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development and performance evaluation of high temperature resistant strong adsorption rigid blocking agent

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Petroleum Science 2024年第4期21卷 2650-2662页

作者： Zhe Xu Jin-Sheng Sun Jing-Ping Liu Kai-He Lv Xiao-dong dong Zong-Lun Wang Tai-Feng Zhang Yuan-Wei Sun Zhi-Wen dai School of Petroleum engineering China University of Petroleum (East China) CNPC engineering Technology r&d Company Limited

As drilling wells continue to move into deep ultra-deep layers, the requirements for temperature resistance of drilling fluid treatments are getting higher and higher. Among them, blocking agent, as one of the key treatment agents, has also become a hot spot of research. In this study, a high temperature resistant strong adsorption rigid blocking agent(QW-1) was prepared using KH570 modified silica,acrylamide(AM) and allyltrimethylammonium chloride(TMAAC). QW-1 has good thermal stability,average particle size of 1.46 μm, water contact angle of 10.5., has a strong hydrophilicity, can be well dispersed in water. The experimental results showed that when 2 wt% QW-1 was added to recipe A(4 wt% bentonite slurry+0.5 wt% dSP-1(filtration loss depressant)), the API filtration loss decreased from 7.8to 6.4 m L. After aging at 240.C, the API loss of filtration was reduced from 21 to 14 m L, which has certain performance of high temperature loss of filtration. At the same time, it is effective in sealing 80-100mesh and 100-120 mesh sand beds as well as 3 and 5 μm ceramic sand discs. Under the same conditions,the blocking performance was superior to silica(5 μm) and calcium carbonate(2.6 μm). In addition, the mechanism of action of QW-1 was further investigated. The results show that QW-1 with amide and quaternary ammonium groups on the molecular chain can be adsorbed onto the surface of clay particles through hydrogen bonding and electrostatic interaction to form a dense blocking layer, thus preventing further intrusion of drilling fluid into the formation.

关键词： High adsorption rigid microsphere High temperature resistance Blocking performance

Hierarchical model updating for high-speed maglev vehicle/guideway coupled system based on multiobjective optimization

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Frontiers of Structural and Civil engineering 2024年第5期18卷 788-804页

作者： dexiang Li Jingyu Huang College of Civil engineering Tongji UniversityShanghai 200092China National Maglev Transportation engineering r&d Center Tongji UniversityShanghai 201804China

The high-speed maglev vehicle/guideway coupled model is an essential simulation tool for investigating vehicle dynamics and mitigating coupled *** improve its accuracy efficiently,this study investigated a hierarchical model updating method integrated with field ***,a high-speed maglev vehicle/guideway coupled model,taking into account the real effect of guideway material properties and elastic restraint of bearings,was developed by integrating the finite element method,multi-body dynamics,and electromagnetic levitation ***,simultaneous in-site measurements of the vehicle/guideway were conducted on a high-speed maglev test line to analyze the system response and structural modal *** the hierarchical updating,an Elman neural network with the optimal Latin hypercube sampling method was used to substitute the FE guideway model,thus improving the computational *** multi-objective particle swarm optimization algorithm with the gray relational projection method was applied to hierarchically update the parameters of the guideway layer and magnetic force layer based on the measured modal parameters and the electromagnet vibration,***,the updated coupled model was compared with the field measurements,and the results demonstrated the model’s accuracy in simulating the actual dynamic response,validating the effectiveness of the updating method.

关键词： high-speed maglev vehicle/guideway coupled model field measurement model updating neural network multi-objective optimization

LdAS&ET-Ad:Learnable distillation Attack Strategies and Evolvable Teachers Adversarial distillation

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Computers, Materials & Continua 2024年第5期79卷 2331-2359页

作者： Shuyi Li Hongchao Hu Xiaohan Yang Guozhen Cheng Wenyan Liu Wei Guo National digital Switching System engineering&Technological r&d Center The PLA Information Engineering UniversityZhengzhou450000China

Adversarial distillation(Ad)has emerged as a potential solution to tackle the challenging optimization problem of loss with hard labels in adversarial ***,fixed sample-agnostic and student-egocentric attack strategies are unsuitable for ***,the reliability of guidance from static teachers diminishes as target models become more *** paper proposes an Ad method called Learnable distillation Attack Strategies and Evolvable Teachers Adversarial distillation(LdAS&ET-Ad).Firstly,a learnable distillation attack strategies generating mechanism is developed to automatically generate sample-dependent attack strategies tailored for distillation.A strategy model is introduced to produce attack strategies that enable adversarial examples(AEs)to be created in areas where the target model significantly diverges from the teachers by competing with the target model in minimizing or maximizing the Ad ***,a teacher evolution strategy is introduced to enhance the reliability and effectiveness of knowledge in improving the generalization performance of the target *** calculating the experimentally updated target model’s validation performance on both clean samples and AEs,the impact of distillation from each training sample and AE on the target model’s generalization and robustness abilities is assessed to serve as feedback to fine-tune standard and robust teachers *** evaluate the performance of LdAS&ET-Ad against different adversarial attacks on the CIFAr-10 and CIFAr-100 *** experimental results demonstrate that the proposed method achieves a robust precision of 45.39%and 42.63%against AutoAttack(AA)on the CIFAr-10 dataset for resNet-18 and MobileNet-V2,respectively,marking an improvement of 2.31%and 3.49%over the baseline *** comparison to state-of-the-art adversarial defense techniques,our method surpasses Introspective Adversarial distillation,the top-performing method in terms of robustne

关键词： Adversarial training adversarial distillation learnable distillation attack strategies teacher evolution strategy

Thickening progression mechanism of silica fume-oil well cement composite system at high temperatures

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Petroleum Science 2024年第4期21卷 2793-2805页

作者： Hang Zhang Miao-Miao Hu Peng-Peng Li Guo-Qing Liu Qing-Lu Chang Jie Cao Ming Liu Wen-Hua Xu Xiu-Jian Xia Jin-Tang Guo School of Chemical engineering and Technology Tianjin University Zhejiang Institute of Tianjin University Haihe Laboratory of Sustainable Chemical Transformations CNPC engineering Technology r&d Company Limited

This work studied the thickening progression mechanism of the silica fume-oil well cement composite system at high temperatures(110-180.C) in order to provide a theoretical guidance for the rational application of silica fume in the cementing engineering. results showed that silica fume seldom affected the thickening progression of oil well cement slurry at 110-120.C, but when temperature reached above130.C, it would aggravate the bulging degree of thickening curves and significantly extend the thickening time, meanwhile causing the abnormal “temperature-based thickening time reversal” and“dosage-based thickening time reversal” phenomena in the range of 130-160.C and 170-180.C respectively. At 130-160.C, the thickening time of oil well cement slurry was mainly associated with the generation rate of calcium hydroxide(CH) crystal. The introduced silica fume would be attracted to the cement minerals' surface that were hydrating to produce CH and agglomerate together to form an“adsorptive barrier” to hinder further hydration of the inner cement minerals. This “adsorptive barrier”effect strengthened with the rising temperature which extended the thickening time and caused the occurrence of the “temperature-based thickening time reversal” phenomenon. At 170-180.C, the pozzolanic activity of silica fume significantly enhanced and considerable amount of C-S-H was generated, thus the “temperature-based thickening time reversal” vanished and the “dosage-based thickening time reversal” was presented.

关键词： Silica fume Oil well cement Thickening time reversal Pozzolanic reaction Adsorptive barrier CH and C−S−H

A new type of lipophilic hydrophobic self-repairing cellulose insulating paper developed with ST-110/FAS/PTFE ternary system as coating substrate

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High Voltage 2024年第2期9卷 474-483页

作者： Zhenglin Zeng Jinshan Qin Zuhao Wang Weimin Tan Chao Tang College of engineering and Technology Southwest UniversityChongqingChina International r&d Center for New Technologies of Smart Grid and Equipment ChongqingChina

The moisture generated by the ageing of the oil-paper insulating system can easily lead to the deterioration of the performance of the insulating *** order to alleviate the impact of moisture on the performance of the insulating paper,we developed a kind of lipophilic hydrophobic self-repairing cellulose insulating paper(new insulating paper)based on the ternary system of polytetrafluoroethylene,fluorocarbon surfactant and fluorinated alkyl silane,and accelerated thermal ageing test for 45 days at 130°C was carried *** experimental results show that the new insulating paper with excellent lipophilic property can realise hydrophobic self-repairing through heat treatment after physical *** tensile strength and elongation at break of the new insulating paper increased by 5%–8%and 6.25%–27%respectively compared with the original cellulose insulating *** the end of ageing,the relative dielectric constant and dielectric loss factor of new insulating paper are 10.4%and 9.9%lower than that of the original cel-lulose insulating paper,while the breakdown voltage is 6.8%*** acid and moisture content produced during the ageing process of the insulating oil impregnated with new insulating paper are also less,indicating that the coating can delay the ageing of the insulating paper.

关键词： coating moisture cellulose

Friction and wear performance of polyether ether ketone(PEEK)polymers in three lubrication regimes

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Friction 2024年第4期12卷 670-682页

作者： davide MASSOCCHI Nora LECIS Marco LATTUAdA davide SCAGLIA Steven CHATTErTON Paolo PENNACCHI department of Mechanical engineering Politecnico di MilanoMilan 20156Italy Eni SpA Downstream product R&DLombardia 20097Italy Eurobearings S.r.L. Lombardia 29016Italy

This experimental study investigates the friction and wear of three coatings commonly used in industrial applications,particularly in hydrodynamic *** three materials under investigation were Babbitt,polyether ether ketone(PEEK)reinforced with 15%carbon fibers,and PEEK reinforced with 20%carbon *** first polymer material was extruded,while the other was produced by fused deposition modelling(FdM).The materials were subjected to sliding tests in a pin-on-disc configuration,with a steel ball serving as the counter *** tests were conducted at room temperature,with a load of 10 N and under three different lubrication conditions:dry,grease,and *** linear speed was set at 0.3 m/s for the dry and semi-solid lubrication tests,while for the oil tests,the speed was set at 0.25 m/*** greases used had consistency grades of NGLI 000 and NGLI *** ISO VG 68 circulation oil was used for the oil lubrication ***,thermodynamic analyses were performed under the most severe conditions(i.e.,dry)to investigate the steel-Babbitt and steel-PEEK contact.

关键词： hydrodynamic bearings polyether ether ketone(PEEK)polymers additive manufacturing grease lubrication sliding oil lubrication ball-on-disk tribology

Experiment of electrothermal stress for different types of end turn grading in the inverter-fed form-wound windings

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High Voltage 2024年第4期9卷 853-861页

作者： Wenhuan Zhao Peng Wang Yingwei Zhu Yue Zhang Shuai Yang Yan Liu Yang Shi Chaofan Yu Electrical engineering department Sichuan UniversityChengduSichuanChina d&r Dongfang Electric Machinery Co.Ltd.DeyangSichuanChina

End turn grading with resistive–capacitive coupling experiences severe electrothermal stress when subjected to pulse width modulation(PWM)*** this paper,several experiments and simulations were carried conducted for four types of end turn *** of all,the temperature rise in the end turn grading increased with a decrease in rise *** the rise time was less than 500 ns,the temperature rise at the terminal was higher owing to the increased capacitive current coupled from the main wall ***,the current in the linear region exhibited minimal variation at different fundamental frequencies resulting in synchronized the temperature rise at the terminal and ***,the jump voltage was the key factor influencing temperature rise in end turn grading,confirmed by comparing different voltage ***,the transient behaviour of the maximum field in the stress grading material was determined at rise *** experimental and simulation results indicate that balancing and interdependently addressing the electrical and thermal stress protection in end turn grading is *** study aims to provide an experimental and theoretical foundation for an insulation system of inverter-fed rotating machinery operating under PWM voltage.

关键词： stress inverter insulation

Prediction of dissolved gas content in transformer oil based on multi-information fusion

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High Voltage 2024年第3期9卷 685-699页

作者： Tongliang Yang Yun Fang Chengming Zhang Chao Tang dong Hu College of engineering and Technology Southwest UniversityChongqingChina International r&d Center for New Technologies of Smart Grid and Equipment Southwest UniversityChongqingChina

In order to accurately predict the content and variation trend of dissolved gas in trans-former oil and guide the condition maintenance of power transformers,a combined prediction model based on multi-information fusion is proposed and its effectiveness is *** of all,based on the possibility of pathological and missing historical sample data,a detection and filling method based on variable weight combination samples is ***,the authors propose two *** at the non-linear and non-stationary characteristics of gas content,a univariate decomposition prediction mode HBA-VMd-TCN which based on the Honey Badger algorithm,variational mode decomposition and time convolutional network(TCN)is *** the multi-variate Informer prediction model is established for gas content affected by multiple ***,the cross-entropy theory is used to determine the weight coefficients of the two models,and the multi-information fusion combined prediction model is ***,on the basis of the above,a method to determine the time step and the position information of the transition point adaptively in the process of prediction is proposed to further improve the prediction *** results show that,through a series of simulation experiments of model comparison and transformer anomaly prediction,the accuracy and effectiveness of the combined prediction model are verified.

关键词： content prediction dissolved

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

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