer XL Neural Networks to enhance the robustness of the powered guidance with respect to atmospheric and aerodynamic uncertainties, navigation and control errors, and dispersed initial conditions. By employing a 6-Degrees-of-Freedom dynamics model and accurate vehicle and environmental simulations, the agent learns a higher fidelity guidance policy compared to existing literature, demonstrating successful and robust performance in Monte Carlo simulations. In this complex scenario, the innovative attention-based neural networks also outperform recurrent neural networks, widely used for Reinforcement Learning-based space guidance applications.
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Rocket reusability is a key factor in enabling quicker and more cost-effective access to space. However, landing on Earth poses significant challenges due to the dynamic and highly uncertain environment. A robust Guidance, Navigation, and Control system is essential to guide the vehicle to the landing site while meeting terminal constraints and minimizing fuel consumption. This research integrates Meta-Reinforcement Learning with Gated Transformer XL Neural Networks to enhance the robustness of the powered guidance with respect to atmospheric and aerodynamic uncertainties, navigation and control errors, and dispersed initial conditions. By employing a 6-Degrees-of-Freedom dynamics model and accurate vehicle and environmental simulations, the agent learns a higher fidelity guidance policy compared to existing literature, demonstrating successful and robust performance in Monte Carlo simulations. In this complex scenario, the innovative attention-based neural networks also outperform recurrent neural networks, widely used for Reinforcement Learning-based space guidance applications.
Active debris removal missions are of paramount importance to mitigate the space debris problem around Earth. However, due to the complexity of such a debris removal mission, the first one is still to be launched. In particular, one critical technology enabler is presented by the guidance, navigation and control (GNC) system, as it is required to autonomously navigate around an uncontrolled and tumbling debris item. Therefore, the current paper is aimed at providing an integrated GNC system design to execute the final rendezvous with an uncooperative and passive debris object in low-Earth orbit (LEO). Specifically, it is focused on executing the most complex phase of an active debris removal mission, given in terms of its close-range rendezvous operations. The innovation of this paper lies in providing an end-to-end GNC system design, containing state of the art algorithms for the guidance, navigation, and control functions, along with the selection of appropriate navigation sensors and control actuators. Moreover, the proposed GNC system design showcases its autonomy and robustness by handing a wide variety of mission scenarios, while maintaining a terminal position accuracy at centimeter level and a limited propellant consumption. Furthermore, it is concluded that, as the developed GNC system design does not contain any intrinsic properties of its target, it can be employed during any generic active debris removal mission in LEO.
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Active debris removal missions are of paramount importance to mitigate the space debris problem around Earth. However, due to the complexity of such a debris removal mission, the first one is still to be launched. In particular, one critical technology enabler is presented by the guidance, navigation and control (GNC) system, as it is required to autonomously navigate around an uncontrolled and tumbling debris item. Therefore, the current paper is aimed at providing an integrated GNC system design to execute the final rendezvous with an uncooperative and passive debris object in low-Earth orbit (LEO). Specifically, it is focused on executing the most complex phase of an active debris removal mission, given in terms of its close-range rendezvous operations. The innovation of this paper lies in providing an end-to-end GNC system design, containing state of the art algorithms for the guidance, navigation, and control functions, along with the selection of appropriate navigation sensors and control actuators. Moreover, the proposed GNC system design showcases its autonomy and robustness by handing a wide variety of mission scenarios, while maintaining a terminal position accuracy at centimeter level and a limited propellant consumption. Furthermore, it is concluded that, as the developed GNC system design does not contain any intrinsic properties of its target, it can be employed during any generic active debris removal mission in LEO.
Aerocapture leverages atmospheric drag to convert a spacecraft’s hyperbolic trajectory into a bound orbit. For some aerocapture missions, heating due to the radiation of high-temperature gases in the shock layer can be much larger than the heat due to convection. This paper provides analytical proof and numerical validation that radiative heat load is minimized by the same trajectory that minimizes the final ΔV: a single switch bang-bang trajectory, starting with lift-up. The proof is general and is valid for several formulations of radiative heat flux; further, the same proof can be used to conclude that convective heat load, computed according to many of the available formulations, is instead maximized by that trajectory. Further, a novel guidance that plans a bang-bang trajectory with constraints in the attitude kinematics is introduced. While achieving performance similar to that of the current state-of-the-art, the inclusion of constraints in attitude kinematics allows for much less tuning. Finally, a lateral guidance that makes use of information on the final inclination of the predicted trajectory is introduced. Such guidance allows for very high accuracy in the inclination requirements with only two reversals by requiring a single parameter to be tuned.
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Aerocapture leverages atmospheric drag to convert a spacecraft’s hyperbolic trajectory into a bound orbit. For some aerocapture missions, heating due to the radiation of high-temperature gases in the shock layer can be much larger than the heat due to convection. This paper provides analytical proof and numerical validation that radiative heat load is minimized by the same trajectory that minimizes the final ΔV: a single switch bang-bang trajectory, starting with lift-up. The proof is general and is valid for several formulations of radiative heat flux; further, the same proof can be used to conclude that convective heat load, computed according to many of the available formulations, is instead maximized by that trajectory. Further, a novel guidance that plans a bang-bang trajectory with constraints in the attitude kinematics is introduced. While achieving performance similar to that of the current state-of-the-art, the inclusion of constraints in attitude kinematics allows for much less tuning. Finally, a lateral guidance that makes use of information on the final inclination of the predicted trajectory is introduced. Such guidance allows for very high accuracy in the inclination requirements with only two reversals by requiring a single parameter to be tuned.
This book explains and describes re-entry systems for both the Earth and other planets. It provides sufficient information for readers to perform entry mission analysis for different bodies in the Solar System. Not only does it discuss re-entry flight mechanics, but also addresses relevant subsystems and fields, enabling readers to put the information into perspective. The book begins with a complete description of planetary environments, including atmosphere, gravity fields and the shape of the primary body. After a detailed discussion of planar flight mechanics, it then moves on to discuss guidance, navigation, and control, entry, descent, and landing systems, as well as thermal protection systems. It uses examples throughout the text, enabling the theory to be linked to practical applications. Ideal for those wanting an updated, thorough discussion of re-entry systems, this book is suitable for students and researchers.
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This book explains and describes re-entry systems for both the Earth and other planets. It provides sufficient information for readers to perform entry mission analysis for different bodies in the Solar System. Not only does it discuss re-entry flight mechanics, but also addresses relevant subsystems and fields, enabling readers to put the information into perspective. The book begins with a complete description of planetary environments, including atmosphere, gravity fields and the shape of the primary body. After a detailed discussion of planar flight mechanics, it then moves on to discuss guidance, navigation, and control, entry, descent, and landing systems, as well as thermal protection systems. It uses examples throughout the text, enabling the theory to be linked to practical applications. Ideal for those wanting an updated, thorough discussion of re-entry systems, this book is suitable for students and researchers.
Within the last decade, the use of launch vehicles has increased as private companies have emerged in the space exploration industry. Compared to the early 1980s, the market for launch vehicles has become significantly more competitive, introducing the desire to have fully reusable launch vehicles. The true benefits of fully reusable launch vehicles can only be achieved once both stages are fully operational and recoverable. This stimulates the need for a comprehensive mission design. In this paper, this is achieved by revisiting the mission profiles of flyback boosters. An extensive analysis of the design-space is performed to identify the contributions of each decision variable to the trajectory design. The results concluded that such an approach supports achieving a more efficient optimization, with better convergence speed and solution performance.
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Within the last decade, the use of launch vehicles has increased as private companies have emerged in the space exploration industry. Compared to the early 1980s, the market for launch vehicles has become significantly more competitive, introducing the desire to have fully reusable launch vehicles. The true benefits of fully reusable launch vehicles can only be achieved once both stages are fully operational and recoverable. This stimulates the need for a comprehensive mission design. In this paper, this is achieved by revisiting the mission profiles of flyback boosters. An extensive analysis of the design-space is performed to identify the contributions of each decision variable to the trajectory design. The results concluded that such an approach supports achieving a more efficient optimization, with better convergence speed and solution performance.
This paper investigates the performance of an autonomous navigation system to navigate a spacecraft in the proximity of a binary asteroid system using optical and laser ranging measurements. The knowledge about the binary asteroid is limited to its orbital parameters and ellipsoid shape models. The accelerometer bias random walk is included in the estimation process. Over a four-hour landing maneuver starting from 6770 m altitude and ending at 550 m, the mean position estimation uncertainty is 41.6 m (3). It is shown that the navigation accuracy is sensitive to the Sun phase angle, the irregularity of the asteroid shape, and the goodness of fit of the ellipsoid shape model. The paper demonstrates that the navigation system is robust to large errors in the initialization of the extended Kalman filter state. The impact of image distortion and two types of image noise on the navigation performance are investigated.
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This paper investigates the performance of an autonomous navigation system to navigate a spacecraft in the proximity of a binary asteroid system using optical and laser ranging measurements. The knowledge about the binary asteroid is limited to its orbital parameters and ellipsoid shape models. The accelerometer bias random walk is included in the estimation process. Over a four-hour landing maneuver starting from 6770 m altitude and ending at 550 m, the mean position estimation uncertainty is 41.6 m (3). It is shown that the navigation accuracy is sensitive to the Sun phase angle, the irregularity of the asteroid shape, and the goodness of fit of the ellipsoid shape model. The paper demonstrates that the navigation system is robust to large errors in the initialization of the extended Kalman filter state. The impact of image distortion and two types of image noise on the navigation performance are investigated.
With the increasing interest in the Solar System's smaller bodies, quite a few missions have been sent to comets and asteroids, and more will be send in the near future. Due to the large distances involved, communication to command mission parameters takes a long time, which has a negative impact on operational safety. Autonomous navigation would be one of the key technologies that can make the mission more robust, safe, and cost effective. This is especially true if one considers the unknown fight environment when the spacecraft is first encountering the body. Most asteroids and comets have a very irregular shape and unknown mass distribution. Therefore, knowledge about its irregular gravity field will be directly beneficial as input to orbital corrections and manoeuvre planning. This paper addresses the estimation process of gravity-field parameters that could potentially be implemented in an autonomous navigation system. The focus is on a spherical-harmonic modelling of asteroid Eros-433, most notably outside the Brillouin sphere where the validity of the model is guaranteed. By using Kalman filtering it is shown that all degree and order coefficients up to degree 8 can be estimated with an error below 10%. This is the first step towards an autonomous navigation system that can operate in a highly-perturbed environment close to the asteroid.
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With the increasing interest in the Solar System's smaller bodies, quite a few missions have been sent to comets and asteroids, and more will be send in the near future. Due to the large distances involved, communication to command mission parameters takes a long time, which has a negative impact on operational safety. Autonomous navigation would be one of the key technologies that can make the mission more robust, safe, and cost effective. This is especially true if one considers the unknown fight environment when the spacecraft is first encountering the body. Most asteroids and comets have a very irregular shape and unknown mass distribution. Therefore, knowledge about its irregular gravity field will be directly beneficial as input to orbital corrections and manoeuvre planning. This paper addresses the estimation process of gravity-field parameters that could potentially be implemented in an autonomous navigation system. The focus is on a spherical-harmonic modelling of asteroid Eros-433, most notably outside the Brillouin sphere where the validity of the model is guaranteed. By using Kalman filtering it is shown that all degree and order coefficients up to degree 8 can be estimated with an error below 10%. This is the first step towards an autonomous navigation system that can operate in a highly-perturbed environment close to the asteroid.
This research performs a surrogate-assisted shape optimisation of hypersonic waveriders, where the trajectories of each shape are optimised with a multi-objective evolutionary algorithm for heat-load and cross-range. A study on the best evolutionary algorithm, node control strategy for angle of attack and bank angle profiles, and population size to use in the trajectory optimisation phase, are identified. The aerodynamics of the waveriders is computed with a new local surface inclination method blending the modified Newtonian and tangent wedge solutions, while the convective heat flux is computed for the leading edges using the Newton-Kays engineering model. Shape variability is introduced according to the layout of central composite designs, and analysis of variance is applied to identify the shape features driving the two objectives. Shock angle, leading edge radius and overall vehicle dimensions are the strongest drivers, while details on the planform shape are less relevant and should be left for posterior studies. The surrogates are a good approximation of the true fitness functions, so they were optimised in a single-objective framework, producing two optimal waverider designs.
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This research performs a surrogate-assisted shape optimisation of hypersonic waveriders, where the trajectories of each shape are optimised with a multi-objective evolutionary algorithm for heat-load and cross-range. A study on the best evolutionary algorithm, node control strategy for angle of attack and bank angle profiles, and population size to use in the trajectory optimisation phase, are identified. The aerodynamics of the waveriders is computed with a new local surface inclination method blending the modified Newtonian and tangent wedge solutions, while the convective heat flux is computed for the leading edges using the Newton-Kays engineering model. Shape variability is introduced according to the layout of central composite designs, and analysis of variance is applied to identify the shape features driving the two objectives. Shock angle, leading edge radius and overall vehicle dimensions are the strongest drivers, while details on the planform shape are less relevant and should be left for posterior studies. The surrogates are a good approximation of the true fitness functions, so they were optimised in a single-objective framework, producing two optimal waverider designs.
Attitude control of conventional launchers is relatively easy and straightforward and gives an adequate performance when applied to the nominal vehicle and mission. However, in the presence of environmental disturbances and vehicle design uncertainties, more robust types of controllers are required to guarantee stable attitudes. This chapter discusses the application of Simple Adaptive Control for the pitch control of a conventional flexible launcher. Because of the large number of design parameters, an optimisation procedure based on an evolutionary algorithm has been applied. With a floating-point representation for the design parameters, stochastic universal sampling selection, arithmetic crossover and non-uniform mutation, the performance of the controller is analysed, and it is identified how the developed methodology can streamline the (conceptual) design phase. Application of Pareto ranking enabled the simultaneous minimisation of the state deviation and the control effort, while the oscillation of the control has been used as an optimisation criterion. A conclusive simulation shows the controller performance for the flexible launch system.
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Attitude control of conventional launchers is relatively easy and straightforward and gives an adequate performance when applied to the nominal vehicle and mission. However, in the presence of environmental disturbances and vehicle design uncertainties, more robust types of controllers are required to guarantee stable attitudes. This chapter discusses the application of Simple Adaptive Control for the pitch control of a conventional flexible launcher. Because of the large number of design parameters, an optimisation procedure based on an evolutionary algorithm has been applied. With a floating-point representation for the design parameters, stochastic universal sampling selection, arithmetic crossover and non-uniform mutation, the performance of the controller is analysed, and it is identified how the developed methodology can streamline the (conceptual) design phase. Application of Pareto ranking enabled the simultaneous minimisation of the state deviation and the control effort, while the oscillation of the control has been used as an optimisation criterion. A conclusive simulation shows the controller performance for the flexible launch system.
This paper focuses on the attitude control and propellant slosh suppression of aeroelastic launch vehicles in a turbulent atmosphere. For a ve-degree pitch-angle block command, the tracking performance of the selected Incremental Non-Linear Dynamic Inversion Sliding Mode Controller (INDI-SMC) shows excellent tracking performance. However, turbulence still inevitably leads to oscillatory behaviour in the swivel command. Various lter designs have been implemented to improve the smoothness of INDI-SMC. Using either a notch or band-pass lter in the sensor-feedback loops of pitch angle and pitch rate only marginally reduced the swivel oscillations, but did not solve the problem for the rigid-body control. For the exible launcher with slosh dynamics, ltering of the sensor-feedback signals reduced the oscillations in swivel command, and elastic and slosh motion signi cantly, but could not completely remove them. The preliminary design of a rigid-body state observer has been included, and the results show that the INDI-SMC controller remains stable in the presence of engine dynamics, sloshing, exible modes, input errors due to the use of rigid-body and slosh-state observers, while ying in a turbulent wind field.
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This paper focuses on the attitude control and propellant slosh suppression of aeroelastic launch vehicles in a turbulent atmosphere. For a ve-degree pitch-angle block command, the tracking performance of the selected Incremental Non-Linear Dynamic Inversion Sliding Mode Controller (INDI-SMC) shows excellent tracking performance. However, turbulence still inevitably leads to oscillatory behaviour in the swivel command. Various lter designs have been implemented to improve the smoothness of INDI-SMC. Using either a notch or band-pass lter in the sensor-feedback loops of pitch angle and pitch rate only marginally reduced the swivel oscillations, but did not solve the problem for the rigid-body control. For the exible launcher with slosh dynamics, ltering of the sensor-feedback signals reduced the oscillations in swivel command, and elastic and slosh motion signi cantly, but could not completely remove them. The preliminary design of a rigid-body state observer has been included, and the results show that the INDI-SMC controller remains stable in the presence of engine dynamics, sloshing, exible modes, input errors due to the use of rigid-body and slosh-state observers, while ying in a turbulent wind field.
To limit the mass of the vehicle's thermal protection system, an optimal trajectory that minimises the total integrated heat load should be own. This means that the maximum heat-ux constraint is followed for as long as possible, until the maximum mechanical load is encountered. Flying as close to this load as possible contributes to minimising the heat load as well. The guidance system to track the path constraints includes two components: a semi-analytical guidance that produces nominal bank-angle commands and a tracking system based on non-linear dynamic inversion. The ight system under consideration is a hypersonic test vehicle of which the stagnation heat-ux should not exceed 1,700 kW/m2, with a limit of the mechanical load of 4.8 g. The preliminary results show that the tracking system extends the duration of heat-ux tracking and is able to tightly track the heat-ux constraint, but reduces the ight range because of that. A simultaneous optimisation of these two con icting objectives should be pursued to rene the guidance-system design in case both have requirements to be met. In none of the cases considered, the g-load constraint was violated, although a more detailed analysis is required to make this part of the guidance more robust.
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To limit the mass of the vehicle's thermal protection system, an optimal trajectory that minimises the total integrated heat load should be own. This means that the maximum heat-ux constraint is followed for as long as possible, until the maximum mechanical load is encountered. Flying as close to this load as possible contributes to minimising the heat load as well. The guidance system to track the path constraints includes two components: a semi-analytical guidance that produces nominal bank-angle commands and a tracking system based on non-linear dynamic inversion. The ight system under consideration is a hypersonic test vehicle of which the stagnation heat-ux should not exceed 1,700 kW/m2, with a limit of the mechanical load of 4.8 g. The preliminary results show that the tracking system extends the duration of heat-ux tracking and is able to tightly track the heat-ux constraint, but reduces the ight range because of that. A simultaneous optimisation of these two con icting objectives should be pursued to rene the guidance-system design in case both have requirements to be met. In none of the cases considered, the g-load constraint was violated, although a more detailed analysis is required to make this part of the guidance more robust.
Parachute/flow interaction is dominant in evaluating a decelerator’s performance. Such interaction is characterized by nonlinear deformations and complex flow phenomena. While testing methods are available to investigate parachute performance, these are often costly and nonrepresentative of the desired flight conditions. To address the need for an accessible technique capable of modeling parachutes at the early design stages, this paper proposes a robust fluid/structure interaction methodology for three-dimensional subsonic simulations. This is attained by replacing the linear springs in Provot’s equation with polynomial expressions whose coefficients are fitted to tensile test data. The nonlinear cloth algorithm is coupled with the rhoPorousSimpleFoam solver in the open-source OpenFOAM toolbox, thereby establishing an iterative process that reaches steady-state convergence in at most six iterations. The transient response is obtained from the average distributed load of the steady-state pressure field and an inertial damping contribution. The simulations are performed for two disk-gap-band parachutes and a ringsail parachute over a velocity range of ring sail 5–30 m/s. The results are compared to the experimental data measured in the Open Jet Facility of Delft University of Technology, yielding errors below 5% for the steady-state cases and overestimations in peak loads of 4.4–12.4% for the transient simulations.
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Parachute/flow interaction is dominant in evaluating a decelerator’s performance. Such interaction is characterized by nonlinear deformations and complex flow phenomena. While testing methods are available to investigate parachute performance, these are often costly and nonrepresentative of the desired flight conditions. To address the need for an accessible technique capable of modeling parachutes at the early design stages, this paper proposes a robust fluid/structure interaction methodology for three-dimensional subsonic simulations. This is attained by replacing the linear springs in Provot’s equation with polynomial expressions whose coefficients are fitted to tensile test data. The nonlinear cloth algorithm is coupled with the rhoPorousSimpleFoam solver in the open-source OpenFOAM toolbox, thereby establishing an iterative process that reaches steady-state convergence in at most six iterations. The transient response is obtained from the average distributed load of the steady-state pressure field and an inertial damping contribution. The simulations are performed for two disk-gap-band parachutes and a ringsail parachute over a velocity range of ring sail 5–30 m/s. The results are compared to the experimental data measured in the Open Jet Facility of Delft University of Technology, yielding errors below 5% for the steady-state cases and overestimations in peak loads of 4.4–12.4% for the transient simulations.
Objects travelling at hypersonic speeds typically experience significant mechanical loads, particularly during acceleration/deceleration. Excluding both technical and economic limitations, sub-orbital point-to-point travel is inevitably restricted to a group of individuals that are trained and whose health is certified prior to travel. This work seeks to explore the possibility of identifying, for a chosen route and reference vehicle, a set of parameters such that an individual could participate in hypersonic travel without health screenings or prior training. An open-loop guidance system is used with idealised navigation and control systems. The guidance method is based on node control with the assumption of instant implementation of commanded states. After an initial design space exploration is performed with various evolutionary algorithms, the Multi-objective Evolutionary Algorithm based on Decomposition with differential evolution (MOEA/D) (DE) is selected for further use, along with a preferred set of objective functions and a decision vector length. The subsequent optimisation strategy is separated into a coupled and decoupled phase approach, where the coupled approach combines the vehicle’s ascent and descent optimisations, while the decoupled approach performs a descent phase optimisation and attempts to link an ascent phase to the optimised descent phase. Decoupling, as performed, did not allow for the identification of a linkable trajectory. An optimal trajectory was identified with the coupled approach that required a significant amount of additional propellant and dry mass, yet maximum g0-loads approached the constraint of an increase of 1 g0. Recommendations are given to further the study.
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Objects travelling at hypersonic speeds typically experience significant mechanical loads, particularly during acceleration/deceleration. Excluding both technical and economic limitations, sub-orbital point-to-point travel is inevitably restricted to a group of individuals that are trained and whose health is certified prior to travel. This work seeks to explore the possibility of identifying, for a chosen route and reference vehicle, a set of parameters such that an individual could participate in hypersonic travel without health screenings or prior training. An open-loop guidance system is used with idealised navigation and control systems. The guidance method is based on node control with the assumption of instant implementation of commanded states. After an initial design space exploration is performed with various evolutionary algorithms, the Multi-objective Evolutionary Algorithm based on Decomposition with differential evolution (MOEA/D) (DE) is selected for further use, along with a preferred set of objective functions and a decision vector length. The subsequent optimisation strategy is separated into a coupled and decoupled phase approach, where the coupled approach combines the vehicle’s ascent and descent optimisations, while the decoupled approach performs a descent phase optimisation and attempts to link an ascent phase to the optimised descent phase. Decoupling, as performed, did not allow for the identification of a linkable trajectory. An optimal trajectory was identified with the coupled approach that required a significant amount of additional propellant and dry mass, yet maximum g0-loads approached the constraint of an increase of 1 g0. Recommendations are given to further the study.
The beginning of the conceptual design phase of (re)entry missions requires aerodynamic methods to reduce the initial design space. For this purpose, full computational fluid dynamics (CFD) simulations are unsuitable due to their computational requirements. Rapid hypersonic methods are thus often employed to approximate the heat flux and skin friction on the most critical parts of the (re)entry vehicle, such as the nose and the leading edges. However, the vast majority of these rapid methods only allow for a computation of these parameters at specific fixed locations and not on the other parts of the vehicle. One method that overcomes this is the axisymmetric analogue method, that determines the entire viscous flowfield from the inviscid flowfield solution. This method has typically been coupled to inviscid Euler simulations, but even Euler simulations can still consume a lot of computational time. In earlier research, it was shown that a reasonable accuracy can also be obtained if this method is coupled with the inviscid flowfield computed via the modified Newtonian technique. In this paper, we extend the validation and estimation of the uncertainties of this method using CFD, evaluate the respective corrections for thermal and chemical fluxes separately, and apply these corrections back to the solver. The biconic DART vehicle, partial optimisation of which was presented in the previous paper, is revisited, here optimising only four parameters instead of five as originally intended, as using five parameters resulted in an unfeasible geometry. We perform a full response surface methodology and analysis of variance accounting for the CFD corrections and examine the final optimised design also again with the Newtonian/axisymmetric code. The proposed methodology leads to a small underestimate of the heat fluxes, but is considered sufficient for the conceptual design phase.
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The beginning of the conceptual design phase of (re)entry missions requires aerodynamic methods to reduce the initial design space. For this purpose, full computational fluid dynamics (CFD) simulations are unsuitable due to their computational requirements. Rapid hypersonic methods are thus often employed to approximate the heat flux and skin friction on the most critical parts of the (re)entry vehicle, such as the nose and the leading edges. However, the vast majority of these rapid methods only allow for a computation of these parameters at specific fixed locations and not on the other parts of the vehicle. One method that overcomes this is the axisymmetric analogue method, that determines the entire viscous flowfield from the inviscid flowfield solution. This method has typically been coupled to inviscid Euler simulations, but even Euler simulations can still consume a lot of computational time. In earlier research, it was shown that a reasonable accuracy can also be obtained if this method is coupled with the inviscid flowfield computed via the modified Newtonian technique. In this paper, we extend the validation and estimation of the uncertainties of this method using CFD, evaluate the respective corrections for thermal and chemical fluxes separately, and apply these corrections back to the solver. The biconic DART vehicle, partial optimisation of which was presented in the previous paper, is revisited, here optimising only four parameters instead of five as originally intended, as using five parameters resulted in an unfeasible geometry. We perform a full response surface methodology and analysis of variance accounting for the CFD corrections and examine the final optimised design also again with the Newtonian/axisymmetric code. The proposed methodology leads to a small underestimate of the heat fluxes, but is considered sufficient for the conceptual design phase.
We present a 3 Degrees of Freedom mission design and analysis for in-situ probing of Uranus' atmosphere consisting of two un-propelled gliders and one orbiting spacecraft in continuous line of sight. We focus on the study of the gliders' navigation and science modules. Because of the lack of a Global Navigation Satellite System around Uranus and the ineffective use of optical sensors due to the planet's large distance to the Sun and high atmospheric opacity, the post-processing relation between the vehicles' estimated state and measured scientific data is investigated to yield accurate state estimations. In-situ probing by the two gliders will make it possible to measure spatially variable atmospheric properties over a flight duration of up to 12 Earth days, as compared to a few hours for a conventional descent probe. Future work will include a 6 Degrees of Freedom simulation of the vehicles' flight, the chosen planet's wind model, a Flush Air Data Sensor as an additional navigation sensor, and a band-pass filter to reduce the estimated variables' noise.
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We present a 3 Degrees of Freedom mission design and analysis for in-situ probing of Uranus' atmosphere consisting of two un-propelled gliders and one orbiting spacecraft in continuous line of sight. We focus on the study of the gliders' navigation and science modules. Because of the lack of a Global Navigation Satellite System around Uranus and the ineffective use of optical sensors due to the planet's large distance to the Sun and high atmospheric opacity, the post-processing relation between the vehicles' estimated state and measured scientific data is investigated to yield accurate state estimations. In-situ probing by the two gliders will make it possible to measure spatially variable atmospheric properties over a flight duration of up to 12 Earth days, as compared to a few hours for a conventional descent probe. Future work will include a 6 Degrees of Freedom simulation of the vehicles' flight, the chosen planet's wind model, a Flush Air Data Sensor as an additional navigation sensor, and a band-pass filter to reduce the estimated variables' noise.
Space safety and hazard-reduction techniques for space-transportation vehicles are becoming critical in the advent of commercial crewed launches and suborbital intercontinental travel. One way to mitigate risks is to use advanced guidance strategies to centralise mission planning, and guidance, navigation and control. Convex optimisation can be suitable for this purpose, as it solves second-order-cone programming problems sequentially in polynomial time. As atmospheric re-entry contains a large number of non-convexities, an advanced optimal-control optimiser based on successive convex optimisation was developed and analysed with a golden-section line-search method to enhance its convergence. A direct-linearisation approach, although slightly sensitive to initial guesses, was seen to be robust when compared in different objective formulations. However, a hybrid approach using a lossless convexification performed better for most problems, although it relied on a regularisation condition, which was sometimes difficult to satisfy. The reachability capabilities of the SPHYNX lifting body during orbital and descent aborts were analysed and showed that around 14 minutes are available to perform an abort to an alternative landing site for a nominal mission. While there is significant room for improvement, the study shows that successive convex optimisation could be potentially used for mission planning and on-board applications as an optimal trajectory planner during realistic re-entry missions.
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Space safety and hazard-reduction techniques for space-transportation vehicles are becoming critical in the advent of commercial crewed launches and suborbital intercontinental travel. One way to mitigate risks is to use advanced guidance strategies to centralise mission planning, and guidance, navigation and control. Convex optimisation can be suitable for this purpose, as it solves second-order-cone programming problems sequentially in polynomial time. As atmospheric re-entry contains a large number of non-convexities, an advanced optimal-control optimiser based on successive convex optimisation was developed and analysed with a golden-section line-search method to enhance its convergence. A direct-linearisation approach, although slightly sensitive to initial guesses, was seen to be robust when compared in different objective formulations. However, a hybrid approach using a lossless convexification performed better for most problems, although it relied on a regularisation condition, which was sometimes difficult to satisfy. The reachability capabilities of the SPHYNX lifting body during orbital and descent aborts were analysed and showed that around 14 minutes are available to perform an abort to an alternative landing site for a nominal mission. While there is significant room for improvement, the study shows that successive convex optimisation could be potentially used for mission planning and on-board applications as an optimal trajectory planner during realistic re-entry missions.
Re-entry shape and trajectory optimisation studies typically require hundreds to thousands of flow solutions to resolve the heat transfer and skin friction. Due to the fact that full CFD simulations and even Euler simulations are typically very expensive, this work presents a development of a much simpler technique, in which the modified Newtonian approximation is coupled with the axisymmetric-analogue-based viscous method. Afterwards, the developed technique is applied to the shape optimisation study of the DART module originally conducted by Sudmeijer and Mooij in 2002. Large differences in heat fluxes are observed mainly owing to the fact that the present method estimates the transition region from approximate transition criteria while the original study assumes the transition point to be fixed at the interface between the cone and the flare. This emphasises the sensitivity of design optimisation studies on delicate parameters such as the location of transition, which typically cannot be accurately predicted during the conceptual phase. Finally, the limitations of the current method are identified and the areas in which the technique will be improved further are outlined.
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Re-entry shape and trajectory optimisation studies typically require hundreds to thousands of flow solutions to resolve the heat transfer and skin friction. Due to the fact that full CFD simulations and even Euler simulations are typically very expensive, this work presents a development of a much simpler technique, in which the modified Newtonian approximation is coupled with the axisymmetric-analogue-based viscous method. Afterwards, the developed technique is applied to the shape optimisation study of the DART module originally conducted by Sudmeijer and Mooij in 2002. Large differences in heat fluxes are observed mainly owing to the fact that the present method estimates the transition region from approximate transition criteria while the original study assumes the transition point to be fixed at the interface between the cone and the flare. This emphasises the sensitivity of design optimisation studies on delicate parameters such as the location of transition, which typically cannot be accurately predicted during the conceptual phase. Finally, the limitations of the current method are identified and the areas in which the technique will be improved further are outlined.