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A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization 被引量:1
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作者 Sheng Qi Rui Wang +3 位作者 Tao Zhang Xu Yang Ruiqing Sun Ling Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第6期1342-1357,共16页
Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.... Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed. 展开更多
关键词 Evolutionary algorithms learning swarm optimiza-tion sparse large-scale optimization sparse large-scale multi-objec-tive problems two-layer encoding.
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Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases 被引量:1
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作者 Yating ZHAO Ming XUE +2 位作者 Jing JIANG Xiao-Ming HU Anning HUANG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第4期619-638,共20页
Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss pos... Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios. 展开更多
关键词 NARCCAP Central United States PRECIPITATION low-level jet large-scale environment diurnal variation
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Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems
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作者 Sheng Qi Rui Wang +3 位作者 Tao Zhang Weixiong Huang Fan Yu Ling Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第8期1786-1801,共16页
Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to tr... Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges. 展开更多
关键词 Evolutionary algorithms pattern mining sparse large-scale multi-objective problems(SLMOPs) sparse large-scale optimization.
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Large-scale model testing of high-pressure grouting reinforcement for bedding slope with rapid-setting polyurethane
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作者 ZHANG Zhichao TANG Xuefeng +2 位作者 LIU Kan YE Longzhen HE Xiang 《Journal of Mountain Science》 SCIE CSCD 2024年第9期3083-3093,共11页
Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining wal... Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining walls,stabilizing piles,and anchors,are time-consuming and labor-and energy-intensive.This study proposes an innovative polymer grout method to improve the bearing capacity and reduce the displacement of bedding slopes.A series of large-scale model tests were carried out to verify the effectiveness of polymer grout in protecting bedding slopes.Specifically,load-displacement relationships and failure patterns were analyzed for different testing slopes with various dosages of polymer.Results show the great potential of polymer grout in improving bearing capacity,reducing settlement,and protecting slopes from being crushed under shearing.The polymer-treated slopes remained structurally intact,while the untreated slope exhibited considerable damage when subjected to loads surpassing the bearing capacity.It is also found that polymer-cemented soils concentrate around the injection pipe,forming a fan-shaped sheet-like structure.This study proves the improvement of polymer grouting for bedding slope treatment and will contribute to the development of a fast method to protect bedding slopes from landslides. 展开更多
关键词 POLYURETHANE Bedding slope GROUTING Slope protection large-scale model test
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Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics
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作者 Siwei Li Liang Yue +1 位作者 Xiangyu Kong Chengshan Wang 《Global Energy Interconnection》 EI CSCD 2024年第3期313-323,共11页
This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online ide... This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective. 展开更多
关键词 Load aggregation Regional large-scale Online recognition Feature extraction method
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A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment
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作者 Chenguang Ouyang Suxing Hu +6 位作者 Fengqi Long Shuai Shi Zhichao Yu Kaichun Zhao Zheng You Junyin Pi Bowen Xing 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第4期1-10,共10页
Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework... Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m. 展开更多
关键词 large-scale positioning Building vector matching Improved particle filter GPS-Denied Vector map
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Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables
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作者 Liang Chen Jingbo Zhang +2 位作者 Linjie Wu Xingjuan Cai Yubin Xu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期363-383,共21页
The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the intera... The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage. 展开更多
关键词 Decision variable grouping large-scale multi-objective optimization algorithms weighted overlapping grouping direction-guided evolution
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A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating
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作者 Rongrong Ren Luyang Su +2 位作者 Xinyu Meng Jianfang Wang Meng Zhao 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第1期429-458,共30页
With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that consid... With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted. 展开更多
关键词 large-scale group decision making social network updating trust relationship group consensus feedback mechanism
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Large-Scale Carbon Dioxide Storage in Salt Caverns:Evaluation of Operation,Safety,and Potential in China
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作者 Wei Liu Xiong Zhang +8 位作者 Jifang Wan Chunhe Yang Liangliang Jiang Zhangxin Chen Maria Jose Jurado Xilin Shi Deyi Jiang Wendong Ji Qihang Li 《Engineering》 SCIE EI CAS CSCD 2024年第9期226-246,共21页
Underground salt cavern CO_(2) storage(SCCS)offers the dual benefits of enabling extensive CO_(2) storage and facilitating the utilization of CO_(2) resources while contributing the regulation of the carbon market.Its... Underground salt cavern CO_(2) storage(SCCS)offers the dual benefits of enabling extensive CO_(2) storage and facilitating the utilization of CO_(2) resources while contributing the regulation of the carbon market.Its economic and operational advantages over traditional carbon capture,utilization,and storage(CCUS)projects make SCCS a more cost-effective and flexible option.Despite the widespread use of salt caverns for storing various substances,differences exist between SCCS and traditional salt cavern energy storage in terms of gas-tightness,carbon injection,brine extraction control,long-term carbon storage stability,and site selection criteria.These distinctions stem from the unique phase change characteristics of CO_(2) and the application scenarios of SCCS.Therefore,targeted and forward-looking scientific research on SCCS is imperative.This paper introduces the implementation principles and application scenarios of SCCS,emphasizing its connections with carbon emissions,carbon utilization,and renewable energy peak shaving.It delves into the operational characteristics and economic advantages of SCCS compared with other CCUS methods,and addresses associated scientific challenges.In this paper,we establish a pressure equation for carbon injection and brine extraction,that considers the phase change characteristics of CO_(2),and we analyze the pressure during carbon injection.By comparing the viscosities of CO_(2) and other gases,SCCS’s excellent sealing performance is demonstrated.Building on this,we develop a long-term stability evaluation model and associated indices,which analyze the impact of the injection speed and minimum operating pressure on stability.Field countermeasures to ensure stability are proposed.Site selection criteria for SCCS are established,preliminary salt mine sites suitable for SCCS are identified in China,and an initial estimate of achievable carbon storage scale in China is made at over 51.8-77.7 million tons,utilizing only 20%-30%volume of abandoned salt caverns.This paper addresses key scientific and engineering challenges facing SCCS and determines crucial technical parameters,such as the operating pressure,burial depth,and storage scale,and it offers essential guidance for implementing SCCS projects in China. 展开更多
关键词 Carbon-neutrality Salt cavern large-scale CO_(2)storage Injection and withdrawal Stability analysis
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Factorized Smith Method for A Class of High-Ranked Large-Scale T-Stein Equations
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作者 LI Xiang YU Bo TANG Qiong 《Chinese Quarterly Journal of Mathematics》 2024年第3期235-249,共15页
We introduce a factorized Smith method(FSM)for solving large-scale highranked T-Stein equations within the banded-plus-low-rank structure framework.To effectively reduce both computational complexity and storage requi... We introduce a factorized Smith method(FSM)for solving large-scale highranked T-Stein equations within the banded-plus-low-rank structure framework.To effectively reduce both computational complexity and storage requirements,we develop techniques including deflation and shift,partial truncation and compression,as well as redesign the residual computation and termination condition.Numerical examples demonstrate that the FSM outperforms the Smith method implemented with a hierarchical HODLR structured toolkit in terms of CPU time. 展开更多
关键词 large-scale T-Stein equations High-ranked Deflation and shift Partially truncation and compression Smith method
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Large-scale spatial data visualization method based on augmented reality
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作者 Xiaoning QIAO Wenming XIE +4 位作者 Xiaodong PENG Guangyun LI Dalin LI Yingyi GUO Jingyi REN 《虚拟现实与智能硬件(中英文)》 EI 2024年第2期132-147,共16页
Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for rese... Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules. 展开更多
关键词 large-scale spatial data analysis Visual analysis technology Augmented reality 3D reconstruction Space environment
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The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine
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作者 GAO Yuan WU Zixuan +4 位作者 SHENG Boyang ZHANG Fu CHENG Yong YAN Junfeng PENG Qinghua 《Digital Chinese Medicine》 CAS CSCD 2024年第2期101-107,共7页
Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve ... Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications. 展开更多
关键词 Traditional Chinese medicine(TCM) Eye diagnosis Artificial intelligence(AI) large-scale model Self-supervised learning Deep neural network
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Numerical and theoretical study of large-scale failure of strata overlying sublevel caving mines with steeply dipping discontinuities
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作者 Kaizong Xia Zhiwei Si +3 位作者 Congxin Chen Xiaoshuang Li Junpeng Zou Jiahao Yuan 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2024年第8期1799-1815,共17页
The deformation and fracture evolution mechanisms of the strata overlying mines mined using sublevel caving were studied via numerical simulations.Moreover,an expression for the normal force acting on the side face of... The deformation and fracture evolution mechanisms of the strata overlying mines mined using sublevel caving were studied via numerical simulations.Moreover,an expression for the normal force acting on the side face of a steeply dipping superimposed cantilever beam in the surrounding rock was deduced based on limit equilibrium theory.The results show the following:(1)surface displacement above metal mines with steeply dipping discontinuities shows significant step characteristics,and(2)the behavior of the strata as they fail exhibits superimposition characteristics.Generally,failure first occurs in certain superimposed strata slightly far from the goaf.Subsequently,with the constant downward excavation of the orebody,the superimposed strata become damaged both upwards away from and downwards toward the goaf.This process continues until the deep part of the steeply dipping superimposed strata forms a large-scale deep fracture plane that connects with the goaf.The deep fracture plane generally makes an angle of 12°-20°with the normal to the steeply dipping discontinuities.The effect of the constant outward transfer of strata movement due to the constant outward failure of the superimposed strata in the metal mines with steeply dipping discontinuities causes the scope of the strata movement in these mines to be larger than expected.The strata in the metal mines with steeply dipping discontinuities mainly show flexural toppling failure.However,the steeply dipping structural strata near the goaf mainly exhibit shear slipping failure,in which case the mechanical model used to describe them can be simplified by treating them as steeply dipping superimposed cantilever beams.By taking the steeply dipping superimposed cantilever beam that first experiences failure as the key stratum,the failure scope of the strata(and criteria for the stability of metal mines with steeply dipping discontinuities mined using sublevel caving)can be obtained via iterative computations from the key stratum,moving downward toward and upwards away from the goaf. 展开更多
关键词 sublevel caving mines universal distinct element code(UDEC)numerical approach large-scale ground movement steeply dipping superimposed cantilever beam toppling failure
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Assessing cutter-rock interaction during TBM tunnelling in granite:Large-scale standing rotary cutting tests and 3D DEM simulations
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作者 Xin Huang Miaoyuan Tang +4 位作者 Shuaifeng Wang Yixin Zhai Qianwei Zhuang Chi Zhang Qinghua Lei 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第9期3595-3615,共21页
The widespread utilisation of tunnel boring machines(TBMs)in underground construction engineering requires a detailed investigation of the cutter-rock interaction.In this paper,we conduct a series of largescale standi... The widespread utilisation of tunnel boring machines(TBMs)in underground construction engineering requires a detailed investigation of the cutter-rock interaction.In this paper,we conduct a series of largescale standing rotary cutting tests on granite in conjunction with high-fidelity numerical simulations based on a particle-type discrete element method(DEM)to explore the effects of key cutting parameters on the TBM cutter performance and the distribution of cutter-rock contact stresses.The assessment results of cutter performance obtained from the cutting tests and numerical simulations reveal similar dependencies on the key cutting parameters.More specifically,the normal and rolling forces exhibit a positive correlation with penetration but are slightly influenced by the cutting radius.In contrast,the side force decreases as the cutting radius increases.Additionally,the side force shows a positive relationship with the penetration for smaller cutting radii but tends to become negative as the cutting radius increases.The cutter's relative effectiveness in rock breaking is significantly impacted by the penetration but shows little dependency on the cutting radius.Consequently,an optimal penetration is identified,leading to a low boreability index and specific energy.A combined Hertz-Weibull function is developed to fit the cutter-rock contact stress distribution obtained in DEM simulations,whereby an improved CSM(Colorado School of Mines)model is proposed by replacing the original monotonic cutting force distribution with this combined Hertz-Weibull model.The proposed model outperforms the original CSM model as demonstrated by a comparison of the estimated cutting forces with those from the tests/simulations.The findings from this work that advance our understanding of TBM cutter performance have important implications for improving the efficiency and reliability of TBM tunnelling in granite. 展开更多
关键词 large-scale standing rotary cutting test Discrete element method(DEM)simulation Cutter-rock interaction Improved CSM(Colorado School of Mines) model Cutting force
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Financial Calculation Problems and Countermeasure Analysis of Large-Scale Engineering Construction Projects
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作者 Qiong Hou 《Proceedings of Business and Economic Studies》 2024年第2期15-21,共7页
The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s... The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s economic benefits,minimize unnecessary costs,and provide decision-makers with a robust financial foundation.Additionally,implementing an effective cash flow control mechanism and conducting a comprehensive assessment of potential project risks can ensure financial stability and mitigate the risk of fund shortages.Developing a practical and feasible fundraising plan,along with stringent fund management practices,can prevent fund wastage and optimize fund utilization efficiency.These measures not only facilitate smooth project progression and improve project management efficiency but also enhance the project’s economic and social outcomes. 展开更多
关键词 large-scale engineering construction projects Financial calculation Fund management
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Digital Application Objectives and Benefit Analysis of BIM Technology in Large-Scale Comprehensive Development Projects
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作者 Chunhui Yang 《Journal of World Architecture》 2024年第5期24-28,共5页
This paper discusses the digital application and benefit analysis of building information model(BIM)technology in the large-scale comprehensive development project of the Guangxi headquarters base.The project covers a... This paper discusses the digital application and benefit analysis of building information model(BIM)technology in the large-scale comprehensive development project of the Guangxi headquarters base.The project covers a total area of 92,100 square meters,with a total construction area of 379,700 square meters,including a variety of architectural forms.Through three-dimensional modeling and simulation analysis,BIM technology significantly enhances the design quality and efficiency,shortens the design cycle by about 20%,and promotes the collaboration and integration of project management,improving the management efficiency by about 25%.During the construction phase,the collision detection and four-dimensional visual management functions of BIM technology have improved construction efficiency by about 15%and saved the cost by about 10%.In addition,BIM technology has promoted green building and sustainable development,achieved the dual improvement of technical and economic indicators and social and economic benefits,set an example for enterprises in digital transformation,and opened up new market businesses. 展开更多
关键词 Building information model technology large-scale comprehensive development Digital application Benefit analysis
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Gleaning insights from German energy transition and large-scale underground energy storage for China’s carbon neutrality 被引量:11
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作者 Yachen Xie Xuning Wu +6 位作者 Zhengmeng Hou Zaoyuan Li Jiashun Luo Christian Truitt Lüddeke Liangchao Huang Lin Wu Jianxing Liao 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2023年第5期529-553,共25页
The global energy transition is a widespread phenomenon that requires international exchange of experiences and mutual learning.Germany’s success in its first phase of energy transition can be attributed to its adopt... The global energy transition is a widespread phenomenon that requires international exchange of experiences and mutual learning.Germany’s success in its first phase of energy transition can be attributed to its adoption of smart energy technology and implementation of electricity futures and spot marketization,which enabled the achievement of multiple energy spatial–temporal complementarities and overall grid balance through energy conversion and reconversion technologies.While China can draw from Germany’s experience to inform its own energy transition efforts,its 11-fold higher annual electricity consumption requires a distinct approach.We recommend a clean energy system based on smart sector coupling(ENSYSCO)as a suitable pathway for achieving sustainable energy in China,given that renewable energy is expected to guarantee 85%of China’s energy production by 2060,requiring significant future electricity storage capacity.Nonetheless,renewable energy storage remains a significant challenge.We propose four large-scale underground energy storage methods based on ENSYSCO to address this challenge,while considering China’s national conditions.These proposals have culminated in pilot projects for large-scale underground energy storage in China,which we believe is a necessary choice for achieving carbon neutrality in China and enabling efficient and safe grid integration of renewable energy within the framework of ENSYSCO. 展开更多
关键词 Carbon neutrality Energy transition large-scale underground energy storage Sector coupling
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Comparison of Pile-Soil-Structure Interaction Modeling Techniques for A 10-MW Large-Scale Monopile Wind Turbine Model Under Wind and Wave Conditions 被引量:2
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作者 ZENG Yu-xin ZHANG Xiao-ming +3 位作者 ZHANG Li-xian SHI Wei WANG Wen-hua LI Xin 《China Ocean Engineering》 SCIE EI CSCD 2023年第3期471-483,共13页
Considering the large diameter effect of piles,the influence of different pile-soil analysis methods on the design of monopile foundations for offshore wind turbines has become an urgent problem to be solved.Three dif... Considering the large diameter effect of piles,the influence of different pile-soil analysis methods on the design of monopile foundations for offshore wind turbines has become an urgent problem to be solved.Three different pile-soil models were used to study a large 10 MW monopile wind turbine.By modeling the three models in the SACS software,this paper analyzed the motion response of the overall structure under the conditions of wind and waves.According to the given working conditions,this paper concludes that under the condition of independent wind,the average value of the tower top x-displacement of the rigid connection method is the smalle st,and the standard deviation is the smallest under the condition of independent wave.The results obtained by the p-y curve method are the most conservative. 展开更多
关键词 large-scale monopile offshore wind turbine pile-soil model wind-wave load combination
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Modular Extremely Large-Scale Array Communication:Near-Field Modelling and Performance Analysis 被引量:2
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作者 Xinrui Li Haiquan Lu +2 位作者 Yong Zeng Shi Jin Rui Zhang 《China Communications》 SCIE CSCD 2023年第4期132-152,共21页
This paper investigates the wireless communication with a novel architecture of antenna arrays,termed modular extremely large-scale array(XLarray),where array elements of an extremely large number/size are regularly m... This paper investigates the wireless communication with a novel architecture of antenna arrays,termed modular extremely large-scale array(XLarray),where array elements of an extremely large number/size are regularly mounted on a shared platform with both horizontally and vertically interlaced modules.Each module consists of a moderate/flexible number of array elements with the inter-element distance typically in the order of the signal wavelength,while different modules are separated by the relatively large inter-module distance for convenience of practical deployment.By accurately modelling the signal amplitudes and phases,as well as projected apertures across all modular elements,we analyse the near-field signal-to-noise ratio(SNR)performance for modular XL-array communications.Based on the non-uniform spherical wave(NUSW)modelling,the closed-form SNR expression is derived in terms of key system parameters,such as the overall modular array size,distances of adjacent modules along all dimensions,and the user's three-dimensional(3D)location.In addition,with the number of modules in different dimensions increasing infinitely,the asymptotic SNR scaling laws are revealed.Furthermore,we show that our proposed near-field modelling and performance analysis include the results for existing array architectures/modelling as special cases,e.g.,the collocated XL-array architecture,the uniform plane wave(UPW)based far-field modelling,and the modular extremely large-scale uniform linear array(XL-ULA)of onedimension.Extensive simulation results are presented to validate our findings. 展开更多
关键词 modular extremely large-scale array practical deployment projected apertures non-uniform spherical wave near-field modelling
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CFSA-Net:Efficient Large-Scale Point Cloud Semantic Segmentation Based on Cross-Fusion Self-Attention 被引量:1
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作者 Jun Shu Shuai Wang +1 位作者 Shiqi Yu Jie Zhang 《Computers, Materials & Continua》 SCIE EI 2023年第12期2677-2697,共21页
Traditional models for semantic segmentation in point clouds primarily focus on smaller scales.However,in real-world applications,point clouds often exhibit larger scales,leading to heavy computational and memory requ... Traditional models for semantic segmentation in point clouds primarily focus on smaller scales.However,in real-world applications,point clouds often exhibit larger scales,leading to heavy computational and memory requirements.The key to handling large-scale point clouds lies in leveraging random sampling,which offers higher computational efficiency and lower memory consumption compared to other sampling methods.Nevertheless,the use of random sampling can potentially result in the loss of crucial points during the encoding stage.To address these issues,this paper proposes cross-fusion self-attention network(CFSA-Net),a lightweight and efficient network architecture specifically designed for directly processing large-scale point clouds.At the core of this network is the incorporation of random sampling alongside a local feature extraction module based on cross-fusion self-attention(CFSA).This module effectively integrates long-range contextual dependencies between points by employing hierarchical position encoding(HPC).Furthermore,it enhances the interaction between each point’s coordinates and feature information through cross-fusion self-attention pooling,enabling the acquisition of more comprehensive geometric information.Finally,a residual optimization(RO)structure is introduced to extend the receptive field of individual points by stacking hierarchical position encoding and cross-fusion self-attention pooling,thereby reducing the impact of information loss caused by random sampling.Experimental results on the Stanford Large-Scale 3D Indoor Spaces(S3DIS),Semantic3D,and SemanticKITTI datasets demonstrate the superiority of this algorithm over advanced approaches such as RandLA-Net and KPConv.These findings underscore the excellent performance of CFSA-Net in large-scale 3D semantic segmentation. 展开更多
关键词 Semantic segmentation large-scale point cloud random sampling cross-fusion self-attention
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