Abstract:2025年26卷第1期目次

Abstract:In view of the problem that in the measurement of infrared radiation characteristics for engine tail jet, the near-field atmospheric transmittance of tail jet is difficult to measure accurately in all-direction, this paper studies a law of the influence from near-field atmospheric transmittance at different angles and distances on the infrared radiation characteristics of the tail jet in 3~5 μm band, and simultaneously finds that the atmospheric permeability in the core area of the tail jet decreases by 5.65% compared with the natural environment. With the increase of distance, the atmospheric transmittance in the tail jet area of the engine decreases rapidly, and the test distance of 25 meters and 50 meters decreases by 22.64% and 29.88%. With the increase of the test angle, the influence of the tail jet on the atmospheric transmittance decreases. The results show that this scientific research achievement can not only support the measurement of atmospheric transmittance of aero-engine infrared characteristics, but also provide data support for the evaluation of near-field atmospheric transmittance and infrared radiation of tail jet.

Abstract:The integrated materials of anti/de-icing-stealth have important research value and application potential in aerospace, especially in the field of UAV. In this study, graphite/silicon based gel composites were prepared by siloxane coupling reaction. The results show that when the graphite content is 40%, the hydrophobic angle of the silicon based gel is 109.3 °± 2.3 °, the temperature in the center of the sample is 69.6 ℃ (heated at 100 ℃ for 60 s), the maximum tensile strength is 0.512 1 MPa and the effective absorption bandwidth is 6.83 GHz@1.61 mm (9.70~16.53 GHz). The intrinsic coupling mechanism of hydrophobic, thermal conductive and microwave absorbing properties of silicon based gel was clarified by characterizing the microscopic factors such as conductivity and defects of gel. This study provides a simple material design strategy for achieving both stealth and anti icing functions of drones simultaneously.

Abstract:In order to research the effect of bolt eccentric distance and install direction on static tensile behavior of bolted joints with L-shaped Ti-Al curved laminate, the researches are adopted by the experimental and numerical methods. A test is accomplished on 7 sets of specimens with 3 groups (i.e. pure tension bolted，up bolted and down bolted) divided. The test results demonstrate the average collapse load and mode of group A respectively. The Influence of eccentric distance and installation direction on mechanical behavior of bolted joints is investigated by group B、C. FEMS are proposed by ABAQUS to reproduce the test results of the above-mentioned groups. Through Johnson-Cook, the plastic and failure criteria of the bolt are developed. The stiffness, failure mode and collapse load obtained by FEM method are in good agreement with the experimental results. Besides, the FEM can clearly describe the starting position and expansion process of bolt breakage. According to the experimental and numerical research, the failure load of butt-bolted joints is much lower than that of the bolt pure tension group due to the additional bending moment, and the ultimate loads decrease with the increase of eccentric distance. Furthermore, the ultimate loads of down bolted are slightly higher than that of the up bolted while comparing specimens with the same eccentric distance. The failure mode of group A and C is bolt cross-section fracture (type I), while the failure mode of group B is bolt head curling failure (type Ⅱ). This study has a certain of guiding significance for the design of bolted joints with L-Shaped curved laminate.

Abstract:A small sized metal-rubber part being vulcanized, the annular rubber surface is a curved surface with high inner and outer rings and a concave middle part, and such a product is not only out of keeping with the design requirements but also an affection of sealing performance. By measuring the protrusion amounts of the highest and lowest points of the rubber surface of the metal-rubber part relative to the metal end face and the concave amount of the rubber itself, the overall protrusion amount of the rubber surface is indirectly described. In this paper, the control variable method is utilized for conducting experiments from the dimensions of mold design, molding vulcanization process and stay time before measurement. It appears from these experiments that the mold molding surface designed to about R50 arc surface can effectively compensate the concave amount in the middle of the rubber surface, the thickness of the rubber blank is controlled at more than 130% of the design thickness, the vulcanization pressure is controlled at more than 6 MPa, the increasing pressure controlled at 40%~60%, and the stay before measurement is not less than 24 hours, ensuring the protrusion amount of the rubber surface for meeting the design requirements and the sealing performance. The experimental results show that thanks to the improvement of the design of the mold forming surface, adjustment of the size of the rubber blank, the vulcanization pressure and the pressurization rate, and prolongation of the stay time before measurement, it has become possible to effectively control the protrusion amount of the rubber surface of small sized metal-rubber parts.

Abstract:In this paper,a directional attack black-box attack method named improved mixup attack (IMA) method is designed aimed at the current problems that researches on adversarial examples of targeted attacks are less,and black-box attack capability is very weak in remote sensing image classification.The method aims to directionally fool the classification model out of the deep neural network,discover its vulnerable parts,and enable our high-value target to be detected as a low or no-value target.The method,firstly,is used to extract the shallow global features of the image by an image classification deep learning model,and is used to realize the targeted attack for changing the input image pixels to approximate the shallow features of the input clean image to the target image.After that,an adaptive control of the iteration step size is designed to improve the efficiency of the iteration and the transferability of the attack.Simultaneously,the idea of model hierarchy is introduced by using multiple models with different architectures as surrogate models,so that the generated adversarial examples have both multi-model features to improve the transferability of the attack.Finally,several models are tested on several remote sensing classification datasets,and the experimental results show that the proposed method is valid.

Abstract:In order to solve the problems of low information utilization and low positioning reliability in the complex battlefield electromagnetic environment, and the difficulty of building an electromagnetic situation database to train deep learning models, this paper proposes a radiation source localization algorithm based on electromagnetic situation data matching. The propagation characteristics under this condition are extracted from the electromagnetic data of the target area, and the propagation data under the visual condition is constructed, and the two parts of the data are matched by window sliding to estimate the possible location of the radiation source. The simulation experiment results show that the algorithm studied in this paper has an average positioning error of less than 64.7 m under the condition of 0.1 perception node proportion, and the required time is only 0.334 s.

Abstract:Aimed at the problems that side-lobe level is on the increase, nulls are shifting, and even beampattern distortion of array antenna is induced by unavoidably existing array errors in practical scenarios, this paper proposes a robust array beamforming method based on an improved encoder-decoder structure. There are models of encoder and decoder in design based on one-dimensional convolutional neural network (1D-CNN) and artificial neural network (ANN), and the encoder and the decoder separately play the role of array synthesizer and analyzer respectively. Specifically, the decoder is firstly trained to establish a mapping relationship between the excitation weight vector of the actual array and the beampattern where the array errors is taken into consideration during the training process. Secondly, the encoder is trained to establish a mapping relationship between the desired beampattern and the required excitation weight vector by combining the trained decoder. And then, continuously iterate is made, and the optimal excitation weight vector is obtained ultimately. To verify the effectiveness of the method, two typical beampattern synthesis, i.e., achieving -45 dB single nulling and -40 dB multiple nulling with -20 dB low sidelobes, are conduced based on 16-element array in the presence of array errors. The simulation results show that the proposed method is valid.

Abstract:In air defense and antimissile operations, constructing an efficient kill-net is a key part to ensuring the success of air defense tasks, while it is tricky to model and to optimize such problems. This paper aims to model the construction of static kill-net from the perspective of combinatorial optimization and propose efficient optimization methods. Considering the characteristics of the kill-net construction problem, this paper establishes a mixed-integer programming model and uses a bilevel optimization modeling scheme for simplification. By the cooperation of the leader problem of tasks assignment and the follower problem of resolving conflicts, the optimization difficulty is reduced. Subsequently, a solution framework based on a bilevel genetic algorithm is designed. In experimental tests on 4 sets of different-scale environments, the algorithm is able to get a fine result quickly, with great interpretability and a good capabilities for solving larger-scale problem. This work provides insights for the autonomous intelligent construction of static kill-net in the field of air defense and could serve as the basis for research focusing on dynamic kill-net adjustment.

Abstract:Aimed at the problem that pulse loss is a significant impact on mode recognition accuracy, an intelligent working mode recognition algorithm for airborne radar is proposed based on PDW reconstruction. Firstly, frequent DTOA items are extracted based on the first-order differential sequence of TOA. Secondly, the radar’s true PRI and the PRI variation pattern are derived from these frequent items. Thirdly, the computed number of pulses under conditions of different PRI are to complete PDW reconstruction. Finally, the reconstructed PDW is inputted into a pre-built temporal convolution network (TCN) for recognizing the onboard radar working mode. Such a method can exploit the temporal correlation within the PDW sequence to further capture the features of the PDW sequence. The results show that the proposed method achieves a mode recognition accuracy of over 95% when the pulse loss rate is less than 70%.

Abstract:Based on the research background of one-to-one near visual range air combat of unmanned aerial vehicles (UAVS), a new air combat decision-making method combining weighted matrix strategy and evolutionary algorithm with coarse and fine granularity optimization is proposed. Firstly, the UAV maneuver model and air combat situation assessment advantage function are established based on the actual combat situation. Secondly, considering that the discrete variable optimization based on maneuvering library and the continuous optimization based on maneuvering ability both have the problems of insufficient accuracy and high calculation cost, a maneuvering decision framework combining coarse and fine granularity optimization is proposed. At the level of coarse-grain optimization, the matrix game method is introduced, and the Kalman filter algorithm is used to adjust the weight of the traditional matrix game method to solve the problem of conservative choice of maneuvering weight reference. At the fine-grained optimization level, based on the differential evolution principle, further search for better maneuvers. The effectiveness of the proposed decision frame is verified by four sets of comparison experiments. The weighted matrix game algorithm based on trajectory prediction can take effective countermeasures against the enemy’s actions.

Abstract:Counter-drone operation is an important part of air and missile operations. In view of the problems that the counter-drone operation capability is subject to the effect of joint air and missile defense system, and the evaluation capability is difficult to perform comprehensively with the counter-drone operation being divorced from the joint air and missile defense system, an evaluation index system of the joint air and missile defense and drone operation capability is constructed, and an evaluation model of the counter-drone operation capability is proposed under condition of joint air and missile defense system. The game theory is utilized for synthesizing the subjective and objective weights of AHP-entropy weight method, and optimizing the weights of evaluation indicators. The results show that the method is reasonable and scientific through the verified examples, providing a theoretical basis for evaluating the anti-drone combat capability of the joint air defense and missile defense system.

Abstract:With the support of big data in recent years, deep learning models have been demonstrating excellent capabilities in the aspects of computer vision and natural language processing. However, in the application of malicious code images fields, it is entirely possible for the malicious code to be insufficient training data. The distribution of whole dataset with number of training samples in some malicious families being limited is hardly characterized fully, and the deep learning model may be over-fitted to these scarce data, resulting in poor model performance. In view of the above-mentioned problems, this paper proposes a dataset expansion method based on the diffusion model to generate new samples. Such a method is to achieve dataset expansion by learning the conversion process from the original data to noise and using the inverse process to reduce the noise samples into new similar samples, generating new samples similar to the original dataset but different from the original dataset, alleviating the impact of the imbalance of data of some of the families on the classification and detection task, and improving the model’s generalization ability.

Abstract:The battlefield environments being complex, dynamic, characterized by high dynamics, incomplete information, and uncertainty, the deep reinforcement learning (DRL) is enabled to provide a new way of thinking about task assignment in modern information warfare. Aimed at the problem that the agent system is inadequate in generalization ability under condition of uncertain scenario, this paper proposes an event-based reward mechanism to reasonably guide the learning of the agent, and the problem that in deep reinforcement learning, a single reward function is difficult to train an agent of being in keeping with human decision logic, this paper proposes an event-based reward mechanism to reasonably guide the learning of the agent. And this paper proposes a multi-agent architecture for different decision styles, enhancing the ability of the agent to adapt to complex environments. Finally, the feasibility and superiority of the proposed method are verified on a digital battlefield.

Abstract:Cement mortar mixed with rubber powder being used as repair material for damaged pavement, its performance of cold-resistance should be able to meet the requirements of airports in high cold area. The effects of mesh number and content of rubber powder in cement mortar on frost resistance and mechanical properties are studied through freeze-thaw cycle tests. The effects are determined by adopting two-factor analysis of variance and range analysis. The effects of rubber powder on the microstructure and products during hydration of cement mortar are revealed by SEM and XRD. The results show that the mesh number and content of rubber powder cement mortar have significant effects on the frost resistance and compressive strength, but the interaction between them is not significant. When the mesh number of rubber powder is 30 mesh and the dosage is 50%, the antifreeze performance is the best. SEM images show that the addition of rubber powder can block the development for micro-cracks, and the XRD results show that 30-mesh rubber powder can enable the hydration reaction between rubber powder and cement mortar to continue efficiently.

Abstract:The cross-tensioned concrete pavement is for the tensile strength of pre-stressed tendon to be utilized fully for making concrete pavement in a state of bi-directional compression prior to bearing vehicle loading and environmental effect by tensioning cross-strands, significantly enhancing bearing capacity and durability of concrete pavement. The model test is conducted to get mechanical performance of local anchorage in cross-tensioned concrete pavement based on its complicated distribution of stress, following by discussing influence of shape of U-shaped notch in prefabricated modules on measured strain. The results show that the local anchorage is in a complicated stress state under action of tensioning of cross-strands. The measured tensile strain reaches its maximum value at the top of U-shaped notch in the section where the tensioning cross-strands locate under action of symmetric tensioning. Additionally, the shape of U-shaped notch has apparently influence on measured strain. The trapezoidal prefabricated modules have simple structure and light weight, but poor mechanical performance owing to phenomenon of stress concentration. While prefabricated modules with larger angle of chamfer are good in mechanical performance, but heavier weight. The prefabricated modules with smaller angle of chamfer simultaneously have better mechanical performance and lighter weight. Furthermore, the gap between adjacent prefabricated modules obviously makes the measured strain on increase, and symmetric tensioning is the most unfavorable loading condition for prefabricated modules. Therefore, the gap between adjacent prefabricated modules should be dealt with grouting before tensioning of cross-strands to decrease tensile strain.