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Flexible metal–organic frameworks based self-lubricating composite

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Friction 2024年第8期12卷 1816-1827页

作者： Xiao YANG Yunbo WANG weihua cao Jinghan ZHENG Changxin LIU Bingli FAN Xiaowen QI School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004China Key Laboratory of Self-Lubricating Spherical Plain Bearing Technology of Hebei Province Yanshan UniversityQinhuangdao 066004China Aviation Key Laboratory of Science and Technology on Generic Technology of Self-Lubricating Spherical Plain Bearing Yanshan UniversityQinhuangdao 066004China Department of Materials.Imperial College London London SW72AZUK

To expand the use of metal–organic frameworks(MOFs)based self-lubricating composite,flexible MOFs MIL-88D has been studied as a nanocontainer for loading *** this work,the mechanism of oleamine adsorption and desorption by MIL-88D was investigated through molecular simulations and *** simulations showed that the oleamines can be physically adsorbed into open MIL-88Ds with the Fe and O atoms of MIL-88D interacting with oleamine *** temperature can cause Ole@MIL-88D to release more oleamines,while higher pressure on Ole@MIL-88D caused less oleamines *** the Ole@MIL-88D was incorporated into epoxy resin(EP)for friction *** optimum mass ratio of MIL-88D to EP is 15 wt%,and the EP/Ole@MIL-88D prefers light load and high frequency *** work suggests that flexible MOFs can be used as a nanocontainer for loading lubricant,and can be used as a new self-lubricating composite.

关键词： self-lubricating composite metal–organic framework(MOFs) MIL-88D molecular dynamic(MD)simulation

大洋钻探过程钻速在线区间预测方法——以微型钻探船室内模拟实验为例

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钻探工程 2024年第5期51卷 45-52页

作者：张琦甘超曹卫华中国地质大学(武汉)自动化学院湖北武汉430074 复杂系统先进控制与智能自动化湖北省重点实验室湖北武汉430074 地球探测智能化技术教育部工程研究中心湖北武汉430074

大洋钻探是从事海洋能源资源勘探开发和地壳构造演化研究的主要手段,常面临复杂海况扰动大、海底地层不确定性强等问题。本文提出一种大洋钻探过程钻速在线区间预测方法,以微型钻探船室内模拟实验为例开展方法的验证工作,为工程化应用... 详细信息

大洋钻探是从事海洋能源资源勘探开发和地壳构造演化研究的主要手段,常面临复杂海况扰动大、海底地层不确定性强等问题。本文提出一种大洋钻探过程钻速在线区间预测方法,以微型钻探船室内模拟实验为例开展方法的验证工作,为工程化应用奠定重要基础。首先,运用数据重采样、数据时深匹配、数据滤波等方法对多源大洋钻探数据进行预处理。其次,引入极限学习机、粒子群优化等方法建立钻速点预测模型。再者,利用非参数估计方法构造置信区间,建立钻速区间预测模型,并开展钻速区间预测。最后,通过滑动窗口方法在线更新区间预测模型参数,实现模型的在线学习和优化。微型钻探船室内模拟实验的对比结果验证了所提方法具有很强的钻速预测能力和鲁棒性,为大洋钻探过程钻速优化控制提供了新的工程解决方案。

关键词：大洋钻探过程钻速区间预测室内模拟实验在线学习误差分析

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深部地质钻进过程地层特征参数建模与安全预警研究进展

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煤田地质与勘探 2024年第10期52卷 195-206页

作者：杨豫龙曹卫华甘超黎育朋吴敏中国地质大学(武汉)自动化学院湖北武汉430074 复杂系统先进控制与智能自动化湖北省重点实验室湖北武汉430074 地球探测智能化技术教育部工程研究中心湖北武汉430074

【意义】新一轮找矿突破战略行动持续开展,资源勘探向地球深部进军。深部地层的岩石种类多样,岩石力学参数复杂难测,存在高温、高压、高地应力的复杂环境,易发生钻具失效、井壁坍塌、井漏、井涌等井下事故,给地质钻探带来了挑战。【进... 详细信息

【意义】新一轮找矿突破战略行动持续开展,资源勘探向地球深部进军。深部地层的岩石种类多样,岩石力学参数复杂难测,存在高温、高压、高地应力的复杂环境,易发生钻具失效、井壁坍塌、井漏、井涌等井下事故,给地质钻探带来了挑战。【进展】针对复杂地质环境的感知与建模问题,从地层可钻性、地层压力建模两方面梳理地层特征参数建模的研究现状,依据可钻性和压力两个关键地层特征参数,为地质钻进过程的工艺调整和效率优化提供指导;围绕地质钻进过程安全、高效的需求,从井壁稳定评估、井下故障监测两方面讨论地质钻进过程安全预警的研究进展,通过钻进过程的安全预警技术,帮助司钻人员及时发现并辨别已发生的井下事故,提前辨别并消除潜在的安全隐患。【展望】面对深部地层更加复杂、严苛的地质条件,地层特征参数模型将在地质钻探各个环节发挥更加重要的作用,钻进过程安全预警将成为新一代智能化地质钻进装备的核心技术。在未来,需要构建以地质勘探数据中台为核心的智能地质勘探系统,发挥数据在地质勘探和矿产开发全流程中的关键作用,推动人工智能技术在地质钻进过程优化、地层环境感知与找矿预测领域的落地应用,为地质钻探的安全和高效开展提供保障。

关键词：地质钻探地质钻进过程环境感知地层特征参数建模安全预警地质勘探数据中台

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主进出水阀制造过程典型质量缺陷分析

设备监理 2024年第4期 25-28页

作者：曹卫华宿国祯北京中水科工程集团有限公司北京100048 国网新源物资有限公司北京100032

受国家能源政策影响,抽水蓄能项目大量上马,有些设备制造过程中难免出现质量问题。本文介绍了某抽水蓄能电站某台主进出水阀加工过程中阀体上游侧法兰螺孔中存在的线性缺陷,以及监造工程师协调制造厂进行缺陷处理的过程;阐述了制造厂采... 详细信息

受国家能源政策影响,抽水蓄能项目大量上马,有些设备制造过程中难免出现质量问题。本文介绍了某抽水蓄能电站某台主进出水阀加工过程中阀体上游侧法兰螺孔中存在的线性缺陷,以及监造工程师协调制造厂进行缺陷处理的过程;阐述了制造厂采取去除缺陷、扩孔、镶套等方式解决问题的过程方法,分析了缺陷产生的原因,提出了改进措施,保证了最终产品质量。

关键词：主进出水阀制造质量缺陷

A Computer-Aided Tuning Method for Microwave Filters by Combing T-S Fuzzy Neural Networks and Improved Space Mapping

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Computer Modeling in Engineering & Sciences 2018年第9期116卷 433-453页

作者： Shengbiao Wu weihua cao Can Liu Min Wu School of Automation China University of GeoscienceWuhanHubei430074China Nanchang Institute of Science and Technology.Nanchang Jiangxi330100China The Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems WuhanHubei430074China

A computer-aided tuning method that combines T-S fuzzy neural network(TS FNN)and offers improved space mapping(SM)is presented in this *** method consists of three main ***,the coupling matrix is effectively extracted under the influence of phase shift and cavity loss after the initial ***,the surrogate model is realized by using a T-S FNN based on subspace ***,the mapping relationship between the actual and the surrogate models is established by the improved space mapping algorithm,and the optimal position of the tuning screws are found by updating the input and output parameters of the surrogate ***,the effectiveness of different methods is verified by an experiment with a nine order cross coupled *** results show that,compared to a back propagation neural network method based on electromagnetic simulation and an SM method based on a least squares support vector machine,the proposed method has obvious advantages in terms of tuning accuracy and tuning time.

关键词： Computer-aided tuning T-S FNN S-parameters coupling matrix

Modeling for coke quality prediction using Gaussian function and SGA

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Science China(Information Sciences) 2022年第1期65卷 282-284页

作者： Yan YUAN Qilin QU weihua cao Min WU School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Dear editor,Recently, we made some new attempts at predicting coke quality. Coke quality prediction provides important guidance for coal blending, improving the quality of coke, and reducing the cost. Prediction usually involves selection of the coal blending parameters and selection of the modeling methods. In recent years, traditional coal quality indicators such as coal impurity(ash Ad, sulfur St.d),

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Simplified outlier detection for improving the robustness of a fuzzy model

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Science China(Information Sciences) 2020年第4期63卷 218-220页

作者： Yali JIN weihua cao Min WU Yan YUAN School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

Dear editor,Fuzzy models have been widely employed in various fields, such as complex industrial process modeling, classification, function approximation, and time series prediction. Extracting fuzzy rules is very important as they determine the capabilities of the fuzzy model. In recent years, data-based methods such as fuzzy clustering, genetic algorithm, and neural networks [1–3], have been pro-

关键词： Simplified outlier detection for improving the robustness of a fuzzy model Gaussian

Cooperative learning with joint state value approximation for multi-agent systems

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控制理论与应用（英文版） 2013年第2期11卷 149-155页

作者： Xin CHEN Gang CHEN weihua cao Min WU School of Information Science and Engineering Central South University

This paper relieves the ＇curse of dimensionality＇ problem, which becomes intractable when scaling rein- forcement learning to multi-agent systems. This problem is aggravated exponentially as the number of agents increases, resulting in large memory requirement and slowness in learning speed. For cooperative systems which widely exist in multi-agent systems, this paper proposes a new multi-agent Q-learning algorithm based on decomposing the joint state and joint action learning into two learning processes, which are learning individual action and the maximum value of the joint state approximately. The latter process considers others＇ actions to insure that the joint action is optimal and supports the updating of the former one. The simulation results illustrate that the proposed algorithm can learn the optimal joint behavior with smaller memory and faster leamin~ soeed comoared with friend-O learnin~ and indet^endent learning.

关键词： Multi-agent system Q-learning Cooperative system Curse of dimensionality Decomposition

Impact of ursodeoxycholic acid therapy in autoimmune liver disease patients with COVID-19 and its clinical prognosis

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Biosafety and Health 2024年第3期6卷 165-170页

作者： Minghui Li weihua cao Tingting Jiang Wen Deng Shiyu Wang Shuling Wu Lu Zhang Yao Lu Min Chang Ruyu Liu Xiaoyan Ding Ge Shen Yuanjiao Gao Hongxiao Hao Xiaoxue Chen Leiping Hu Mengjiao Xu Yuyong Jiang Wei Yi Yao Xie Rui Song Department of Hepatology Division 2 Beijing Ditan HospitalCapital Medical UniversityBeijing 100015China Department of Hepatology Division 2 Peking University Ditan Teaching HospitalBeijing 100015China Department of Medical Oncology Beijing Ditan HospitalCapital Medical UniversityBeijing 100015China Center of Integrative Medicine Beijing Ditan HospitalCapital Medical UniversityBeijing 100015China Department of Gynecology and Obstetrics Beijing Ditan HospitalCapital Medical UniversityBeijing 100015China Department of Infectious Disease Beijing Ditan HospitalCapital Medical UniversityBeijing 100015China

To explore the impact of ursodeoxycholic acid(UDCA)on severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection and clinical outcomes in patients with autoimmune liver disease(AILD).Patients diagnosed with AILD were enrolled and divided into a UDCA group and a non-UDCA group based on whether they received UDCA *** data were collected regarding AILD diagnosis,treatment,biochemical indicators,and imaging *** incidence of SARS-CoV-2 infection and the prognosis of AILD patients were observed.A total of 1,138 patients completed *** usage rate of hormone(P=0.003)and immunosuppressant(P=0.001)used for treating AILD in the non-UDCA group was markedly lower than in the UDCA *** UDCA usage rate was markedly lower in SARS-CoV-2 infected patients than in uninfected patients(P=0.003).The rate of SARS-CoV-2 infection in the non-UDCA group was significantly higher than in the UDCA group(P=0.018).Logistic regression analysis showed that UDCA use(P=0.003)was correlated to a lower incidence of SARS-CoV-2,while immunosuppressant use(P=0.017)increased the *** time from SARS-CoV-2 infection was markedly longer for those receiving UDCA treatment than those in the non-UDCA group(P=0.018).UDCA is associated with low SARS-CoV-2 incidence in AILD patients,while immunosuppressant increases its incidence *** receiving UDCA treatment have a longer recovery time after being infected.

关键词： Ursodeoxycholic acid(UDCA) Autoimmune liver disease(AILD) Coronavirus disease 2019(COVID-19) Primary biliary cholangitis(PBC) Autoimmune hepatitis(AIH)