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Chinese Journal of Polymer Science 2024年第7期42卷 916-925,I0006页

作者： Bin Zhang Zheng-Li Dou Yong-Zheng Zhang qiang fu kai Wu College of Polymer Science and Engineering State Key Laboratory of Polymer Materials EngineeringSichuan UniversityChengdu610065China

Effective thermal transport across solid-solid interfaces which is essential in thermal interface materials(TIMs),necessitates both optimal thixotropy and high thermal *** role of filler surface modification,a fundamental aspect of TIM fabrication,in the influence of these properties is not fully *** study employs the use of a silane coupling agent(SCA)to modify alumina,integrating experimental approaches with molecular dynamics simulations,to elucidate the interface effects on thixotropy and thermal conductivity in polydimethylsiloxane(PDMS)-based *** findings reveal that the variations of SCAs modify both interface binding energy and transition layer *** interface binding energy restricts macromolecular segmental relaxation near the interface,hindering desirable thixotropy and bond line *** the contrary,the thickness of the transition layer at the interface positively influences thermal conductivity,facilitating the transport of phonons between the polymer and ***,selecting an optimal SCA allows a balance between traditionally conflicting goals of high thermal conductivity and minimal bond line thickness,achieving an impressively low interface thermal resistance of just 2.45-4.29 K·mm^(2)·W^(-1)at275.8 kPa.

关键词： Thermal interface material Surface modification Thermal conductivity Thixotropy Interface thermal resistance

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

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Petroleum Science 2024年第4期21卷 2329-2344页

作者： Jiu-qiang Yang Nian-Tian Lin kai Zhang Yan Cui Chao fu Dong Zhang College of Earth Sciences and Engineering Shandong University of Science and Technology Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology Transportation Institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

Preparation of Self-limiting Heating Cables with Excellent Processability, Mechanical Properties and PTC Effect via Thermal and Electrical Treatments

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Chinese Journal of Polymer Science 2024年第4期42卷 511-520页

作者： Tian-Hao Yang Tong Wu qiang fu State Key Laboratory of Polymer Materials Engineering College of Polymer Science and EngineeringSichuan UniversityChengdu610065China State Key Laboratory of Polymer Materials Engineering Polymer Research Institute of Sichuan UniversityChengdu610065China

Polymer/conductive filler composites have been widely used for the preparation of self-limiting heating cables with the positive temperature coefficient (PTC) effect. The control of conductive filler distribution and network in polymer matrix is the most critical for performance of PTC materials. In order to compensate for the destruction of the filler network structure caused by strong shearing during processing, an excessive conductive filler content is usually added into the polymer matrix, which in turn sacrifices its processability and mechanical properties. In this work, a facile post-treatment of the as-extruded cable, including thermal and electrical treatment to produce high-density polyethylene (HDPE)/carbon black (CB) cable with excellent PTC effect, is developed. It is found for the as-extruded sample, the strong shearing makes the CB particles disperse uniformly in HDPE matrix, and 25 wt% CB is needed for the formation of conductive paths. For the thermal-treated sample, a gradually aggregated CB filler structure is observed, which leads to the improvement of PTC effect and the notable reduction of CB content to 20 wt%. It is very interesting to see that for the sample with combined thermal and electrical treatment, CB particles are agglomerated and oriented along the electric field direction to create substantial conductive paths, which leads to a further decrease of CB content down to 15 wt%. In this way, self-limiting heating cables with excellent processability, mechanical properties and PTC effect have simultaneously been achieved.

关键词： Self-limiting heating cables Positive temperature coefficient Thermal treatment Electrical treatment

Super-resolution Imaging of Telescopic Systems based on Optical-neural Network Joint Optimization

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Research in Astronomy and Astrophysics 2024年第9期24卷 167-177页

作者： You-Hong Sun Tao Zhang Hao-Dong Shi qiang fu Jia-Nan Liu kai-kai Wang Chao Wang Research Institute of Chongqing Changchun University of Science and TechnologyChangchun 130022China National and Local Joint Engineering Research Center for Space Photoelectric Technology Changchun University of Science and TechnologyChangchun 130022China The Institute of Remote Sensing Satellites China Academy of Space Technology(CAST)Beijing 100094China

Optical telescopes are an important tool for acquiring optical information about distant objects,and resolution is an important indicator that measures the ability to observe object ***,due to the effects of system aberration,atmospheric seeing,and other factors,the observed image of ground-based telescopes is often degraded,resulting in reduced *** paper proposes an optical-neural network joint optimization method to improve the resolution of the observed image by co-optimizing the point-spread function(PSF)of the telescopic system and the image super-resolution(SR)*** improve the speed of image reconstruction,we designed a generative adversarial net(LCR-GAN)with light parameters,which is much faster than the latest unsupervised *** reconstruct the PSF trained by the network in the optical path,a phase mask is *** improves the image reconstruction effect of LCR-GAN by reconstructing the PSF that best matches the *** results of simulation and verification experiments show that compared with the pure deep learning method,the SR image reconstructed by this method is rich in detail and it is easier to distinguish stars or stripes.

关键词： Techniques:image processing Telescopes Stars:imaging

MADDPG-D2: An Intelligent Dynamic Task Allocation Algorithm Based on Multi-Agent Architecture Driven by Prior Knowledge

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2559-2586页

作者： Tengda Li Gang Wang qiang fu College of Air and Missile Defense Air Force Engineering UniversityXi’an710051China

Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinforce-ment learning(DRL)theory and an improved Multi-Agent Deep Deterministic Policy Gradient(MADDPG-D2)algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of *** algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm,and considers the introduction of a double noise mechanism to increase the action exploration space in the early stage of the algorithm,and the introduction of a double experience pool to improve the data utilization rate;at the same time,in order to accelerate the training speed and efficiency of the agents,and to solve the cold-start problem of the training,the a priori knowledge technology is applied to the training of the ***,the MADDPG-D2 algorithm is compared and analyzed based on the digital battlefield of ground and air *** experimental results show that the agents trained by the MADDPG-D2 algorithm have higher win rates and average rewards,can utilize the resources more reasonably,and better solve the problem of the traditional single agent algorithms facing the difficulty of solving the problem in the high-dimensional decision *** MADDPG-D2 algorithm based on multi-agent architecture proposed in this paper has certain superiority and rationality in DTA.

关键词： Deep reinforcement learning dynamic task allocation intelligent decision-making multi-agent system MADDPG-D2 algorithm

Impact of initial fluctuations and nuclear deformations in isobar collisions

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Nuclear Science and Techniques 2024年第6期35卷 155-162页

作者： Jian-Fei Wang Hao-Jie Xu fu-qiang Wang Department of Modern Physics University of Science and Technology of ChinaHefei 230026China School of Science Huzhou UniversityHuzhou 313000China Strong-Coupling Physics International Research Laboratory(SPiRL) Huzhou UniversityHuzhou 313000China Department of Physics and Astronomy Purdue UniversityWest LafayetteIN 47907USA

Relativistic isobar^(96)_(44)Ru+^(96)_(44)Ru and^(96)_(40)Zr+^(96)_(40)Zrcollisions have revealed intricate differences in their nuclear size and shape,inspiring unconventional studies of nuclear structure using relativistic heavy ion *** this study,we investigate the relative differences in the mean multiplicityR_()and the secondR_(ε2)and third-order eccentricityR_(ε3)between isobar collisions using initial state Glauber *** is found that initial fluctuations and nuclear deformations have negligible effects on R_()in most central collisions,while both are important for the R_(ε2)and R_(ε3),the degree of which is sensitive to the underlying nucleonic or sub-nucleonic degree of *** features,compared to real data,may probe the particle production mechanism and the physics underlying nuclear structure.

关键词： Relativistic isobar collisions Initial fluctuations Nuclear deformation

The Effect of Key Nodes on theMalware Dynamics in the Industrial Control Network

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Computers, Materials & Continua 2024年第4期79卷 329-349页

作者： qiang fu JunWang Changfu Si Jiawei Liu College of Computer Science and Technology Shenyang University of Chemical TechnologyShenyang110142China College of Computer Science and Engineering Northeastern UniversityShenyang110169China

As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security *** paper proposes a model for the industrial control *** includes a malware containment strategy that integrates intrusion detection,quarantine,and ***,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment *** addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction ***,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is *** otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control *** earlier the immunization of key nodes,the *** the time exceeds the threshold,immunizing key nodes is almost *** analysis provides a better way to contain the malware in the industrial control network.

关键词： Key nodes dynamic model industrial control network simulation

Mechanical property of cylindrical sandwich shell with gradient core of entangled wire mesh

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Defence Technology（防务技术） 2024年第1期31卷 510-522页

作者： Xin Xue Chao Zheng fu-qiang Lai Xue-qian Wu Institute of Metal-rubber&Vibration Noise School of Mechanical Engineering and AutomationFuzhou UniversityFuzhou350116China fujian Metallurgical Industry Design Institute Fuzhou350116China

To explore the wide-frequency damping and vibration-attenuation performances in the application of aerospace components,the cylindrical sandwich shell structure with a gradient core of entangled wire mesh was proposed in this ***,the gradient cores of entangled wire mesh in the axial and radial directions were prepared by using an in-house Numerical Control weaving machine,and the metallurgical connection between skin sheets and the gradient core was performed using vacuum ***,to investigate the mechanical properties of cylindrical sandwich shells with axial or radial gradient cores,quasi-static and dynamic mechanical experiments were carried *** primary evaluations of mechanical properties include secant stiffness,natural frequency,Specific Energy Absorption(SEA),vibration acceleration level,and so *** results suggest that the vibration-attenuation performance of the sandwich shell is remarkable when the high-density core layer is at the end of the shell or abuts the inner *** axial gradient material has almost no influence on the vibration frequencies of the shell,whereas the vibration frequencies increase dramatically when the high-density core layer approaches the ***,compared to the conventional sandwich shells,the proposed functional grading cylindrical sandwich shell exhibits more potential in mass reduction,stiffness designing,and energy dissipation.

关键词： Entangled wire mesh Gradient cylindrical sandwich shell Vacuum brazing Secant stiffness Damping

Experimental study and correlation development for the two-phase frictional pressure drop of flow boiling in copper foam fin microchannels

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Science China(Technological Sciences) 2024年第9期67卷 2758-2776页

作者： fu kai XU XiangHua LIANG XinGang School of Aerospace Engineering Tsinghua UniversityBeijing 100084China

Flow boiling in microchannels with porous walls has received extensive attention in recent years. Compared with the emphasis on heat transfer, there is a lack of research on the effect of the porous wall structures on the pressure drop characteristics. In this study, systematic experiments are performed to measure the pressure drop of water-vapor two-phase flow in five microchannels with copper foam fins, which consist of nine or six channels and fins of copper foam. The porosities of the foam fins range from0.78 to 0.82 and ratios of fin width to channel width range from 0.5 to 2. The channels are approximately 0.5 or 1 mm in width and 1 mm in height. Both adiabatic and flow boiling experiments are conducted with water at mass fluxes ranging from 66 to 407 kg/(m^(2)s). In the adiabatic experiments, the average quality in channels is between 0.017 and 0.846. In the flow boiling experiments, the outlet quality of channels is between 0.040 and 0.863. Slug flow, churn flow, annular flow, and wispy-annular flow are observed in adiabatic experiments. A two-phase frictional pressure drop correlation based on the Lockhart-Martinelli model is developed for copper foam fin microchannels by introducing the effects of the mass flux, porosity, ratio of fin width to channel width, and heating condition step by step. The mean absolute percentage errors of the new correlation are 7.53% for 325data points under adiabatic conditions and 5.51% for 268 data points under flow boiling conditions, respectively. This work provides insight into the correlations of frictional pressure drop in microchannels with porous walls.

关键词： two-phase flow boiling pressure drop correlation microchannel copper foam porous wall

Design of quasi-zero-stiffness elastic diodes for low-frequency nonreciprocity through machine learning

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Acta Mechanica Sinica 2024年第7期40卷 137-151页

作者： Junsen He Jiaxi Zhou kai Wang qiang Wang College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082China Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan UniversityChangsha 410082China Department of Mechanical Engineering Hong Kong Polytechnic UniversityHong KongChina

Elastic diodes with nonreciprocity have the potential to enable unidirectional modulation of elastic ***,it is a challenge to achieve nonreciprocity at low frequencies(<100 Hz)using existing elastic *** paper proposes... 详细信息

Elastic diodes with nonreciprocity have the potential to enable unidirectional modulation of elastic ***,it is a challenge to achieve nonreciprocity at low frequencies(fulfill high-quality low-frequency *** proposed elastic diode is invented by combining a QZS locally resonant metamaterial with a linear one,where the beneficial nonlinearity of the QZS metamaterial facilitates opening an amplitude-dependent band gap at very low ***,the dispersion relation of the QZS metamaterial is derived theoretically based on the harmonic balance method(HBM).Then,the transmissibility of the QZS elastic diode in both the forward and backward directions is calculated through theoretical analyses and numerical ***,the influences of system parameters on the low-frequency nonreciprocal effect are *** results indicate that considerable nonreciprocity is observed at a quite low frequency(e.g.,9 Hz),which is achieved by amplitude-dependent local resonance combined with interface ***,a machine learning-based design optimization is introduced to evaluate and enhance the nonreciprocal effect of the QZS elastic *** the aid of machine learning(ML),the computational cost of predicting nonreciprocal effects during design optimization can be significantly *** design optimization,the nonreciprocal frequency bandwidth can be broadened while maintaining considerable isolation quality at low frequencies.

关键词： Nonreciprocity Low-frequency Elastic diode Quasi-zero-stiffness Nonlinear elastic metamaterials Machine learning