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Chinese Journal of Electronics 2024年第1期33卷 128-138页

作者： Jinxue peng Yong WANG Jingfeng XUE Zhenyan LIU School of Computer Science and Technology Beijing Institute of Technology

Cross-platform binary code similarity detection aims at detecting whether two or more pieces of binary code are similar or not. Existing approaches that combine control flow graphs(CFGs)-based function representation and graph convolutional network(GCN)-based similarity analysis are the best-performing ones. Due to a large amount of convolutional computation and the loss of structural information, the use of convolution networks will inevitably bring problems such as high overhead and sometimes inaccuracy. To address these issues, we propose a fast cross-platform binary code similarity detection framework that takes advantage of natural language processing(NLP)and inductive graph neural network(GNN) for basic blocks embedding and function representation respectively by simulating extracting structural features and temporal features. GNN’s node-centric and small batch is a suitable training way for large CFGs, it can greatly reduce computational overhead. Various NLP basic block embedding models and GNNs are evaluated. Experimental results show that the scheme with long short term memory(LSTM)for basic blocks embedding and inductive learning-based Graph SAGE(GAE) for function representation outperforms the state-of-the-art works. In our framework, we can take only 45% overhead. Improve efficiency significantly with a small performance trade-off.

关键词： Training Semantics Process control Binary codes Feature extraction Natural language processing Graph neural networks

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Hole cleaning evaluation and installation spacing optimization of cuttings bed remover in extended-reach drilling

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Petroleum Science 2024年第3期21卷 2005-2022页

作者： Shuo peng Wen-Jun Huang De-Li Gao MOE Key Laboratory of Petroleum Engineering China University of Petroleum-BeijingBeijing102249China State Key Laboratory of Petroleum Resources and Engineering China University of Petroleum-BeijingBeijing102249China

In extended-reach or long-horizontal drilling,cuttings usually deposit at the bottom of the *** cuttings accumulate to a certain thickness,complex problems such as excessive torque and drag,tubing buckling,and pipe stuck probably occur,which results in a lot of non-productive time and remedial *** bed remover can efficiently destroy deposited cuttings in time through hydraulic and mechanical stirring *** paper aims to build a method for hole cleaning evaluation and installation spacing optimization of cuttings bed remover to improve the wellbore cleaning ***,a Computational Fluid Dynamics approach with Eulerian—Eulerian multiphase model was utilized to investigate the mechanism of cuttings transportation,and a new type of cuttings bed remover was ***,an evaluation method of hole cleaning effect of remover was *** that,the effects of several drilling parameters on hole cleaning including flow rate of drilling fluid,rotational speed of drillpipe,rate of penetration,wellbore size,rheological property of drilling fluid,and remover eccentricity on the performance of cuttings bed remover were *** results demonstrate that the new type of remover with streamline blade performs better than conventional *** efficiency of hole cleaning is greatly improved by increasing the rotational speed of drillpipe,flow rate of drilling fluid,remover eccentricity,and 6 rpm Fann dial reading for drilling *** higher rate of penetration and large wellbore size result in worse hole *** findings can serve as an important guide for the structure optimization design of cuttings bed remover and installation spacing of removers.

关键词： Extended-reach drlling Drilling hydraulics Cuttings transport Hole cleaning Cuttings bed remover

Recorded recurrent deep reinforcement learning guidance laws for intercepting endoatmospheric maneuvering missiles

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Defence Technology（防务技术） 2024年第1期31卷 457-470页

作者： Xiaoqi Qiu peng Lai Changsheng Gao Wuxing Jing Department of Aerospace Engineering Harbin Institute of TechnologyHarbin150001China Shanghai Electro-Mechanical Engineering Institute Shanghai Academy of Spaceflight TechnologyShanghai201100China

This work proposes a recorded recurrent twin delayed deep deterministic(RRTD3)policy gradient algorithm to solve the challenge of constructing guidance laws for intercepting endoatmospheric maneuvering missiles with uncertainties and observation *** attack-defense engagement scenario is modeled as a partially observable Markov decision process(POMDP).Given the benefits of recurrent neural networks(RNNs)in processing sequence information,an RNN layer is incorporated into the agent’s policy network to alleviate the bottleneck of traditional deep reinforcement learning methods while dealing with *** measurements from the interceptor’s seeker during each guidance cycle are combined into one sequence as the input to the policy network since the detection frequency of an interceptor is usually higher than its guidance *** training,the hidden states of the RNN layer in the policy network are recorded to overcome the partially observable problem that this RNN layer causes inside the *** training curves show that the proposed RRTD3 successfully enhances data efficiency,training speed,and training *** test results confirm the advantages of the RRTD3-based guidance laws over some conventional guidance laws.

关键词： Endoatmospheric interception Missile guidance Reinforcement learning Markov decision process Recurrent neural networks

Nonlinear metamaterial enabled aeroelastic vibration reduction of a supersonic cantilever wing plate

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Applied Mathematics and Mechanics(English Edition) 2024年第10期45卷 1749-1772页

作者： peng SHENG Xin FANG Dianlong YU Jihong WEN Laboratory of Science and Technology on Integrated Logistics Support College of Intelligence Science and TechnologyNational University of Defense TechnologyChangsha 410073China

The violent vibration of supersonic wings threatens aircraft *** paper proposes the strongly nonlinear acoustic metamaterial(NAM)method to mitigate aeroelastic vibration in supersonic wing *** employ the cantilever plate to simulate the practical behavior of a *** aeroelastic vibration model of the NAM cantilever plate is established based on the mode superposition method and a modified third-order piston *** aerodynamic properties are systematically studied using both the timedomain integration and frequency-domain harmonic balance *** presenting the flutter and post-flutter behaviors of the NAM wing,we emphasize more on the preflutter broadband vibration that is prevalent in *** results show that the NAM method can reduce the low-frequency and broadband pre-flutter steady vibration by 50%-90%,while the post-flutter vibration is reduced by over 95%,and the critical flutter velocity is also slightly *** clarified,the significant reduction arises from the bandgap,chaotic band,and nonlinear resonances of the NAM *** reduction effect is robust across a broad range of parameters,with optimal performance achieved with only 10%attached *** work offers a novel approach for reducing aeroelastic vibration in aircraft,and it expands the study of nonlinear acoustic/elastic metamaterials.

关键词： nonlinear acoustic metamaterial(NAM) hypersonic aeroelastic vibration vibration reduction fluid-structure interaction

An axisymmetric characteristic model for enhancing prediction of centrifugal compressor characteristics

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Chinese Journal of Aeronautics 2024年第4期37卷 203-215页

作者： peng REN Xiangjun FANG Zeyu JIAO Ying HAN School of Energy and Power Engineering Beihang UniversityBeijing 100191China Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent ManufacturingGuangdong Academy of SciencesGuangzhou 510070China

Rapid and accurate determination of compressor characteristic maps is essential for the initial design of centrifugal compressors in aircraft power systems. The accuracy of existing methodologies, which rely on combinations of loss models, varies significantly depending on the compressor's geometry and operational range. This variance necessitates substantial experimental or Computational Fluid Dynamics(CFD) data for coefficient calibration. To address this challenge, this study presents an axisymmetric characteristic model for compressor performance assessment. This model incorporates the factors of blade angle, meridional passage area, and the radial deflection angle of meridional streamlines of the compressor. These factors are derived from fundamental aerodynamic equations encompassing mass, momentum, and energy conservation of the compressor. In contrast to conventional one-dimensional approaches, the proposed method reduces the number of loss coefficients and more effectively accounts for the impact of geometric alterations on centrifugal compressor properties. Furthermore, the model reduces dependence on experimental and CFD data. Efficacy of the model is validated using experimental data from four distinct types of centrifugal compressors. Correlation analysis reveals that the model's coefficients can be expressed as functions of the ratio of the Reynolds number to the impeller tip speed. This ratio serves as a characteristic parameter for the design and optimization of centrifugal compressors. Consequently, the proposed method offers an efficient and accurate means for the quick computation of centrifugal compressor characteristics. This is of great significance for improving the efficiency of centrifugal compressors and reducing energy consumption.

关键词： Centrifugal compressor Positive problem Characteristic prediction Aerodynamic characteristic Axisymmetric model

Differences in and factors controlling organic matter enrichment in the Ziliujing Formation shale in the Sichuan Basin

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Petroleum Science 2024年第1期21卷 77-86页

作者： peng Li Zhong-Bao Liu He Bi Tao Jiang Rui-Kang Bian peng-Wei Wang Xiao-Yu Shang State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Efficient Development Beijing102206China Key Laboratory of Shale Oil/Gas Exploration and Production Technology SINOPECBeijing102206China Petroleum Exploration and Production Research Institute SINOPECBeijing102206China Research Institute of Petroleum Exploration and Development PetroChinaBeijing100083China Chinese Academy of Geological Sciences Beijing100037China No.4 Oil Production Plant in Daqing Oilfield Co Ltd. Daqing163511HeilongjiangChina

Lacustrine shale oil and gas are important fields for unconventional exploration and development in China,and organic-rich shale deposition lays down the critical foundation for hydrocarbon *** are two sets of shale,the Dongyuemiao and Da’anzhai Members,in the Ziliujing Formation in the Sichuan *** identify the differential enrichment characteristics of organic matter and clarify its controlling factors,geochemical analyses of organic and inorganic geochemical analyses were *** results showed that the total organic carbon content of the Dongyuemiao shale(1.36%)is slightly higher than that of the Da’anzhai shale(0.95%).The enrichment of organic matter in the two shales resulted from the comprehensive controls of paleoproductivity,paleoenvironment,and terrigenous input,but different factors have different *** addition,driven by climate,the change in the sulfate concentration in the bottom water further led to the different intensities of bacterial sulfate reduction in early *** made a great difference regarding organic matter accumulation in the two *** general,climate may have played a dominant role in organic matter enrichment in the two sets of shale.

关键词： Lacustrine shale Ziliujing Formation Sichuan Basin Enrichment mechanism of organic matter

Friction of graphene on a substrate with a cavity defect

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Science China(Technological Sciences) 2024年第9期67卷 2834-2841页

作者： ZHOU peng HUO ZhanLei CHANG TienChong Shanghai Institute of Applied Mathematics and Mechanics Shanghai Key Laboratory of Mechanics in Energy EngineeringShanghai Frontier Science Center of MechanoinformaticsSchool of Mechanics and Engineering ScienceShanghai UniversityShanghai 200072China The Center for Computational Mechanics and Engineering Applications Provincial Mechanics Experimental Teaching Demonstration CenterSchool of Civil EngineeringHebei University of EngineeringHandan 056038China Shanghai Institute of Aircraft Mechanics and Control Tongji UniversityShanghai 200092China Joint-Research Center for Computational Materials Zhejiang LaboratoryHangzhou 311100China

The frictional behavior of supported graphene is known to be influenced by the physical properties and surface morphologies of the underlying substrate. However, it is unclear how a surface defect on the substrate affects the friction of supported graphene,and it is even unknown how to define the defect-induced friction force in this context. Here we conduct molecular dynamics(MD) simulations to investigate the friction between a square diamond slider and a graphene sheet supported by a copper substrate with a surface cavity defect. Our results demonstrate that the defect-induced friction exhibits a nonlinear increase with cavity size, while it decreases nonlinearly with slider size. We propose that the definition of defect-induced friction can be linked to the increase in friction work over the length of the slider, and is closely correlated to the defect-induced relative change in indentation depth and the ratio of the cavity area to the contact area. These findings provide a comprehensive evaluation of the impact of a substrate cavity defect on the friction of supported graphene and offer insights that may have broader implications for understanding defect-induced friction in other two-dimensional materials.

关键词： friction graphene underneath substrate cavity defect

Real-time hybrid method for maneuver detection and estimation of non-cooperative space targets

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Astrodynamics 2024年第3期8卷 437-453页

作者： peng Zhang Di Wu Hexi Baoyin School of Aerospace Engineering Tsinghua UniversityBeijing100084China

A novel hybrid scheme for the maneuver detection and estimation of a noncooperative space target was proposed in this *** optical measurements,together with the range and range rate measurements from the ground-based radars,were used in the tracking *** many tracking scenarios,radar resources for non-cooperative targets are constrained,particularly for near-earth targets,where multiple objects can only be tracked by a single radar at a *** limitation hinders the accurate estimation of noncooperative target maneuvers,and can at times result in target *** literature has addressed this issue to some extent through various maneuvering target-tracking *** address this problem,a hybrid maneuver detection and estimation method that combines the input detection and estimation extended kalman filter and the weighted nonlinear least squares method is *** results demonstrate that the proposed method outperforms the previous method,offering more accurate and efficient estimations.

关键词： orbit determination unknown maneuver maneuver detection and estimation extended Kalman filter weighted least squares method(WLS)

A hybrid machine learning optimization algorithm for multivariable pore pressure prediction

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Petroleum Science 2024年第1期21卷 535-550页

作者： Song Deng Hao-Yu Pan Hai-Ge Wang Shou-Kun Xu Xiao-peng Yan Chao-Wei Li Ming-Guo peng Hao-Ping peng Lin Shi Meng Cui Fei Zhao School of Petroleum and Natural Gas Engineering Changzhou UniversityChangzhou213164JiangsuChina Tubular Goods Research Institute of CNPC Beijing102249China CNPC Engineering Technology R&D Company Limited Beijing102206China

Pore pressure is essential data in drilling design,and its accurate prediction is necessary to ensure drilling safety and improve drilling *** methods for predicting pore pressure are limited when forming particular structures and *** this paper,a machine learning algorithm and effective stress theorem are used to establish the transformation model between rock physical parameters and pore *** study collects data from three *** 1 had 881 data sets for model training,and Wells 2 and 3 had 538 and 464 data sets for model *** this paper,support vector machine(SVM),random forest(RF),extreme gradient boosting(XGB),and multilayer perceptron(MLP)are selected as the machine learning algorithms for pore pressure *** addition,this paper uses the grey wolf optimization(GWO)algorithm,particle swarm optimization(PSO)algorithm,sparrow search algorithm(SSA),and bat algorithm(BA)to establish a hybrid machine learning optimization algorithm,and proposes an improved grey wolf optimization(IGWO)*** IGWO-MLP model obtained the minimum root mean square error(RMSE)by using the 5-fold cross-validation method for the training *** the pore pressure data in Well 2 and Well 3,the coefficients of determination(R^(2))of SVM,RF,XGB,and MLP are 0.9930 and 0.9446,0.9943 and 0.9472,0.9945 and 0.9488,0.9949 and *** achieves optimal performance on both training and test data,and the MLP model shows a high degree of *** indicates that the IGWO-MLP is an excellent predictor of pore pressure and can be used to predict pore pressure.

关键词： Pore pressure Grey wolf optimization Multilayer perceptron Effective stress Machine learning

Heterophilic Graph Neural Network Based on Spatial and Frequency Domain Adaptive Embedding Mechanism

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1701-1731页

作者： Lanze Zhang Yijun Gu Jingjie peng College of Information and Cyber Security People’s Public Security University of ChinaBeijing100038China

Graph Neural Networks(GNNs)play a significant role in tasks related to homophilic *** GNNs,based on the assumption of homophily,employ low-pass filters for neighboring nodes to achieve information aggregation and ***,in heterophilic graphs,nodes from different categories often establish connections,while nodes of the same category are located further apart in the graph *** characteristic poses challenges to traditional GNNs,leading to issues of“distant node modeling deficiency”and“failure of the homophily assumption”.In response,this paper introduces the Spatial-Frequency domain Adaptive Heterophilic Graph Neural Networks(SFA-HGNN),which integrates adaptive embedding mechanisms for both spatial and frequency domains to address the aforementioned ***,for the first problem,we propose the“Distant Spatial Embedding Module”,aiming to select and aggregate distant nodes through high-order randomwalk transition probabilities to enhance modeling *** the second issue,we design the“Proximal Frequency Domain Embedding Module”,constructing adaptive filters to separate high and low-frequency signals of nodes,and introduce frequency-domain guided attention mechanisms to fuse the relevant information,thereby reducing the noise introduced by the failure of the homophily *** deploy the SFA-HGNN on six publicly available heterophilic networks,achieving state-of-the-art results in four of ***,we elaborate on the hyperparameter selection mechanism and validate the performance of each module through experimentation,demonstrating a positive correlation between“node structural similarity”,“node attribute vector similarity”,and“node homophily”in heterophilic networks.

关键词： Heterophilic graph graph neural network graph representation learning failure of the homophily assumption