Search Results (22)

This paper addresses the real-time trajectory generation problem for hypersonic glide vehicles (HGVs) during atmospheric entry, subject to complex constraints including aerothermal limits, actuator bounds, and no-fly zones (NFZs). To achieve efficient and reliable trajectory planning, a two-phase hp-adaptive sequential convex programming (SCP) framework is proposed. NFZ avoidance is reformulated as a soft objective to enhance feasibility under tight geometric constraints. In Phase I, a shrinking-trust-region strategy progressively tightens the soft trust-region radius by increasing the penalty weight, effectively suppressing linearization errors. A sensitivity-driven mesh refinement method then allocates collocation points based on their contribution to the objective function. Phase II applies residual-based refinement to reduce discretization errors. The resulting reference trajectory is tracked using a linear quadratic regulator (LQR) within a reference-trajectory-tracking guidance (RTTG) architecture. Simulation results demonstrate that the proposed method achieves convergence in only a few iterations, generating high-fidelity trajectories within 2–3 s. Compared to pseudospectral solvers, the method achieves over 12× computational speed-up while maintaining kilometer-level accuracy. Monte Carlo tests under uncertainties confirm a 100% success rate, with all constraints satisfied. These results validate the proposed method’s robustness, efficiency, and suitability for onboard real-time entry guidance in dynamic mission environments. Full article

This study starts from the physical perspective of electromagnetic wave propagation in ionosphere media, and the skywave OTH (over-the-horizon) ionosphere channel model is established for hypersonic vehicles based on the ray-tracing method, and this study identifies the key parameters influencing channel characteristics. Secondly, using the re-entry trajectory of the RAM C-II flight experiment as an example, dynamic multipath channel characteristic parameters—such as loss, delay, and Doppler shift—are analyzed in multiple seasons during the noon and midnight periods at a communication frequency of 14 MHz. The results indicate that the settling effect of the ionosphere at midnight makes the changes in the channel more complex, with the irregular sudden appearance and disappearance of multipath numbers. In addition, channel loss is greater in low-elevation propagation mode than in high-elevation propagation mode, indicating that the channel multipath exhibits high loss and low delay characteristics. The skywave communication channel model for hypersonic vehicles, and the dynamic multipath channel characteristic parameters presented in this study offer valuable support for the design, development, and evaluation of long-distance TT&C (Tracking, Telemetering, and Command) communication systems. Full article

Materials used in aircraft engines, gas turbines, nuclear reactors, re-entry vehicles, and hypersonic structures are subject to severe environmental conditions that present significant challenges. With their remarkable properties, such as high melting temperatures, strong resistance to oxidation, corrosion, and ablation, minimal creep, and advantageous thermal cycling behavior, ceramic matrix composites (CMCs) show great promise as a material to meet the strict requirements in these kinds of environments. Furthermore, the addition of boron nitride nanoparticles with continuous fibers to the CMCs can offer thermal resistivity in harsh conditions, which will improve the composites’ strength and fracture toughness. Therefore, in extreme situations, it is crucial to understand the thermal resistivity period of composite materials. To forecast the ablation performance of composites, we developed six machine learning regression methods in this study: decision tree, random forest, support vector machine, gradient boosting, extreme gradient boosting, and adaptive boosting. When evaluating model performance using metrics including R2 score, root mean square error, mean absolute error, and mean absolute percentage error, the gradient boosting and extreme gradient boosting machine learning regression models performed better than the others. The effectiveness of machine learning models as a useful tool for forecasting the ablation behavior of ceramic matrix composites was effectively explained by this study. Full article

Explorations involving long-endurance and maneuvering flights in the upper atmosphere, as well as research on atmospheric entries of space debris or asteroids, call for a full understanding of hypersonic rarefied flows. The inverse Magnus effect occurs in the hypersonic rarefied flow past a rotating sphere, but the aerodynamic behavior is contrary to the Magnus effect in the continuum flow regime. In this article, a series of such flows are numerically studied using the direct simulation Monte Carlo (DSMC) method. By analyzing the flow fields, as well as the distributions of pressure and shear stress on the sphere, the formation of the inverse Magnus force can be attributed to the tangential momentum transfer between incident gas molecules and the windward surface. The variation laws of aerodynamic parameters with the rotation rate are presented and discussed. Full article

The goal of this paper is to investigate the aerodynamic and aerothermodynamic behavior of the Schiaparelli capsule after the deployment of a supersonic disk-gap-band (DGB) parachute during its re-entry phase into the Martian atmosphere. The novelty of this work lies in the investigation by LES (large-eddy simulations) of the coupled interaction of the flow field generated behind the capsule and that in front of the flexible DGB parachute. These simulations are performed at an altitude of 10 km and a Mach number around 2, i.e., a regime in which large canopy-area oscillations are observed. LES results have shown a strong interaction between the bow shock, the recompression and expansion waves, high pressure, density and temperature gradients, heat flux towards the airstream and the body implying turbulence generation, ingestion, and amplification through the shock waves. Vortices released from the capsule at a frequency of about 52 Hz and 159 Hz, corresponding to Strouhal numbers of ~0.2 and 0.75, respectively, are the main factors responsible for the instabilities of the hypersonic re-entry capsule and the disk-gap-band parachute coupled system. The nonlinear turbulence flow field generated at the capsule back is amplified when passing the parachute bow shock, and this is responsible for the non-axisymmetric behavior around and behind the parachute that caused the uncontrolled capsule oscillations and the Schiaparelli mission failure. In fact, an LES of the parachute without the capsule, for the same conditions, show a completely axisymmetric field, varying in time, but axisymmetric. In order to avoid this turbulence amplification, dampening of the vortex shedding is critical. Different techniques have been already proposed for other applications. In the case of capsule re-entry, due to the high temperatures in front of the capsule behind the bow shock since air plasma is generated, damping of the vortex shedding could be achieved by means of magnetohydrodynamic (MHD) control. Full article

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. Full article

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. Full article

This work deals with the numerical solution of hypersonic flow of viscous fluid over a compressible ramp. The solved case involves very important and complicated phenomena such as the interaction of the shock wave with the boundary layer or the transition from a laminar to a turbulent state. This type of problem is very important as it is often found on re-entry vehicles, engine intakes, system and sub-system junctions, etc. Turbulent flow is modeled by the system of averaged Navier–Stokes equations, which is completed by the explicit algebraic model of Reynolds stresses (EARSM model) and further enhanced by the algebraic model of bypass transition. The numerical solution is obtained by the finite volume method based on the rotated-hybrid Riemann solver and explicit multistage Runge–Kutta method. The numerical solution is then compared with the results of a direct numerical simulation. Full article

A human Mars mission is more challenging to astronauts than the Apollo mission because of travel time, life support requirements, and the space environment. Although plans for Mars exploration by NASA and SpaceX based on conventional rockets have been presented, there are considerations that suggest alternatives for the mid- or long-term. The purpose of this paper is to outline a fast mission enabled by advanced (nuclear) propulsion and by internationally shared technology. Whether the destination is the Mars surface or Phobos, for a chemical powered spacecraft, the round trip takes about 990 days, including a 480-day surface stay, compared to only 370 days, including a 41-day surface stay, for the nuclear-powered spacecraft assumed here. Since nuclear propulsion can provide higher speed than chemical, the radiation dose can be drastically reduced. The logistics of such a mission involve one or more cargo craft that must precede the astronauts. Ballistic entry into Mars’ atmosphere depends on accurate knowledge of its features, to date poorly known, that may result in uncertainty in landing coordinates. For a single vehicle, this is not critical, but for a human crew ballistic landing kilometers away from cargo is unacceptable: walking for anything but the shortest distance cannot be afforded with current space suits. In this context, the concept of a modest L/D maneuvering cargo glider based on the past Russian “Kliper” is recommended and developed to ensure landing within a hundred meters of each spacecraft. The crewed lander vehicle is based on the high L/D, inherently stable USAF FDL-7C/D hypersonic glider experience. In a similar approach, an exploration vehicle powered by in situ manufactured CO₂ and silane is described that can explore the Martian surface much faster and efficiently than with rovers or rocket-powered ‘hoppers’. Full article

A high-temperature plasma sheath is generated on the surface of the re-entry vehicle through the conversion of kinetic energy to thermal and chemical energy across a strong shock wave at the hypersonic speed. Such a condition results in the forming of a blackout which significantly affects the communication components. To analyze the re-entry vehicle at the hypersonic speed, an unconditionally stable system incorporated factorization-splitting (SIFS) algorithm is proposed in finite-difference time-domain (FDTD) grids. The proposed algorithm shows advantages in the entire performance by simplifying the update implementation in multi-scale problems. The plasma sheath is analyzed based on the modified auxiliary difference equation (ADE) method according to the integer time step scheme in the unconditionally stable algorithm. Higher order perfectly matched layer (PML) formulation is modified to simulate open region problems. Numerical examples are carried out to demonstrate the performance of the algorithm from the aspects of target characteristics and antenna model. From resultants, it can be concluded that the proposed algorithm shows considerable accuracy, efficiency, and absorption during the simulation. Meanwhile, plasma sheath significantly affects the communication and detection of the re-entry vehicle. Full article

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. Full article

In response to the increasing threat of hypersonic weapons, it is of great importance for the defensive side to achieve fast prediction of their feasible attack domain and online inference of their most probable targets. In this study, an online footprint prediction and attack intention inference algorithm for hypersonic glide vehicles (HGVs) is proposed by leveraging the utilization of deep neural networks (DNNs). Specifically, this study focuses on the following three contributions. First, a baseline multi-constrained entry guidance algorithm is developed based on a compound bank angle corridor, and then a dataset containing enough trajectories for the following DNN learning is generated offline by traversing different initial states and control commands. Second, DNNs are developed to learn the functional relationship between the flight state/command and the corresponding ranges; on this basis, an online footprint prediction algorithm is developed by traversing the maximum/minimum ranges and different heading angles. Due to the substitution of DNNs for multiple times of trajectory integration, the computational efficiency for footprint prediction is significantly improved to the millisecond level. Third, combined with the predicted footprint and the hidden information in historical flight data, the attack intention and most probable targets can be further inferred. Simulations are conducted through comparing with the state-of-the-art algorithms, and results demonstrate that the proposed algorithm can achieve accurate prediction for flight footprint and attack intention while possessing significant real-time advantage. Full article

To facilitate future Hypersonic Flight Vehicle (HFV) implementation with high maneuverability throughout its reentry trajectory, an Active Jets-Matrix (AJM) is designed to serve as the flapless pitch control surface. The AJM consists of four control groups composed in total of 48 supersonic nozzles. The AJM aims to utilize the jet flow-interaction-induced additional control moment to improve the control efficiency during atmospheric entry. A comparative research method is employed to study the eight simulation cases for three different HFV configurations (baseline, mechanical control surface with 30° deflection, and the AJM configuration) and two AJM control moment adjustment strategies (nozzle chamber pressure regulation and discretized nozzle group on–off control). A conventional in-house computational fluid dynamics (CFD) solver with the two-equation SST turbulence model is employed to undertake the simulation tasks. Simulation results indicate that: (a) only the AJM configuration is capable of trimming the HFV in pitch channel; (b) nonlinearity exists between the augmentation moment and the specific control variable from respective adjustment strategies; (c) the chamber pressure regulation strategy bears higher overall efficiency, while the discretized control strategy induces more intense local jet-flow interaction. With a maximum control moment augmentation of 1.58, the AJM presents itself as a competitive candidate for future HFV flapless control methods. Full article

A computer program, MC-New, to calculate Newtonian aerodynamics is presented. The aerodynamic coefficients of a geometry expressed by an analytic function are calculated in a Monte-Carlo integration manner, in which the local forces on the randomly chosen sample points are summed up. The verification study and the accuracy analysis show that the program can provide good approximations of exact solutions. The example results of the parametric study on the Apollo-like entry capsule geometry are presented, showing the potential capability of the MC-New program as an efficient open-source tool for designing hypersonic vehicles. Full article

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. Full article