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Research on simulation of gun muzzle flow field empowered by artificial intelligence

Defence technology（防务技术） 2024年第2期32卷 196-208页

作者： Mengdi Zhou Linfang Qian Congyong Cao Guangsong Chen Jin Kong Ming-hao Tong School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing210094China Northwest Institute of Mechanical and Electrical Engineering Xianyang712099ShaanxiChina School of Automation Nanjing University of Science and TechnologyNanjing210094China

Artificial intelligence technology is introduced into the simulation of muzzle flow field to improve its simulation efficiency in this paper.A data-physical fusion driven framework is ***,the known flow field data is used to initialize the model parameters,so that the parameters to be trained are close to the optimal *** physical prior knowledge is introduced into the training process so that the prediction results not only meet the known flow field information but also meet the physical conservation *** two examples,it is proved that the model under the fusion driven framework can solve the strongly nonlinear flow field problems,and has stronger generalization and *** proposed model is used to solve a muzzle flow field,and the safety clearance behind the barrel side is *** is pointed out that the shape of the safety clearance under different launch speeds is roughly the same,and the pressure disturbance in the area within 9.2 m behind the muzzle section exceeds the safety threshold,which is a dangerous *** with the CFD results shows that the calculation efficiency of the proposed model is greatly improved under the condition of the same calculation *** proposed model can quickly and accurately simulate the muzzle flow field under various launch conditions.

关键词： Muzzle flow field Artificial intelligence Deep learning Data-physical fusion driven Shock wave

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Flow field distribution and overpressure characteristics inside the crew compartment of a truck-mounted howitzer under the effect of muzzle blast

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Defence technology(防务技术) 2025年第2期44卷 190-205页

作者： Shengcheng Wei Linfang Qian Yadong Xu Qiang Yin Xinyu Xiong School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing210094China Northwest Institute of Mechanical and Electrical Engineering Xianyang712099China

The muzzle blast overpressure induces disturbances in the flow field inside the crew compartment(FFICC)of a truck-mounted howitzer during the artillery *** overpressure is the primary factor preventing personnel from firing artillery within the *** investigate the overpressure characteristics of the FFICC,a foreign trade equipment model was used as the research object,and a numerical model was established to analyze the propagation of muzzle blast from the muzzle to the interior of the crew compartment under extreme firing *** comparative verification,the muzzle blast experiment included overpressure data from both the flow field outside the crew compartment(FFOCC)and the FFICC,as well as the acceleration data of the crew compartment structure(Str-CC).The research findings demonstrate that the overpressure-time curves of the FFICC exhibit multi-peak characteristics,while the pressure wave shows no significant *** enclosed nature of the cab hinders the dissipation of pressure wave energy within the FFICC,leading to sustained high-amplitude *** frameskin structure helps attenuate the impact of muzzle blast on the ***,local high overpressure caused by the convex or concave features of the cab's exterior significantly amplifies the overpressure amplitude within the FFICC.

关键词： Truck-mounted howitzer Muzzle blast Flow field inside the crew compartment(FFICC) Overpressure characteristics Flow-structure interaction

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Cooperative Covert Communication in Multi-Antenna Broadcast Channels

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China Communications 2024年第6期21卷 246-260页

作者： Qiao Sen Liu Guangjie Ji Xiaopeng Liu Weiwei School of Electrical and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China School of Automation Nanjing University of Science and TechnologyNanjing 210094China

With the gradual popularization of 5G communications,the application of multi-antenna broadcasting technology has become ***,this study aims to investigate the wireless covert communication in the two-user cooperative multi-antenna broadcast *** focus on the issue that the deteriorated reliability and undetectability are mainly affected by the transmission *** tackle this issue,we design a scheme based on beamforming to increase the reliability and undetectability of wireless covert communication in the multi-antenna broadcast *** first modeled and analyzed the cooperative multi-antenna broadcasting system,and put forward the target *** we use the SCA(successive convex approximation)algorithm to transform the target problem into a series of convex *** the convex problems are solved and the covert channel capacity is *** order to verify the effectiveness of the scheme,we conducted simulation *** simulation results show that the proposed beamforming scheme can effectively improve the reliability and undetectability of covert communication in multi-antenna broadcast channels.

关键词： beamforming covert communication multi-antenna broadcast channels OFDM

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From Extraction to Generation: Multimodal Emotion-Cause Pair Generation in Conversations

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IEEE Transactions on Affective Computing 2024年第2期16卷 1-12页

作者： Ma, Heqing Yu, Jianfei Wang, Fanfan Cao, Hanyu Xia, Rui School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing Jiangsu China

As an important task in emotion analysis, Multimodal Emotion-Cause Pair Extraction in conversations (MECPE) aims to extract all the emotion-cause utterance pairs from a conversation. However, there are two shortcomings in the MECPE task: 1) it ignores emotion utterances whose causes cannot be located in the conversation but require contextualized inference;2) it fails to locate the exact causes that occur in vision or audio modalities beyond text. To address these issues, in this paper, we introduce a new task named Multimodal Emotion-Cause Pair Generation in Conversations (MECPG), which aims to identify the emotion utterances with their emotion categories and generate their corresponding causes in a conversation. To tackle the MECPG task, we construct a dataset based on a benchmark corpus for MECPE. We further propose a generative framework named MONICA, which jointly performs emotion recognition and emotion cause generation with a sequence-to-sequence model. Experiments on our annotated dataset show the superiority of MONICA over several competitive systems. Our dataset and source codes will be publicly released. IEEE

关键词： Emotion Recognition

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Denoising graph neural network based on zero-shot learning for Gibbs phenomenon in high-order DG applications

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Chinese Journal of Aeronautics 2025年第3期38卷 234-248页

作者： Wei AN Jiawen LIU Wenxuan OUYANG Haoyu RU Xuejun LIU Hongqiang LYU College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China

With the availability of high-performance computing technology and the development of advanced numerical simulation methods, Computational Fluid Dynamics (CFD) is becoming more and more practical and efficient in engineering. As one of the high-precision representative algorithms, the high-order Discontinuous Galerkin Method (DGM) has not only attracted widespread attention from scholars in the CFD research community, but also received strong development. However, when DGM is extended to high-speed aerodynamic flow field calculations, non-physical numerical Gibbs oscillations near shock waves often significantly affect the numerical accuracy and even cause calculation failure. Data driven approaches based on machine learning techniques can be used to learn the characteristics of Gibbs noise, which motivates us to use it in high-speed DG applications. To achieve this goal, labeled data need to be generated in order to train the machine learning models. This paper proposes a new method for denoising modeling of Gibbs phenomenon using a machine learning technique, the zero-shot learning strategy, to eliminate acquiring large amounts of CFD data. The model adopts a graph convolutional network combined with graph attention mechanism to learn the denoising paradigm from synthetic Gibbs noise data and generalize to DGM numerical simulation data. Numerical simulation results show that the Gibbs denoising model proposed in this paper can suppress the numerical oscillation near shock waves in the high-order DGM. Our work automates the extension of DGM to high-speed aerodynamic flow field calculations with higher generalization and lower cost.

关键词： Computational fluid dynamics High-order discon tinuous Galerkin method Gibbs phenomenon Graph neural networks Zero-shot learning

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Real-time all-frequency global llumination with radiance caching

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Computational Visual Media 2024年第5期10卷 923-936页

作者： Youxin Xing Gaole Pan Xiang Chen Ji Wu Lu Wang Beibei Wang School of Software Shandong UniversityJinan 250101China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China

Global illumination(GI)plays a crucial role in rendering realistic results for virtual exhibitions,such as virtual car *** scenarios usually include all-frequency bidirectional reflectance distribution functions(BRDFs),although their geometries and light configurations may be *** allfrequency BRDFs in real time remains challenging due to the complex light *** approaches,including precomputed radiance transfer,light probes,and the most recent path-tracing-based approaches(ReSTIR PT),cannot satisfy both quality and performance requirements ***,we propose a practical hybrid global illumination approach that combines ray tracing and cached GI by caching the incoming radiance with *** approach can produce results close to those of ofline renderers at the cost of only approximately 17 ms at runtime and is robust over all-frequency *** approach is designed for applications involving static lighting and geometries,such as virtual exhibitions.

关键词： real-time global illumination all-frequency BRDFs Haar wavelets radiance caching

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Uncertainty quantification of mechanism motion based on coupled mechanism—motor dynamic model for ammunition delivery system

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Defence technology（防务技术） 2024年第3期33卷 125-133页

作者： Jinsong Tang Linfang Qian Longmiao Chen Guangsong Chen Mingming Wang Guangzu Zhou Nanjing University of Science and Technology Nanjing 210094China Northwest Institute of Mechanical and Electrical Engineering Xianyang 712099China

In this paper,a dynamic modeling method of motor driven electromechanical system is presented,and the uncertainty quantification of mechanism motion is investigated based on this *** main contribution is to propose a novel mechanism-motor coupling dynamic modeling method,in which the relationship between mechanism motion and motor rotation is established according to the geometric coordination of the *** advantages of this include establishing intuitive coupling between the mechanism and motor,facilitating the discussion for the influence of both mechanical and electrical parameters on the mechanism,and enabling dynamic simulation with controller to take the randomness of the electric load into *** simulation considering feedback control of ammunition delivery system is carried out,and the feasibility of the model is verified *** on probability density evolution theory,we comprehensively discuss the effects of system parameters on mechanism motion from the perspective of uncertainty *** work can not only provide guidance for engineering design of ammunition delivery mechanism,but also provide theoretical support for modeling and uncertainty quantification research of mechatronics system.

关键词： Ammunition delivery system Electromechanical coupling dynamics Uncertainty quantification Generalized probability density evolution

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A Generative Image Steganography Based on Disentangled Attribute Feature Transformation and Invertible Mapping Rule

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computers, Materials & Continua 2025年第4期83卷 1149-1171页

作者： Xiang Zhang Shenyan Han Wenbin Huang Daoyong Fu School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Engineering Research Center of Digital Forensics Nanjing University of Information Science and TechnologyMinistry of EducationNanjing210044China

Generative image steganography is a technique that directly generates stego images from secret *** traditional methods,it theoretically resists steganalysis because there is no cover ***,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information ***,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping ***,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,***,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute *** noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference ***,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed *** results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden ***,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.

关键词： Image information hiding generative information hiding disentangled attribute feature transformation invertible mapping rule steganalysis resistance

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From light sensing to adaptive learning:hafnium diselenide reconfigurable memcapacitive devices in neuromorphic computing

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Light(science & Applications) 2025年第1期14卷 215-226页

作者： Bashayr Alqahtani Hanrui Li Abdul Momin Syed Nazek El-Atab Electrical and Computer Engineering Program Computer Electrical Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)ThuwalSaudi Arabia Electrical Engineering Department College of EngineeringPrincess Nourah Bint Abdulrahman University(PNU)RiyadhSaudi Arabia

Advancements in neuromorphic computing have given an impetus to the development of systems with adaptive behavior,dynamic responses,and energy efficiency *** charge-based or emerging memory technologies such as memristors have been developed to emulate synaptic plasticity,replicating the key functionality of neurons—integrating diverse presynaptic inputs to fire electrical impulses—has remained *** this study,we developed reconfigurable metal-oxide-semiconductor capacitors(MOSCaps)based on hafnium diselenide(HfSe2).The proposed devices exhibit(1)optoelectronic synaptic features and perform separate stimulus-associated learning,indicating considerable adaptive neuron emulation,(2)dual light-enabled charge-trapping and memcapacitive behavior within the same MOSCap device,whose threshold voltage and capacitance vary based on the light intensity across the visible spectrum,(3)memcapacitor volatility tuning based on the biasing conditions,enabling the transition from volatile light sensing to non-volatile optical data *** reconfigurability and multifunctionality of MOSCap were used to integrate the device into a leaky integrate-and-fire neuron model within a spiking neural network to dynamically adjust firing patterns based on light stimuli and detect exoplanets through variations in light intensity.

关键词： integrate volatile integrating

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A new method for evaluating the firing precision of multiple launch rocket system based on Bayesian theory

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Defence technology（防务技术） 2024年第2期32卷 232-241页

作者： Yunfei Miao Guoping Wang Wei Tian College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and AstronauticsNanjingJiangsuChina Institute of Launch Dynamics Nanjing University of Science and TechnologyNanjingJiangsuChina

How to effectively evaluate the firing precision of weapon equipment at low cost is one of the core contents of improving the test level of weapon system.A new method to evaluate the firing precision of the MLRS considering the credibility of simulation system based on Bayesian theory is proposed in this *** of all,a comprehensive index system for the credibility of the simulation system of the firing precision of the MLRS is constructed combined with the group analytic hierarchy process.A modified method for determining the comprehensive weight of the index is established to improve the rationality of the index weight *** Bayesian posterior estimation formula of firing precision considering prior information is derived in the form of mixed prior distribution,and the rationality of prior information used in estimation model is discussed *** the simulation tests,the different evaluation methods are compared to validate the effectiveness of the proposed ***,the experimental results show that the effectiveness of estimation method for firing precision is improved by more than 25%.

关键词： Multiple launch rocket system Bayesian theory Simulation credibility Mixed prior distribution Firing precision

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