Article of the Year 2020
Processing Technology Based on Radar Signal Design and ClassificationRead the full article
International Journal of Aerospace Engineering serves the international aerospace engineering community through the dissemination of scientific knowledge on practical engineering and design methodologies pertaining to aircraft and space vehicles.
Chief Editor, Professor Zhao, is based at the University of Canterbury and his research interests include applying theoretical, numerical and experimental approaches to study combustion instability, thermoacoustics and aerodynamics.
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On High-Dimensional Time-Variant Reliability Analysis with the Maximum Entropy Principle
The structural reliability analysis suffers from the curse of dimensionality if the associated limit state function involves a large number of inputs. This study develops a reliability analysis method that deals with high-dimensional inputs over time. The probability distribution of the structural response is reconstructed by the maximum entropy principle which is achieved by solving an optimization problem derived from the concept of relative entropy. The optimization problem is transformed into a convex one with respect to the orders of fractional moments and the Lagrange multipliers. Additionally, considering the associated computational issues, it is reformulated with side constraints on the parameters of the maximum entropy distribution. Then, a global optimization procedure is performed. The proposed method is successfully applied to the reliability analysis of a linear and a nonlinear structural system, which involves a large number of inputs deriving from the discretization of the input random processes.
Design and Analysis of Direct Abort Orbits in the Earth-Moon Transfer Phase of Crewed Lunar Exploration Missions
A direct abort orbit design method is presented for direct abort missions in the Earth-Moon transfer phase of crewed lunar exploration missions. First, according to the demand of an emergency rescue in the Earth-Moon transfer phase, two direct abort orbit schemes are introduced. Then, a serial orbit design method is proposed for a high-fidelity direct abort orbit. An analytical model is established for the calculation of initial values, and the optimization design is performed in the high-fidelity orbit model to determine a single-impulse abort orbit. A hybrid optimization design process is proposed to generate a two-impulse abort orbit. The results of simulation examples verify the validity and feasibility of the proposed direct abort orbit design method. Finally, extensive simulations are carried out to analyze the characteristics of abort impulse and abort return time and reveal the general rules of direct abort orbits. The research conclusions can provide a reference for the design of emergency rescue schemes in future crewed lunar exploration missions.
Numerical Investigation of Contact Burning in an Air-Breathing Continuous Rotating Detonation Engine
Three-dimensional (3D) numerical simulations of a continuous rotating detonation engine are carried out with an unsteady Reynolds-averaged Navier-Stokes solver. The second-order upwind advection upstream splitting method and second-order Runge-Kutta method are used to discretize space and time terms, and detailed 9-species 19-step hydrogen-oxygen reactions are applied in this study. Nonpremixed rotating detonation is successfully realized numerically, and the characteristics of the detonation wave are revealed. The expanding angle of the combustor has a great impact on the shape of the detonation wave but has little influence on the propagation velocity. The evolution of combustion on the contact region is analyzed in detail; a more accurate schematic of non-premixed air-breathing rotating detonation engines is given in this paper. A rough analysis of the heat performance of the contact region shows that the heat release of the contact region is approximately one-third of the total heat release and the configurations of the combustors do not affect the proportion.
Effects of the Air Inlet Angle on the Combustion and Ablation Environment of a Hybrid Powder-Solid Ramjet
A hybrid powder-solid ramjet (HPSR) that combined the advantages of a solid rocket ramjet (SRJ) and a powder ramjet engine was investigated in this research. To improve the combustion efficiency and optimize the inner wall thermal protection of the afterburner, the effects of the air inlet angle on the combustion and wall ablation environment were studied. The standard - model, the eddy-dissipation model (EDM), and the boron particle ignition and combustion model were adopted to simulate the two-phase flow in the afterburners with different air inlet angles (45°, 60°, 75°, and 90°). The results showed that the global flow field and the distribution of the vortexes in the afterburner that had a significant influence on the ablation environment of the inner wall and the combustion efficiency were determined by the impact effect and the squeezing effect of the ram air on the primary fuel gas, which was affected by the air inlet angle. As the air inlet angle increased, the total combustion efficiency of the four cases first increased and then decreased, reaching 80.38%, 81.64%, 84.34%, and 83.26% for angles of 45°, 60°, 75°, and 90°, respectively. At the same time, the inner wall ablation became more severe because both the erosion effect of the condensed phase particles and the gas-flow scouring effect were enhanced, and a large temperature gradient was generated on the inner wall. The study results can provide a reference for designing the air inlet angle of an HPSR.
Robust Data-Driven Fault Detection: An Application to Aircraft Air Data Sensors
Fault detection (FD) is important for health monitoring and safe operation of dynamical systems. Previous studies use model-based approaches which are sensitive to system specifics, attenuating the robustness. Data-driven methods have claimed accurate performances which scale well to different cases, but the algorithmic structures and enclosed operations are “black,” jeopardizing its robustness. To address these issues, exemplifying the FD problem of aircraft air data sensors, we explore to develop a robust (accurate, scalable, explainable, and interpretable) FD scheme using a typical data-driven method, i.e., deep neural networks (DNN). To guarantee the scalability, aircraft inertial reference unit measurements are adopted as equivalent inputs to the DNN, and a database associated with 6 different aircraft/flight conditions is constructed. Convolutional neural networks (CNN) and long-short time memory (LSTM) blocks are used in the DNN scheme for accurate FD performances. To enhance robustness of the DNN, we also develop two new concepts: “large structure” which corresponds to the parameters that can be objectively optimized (e.g., CNN kernel size) via certain metrics (e.g., accuracy) and “small structure” that conveys subjective understanding of humans (e.g., class activation mapping in CNN) within a certain context (e.g., object detection). We illustrate the optimization process we adopted in devising the DNN large structure, which yields accurate (90%) and scalable (24 diverse cases) performances. We also interpret the DNN small structure via class activation mapping, which yields promising results and solidifies the robustness of DNN. Lessons and experiences we learned are also summarized in the paper, which we believe is instructive for addressing the FD problems in other similar fields.
Receding Horizon Control with Extended Solution for UAV Path Planning
The receding horizon control (RHC) greatly reduces the planning time and achieves great success in UAV online path planning because of rolling window optimization. However, due to its small range of path search in the time window, UAVs cannot cope with environments with uncertain obstacles and multiple flight constraints. Therefore, the receding horizon control with extended solution (RHC-eS) method is proposed for UAV path planning based on the traditional RHC. This method first designs the path expansion mechanism, which not only expands the search range of feasible solutions but also ensures the real-time performance by the two-way search strategy. Secondly, in order to increase the richness of solutions, the crossover and directional variation strategy of Genetic Algorithm (GA) are integrated. Finally, the Sequential Quadratic Programming (SQP) method is used to optimize the objective function. The simulation results of UAV path planning in simple and complex environments certify that the proposed method can obtain shorter, safer, and smoother paths compared with the existing methods.