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Intelligent direct analysis of physical and mechanical parameters of tunnel surrounding rock based on adaptive immunity algorithm and BP neural network

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Journal of Pharmaceutical Analysis 2009年第1期21卷 22-30页

作者： xiao-rui wang1,2. yuan-han wang1,{2.,huazhong university of science and Technology, wuhan 43.074,china 2.Department of civil engineering,Nanyang Institute of Technology,Nanyang 473004,china 3.Department of Chemistry and Bioengineering,Nanyang Institute of Technology,Nanyang 473004,china. school of civil {2. and mechanics Huazhong University of Science and Technology Wuhan 430074 China Department of civil engineering Nanyang Institute of Technology Nanyang 473004 China Department of Chemistry and Bioengineering Nanyang Institute of Technology Nanyang 473004 China

Because of complexity and non-predictability of the tunnel surrounding rock, the problem with the determination of the physical and mechanical parameters of the surrounding rock has become a main obstacle to theoretical research and numerical analysis in tunnel engineering. During design, it is a frequent practice, therefore, to give recommended values by analog based on experience. It is a key point in current research to make use of the displacement back analytic method to comparatively accurately determine the parameters of the surrounding rock whereas artificial intelligence possesses an exceptionally strong capability of identifying, expressing and coping with such complex non-linear relationships. The parameters can be verified by searching the optimal network structure, using back analysis on measured data to search optimal parameters and performing direct computation of the obtained results. In the current paper, the direct analysis is performed with the biological emulation system and the software of Fast Lagrangian Analysis of Continua (FLAC3D. The high non-linearity, network reasoning and coupling ability of the neural network are employed. The output vector required of the training of the neural network is obtained with the numerical analysis software. And the overall space search is conducted by employing the Adaptive Immunity Algorithm. As a result, we are able to avoid the shortcoming that multiple parameters and optimized parameters are easy to fall into a local extremum. At the same time, the computing speed and efficiency are increased as well. Further, in the paper satisfactory conclusions are arrived at through the intelligent direct-back analysis on the monitored and measured data at the Erdaoya tunneling project. The results show that the physical and mechanical parameters obtained by the intelligent direct-back analysis proposed in the current paper have effectively improved the recommended values in the original prospecting data. This is of p

关键词： adaptive immunity algorithm BP neural network physical and mechanical parameters surrounding rock direct-back analysis

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Frontiers in high entropy alloys and high entropy functional materials

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Rare Metals 2024年第10期43卷 4639-4776页

作者： Wen-Tao Zhang Wen Huang Fu-Jie Yu Qi Zhao Xin-Dong Zhu Tao feng Yao jiang xiao-Ming Li Xue-Fei Miao He Zhu Si Lan Xue-Qian wang Bao-Long Shen Zhe jia feng-Qi Zhang Wei wang Qi Liu Yang Ren Xun-Li wang xiao-Ya Cui xiao-Yang wang Ya-Nan Chen Bing-Bing Fan Meng-Ru Li Qi-Long Gao jia-Ming Guo Zeng-Bao jiao Zhi-Min Guo Yu-Ping Zhao Qian Yu rui Huang Ling-Kun Zhang Yi-Ping Lu Xu-Bo Li Huai-Jun Lin Yan Ma Wei-Ming Yang Zhi-Hua Shen Hai-Yan He Yong-Gang Sun Yong-jiang Huang De-Zhuang wang Qing-feng Liu Fei-Yang wang Hui Liu Hong-Hui Wu Li-Qiang wang Yang Lu Nan wang Tian-Li wang Wei-Bing Liao Yi-han wang yuan Wu Yu-Zhen Yin Jie Pan Yi Zhang Qing wang jian-Yang Zhang Tao Yang Yasir Sohail Jin-Yu Zhang Hua Ji Qiang Li Wei-Di Liu Zhi-Gang Chen Xiong-Jun Liu Wen Ma Liang Mao Zhen-Duo Wu school of Materials science and {2. Nanjing University of Science and Technology jiangsu Key Laboratory for Advanced Metallic Materials School of Materials Science and Engineering Southeast University Department of Physics City University of Hong Kong school of Materials science and {2. Tianjin University school of Physics and Microelectronics Zhengzhou University Department of Mechanical engineering Research Institute for Advanced Manufacturing The Hong Kong Polytechnic University Center of Electron Microscopy and State Key Laboratory of Silicon Materials School of Materials Science and Engineering Zhejiang University Key Laboratory of Solidification Control and Digital Preparation Technology (Liaoning Province) School of Materials Science and Engineering Dalian University of Technology Institute of Advanced Wear & Corrosion Resistance and Functional Materials Jinan University school of mechanics and {2. engineering China University of Mining and Technology school of Physical sciences Great Bay University school of Materials science and{2. Harbin Institute of Technology State Key Laboratory of Materials-Oriented Chemical engineering College of Chemical Engineering Nanjing Tech University Beijing Advanced Innovation Center for Materials Genome engineering Research Institute for Carbon Neutrality University of Science and Technology Beijing Department of Mechanical engineering The University of Hong Kong school of Computing Macquarie University Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University State Key Laboratory for Advanced Metals and Materials University of Science and Technology Beijing State Key Laboratory of Materials Processing and Die & Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology Institute of materials Shanghai University Department of Materials science and engineering C

Owing to their exceptional properties, high-entropy alloys(HEAs) and high-entropy materials have emerged as promising research areas and shown diverse applications. Here,the recent advances in the field are comprehensively reviewed,organized into five sections. The first section introduces the background of HEAs, covering their definition, significance,application prospects, basic properties, design principles, and microstructure. The subsequent section focuses on cutting-edge high-entropy structural materials, highlighting developments such as nanostructured alloys, grain boundary engineering,eutectic systems, cryogenic alloys, thin films, micro-nano-lattice structures, additive manufacturing, high entropy metallic glasses, nano-precipitate strengthened alloys, composition modulation, alloy fibers, and refractory systems. In the following section, the emphasis shifts to functional materials, exploring HEAs as catalysts, magneto-caloric materials, corrosion-resistant alloys, radiation-resistant alloys, hydrogen storage systems, and materials for biomedicine. Additionally, the review encompasses functional high-entropy materials outside the realm of alloys, including thermoelectric, quantum dots, nanooxide catalysts, energy storage materials, negative thermal expansion ceramics,and high-entropy wave absorption materials. The paper concludes with an outlook, discussing future directions and potential growth areas in the field. Through this comprehensive review,researchers, engineers, and scientists may gain valuable insights into the recent progress and opportunities for further exploration in the exciting domains of high-entropy alloys and functional materials.

关键词： Cutting-edge structural materials Cutting-edgefunctional materials High entropy alloys

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CEPC Technical Design Report

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Radiation Detection Technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-S{2. Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash C{2.dra Behera Alexander Belyaev Michele Bertucci xiao-Jun Bi yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua Cai Wenyong Cai Wujun Cai Yijian Cai Yizhou Cai Yuchen Cai Haiying Cai Huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao jianshe Cao Antoine C{2.ce Xuejun C{2.g Yue C{2.g Zhe C{2.g Xinyuan C{2.g Wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-yuan Chen Kai Chen Mali Chen Mingjun Chen Mingshui Chen Ning Chen S{2.hong Chen S{2.zhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen Wei Chen Xiang Chen xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng S{2. Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen {2. Chiu Guk Cho Ming-Chung Chu xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin {2.hua Cui xiaohao Cui Zhaoyuan Cui Brunella D'Anzi Ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong jianin AGH university of science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui university HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu university Institute of ScienceVaranasi Bandirma Onyedi Eylul university Bandirma Beihang university Beijing Beijing Computational science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal university Beijing Brown university ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad university Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo university Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central china Normal university WuhanHubei Central South university ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa Chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan china academy of engineering physics MianyangSichuan china building materials academy Beijing china Center of Advanced science and Technology Beijing china Institute of Atomic Energy Beijing china Jiliang university HangzhouZhejiang china Nuclear Instrument CO. LTDBeijing china university of Geo{2.s Beijing china university of Geo{2.s WuhanHubei china university of Mining and Technology XuzhouJiangsu china West Normal university NanchongSichuan Chongqing university Department of PhysicsChongqing Chulalongkorn university Bangkok City university of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell university IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu university DalianLiaoning Dalian university of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East china university Of {2. And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by china,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV Linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The Linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 MW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2.s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2.15)and the Conceptual Design Report(CDR,2.18),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil {2. ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming {2. design phase and site selection *** is anticipated to begin around 2.2.-2.2.,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2.30s.

关键词： initiated exceeding precise

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波形钢腹板组合箱梁带栓钉埋入式抗剪连接件承载力推出试验及有限元模拟分析研究

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工程力学 2021年第11期38卷 43-56页

作者：胡锋刘晓东袁阳光韩万水许昕王俊峰河南省交通科学技术研究院有限公司河南郑州450006 长安大学公路学院陕西西安710064 西安建筑科技大学土木工程学院陕西西安710055

针对一座波形钢腹板组合箱梁部分斜拉桥的受力需求,设计了带栓钉埋入式抗剪连接件。为研究其抗剪承载力,设计并开展了推出试验并进行了试验全过程的有限元模拟,对试验过程中试件的破坏及受力机理进行分析;随后根据该类型连接件的承载机... 详细信息

针对一座波形钢腹板组合箱梁部分斜拉桥的受力需求,设计了带栓钉埋入式抗剪连接件。为研究其抗剪承载力,设计并开展了推出试验并进行了试验全过程的有限元模拟,对试验过程中试件的破坏及受力机理进行分析;随后根据该类型连接件的承载机理及受力特点,建立了承载力的近似计算方法。结果发现:对于该带栓钉埋入式抗剪连接件,当栓钉焊接在连接件波形板的直板外侧时,其承载力高于在内侧焊接的情形;当开孔位置位于直板、上折板与下折板时,其承载力依次降低;连接件波形板的上折板荷载-位移曲线存在明显的强化阶段,而下折板几乎不存在强化阶段,直板处荷载-位移曲线特征介于二者之间;另外,该类连接件混凝土开裂及主裂缝均在荷载水平达到0.8倍极限承载力以后形成发展的。所建立的推出试验全过程有限元模拟方法能够准确模拟试验过程中试件的受力行为,并能够诠释栓钉焊接位置、开孔位置对抗剪承载力的影响以及试件破坏机理;基于推出试验与有限元模拟分析,分析可得该类连接件承载力主要由波形板包裹的混凝土与约束钢筋所形成的块连接件、开孔内混凝土剪力销以及栓钉提供,随之建立的抗剪承载力近似计算方法分析结果与试验结果相对误差不超过8.93%,与有限元模拟结果相对误差不超过5.47%,具有良好的适用性。

关键词：桥梁工程波形钢腹板带栓钉埋入式抗剪连接件推出试验有限元模拟分析承载力计算方法

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