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Exploring the Applications of Digital Twin Technology in Enhancing Sustainability in Civil Engineering:A Review

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Structural Durability & Health Monitoring 2024年第5期18卷 577-598页

作者： Jiamin Huang ping Wu Wangxin Li jun Zhang Yidong Xu School of Civil Engineering Chongqing Jiaotong UniversityChongqing400074China School of Civil Engineering and Architecture NingboTech UniversityNingbo315100China School of Civil Engineering Lanzhou University of TechnologyLanzhou730050China

With the advent of the big data era and the rise of Industrial Revolution 4.0,digital twins(DTs)have gained sig-niﬁcant attention in various *** offer the opportunity to combine the physical and digital worlds and aid the digital transformation of the civil engineering *** this paper,605 documents obtained from the search wereﬁrst analysed using CiteSpace for literature visualisation,and an author co-occurrence network,a keyword co-occurrence network,and a keyword clustering set were ***,through a literature review of 86 papers,this paper summarises the current status of DT application in civil engineering based on a review of the origins,concepts,and implementation techniques of DTs,and it introduces the application of DTs in the full project *** study shows that DTs have great potential to address many of the challenges faced by civil *** this regard,the paper also presents some thoughts on the future directions of DT research.

关键词： Digital twins civil engineering full lifecycle literature visualisation analysis

Quantitative characterizations of anisotropic dynamic properties in organic-rich shale with different kerogen content

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Petroleum Science 2024年第2期21卷 855-865页

作者： Jian-Yong Xie Yan-ping Fang Xing-Hua Wu Jian'er Zhao jun-Cheng Dai jun-Xing Cao Ji-Xin Deng State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Chengdu University of TechnologyChengdu610059SichuanChina Key Lab of Earth Exploration&Information Techniques of Ministry of Education Geophysical InstituteChengdu University of TechnologyChengdu610059SichuanChina PetroChina Southwest Oil&Gasfield Company Chengdu610017SichuanChina

Understanding the quantitative responses of anisotropic dynamic properties in organic-rich shale with different kerogen content(KC)is of great significance in hydrocarbon exploration and *** controlled experiments with a single variable is challenging for natural shales due to their high variations in components,diagenesis conditions,or pore *** employed the hot-pressing technique to construct 11 well-controlled artificial shale with varying *** artificial shale samples were successive machined into prismatic shape for ultrasonic measurements along different *** revealed bedding perpendicular P-wave velocities are more sensitive to the increasing KC than bedding paralleling velocities due to the preferential alignments of *** elastic stiffnesses except C_(13)are generally decreasing with the increasing KC,the variation of C_(1) and C_(33)on kerogen content are more sensitive than those of C_(44)and C_(66).Apparent dynamic mechanical parameters(v and E)were found to have linear correlation with the true ones from complete anisotropic equations independent of KC,which hold value towards the interpretation of well logs consistently across formations,Anisotropic mechanical parameters(ΔE and brittlenessΔB)tend to decrease with the reducing KC,withΔB showing great sensitivity to KC *** the range of low KC(10%)shale,compilation of data from natural organic rich-shales globally verified the similar systematic relationships that can be empirically used to predict the fraction of KC in shales.

关键词： Elastic properties Organic shale Anisotropy Kerogen content Physical modeling

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Subsurface multi-physical characterization of mountain excavation and city construction in loess plateau with a fiber-optic sensing system

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第8期16卷 2935-2946页

作者： Jie Liu Bin shi Kai Gu Meng-Ya Sun jun-Cheng Yao He-Ming Han School of Earth Sciences and Engineering Nanjing UniversityNanjingJiangsu210023China Frontiers Science Center for Critical Earth Material Cycling Nanjing UniversityNanjing210023China School of Earth Sciences and Engineering Hohai UniversityNanjing210098China

Mountain excavation and city construction(MECC)projects being launched in the Loess Plateau in China involve the creation of large-scale artificial *** the subsurface evolution characteristics of the artificial land is essential,yet ***,we use an improved fiber-optic monitoring system for its subsurface multi-physical *** system enables us to gather spatiotemporal distribution of various parameters,including strata deformation,temperature,and ***’an New District was selected as a case study to conduct refined in-situ monitoring through a 77 m-deep borehole and a 30 m-long *** reveal that the ground settlement involves both the deformation of the filling loess and the underlying intact ***,the filling loess exhibits a stronger creep capability compared to underlying intact *** deformation along the profile is unevenly distributed,with a positive correlation with soil *** accumulation has been observed at the interface between the filling loess and the underlying intact loess,leading to a significant ***,the temperature and moisture in the filling loess have reached a new equilibrium state,with their depths influenced by atmospheric conditions measuring at 31 m and 26 m,*** refined investigation allows us to identify critical layers that matter the sustainable development of newly created urban areas,and provide improved insights into the evolution mechanisms of land creation.

关键词： Mountain excavation and city construction Fiber-optic monitoring Multi-physical characterization Compacted loess

Intelligent geochemical interpretation of mass chromatograms:Based on convolution neural network

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Petroleum Science 2024年第2期21卷 752-764页

作者： Kai-Ming Su jun-Gang Lu Jian Yu Zi-Xing Lu shi-Jia Chen Hubei Key Laboratory of Petroleum Geochemistry and Environment Wuhan430100HubeiChina College of Resources and Environment Yangtze UniversityWuhan430100HubeiChina School of Geoscience and Technology Southwest Petroleum UniversityChengdu610500SichuanChina Changqing Oilfield Company PetroChinaXi'an710021ShaanxiChina

Gas chromatography-mass spectrometry(GC-MS)is an extremely important analytical technique that is widely used in organic *** is the only approach to capture biomarker features of organic matter and provides the key evidence for oil-source correlation and thermal maturity ***,the conventional way of processing and interpreting the mass chromatogram is both timeconsuming and labor-intensive,which increases the research cost and restrains extensive applications of this *** overcome this limitation,a correlation model is developed based on the convolution neural network(CNN)to link the mass chromatogram and biomarker features of samples from the Triassic Yanchang Formation,Ordos Basin,*** this way,the mass chromatogram can be automatically *** research first performs dimensionality reduction for 15 biomarker parameters via the factor analysis and then quantifies the biomarker features using two indexes(*** and PMI)that represent the organic matter thermal maturity and parent material type,***,training,interpretation,and validation are performed multiple times using different CNN models to optimize the model structure and hyper-parameter setting,with the mass chromatogram used as the input and the obtained MI and PMI values for supervision(label).The optimized model presents high accuracy in automatically interpreting the mass chromatogram,with R2values typically above 0.85 and0.80 for the thermal maturity and parent material interpretation results,*** significance of this research is twofold:(i)developing an efficient technique for geochemical research;(ii)more importantly,demonstrating the potential of artificial intelligence in organic geochemistry and providing vital references for future related studies.

关键词： Organic geochemistry Biomarker Mass chromatographic analysis Automated interpretation Convolution neural network Machine learning

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Incremental Data Stream Classification with Adaptive Multi-Task Multi-View Learning

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Big Data Mining and Analytics 2024年第1期7卷 87-106页

作者： jun Wang Maiwang shi Xiao Zhang Yan Li Yunsheng Yuan Chengei Yang Dongxiao Yu School of Computer Science and Technology Shandong UniversityQingdao 266237China School of Software Shandong UniversityJinan 250101China

With the enhancement of data collection capabilities,massive streaming data have been accumulated in numerous application ***,the issue of classifying data streams based on mobile sensors can be formalized as a multi-task multi-view learning problem with a specific task comprising multiple views with shared features collected from multiple *** incremental learning methods are often single-task single-view,which cannot learn shared representations between relevant tasks and *** adaptive multi-task multi-view incremental learning framework for data stream classification called MTMVIS is proposed to address the above challenges,utilizing the idea of multi-task multi-view ***,the attention mechanism is first used to align different sensor data of different *** addition,MTMVIS uses adaptive Fisher regularization from the perspective of multi-task multi-view learning to overcome catastrophic forgetting in incremental *** reveal that the proposed framework outperforms state-of-the-art methods based on the experiments on two different datasets with other baselines.

关键词： data stream classification mobile sensors multi-task multi-view learning incremental learning

A novel thermally-stable single-phase phosphor Ca2InTaO6:Dy3+ for NUV-excited white LEDs

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Journal of Rare Earths 2024年第10期42卷 1855-1864页

作者： Jian Hu Ruirui Cui jun Zhang Peng Linghu Youzhen shi Xiang Guo Key Laboratory of Micro-Nano-Electronics and Software Technology of Guizhou Province College of Big Data and Information EngineeringGuizhou University College of Computer and Information Engineering Guizhou University of Commerce

The work focuses on the utilization of the conventional solid-state sintering procedure to synthesize white phosphors Ca2InTaO6:xDy3+（0.02≤x≤0.12）.Utilizing X-ray diffraction,the phase structure of samples was examined,and the crystal structure was refined using the Rietveld method.A scanning electron microscope was used to analyze the microstructure of ***-principles calculations confirm that the indirect bandgap of Ca2InTaO6is 3.786 eV,The luminous properties and energy transfer mechanism of Ca2InTaO6:xDy3+were studied using photoluminescence ***4F9/2→6H13/2transition of Dy3+ions is responsible for the greatest emission peak,which was measured at 575 *** to research,the lifespan falls as the concentration of Dy3+doping amount rises because of frequent interaction and ene rgy transfer between Dy3+*** correlated color temperature of the WLEDs packaged with Ca2InTaO6:0.08Dy3+is 4677 K and CIE 1931 chromaticity coordinates are（0.3578,0.3831）.Meantime,the phosphor also shows outstanding te mperature stability property,which maintains 83.8% of its initial emission intensity at 450 K（activation energy of 0.1467 eV）.The W-LEDs retain their performance for 100 min when powered at 3.4 V voltage and 600 mA current,demonstrating the packed W-LEDs' sustaine d operation at high temperatures.

关键词： Ca2InTaO6:Dy3+ phosphors Photoluminescence Rare earths Thermal imaging Thermal stability W-LEDs

Federated Dynamic Client Selection for Fairness Guarantee in Heterogeneous Edge Computing

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Journal of Computer Science & Technology 2024年第1期39卷 139-158页

作者：毛莺池沈莉娟吴俊平萍吴杰 Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai UniversityNanjing 211100China College of Computer and Information Hohai UniversityNanjing 211100China Center of Networked Computing Temple UniversityPhiladelphiaPA 19122-6096U.S.A

Federated learning has emerged as a distributed learning paradigm by training at each client and aggregat-ing at a parameter *** heterogeneity hinders stragglers from responding to the server in time with huge com-munication *** client grouping in federated learning can solve the straggler problem,the stochastic selection strategy in client grouping neglects the impact of data distribution within each ***,current client grouping ap-proaches make clients suffer unfair participation,leading to biased performances for different *** order to guaran-tee the fairness of client participation and mitigate biased local performances,we propose a federated dynamic client selec-tion method based on data representativity(FedSDR).FedSDR clusters clients into groups correlated with their own lo-cal computational *** estimate the significance of client datasets,we design a novel data representativity evalua-tion scheme based on local data ***,the two most representative clients in each group are selected to optimize the global ***,the DYNAMIC-SELECT algorithm updates local computational efficiency and data representativity states to regroup clients after periodic average *** on real datasets show that FedS-DR improves client participation by 27.4%,37.9%,and 23.3%compared with FedAvg,TiFL,and FedSS,respectively,tak-ing fairness into account in federated *** addition,FedSDR surpasses FedAvg,FedGS,and FedMS by 21.32%,20.4%,and 6.90%,respectively,in local test accuracy variance,balancing the performance bias of the global model across clients.

关键词： federated learning fairness computational efficiency data distribution client selection client grouping

基于自适应混沌变异粒子群优化算法的旋转弹丸气动参数辨识

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兵工学报 2017年第1期38卷 73-80页

作者：管军周家胜易文俊刘世平常思江史继刚南京理工大学瞬态物理国家重点实验室江苏南京210094 海军驻沈阳弹药专业军事总代表室辽宁沈阳110045 南京理工大学能源与动力工程学院江苏南京210094

将最大似然准则应用于高速旋转弹丸的气动参数辨识问题中,提出一种新的自适应混沌变异粒子群算法求解该准则下的气动参数最优解,进而得到弹丸的气动参数。该算法通过自适应调整惯性权重、利用混沌优化的思想产生初始粒子、设定早熟判别... 详细信息

将最大似然准则应用于高速旋转弹丸的气动参数辨识问题中,提出一种新的自适应混沌变异粒子群算法求解该准则下的气动参数最优解,进而得到弹丸的气动参数。该算法通过自适应调整惯性权重、利用混沌优化的思想产生初始粒子、设定早熟判别机制来判断是否陷入局部最优解,并通过粒子变异的策略使其跳出局部最优解等方法进一步优化基本粒子群算法。通过常用的测试函数对该算法进行了测试,测试结果表明:相比于基本粒子群算法,该算法具有收敛速度快、寻优精度高、应用范围广等优点。利用系统仿真的方法模拟弹丸的自由飞行数据,并利用该数据结合所提算法对弹丸的主要气动参数进行辨识,辨识结果表明:该算法可以有效辨识弹丸的气动参数,且精度高,收敛速度快,可以应用于工程实际问题。

关键词：兵器科学与技术弹丸气动参数辨识粒子群优化算法最大似然准则

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Effect of solute Ce,Mn,and Si on mechanical properties of silicon steel:insights from DFT calculations

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Journal of Iron and Steel Research International 2024年第3期31卷 700-709页

作者： Xiang-jun Liu Ji-chun Yang Hui-ping Ren Xiao-bin Jia Ming-yi Zhang Chang-qiao Yang School of Materials and Metallurgy Inner Mongolia University of Science and TechnologyBaotou 014010Inner MongoliaChina Key Laboratory of Integrated Exploitation of Bayan Obo Multi-Metal Resource Inner Mongolia University of Science and TechnologyBaotou 014010Inner MongoliaChina Inner Mongolia North Heavy Industries Group Co. Ltd.Baotou 014010Inner MongoliaChina Inner Mongolia Metal Material Research Institute Baotou 014010Inner MongoliaChina

The influence of solute Ce,Mn,and Si on the mechanical properties of silicon steel was investigated by first-principles ***,Mn,and Si can all be solubilized in Fe *** significantly reduces the incompressibility and rigidity of the system but also significantly improves the toughness and *** effect of Mn on mechanical properties of the system is not *** has a significant effect on the improvement in incompressibility and rigidity but a limited effect on the improvement in toughness and *** metallic bond strength of Fe-Ce,Fe-Mn,and Fe-Si doped systems is weaker than that of the pure Fe system,which can be used to explain the reduction in the incompressibility and rigidity of these doped *** relatively high electron cloud density in the doped system may be responsible for the increase in toughness.

关键词： Silicon steel Rare earth First-principles calculation Elastic modulus Electronic structure