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Pre-Training Physics-Informed Neural Network with Mixed Sampling and Its Application in High-Dimensional Systems

Journal of Systems Science & Complexity 2024年第2期37卷 494-510页

作者： LIU Haiyi ZHANG Yabin WANG Lei School of Mathematics and Physics North China Electric Power UniversityBeijing 102206China School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China

Recently,the physics-informed neural network shows remarkable ability in the context of solving the low-dimensional nonlinear partial differential ***,for some cases of high-dimensional systems,such technique may be time-consuming and *** this paper,the authors put forward a pre-training physics-informed neural network with mixed sampling(ppiNN)to address these *** based on the initial and boundary conditions,the authors design the pre-training stage to filter out the set of the misfitting points,which is regarded as part of the training points in the next *** authors further take the parameters of the neural network in Stage 1 as the initialization in Stage *** advantage of the proposed approach is that it takes less time to transfer the valuable information from the first stage to the second one to improve the calculation accuracy,especially for the high-dimensional *** verify the performance of the ppiNN algorithm,the authors first focus on the growing-and-decaying mode of line rogue wave in the Davey-Stewartson I *** case is the accelerated motion of lump in the inhomogeneous Kadomtsev-Petviashvili equation,which admits a more complex evolution than the uniform *** exact solution provides a perfect sample for data experiments,and can also be used as a reference frame to identify the performance of the *** experiments confirm that the ppiNN algorithm can improve the prediction accuracy and training efficiency well,and reduce the training time to a large extent for simulating nonlinear waves of high-dimensional equations.

关键词： High-dimensional systems mixed sampling nonlinear wave pre-training physics-informed neural network

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Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

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Petroleum Science 2024年第2期21卷 1062-1080页

作者： Zhao-Qin Huang Zhao-Xu Wang Hui-Fang Hu Shi-Ming Zhang Yong-Xing Liang Qi Guo Jun Yao School of Petroleum Engineering China University of Petroleum(East China)Qingdao266580ShandongChina Exploration and Development Research Institute Shengli OilfieldSINOPECDongying257015ShandongChina

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in china's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention *** on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

关键词： Graph neural network Dynamic interwell connectivity Production-injection splitting Attention mechanism Multi-layer reservoir

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Study on thermal decomposition kinetics of azobenzene-4,4′-dicarboxylic acid by using compensation parameter method and nonlinear fitting evaluation

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Chinese Journal of Chemical Engineering 2024年第6期70卷 269-279页

作者： Shuyi Shen Song Guo Sining Chen Jinhua Zhao Nanjing University of Science&Technology Nanjing 210094China china Academy of Safety Science and Technology Beijing 100012China

Recently,azobenzene-4,4'-dicarboxylic acid(ADCA)has been produced gradually for use as an organic synthesis or pharmaceutical intermediate due to its eminent *** large quantities put into application in the future,the thermal stability of this substance during storage,transportation,and use will become quite ***,in this work,the thermal decomposition behavior,thermal decomposition kinetics,and thermal hazard of ADCA were *** were conducted by using a SENSYS evo DSC device.A combination of differential iso-conversion method,compensation parameter method,and nonlinear fitting evaluation were also used to analyze thermal kinetics and mechanism of ADCA *** results show that when conversion rate α increases,the activation energies of ADCA's first and main decomposition peaks *** amount of heat released during decomposition varies between 182.46 and 231.16 J·g^(-1).The proposed kinetic equation is based on the Avrami-Erofeev model,which is consistent with the decomposition *** the Frank-Kamenetskii model,a calculated self-accelerating decomposition temperature of 287.0℃is obtained.

关键词： Azobenzene-4,4′-dicarboxylic acid Thermal decomposition behavior Kinetic mechanism Thermal hazard evaluation Compensation parameter effect

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Self-supervised recalibration network for person re-identification

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Defence Technology（防务技术） 2024年第1期31卷 163-178页

作者： Shaoqi Hou Zhiming Wang Zhihua Dong Ye Li Zhiguo Wang Guangqiang Yin Xinzhong Wang Shenzhen Institute of Information Technology Shenzhen518172China University of Electronic Science and Technology of china Chengdu611731China Kash Institute of Electronics and Information Industry Kashi844099China

The attention mechanism can extract salient features in images,which has been proved to be effective in improving the performance of person re-identification(Re-ID).However,most of the existing attention modules have the following two shortcomings:On the one hand,they mostly use global average pooling to generate context descriptors,without highlighting the guiding role of salient information on descriptor generation,resulting in insufficient ability of the final generated attention mask representation;On the other hand,the design of most attention modules is complicated,which greatly increases the computational cost of the *** solve these problems,this paper proposes an attention module called self-supervised recalibration(SR)block,which introduces both global and local information through adaptive weighted fusion to generate a more refined attention *** particular,a special"Squeeze-Excitation"(SE)unit is designed in the SR block to further process the generated intermediate masks,both for nonlinearizations of the features and for constraint of the resulting computation by controlling the number of ***,we combine the most commonly used Res Net-50 to construct the instantiation model of the SR block,and verify its effectiveness on multiple Re-ID datasets,especially the mean Average Precision(m AP)on the Occluded-Duke dataset exceeds the state-of-the-art(SOTA)algorithm by 4.49%.

关键词： Person re-identification Attention mechanism Global information Local information Adaptive weighted fusion

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CO_(2)flooding in shale oil reservoir with radial borehole fracturing for CO_(2)storage and enhanced oil recovery

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Petroleum Science 2024年第1期21卷 519-534页

作者： Jia-Cheng Dai Tian-Yu Wang Jin-Tao Weng Kang-Jian Tian Li-Ying Zhu Gen-Sheng Li State Key Laboratory of Petroleum Resources and Prospecting China University of PetroleumBeijing102249China china National Oil and Gas Exploration and Development Company Limited Beijing100034China

This study introduces a novel method integrating CO_(2)flooding with radial borehole fracturing for enhanced oil recovery and CO_(2)underground storage,a solution to the limited vertical stimulation reservoir volume in horizontal well fracturing.A numerical model is established to investigate the production rate,reservoir pressure field,and CO_(2)saturation distribution corresponding to changing time of CO_(2)flooding with radial borehole fracturing.A sensitivity analysis on the influence of CO_(2)injection location,layer spacing,pressure difference,borehole number,and hydraulic fractures on oil production and CO_(2)storage is *** CO_(2)flooding process is divided into four *** in layer spacing will significantly improve oil production rate and gas storage ***,serious gas channeling can occur when the spacing is lower than 20 *** the pressure difference between the producer and injector,the borehole number,the hydraulic fracture height,and the fracture width can also increase the oil production rate and gas storage *** analysis shows that layer spacing and fracture height greatly influence gas storage and oil *** outcomes are expected to provide a theoretical basis for the efficient development of shale oil reservoirs in the vertical direction.

关键词： Shale oil Radial borehole fracturing Embedded discrete fracture model Enhanced oil recovery Carbon storage

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Geochemistry and origins of hydrogen-containing natural gases in deep Songliao Basin,china:Insights from continental scientific drilling

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Petroleum Science 2024年第2期21卷 741-751页

作者： Shuang-Biao Han Chao-Han Xiang Xin Du Lin-Feng Xie Jie Huang Cheng-Shan Wang College of Geoscience and Surveying Engineering China University of Mining and TechnologyBeijing100083China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesBeijing100083China

The different reservoirs in deep Songliao Basin have non-homogeneous lithologies and include multiple layers with a high content of hydrogen *** gas composition and stable isotope characteristics vary significantly,but the origin analysis of different gas types has previously been *** on the geochemical parameters of gas samples from different depths and the analysis of geological settings,this research covers the diverse origins of natural gas in different *** gas components are mainly methane with a small amount of C_(2+),and non-hydrocarbon gases,including nitrogen(N_(2)),hydrogen(H_(2)),carbon dioxide(CO_(2)),and helium(He).At greater depth,the carbon isotope of methane becomes heavier,and the hydrogen isotope points to a lacustrine sedimentary *** increasing depth,the origins of N_(2)and CO_(2)change gradually from a mixture of organic and inorganic to *** origins of hydrogen gas are complex and include organic sources,water radiolysis,water-rock(Fe^(2+)-containing minerals)reactions,and *** shales of Denglouku and Shahezi Formations,as source rocks,provide the premise for generation and occurrence of organic ***,the deep faults and fluid activities in Basement Formation control the generation and migration of mantle-derived *** discovery of a high content of H_(2)in study area not only reveals the organic and inorganic association of natural-gas generation,but also provides a scientific basis for the exploration of deep hydrogen-rich gas.

关键词： Gas compositions Stable isotopes Gas origins Hydrogen gas Songliao Basin

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Boron nitride silicone rubber composite foam with low dielectric and high thermal conductivity

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Chinese Journal of Chemical Engineering 2024年第4期68卷 224-230页

作者： Shuilai Qiu Hang Wu Fukai Chu Lei Song College of Safety and Ocean Engineering China University of Petroleum-BeijingBeijing 102249China State Key Laboratory of Fire Science University of Science and Technology of ChinaHefei 230026China

Silicone rubber(SR)is widely used in the field of electronic packaging because of its low dielectric *** this work,the porosity of the SR was improved,and the dielectric constant of the SR foam was reduced by adding expanded microspheres(EM).Then,the thermal conductivity of the system was improved by combining the modified boron nitride(f-BN).The results showed that after the f-BN was added,the dielectric constant and dielectric loss were much lower than those of pure ***-sized modified boron nitride(f-mBN)improved the dielectric and thermal conductivity of the SR foam better than that of nano-sized modified boron nitride(f-nBN),but f-nBN improved the volume resistivity,tensile strength,and thermal stability of the SR better than *** the mass ratio of f-mBN and fnBN is 2:1,the thermal conductivity of the SR foam reaches the maximum value of 0.808 W·m^(-1)·K^(-1),which is 6.5 times that before the *** heat release rate and fire growth index are the lowest,and the improvement in flame retardancy is mainly attributed to the high thermal stability and physical barrier of f-BN.

关键词： Foam Composites Dielectric properties Thermal conductivity Mechanical properties Flame retardant

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Prediction of impurity spectrum function by deep learning algorithm

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Chinese Physics B 2024年第5期33卷 52-63页

作者：刘婷韩榕生陈亮 School of Mathematics and Physics North China Electric Power UniversityBeijing 102206China Institute of Condensed Matter Physics North China Electric Power UniversityBeijing 102206China Hebei Key Laboratory of Physics and Energy Technology North China Electric Power UniversityBaoding 071003China

By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity *** dataset contains the density of states(DOS)of the host material,the strength of Coulomb interaction between on-site electrons(U),and the hybridization between the host material and the impurity site(Γ).The continued DOS and spectral functions are stored with Chebyshev coefficients and wavelet functions,*** this dataset,we build seven different machine learning networks to predict the spectral function from the input data,DOS,U,andΓ.Three different evaluation indexes,mean absolute error(MAE),relative error(RE)and root mean square error(RMSE),are used to analyze the prediction abilities of different network *** analysis shows that,for the two kinds of widely used recurrent neural networks(RNNs),gate recurrent unit(GRU)has better performance than the long short term memory(LSTM)network.A combination of bidirectional GRU(BiGRU)and GRU has the best performance among GRU,BiGRU,LSTM,and *** MAE peak of BiGRU+GRU reaches *** have also tested a one-dimensional convolutional neural network(1DCNN)with 20 hidden layers and a residual neural network(ResNet),we find that the 1DCNN has almost the same performance of the BiGRU+GRU network for the original dataset,while the robustness testing seems to be a little weak than BiGRU+GRU when we test all these models on two other independent *** ResNet has the worst performance among all the seven network *** datasets presented in this paper,including the large data set of the spectral function of Anderson quantum impurity model,are openly available at https://***/10.57760/sciencedb.j00113.00192.

关键词： machine learning Anderson impurity model spectral function

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Benchmark experiment on slab^(238)U with D-T neutrons for validation of evaluated nuclear data

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Nuclear Science and Techniques 2024年第2期35卷 145-159页

作者： Yan-Yan Ding Yang-Bo Nie Yue Zhang Zhi-Jie Hu Qi Zhao Huan-Yu Zhang Kuo-Zhi Xu Shi-Yu Zhang Xin-Yi Pan Chang-Lin Lan Jie Ren Xi-Chao Ruan Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China School of Nuclear Science and Technology Lanzhou UniversityLanzhou 730000China Institute of Fluid Physics China Academy of Engineering PhysicsMianyang 62100China

A benchmark experiment on^(238)U slab samples was conducted using a deuterium-tritium neutron source at the china Institute of Atomic *** leakage neutron spectra within energy levels of 0.8-16 MeV at 60°and 120°were measured using the time-of-flight *** samples were prepared as rectangular slabs with a 30 cm square base and thicknesses of 3,6,and 9 *** leakage neutron spectra were also calculated using the MCNP-4C program based on the latest evaluated files of^(238)U evaluated neutron data from CENDL-3.2,ENDF/B-Ⅷ.0,JENDL-5.0,and *** on the comparison,the deficiencies and improvements in^(238)U evaluated nuclear data were *** results showed the following.(1)The calculated results for CENDL-3.2 significantly overestimated the measurements in the energy interval of elastic scattering at 60°and 120°.(2)The calculated results of CENDL-3.2 overestimated the measurements in the energy interval of inelastic scattering at 120°.(3)The calculated results for CENDL-3.2 significantly overestimated the measurements in the 3-8.5 MeV energy interval at 60°and 120°.(4)The calculated results with JENDL-5.0 were generally consistent with the measurement results.

关键词： Leakage neutron spectra Uranium D-T neutron source Evaluated nuclear data

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CO_(2) corrosion of X80 steel welded joints under micro-turbulence induced by welding reinforcement height

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Journal of Iron and Steel Research International 2024年第4期31卷 1015-1032页

作者： Xiao-hui Dou Bin Li Zong-hao He Xin-wei Zhang Da-lei Zhang Yan Li School of Materials Science and Engineering China University of Petroleum(East China)Qingdao 266580ShandongChina School of Energy and Power Engineering Jiangsu UniversityZhenjiang 212013JiangsuChina

Corrosion failure accidents owing to flow erosion and pipeline corrosion frequently occur during *** welding reinforcement height(WRH)can induce locally micro-turbulent flow field,which aggravates local corrosion of welded joints.A high wall shear stress(WsS)experimental setup was established to conduct the online electrochemical corrosion *** influence of WRH sizes on local corrosion of welded joints was studied at different flow *** electrochemical signals of the local corrosion of X80 welded joints at different flow rates were monitored in real time using electrochemical impedance spectroscopy and wire beam *** addition,the corrosion products composition and properties were *** results show that the micro-turbulent flow fields induced by the WRHs can enhance ion mass transfer near the welded *** corrosion products on the WRH surface also present different microscopic morphologies at different flow *** strong flow fields,the locally enhanced wsS can peel off the dense corrosion product partially,leading to the electrochemical distribution of large cathode and small anode,which accelerates the occurrence and development processes of the local corrosion of welded *** scientific guidelines for the corrosion protection of long-distance oil and gas pipelines can be potentially provided.

关键词： X80 steel welded joint Welding reinforcement height Micro-turbulence CO_(2)corrosion-Ion mass transfer

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