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The mechanisms of thermal solidification agent promoting steam diversion in heavy oil reservoirs

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Petroleum science 2024年第3期21卷 1902-1914页

作者： Zhan-Xi Pang qian-Hui Wang qiang Meng Bo Wang Dong Liu State Key Laboratory of Petroleum Resources and Engineering China University of Petroleum(Beijing)Beijing102249China Liaohe Oilfield Institute CNPC ChinaPanjin124000LiaoningChina Henan Oilfield Institute Sinopec ChinaNanyang473400HenanChina Tianjin Branch of china National Offshore Oil Company(CNOOC)Ltd. Tianjin300452China

At high cycles of steam huff&puff,oil distribution in reservoirs becomes stronger heterogeneity due to steam *** solidification agent can be used to solve this *** solution is a lowviscosity liquid at normal temperature,but it can be solidified above 80℃.The plugging degree is up to 99%at 250℃.The sweep efficiency reaches 59.2%,which is 7.3%higher than pure steam *** addition,simultaneous injection of viscosity reducer and/or nitrogen foams can further enhance oil *** mechanism of this technology depends on its strong plugging ability,which changes the flowing pattern of steam to effectively mobilize remaining *** reducer and nitrogen foams further expand the sweep range and extends the effective ***,thermal solidification agent can plug steam channeling paths and adjust steam flowing direction to significantly enhance oil recovery at high cycles of steam huff&puff.

关键词： Heavy oil reservoir Steam huff&puff Steam channeling Steam diversion Plugging performance Mechanism analysis

A deep reinforcement learning approach to gasoline blending real-time optimization under uncertainty

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Chinese Journal of Chemical Engineering 2024年第7期71卷 183-192页

作者： Zhiwei Zhu Minglei Yang Wangli He Renchu He Yunmeng Zhao Feng qian Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

The gasoline inline blending process has widely used real-time optimization techniques to achieve optimization objectives,such as minimizing the cost of ***,the effectiveness of real-time optimization in gasoline blending relies on accurate blending models and is challenged by stochastic ***,we propose a real-time optimization algorithm based on the soft actor-critic(SAC)deep reinforcement learning strategy to optimize gasoline blending without relying on a single blending model and to be robust against *** approach constructs the environment using nonlinear blending models and feedstocks with *** algorithm incorporates the Lagrange multiplier and path constraints in reward design to manage sparse product *** abstracted states facilitate algorithm convergence,and the normalized action vector in each optimization period allows the agent to generalize to some extent across different target production *** these well-designed components,the algorithm based on the SAC outperforms real-time optimization methods based on either nonlinear or linear *** even demonstrates comparable performance with the time-horizon based real-time optimization method,which requires knowledge of uncertainty models,confirming its capability to handle uncertainty without accurate *** simulation illustrates a promising approach to free real-time optimization of the gasoline blending process from uncertainty models that are difficult to acquire in practice.

关键词： Deep reinforcement learning Gasoline blending Real-time optimization Petroleum Computer simulation Neural networks

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

Plasma Surface Modification of Li_(2)TiSiO_(5)Anode for Lithium-Ion Batteries

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Energy Engineering 2024年第10期121卷 2769-2776页

作者： Shangqi Sun Lingchao Xiao Qifeng qian Yunfeng Deng School of Materials science and Engineering Tianjin UniversityTianjin300072China School of Mechanical Engineering and Rail Transit Changzhou UniversityChangzhou213164China Zhejiang Sunoren Solar technology Co. Ltd.Haining314400China

Solving intrinsic structural problems such as low conductivity is the main challenge to promote the commercial application of Li_(2)TiSiO_(5).In this study,Li_(2)TiSiO_(5)is synthesized by the sol-gelmethod,and the surface modification of Li_(2)TiSiO_(5)is carried out at different temperatures using low-temperature plasma to enhance its lithium storage *** morphological structure and electrochemical tests demonstrate that plasma treatment can improve the degree of *** peak position of the plasma-treated Li_(2)TiSiO_(5)is shifted to a lower angle,and the shift angle increases with increasing sputtering ***_(2)TiSiO_(5)after 300 W bombardment shows excellent capacity(144.7 mA·hg^(−1)after 500 cycles at 0.1 Ag^(−1))and rate performance(140 mA·hg^(−1)at 5 Ag^(−1)).Electrochemical analysis indicates that excellent electrochemical performance is attributed to the enhancement of electronic and ionic conductivity by plasma bombardment.

关键词： Plasma Li_(2)TiSiO_(5) surface modification anode

Self-initiated static-dynamic state transition behavior and triggering mechanism of strain rockburst using three-dimensional discrete element method

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Underground Space 2024年第3期16卷 143-163页

作者： Yuan qian Cheng Zhao Rui Wei Rui Zhang Lin Huang Huiguan Chen Department of Geotechnical Engineering College of Civil EngineeringTongji UniversityShanghai 200092China Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education Tongji UniversityShanghai 200092China School of Engineering Tibet UniversityLhasaTibet850000China

The accurate understanding of rockburst mechanism poses a global challenge in the field of rock *** for strain rockburst,achieving self-initiated static-dynamic state transition is a crucial step in the formation of catastrophic ***,the state transition behavior and its impact on rockburst have not received sufficient attention,and are still poorly ***,this study specifically focuses on the state transition behavior,aiming to investigate its abrupt transition process and formation mechanism,and triggering effects on *** facilitate the study,a novel burst rock-surrounding rock combined laboratory test model is proposed and its effectiveness is validated through experiment ***,corresponding numerical models are established using the three-dimensional(3D)discrete element method(DEM),enabling successful simulation of static brittle failure and rockbursts of varying intensities under quasi-static displacement loading ***,through secondary development,comprehensive recording of the mechanical and energy information pertaining to the combined specimen system and its subsystems is *** a result of numerical investigation studies,the elastic rebound dynamic behavior of the surrounding rock was discovered and identified as the key factor triggering rockburst and controlling its *** impact loading on the burst rock,induced by elastic rebound,directly initiates the dynamic processes of rockburst,serving as the direct ***,the transient work and energy convergence towards the burst rock resulting from elastic rebound are recognized as the inherent cause of ***,it has been observed that a larger extent of surrounding rock leads to a stronger elastic rebound,thereby directly contributing to a more intense *** findings can provide novel theoretical insights for the exploring of rockburst mechanism and the development of monitoring and

关键词： Strain rockburst Static-dynamic state transition Self-initiation Triggering mechanism Elastic rebound Discrete element method

Development and Application of a Power Law Constitutive Model for Eddy Current Dampers

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Computer Modeling in Engineering & sciences 2024年第3期138卷 2403-2419页

作者： Longteng Liang Zhouquan Feng Hongyi Zhang Zhengqing Chen Changzhao qian School of Civil Engineering and Architecture Xiamen University of TechnologyXiamen361024China Hunan Provincial Key Laboratory ofWind and Bridge Engineering Hunan UniversityChangsha410082China Fujian Provincial Key Laboratory ofWind Disaster and Engineering Xiamen University of TechnologyXiamen361024China State Key Laboratory of Bridge Engineering Safety and Resilience Hunan UniversityChangsha410082China

Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to theirexceptional damping performance and durability. However, the existing constitutive models present challenges tothe widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA)software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing anewconstitutivemodel that is both easily understandable and user-friendly for FEAsoftware. By utilizing numericalresults obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture thenonlinear behavior of ECDs. The effectiveness of the power law constitutive model is validated throughmechanicalproperty tests and numerical seismic analysis. Furthermore, a detailed description of the application process ofthe power law constitutive model in ANSYS FEA software is provided. To facilitate the preliminary design ofECDs, an analytical derivation of energy dissipation and parameter optimization for ECDs under harmonicmotionis performed. The results demonstrate that the power law constitutive model serves as a viable alternative forconducting dynamic analysis using FEA and optimizing parameters for ECDs.

关键词： Eddy current damper constitutive model finite element analysis vibration control power law constitutive model

Rethinking multi-spatial information for transferable adversarial attacks on speaker recognition systems

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CAAI Transactions on Intelligence technology 2024年第3期9卷 620-631页

作者： Junjian Zhang Hao Tan Le Wang Yaguan qian Zhaoquan Gu Guangzhou university GuangzhouChina Department of New Networks Peng Cheng LaboratoryShenzhenChina Harbin Institute of technology(Shenzhen) ShenzhenChina Zhejiang university of science and technology HangzhouChina

Adversarial attacks have been posing significant security concerns to intelligent systems,such as speaker recognition systems(SRSs).Most attacks assume the neural networks in the systems are known beforehand,while black-box attacks are proposed without such information to meet practical *** black-box attacks improve trans-ferability by integrating multiple models or training on multiple datasets,but these methods are *** by the optimisation strategy with spatial information on the perturbed paths and samples,we propose a Dual Spatial Momentum Iterative Fast Gradient Sign Method(DS-MI-FGSM)to improve the transferability of black-box at-tacks against ***,DS-MI-FGSM only needs a single data and one model as the input;by extending to the data and model neighbouring spaces,it generates adver-sarial examples against the integrating *** reduce the risk of overfitting,DS-MI-FGSM also introduces gradient masking to improve *** authors conduct extensive experiments regarding the speaker recognition task,and the results demonstrate the effectiveness of their method,which can achieve up to 92%attack success rate on the victim model in black-box scenarios with only one known model.

关键词： speaker recognition spoofing attacks

Bioinspired ionic control for energy and information flow

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International Journal of Smart and Nano Materials 2024年第1期15卷 198-221页

作者： Puguang Peng Han qian Jiajin Liu Zhonglin Wang Di Wei beijing Institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijingChina School of Nanoscience and Engineering University of Chinese Academy of SciencesBeijingChina School of Materials science and Engineering Georgia Institute of TechnologyAtlantaGAUSA

The control of ion transport by responding to stimulus is a necessary condition for the existence of *** iontronics could enable anomalous ion dynamics in the nano-confined spaces,creating many efficient energy systems and neuromorphic in-sensor computing networks:Unlike tradi-tional electronics based on von Neumann computing architec-ture,the Boolean logic computing based on the iontronics could avoid complex wiring with higher energy efficiency and programmable neuromorphic ***,a systematic summary on the state of art in bioinspired iontronics is pre-sented and the stimulus from chemical potentials,electric fields,light,heat,piezo and magnetic fields on ion dynamics are *** and perspectives are also addressed in the aspects of iontronic integrated *** is believed that comprehensive investigations in bioinspired ionic control will accelerate the development on more efficient energy and information flow for the futuristic human-machine interface.

关键词： lontronics nanoconfined ion transport ion dynamics bioinspired iontronics ionic-electronic coupling interface

QoS Routing Optimization Based on Deep Reinforcement Learning in SDN

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Computers, Materials & Continua 2024年第5期79卷 3007-3021页

作者： Yu Song Xusheng qian Nan Zhang Wei Wang Ao Xiong State Key Laboratory of Networking and Switching technology Beijing University of Posts and TelecommunicationsBeijing100876China Marketing Service Center State Grid Jiangsu Electric Power Co.Ltd.Nanjing220000China Customer Service Center State Grid Co.Ltd.Nanjing211161China

To enhance the efficiency and expediency of issuing e-licenses within the power sector, we must confront thechallenge of managing the surging demand for data traffic. Within this realm, the network imposes stringentQuality of Service (QoS) requirements, revealing the inadequacies of traditional routing allocation mechanismsin accommodating such extensive data flows. In response to the imperative of handling a substantial influx of datarequests promptly and alleviating the constraints of existing technologies and network congestion, we present anarchitecture forQoS routing optimizationwith in SoftwareDefinedNetwork (SDN), leveraging deep reinforcementlearning. This innovative approach entails the separation of SDN control and transmission functionalities, centralizingcontrol over data forwardingwhile integrating deep reinforcement learning for informed routing decisions. Byfactoring in considerations such as delay, bandwidth, jitter rate, and packet loss rate, we design a reward function toguide theDeepDeterministic PolicyGradient (DDPG) algorithmin learning the optimal routing strategy to furnishsuperior QoS provision. In our empirical investigations, we juxtapose the performance of Deep ReinforcementLearning (DRL) against that of Shortest Path (SP) algorithms in terms of data packet transmission delay. Theexperimental simulation results show that our proposed algorithm has significant efficacy in reducing networkdelay and improving the overall transmission efficiency, which is superior to the traditional methods.

关键词： Deep reinforcement learning SDN route optimization QoS