Accurately forecasting the operational performance of a tunnel boring machine(TBM)in advance is useful for making timely adjustments to boring parameters,thereby enhancing overall boring efficiency.In this study,we us...Accurately forecasting the operational performance of a tunnel boring machine(TBM)in advance is useful for making timely adjustments to boring parameters,thereby enhancing overall boring efficiency.In this study,we used the Informer model to predict a critical performance parameter of the TBM,namely thrust.Leveraging data from the Guangzhou Metro Line 22 project on the big data platform in China,the model’s performance was validated,while data from Line 18 were used to assess its generalization capability.Results revealed that the Informer model surpasses random forest(RF),extreme gradient boosting(XGB),support vector regression(SVR),k-nearest neighbors(KNN),back propagation(BP),and long short-term memory(LSTM)models in both prediction accuracy and generalization performance.In addition,the optimal input lengths for maximizing accuracy in the single-time-step output model are within the range of 8–24,while for the multiple-time-step output model,the optimal input length is 8.Furthermore,the last predicted value in the case of multiple-time-step outputs showed the highest accuracy.It was also found that relaxation of the Pearson analysis method metrics to 0.95 improved the performance of the model.Finally,the prediction results were most affected by earth pressure,rotation speed,torque,boring speed,and the surrounding rock grade.The model can provide useful guidance for constructors when adjusting TBM operation parameters.展开更多
We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpr...We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpreting these parameters is crucial for effectively exploring and developing oil and gas.However,with the increasing complexity of geological conditions in this industry,there is a growing demand for improved accuracy in reservoir parameter prediction,leading to higher costs associated with manual interpretation.The conventional logging interpretation methods rely on empirical relationships between logging data and reservoir parameters,which suffer from low interpretation efficiency,intense subjectivity,and suitability for ideal conditions.The application of artificial intelligence in the interpretation of logging data provides a new solution to the problems existing in traditional methods.It is expected to improve the accuracy and efficiency of the interpretation.If large and high-quality datasets exist,data-driven models can reveal relationships of arbitrary complexity.Nevertheless,constructing sufficiently large logging datasets with reliable labels remains challenging,making it difficult to apply data-driven models effectively in logging data interpretation.Furthermore,data-driven models often act as“black boxes”without explaining their predictions or ensuring compliance with primary physical constraints.This paper proposes a machine learning method with strong physical constraints by integrating mechanism and data-driven models.Prior knowledge of logging data interpretation is embedded into machine learning regarding network structure,loss function,and optimization algorithm.We employ the Physically Informed Auto-Encoder(PIAE)to predict porosity and water saturation,which can be trained without labeled reservoir parameters using self-supervised learning techniques.This approach effectively achieves automated interpretation and facilitates generalization across diverse datasets.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
Blended teaching is one of the essential teaching methods with the development of information technology.Constructing a learning effect evaluation model is helpful to improve students’academic performance and helps t...Blended teaching is one of the essential teaching methods with the development of information technology.Constructing a learning effect evaluation model is helpful to improve students’academic performance and helps teachers to better implement course teaching.However,a lack of evaluation models for the fusion of temporal and non-temporal behavioral data leads to an unsatisfactory evaluation effect.To meet the demand for predicting students’academic performance through learning behavior data,this study proposes a learning effect evaluation method that integrates expert perspective indicators to predict academic performance by constructing a dual-stream network that combines temporal behavior data and non-temporal behavior data in the learning process.In this paper,firstly,the Delphi method is used to analyze and process the course learning behavior data of students and establish an effective evaluation index system of learning behavior with universality;secondly,the Mann-Whitney U-test and the complex correlation analysis are used to analyze further and validate the evaluation indexes;and lastly,a dual-stream information fusion model,which combines temporal and non-temporal features,is established.The learning effect evaluation model is built,and the results of the mean absolute error(MAE)and root mean square error(RMSE)indexes are 4.16 and 5.29,respectively.This study indicates that combining expert perspectives for evaluation index selection and further fusing temporal and non-temporal behavioral features that for learning effect evaluation and prediction is rationality,accuracy,and effectiveness,which provides a powerful help for the practical application of learning effect evaluation and prediction.展开更多
为了保证运维阶段桥梁结构安全,提升桥梁运维工作的效率,开展公路混凝土梁式桥运维阶段建筑信息模型(building information modeling,BIM)技术应用研究。在对公路桥梁现行编码体系进行扩展的基础上,提出1种参数化快速建模方法,以快速完...为了保证运维阶段桥梁结构安全,提升桥梁运维工作的效率,开展公路混凝土梁式桥运维阶段建筑信息模型(building information modeling,BIM)技术应用研究。在对公路桥梁现行编码体系进行扩展的基础上,提出1种参数化快速建模方法,以快速完成桥梁构件族的创建与整体模型的集成。借助Autodesk Revit软件应用程序编程接口(application programming interface,API),采用C#语言,开发公路混凝土梁式桥智慧运维状态评估系统,以实际工程应用进行验证分析。研究结果表明:全面统一的桥梁信息编码体系,能够提高桥梁信息统计与检索效率;提出的快速建模方法能够显著减少建模工作量,建模时间较传统建模方法可减少60%,并保证模型的准确性与规范性;运维状态评估系统能够实现养护数据的充分利用与桥梁评定工作的自动化,通过对桥梁运维信息的有效组织,实现服役性能的长期追踪,从而确保运营期桥梁结构状态安全稳定。研究结果可为公路混凝土梁式桥运维管理提供技术支撑,提升桥梁运维的数字化水平。展开更多
As the number of high-density buildings has increased,the management of property with complex condominium ownership has become an ongoing challenge in property registration and management.The three-dimensional(3D)mode...As the number of high-density buildings has increased,the management of property with complex condominium ownership has become an ongoing challenge in property registration and management.The three-dimensional(3D)modeling of condominium ownership has emerged as an effective means of meeting this challenge and has attracted great attention from fields such as geographical information science,urban planning and management,and property administration.Much progress has been made in building 3D models of condominium ownership;however,existing studies are all on a case-by-case basis and have left some critical issues unsolved,such as vague ownership boundaries,spatial rights without physical counterparts,and the unfixed spatial extent.The purpose of this study is to construct a 3D building ownership model with multiple levels of detail in the context of Chinese law to overcome the defects of 3D models above.This 3D model is presented in a case study of China by subdividing ownership boundaries based on clarifying the internal structure of condominium ownership,embedding the apportionment mechanism,and integrating the semantics,attributes,and geometry associated with the physical and legal entity of the condominium.The proposed 3D model is implemented by extending Building Information Modeling(BIM)based on the Industry Foundation Classes(IFC)and inheriting legal information from Land Administration Domain Model(LADM).In this study,examples of condominium ownership from three real legal dispute cases in China are analyzed and tested.The study clearly demonstrates that the proposed model can provide a better cognitive understanding of the legal space of property by rendering unambiguous ownership boundaries and presenting the spatial internal structure of ownership,which offers solid technical support for dealing with property registration and many legal dispute cases about condominium ownership.展开更多
This paper was motivated by the existing problems of Cloud Data storage in Imo State University, Nigeria such as outsourced data causing the loss of data and misuse of customer information by unauthorized users or hac...This paper was motivated by the existing problems of Cloud Data storage in Imo State University, Nigeria such as outsourced data causing the loss of data and misuse of customer information by unauthorized users or hackers, thereby making customer/client data visible and unprotected. Also, this led to enormous risk of the clients/customers due to defective equipment, bugs, faulty servers, and specious actions. The aim if this paper therefore is to analyze a secure model using Unicode Transformation Format (UTF) base 64 algorithms for storage of data in cloud securely. The methodology used was Object Orientated Hypermedia Analysis and Design Methodology (OOHADM) was adopted. Python was used to develop the security model;the role-based access control (RBAC) and multi-factor authentication (MFA) to enhance security Algorithm were integrated into the Information System developed with HTML 5, JavaScript, Cascading Style Sheet (CSS) version 3 and PHP7. This paper also discussed some of the following concepts;Development of Computing in Cloud, Characteristics of computing, Cloud deployment Model, Cloud Service Models, etc. The results showed that the proposed enhanced security model for information systems of cooperate platform handled multiple authorization and authentication menace, that only one login page will direct all login requests of the different modules to one Single Sign On Server (SSOS). This will in turn redirect users to their requested resources/module when authenticated, leveraging on the Geo-location integration for physical location validation. The emergence of this newly developed system will solve the shortcomings of the existing systems and reduce time and resources incurred while using the existing system.展开更多
Value-added services in recent networks are provided with smart grid technology and particularly smart street lighting.The effective management of services and networks,structured as smart,imposes development of manag...Value-added services in recent networks are provided with smart grid technology and particularly smart street lighting.The effective management of services and networks,structured as smart,imposes development of management information model,which meets the requirements of network operator,service provider,and subscribers.Paradigm of smart grid defines only management framework without specification of architecture model and functions.The bright deployment of smart grid is based on development of management models.To this moment they are short specialized,cover only some of management functional areas,and reflect partially the actors’requirements.This paper represents implementation aspects of models for service management and network management in smart street lighting.Object-oriented method is used by models’design.Management functions for services and network are considered in installation,provision,configuration,maintenance,security,accounting,and performance.The focus is on problems regarding optimization of developed models and their reducing to Boyce-Codd Normal Form.The procedures for Service Installation and Service Provision are demonstrated with different methods:direct method and method with decomposition.The paper is intended to business developers,university professors,and students.展开更多
The whole-process project cost management based on building information modeling(BIM)is a new management method,aiming to realize the comprehensive optimization and improvement of project cost management through the a...The whole-process project cost management based on building information modeling(BIM)is a new management method,aiming to realize the comprehensive optimization and improvement of project cost management through the application of BIM technology.This paper summarizes and analyzes the whole-process project cost management based on BIM,aiming to explore its application and development prospects in the construction industry.Firstly,this paper introduces the role and advantages of BIM technology in engineering cost management,including information integration,data sharing,and collaborative work.Secondly,the paper analyzes the key technologies and methods of the whole-process project cost management based on BIM,including model construction,data management,and cost control.In addition,the paper also discusses the challenges and limitations of the whole-process BIM project cost management,such as the inconsistency of technical standards,personnel training,and consciousness change.Finally,the paper summarizes the advantages and development prospects of the whole-process project cost management based on BIM and puts forward the direction and suggestions for future research.Through the research of this paper,it can provide a reference for construction cost management and promote innovation and development in the construction industry.展开更多
Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to ...Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.展开更多
Purpose-The rapid development of China’s railway construction has led to an increase in data generated by the high-speed rail(HSR)catenary system.Traditional management methods struggle with challenges such as poor i...Purpose-The rapid development of China’s railway construction has led to an increase in data generated by the high-speed rail(HSR)catenary system.Traditional management methods struggle with challenges such as poor information sharing,disconnected business applications and insufficient intelligence throughout the lifecycle.This study aims to address these issues by applying building information modeling(BIM)technology to improve lifecycle management efficiency for HSR catenary systems.Design/methodology/approach-Based on the lifecycle management needs of catenary engineering,incorporating the intelligent HSR“Model-Data Driven,Axis-Plane Coordination”philosophy,this paper constructs a BIM-based lifecycle management framework for HSR catenary engineering.Findings-This study investigates the full-process lifecycle management of the catenary system across various stages of design,manufacture,construction and operation,exploring integrated BIM models and data transmission methods,along with key technologies for BIM model transmission,transformation and lightweighting.Originality/value-This study establishes a lossless information circulation and transmission system for HSR catenary lifecycle management.Multi-stage applications are verified through the construction of the Chongqing-Kunming High-Speed Railway,comprehensive advancing the intelligent promotion and highquality development of catenary engineering.展开更多
Indoor environmental comfort is fundamental to human health as people spend 90%of their time indoors.This aspect is even more crucial in hospitals,where the concept of health is closely linked to well-being,ethics and...Indoor environmental comfort is fundamental to human health as people spend 90%of their time indoors.This aspect is even more crucial in hospitals,where the concept of health is closely linked to well-being,ethics and environmental aspects.Emerging methodologies and technologies such as digital twin,building information modelling,the internet of things,sensing technologies and data analytics offer new opportunities to ensure healthier environments and more efficient building management.This paper provides an assessment of how digitalisation can support decision-making processes related to maintaining high levels of indoor environmental comfort in hospital settings,particularly by analysing how real-time data processing and the application of machine learning can promote proactive interventions in these facilities.The methodological approach was based on four phases:defining the objectives of the digital twin,identifying the input data to build and feed the digital model,defining the KPIs to evaluate the system's correct functioning and identifying the enabling technologies to be integrated into the system to achieve the set goal.The result is a digital twin for managing the operating room and its related services,with the aim of guiding decisions based on accurate data and improving operational efficiency,levels of environmental comfort,and safety regarding the diffusion of medical gases.展开更多
To explore the influence of emergency evacuation signs on passenger behavior during subway fires and improve evacuation efficiency in emergencies,this paper proposes a dynamic emergency evacuation sign system.A simula...To explore the influence of emergency evacuation signs on passenger behavior during subway fires and improve evacuation efficiency in emergencies,this paper proposes a dynamic emergency evacuation sign system.A simulation platform integrating building information modeling(BIM)and virtual reality(VR)technologies was em-ployed to create subway fire evacuation scenarios using both the current and proposed dynamic emergency evacuation signage systems.Through simulation experiments,fine-grained microscopic data on passenger behavior was collected.Seven indicators were selected to assess evacuation efficiency and wayfinding difficulty.The analysis explored the influence of evacuation signs on passenger behavior in both overall and decision-making areas,thereby validating the effectiveness of the new emergency evacuation signage system.The results show that the dynamic evacuation signage system significantly improves overall passenger evacuation efficiency and reduces decision-making errors.It also improves wayfinding efficiency in critical decision areas by reducing the need for direction identification,minimizing stopping times,and lowering the frequency of decision errors.The method for evaluating the effects of emergency evacuation signs on passenger evacuation behavior proposed in this study provides a robust theoretical basis for the design and optimization of emergency-oriented signs.展开更多
Objective:To investigate the effect of an information-knowledge-attitude-practice(IKAP)nursing intervention on the caregiving capacity of family caregivers of elderly dementia patients.Methods:Sixty-nine family caregi...Objective:To investigate the effect of an information-knowledge-attitude-practice(IKAP)nursing intervention on the caregiving capacity of family caregivers of elderly dementia patients.Methods:Sixty-nine family caregivers of elderly dementia patients attending the neurology outpatient clinic of a hospital between October 2024 and March 2025 were selected.They were randomly divided into a control group(n=35)and an observation group(n=34).The control group received routine health education,while the observation group additionally underwent a systematic Information-Knowledge-Attitude-Practice(IKAP)nursing intervention.Care competence and self-efficacy scores were compared between groups before intervention and after 12 weeks.Results:Pre-intervention,no statistically significant difference existed in care competence or self-efficacy scores between groups(p>0.05).Following the 12-week intervention,all scores significantly increased in both groups,with the observation group demonstrating superior outcomes compared to the control group(p<0.001).Conclusion:The care intervention program based on the IKAP model effectively enhances caregivers’care competence and self-efficacy,thereby positively promoting the quality of life for patients with dementia.展开更多
Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to effici...Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to efficiently model underground pipeline networks,using the building information modeling(BIM)-based software Revit.The system comprises separate pipe point and tubulation models.Using a Revit application programming interface(API),the spatial position and attribute data of the pipe points are extracted from a pipeline database,and the corresponding tubulation data are extracted from a tubulation database.Using the Family class in Revit API,the cluster in the self-built library of pipe point is inserted into the spatial location and the attribute data is added;in the same way,all pipeline instances in the pipeline system are created.The extension and localization of the model accelerated the modeling speed.The system was then used in a real construction project.The expansion of the model database and rapid modeling made the application of BIM technology in three-dimensional visualization of underground pipeline networks more convenient.Furthermore,it has applications in pipeline engineering construction and management.展开更多
Slope aspect is one of the indispensable internal factors besides lithology, relative elevation and slope degree. In this paper authors use information value model with Geo graphical Information System （GIS） technol...Slope aspect is one of the indispensable internal factors besides lithology, relative elevation and slope degree. In this paper authors use information value model with Geo graphical Information System （GIS） technology to study how slope aspect contributes to landslide growth from Yunyang to Wushan segment in the Three Gorges Reservoir area, and the relationship between aspect and landslide growth is quantified. Through the research on 205 landslides examples, it is found that the slope contributes most whose aspect is towards south,southeast and southwest aspect contribute moderately, and other five aspects contribute little. The research result inosculates preferably with the fact. The result of this paper can provide potent gist to the construction of Three Gorges Reservoir area in future.展开更多
Motion simulation and performance analysis of mechanism are important methods for analyzing assembly quality after finishing assembly simulation in virtual assembly environment. However, most simulation systems have n...Motion simulation and performance analysis of mechanism are important methods for analyzing assembly quality after finishing assembly simulation in virtual assembly environment. However, most simulation systems have no function of mechanism motion simulation due to the randomicity of mechanism and lack of universal mechanism modeling method. In order to realize the simulation of any mechanism after finishing assembly simulation in a virtual environment, a new universal mechanism modeling method is presented. Two main models are contained in the mechanism model： information model and mathematical model. Firstly, the information model of mechanism is proposed to describe the data structure of mechanism which contains bottom geometry data, information of constraint, link, kinematic pair and physical data. Because the object of mechanism simulation is the assembly, which is assembled during the process of assembly simulation, the information of mechanism can be obtained automatically through mechanism automatic search method. Secondly, mathematical model of mechanism is presented. The mathematical model uses mathematical method to express the mechanism. In order to realize the automatic expression of any random mechanism, basic constraint library is presented, consequently random mechanism can be described based on the basic constraint library. Finally, two examples are introduced to validate the method in the prototype system named VAPP（Virtual Assembly Process Planning）. The validation result shows that the mechanism modeling provides a universal modeling method for mechanism motion simulation in virtual assembly environment. This research has important effect on the development both of mechanism motion simulation and virtual assembly.展开更多
Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected ...Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected images.Nevertheless,assessing the damage′s impact on structural safety requires localizing damage to specific building components with known design and function.This paper proposes a BIM-based automated inspection framework to provide context for visual surveys.A deep learning-based semantic segmentation algorithm is trained to automatically identify damage in images.The BIM automatically associates any identified damage with specific building components.Then,components are classified into damage states consistent with component fragility models for integration with a structural analysis.To demonstrate the framework,methods are developed to photorealistically simulate severe structural damage in a synthetic computer graphics environment.A graphics model of a real building in Urbana,Illinois,is generated to test the framework;the model is integrated with a structural analysis to apply earthquake damage in a physically realistic manner.A simulated UAV survey is flown of the graphics model and the framework is applied.The method achieves high accuracy in assigning damage states to visible structural components.This assignment enables integration with a performance-based earthquake assessment to classify building safety.展开更多
As-built building information model （BIM） is an urgent need of the architecture, engineering, construction and facilities management （AEC/FM） community. However, its creation procedure is still labor-intensive and...As-built building information model （BIM） is an urgent need of the architecture, engineering, construction and facilities management （AEC/FM） community. However, its creation procedure is still labor-intensive and far from maturity. Taking advantage of prevalence of digital cameras and the development of advanced computer vision technology, the paper proposes to reconstruct a building facade and recognize its surface materials from images taken from various points of view. These can serve as initial steps towards automatic generation of as-built BIM. Specifically, 3D point clouds are generated from multiple images using structure from motion method and then segmented into planar components, which are further recognized as different structural components through knowledge based reasoning. Windows are detected through a multilayered complementary strategy by combining detection results from every semantic layer. A novel machine learning based 3D material recognition strategy is presented. Binary classifiers are trained through support vector machines. Material type at a given 3D location is predicted by all its corresponding 2D feature points. Experimental results from three existing buildings validate the proposed system.展开更多
There are heterogeneous problems between the CAD model and the assembly process document.In the planning stage of assembly process,these heterogeneous problems can decrease the efficiency of information interaction.Ba...There are heterogeneous problems between the CAD model and the assembly process document.In the planning stage of assembly process,these heterogeneous problems can decrease the efficiency of information interaction.Based on knowledge graph,this paper proposes an assembly information model(KGAM)to integrate geometric information from CAD model,non-geometric information and semantic information from assembly process document.KGAM describes the integrated assembly process information as a knowledge graph in the form of“entity-relationship-entity”and“entity-attribute-value”,which can improve the efficiency of information interaction.Taking the trial assembly stage of a certain type of aeroengine compressor rotor component as an example,KGAM is used to get its assembly process knowledge graph.The trial data show the query and update rate of assembly attribute information is improved by more than once.And the query and update rate of assembly semantic information is improved by more than twice.In conclusion,KGAM can solve the heterogeneous problems between the CAD model and the assembly process document and improve the information interaction efficiency.展开更多
基金supported by the National Natural Science Foundation of China(No.41827807)the Foundation of the Guangdong Provincial Key Laboratory of Modern Civil Engineering Technology(No.2021B1212040003),China.
文摘Accurately forecasting the operational performance of a tunnel boring machine(TBM)in advance is useful for making timely adjustments to boring parameters,thereby enhancing overall boring efficiency.In this study,we used the Informer model to predict a critical performance parameter of the TBM,namely thrust.Leveraging data from the Guangzhou Metro Line 22 project on the big data platform in China,the model’s performance was validated,while data from Line 18 were used to assess its generalization capability.Results revealed that the Informer model surpasses random forest(RF),extreme gradient boosting(XGB),support vector regression(SVR),k-nearest neighbors(KNN),back propagation(BP),and long short-term memory(LSTM)models in both prediction accuracy and generalization performance.In addition,the optimal input lengths for maximizing accuracy in the single-time-step output model are within the range of 8–24,while for the multiple-time-step output model,the optimal input length is 8.Furthermore,the last predicted value in the case of multiple-time-step outputs showed the highest accuracy.It was also found that relaxation of the Pearson analysis method metrics to 0.95 improved the performance of the model.Finally,the prediction results were most affected by earth pressure,rotation speed,torque,boring speed,and the surrounding rock grade.The model can provide useful guidance for constructors when adjusting TBM operation parameters.
基金supported by National Key Research and Development Program (2019YFA0708301)National Natural Science Foundation of China (51974337)+2 种基金the Strategic Cooperation Projects of CNPC and CUPB (ZLZX2020-03)Science and Technology Innovation Fund of CNPC (2021DQ02-0403)Open Fund of Petroleum Exploration and Development Research Institute of CNPC (2022-KFKT-09)
文摘We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpreting these parameters is crucial for effectively exploring and developing oil and gas.However,with the increasing complexity of geological conditions in this industry,there is a growing demand for improved accuracy in reservoir parameter prediction,leading to higher costs associated with manual interpretation.The conventional logging interpretation methods rely on empirical relationships between logging data and reservoir parameters,which suffer from low interpretation efficiency,intense subjectivity,and suitability for ideal conditions.The application of artificial intelligence in the interpretation of logging data provides a new solution to the problems existing in traditional methods.It is expected to improve the accuracy and efficiency of the interpretation.If large and high-quality datasets exist,data-driven models can reveal relationships of arbitrary complexity.Nevertheless,constructing sufficiently large logging datasets with reliable labels remains challenging,making it difficult to apply data-driven models effectively in logging data interpretation.Furthermore,data-driven models often act as“black boxes”without explaining their predictions or ensuring compliance with primary physical constraints.This paper proposes a machine learning method with strong physical constraints by integrating mechanism and data-driven models.Prior knowledge of logging data interpretation is embedded into machine learning regarding network structure,loss function,and optimization algorithm.We employ the Physically Informed Auto-Encoder(PIAE)to predict porosity and water saturation,which can be trained without labeled reservoir parameters using self-supervised learning techniques.This approach effectively achieves automated interpretation and facilitates generalization across diverse datasets.
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supported by the National Key R&D Program of China(2022YFB3203800)National Natural Science Foundation of China(62007026)+2 种基金National Young Talent Program,Shaanxi Young Top-notch Talent Program,Key Research and Development Program of Shaanxi(2022GY-313)Xi’an Science and Technology Project(23ZDCYJSGG0026-2023)the Fundamental Research Funds for Central Universities(ZYTS23192).
文摘Blended teaching is one of the essential teaching methods with the development of information technology.Constructing a learning effect evaluation model is helpful to improve students’academic performance and helps teachers to better implement course teaching.However,a lack of evaluation models for the fusion of temporal and non-temporal behavioral data leads to an unsatisfactory evaluation effect.To meet the demand for predicting students’academic performance through learning behavior data,this study proposes a learning effect evaluation method that integrates expert perspective indicators to predict academic performance by constructing a dual-stream network that combines temporal behavior data and non-temporal behavior data in the learning process.In this paper,firstly,the Delphi method is used to analyze and process the course learning behavior data of students and establish an effective evaluation index system of learning behavior with universality;secondly,the Mann-Whitney U-test and the complex correlation analysis are used to analyze further and validate the evaluation indexes;and lastly,a dual-stream information fusion model,which combines temporal and non-temporal features,is established.The learning effect evaluation model is built,and the results of the mean absolute error(MAE)and root mean square error(RMSE)indexes are 4.16 and 5.29,respectively.This study indicates that combining expert perspectives for evaluation index selection and further fusing temporal and non-temporal behavioral features that for learning effect evaluation and prediction is rationality,accuracy,and effectiveness,which provides a powerful help for the practical application of learning effect evaluation and prediction.
基金supported by the National Natural Science Foundation of China[grant number 41871298].
文摘As the number of high-density buildings has increased,the management of property with complex condominium ownership has become an ongoing challenge in property registration and management.The three-dimensional(3D)modeling of condominium ownership has emerged as an effective means of meeting this challenge and has attracted great attention from fields such as geographical information science,urban planning and management,and property administration.Much progress has been made in building 3D models of condominium ownership;however,existing studies are all on a case-by-case basis and have left some critical issues unsolved,such as vague ownership boundaries,spatial rights without physical counterparts,and the unfixed spatial extent.The purpose of this study is to construct a 3D building ownership model with multiple levels of detail in the context of Chinese law to overcome the defects of 3D models above.This 3D model is presented in a case study of China by subdividing ownership boundaries based on clarifying the internal structure of condominium ownership,embedding the apportionment mechanism,and integrating the semantics,attributes,and geometry associated with the physical and legal entity of the condominium.The proposed 3D model is implemented by extending Building Information Modeling(BIM)based on the Industry Foundation Classes(IFC)and inheriting legal information from Land Administration Domain Model(LADM).In this study,examples of condominium ownership from three real legal dispute cases in China are analyzed and tested.The study clearly demonstrates that the proposed model can provide a better cognitive understanding of the legal space of property by rendering unambiguous ownership boundaries and presenting the spatial internal structure of ownership,which offers solid technical support for dealing with property registration and many legal dispute cases about condominium ownership.
文摘This paper was motivated by the existing problems of Cloud Data storage in Imo State University, Nigeria such as outsourced data causing the loss of data and misuse of customer information by unauthorized users or hackers, thereby making customer/client data visible and unprotected. Also, this led to enormous risk of the clients/customers due to defective equipment, bugs, faulty servers, and specious actions. The aim if this paper therefore is to analyze a secure model using Unicode Transformation Format (UTF) base 64 algorithms for storage of data in cloud securely. The methodology used was Object Orientated Hypermedia Analysis and Design Methodology (OOHADM) was adopted. Python was used to develop the security model;the role-based access control (RBAC) and multi-factor authentication (MFA) to enhance security Algorithm were integrated into the Information System developed with HTML 5, JavaScript, Cascading Style Sheet (CSS) version 3 and PHP7. This paper also discussed some of the following concepts;Development of Computing in Cloud, Characteristics of computing, Cloud deployment Model, Cloud Service Models, etc. The results showed that the proposed enhanced security model for information systems of cooperate platform handled multiple authorization and authentication menace, that only one login page will direct all login requests of the different modules to one Single Sign On Server (SSOS). This will in turn redirect users to their requested resources/module when authenticated, leveraging on the Geo-location integration for physical location validation. The emergence of this newly developed system will solve the shortcomings of the existing systems and reduce time and resources incurred while using the existing system.
文摘Value-added services in recent networks are provided with smart grid technology and particularly smart street lighting.The effective management of services and networks,structured as smart,imposes development of management information model,which meets the requirements of network operator,service provider,and subscribers.Paradigm of smart grid defines only management framework without specification of architecture model and functions.The bright deployment of smart grid is based on development of management models.To this moment they are short specialized,cover only some of management functional areas,and reflect partially the actors’requirements.This paper represents implementation aspects of models for service management and network management in smart street lighting.Object-oriented method is used by models’design.Management functions for services and network are considered in installation,provision,configuration,maintenance,security,accounting,and performance.The focus is on problems regarding optimization of developed models and their reducing to Boyce-Codd Normal Form.The procedures for Service Installation and Service Provision are demonstrated with different methods:direct method and method with decomposition.The paper is intended to business developers,university professors,and students.
文摘The whole-process project cost management based on building information modeling(BIM)is a new management method,aiming to realize the comprehensive optimization and improvement of project cost management through the application of BIM technology.This paper summarizes and analyzes the whole-process project cost management based on BIM,aiming to explore its application and development prospects in the construction industry.Firstly,this paper introduces the role and advantages of BIM technology in engineering cost management,including information integration,data sharing,and collaborative work.Secondly,the paper analyzes the key technologies and methods of the whole-process project cost management based on BIM,including model construction,data management,and cost control.In addition,the paper also discusses the challenges and limitations of the whole-process BIM project cost management,such as the inconsistency of technical standards,personnel training,and consciousness change.Finally,the paper summarizes the advantages and development prospects of the whole-process project cost management based on BIM and puts forward the direction and suggestions for future research.Through the research of this paper,it can provide a reference for construction cost management and promote innovation and development in the construction industry.
文摘Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.
基金supported by China Academy of Railway Sciences Foundation(Research on Multi Agent Collaborative Mechanism of Intelligent High Speed Rail System Based on Complex Adaptive System Theory,Grant 2023YJ392).
文摘Purpose-The rapid development of China’s railway construction has led to an increase in data generated by the high-speed rail(HSR)catenary system.Traditional management methods struggle with challenges such as poor information sharing,disconnected business applications and insufficient intelligence throughout the lifecycle.This study aims to address these issues by applying building information modeling(BIM)technology to improve lifecycle management efficiency for HSR catenary systems.Design/methodology/approach-Based on the lifecycle management needs of catenary engineering,incorporating the intelligent HSR“Model-Data Driven,Axis-Plane Coordination”philosophy,this paper constructs a BIM-based lifecycle management framework for HSR catenary engineering.Findings-This study investigates the full-process lifecycle management of the catenary system across various stages of design,manufacture,construction and operation,exploring integrated BIM models and data transmission methods,along with key technologies for BIM model transmission,transformation and lightweighting.Originality/value-This study establishes a lossless information circulation and transmission system for HSR catenary lifecycle management.Multi-stage applications are verified through the construction of the Chongqing-Kunming High-Speed Railway,comprehensive advancing the intelligent promotion and highquality development of catenary engineering.
基金supported by Agenzia Del Demanio(Grant 0002716).
文摘Indoor environmental comfort is fundamental to human health as people spend 90%of their time indoors.This aspect is even more crucial in hospitals,where the concept of health is closely linked to well-being,ethics and environmental aspects.Emerging methodologies and technologies such as digital twin,building information modelling,the internet of things,sensing technologies and data analytics offer new opportunities to ensure healthier environments and more efficient building management.This paper provides an assessment of how digitalisation can support decision-making processes related to maintaining high levels of indoor environmental comfort in hospital settings,particularly by analysing how real-time data processing and the application of machine learning can promote proactive interventions in these facilities.The methodological approach was based on four phases:defining the objectives of the digital twin,identifying the input data to build and feed the digital model,defining the KPIs to evaluate the system's correct functioning and identifying the enabling technologies to be integrated into the system to achieve the set goal.The result is a digital twin for managing the operating room and its related services,with the aim of guiding decisions based on accurate data and improving operational efficiency,levels of environmental comfort,and safety regarding the diffusion of medical gases.
基金Beijing Natural Science Foundation-Fengtai Rail Transit Frontier Research Joint Foundation(No.L211024),the National Natural Science Foundation of China(No.52072012).
文摘To explore the influence of emergency evacuation signs on passenger behavior during subway fires and improve evacuation efficiency in emergencies,this paper proposes a dynamic emergency evacuation sign system.A simulation platform integrating building information modeling(BIM)and virtual reality(VR)technologies was em-ployed to create subway fire evacuation scenarios using both the current and proposed dynamic emergency evacuation signage systems.Through simulation experiments,fine-grained microscopic data on passenger behavior was collected.Seven indicators were selected to assess evacuation efficiency and wayfinding difficulty.The analysis explored the influence of evacuation signs on passenger behavior in both overall and decision-making areas,thereby validating the effectiveness of the new emergency evacuation signage system.The results show that the dynamic evacuation signage system significantly improves overall passenger evacuation efficiency and reduces decision-making errors.It also improves wayfinding efficiency in critical decision areas by reducing the need for direction identification,minimizing stopping times,and lowering the frequency of decision errors.The method for evaluating the effects of emergency evacuation signs on passenger evacuation behavior proposed in this study provides a robust theoretical basis for the design and optimization of emergency-oriented signs.
文摘Objective:To investigate the effect of an information-knowledge-attitude-practice(IKAP)nursing intervention on the caregiving capacity of family caregivers of elderly dementia patients.Methods:Sixty-nine family caregivers of elderly dementia patients attending the neurology outpatient clinic of a hospital between October 2024 and March 2025 were selected.They were randomly divided into a control group(n=35)and an observation group(n=34).The control group received routine health education,while the observation group additionally underwent a systematic Information-Knowledge-Attitude-Practice(IKAP)nursing intervention.Care competence and self-efficacy scores were compared between groups before intervention and after 12 weeks.Results:Pre-intervention,no statistically significant difference existed in care competence or self-efficacy scores between groups(p>0.05).Following the 12-week intervention,all scores significantly increased in both groups,with the observation group demonstrating superior outcomes compared to the control group(p<0.001).Conclusion:The care intervention program based on the IKAP model effectively enhances caregivers’care competence and self-efficacy,thereby positively promoting the quality of life for patients with dementia.
基金supported by a grant(No.14DZ2292800,http://www.greengeo.net/)from“Technology Service Platform of Civil Engineering”of Science and Technology Commission of Shanghai Municipality.
文摘Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to efficiently model underground pipeline networks,using the building information modeling(BIM)-based software Revit.The system comprises separate pipe point and tubulation models.Using a Revit application programming interface(API),the spatial position and attribute data of the pipe points are extracted from a pipeline database,and the corresponding tubulation data are extracted from a tubulation database.Using the Family class in Revit API,the cluster in the self-built library of pipe point is inserted into the spatial location and the attribute data is added;in the same way,all pipeline instances in the pipeline system are created.The extension and localization of the model accelerated the modeling speed.The system was then used in a real construction project.The expansion of the model database and rapid modeling made the application of BIM technology in three-dimensional visualization of underground pipeline networks more convenient.Furthermore,it has applications in pipeline engineering construction and management.
文摘Slope aspect is one of the indispensable internal factors besides lithology, relative elevation and slope degree. In this paper authors use information value model with Geo graphical Information System （GIS） technology to study how slope aspect contributes to landslide growth from Yunyang to Wushan segment in the Three Gorges Reservoir area, and the relationship between aspect and landslide growth is quantified. Through the research on 205 landslides examples, it is found that the slope contributes most whose aspect is towards south,southeast and southwest aspect contribute moderately, and other five aspects contribute little. The research result inosculates preferably with the fact. The result of this paper can provide potent gist to the construction of Three Gorges Reservoir area in future.
基金supported by National Natural Science Foundation of China(Grant No. 51275047)
文摘Motion simulation and performance analysis of mechanism are important methods for analyzing assembly quality after finishing assembly simulation in virtual assembly environment. However, most simulation systems have no function of mechanism motion simulation due to the randomicity of mechanism and lack of universal mechanism modeling method. In order to realize the simulation of any mechanism after finishing assembly simulation in a virtual environment, a new universal mechanism modeling method is presented. Two main models are contained in the mechanism model： information model and mathematical model. Firstly, the information model of mechanism is proposed to describe the data structure of mechanism which contains bottom geometry data, information of constraint, link, kinematic pair and physical data. Because the object of mechanism simulation is the assembly, which is assembled during the process of assembly simulation, the information of mechanism can be obtained automatically through mechanism automatic search method. Secondly, mathematical model of mechanism is presented. The mathematical model uses mathematical method to express the mechanism. In order to realize the automatic expression of any random mechanism, basic constraint library is presented, consequently random mechanism can be described based on the basic constraint library. Finally, two examples are introduced to validate the method in the prototype system named VAPP（Virtual Assembly Process Planning）. The validation result shows that the mechanism modeling provides a universal modeling method for mechanism motion simulation in virtual assembly environment. This research has important effect on the development both of mechanism motion simulation and virtual assembly.
基金Financial support for this research was provided in part by the US Army Corps of Engineers through a subaward from the University of California,San Diego,USA。
文摘Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected images.Nevertheless,assessing the damage′s impact on structural safety requires localizing damage to specific building components with known design and function.This paper proposes a BIM-based automated inspection framework to provide context for visual surveys.A deep learning-based semantic segmentation algorithm is trained to automatically identify damage in images.The BIM automatically associates any identified damage with specific building components.Then,components are classified into damage states consistent with component fragility models for integration with a structural analysis.To demonstrate the framework,methods are developed to photorealistically simulate severe structural damage in a synthetic computer graphics environment.A graphics model of a real building in Urbana,Illinois,is generated to test the framework;the model is integrated with a structural analysis to apply earthquake damage in a physically realistic manner.A simulated UAV survey is flown of the graphics model and the framework is applied.The method achieves high accuracy in assigning damage states to visible structural components.This assignment enables integration with a performance-based earthquake assessment to classify building safety.
基金supported by National Natural Science Foundation of China(No.51208425)Research Foundation of Northwestern Polytechnical University(No.JCY20130127)
文摘As-built building information model （BIM） is an urgent need of the architecture, engineering, construction and facilities management （AEC/FM） community. However, its creation procedure is still labor-intensive and far from maturity. Taking advantage of prevalence of digital cameras and the development of advanced computer vision technology, the paper proposes to reconstruct a building facade and recognize its surface materials from images taken from various points of view. These can serve as initial steps towards automatic generation of as-built BIM. Specifically, 3D point clouds are generated from multiple images using structure from motion method and then segmented into planar components, which are further recognized as different structural components through knowledge based reasoning. Windows are detected through a multilayered complementary strategy by combining detection results from every semantic layer. A novel machine learning based 3D material recognition strategy is presented. Binary classifiers are trained through support vector machines. Material type at a given 3D location is predicted by all its corresponding 2D feature points. Experimental results from three existing buildings validate the proposed system.
基金the National Natural Science Foundation of China(No.51805079)。
文摘There are heterogeneous problems between the CAD model and the assembly process document.In the planning stage of assembly process,these heterogeneous problems can decrease the efficiency of information interaction.Based on knowledge graph,this paper proposes an assembly information model(KGAM)to integrate geometric information from CAD model,non-geometric information and semantic information from assembly process document.KGAM describes the integrated assembly process information as a knowledge graph in the form of“entity-relationship-entity”and“entity-attribute-value”,which can improve the efficiency of information interaction.Taking the trial assembly stage of a certain type of aeroengine compressor rotor component as an example,KGAM is used to get its assembly process knowledge graph.The trial data show the query and update rate of assembly attribute information is improved by more than once.And the query and update rate of assembly semantic information is improved by more than twice.In conclusion,KGAM can solve the heterogeneous problems between the CAD model and the assembly process document and improve the information interaction efficiency.
