Due to the complexity of artillery firepower strike system and the coupling of various elements,the traditional design methods for designing the subsystems to be relatively independent of each other are insufficient to meet the needs of integrated system development.A firepower strike system design model based on multi-objective optimization is constructed to address this issue.According to the composition of artillery firepower strike system,the parameter models for multiple subsystems are established,and the main constraint parameters and the design parameters are determined.An optimization design model is established by taking the mission time,ammunition consumption,and mission cost as the objectives.The multi-objective optimization algorithm of the second-generation non-dominated sorting genetic algorithm (NSGA-II) is used to complete the optimization design of a typical firepower system,thereby determining the main design parameters of subsystems such as drones,command and control equipment,artillery,ammunition,and chassis.The research results show that the multi-objective optimization method can solve the problem of multi-parameter coupling in the design of multiple subsystems,achieve the optimal design results for system performance,and provide support for the configuration of the firepower system according to operational mission requirements.

Trajectory tracking is a crucial functionality of the autonomous driving control system.The vehicle dynamics model has a significant impact on trajectory tracking performance,however,there is a conflict between model complexity and solving efficiency,often leading to insufficient tracking accuracy under nonlinear conditions.To address this challenge,this paper proposes a model predictive control method based on Gaussian process regression (GPR) for trajectory tracking.A simplified model is used to ensure solving efficiency,and GPR model is employed to compensate for the vehicle model,thereby enhancing the trajectory tracking performance.First,a vehicle state fusion estimation method based on the single-track dynamics model is developed to obtain the GPR compensation model.A trajectory tracking error model is developed.Based on the trajectory tracking error from vehicle dynamics model,the iterative equation for GPR error compensation within the predictive horizon is derived to dynamically compensate for model errors in the vehicle state prediction for achieving the trajectory tracking control.Finally,a real-vehicle validation platform is constructed to validate the proposed method under typical driving conditions.The proposed method is compared with other predictive control methods without GPR compensation.The results show the proposed method achieves a significant improvement in trajectory tracking accuracy.Specifically,the lateral and heading errors are reduced by 33.3% and 27.9%,respectively.Furthermore,the vehicle comfort performance is also improved,and the mean lateral acceleration and yaw rate are reduced by 17.1% and 21.7%,respectively.

Unmanned aerial vehicle (UAV) formation can execute complex collective tasks and reduce the risk and operation difficulty of a single UAV. A distributed formation compound control method with the leader-follower structure is designed based on the prescribed-time stability theory and multi-agent consensus theory for the control of UAV swarm formation in three-dimensional scene.Firstly,a multi-UAVs kinematic model is established by analyzing the relationship between the actual input and the equivalent control.In order to enhance the robustness of UAVs against external disturbances,a prescribed-time convergent extended state observer is designed to achieve online estimation of disturbance based on active disturbance rejection control theory.Furthermore,considering that only the followers connecting to the leader can access the leader's state information,a prescribed-time convergent distributed estimator is introduced to rapidly estimate the leader's state.On this basis,a prescribed-time convergent consensus formation control algorithm is proposed combined with the outputs of the observer and the estimator,and the prescribed-time stability of closed-loop system is proved by Lyapunov theory.The simulated results validate the effectiveness of the proposed method.The research results show that the proposed control method can achieve the stable cooperative control of UAV formation within a preset time in the presence of external disturbances.

The cooperative operation of multiple autonomous underwater vehicles (AUVs) shows broad application prospects in underwater combat scenarios.A dual-loop prescribed-time formation control method is proposed for the control of underactuated multi-AUV three-dimensional formation under model uncertainties and unknown environmental disturbances.A mathematical model of AUV motion is established and an underactuated coordinate transformation is introduced to solve the underactuation problem of AUV.To mitigate the adverse effects of model uncertainty and unknown environmental disturbances on the system,a fixed-time extended state observer is designed to estimate and compensate for model uncertainty and unknown environmental disturbances.In order to achieve the prescribed-time convergence in multi-AUV formation,a dual-loop prescribed-time controller,consisting of an outer-loop control law and an inner-loop control law,is designed.The outer-loop control law is used to adjust the desired velocity of AUV to achieve the formation objective,while the inner-loop control law is responsible for tracking the desired velocity.Theoretical analysis demonstrates that the proposed method enable the system to converge within a prescribed time.+++Simulated results show that,compared to the finite-time and fixed-time control methods,the proposed method can achieve prescribed-time convergence and further enhances the system's convergence speed,providing a new approach for multi-AUV formation control in tasks with high coordination requirements.

The traditional dung beetle optimization algorithm (DBO) exhibits the poor stability and insufficient optimization ability in the trajectory planning of unmanned aerial vehicles (UAVs) in complex environments,DBO Optimization Algorithm with Group-based Optimization and Adaptive t-Distribution (GOTDBO) is proposed.Based on the DBO algorithm,the GOTDBO algorithm combines the composite population initialization strategy,the adaptive disturbance global exploration strategy and the adaptive t-distribution disturbance strategy,effectively enhancing the global exploration and local exploitation capabilities of the algorithm and improving the convergence speed of the algorithm.The smoothness and safety of the trajectory are further optimized by constructing an objective function that comprehensively considers the total flight length,corner curvature and maximum flight direction change,and introducing the penalty function method to handle no-fly zones and other constraints in the path,the smoothness and safety of the trajectory are further optimized.Experimental results show that,in terms of the flight range,When the GOTDBO algorithm is applied to route planning in scenarios with different complex environments,it can plan compact and efficient routes,performs excellently in terms of maximum range,and effectively improves the economy of endurance.In terms of threat avoidance,the trajectory planned by the GOTDBO algorithm has the least number of approaches to threat areas,thus ensuring higher flight safety.In terms of altitude control,the degree of altitude deviation is low,enabling stable and accurate altitude control.Although the GOTDBO algorithm is comparable to other algorithms in the trajectory smoothness,it has significant advantages in multiple core indicators.It is energy-saving and efficient,safe,and reliable in UAV trajectory planning,and has high application value and broad prospects.

Application of reinforcement learning in unmanned aerial vehicle (UAV) air combat faces the challenges of which the rigid reward functions and single models are used to handle the complex tasks difficultly in high-dimensional continuous state spaces.This severely limits the decision-making generalization capability in dynamic and of algorithm varied situations.Addressing the aforementioned issues,an autonomous decision-making framework with the deep double Q-network (DDQN) and deep deterministic policy gradient (DDPG) algorithms is proposed,which integrates the essence of hierarchical and distributed architectures.Based on the advantage differences between the opposing forces in various situations,a series of DDPG algorithm models with different reward function weight combinations are designed to construct a bottom-level distributed deep deterministic policy gradient (D³PG) decision-making network.The DDQN algorithm which excels in handling discrete action spaces is introduced to construct a top-level decision-making network.It allows for autonomous selection and switching to the most suitable bottom-level policy model based on real-time situation changes,thereby achieving the instant adjustment and optimization of decisions.To further enhance the realism and challenge of combat environment,a self-play mechanism is introduced into the DDPG algorithm training to construct an enemy decision-making model with high intelligence.The experimental results demonstrate that UAVs equipped with the proposed algorithm achieve a maximum win rate of 96% in adversarial engagements against intelligent opponents,which is increased by more than 20% compared to those of baseline algorithms such as D³PG.Moreover,it consistently defeats the opponents under various initial conditions,confirming the effectiveness and advancement of the proposed algorithm.

As a new type of aircraft,the unmanned aerial vehicle (UAV) is gradually integrating into the modern weaponry system and becoming an indispensable and important part of the military field.In order to equip UAV with a safe landing decision-making system that can autonomously perform landing tasks without ground marking,this paper proposes a phased autonomous location selection technique based on multi-sensor data fusion from coarse to fine.The rough landing point search is realized based on the semantic segmentation of the image information.After guiding the UAV to reduce the flight altitude,the terrain parameters are calculated from the elevation value of point cloud information to construct a terrain cost map,and the semantic information of the image is fused by considering the category of a terrain to complete the fine landing point search.The experimental results show that the proposed location selection technique can well delineate the safe and dangerous areas,and enables UAVs to autonomously arrive at a safe landing position.Meanwhile,the comparative analysis of the decision-making in the fine landing point search stage with the fitted point cloud plane verifies that the technique can save decision-making time to a greater extent and improve the efficiency of location selection.

The trajectory planning online applications for the formation transformation,impact time and terminal entry angle constraint of unpowered gliding vehicle clusters during the re-entry phase are studied.A real-time coordinated trajectory planning method for unpowered gliding vehicle cluster based on master-slave architecture is proposed.The trajectories of the vehicles are first decoupled into longitudinal and lateral planes,and a segmented function-based angle-of-attack velocity profile method is developed to handle the nonlinear constraints encountered during the re-entry phase.A cooperative control method based on time-varying heading angles is then proposed,which involves solving differential equations to generate a trajectory that satisfies the formation transformation and the impact time and entry angle constraints under quasi-equilibrium glide conditions.An online adjustment strategy is further introduced to accommodate the real-time updates to the target area,and the feasibility of the proposed method for online application is demonstrated.Simulated results indicate that the proposed method can achieve real-time coordinated trajectory planning across various flight scenarios,thus demonstrating its robustness,adaptability to multiple cooperative control schemes,and practical applicability to unpowered gliding vehicle clusters.

A sliding mode fault-tolerant control method based on polytopic linear parameter-varying (LPV) model is proposed to address the matched disturbances and actuator multiplicative failures of morphing aircraft during the flight process.An LPV model of morphing aircraft is established based on the longitudinal nonlinear dynamics model of morphing aircraft undergoing wingspan deformation.The LPV model is transformed into a polytopic form,which can convert the infinite-dimensional linear matrix inequality (LMI) problem into a finite-dimensional LMI problem.In order to ensure the stability and robustness of the morphing aircraft when the system actuator malfunctions,a gain-scheduled fault-tolerant control algorithm is proposed by selecting a suitable sliding mode surface and designing a sliding mode fault-tolerant control law.The fault-tolerant control algorithm is applied to the morphing aircraft for simulation verification.The simulated results show that the fault-tolerant control algorithm can be used to ensure the stability and anti-interference ability of the closed-loop system when the actuator fails.

Multi-axle articulated wheeled vehicles are prone to occurring “tail amplification” effects and lateral instability during trajectory tracking.The study of stable trajectory tracking for multi-axle articulated wheeled vehicles is of significant importance.For the multi-axle articulated wheeled vehicle,a 7-degree-of-freedom vehicle dynamics model is established,and a bi-level strategy trajectory tracking control method is proposed.The upper-level strategy is used to address the tractor trajectory tracking problem,while the lower-level strategy is used to optimize the trailer trajectory tracking,ensuring precise tracking for both tractor and trailer.To guarantee the real-time computation of the control strategy,the upper-level trajectory tracking strategy is solved using a finite-horizon approximate dynamic programming approach,and the online optimization problem is transformed into an offline pre-solution of parameters,thus reducing the time required for online solving.This approach significantly reduces online computation time.Co-simulation experiments with high fidelity simulation software demonstrate that the proposed method is used to improve the trajectory tracking accuracy of multi-axle articulated wheeled vehicles by 12.82%,and keep a single-step solution time below 10ms,enhancing computational efficiency by three orders of magnitude compared with the model predictive control algorithm.

The dynamic impacts generated during the transient shifting process of a planetary integrated transmission system for tracked vehicle have serious effect on the service performance and reliability of transmission system.For a certain planetary integrated transmission system,the torsional dynamics models of gear transmission components,clutches and brakes,etc are established,and a dynamics model of transmission system during the shifting process is constructed.The simulation and bench tests of the shifting process of the integrated transmission system are carried out.The changing trends of the simulated and test results are basically consistent,thus verifying the correctness of the dynamics model.The impact loads of typical components during the shifting process are further studied,and the influence laws of the throttle opening and the characteristics curves of oil charging and discharging,etc.on the dynamic torques of the operating components are revealed.The main conclusions are as follows.The reverse dynamic torque of disengaging operating component and the maximum impact torque of engaging operating component gradually increase with the increase in oil discharging delay.With the extension of oil discharging time,the reverse dynamic torque of disengaging operating component gradually increases,and the maximum impact torque of engaging operating component decreases first and then increases.The faster the oil charging is in the fourth pressure increasing stage,the greater the maximum impact torque of engaging operating component is,and the maximum impact value is 11% higher than the minimum impact value.With the increase in throttle opening,the maximum dynamic torque of operating component gradually increases,and the maximum dynamic torque value is 73.8% higher than the minimum dynamic torque value.

Multi-axle wheeled vehicle dynamics model is the basis for the rapid development of new vehicle equipment,the optimization of vehicle design parameters and the construction of control algorithms.The commonly used commercial software is difficult to obtain the dynamic equations and model gradient information so that it cannot be used for the dynamic optimization of vehicle global design and control parameters.And the effects of top-loading dynamics have been given less consideration in existing commercial software and theoretical modelling studies.In order to address the aforementioned issues,a vectorized modeling method is employed to construct a 24-degrees-of-freedom dynamics model of an 8×8 wheeled vehicle based on Lagrangian dynamics,which considers the influences of the longitudinal and lateral motions of unsprung mass and the reaction force of top load on the vehicle dynamics.The modeling is based on Lagrangian dynamics,and the software is developed using C++ and M languages,respectively.The proposed model is comprehensively compared with the commercial software TruckSim under a variety of working conditions,including variable acceleration,step steering,double lane change,swept sine steering.The results demonstrate that the tire force,suspension force and air resistance,as well as the longitudinal,lateral and vertical motions of the proposed simulation model exhibit high consistency with those of the commercial software with an error of less than 5%.This verifies the accuracy of the methodology.

The reactive filling structure exhibits a unique behavior of self-distributed deflagration and energy release,along with mechanically and chemically coupled dynamic characteristics when penetrating multi-layered plates.This results in a multi-peak,long-duration deflagration overpressure behind the plates,featuring a complex evolution and waveform mechanism of the deflagration process.To better understand this distinctive energy-releasing behavior,overpressure signals were recorded during experiments that involved the reactive filling structure penetrating multi-layered plates at various velocities.An equivalent deflagration position model and theories for deflagration overpressure were developed to clarify the waveform characteristics of deflagration shock wave.Experimental results show that the third collision produced the maximum peak overpressure.,which increased from 0.0607MPa to 0.246MPa as the velocity rose from 594m/s to 819m/s(the impact stress in the range of 2.54GPa to 3.92GPa).The equivalent deflagration model indicates that the intense deflagration reaction occurred within a distance of 20.73mm behind the plates.The peak deflagration overpressure is influenced by several factors,including thickness of the structure's head,the impact velocity,and the thickness of plates,all of which affect the effective initiated mass of the reactive filling.The analytical model aligns well with the experimental results,providing credible support for further investigations into the after-effects of the reactive filling structure.

To explore the explosive shock wave characteristics of typical cylindrical explosives with elliptical cross-section,an experiment on the static explosion of variable-section cylindrical explosives in free field is conducted,and a corresponding numerical simulation model is established.The reliability of the numerically simulated results is verified by comparing with the experimental results.The explosions of cylindrical explosives with different cross-sectional shapes in free field are numerically simulated to investigate the influence of cross-sectional shape on the power characteristics of explosive shock waves.The research results indicate that the explosive shock wave generated by the cylindrical explosives with elliptical cross-section produces a wave system structure similar to that generated by the cylindrical explosives with a circular cross section,but there are differences in the propagation characteristics of shock wave at different azimuth angles.The peak overpressure,maximum impulse,and shock wave velocity in the short-axis direction are all greater than those in the long-axis direction.For elliptical cross-section explosives with different aspect ratios of long axis to short axis,the greater the aspect ratio is,the more significant this difference becomes.An equivalent radius is introduced to fit and obtain a formula for calculating the peak overpressure and the shape factor of peak overpressure,which includes the aspect ratio as a variable,and a deviation between the calculated results and the numerically simulated results is less than 10%.

To further enhance the post-target damage effectiveness of the penetrator with enhanced lateral effect (PELE),a PELE design with spiral slits is proposed.Based on the experimental validation of the numerical simulation model,the penetration,fragmentation and after-effects of PELEs with different structures are studied using the finite element method and the fracture softening and random failure algorithms.The impacts of rotational speed and direction on the fragmentation and damage effectiveness of PELE with spiral slits are also analyzed.The post-target fragmentation dispersions and damage effectivenesses of conventional PELE and PELE with spiral slits are compared through experiments.The results indicate that the penetration of PELE into a 12mm-thick 4340 steel target is divided into two stages:hole formation and hole expansion.During penetration,the fragmentation of the conventional PELE shell is relatively random,while the cracks in PELE with spiral slits propagate along the direction of slits.The initial crack propagation of PELE with axial slits starts near the projectile/target contact interface.The cracks in PELE with spiral slits initiate at the projectile/target contact interface and extend toward the tail along the slit,and the fragments undergo tensile fracture due to circumferential tensile stress.The fragmentation degree of PELE with spiral slits is the highest among three types of PELEs,and its fragment size and dispersion are the most uniform.The dispersion range of its fragments is increased by 38% and 42%,respectively,compared to the conventional PELE and PELE with axial slits.The post-target fragments of conventional PELE and PELE with axial slits exhibit a conical distribution,while the fragments of PELE with spiral slits are approximately planar in distribution.When the rotational direction of projectile is opposite to the slit direction,its fragmentation is more uniform,the fragment dispersion is more even,and the perforation diameter in the target is generally larger.

To address the needs for intelligent decision-making and synchronized strikes in loitering munition swarms and to enable the application of theoretical algorithms on resource-constrained hardware platforms,this study proposes a threat assessment mathematical model and distribution method tailored for Field Programmable Gate Array (FPGA).Utilizing techniques such as Analytic Hierarchy Process (AHP),entropy-based evaluation,and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS),the model incorporates radix sorting and equivalent substitution to construct an FPGA-based threat assessment framework.A multi-node low-latency adaptive delayed detonation method is developed based on a distributed communication architecture and multi-hop data transmission strategy.Comparative simulations on both software and hardware platforms demonstrate the proposed model's efficiency and accuracy,achieving a computation time of 50μs per evaluation.Full-process simulations validate the feasibility of multi-node task allocation,node security,state transitions,and adaptive delayed detonation.Dynamic multi-node experiments further confirm the accuracy and effectiveness of four-node collaborative decision-making.Static end-to-end experiments validate precise synchronized detonation,with a total delay of detonation signal output across four nodes not exceeding 200μs.

In order to solve the problems of high dimensionality,multiple constraints and discontinuity of firepower resource allocation,an objective function of firepower resource allocation is constructed based on the four firepower resource allocation indexes,i.e.,the minimization of the number of missiles used,ballistic crossing,interception probability and maximizing strike timeliness,by considering the constraints such as damage efficiency,interception probability,penetration probability,ammunition quantity and damage level.From the perspective of damage assessment,the damage features are designed,which comprise two categories:1)four operational area features:strike timeliness,comprehensive launch capability,firepower coverage capability,and firepower penetration capability;2)five damage scheme features:total quantity requirement,total cost requirement,damage level satisfaction ability,damage scheme cost-effectiveness ratio,and firepower accessibility.A fitness evaluation model based on fused damage characteristics is developed,enabling the generation of high-quality initial solutions and significantly enhancing the optimization efficiency of the algorithm.Furthermore,the heuristic algorithm of efficient neighborhood search is used to obtain the optimal solution of firepower resource allocation problem.The experimental results show that the proposed algorithm can obtain the optimized results more quickly at the small,medium and large scales compared with GA,PSO,WOA,BSO,DGMBSO and RCI-DGMBSO algorithms,which reflects the strong adaptability and efficiency of the proposed algorithm.

In order to clarify the injury mechanism of human head under blunt ballistic impact,a finite element model fitting the characteristics of Chinese 50th percentile male adult heads is constructed by the material parameter optimization,proportional scaling and fluid-structure interaction methods based on the total human model for safety (THUMS) model.LS-DYNA (Livermore software technology corporation's dynamic analyzer) is taken as a simulation platform,and the arbitrary Lagrangian-Eulerian algorithm is used to define the fluid characteristics of cerebrospinal fluid,optimize the elastic-plastic material parameters of skull and brain tissue,and realize the localization of head size and anatomical structure through mesh deformation technology.The biomechanical response of the model is verified by comparing the data of Nahum cadaver experiment and THUMS model for the typical vulnerable parts,such as forehead,parietal wall,occipital and posterior fossa,of human body.The results show that the peak values of intracranial pressure in the vulnerable area of the improved model are 150kPa,75kPa,53kPa and 69kPa,respectively,and the error between the improved model and the experimental data is 4%-10%,and the shape of the dynamic response curve is consistent.The maximum von Mises stress of brain tissue (29.5kPa) and the principal stress of skull (18.7kPa) are close to the threshold of Marjoux and Yoganandan simulation experiment,which verifies that the proposed model could effectively predict the risk of craniocerebral injury.The assessment based on NATO AEP-103 standard indicates that the peak value of the forehead intracranial pressure under typical impact is 511.1kPa,far exceeding the threshold of skull fracture (150kPa),which highlights the optimization needs of existing protective equipment.The proposed model has strong applicability and can provide reference and theoretical support for head injury assessment and safety protection under blunt ballistic impact.

Bottom mines are typically deployed on the seabed and are designed to damage the surface ships and submarines during underwater explosion.The casing of bottom mine is the key factor influencing the energy output structure of charge underwater explosion (UNDEX).Based on the theory of UNDEX,the coupled Euler-Lagrange (CEL) method is used to establish a numerical model of the UNDEX of cased charge near the seabed.The characteristics of shock wave loads generated by the underwater explosion of cased charge are studied and the effects of various factors,such as charge shape,detonation mode,casing configuration,casing thickness ratio,and casing-to-charge mass ratio,on the characteristics of shock wave loads generated by underwater detonation of charges are analyzed.Furthermore,a casing with a variable wall thickness suitable for near seabed conditions is proposed,which significantly enhances the shock wave load.The results show that the constraint characteristics of the casing can cause the slower attenuation in the shock wave due to the underwater explosion of charge with distance.The casing with variable wall thickness has an enhancing effect on the shock wave load due to the underwater explosion of charges.The peak pressure of shock wave at 800 mm significantly increases with the increase of δ,and the growth rate can reach 9.74%.It can provide reference for the design of underwater weapons.

To develop the electrically-heated composites that have both anti-icing/de-icing functionality and meet load-bearing performance requirements,three types of electrically-heated fabrics containing nickel-chromium alloy wires with parallel spacings of 6.67mm,4.00mm and 2.86mm and their reinforced composites are designed and fabricated based on the tailored fiber placement process.The lowest surface temperature of the composites reaches 87.2℃ within three minutes at 25W.The low-velocity impact properties,electro-thermal properties and compression properties of the composites subjected to 7J impact load are tested and analyzed using a drop weight impact tester,an infrared thermal imager,and a universal testing machine.The results indicate that the impact energy absorption of composite with a the nickel-chromium alloy wire electrically-heated layer is increased by at least 23.6%.The surface temperature of the damaged areas in the electrically-heated composites can still reach above 72.4℃ after impact,and the retention rates of post-impact compressive modulus and compressive strength are 88.73% and 94.97%,respectively.Compared to glass fiber/epoxy composites,the decrease in the parallel spacing of nickel-chromium alloy wires results in a more pronounced delamination phenomenon in the electrically-heated layer under post-impact compressive load.These findings provide practical guidance for the design of electrically-heated composites for aircraft anti-icing/de-icing applications,ensuring a balance between mechanical performance and functional requirements.

Explosion-induced seismic waves have become the main factors inducing secondary disasters such as building collapse and infrastructure damage due to their long wavelength,strong amplitude and fast propagation speed.Based on two kinds of typical explosion-proof equipment,the static explosion tests with different TNT dosages are carried out to study the propagation and attenuation law of explosion-induced seismic waves under three different protection conditions of free-air blast (FAB),steel explosion-proof (SEP) and flexible explosion-proof (FEP).The vibration velocity time-domain responses and main vibration frequency characteristics of SEP and FEP equipment are analyzed.The three-axis peak vibration velocity vector and attenuation models under the protection of SEP and FEP equipment are constructed,and the damage level of building is divided accordingly,which is subdivided into three criteria of safety,slight damage and serious damage.It is found that the vector sum of triaxial peak vibration velocities increases with the increase of TNT charge,and decreases with the increase of detonation distance.The triaxial dominant frequency shows no obvious change rule when the detonation distance or TNT charge increases.Compared with FAB,both SEP and FEP show significant protection performance against the triaxial peak vibration velocity of explosion-induced seismic waves.The research results can provide reference for the structural design of related explosion-proof equipment and the evaluation of explosion-induced seismic wave protection effectiveness.

The staggered layout of urban building complex makes the propagation path of explosion shock wave more complicated,thereby increasing the difficulty of evaluating the damage effect comprehensively and accurately.Numerical simulation methods based on computational fluid dynamics can accurately simulate the blast loading,but the calculated amount is large and the calculation time is long.In order to rapidly predict the blast loading in urban building complex,a fast blast loading prediction method based on neural network is proposed.The influence of the number of training samples on the prediction accuracy and the effect of regional division on the prediction performance of the model are analyzed.In order to meet the data requirements for training the neural network model,the explosion simulation software is used to analyze the mesh sensitivity in a typical dense urban building complex and generate a dataset for 80 sets of explosion scenarios while considering simulation speed and accuracy.In order to determine the appropriate model structure,the fully connected neural networks with different numbers of layers are constructed for comparative experiment and analysis.The effects of the number of training samples,the division of region and the construction of dual models on the prediction accuracy of the model are analyzed through comparative experiments.The results show that the prediction error of the proposed method is less than 10% on 16 sets of test data except the training data,and the inference time only takes 2 seconds.The proposed method has a balanced and good prediction ability for various ranges of peak overpressure,and provides a new approach and perspective for realizing the rapid prediction of blast loading in urban building complex.

The launch of Mars Ascent Vehicle (MAV) is the key technology to realize China's 2030 Mars Sample Return.To study the oblique cold launch technology of MAV,based on the theory of interior ballistics of catapults,a parallel recoilless interior ballistic scheme is designed to meet the launch conditions of Mars.Based on the discrete element method,a discrete element model of Mars soil is established.Additionally,a rigid-flexible coupling dynamics model of the launcher system is constructed.Finally,based on the launch dynamics theory,the entire launch process of the MAV under different working conditions is simulated and analyzed.The results show that the internal ballistics scheme obtained can meet the launch requirements.The recoilless design plays an important role in ensuring the stability of the launch vehicle.Discretization of soil helps to characterize the dynamic behavior of Martian soil.The larger the ground inclination angle,the worse the stability and launch accuracy.Among the four directions at the same inclination angle,the stability of the launch facing uphill is the worst.The “virtual leg” phenomenon can reduce launch stability and may even cause the launch device to topple,leading to launch failure.

In order to study the mechanochemical response behavior of PTFE/Al/W fluoropolymer-matrix reactive materials under shock loading,the drop-weight impact test of fluoropolymer-matrix reactive materials is carried out,and a weak coupling trans-scale numerical calculation method is proposed.Based on this method,a trans-scale numerical simulation model is established for the drop-weight impact loading reaction process of macro-meso scale fluoropolymer-matrix reactive material.The mechanochemical response behaviors and impact activation mechanisms of macroscopic and mesoscopic structures of sample in the drop-weight impact test are discussed and analyzed through trans-scale numerical simulation.The results show that the content of W has a significant effect on the impact activation reaction of fluoropolymer-matrix reactive materials,and the impact activation threshold of the reactive materials system decreases with the increase of W content.The weak coupling trans-scale numerical simulation analysis model effectively simulates the mechanochemical response process of fluoropolymer-matrix reactive materials.The X-shaped shear band is the dominant mechanism for the breakage and activation of fluoropolymer-matrix reactive materials,and its formation,evolution and distribution are greatly affected by W content.

The influences of forebody compression methods and compression levels on the thrust performance of oblique detonation engine (ODE) are studied.The effects of 1-,2-,and 3-stage oblique shocks and compression angles on the thrust performance of hydrogen-air ODE under flight conditions of Mach number 10 and altitude 35km are examined through theoretical analysis.The results indicate a significant enhancement in thrust performance with an increase in the number of compression stages.Within the range of compression angles from 2° to 24°,the fuel specific impulse exhibits an initial increase followed by a decrease with the increase in the compression angle of the 1st stage,while the increases in the angles of the 2nd and 3rd compression lead to a continuous improvement in fuel specific impulse,thus delaying the appearance of peak thrust performance.Analysis of the impact of inlet compression stages on the total pressure at the outlet of inlet duct,the exit of mixing section,and the exit of combustion chamber reveals that the increase in the compression angle of the 1st stage wedge leads to a rapid rise in the outlet airflow temperature of inlet duct,limiting the pressure-gain capability of detonation combustion.Conversely,the multi-stage compression achieves higher combustion product pressure and velocity,thereby enhancing the thrust performance and reducing the total pressure loss.

Ship target segmentation plays a crucial role in enhancing the automation level of marine monitoring systems.However,the existing target segmentation methods often suffers from the issues such as mis-segmentation,susceptibility to noise interference,and low processing efficiency,making them difficult to adapt flexibly and efficiently to real-world scenarios.To address these challenges in maritime ship target segmentation tasks,a segmentation algorithm based on an improved DeepLabV3+ network,termed MET-DeepLabV3+,is proposed.During the image preprocessing stage,the bilateral filtering,multi-scale Retinex algorithm,and linear transformation are employed to mitigate the effects of noise,weather and other adverse factors.In terms of model design,the lightweight MobileNetV2 is used as the backbone network to reduce model complexity,and the ECA-Net attention mechanism is introduced to enhance the model's ability to capture the multi-scale features.Additionally,a transfer learning approach is adopted,and the feature weights pre-trained on the SeaShips dataset are applied to model training to further optimize the segmentation performance.Experimental results demonstrate that the improved algorithm achieves an average interaction-over-union (IoU) of 91.62% and an average pixel accuracy (PA) of 92.87%,which are improved by 2.13% and 1.11%,respectively,compared with those of the baseline DeepLabV3+ model.Moreover,it outperforms the segmentation models such as HRNet,PSPNet,and UNet,which effectively meets the practical demands of ship target segmentation tasks and offers significant application value.

For the target threat assessment in uncertain scenarios,the weights of target threat assessment indexes are difficult to be optimized,and meanwhile the assessment results are poor in anti-interference performance.To deal with these problems,a target threat assessment approach for maritime ships is proposed by adopting intuitionistic fuzzy theory,grey correlation degree and quadratic programming solving methods,which takes into account both the subjective and objective evaluations.Firstly,a two-level and three-layer assessment index system is constructed according to the multi-dimensional capability of warship formation.The intuitionistic fuzzy set is used to quantitatively describe and deal with the uncertainty assessment indexes caused by noise,sensor bias and cognitive fuzzy.The subjective and objective ideal solution mother sequences are defined,and used for computing the grey correlation degrees based on the characteristics of the objective data and the subjective expert's preference,respectively.Then,an attribute index weight optimization model is constructed,which integrates the subjective and objective grey correlation degrees,and the Lagrange method is adopted to solve the optimal weights.Lastly,the impacts of unexpected external interference factors on the credibility of evaluation are considered,and a group generalized intuitionistic fuzzy soft set is used to describe the expert's judgment on the degree of interference in order to correct the evaluation results.The effectiveness of the proposed approach is verified by the simulated results.

In modern complex and dynamic battlefield environments,personnel and equipment are exposed to the threats such as extreme cold,electromagnetic radiation,and bullet impacts.Therefore,there is an urgent need to develop the lightweight and portable multifunctional protective materials.While the existing research explores multifunctional textiles,the physical integration of single-function materials exacerbates mass and cost issues.MS-Twaron multifunctional protective material is made by using MXene materials as the functional layer and aramid fibers (Twaron) as the base material with silicone gel as a surface waterproof layer.The contact angle test,electromagnetic interference (EMI) shielding test,flame retardant test,ballistic test,and photo-thermal experiment are made on MS-Twaron.The results indicate that:1)Compared to the hydrophilic material Twaron (water contact angle of 29.7°),MS-Twaron exhibits the excellent hydrophobic properties (water contact angle of 112.3°); 2)Compared to Twaron which exhibits no EMI properties,MS-Twaron with MXene mass fraction of 8.61% shows an improved EMI properties in X-band,ranging from 13.490dB to 14.969dB; 3)Compared to Twaron,MS-Twaron exhibits a 5.0s increase in afterglow time,a 3.5s reduction in glowing time,and a 5.3mm decrease in average char length.MS-Twaron has impact resistant properties of which the ballistic indentation depth is 6.12mm smaller than that of Twaron.The surface temperature of MS-Twaron can achieve up to 50.22℃ under natural light (light intensity of 100.3×10³ LUX),39.58℃ under incandescent light (100W,30cm),and 97.18℃ under infrared light (375W,40cm).With its integration of lightweight,photothermal and EMI properties,MS-Twaron offers design insights for the next-generation multifunctional protective equipment.

The toroidal propeller is a kind of novel propeller,of which the cavitation characteristics are not yet clear.A three-dimensional numerical model is established to analyze the cavity distribution and cavitation mechanism of toroidal propeller.The toroidal propeller are simulated based on the multiple reference frames method and the Schnerr-Sauer cavitation model,and the cavitation characteristics of toroidal propeller under different rotational speeds and advance coefficients are analyzed.The calculated results of the volume fraction of gas phase under different rotational speeds and advance coefficients show that the cavitation laws of the front and rear edges of toroidal propeller are very different,and the suction surface of the transition section is the most prone to cavitation.The cavitation of the front edge pressure surface always occurs earlier than that of the rear edge pressure surface,while the cavitations of the front and rear edge suction surfaces occur almost simultaneously.The research results can support the further improvement on the noise and hydrodynamic performances of toroidal propeller.

The efficient and accurate detection and tracking of dynamic target features in dark environments,where contours are blurred and occlusions are present,hold practical significance for disaster relief,search and tracking operations.To effectively detect and track the blurred contour features in dark environments,an improved real-time infrared target tracking and detection algorithm is proposed.This algorithm,based on the deep learning network (Spatial Local Dynamic You Only Look Once,SLD-YOLOv8),incorporates a non-local adaptive module and a spatial channel convolution (SCC) correlation module to optimize the Bottleneck CSP of YOLOv8 network for better feature extraction.A dedicated 160×160 detection layer and a dynamic head are introduced for the improved detection of small-scale targets and the enhanced boundary regression capabilities in low-light scenarios,enabling the accurate real-time inference of relative target position.Experimental validation shows that the proposed algorithm has good robustness and accuracy in detecting the dynamic features in dark environments.The average precision evaluation metrics mAP_0.5 and mAP_0.5:0.95 of this model are increased by 5.6% and 4.5%,respectively,compared to the original model,affirming its effectiveness of tracking the targets in dark environments.

To address the issue of low visual resolution caused by imbalanced grayscale in synthetic aperture sonar (SAS) images,a synthetic aperture sonar image equalization method based on the total variation framework is proposed by combining the sonar echo model,speckle noise statistical characteristics,and prior assumptions of decomposition model.The synthetic aperture sonar image decomposition model considering background noise is derived based on the Rayleigh distribution characteristics of multiplicative noise in the image and the maximum likelihood estimation.In response to the terrain and beam patterns of illumination component,the sediment angle response of reflection component,and the influence of noise,an objective function for the decomposition of synthetic aperture sonar images is established through the segmented smoothing constraints on the illumination component,the sediment echo intensity information constraints on the reflection component,and the anisotropic total variation constraints.Finally,after the contrast component is enhanced,a balanced image is obtained by multiplying it with the reflection component.The experimental results show that the proposed method solves the problem of uneven brightness of SAS images,greatly improves image brightness and contrast,and outperforms the methods in noise suppression and image equalization.

The formation mechanism of Airy phase of Scholte wave is studied to clarify its characteristics and variation laws.The wave field expression of Scholte wave excited by pulse sound source are derived based on the shallow water semi-infinite elastic seabed sound field model.The high-order staggered grid finite difference algorithm is used to simulate the Scholte wave excited by the pulse sound source.The relationship between the amplitude of Airy wave and the propagation distance was obtained through simulation.The results show that the frequency dispersion of Scholte wave can cause a minimum group velocity,leading to the appearance of Airy wave during the propagation of the pulse signal,with an amplitude being proportional tor^-5/6.A Scholte wave experiment excited by an airgun sound source on the lake is made,and the moving window analysis method is used to analyze the experiment data.The analyzed results show that there is obvious frequency dispersion phenomenon in the frequency band below 12Hz.When the frequency is higher than 12Hz,the group velocity remaines basically unchanged with the increase in frequency.At the same time,the group velocity showes a first decreasing and then increasing trend with the increase in frequency,reproducing and confirming the dispersion relationship of Scholte wave group velocity in theoretical research.