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With the continuous development of information technology, distributed database has become a research hotspot. Due to the limit support for SQL and defects in transaction processing and consistency of distributed databases based on NoSQL architecture, NewSQL databases based on LSM-Tree become gradually the mainstream of applications, such as TiDB and OceanBase. The distributed LSM-Tree storage architecture divides the data into baseline data and incremental data. Through the compaction operation, the incremental data of different partitions and the baseline data are continuously merged and stored on the disk, thereby reducing memory pressure. However, compaction will occupy a large amount of system resources and seriously affect system availability. This paper proposes an asynchronous compaction mechanism based on LSM-Tree architecture. By subdividing the compaction process, the data merging is asynchronous, which effectively shortens the time for a single compaction operation. Experiments show that the asynchronous compaction mechanism proposed in this paper can significantly shorten the data merging time and improve the robustness and usability of the system in high-frequency writing scenarios.

The existing deep reinforced learning algorithms cannot see local environments and have insufficient perceptual information on UAV autonomous navigation tasks. The paper investigates the UAV's autonomous navigation tasks in its unknown environments based on the nondeterministic policy soft actor-critic (SAC) reinforced learning model. Specifically, the paper proposes a policy network based on a memory enhancement mechanism, which integrates the historical memory information processing with current observations to extract the temporal dependency of the statements so as to enhance the state estimation ability under locally observable conditions and avoid the learning algorithm from falling into a locally optimal solution. In addition, a non-sparse reward function is designed to reduce the challenge of the reinforced learning strategy to converge under sparse reward conditions. Finally, several complex scenarios are trained and validated in the Airsim+UE4 simulation platform. The experimental results show that the proposed method has a navigation success rate 10% higher than that of the benchmark algorithm and that the average flight distance is 21% shorter, which effectively enhances the stability and convergence of the UAV autonomous navigation algorithm.

With the refinement of civil aircraft technology and the enhancement of product complexity, civil aircraft design has changed from traditional text-based system engineering to model-based system engineering, the expression of the system has also transformed from text-centered to model-centered. To further improve the model quality and correctness of aircraft system modeling, this paper explores the applicability of model-driven and verification-oriented system engineering methods in the field of civil aircraft design, and establishes the system engineering practice framework of civil aircraft design, which can ensure the rapid design and efficient delivery of civil aircraft. Firstly, starting from the Harmony SE modeling method, the workflow and modeling ideas of system are introduced; then the noticeable problems in the practice of civil aircraft system engineering are analyzed, and the system engineering practice of civil aircraft design is established with the support of the applicability of the Harmony SE method; finally, the fuel tank pressurization component is taken as the research object of the practice system in component-level. The results show that the system engineering practice framework of civil aircraft design and method proposed in this paper can correctly and reasonably allocate design requirements and establish a complete system model, which is helpful to improve the efficiency and accuracy of civil aircraft design at this stage.

Compared with the traditional source radiated power estimation method, the matched-field source radiated power estimation method can obtain more accurate estimation results. However, its performance is greatly influenced by environmental mismatch. This paper defines the impact factor of environmental mismatch to quantify the impact of environmental mismatch on the acoustic transfer function and the matched-field source radiated power estimation method. It determines that the key to improve the robustness of environmental mismatch is to accurately estimate the acoustic transfer function. In the traditional matched-field source radiated power estimation method, the search domain of the acoustic transfer function is a distance-depth two-dimensional plane and does not contain the true acoustic transfer function when the environment is mismatched. Therefore, the estimation results of the acoustic transfer function are bound to deviate from those of the true acoustic transfer function. The paper expands the search domain dimension to a three-dimensional search domain that contains distance, depth and uncertain parameter sets. The true acoustic transfer function is included in the search domain. Thus the optimal alternative acoustic transfer function is equal to the true acoustic transfer function. The objective function for the three-dimensional search domain is constructed. The smaller the absolute value of the objective function, the less the acoustic transfer function estimation deviates from the true acoustic transfer function. The source radiated power is estimated more accurately when the alternative acoustic transfer function estimation corresponding to the minimum absolute value of the objective function. The simulation results verify the theoretical analysis results.

The replenishment of water resources in a space station is essential for achieving an astronaut's long-term and on-orbit residence. Recycling his or her urine is one of important and major ways of wastewater recovery. However, traditional urine treatment methods have the disadvantages of equipment that takes large space, complex procedures and low atomic utilization. Therefore, this paper designs a novel wastewater reuse system that treats urine based on urea electrooxidation technology, introduces methane fuel cell coupled with the Sabatier reactor and hydrogen-oxygen fuel cell to further utilize urine treatment products and to allocate water resources precisely in the space station through designing grading treatment and dynamic control systems. The wastewater reuse system designed in the paper contributes to saving valuable space and reducing energy consumption during urine treatment, thus improving water recovery rate and optimizing resource allocation.

This paper proposes the use of aperture sharing synergistic operation in the structure of the metalens, together with the rational selection of the scattering unit size according to the linear relationship between the output phase and frequency of the scattering unit, and the selection of the slope of the phase variation with frequency, combined with the modulation of the phase change material Ge2Sb2Te5 crystallization rate m value, in the set wavelength band, for different wavelengths of incident light through the metasurface can produce a uniform phase distribution. The method is used to achieve a polarization-insensitive achromatic metalens in the 9.5-13 μm continuous wavelength band by adjusting the m value of the phase transition material Ge2Sb2Te5 crystallization rate and producing a phase distribution with a uniform focal length for different wavelengths of incident light passing through the metasurface. The simulation results show that the focal length of the achromatic metasurface varies by 3.57 μm in the working band, with an error of about 4.3% from the set focal length, and the full width of the half-peak of the focal point at all wavelengths of incidence reaches the diffraction limit, and the focusing efficiency exceeds 60%. The achromatic metalens proposed in this paper provides a new idea for the design of achromatic metasurfaces and promotes the research of phase change materials in broadband achromatic metasurfaces.

The precise detection of military targets under complex conditions is a key factor to enhance the ability of war situation generation and prediction. The current technology can not overcome the problems of smoke and occlusion interference, target height change, and different scales in aerial video. In this paper, a multi feature cross fusion and cross layer cascade aerial military target detection algorithm (YOLOv5-MFLC) is proposed. Firstly, aiming at the high confidentiality of the military targets and the shortage of battlefield aerial image resources, a real scene based aerial military target dataset is constructed, and the methods of random splicing and random extraction embedding are used for data enhancement in order to improve the diversity and generalization of targets. Secondly, aiming at the problem of complex background interference, a multi feature cross fusion attention mechanism is constructed to enhance the available information of target features. Finally, for the multi-scale problem of targets in aerial images, a cross layer cascaded multi-scale feature fusion pyramid is designed to improve the detection accuracy of cross scale targets. The experimental results show that, comparing with the existing advanced detection models, the detection accuracy of the algorithm in this paper has been greatly improved. The average accuracy of the algorithm can reach 81.0%, which is 5.2% higher than the original network. In particular, it has reached 55.9% in the smaller target category "person", which is 9.4% higher. And the experimental results further show the usefulness of the improved algorithm for small target detection. At the same time, the detection rate of this algorithm can reach 56 frame/s, which can effectively achieve accurate and fast detection of battlefield targets, and has certain experience value for guiding complex modern wars.

With the increase of satellite power, the current-carrying and heat dissipation of power cable is increasing significantly and the thermal safety problem becomes prominent. Therefore, the need for accurate modeling and fine design of power cable becomes increasingly urgent. In this paper, the thermal analysis modeling method for high-power cable bundle is proposed based on ground test data, and the heat transfer parameters at the installation and bundling points are obtained. At the same time, the thermal effect of cable bundling is quantitatively analyzed by simulating the splitting and binding power cable bundle. The result indicates that enhancing the radiation heat transfer between cables and the surrounding environment is the most effective means to improve the heat dissipation condition of cable bundles. The thermal model of high-power satellite power cable proposed in this paper can be used as an important basis for the prediction of on-orbit temperature and fine laying design of the power cable.

In the large-scale satellite constellation technology, the establishment of satellite internal network is the top priority. As the network capacity of the constellation continues to expand and the number of satellite nodes continues to increase, the previous multiple access technology can no longer meet the network capacity requirements of large-scale constellations. In order to meet the requirements of massive connections of satellite nodes in large-scale constellation for new networking communication methods, this paper establishes a sparse spread spectrum inter-satellite communication system with sparse code multiple access (SCMA) as the core. At the same time, the channel characteristics of large-scale constellation are analyzed and the corresponding inter satellite channel model is established in MATLAB. Based on this channel model, the performance of the system is simulated. The simulation results show that under the same signal energy to noise ratio, the sparse spread spectrum inter-satellite communication system established in this paper has better BER characteristics compared with orthogonal frequency division multiple access (OFDMA) and code division multiple access (CDMA). In addition, the threshold signal energy to noise ratio of the system is more than 2 dB better than that of CDMA technology, and the utilization rate of time-frequency resources is 50% higher than that of OFDMA technology.

Accurate and fast random error estimation is essential to improve satellite control. In this paper, the random error of the satellite being launched into orbit is explored. According to the uncertainty matrix of six satellite orbit parameters associated with the project, the uncertainty of the orbit position in the three axes of the geocentric inertial frame of reference is calculated via the propagation rate of the covariance matrix. Then, the random error probability density of the satellite position is constructed for normal distribution. The surface of the error with the same probability density is approximated as an ellipsoid, the size is deduced along with the ellipsoid's shape and direction, and the satellite's spatial position probability is obtained. Monte Carlo method and STK software were employed to simulate low-earth orbit micro-nano satellite launching into the same orbital position. It is confirmed that the results obtained via the theoretical model are in line with practice. Therefore, the ellipsoid theory proposed in this paper can be used to describe the satellite random position error.

To effectively monitor the operation state of landing gear, a back propagation neural network-based on multi-strategy cooperative optimization(MSCO-BPNN) is proposed. The multi-strategy optimization algorithm is composed of chaotic mapping strategy, adaptive spiral capture strategy, crossover mutation strategy and whale optimization algorithm(WOA). WOA is applied to find the optimal hyperparameters of back propagation neural network(BPNN). The search efficiency, multi-local search ability and global search performance of model can be improved by using chaotic mapping strategy, adaptive spiral capture strategy and crossover mutation strategy. The BPNN with optimal hyperparameters is introduced to establish the implicit model of input parameters and output responses. Based on quick access recorder(QAR) data, landing gear left side brake temperature is act as the monitoring objective of this paper. The validity and applicability of MSCO-BPNN are verified by compared with WOA-BPNN, particle swarm optimization BPNN and traditional BPNN. The results show that MSCO-BPNN can monitor the operation status of landing gear with high efficiency and accuracy. The efforts of this paper provide a promising insight for the precise condition monitoring of complex structures.

Considering the drag-divergence performance as a constraint, this paper presents a multi-point aero-structural design optimization of wings on a wing-body-tail-engine configuration of long-range dual-aisle civil aircraft by using a gradient-based method based on the discrete adjoint method. Firstly, the accuracy of the coupled aero-structural analysis method used in this paper was validated with DLR-F6 wing-body configuration. Then a wing aero-structural design optimization based on a dual-aisle civil aircraft is offered. The drag coefficient of the optimized configuration in every state decreased, which was reduced by 13.67 counts at the cruise condition, the difference in drag coefficient from Mach 0.85 to Mach 0.87 was decreased from 28.52 counts to 18.98 counts, indicating its drag-divergence performance has been improved undoubtedly. Finally, we compared the performance among the multi-point aero-structural optimized configuration, the single-point aerodynamic optimized configuration and the single-point structural optimized configuration. The results show that the multi-point aero-structural design optimization considering drag-divergence performance has great potential to gain a design configuration with better comprehensive and practical performance compared with a single-point optimization in a single discipline.

This paper studies several problems that may exist in the aerodynamic design of low Mach number general aircraft, and discusses the design characteristics of the pressure distribution of some related airfoils while part of the characteristics is verified by a multi-point laminar airfoil design case. Firstly, several issues which exist in the aerodynamic design of low Mach number general aircraft, such as relatively large zero-lift drag coefficient, high stall performance requirements, and large variation range of Reynolds number, are discussed and analyzed. Then, to address these issues, the paper extracts some useful design features that are beneficial to the airfoil aerodynamic performance from the study on the design characteristics of the pressure distribution of several turbulent flow airfoils and laminar flow airfoils that are designed for low Mach number general aircraft. Finally, by considering the typical design conditions of a light multi-purpose single-turboprop-engine general aircraft, including the cruise, climb and stall conditions, a multi-point laminar airfoil optimization is offered by using the GAW-1 airfoil as the baseline. The optimized foil has a 9.6 improvement in the lift-to-drag ratio of the cruise condition, a 16.3 improvement in the lift-to-drag ratio of the climb condition but a 0.115 decrease in the maximum lift coefficient of the stall condition. The results show that the requirements from the cruise, climb and stall conditions are contradictory to some degree in the considering multi-point optimization case, and the designers should deal with this trade-off carefully based on the features of the low Mach number general aircraft.

To address the issue of low brightness, high noise and obscure details of UAV aerial low-light images, this paper proposes an UAV aerial low-light image enhancement algorithm based on dual-path inspired by the dual-path model in human vision system. Firstly, a U-Net network based on residual element is constructed to decompose UAV aerial low-light image into structural path and detail path. Then, an improved generative adversarial network (GAN) is proposed to enhance the structural path, and edge enhancement module is added to enhance the edge information of the image. Secondly, the noise suppression strategy is adopted in detail path to reduce the influence of noise on image. Finally, the output of the two paths is fused to obtain the enhanced image. The experimental results show that the proposed algorithm visually improves the brightness and detail information of the image, and the objective evaluation index is better than the other comparison algorithms. In addition, this paper also verifies the influence of the proposed algorithm on the target detection algorithm under low illumination conditions, and the experimental results show that the proposed algorithm can effectively improve the performance of the target detection algorithm.

Aiming at the problems existing in the current mechanisms of delay guarantee in wireless networks(i.e. poor scalability, coarse granularity for provided service levels, and improving delay performance at the expense of sacrificing some resource utilization), this paper puts forward both the idea of particle access and the corresponding access mechanism. In this paper, a traffic flow is modeled as a group of information particles that carry a certain amount of information and are valid for certain periods of time. Firstly, the definitions of information particles and the group of information particles are given. It is proved that the minimum reachable access bandwidth of an information particle group can be achieved by using the EDF(earliest deadline first) transmission strategy. Moreover, a fine-grained mechanism of delay guarantee based on the idea of particle access is proposed for the dynamic access environment in wireless networks. Extensive simulations are carried out for the application scenario of downlink transmissions, and it is shown that, in the case of heavy traffic loads, comparing with the rapid growth of the average packet delays and the packet loss rates in a legacy access mechanism, the proposed fine-grained access strategy based on the idea of particle access can also achieve the better performance on the average packet delays and the packet loss rates, and hence higher effective throughput is obtained. The research in this paper pave a new way for further improving quality of service (QoS) mechanisms of wireless networks.

Sector partition is an important task of air traffic control, and a reasonable sector partition can improve the utilization rate of airspace and protect the flight safety of aircrafts. Since the sector partition during flat hours is not well suited to the complex air situation, this paper proposes a sector optimization method based on Voronoi diagram and improved K-means. Firstly, a conflict network is constructed based on the air situation, and a comprehensive sector control workload measurement method is proposed by combining aircraft velocity obstacle relationship and complex network theory. Based on the workload value, a cluster center is determined as the generating element of Voronoi diagram by using the improved K-means method, and then the sector is optimized by using the division method of Voronoi diagram. In this paper, the data of Xiamen airspace control sectors are collected as a simulation scenario for calculation and analysis. The simulation results show that the average variance of the optimized sector control workload is reduced by 66.04% during the peak hours and 13.88% during the flat hours compared with the original sector. The method achieves the purpose of balancing the sector workload, verifies the effectiveness of the sector optimization method, and provides a reference basis for the existing sector partition work.

In order to reduce the probability of human error in the cockpit of a civil aircraft, based on the SHEL model, this paper classifies performance shaping factors (PSF) that affect the human factor reliability of the human-machine interface. Then it constructs the relevant PSF system and uses the interpretation structure model to establish the corresponding adjacency matrix. When a multi-level recursive structure is obtained, the Noisy-OR model is introduced to construct the Bayesian network, thus establishing the new human-machine interface evaluation method. Real cases are used to verify the effectiveness of the method thus established through causal inference with the Bayesian network. The evaluation method for the reliability of a set of human factors this paper proposes provides a new approach to evaluating the human-machine interface in the cockpit of a civil aircraft.

The transition state is the most critical and dangerous state of the VTOL fixed wing aircraft in the whole flight process. In this paper, a transition corridor for a distributed propulsion VTOL fixed-wing aircraft is studied based on the lift characteristics of the wing and the power constraints of the power unit. Firstly, according to the sliding flow theory, the dynamic characteristics models of the lift fan system in the front part of the fuselage and the distributed duct system in the rear part of the fuselage were established by introducing the influence factor of the duct, and verified with the test data. Secondly, according to the lift characteristics of the wing, the transition curves of the aircraft at different angles of attack are calculated, in which the transition curves corresponding to the zero-lift attack angle and stall attack angle constitute the lift characteristics transition corridor of the distributed propulsion VTOL fixed-wing aircraft. Finally based on the dynamic performance of the power unit model, calculate the lift characteristic transition each state point in corridor corresponding power demand, according to the power limit of the lift fan system, distributed duct system and power unit total power limitation, get distributed to promote vertical take-off and landing a fixed wing aircraft power limitation in lifting features and power unit under the condition of complete transition corridor. The final results show that the minimum forward velocity is inversely proportional to the attack angle. The power required by the tail distributed duct system will exceed the limit when the aircraft is in low speed and small dip angle transition. For the power limit boundary required, the power limit condition of individual component is stricter than the total power limit condition. The research results of this paper can provide some reference for the transition corridor research of such VTOL fixed-wing aircraft, and on this basis, the subsequent work such as parameter sensitivity analysis and control system design of transition corridor can be carried out.

A solar-powered UAV usually has a high-aspect-ratio and flexible structural design. Its aerodynamic and mass characteristics are different from those of a conventional aircraft. This paper compares the differences in lateral aerodynamic data with those of Class I and Class III aircrafts. Based on the rigid-body dynamics theory, the effects of flexible wing deformation on the stability of the UAV are analyzed. Then, by combining the structural deformation, inertia variation and aerodynamic derivative, the solar-powered UAV's lateral stability is analyzed based on the root locus method. The variation of eigenvalues with wing deformation is also investigated. The rolling moment equation is combined with the kinematic equation to reveal the roll attitude limitation envelope constrained by the kinematic coupling and aileron effects. Taking into account the aerodynamic characteristics of the solar-powered UAV, its wing deformation and roll attitude limitation problem, this paper proposes an adaptive back-stepping control method with strong robustness to achieve the accurate control of the roll attitude of the solar-powered UAV.

The severe attenuation and scattering of light in the water reduces the effective field of view of the underwater camera, making the scene information contained in a single image limited, and it is difficult to meet the application requirements of the large-scale underwater scenes. To solve this problem, an underwater multi-frame target images mosaic method based on adaptive image enhancement is proposed in this paper. Firstly, the image blur prior is used to achieve the adaptive enhancement of underwater images to suppress the blur and colour distortion of underwater images. Then, the feature point matching method based on the improved SURF realizes the extraction and matching of the feature points of underwater multi-frame target images. Finally, combining with the fusion strategy of gradual in and out, the seamless splicing and fusion of underwater multi-frame target images is realized. The pool and shallow sea tests were carried out respectively, and the results show that the method proposed in this paper increases the number of effective feature point matching and improves the splicing effect.

Due to the space limitation of the launching platform, the wings of the space-based gravity delivery UAV need to be folded before launching. In the process of wing folding and launching, the dynamics model of UAV will show the characteristics of multiple rigid bodies and multiple degrees of freedom, and the aerodynamic characteristics of UAV are also quite different from that of cruise stage, so the traditional aircraft dynamics modeling method is no longer applicable. In this paper, the multibody dynamics model of gravitational airdrop UAV is first built based on the Lagrange equation, and then according to the aerodynamic change on unmanned aerial vehicle in deploying process, the angle between the wing and the fuselage is introduced as a new variable, the UAV launch phase nonlinear aerodynamic model is established, and through comparison with software calculation results the reliability of the aerodynamic model is verified. Based on the aerodynamic model and dynamics model, the dynamic response of UAV deployment process is simulated, and the influence of UAV deployment process on UAV subsequent pulling stage under the same control instructions is compared, and the dynamics and kinematics characteristics of gravity launch are studied and explored. Finally, the simulation results are compared with the experimental data, indicating that the multi-body dynamic model established in this paper can accurately describe the dynamic response of UAV in the launching stage and the subsequent modification stage, which can provide reference for the technical personnel engaged in the design, test and use of related models.

Morphing aircraft can flexibly change its aerodynamic shape to adapt to the varying flight conditions during a flight. Compared with the traditional fixed shape aircraft, it has a very obvious advantage. This paper proposed a solution flow based on the multi-fidelity model for the morphing aircraft with morphing wings, and the optimal trajectory and morphing rules are studied. The angle of attack, Mach number, sweep angle and axial position of the morphing wing are defined as variables for generating training data for building the multi-fidelity Kriging model, which is used to predict the aerodynamic performance of the aircraft. Based on the hp-adaptive pseudospectral method, the model is used as aerodynamic input to establish the optimization process of morphing rules, and the trajectory optimization is carried out for the contrast fixed wing aircraft and morphing aircraft with the goal of minimum fuel consumption, respectively. The control parameters such as morphing parameters, angle of attack and engine control parameters are optimized simultaneously while meeting the flight mission requirements. The results show that the morphing aircraft has higher climbing and descending efficiency, and the optimal trajectory has obvious advantages. Moreover, the research flow proposed in this paper is universal, which can effectively reduce the CFD calculation cost and improve the efficiency of trajectory optimization of the variable shape vehicle.

In order to study the problem that the array manifold of conformal arrays deviates from the ideal value due to the sound scattering caused by the rigid baffles of arrays, in this paper, the influence of the scattering phenomenon caused by the rigid baffle on the receiving response of array is analyzed by using sound field prediction method based on a conformal array-semi-cylindrical volume array. The sound field distribution of conformal array at different angles is calculated by using the sound field modeling and simulation. Based on the above distribution, an actual array manifold is constructed under consideration of rigid barrier, and its variation under the influence of scattered sound is analyzed. The variation is described by two physical quantities defined in this paper: the first-order response composed of amplitude and phase and the second-order response composed of cross-correlation. Simulation shows that compared with the ideal model, the scattered signals generated by rigid baffles on conformal array varies with the azimuth and signal-to-noise ratio(SNR), which further leads to the deviation of each hydrophone of conformal array. The experimental data verifies that the simulation results are basically consistent with the actual situation. The effect of the scattering on the conformal array should be considered when designing and performing in practice.

Aiming at the low exploration level, slow speed and repeated exploration of UAVs in unknown environments, this paper improves the selection of boundary points based on the boundary driving method, and proposes a method suitable for UAVs to quickly explore in unknown environments. Planning method: while using the depth image (RGBD) sensor to receive environmental information, the octree map of the known environment is constructed in real time, and the common indoor environment is divided into six local environmental types. The drone observes according to the RGBD camera on board. The local environment type generates instantaneous speed commands, and designs composite boundary points, from which the point with the largest information gain and the smallest yaw angle is weighed as the boundary guide point. Finally, a simulation experiment was carried out and comparing with the existing methods. The time required to explore the apartment environment in the next best viewpoint (NBV) in Document with the present method is 68.7% less than the exploration time in the paper. In addition, this paper designs There are four types of environments. In these environments, the present method reduces the average exploration time by 97.1% comparing with the method in Document. The experimental results show that the present method can effectively improve the exploration efficiency and has strong feasibility.

This paper studied the trajectory tracking control of a failure satellite that has actuator jumping fault. It proposed a design method based on the jumping control input for the model reference tracking controller. By comb-ining the stochastic stability definition with model reference tracking, it gave the mathematical descriptions of the trajectory tracking control of the failure satellite. It used the linear matrix inequality method and the parametric solution method of the nonhomogeneous generalized Sylvester matrix equation to design the robust H∞ state feedback control law and the complete parametric feed-forward tracking compensator respectively, with the disturbance of the failure satellite and its thrust constraint considered simultaneously. The numerical simulation results on the model of the satellite rendezvous system show that the design method proposed in this paper is effective.

To improve the efficiency of the composite material wing structure of a solar-powered UAV, this paper proposed an efficient discrete structural topological optimization method based on the notion of bionic design. The method considers the features of such wing structures as discrete stiffness, high aspect ratio and ultralight. Through multi-step optimization, the grid relationship of the base structure method is established with the GRAND method, so as to obtain the design space of discrete topological optimization. First, linear programming is used to solve optimization problems and thus gives the topological relations of a wing structure. Then, by extracting the information on node dimensions of the discrete topological structure, a bionic geometric model is established with the notion of bionic design. In order to obtain the optimal topological form of the bionic surface grid structure of the wing, the finite element analysis and the structural dimension optimization are carried out with the parameterization method. On the condition that design requirements are satisfied, the optimization reduces the weight of the wing by 34.4%, compared with the traditional design methods. Results show that the structural optimization method proposed in the paper is effective for this special composite material wing structure and can be used for the lightweight design of similar structures.

In order to enhance the global asymptotic stability of the system in sliding mode control for permanent magnet synchronous motor (PMSM), a nonsingular terminal sliding mode speed loop controller based on nonlinear sliding mode surface is designed in this paper, which ensures the finite-time convergence and improves the steady state precision of the system. Meanwhile, it avoids the singularity problem and reduces the chattering problem of the system. In order to improve the anti-interference ability and control precision of the system, a new disturbance observer is designed, which feeds the observed values back to the speed controller. Aiming at the safety and reliability of the position sensor, a sliding mode position observer is also designed which enable the real-time, fast and accurate tracking of the position signal to be realized. The simulation results show that the control strategy proposed in this paper can effectively improve the control precision and response speed of the system, and enhance the anti-interference ability of the PMSM control system.

In order to study the aerodynamic interaction of the airfoil and jet flow, the free streamline model and the panel method are combined to establish a calculation method for the aerodynamic characteristics of the airfoil in a two-dimensional inviscid jet flow. Using the assumption of constant total pressure difference and free streamline model to determine the vortex strength and position of the jet boundary, the aerodynamic force of the airfoil is solved by the vortex panel method, and the whole process is calculated by relaxation iteration. Firstly, the relevant theory in this paper is introduced, and the convergence and effectiveness of the present method are also tested. Next, the influence of the position and the ratio of jet height to airfoil chord on airfoil aerodynamics in the jet flow are studied. Finally, the momentum theory is used to analyze the aerodynamic characteristics of the airfoil in the jet flow. The results show that the aerodynamic characteristics of the airfoil in the jet flow is quite different from that in the freestream. When the jet flow is deflected, the airfoil will not only generate lift but also drag. The method in this paper can be used to study the aerodynamic characteristics of the airfoil immersed in the jet flow.

Parafoil is an important novel method to realize the precise recovery of sub-stage booster of rocket. In this paper, a parafoil optimal path planning algorithm based on longicorn algorithm is proposed to solve the problems that the parafoil is easily affected by wind field and the error of landing point is large in the recovery of sub-stage booster of rocket. Firstly, according to the dynamics and kinematics equations of the parafoil and a rocket sub-stage combined system, a 6-degree-of-freedom model of the system was established to analyze the effects of different downward deviation on the forward velocity, vertical velocity and the trajectory planning of the parafoil during the homing process of the rocket sub-stage. On this basis, the number of circling turns, radius and azimuth of the cutting-high section of the combination of the parafoil and the sub-stage booster were taken as the optimal parameters, and the optimal path planning was carried out by using the longicorn algorithm. Finally, a homing path with comprehensive consideration of energy and the accuracy of the landing point was obtained. The simulation results show that the piecewise optimal flight path planning algorithm based on longicorn algorithm proposed in this paper has fast convergence speed and high precision of flight track landing point.

The paper studies the formed body after completing its autonomous formation task and then proposes a self-healing method that flexibly scales with the scale of the loss in the situation that a large-scale swarm robot is locally missing due to external disturbances. With the stratified mechanism that includes layer-by-layer separation, layer-by-layer filling and iteration loop, the macro-level behavior of a swarm robot is transformed to the local action of an individual robot within the edge layers of the current aggregate. Based on the existing formation technique, driven by the shape genes of the formed body and the changes in the scale of population, the self-healing goal of the large scale of population is transformed into the similar scale of the formed body after scaling. Through the self-healing movement control method centered on individual behavior rules, the bottom-up self-healing configuration is presented on a scaled scale. The paper verifies the feasibility and scalability of this novel method through simulations. The maximum number of robots can reach tens of thousands. Finally, the self-healing method is used to implement the Cilibot robot, a hardware system developed by our laboratory.

FLS approach is an effective means to improve approach perception and reduce operational risk, and it is one of the key functions of flight management system of advanced commercial aircraft. This paper studies the generating virtual beam, calculating beam deviation and guidance command in FLS advanced approach guidance technology, and proposes a method of generating virtual beam based on navigation database information and a method of calculating beam deviation based on spatial geometric relationship. The guidance law was constructed based on angle deviation and lateral distance between the actual path and FLS beam, and the simulation test examle was designed to verity the deviation and guidance command calculation algorithm. The simulation results show that the FLS guidance algorithm proposed in this paper can achieve high-accuracy approach guidance.

Special scene classification and identification tasks are not easily fulfilled to obtain samples, which results in a shortage of samples. The focus of current researches lies in how to use source domain data (or auxiliary domain data) to build domain adaption transfer learning models and to improve the classification accuracy and performance of small sample machine learning in these special and difficult scenes. In this paper, a model of deep convolution and Grassmann manifold embedded selective pseudo-labeling algorithm (DC-GMESPL) is proposed to enable transfer learning classifications among multiple small sample datasets. Firstly, DC-GMESPL algorithm uses satellite remote sensing image sample data as the source domain to extract the smoke features simultaneously from both the source domain and the target domain based on the Resnet50 deep transfer network. This is done for such special scene of the target domain as the lack of local sample data for forest fire smoke video images. Secondly, DC-GMESPL algorithm makes the source domain feature distribution aligned with the target domain feature distribution. The distance between the source domain and the target domain feature distribution is minimized by removing the correlation between the source domain features and re-correlation with the target domain. And then the target domain data is pseudo-labeled by selective pseudo-labeling algorithm in Grassmann manifold space. Finally, a trainable model is constructed to complete the transfer classification between small sample datasets. The model of this paper is evaluated by transfer learning between satellite remote sensing image and video image datasets. Experiments show that DC-GMESPL transfer accuracy is higher than DC-CMEDA, Easy TL, CMMS and SPL respectively. Compared with our former DC-CMEDA, the transfer accuracy of our new DC-GMESPL algorithm has been further improved. The transfer accuracy of DC-GMESPL from satellite remote sensing image to video image has been improved by 0.50%, the transfer accuracy from video image to satellite remote sensing image has been improved by 8.50% and then, the performance has been greatly improved.

The similar scale model experiment can provide some reference for the research and development of naval gun weapons. This paper takes the naval gun bracket as an example to explain. Based on the dimensional analysis, equation analysis and finite element method, the modal parameter similarity relationship between the original model for bracket and the shrinkage ratio model is established. The results show that the error of predicting the natural frequency of the original model based on similarity relation is less than 2% comparing with the results of finite element numerical simulation, and the error is less than 10% comparing with the experimental results, and the mode of shrinkage model is close to that of the original model. It is proved that the theoretical method in this paper is feasible and practical in engineering. Therefore, the vibration characteristics of the original model can be estimated by analyzing the vibration characteristics of the carrier shrinkage ratio model, which provides a reference for ship gun designers.

This paper established the three-dimensional edge-based smoothed finite element method(ES-FEM) based on polyhedral mesh, divided the smoothed domain, constructed the shape function and derived the geometric matrix and the stiffness matrix. The MATLAB software was used to prepare the corresponding computing programs, with which the paper studied the stress distribution of a hollow sphere model and a beam model under different numbers of polyhedral elements. The paper compared the calculation results from the conventional finite element methods(FEM) that use tetrahedral elements and hexahedral elements respectively in terms of stress relative error and energy relative error. The comparison results show that the three-dimensional ES-FEM based on polyhedral mesh has better precision and convergence than the conventional FEM and better adaptability to complex geometric structures.

The accurate description of acoustic emission signals produced by the localized fault of a rolling element bearing plays an important role in its feature extraction and analysis. This paper analyzes the excitation mechanisms and develops the analytical model of acoustic emission signals produced when the rolling element bearing passes across the localized fault on the inner or outer race. Based on the analytical model, the spectral characteristics are discussed substantially. Simulations and experiments are carried out to validate the efficacy of the model developed in the paper. The experimental results show that the response signal thus produced has two parts. The first one is produced by the entry of the rolling element bearing, while the other is produced by the departure of the rolling element bearing. The energy of both parts is concentrated around the resonance frequency of the acoustic emission transducer. Generally, the interval of adjacent acoustic emission events is not equivalent to each other and the corresponding spectrum is continuous in the high frequency band.

Autonomous underwater vehicle will be subjected to a huge impact load during high speed water entry, which will damage the structure and the internal instruments of the vehicle. Therefore, it is of great significance to study the buffer mechanism of the vehicle during the process of water-entry. In this paper, a kind of head-jetting device with disk cavitation is used. The complex cavitation forms, under the three-phase coupling of gas, liquid and solid, in the water entry process of the vehicle on which the device is installed. In this paper, the numerical simulation of high-speed water entry of the vehicle equipped with head jet device is carried out. Through the analysis of water entry cavitation under typical working conditions, the following conclusions are obtained. After the installation of head jet device, the water entry cavity of the vehicle changes gradually from cone to spindle shape. The air jet, compared with that without jet, can promote the formation of water inlet supercavitation, decrease the interaction area between the vehicle and water, and reduce the impact load during water entry. At the same water entry depth, the diameter of cavitation increases with the amount of air jet. The water entry velocity has a great influence on the difference of cavitation shape. The water entry depth closure phenomenon, when the water entry velocity is less than 100 m/s, can be observed in the depth of 3.5 times of the projectile length. The water entry angle has a significant effect on the cavitation shape. The cavity shows obvious asymmetry when the vehicle slants into the water, and the diameter and length of the bubbles decrease with the increase of the water entry angle. The research content of this paper provides technical support for the engineering practice of high-speed water entry and load reduction, and the conclusions are of great significance in related fields.

Arc-heated facilties play an important role in ground tests, such as appraisal of thermal protection systems(TPS) of various hypersonic vehicles and simulation of a high Mach scramjet's thermal structure and combustion chamber performance. This paper analyzes the requirements for developing a high power arc heater. Key technologies for developing it include high power, high voltage, high enthalpy and electrode erosion in high currents. Finally, the paper proposes the related ideas and methods for these key technologies, providing theoretical references for China's development of a super-high power arc heater.

Aiming at the distance measurement of moving sound sources in shallow seas, this paper proposes a method of histogram filtering to realize underwater distance estimation of moving sound sources in shallow seas. The algorithm used the transmission loss, target motion parameter in the sound propagation and receival signal as prior knowledge to updated the state vector of the sound source, so as to realize the distance estimation of the shallow sea sound source, and this paper used SwellEx-96 database for experimental verification. The experimental results shown that: the depth estimating error of moving sound source is small, and when the detected horizontal distance is in the range of 10 km, the maximum range error of the horizontal distance is ±10 m, meanwhile the accuracy of ranging can be improved by improving the prior knowledge of the target motion parameters, which verifies that the histogram filtering algorithm can achieve better ranging for underwater moving targets.

With the widespread using of GPU hardware facilities, more and more distributed machine learning applications have begun to use CPU-GPU hybrid cluster resources to improve the efficiency of algorithms. However, the existing distributed machine learning scheduling framework either only considers task scheduling on CPU resources or only considers task scheduling on GPU resources. Even considering the difference between CPU and GPU resources, it is difficult to improve the resource usage of the entire system. In other words, the key challenge in using CPU-GPU clusters for distributed machine learning jobs is how to efficiently schedule tasks in the job. In the full paper, we propose a CPU-GPU hybrid cluster schedule framework in detail. First, according to the different characteristics of the computing power of the CPU and the computing power of the GPU, the data is divided into data fragments of different sizes to adapt to CPU and GPU computing resources. Second, the paper introduces the task scheduling method under the CPU-GPU hybrid. Finally, the proposed method is verified at the end of the paper. After our verification for K-Means, using the CPU-GPU hybrid computing framework can increase the performance of K-Means by about 1.5 times. As the number of GPUs increases, the performance of K-Means can be significantly improved.

Sonic boom reduction has been an urgent need to develop the future supersonic transport, because of the heavy damages of the noise pollution. This paper provides an active control method for the supersonic aircraft to reduce the sonic boom, wherein a suction slot near the leading edge and an injection slot near the trailing edge on the airfoil suction surface are opened, and the mass flow sucked in near the leading edge is equal to the mass flow injected near the trailing edge. The diamond and 566 airfoils are adopted as the baseline airfoil to verify the capability of the active control method, and the effects of the suction and injection location, the mass flow rate and the attack angle on the ground boom signature, the maximum overpressure, the drag coefficients and the ratio of lift to drag are studied in detail. The results show that the proposed active control method can significantly reduce the sonic boom, and the reduction of the sonic boom intensity is more sensitive to the injection near the trailing edge than the suction near the leading edge. Applying this active control method to the diamond (NACA0008) airfoil, when the mass flow rate is 6.5 kg/s(7.5 kg/s), the value of maximum positive overpressure is decreased by 12.87%(12.85%), the value of maximum negative overpressure is decreased by 33.83%(56.77%) and the drag coefficient is decreased by 9.50%(10.96%). It can be seen that the method proposed in this paper has great benefits in the reduction of sonic boom and provides a useful reference for designing a new generation of lower sonic boom supersonic aircraft.

The paper studies how to plan the trajectories of an unmanned combat aerial vehicle (UCAV) that releases its airborne weapons and presents an online trajectory planning method based on threat modeling. Firstly, it analyzes the aerodynamic characteristics, engine thrust and fuel characteristics of the UCAV and builds its dynamic and kinematic models. Secondly, the trajectory planning model of the UCAV is formulated with flight performance constraints and battlefield threat constraints considered. To improve the accuracy of ground attacks, the envelope of a guided bomb's acceptable region of weapon release is studied, and the release center and posture of the guided bomb work as terminal planning conditions. Thirdly, an online trajectory planning method is proposed. With the help of threat modeling, the complicated trajectory planning problem is transformed into a simplified situation classification. Finally, the simulation results demonstrate that the online planning method proposed in the paper can provide feasible trajectories for a UCAV to succeed in releasing its airborne weapons.

Compared with traditional gear transmission, the multi-branch split-torsion gear transmission system has the advantages of large transmission power, small size and high reliability, so it is more and more used in high-speed heavy load occasions such as ships and aircraft. Since the transmission system of multi-branch split torsional gears belongs to over-constrained configuration, it is necessary to meet strict tooth matching condition in the design process in order to realize the correct synchronous meshing of each branch, which is of great significance to ensure its uniform installation and motion synchronization.Aiming at the coaxial six-branch twisted herringbone gear transmission system, this paper establishes a calculation method for the proper meshing conditions of each branch on the basis of considering the movement synchronization of each branch and preventing geometric interference.In addition, the calculation of gear allocation was carried out for a ship's power transmission system, and a parameter scheme that satisfies the requirements of transmission ratio, concentricity and synchronous meshing was obtained.The correctness of the calculation method of tooth matching in this paper is verified by three-dimensional modeling. This method has universal application value to the tooth matching design of other coaxial multi-branch gear transmissions.

In order to solve the problems of high data dimension and insufficient consideration of time series correlation information, a multi-scale deep convolutional neural network and long-short-term memory (MSDCNN-LSTM) hybrid model is proposed for remaining useful life (RUL) of equipments. First, the sensor data is processed through normalization and sliding time window to obtain input samples; then multi-scale deep convolutional neural network (MSDCNN) is used to capture detailed spatial features, at the same time, time-dependent features are extracted for effective prediction combining with long short-term memory (LSTM). Experiments on simulation dataset of commercial modular aero-propulsion system show that, compared with other state-of-the-art methods, the prediction method proposed in this paper has achieved better RUL prediction results, especially for the prediction of the life of equipment with complex failure modes and operating conditions. The effect is obvious. It can be seen that the prediction method proposed in this paper is feasible and effective.

Aiming at the attitude solution accuracy and robustness for small UAVs in complex flight conditions, this paper proposes a dynamic adaptive attitude and heading systems(AHRS) estimator with singular value decomposition Cubature Kalman filter(SVDCKF). Considering the problem of random bias for the low-cost attitude sensor, this paper designs a method that the sensor random bias is used as the state vector to eliminate the effect of the sensor random bias. Due to the non-linearity of small UAVs AHRS model and the non-positive definite phenomenon of the covariance matrix, a nonlinear AHRS filter combined with the Cubature Kalman filter and singular value decomposition is designed to improve the attitude solution accuracy. In addition, when the UAV flies in the different flight conditions, the three-axis acceleration of the attitude sensor will affect the attitude solution. Thus, a dynamic adaptive factor based on adaptive filtering is used to adjust continuously the acceleration noise variance to improve the robustness of the AHRS. The experimental results show that the method and algorithm proposed not only improve the attitude solution accuracy, and satisfy the flight requirements of small UAVs, but also eliminate the influence of the attitude sensor random bias and three-axis acceleration for the attitude solution to improve the proposed algorithm robustness and anti-interference.

Most of the solutions to existing test selection problems are based on single-objective optimization algorithms and multi-signal models, which maybe lead to some problems such as rough index calculation and large solution set limitations. To solve these problems, a test optimization selection method based on NSGA-3 algorithm and Bayesian network model is proposed. Firstly, the paper describes the improved Bayesian network model, expounds the method of model establishment, and introduces the model's learning ability and processing ability on uncertain information. According to the constraints and objective functions established by the design requirements, NSGA-3 is used to calculate the test optimization selection scheme based on the improved Bayesian network model. Taking a certain component of the missile airborne radar as an example, the fault detection rate and isolation rate are selected as constraints, and the false alarm rate, misdiagnosis rate, test cost, and test quantity are the optimization goals. The method of this paper is used for test optimization selection. It has been verified that this method can effectively solve the problem of multi-objective test selection, and has guiding significance for testability design.

This paper selects SST k-w turbulence model and VOF wave to construct a numerical calculation model of moving body planning on a flat free surface based on STAR-CCM+ numerical simulation software. The construction model is checked through foreign classic literature, and the numerical simulation results are in good agreement with the experimental results. The hydrodynamic numerical errors are less than 5%, which is within the engineering error range. The model can be used for the numerical simulation of the planning cylinder. In this paper, it is used to simulate the planing process of cylinder with different speeds and different submerged depths, and the flow field characteristics and hydrodynamic characteristics in the planing process are obtained. The results show that waves appear at the tail and the tail liquid splashes to form a water splash during the planing process of the cylinder on a flat surface. The higher the speed of the planning cylinder is, and the deeper the submersion depth, the more pronounced waves at the tail. When the cylinder has a Fr number Cv≥8, the hydrodynamic force of the cylinder is almost unchanged, and it is not affected by the speed. But when Cv=3, the hydrodynamic characteristic coefficient is higher. The drag coefficient is 20% higher than that in the high-speed (Cv≥8) planing process. The lift coefficient is 3 times of high-speed planing lift coefficient. It is related to the surface pressure and frictional force distribution of cylinder during the low-speed planing. There is a linear relationship between the drag coefficient and the submerged depth during the cylinder planing at different submerged depths.

To plan a UAV's full-area reconnaissance path under uncertain information conditions, an unsupervised learning neural network based on the genetic algorithm is proposed. Firstly, the environment model, the UAV model and evaluation indexes are presented, and the neural network model for planning the UAV's full-area reconnaissance path is established. Because it is difficult to obtain the training samples for planning the UAV's full-area reconnaissance path, the genetic algorithm is used to optimize the unsupervised learning neural network parameters. Compared with the traditional methods, the evaluation indexes constructed in this paper do not need to specify UAV maneuver rules. The offline learning method proposed in the paper has excellent transfer performances. The simulation results show that the UAV based on the unsupervised learning neural network can plan effective full-area reconnaissance paths in the unknown environments and complete full-area reconnaissance missions.

To address the unmeasured velocity, external disturbance and internal model uncertainty for following the path of an under-actuated ship, the paper presents a sliding mode control method based on the radial basis function(RBF) neural network and the velocity observer. To enhance the RBF performance of approximating the unknown, an arc tangent function was exploited in the RBF neural network to update its weight values. Then, the nonlinear observer was built via the hyperbolic tangent function to deal with the unmeasured velocity of the ship. Furthermore, in order to avoid overshoots when the ship is moving to its way points, the virtual paths of a variable circle based on the turning angle were designed at the joints of the path of the ship to enhance its path following capability. Finally, the simulation results show that the sliding mode controller designed in the paper can force the ship to follow accurately the reference path in case of time-varying disturbances without measured velocity and enhance the path following performance of the ship and the accuracy of the RBF neural network, thus demonstrating its effectiveness.

Applying deep learning to aerodynamic data modeling has important practical significance. In this paper, the composite neural network is applied to the aerodynamics, making full use of the different characteristics of high and low-fidelity aerodynamic data. Multi-fidelity analysis technique is also used to analyze the correlation between the two types of data so as to establish the composite neural network. The experimental results show that the learning of multi-fidelity aerodynamic data based on the composite neural network model can better capture the mapping relationship between the aerodynamic input and the output data. And after comparing with the single neural network, it is verified that the present model has excellent performance in the regression modeling of aerodynamic data.

With the help of lightweight virtualization technology such as containers, the spaceborne virtualization platform encapsulates computing tasks into containers to form task containers, so as to achieve efficient utilization of resources. However, the platform's task container scheduling problem is a difficult problem that needs to be solved urgently. In this paper, we aim at this problem by establishing a multi-pass scheduling model for separable container tasks based on non-blocking communication mode. On the basis of this model, we propose a new scheduling algorithm, aiming at determining the optimal processor scheduling sequence and scheduling times. The algorithm combines the concept of divisible task container and multi-pass scheduling. By decomposing the task into executable subtasks, and performing task allocation and processor scheduling in multiple scheduling stages, it can optimize the scheduling order to improve the overall processing efficiency. This algorithm is an improved genetic algorithm that adds the optimization strategy of subpopulation isolation to the traditional genetic algorithm. Its core idea is to improve the performance and effect of the genetic algorithm by introducing the population division strategy into the algorithm process. We verify the effectiveness and convergence of the algorithm through experiments, and the experimental results show that the algorithm makes the task have less completion time.