Hypersonic Entry Research Articles

Entry guidance for spatial no-fly zones avoidance via model-based reinforcement learning

This paper proposes a novel guidance law for hypersonic entry vehicles, considering no-fly zones with height limits. Traditional planar assumptions restrict the flexibility of trajectory design for scenarios like radar avoidance. Besides, the numerical integration proves inefficient for long-term prediction and avoidance. Therefore, a model-based reinforcement learning policy is designed. It offline learns entry dynamics in advance and onboard plans a feasible trajectory. The planner's state includes flight status and no-fly zones; action presents waypoints; and reward ensures constraint while maximizing terminal precision. Then, analytical prediction converts spatial no-fly zone constraints to flight-path angle constraints, improving precision compared to traditional one-step estimates. Finally, the two parts are assembled into the predictor-corrector framework, which gives the augmented guidance commands. While retaining its robustness to bias, our method reduces online optimization calculations and outperforms constraint satisfaction. Experiments show that the model-based method reduces 60% training in offline training compared with proximal policy optimization. Besides, our method is 80% faster than conventional predictor-corrector guidance regarding online computation speed.

A Conceptual Modeling Approach for Performance of Magnetohydrodynamic Drag During Planetary Entry

Future higher-mass Mars missions present numerous engineering challenges and will require significant technological development, particularly of the entry, descent, and landing systems. One such development concept utilizes magnetohydrodynamic interaction with the plasma created during hypersonic planetary entry for energy generation, drag augmentation, and heat-flux mitigation. In this study, a performance estimation methodology for magnetohydrodynamic drag augmentation during Mars entry compatible with conceptual design is developed. A demonstrative investigation utilizing the developed methodology is then conducted, and simulated trajectory results are presented for various entry vehicles and magnetic field strengths. The study results show potential for significant magnetohydrodynamic drag augmentation during hypersonic entry at Mars, with calculated effective ballistic coefficient- reduction factors of up to 4, across entry vehicles ranging in mass from 70 MT to 4 MT. These results show that magnetohydrodynamic drag augmentation can have comparable impact to significant aeroshell diameter increases and also suggest that it could prove an effective form of drag-augmentation control authority by varying the applied magnetic field.

Constructing lightweight ternary interpenetrating network of carbon fabric/siloxane/phenolic aerogels for long-time high-temperature thermal protection

Lightweight ablative material has served the critical role of protecting space vehicles upon hypersonic entry. However, low oxidation resistance hinders its long-time high-efficiency service in a high-temperature oxidizing atmosphere. Herein, we prepared a lightweight ternary interpenetrating network of three-dimensional carbon fabric, siloxane aerogel, and phenolic aerogel, which are structurally interpenetrating in macro-, micron-to nanoscale and chemically crosslinking at the molecular scale, resulting in a unique combination of low-density (∼0.3 g/cm3), good thermal stability and oxidation resistance, outstanding mechanical properties, and ultralow thermal conductivity. More intriguingly, long-time thermal protection performance (zero surface recession and temperature below 60 °C at 38 mm in-depth after being exposed to 1300 °C for 20 min). The findings of this work provide not only a great potential candidate material for long-time thermal protection in aviation and aerospace applications but also a simple but efficient approach to fabricating multifunctional binary, ternary, and even multiple interpenetrating networks.

A Real-Time and Optimal Hypersonic Entry Guidance Method Using Inverse Reinforcement Learning

The mission of hypersonic vehicles faces the problem of highly nonlinear dynamics and complex environments, which presents challenges to the intelligent level and real-time performance of onboard guidance algorithms. In this paper, inverse reinforcement learning is used to address the hypersonic entry guidance problem. The state-control sample pairs and state-rewards sample pairs obtained by interacting with hypersonic entry dynamics are used to train the neural network by applying the distributed proximal policy optimization method. To overcome the sparse reward problem in the hypersonic entry problem, a novel reward function combined with a sophisticated discriminator network is designed to generate dense optimal rewards continuously, which is the main contribution of this paper. The optimized guidance methodology can achieve good terminal accuracy and high success rates with a small number of trajectories as datasets while satisfying heating rate, overload, and dynamic pressure constraints. The proposed guidance method is employed for two typical hypersonic entry vehicles (Common Aero Vehicle-Hypersonic and Reusable Launch Vehicle) to demonstrate the feasibility and potential. Numerical simulation results validate the real-time performance and optimality of the proposed method and indicate its suitability for onboard applications in the hypersonic entry flight.

Fast Trajectory Generation with a Deep Neural Network for Hypersonic Entry Flight

Optimal entry flight of hypersonic vehicles requires achieving specific mission objectives under complex nonlinear flight dynamics constraints. The challenge lies in rapid generation of optimal or near-optimal flight trajectories with significant changes in the initial flight conditions during entry. Deep Neural Networks (DNNs) have shown the capability to capture the inherent nonlinear mapping between states and optimal actions in complex control problems. This paper focused on comprehensive investigation and evaluation of a DNN-based method for three-dimensional hypersonic entry flight trajectory generation. The network is designed using cross-validation to ensure its performance, enabling it to learn the mapping between flight states and optimal actions. Since the time-consuming training process is conducted offline, the trained neural network can generate a single optimal control command in about 0.5 milliseconds on a PC, facilitating onboard applications. With the advantages in mapping capability and calculating speed of DNNs, this method can rapidly generate control action commands based on real-time flight state information from the DNN model. Simulation results demonstrate that the proposed method maintains a high level of accuracy even in scenarios where the initial flight conditions (including altitude, velocity, and flight path angle) deviate from their nominal values, and it has certain generalization ability.

Formation of N(2D) from Hyperthermal Collisions between O(3P) and NO(X2Π).

Hyperthermal collisions between O(3P) and NO(X2Π) could lead to the formation of the first electronically excited atomic nitrogen (N(2D)), which plays a key role in plasma formation in shock-heated air. This process is facilitated mainly by four doublet states, and to a much lesser extent by two quartet states. In this work, we report quasi-classical trajectory studies of this reactive process using the four analytical adiabatic potential energy surfaces for the doublet states developed previously from fitting high-level ab initio data. The reactions were found to be strongly enhanced by vibrational excitation of the NO reactant, consistent with the existence of potential energy barriers in the exit channel. Despite the large endothermicity of the reaction, the rate coefficient is significant at high temperatures, suggesting a possible role of this reaction in the hyperthermal kinetics in the shock layer of a hypersonic (re)entry vehicle.

Real-Time Trajectory Planning for Hypersonic Entry Using Adaptive Non-Uniform Discretization and Convex Optimization

This paper introduces an improved sequential convex programming algorithm using adaptive non-uniform discretization for the hypersonic entry problem. In order to ensure real-time performance, an inverse-free precise discretization based on first-order hold discretization is adopted to obtain a high-accuracy solution with fewer temporal nodes, which would lead to constraint violation between the temporal nodes due to the sparse time grid. To deal with this limitation, an adaptive non-uniform discretization is developed, which provides a search direction for purposeful clustering of discrete points by adding penalty terms in the problem construction process. Numerical results show that the proposed method has fast convergence with high accuracy while all the path constraints are satisfied over the time horizon, thus giving potential to real-time trajectory planning.

Real-time quantitative imaging of RTV silicone pyrolysis

Quantitative microstructural analysis of Room Temperature Vulcanized (RTV) silicone pyrolysis at high temperatures is presented. RTV is used as a bonding agent in multiple industries, particularly filling gaps in ablative tiles for hypersonic (re-)entry vehicles and fire prevention. Decomposition of RTV is resolved in real time using in situ high-temperature X-ray computed micro-tomography. Tomographies are acquired every 45 seconds for four different linear heating rates ranging from 7 to 54°C/min. The microstructure is resolved below 5 μm/pixel, allowing for a quantitative analysis of the micro-structural evolution and porous network development. Results are heating rate dependent, and are evaluated for bulk sample volume change, porosity, pore network size, and densification from X-ray attenuation. The outcome of this work is critical to develop multi-physics models for thermal response.

Parachute deployment on Venus : Recovery of “Lost” Pioneer Venus large probe entry accelerometer data

Previously-unpublished data from the Pioneer Venus multiprobe mission are presented, documenting key events in the entry and descent. The data comprise the latter part of the hypersonic entry as documented by accelerometers, and show the deceleration of the vehicle through the transonic region, and the deployment of the parachute. Such data are of interest for comparison with the DAVINCI mission under development, and the parachute deployment record is compared with those of other missions to inform the sample rate needed to characterize key events.

A deep learning-based approach to time-coordination entry guidance for multiple hypersonic vehicles

AbstractA multiple-vehicles time-coordination guidance technique based on deep learning is suggested to address the cooperative guiding problem of hypersonic gliding vehicle entry phase. A dual-parameter bank angle profile is used in longitudinal guiding to meet the requirements of time coordination. A vehicle trajectory database is constructed along with a deep neural network (DNN) structure devised to fulfill the error criteria, and a trained network is used to replace the conventional prediction approach. Moreover, an extended Kalman filter is constructed to detect changes in aerodynamic parameters in real time, and the aerodynamic parameters are fed into a DNN. The lateral guiding employs a logic for reversing the sign of bank angle, which is based on the segmented heading angle error corridor. The final simulation results demonstrate that the built DNN is capable of addressing the cooperative guiding requirements. The algorithm is highly accurate in terms of guiding, has a fast response time, and does not need inter-munition communication, and it is capable of solving guidance orders that satisfy flight requirements even when aerodynamic parameter disruptions occur.

Novel Engineering Methodology for Decoupled Aerothermal Analysis of Hypersonic Atmospheric Entry Flows

Analyses of thermal protection system response to atmospheric entry are generally performed in a decoupled manner where some terms in the surface balance equations are simplified. In such an approach, surface fluxes are calculated using a fluid dynamics solution of the hypersonic flowfield. These are nondimensionalized for use by a material response code, where correction terms are applied to account for the missing physics. A new method is presented here that directly includes ablation physics, thus removing the need for correction models. This approach includes the diffusion processes of ablative species in the boundary layer and nonequilibrium surface chemistry. The new approach is compared to the heritage methodology using a trajectory designed to allow molecular dissociation and vibrational energy contribution. The new methodology predicts surface temperatures with the same qualitative trend, with the largest disagreements in areas of the trajectory where nonequilibrium effects are expected to occur. The solid ablation flux and subsequent recession behavior are consistently lower for the new method, but this discrepancy in surface thermochemistry can be decreased by adopting kinetic models with more aggressive oxidation mechanisms. It is found that a large difference in computed recession does not necessarily equate to the largest difference in heat shield sizing.

Stagnation point heat flux characterization under numerical error and boundary conditions uncertainty

The numerical simulation of hypersonic atmospheric entry flows is a challenging problem. Prediction of quantities of interest, such as surface heat flux and pressure, is strongly influenced by the mesh quality using conventional second-order spatial accuracy schemes while depending on boundary conditions, which may generally suffer from uncertainty. This paper illustrates one of the first systematic quantification of the numerical error and the uncertainty-induced variability for the simulation of hypersonic flows. Specifically, a mesh-convergence study using grid adaptation tools is coupled with surrogate-based approaches to Uncertainty Quantification. The illustrative example is the simulation of the EXPERT vehicle of the European Space Agency employing the US3D solver. First, we show the benefits in using mesh adaptation to simulate hypersonic flows under uncertainty. On the one hand, this practice reduces the numerical uncertainty associated with each prediction and, on the other hand, allows us to obtain a more reliable surrogate model for Uncertainty Quantification by preventing non-physical heat flux values.Secondly, we perform a sensitivity analysis to compare the numerical uncertainty associated with a given mesh with the UQ-induced variability for a specific quantity of interest. In the case considered, the impact of the numerical uncertainty turned out to be at least one order of magnitude less than the quantity of interest variability. This result indicates the possibility of using coarse and adapted meshes for future UQ studies.

Performance Analysis of Mars-Powered Descent-Based Landing in a Constrained Optimization Control Framework

It is imperative to find new places other than Earth for the survival of human beings. Mars could be the alternative to Earth in the future for us to live. In this context, many missions have been performed to examine the planet Mars. For such missions, planetary precision landing is a major challenge for the precise landing on Mars. Mars landing consists of different phases (hypersonic entry, parachute descent, terminal descent comprising gravity turn, and powered descent). However, the focus of this work is the powered descent phase of landing. Firstly, the main objective of this study is to minimize the landing error during the powered descend landing phase. The second objective involves constrained optimization in a predictive control framework for landing at non-cooperative sites. Different control algorithms like PID and LQR have been developed for the stated problem; however, the predictive control algorithm with constraint handling’s ability has not been explored much. This research discusses the Model Predictive Control algorithm for the powered descent phase of landing. Model Predictive Control (MPC) considers input/output constraints in the calculation of the control law and thus it is very useful for the stated problem as shown in the results. The main novelty of this work is the implementation of Explicit MPC, which gives comparatively less computational time than MPC. A comparison is done among MPC variants in terms of feasibility, constraints handling, and computational time. Moreover, other conventional control algorithms like PID and LQR are compared with the proposed predictive algorithm. These control algorithms are implemented on quadrotor UAV (which emulates the dynamics of a planetary lander) to verify the feasibility through simulations in MATLAB.

In situ tensile behavior of Hi‐Nicalon silicon carbide fibers exposed to high‐temperature argon plasma

AbstractDirect mechanical characterization of silicon carbide fibers in extreme hypersonic aerothermal environment is critical to the development of next‐generation inflatable thermal protection systems that could enable delivery of large payloads to planetary surfaces. In this article, we report direct measurements of tensile properties in Hi‐Nicalon silicon carbide fibers exposed to high‐temperature argon plasma exceeding 1100°C using an in situ mechanical testing system integrated into a 30‐kW inductively coupled plasma torch chamber simulating the hypersonic atmospheric entry conditions. As a comparison, ex situ tensile tests were performed on virgin Hi‐Nicalon silicon carbide fibers in both ambient air and vacuum conditions. In situ thermal and optical imaging was used to obtain a real‐time resolution of the thermo‐mechanical events occurring on the fibers during the high‐temperature argon plasma exposure. It is found that the high‐temperature tensile strength of Hi‐Nicalon fiber tows exposed to argon plasma is 0.74 ± 0.19 GPa, which denotes a 59% reduction from the virgin fiber strength in ambient air (1.81 ± 0.19 GPa). Fractographic characterization by scanning electron microscopy shows that the substantial degradation of tensile strength in Hi‐Nicalon fibers results from a reduction of fiber cross‐section due to active surface attack from high‐temperature argon plasma.

Shock wave propagation through air: a reactive molecular dynamics study

Shock compression of air is observed in numerous situations ranging from explosions to hypersonic vehicle entry into atmosphere. In an effort to develop continuum-based equation of state for air subjected to shock compression, it is necessary to understand the dynamics of the shock compression process with regards to formation of new chemical species in air at the molecular level. With this in perspective, three different models of air (consisting a mixture of O 2 , N 2 and CO 2 gas, with or without H 2 O based on presence of humidity) are subjected to shock compression ranging from 0.5 km s −1 to 5.0 km s −1 particle velocities. Thermodynamic quantities are evaluated to plot Rankine Hugoniot planes for the three different air models: dry air at mean sea level (MSL), humid air at MSL and dry air at high altitude level of 36 000 ft above MSL. It is observed that high shock velocities eventually results in dissociation of gaseous molecules and formation of new gaseous species which has been quantified in the manuscript.

Adaptive Entry Guidance for Hypersonic Gliding Vehicles Using Analytic Feedback Control

This paper presents an adaptive, simple, and effective guidance approach for hypersonic entry vehicles with high lift-to-drag (L/D) ratios (e.g., hypersonic gliding vehicles). The core of the constrained guidance approach is a closed-form, easily obtained, and computationally efficient feedback control law that yields the analytic bank command based on the well-known quasi-equilibrium glide condition (QEGC). The magnitude of the bank angle command consists of two parts, i.e., the baseline part and the augmented part, which are calculated analytically and successively. The baseline command is derived from the analytic relation between the range-to-go and the velocity to guarantee the range requirement. Then, the bank angle is augmented with the predictive altitude-rate feedback compensations that are represented by an analytic set of flight path angle needed for the terminal constraints. The inequality path constraints in the velocity-altitude space are translated into the velocity-dependent bounds for the magnitude of the bank angle based on the QEGC. The sign of the bank command is also analytically determined using an automated bank-reversal logic based on the dynamic adjustment criteria. Finally, a feasible three-degree-of-freedom (3DOF) entry flight trajectory is simultaneously generated by integrating with the real-time updated command. Because no iterations and no or few off-line parameter adjustments are required using almost all analytic processing, the algorithm provides remarkable simplicity, rapidity, and adaptability. A considerable range of entry flights using the vehicle data of the CAV-H is tested. Simulation results demonstrate the effectiveness and performance of the presented approach.

Multifidelity Modeling for Efficient Aerothermal Prediction of Deployable Entry Vehicles

The objective of this work was to investigate a multifidelity modeling approach to accurately and efficiently predict the aerothermal response of a large-diameter deployable hypersonic entry vehicle in Mars entry. A cokriging-based multifidelity modeling approach was developed that used several refinements including lower–upper decomposition for parallelization, distance weighted root-mean-square error adaptive sampling, and surface distribution parameterization using Hicks–Henne bump functions. Several computational tools of varying fidelity were investigated to model the surface convective heat flux, shear stress, pressure, and radiative heat flux in the multifidelity modeling process. The multifidelity model was found to have a mean convective heat rate error of 4.6%, a mean pressure force error of 0.81%, a mean shear force error of 2.86%, and a mean radiative heat rate error of 11.1% when compared to high-fidelity computational fluid dynamics simulations. Compared to a single-fidelity model, the multifidelity model required approximately one-half the number of high-fidelity model evaluations to obtain the same accuracy level. The computational cost of constructing and evaluating the multifidelity model were approximately one and five orders of magnitude less, respectively, than one high-fidelity model simulation.

Structural Response Modeling of a Woven Thermal Protection System

Woven thermal protection systems (TPSs) are being developed for extreme heating conditions experienced during hypersonic atmospheric entry. A linear elasticity solver is used to model this new class of TPS. In particular, this paper explores and assesses the effectiveness of the linear elastic model for the Heatshield for Extreme Entry Environment Technology (HEEET) woven material through comparisons with experimental data measured on a 24 in. HEEET weave. Initial assessments are performed using a known set of stiffness properties previously derived from a 13 in. HEEET weave. Comparisons between simulation results and experimental strain gauge measurements show excellent agreement on the insulation surface but a considerable overprediction of the deformation on the recession surface. The manufacturing process for the 24 in. weave is postulated to have resulted in a stiffer recession layer weave. To account for this, inverse optimization is used to infer stiffness properties of this tighter weave with no a priori properties. The results indicate that the 24 in. weave is approximately twice as stiff as that of the 13 in. weave, and comparisons between simulation displacement predictions using the inferred properties and experimental linear variable displacement transducer measurements show excellent agreement.

New Method for Systems and Cost Analysis of Human Mars Entry Vehicles

Cost is one of the biggest obstacles to sending humans to Mars. However, spacecraft costs are typically not estimated until after the preliminary vehicle and mission concepts have been designed. By automating the cost estimation process, the effect of any change in vehicle or mission design on the mission cost can be determined more efficiently. This paper describes an extension to the systems analysis for planetary entry, descent, and landing tool. This extension integrates the cost modeling software SEER-H (which stands for system estimation and evaluation of resources hardware) with a number of systems analysis tools. This new method is used to analyze several tradespaces of a hypersonic inflatable aerodynamic decelerator entry vehicle for human Mars missions. Key findings include quantifying the impacts of the ballistic coefficient, the main engine specific impulse, and the thrust-to-weight ratio on the overall cost of the vehicle; as well as how the payload per lander and the number of landers affect the cost of a campaign to Mars.

Rapid trajectory optimization for hypersonic entry using convex optimization and pseudospectral method

Purpose This paper aims to develop a novel trajectory optimization algorithm which is capable of producing high accuracy optimal solution with superior computational efficiency for the hypersonic entry problem. Design/methodology/approach A two-stage trajectory optimization framework is constructed by combining a convex-optimization-based algorithm and the pseudospectral-nonlinear programming (NLP) method. With a warm-start strategy, the initial-guess-sensitive issue of the general NLP method is significantly alleviated, and an accurate optimal solution can be obtained rapidly. Specifically, a successive convexification algorithm is developed, and it serves as an initial trajectory generator in the first stage. This algorithm is initial-guess-insensitive and efficient. However, approximation error would be brought by the convexification procedure as the hypersonic entry problem is highly nonlinear. Then, the classic pseudospectral-NLP solver is adopted in the second stage to obtain an accurate solution. Provided with high-quality initial guesses, the NLP solver would converge efficiently. Findings Numerical experiments show that the overall computation time of the two-stage algorithm is much less than that of the single pseudospectral-NLP algorithm; meanwhile, the solution accuracy is satisfactory. Practical implications Due to its high computational efficiency and solution accuracy, the algorithm developed in this paper provides an option for rapid trajectory designing, and it has the potential to evolve into an online algorithm. Originality/value The paper provides a novel strategy for rapid hypersonic entry trajectory optimization applications.