To comprehensively utilize the valuable geological map,exploration profile,borehole,and geochemical logging data and the knowledge on the formation of the Jinshan Ag-Au deposit for forecasting the exploration targets ...To comprehensively utilize the valuable geological map,exploration profile,borehole,and geochemical logging data and the knowledge on the formation of the Jinshan Ag-Au deposit for forecasting the exploration targets of concealed ore bodies,three-dimensional Mineral Prospectivity Modeling(MPM)of the deposit has been conducted using the weights-of-evidence(WofE)method.Conditional independence between evidence layers was tested,and the outline results using the prediction-volume(P-V)and Student's t-statistic methods for delineating favorable mineralization areas from continuous posterior probability map were critically compared.Four exploration targets delineated ultimately by the Student's t-statistic method for the discovery of minable ore bodies in each of the target areas were discussed in detail.The main conclusions include:(1)three-dimensional modeling of a deposit using multi-source reconnaissance data is useful for MPM in interpreting their relationships with known ore bodies;(2)WofE modeling can be used as a straightforward tool for integrating deposit model and reconnaissance data in MPM;(3)the Student's t-statistic method is more applicable in binarizing the continuous prospectivity map for exploration targeting than the PV approach;and(4)two target areas within high potential to find undiscovered ore bodies were diagnosed to guide future near-mine exploration activities of the Jinshan deposit.展开更多
Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to en...Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to engineering requirements, aiming to optimize satellite heat dissipation while considering constraints on static stability, 3D geometric relationships between components, and special component positions. The 3D-SCALO problem is a challenging bilevel combinatorial optimization task, involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer,with both influencing each other. To address this issue, first, a Mixed Integer Programming(MIP) model is proposed, which reformulates the original bilevel problem into a single-level optimization problem, enabling the exploration of a more comprehensive optimization space while avoiding iterative nested optimization. Then, to model the 3D geometric relationships between components within the MIP framework, a linearized 3D Phi-function method is proposed, which handles non-overlapping and safety distance constraints between cuboid components in an explicit and effective way. Subsequently, the Finite-Rectangle Method(FRM) is proposed to manage 3D geometric constraints for complex-shaped components by approximating them with a finite set of cuboids, extending the applicability of the geometric modeling approach. Finally, the feasibility and effectiveness of the proposed MIP model are demonstrated through two numerical examples"and a real-world engineering case, which confirms its suitability for complex-shaped components and real engineering applications.展开更多
In the context of global digital transformation and the rising prominence of maker education,this study explores the innovative integration of digital modeling technologies with traditional Nixing Pottery craftsmanshi...In the context of global digital transformation and the rising prominence of maker education,this study explores the innovative integration of digital modeling technologies with traditional Nixing Pottery craftsmanship.By constructing a teaching framework under maker education theory,the research investigates how 3D modeling,CAD design,and 3D printing technologies can empower learners to address challenges in cultural heritage preservation and artistic innovation.Through experimental teaching and case analysis,the study verifies that this integrated approach significantly enhances learners’digital literacy,creative thinking,and cultural identity while optimizing Nixing Pottery’s production processes and design possibilities.The findings contribute to theoretical models of technology-enhanced craft education and provide practical pathways for the digital transformation of intangible cultural heritage.展开更多
Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel beha...Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel behaviors,e.g.,large-scale/small-scale fading,spatio-temporal-frequency non-stationarity,through mathematical and data-driven methods.This enables simulation-based validation across system development stages—from protocol design to network optimization-without costly physical testing.展开更多
The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D desi...The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.展开更多
Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade compone...Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade components.In this paper,a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established.Based on Kirchhoff's plate assumptions,the displacement variables of the plate are expressed.By incorporating the braiding directions into the constitutive equation of the braided composites,the dynamic model of the plate considering braiding directions is obtained.The effects of the speeds,braiding directions,and braided angles on the responses of the plate with fixed-axis rotation and translational motion,respectively,are investigated.This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions.It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.展开更多
The problem of taking an unorganized point cloud in 3D space and fitting a polyhedral surface to those points is both important and difficult. Aiming at increasing applications of full three dimensional digital terrai...The problem of taking an unorganized point cloud in 3D space and fitting a polyhedral surface to those points is both important and difficult. Aiming at increasing applications of full three dimensional digital terrain surface modeling, a new algorithm for the automatic generation of three dimensional triangulated irregular network from a point cloud is pro- posed. Based on the local topological consistency test, a combined algorithm of constrained 3D Delaunay triangulation and region-growing is extended to ensure topologically correct reconstruction. This paper also introduced an efficient neighbor- ing triangle location method by making full use of the surface normal information. Experimental results prove that this algo- rithm can efficiently obtain the most reasonable reconstructed mesh surface with arbitrary topology, wherein the automati- cally reconstructed surface has only small topological difference from the true surface. This algorithm has potential applica- tions to virtual environments, computer vision, and so on.展开更多
Despite broad consensus on the importance of enterprise digital transformation,significant discrepancies persist regarding its actual effects.This divergence stems primarily from two key measurement challenges:(1)a la...Despite broad consensus on the importance of enterprise digital transformation,significant discrepancies persist regarding its actual effects.This divergence stems primarily from two key measurement challenges:(1)a lack of clear and consistent definitions of enterprise digital transformation,and(2)a lack of rigorous and accurate measurement methodologies.These shortcomings lead to research findings that are incomparable,difficult to replicate,and often conflicting.To effectively address the aforementioned challenges,this paper employs machine learning and large language models(LLMs)to construct a novel set of indicators for enterprise digital transformation.The work begins by manually annotating sentences from annual reports of listed companies in China from 2006 to 2020.These labeled sentences are then used to train and fine-tune several machine learning models,including LLMs.The ERNIE model,demonstrating the best classification performance among the models tested,is selected as the sentence classifier to predict sentence labels across the full text of the annual reports,ultimately constructing the enterprise digital transformation metrics.Both theoretical analysis and multiple data cross-validations demonstrate that the metrics developed in this paper are more accurate than existing approaches.Based on these metrics,the paper empirically examines the impact of enterprise digital transformation on financial performance.Our findings reveal three key points:(1)enterprise digital transformation significantly enhances financial performance,with big data,AI,mobile internet,cloud computing,and the Internet of Things(IoT)all playing a significant role;however,blockchain technology does not show a significant effect;(2)the significant positive effect of digital transformation on financial performance is primarily observed in firms with weaker initial financial performance;and(3)enterprise digital transformation improves financial performance mainly through enhancing efficiency and reducing costs.This research has practical implications for promoting enterprise digital transformation and fostering high-quality economic development.展开更多
The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying ge...The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying geotechnical responses(e.g.consolidation settlement)in a 3D spatial domain.However,traditional 3D numerical model updating approaches are computationally prohibitive and therefore difficult to update the 3D responses in real time.To address these challenges,this study proposes a novel machine learning framework called sparse dictionary learning(T-3D-SDL)for real-time updating of time-varying 3D geotechnical responses.In T-3D-SDL,a concerned dataset(e.g.time-varying 3D settlement)is approximated as a linear superposition of dictionary atoms generated from 3D random FEM analyses.Field monitoring data are then used to identify non-trivial atoms and estimate their weights within a Bayesian framework for model updating and prediction.The proposed approach enables the real-time update of temporally varying settlements with a high 3D spatial resolution and quantified uncertainty as field monitoring data evolve.The proposed approach is illustrated using an embankment construction project.The results show that the proposed approach effectively improves settlement predictions along temporal and 3D spatial dimensions,with minimal latency(e.g.within minutes),as monitoring data appear.In addition,the proposed approach requires only a reasonably small number of 3D FEM model evaluations,avoids the use of widely adopted yet often criticized surrogate models,and effectively addresses the limitations(e.g.computational inefficiency)of existing 3D model updating approaches.展开更多
Geared-rotor systems are critical components in mechanical applications,and their performance can be severely affected by faults,such as profile errors,wear,pitting,spalling,flaking,and cracks.Profile errors in gear t...Geared-rotor systems are critical components in mechanical applications,and their performance can be severely affected by faults,such as profile errors,wear,pitting,spalling,flaking,and cracks.Profile errors in gear teeth are inevitable in manufacturing and subsequently accumulate during operations.This work aims to predict the status of gear profile deviations based on gear dynamics response using the digital model of an experimental rig setup.The digital model comprises detailed CAD models and has been validated against the expected physical behavior using commercial finite element analysis software.The different profile deviations are then modeled using gear charts,and the dynamic response is captured through simulations.The various features are then obtained by signal processing,and various ML models are then evaluated to predict the fault/no-fault condition for the gear.The best performance is achieved by an artificial neural network with a prediction accuracy of 97.5%,which concludes a strong influence on the dynamics of the gear rotor system due to profile deviations.展开更多
The identification of rock mass discontinuities is critical for rock mass characterization.While high-resolution digital outcrop models(DOMs)are widely used,current digital methods struggle to generalize across divers...The identification of rock mass discontinuities is critical for rock mass characterization.While high-resolution digital outcrop models(DOMs)are widely used,current digital methods struggle to generalize across diverse geological settings.Large-scale models(LSMs),with vast parameter spaces and extensive training datasets,excel in solving complex visual problems.This study explores the potential of using one such LSM,Segment anything model(SAM),to identify facet-type discontinuities across several outcrops via interactive prompting.The findings demonstrate that SAM effectively segments two-dimensional(2D)discontinuities,with its generalization capability validated on a dataset of 2426 identified discontinuities across 170 outcrops.The model achieves 0.78 mean IoU and 0.86 average precision using 11-point prompts.To extend to three dimensions(3D),a framework integrating SAM with Structure-from-Motion(SfM)was proposed.By utilizing the inherent but often overlooked relationship between image pixels and point clouds in SfM,the identification process was simplified and generalized across photogrammetric devices.Benchmark studies showed that the framework achieved 0.91 average precision,identifying 87 discontinuities in Dataset-3D.The results confirm its high precision and efficiency,making it a valuable tool for data annotation.The proposed method offers a practical solution for geological investigations.展开更多
Against the backdrop of the rapid development of the digital economy,corporate financial management faces unprecedented challenges and opportunities.This paper will start with the concept of financial shared services ...Against the backdrop of the rapid development of the digital economy,corporate financial management faces unprecedented challenges and opportunities.This paper will start with the concept of financial shared services to deeply explore the role and significance of the financial shared service model in the digital transformation of corporate finance.It analyzes the existing problems in the current process of digital transformation of corporate finance and proposes corresponding solutions,providing valuable references and guidance for enterprises to achieve digital transformation of finance.展开更多
The digital economy has injected continuous momentum into the development of urban economy and plays a positive and important role in the transformation and upgrading of urban energy consumption.Specifically,the digit...The digital economy has injected continuous momentum into the development of urban economy and plays a positive and important role in the transformation and upgrading of urban energy consumption.Specifically,the digital economy can significantly improve the efficiency of urban energy consumption by virtue of its distinctive characteristics of low pollution and high efficiency.Moreover,empowered by the digital economy,the pace of transformation and upgrading of high-pollution traditional industries has been accelerated.Particularly importantly,the urban energy consumption structure has been optimized and adjusted through the indirect role of intermediate factors.From this perspective,studying the current situation and countermeasures of urban energy consumption under the digital economy holds important practical significance both in theory and practice.This paper first briefly summarizes the relevant literature on the impact of the digital economy on the energy consumption structure;then,it focuses on detailed data to explore the current situation of urban energy consumption under the digital economy model;finally,based on the summary of the current situation,it puts forward practical and feasible suggestions,hoping to provide a decision-making basis for the implementation of policies in different types of cities and offer innovative ideas for promoting the high-quality development of urban energy systems.展开更多
With the advancement of digital technology,new technologies such as artificial intelligence,big data,and cloud computing have gradually permeated higher education,leading to fundamental changes in teaching and learnin...With the advancement of digital technology,new technologies such as artificial intelligence,big data,and cloud computing have gradually permeated higher education,leading to fundamental changes in teaching and learning methods.Therefore,in the process of reforming and developing higher education,it is essential to take digital technology empowering the optimization of the education industry as a breakthrough,focusing on five key areas:the construction of smart classrooms,the digital integration of teaching resources,the development of personalized learning support systems,the reform of online-offline hybrid teaching,and the intelligentization of educational management.This paper also examines the experiences,challenges,and shortcomings of typical universities in using digital technology to improve teaching quality,optimize resource allocation,and innovate teaching management models.Finally,corresponding countermeasures and suggestions are proposed to facilitate the smooth implementation of digital transformation in higher education institutions.展开更多
It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimens...It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.展开更多
Under the dual impetus of the fundamental task of“cultivating virtue and nurturing talent”and the national strategy of digitalizing education,promoting the deep integration of ideological and political education in ...Under the dual impetus of the fundamental task of“cultivating virtue and nurturing talent”and the national strategy of digitalizing education,promoting the deep integration of ideological and political education in courses with digital technology has become a core issue in the curriculum reform of colleges and universities.This paper takes the course“Business Model Innovation”as the research object and focuses on the problems existing in the current course,such as lagging content update,superficial application of digital tools,and weakening elements of ideological and political education.This paper proposes a teaching reform path that is supported by digital means and centered on value guidance,and focuses on how to systematically optimize teaching content design,interactive teaching scenarios,evaluation and feedback mechanisms,and teacher collaboration systems through specific tools such as“Rain Classroom,”“Enterprise Sand Table,”and“Smart Classroom Platform.”We aim to build a digital model of ideological and political education in the curriculum that integrates knowledge imparting,ability training,and value shaping,and to provide practical reference and path support for the cultivation of high-quality business talents in the new era.展开更多
To address the shortage of characterization scale of field outcrops,we used the characteristics of unmanned aerial vehicle(UAV)oblique photography with a wide field of view and a high degree of quantification for imag...To address the shortage of characterization scale of field outcrops,we used the characteristics of unmanned aerial vehicle(UAV)oblique photography with a wide field of view and a high degree of quantification for image acquisition,data processing,and geological interpretation of the outcrops of the Shaximiao Formation in the Sichuan Basin.We established a 3D digital outcrop model(DOM),which combines the advantages of visualization and digitization the 3D DOM to interpret the characteristics of typical channel sand bodies.Within the study area,we have identified three types of channel deposition:composite channel deposition,crevasse channel deposition,and abandoned channel deposition.Among these,the composite channel deposition was mainly sandstone,the bottom contains conglomerate,with large cross-bedding,and the maximum thickness of the single sand body was 1.96 m.The crevasse channel deposition was mainly fine sandstone and siltstone,with massive bedding and small cross-bedding,and the maximum thickness of the single sand body was 0.64 m.The abandoned channel deposition dominated by mudstone with thin sandstone,the sandstone was mainly lenticular in section,and the maximum thickness of the single sand body was 0.28 m.We identified the depositional model of the studied region,which is dominated by braided river deposition,based on the growth size and correspondence of the sand bodies.The research provides a comparative foundation for the detailed characterisation of the underground reservoir sands found in the Jurassic Shaximiao Formation in the Sichuan Basin.It also serves as a reference for the effective study of UAV oblique photography technology in the field.展开更多
Coral reef limestone(CRL)constitutes a distinctive marine carbonate formation with complex mechanical properties.This study investigates the multiscale damage and fracture mechanisms of CRL through integrated experime...Coral reef limestone(CRL)constitutes a distinctive marine carbonate formation with complex mechanical properties.This study investigates the multiscale damage and fracture mechanisms of CRL through integrated experimental testing,digital core technology,and theoretical modelling.Two CRL types with contrasting mesostructures were characterized across three scales.Macroscopically,CRL-I and CRL-II exhibited mean compressive strengths of 8.46 and 5.17 MPa,respectively.Mesoscopically,CRL-I featured small-scale highly interconnected pores,whilst CRL-II developed larger stratified pores with diminished connectivity.Microscopically,both CRL matrices demonstrated remarkable similarity in mineral composition and mechanical properties.A novel voxel average-based digital core scaling methodology was developed to facilitate numerical simulation of cross-scale damage processes,revealing network-progressive failure in CRL-I versus directional-brittle failure in CRL-II.Furthermore,a damage statistical constitutive model based on digital core technology and mesoscopic homogenisation theory established quantitative relationships between microelement strength distribution and macroscopic mechanical behavior.These findings illuminate the fundamental mechanisms through which mesoscopic structure governs the macroscopic mechanical properties of CRL.展开更多
The human digital twin(HDT)emerges as a promising human-centric technology in Industry 5.0,but challenges remain in human modeling and simulation.Digital human modeling(DHM)provides solutions for modeling and simulati...The human digital twin(HDT)emerges as a promising human-centric technology in Industry 5.0,but challenges remain in human modeling and simulation.Digital human modeling(DHM)provides solutions for modeling and simulating human physical and cognitive aspects to support ergonomic analysis.However,it has limitations in real-time data usage,personalized services,and timely interaction.The emerging HDT concept offers new possibilities by integrating multi-source data and artificial intelligence for continuous monitoring and assessment.Hence,this paper reviews the evolution from DHM to HDT and proposes a unified HDT framework from a human factors perspective.The framework comprises the physical twin,the virtual twin,and the linkage between these two.The virtual twin integrates human modeling and AI engines to enable model-data-hybrid-enabled simulation.HDT can potentially upgrade traditional ergonomic methods to intelligent services through real-time analysis,timely feedback,and bidirectional interactions.Finally,the future perspectives of HDT for industrial applications as well as technical and social challenges are discussed.In general,this study outlines a human factors perspective on HDT for the first time,which is useful for cross-disciplinary research and human factors innovation to enhance the development of HDT in industry.展开更多
To address the problem that the display effect of hydrologic test data was not intuitive,the three-dimensional modeling technology of a hydrologic test reach based on GIS technology was proposed.The reach of of the Ye...To address the problem that the display effect of hydrologic test data was not intuitive,the three-dimensional modeling technology of a hydrologic test reach based on GIS technology was proposed.The reach of of the Yellow River around Lanzhou hydrological station was selected to study three-dimensional modeling.The elevation data of river was processed through three-dimensional model constructing,water surface modeling and three-dimensional animation demonstration by using ArcGIS Pro software.Based on the historical highest flood level data of the test reach on September 15,1981,the real scene restoration was carried out based on the three-dimensional model,and the hydrological factors such as water depth and channel storage were analyzed.The three-dimensional modeling based on GIS technology can directly and realistically reflect the changes of topography and water surface of the test reach,and improve the application of hydrologic test results in flood control.展开更多
基金financially supported by the Ministry of Science and Technology of China(Nos.2022YFF0801201,2021YFC2900300)the National Natural Science Foundation of China(Nos.41872245,U1911202)the Guangdong Basic and Applied Basic Research Foundation(No.2020A1515010666)。
文摘To comprehensively utilize the valuable geological map,exploration profile,borehole,and geochemical logging data and the knowledge on the formation of the Jinshan Ag-Au deposit for forecasting the exploration targets of concealed ore bodies,three-dimensional Mineral Prospectivity Modeling(MPM)of the deposit has been conducted using the weights-of-evidence(WofE)method.Conditional independence between evidence layers was tested,and the outline results using the prediction-volume(P-V)and Student's t-statistic methods for delineating favorable mineralization areas from continuous posterior probability map were critically compared.Four exploration targets delineated ultimately by the Student's t-statistic method for the discovery of minable ore bodies in each of the target areas were discussed in detail.The main conclusions include:(1)three-dimensional modeling of a deposit using multi-source reconnaissance data is useful for MPM in interpreting their relationships with known ore bodies;(2)WofE modeling can be used as a straightforward tool for integrating deposit model and reconnaissance data in MPM;(3)the Student's t-statistic method is more applicable in binarizing the continuous prospectivity map for exploration targeting than the PV approach;and(4)two target areas within high potential to find undiscovered ore bodies were diagnosed to guide future near-mine exploration activities of the Jinshan deposit.
基金supported by the National Natural Science Foundation of China(No.92371206)the Postgraduate Scientific Research Innovation Project of Hunan Province,China(No.CX2023063).
文摘Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to engineering requirements, aiming to optimize satellite heat dissipation while considering constraints on static stability, 3D geometric relationships between components, and special component positions. The 3D-SCALO problem is a challenging bilevel combinatorial optimization task, involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer,with both influencing each other. To address this issue, first, a Mixed Integer Programming(MIP) model is proposed, which reformulates the original bilevel problem into a single-level optimization problem, enabling the exploration of a more comprehensive optimization space while avoiding iterative nested optimization. Then, to model the 3D geometric relationships between components within the MIP framework, a linearized 3D Phi-function method is proposed, which handles non-overlapping and safety distance constraints between cuboid components in an explicit and effective way. Subsequently, the Finite-Rectangle Method(FRM) is proposed to manage 3D geometric constraints for complex-shaped components by approximating them with a finite set of cuboids, extending the applicability of the geometric modeling approach. Finally, the feasibility and effectiveness of the proposed MIP model are demonstrated through two numerical examples"and a real-world engineering case, which confirms its suitability for complex-shaped components and real engineering applications.
文摘In the context of global digital transformation and the rising prominence of maker education,this study explores the innovative integration of digital modeling technologies with traditional Nixing Pottery craftsmanship.By constructing a teaching framework under maker education theory,the research investigates how 3D modeling,CAD design,and 3D printing technologies can empower learners to address challenges in cultural heritage preservation and artistic innovation.Through experimental teaching and case analysis,the study verifies that this integrated approach significantly enhances learners’digital literacy,creative thinking,and cultural identity while optimizing Nixing Pottery’s production processes and design possibilities.The findings contribute to theoretical models of technology-enhanced craft education and provide practical pathways for the digital transformation of intangible cultural heritage.
文摘Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel behaviors,e.g.,large-scale/small-scale fading,spatio-temporal-frequency non-stationarity,through mathematical and data-driven methods.This enables simulation-based validation across system development stages—from protocol design to network optimization-without costly physical testing.
文摘The management of large-scale architectural engineering projects(e.g.,airports,hospitals)is plagued by information silos,cost overruns,and scheduling delays.While building information modeling(BIM)has improved 3D design coordination,its static nature limits its utility in real-time construction management and operational phases.This paper proposes a novel synergistic framework that integrates the static,deep data of BIM with the dynamic,real-time capabilities of digital twin(DT)technology.The framework establishes a closed-loop data flow from design(BIM)to construction(IoT,drones,BIM 360)to operation(DT platform).We detail the technological stack required,including IoT sensors,cloud computing,and AI-driven analytics.The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project,demonstrating potential reductions in rework by 15%,improvement in labor productivity by 10%,and enhanced predictive maintenance capabilities.This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.
基金Project supported by the National Natural Science Foundation of China(Nos.12372071 and 12372070)the Aeronautical Science Fund of China(No.2022Z055052001)the Foundation of China Scholarship Council(No.202306830079)。
文摘Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade components.In this paper,a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established.Based on Kirchhoff's plate assumptions,the displacement variables of the plate are expressed.By incorporating the braiding directions into the constitutive equation of the braided composites,the dynamic model of the plate considering braiding directions is obtained.The effects of the speeds,braiding directions,and braided angles on the responses of the plate with fixed-axis rotation and translational motion,respectively,are investigated.This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions.It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.
基金Supported by the National Natural Science Foundation of China （No.40671158）, the National 863 Program of China（No.2006AA12Z224） and the Program for New Century Excellent Talents in University （No.NCET-05-0626）.
文摘The problem of taking an unorganized point cloud in 3D space and fitting a polyhedral surface to those points is both important and difficult. Aiming at increasing applications of full three dimensional digital terrain surface modeling, a new algorithm for the automatic generation of three dimensional triangulated irregular network from a point cloud is pro- posed. Based on the local topological consistency test, a combined algorithm of constrained 3D Delaunay triangulation and region-growing is extended to ensure topologically correct reconstruction. This paper also introduced an efficient neighbor- ing triangle location method by making full use of the surface normal information. Experimental results prove that this algo- rithm can efficiently obtain the most reasonable reconstructed mesh surface with arbitrary topology, wherein the automati- cally reconstructed surface has only small topological difference from the true surface. This algorithm has potential applica- tions to virtual environments, computer vision, and so on.
基金supported by the Fundamental Research Funds for the Central Universitiesfollowing projects:the Major Project of the National Social Science Fund of China(NSSFC)“Research on the Synergistic Mechanisms of Innovation and Governance for High-Quality Development of the Digital Economy”(Grant No.22&ZD070)+1 种基金the Youth Project of the National Natural Science Foundation of China(NSFC)“Research on Risk-Taking of Zombie Enterprises from a Government-Enterprise Interaction Perspective:Tendency,Behavioral Patterns,and Economic Consequences”(Grant No.72002213)the General Program of the National Natural Science Foundation of China(NSFC)“Reshaping Enterprise Nature,Boundaries,and Internal Organization in the Digital Economy”(Grant No.72273144).
文摘Despite broad consensus on the importance of enterprise digital transformation,significant discrepancies persist regarding its actual effects.This divergence stems primarily from two key measurement challenges:(1)a lack of clear and consistent definitions of enterprise digital transformation,and(2)a lack of rigorous and accurate measurement methodologies.These shortcomings lead to research findings that are incomparable,difficult to replicate,and often conflicting.To effectively address the aforementioned challenges,this paper employs machine learning and large language models(LLMs)to construct a novel set of indicators for enterprise digital transformation.The work begins by manually annotating sentences from annual reports of listed companies in China from 2006 to 2020.These labeled sentences are then used to train and fine-tune several machine learning models,including LLMs.The ERNIE model,demonstrating the best classification performance among the models tested,is selected as the sentence classifier to predict sentence labels across the full text of the annual reports,ultimately constructing the enterprise digital transformation metrics.Both theoretical analysis and multiple data cross-validations demonstrate that the metrics developed in this paper are more accurate than existing approaches.Based on these metrics,the paper empirically examines the impact of enterprise digital transformation on financial performance.Our findings reveal three key points:(1)enterprise digital transformation significantly enhances financial performance,with big data,AI,mobile internet,cloud computing,and the Internet of Things(IoT)all playing a significant role;however,blockchain technology does not show a significant effect;(2)the significant positive effect of digital transformation on financial performance is primarily observed in firms with weaker initial financial performance;and(3)enterprise digital transformation improves financial performance mainly through enhancing efficiency and reducing costs.This research has practical implications for promoting enterprise digital transformation and fostering high-quality economic development.
基金supported by a grant from the Research Grant Council of Hong Kong Special Administrative Region(Project No.11207724).
文摘The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying geotechnical responses(e.g.consolidation settlement)in a 3D spatial domain.However,traditional 3D numerical model updating approaches are computationally prohibitive and therefore difficult to update the 3D responses in real time.To address these challenges,this study proposes a novel machine learning framework called sparse dictionary learning(T-3D-SDL)for real-time updating of time-varying 3D geotechnical responses.In T-3D-SDL,a concerned dataset(e.g.time-varying 3D settlement)is approximated as a linear superposition of dictionary atoms generated from 3D random FEM analyses.Field monitoring data are then used to identify non-trivial atoms and estimate their weights within a Bayesian framework for model updating and prediction.The proposed approach enables the real-time update of temporally varying settlements with a high 3D spatial resolution and quantified uncertainty as field monitoring data evolve.The proposed approach is illustrated using an embankment construction project.The results show that the proposed approach effectively improves settlement predictions along temporal and 3D spatial dimensions,with minimal latency(e.g.within minutes),as monitoring data appear.In addition,the proposed approach requires only a reasonably small number of 3D FEM model evaluations,avoids the use of widely adopted yet often criticized surrogate models,and effectively addresses the limitations(e.g.computational inefficiency)of existing 3D model updating approaches.
文摘Geared-rotor systems are critical components in mechanical applications,and their performance can be severely affected by faults,such as profile errors,wear,pitting,spalling,flaking,and cracks.Profile errors in gear teeth are inevitable in manufacturing and subsequently accumulate during operations.This work aims to predict the status of gear profile deviations based on gear dynamics response using the digital model of an experimental rig setup.The digital model comprises detailed CAD models and has been validated against the expected physical behavior using commercial finite element analysis software.The different profile deviations are then modeled using gear charts,and the dynamic response is captured through simulations.The various features are then obtained by signal processing,and various ML models are then evaluated to predict the fault/no-fault condition for the gear.The best performance is achieved by an artificial neural network with a prediction accuracy of 97.5%,which concludes a strong influence on the dynamics of the gear rotor system due to profile deviations.
基金support in dataset preparation.This study was funded by National Natural Science Foundation of China(Nos.42422704 and 52379109)Opening the fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology)(No.SKLGP2024K028)Science and Technology Research and Design Projects of China State Construction Engineering Corporation Ltd.(No.CSCEC-2024-Q-68).
文摘The identification of rock mass discontinuities is critical for rock mass characterization.While high-resolution digital outcrop models(DOMs)are widely used,current digital methods struggle to generalize across diverse geological settings.Large-scale models(LSMs),with vast parameter spaces and extensive training datasets,excel in solving complex visual problems.This study explores the potential of using one such LSM,Segment anything model(SAM),to identify facet-type discontinuities across several outcrops via interactive prompting.The findings demonstrate that SAM effectively segments two-dimensional(2D)discontinuities,with its generalization capability validated on a dataset of 2426 identified discontinuities across 170 outcrops.The model achieves 0.78 mean IoU and 0.86 average precision using 11-point prompts.To extend to three dimensions(3D),a framework integrating SAM with Structure-from-Motion(SfM)was proposed.By utilizing the inherent but often overlooked relationship between image pixels and point clouds in SfM,the identification process was simplified and generalized across photogrammetric devices.Benchmark studies showed that the framework achieved 0.91 average precision,identifying 87 discontinuities in Dataset-3D.The results confirm its high precision and efficiency,making it a valuable tool for data annotation.The proposed method offers a practical solution for geological investigations.
文摘Against the backdrop of the rapid development of the digital economy,corporate financial management faces unprecedented challenges and opportunities.This paper will start with the concept of financial shared services to deeply explore the role and significance of the financial shared service model in the digital transformation of corporate finance.It analyzes the existing problems in the current process of digital transformation of corporate finance and proposes corresponding solutions,providing valuable references and guidance for enterprises to achieve digital transformation of finance.
文摘The digital economy has injected continuous momentum into the development of urban economy and plays a positive and important role in the transformation and upgrading of urban energy consumption.Specifically,the digital economy can significantly improve the efficiency of urban energy consumption by virtue of its distinctive characteristics of low pollution and high efficiency.Moreover,empowered by the digital economy,the pace of transformation and upgrading of high-pollution traditional industries has been accelerated.Particularly importantly,the urban energy consumption structure has been optimized and adjusted through the indirect role of intermediate factors.From this perspective,studying the current situation and countermeasures of urban energy consumption under the digital economy holds important practical significance both in theory and practice.This paper first briefly summarizes the relevant literature on the impact of the digital economy on the energy consumption structure;then,it focuses on detailed data to explore the current situation of urban energy consumption under the digital economy model;finally,based on the summary of the current situation,it puts forward practical and feasible suggestions,hoping to provide a decision-making basis for the implementation of policies in different types of cities and offer innovative ideas for promoting the high-quality development of urban energy systems.
文摘With the advancement of digital technology,new technologies such as artificial intelligence,big data,and cloud computing have gradually permeated higher education,leading to fundamental changes in teaching and learning methods.Therefore,in the process of reforming and developing higher education,it is essential to take digital technology empowering the optimization of the education industry as a breakthrough,focusing on five key areas:the construction of smart classrooms,the digital integration of teaching resources,the development of personalized learning support systems,the reform of online-offline hybrid teaching,and the intelligentization of educational management.This paper also examines the experiences,challenges,and shortcomings of typical universities in using digital technology to improve teaching quality,optimize resource allocation,and innovate teaching management models.Finally,corresponding countermeasures and suggestions are proposed to facilitate the smooth implementation of digital transformation in higher education institutions.
基金supported by grants from the Human Resources Development program (Grant No.20204010600250)the Training Program of CCUS for the Green Growth (Grant No.20214000000500)by the Korea Institute of Energy Technology Evaluation and Planning (KETEP)funded by the Ministry of Trade,Industry,and Energy of the Korean Government (MOTIE).
文摘It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.
基金The 2024 Higher Education Teaching Reform Project of Guangdong University of Science and Technology“Teaching Practice of Human Resource Management Course Based on SPOC+FC Hybrid Teaching Mode”(GKZLGC2024024)。
文摘Under the dual impetus of the fundamental task of“cultivating virtue and nurturing talent”and the national strategy of digitalizing education,promoting the deep integration of ideological and political education in courses with digital technology has become a core issue in the curriculum reform of colleges and universities.This paper takes the course“Business Model Innovation”as the research object and focuses on the problems existing in the current course,such as lagging content update,superficial application of digital tools,and weakening elements of ideological and political education.This paper proposes a teaching reform path that is supported by digital means and centered on value guidance,and focuses on how to systematically optimize teaching content design,interactive teaching scenarios,evaluation and feedback mechanisms,and teacher collaboration systems through specific tools such as“Rain Classroom,”“Enterprise Sand Table,”and“Smart Classroom Platform.”We aim to build a digital model of ideological and political education in the curriculum that integrates knowledge imparting,ability training,and value shaping,and to provide practical reference and path support for the cultivation of high-quality business talents in the new era.
基金supported by the Natural Science Foundation of China(No.42130813)CNPC Innovation Fund(No.2024DQ02-0502)。
文摘To address the shortage of characterization scale of field outcrops,we used the characteristics of unmanned aerial vehicle(UAV)oblique photography with a wide field of view and a high degree of quantification for image acquisition,data processing,and geological interpretation of the outcrops of the Shaximiao Formation in the Sichuan Basin.We established a 3D digital outcrop model(DOM),which combines the advantages of visualization and digitization the 3D DOM to interpret the characteristics of typical channel sand bodies.Within the study area,we have identified three types of channel deposition:composite channel deposition,crevasse channel deposition,and abandoned channel deposition.Among these,the composite channel deposition was mainly sandstone,the bottom contains conglomerate,with large cross-bedding,and the maximum thickness of the single sand body was 1.96 m.The crevasse channel deposition was mainly fine sandstone and siltstone,with massive bedding and small cross-bedding,and the maximum thickness of the single sand body was 0.64 m.The abandoned channel deposition dominated by mudstone with thin sandstone,the sandstone was mainly lenticular in section,and the maximum thickness of the single sand body was 0.28 m.We identified the depositional model of the studied region,which is dominated by braided river deposition,based on the growth size and correspondence of the sand bodies.The research provides a comparative foundation for the detailed characterisation of the underground reservoir sands found in the Jurassic Shaximiao Formation in the Sichuan Basin.It also serves as a reference for the effective study of UAV oblique photography technology in the field.
基金the National Key Research and Development Program of China(No.2021YFC3100800)the National Natural Science Foundation of China(Nos.42407235 and 42271026)the Project of Sanya Yazhou Bay Science and Technology City(No.SCKJ-JYRC-2023-54).
文摘Coral reef limestone(CRL)constitutes a distinctive marine carbonate formation with complex mechanical properties.This study investigates the multiscale damage and fracture mechanisms of CRL through integrated experimental testing,digital core technology,and theoretical modelling.Two CRL types with contrasting mesostructures were characterized across three scales.Macroscopically,CRL-I and CRL-II exhibited mean compressive strengths of 8.46 and 5.17 MPa,respectively.Mesoscopically,CRL-I featured small-scale highly interconnected pores,whilst CRL-II developed larger stratified pores with diminished connectivity.Microscopically,both CRL matrices demonstrated remarkable similarity in mineral composition and mechanical properties.A novel voxel average-based digital core scaling methodology was developed to facilitate numerical simulation of cross-scale damage processes,revealing network-progressive failure in CRL-I versus directional-brittle failure in CRL-II.Furthermore,a damage statistical constitutive model based on digital core technology and mesoscopic homogenisation theory established quantitative relationships between microelement strength distribution and macroscopic mechanical behavior.These findings illuminate the fundamental mechanisms through which mesoscopic structure governs the macroscopic mechanical properties of CRL.
基金Supported by National Natural Science Foundation of China(Grant No.72071179)ZJU-Sunon Joint Research Center of Smart Furniture,Zhejiang University,China.
文摘The human digital twin(HDT)emerges as a promising human-centric technology in Industry 5.0,but challenges remain in human modeling and simulation.Digital human modeling(DHM)provides solutions for modeling and simulating human physical and cognitive aspects to support ergonomic analysis.However,it has limitations in real-time data usage,personalized services,and timely interaction.The emerging HDT concept offers new possibilities by integrating multi-source data and artificial intelligence for continuous monitoring and assessment.Hence,this paper reviews the evolution from DHM to HDT and proposes a unified HDT framework from a human factors perspective.The framework comprises the physical twin,the virtual twin,and the linkage between these two.The virtual twin integrates human modeling and AI engines to enable model-data-hybrid-enabled simulation.HDT can potentially upgrade traditional ergonomic methods to intelligent services through real-time analysis,timely feedback,and bidirectional interactions.Finally,the future perspectives of HDT for industrial applications as well as technical and social challenges are discussed.In general,this study outlines a human factors perspective on HDT for the first time,which is useful for cross-disciplinary research and human factors innovation to enhance the development of HDT in industry.
文摘To address the problem that the display effect of hydrologic test data was not intuitive,the three-dimensional modeling technology of a hydrologic test reach based on GIS technology was proposed.The reach of of the Yellow River around Lanzhou hydrological station was selected to study three-dimensional modeling.The elevation data of river was processed through three-dimensional model constructing,water surface modeling and three-dimensional animation demonstration by using ArcGIS Pro software.Based on the historical highest flood level data of the test reach on September 15,1981,the real scene restoration was carried out based on the three-dimensional model,and the hydrological factors such as water depth and channel storage were analyzed.The three-dimensional modeling based on GIS technology can directly and realistically reflect the changes of topography and water surface of the test reach,and improve the application of hydrologic test results in flood control.
