Whole-Process Project Cost Management Based on Building Information Modeling (BIM)

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.

Multi-source information fused generative adversarial network model and data assimilation based history matching for reservoir with complex geologies

For reservoirs with complex non-Gaussian geological characteristics,such as carbonate reservoirs or reservoirs with sedimentary facies distribution,it is difficult to implement history matching directly,especially for the ensemble-based data assimilation methods.In this paper,we propose a multi-source information fused generative adversarial network(MSIGAN)model,which is used for parameterization of the complex geologies.In MSIGAN,various information such as facies distribution,microseismic,and inter-well connectivity,can be integrated to learn the geological features.And two major generative models in deep learning,variational autoencoder(VAE)and generative adversarial network(GAN)are combined in our model.Then the proposed MSIGAN model is integrated into the ensemble smoother with multiple data assimilation(ESMDA)method to conduct history matching.We tested the proposed method on two reservoir models with fluvial facies.The experimental results show that the proposed MSIGAN model can effectively learn the complex geological features,which can promote the accuracy of history matching.

Full feature data model for spatial information network integration

In allusion to the difficulty of integrating data with different models in integrating spatial information, the characteristics of raster structure, vector structure and mixed model were analyzed, and a hierarchical vector-raster integrative full feature model was put forward by integrating the advantage of vector and raster model and using the object-oriented method. The data structures of the four basic features, i.e. point, line, surface and solid, were described. An application was analyzed and described, and the characteristics of this model were described. In this model, all objects in the real world are divided into and described as features with hierarchy, and all the data are organized in vector. This model can describe data based on feature, field, network and other models, and avoid the disadvantage of inability to integrate data based on different models and perform spatial analysis on them in spatial information integration.

A Multi-layer Information Integration Platform for Chemical Process Operation Systems

In the process industry, automation and process control systems are widely implemented, information integration is however far away from satisfactory. It remains a hard job for senior managers to make decisions based on the plant-wide real-time integrated information. This paper proposes a multi-layer information integration platform. In the data integration level, the standard for the exchange of product (STEP) and the extensible markup language (XML) are used to unify these data of the chemical process. In the model integration level, the models are integrated by using the neutral model repository and CAPE-OPEN. In the integration of process task, the common object request broker architecture (CORBA) is used as the communication mediator. The XML is taken as the data standard. A uniform information platform is thus constructed and realized. The proposed information integration platform is satisfactorily implemented to solve the Tennessee Eastman (TE) problem.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.

Fault monitoring based on mutual information feature engineering modeling in chemical process

A large amount of information is frequently encountered when characterizing the sample model in chemical process.A fault diagnosis method based on dynamic modeling of feature engineering is proposed to effectively remove the nonlinear correlation redundancy of chemical process in this paper.From the whole process point of view,the method makes use of the characteristic of mutual information to select the optimal variable subset.It extracts the correlation among variables in the whitening process without limiting to only linear correlations.Further,PCA(Principal Component Analysis)dimension reduction is used to extract feature subset before fault diagnosis.The application results of the TE(Tennessee Eastman)simulation process show that the dynamic modeling process of MIFE(Mutual Information Feature Engineering)can accurately extract the nonlinear correlation relationship among process variables and can effectively reduce the dimension of feature detection in process monitoring.

Evaluation on Information Model about Sensors Featured by Relationships to Measured Structural Objects

In accordance with the requirements of expanding Machine-To-Machine communication (M2M), the network overlay is in progress in several domains such as Smart Grid. Consequently, it is predictable that opportunities and cases of integrating yielded data from devices such as sensors will increase more. Accordingly, the importance of Ontology and Information Models (IM) which normalize the semantics including sensor expressions, have increased, and the standards of these definitions have been more important as well. So far, there have been multiple initiatives for standardizing the Ontology and IM in regards to the sensors expression such as Sensor Standards Harmonization by the National Institute of Standards and Technology (NIST), W3C Semantic Sensor Network (SSN) and the recent W3C IoT-Lite Ontology. However, there is still room to improve the current level of the Ontology and IM on the viewpoint of the implementing structure. This paper presents a set of IMs on abstract sensors and contexts in regards to the phenomenon around these sensors from the point of view of a structure implementing these specified sensors. As several previous studies have pointed out, multiple aspects on the sensors should be modeled. Accordingly, multiple sets of Ontology and IM on these sensors should be defined. Our study has intended to clarify the relationship between configurations and physical measured quantities of the structures implementing a set of sensors. Up to present, they have not been generalized and have remained unformulated. Consequently, due to the result of this analysis, it is expected to implement a more generalized translator module easily, which aggregates the measured data from the sensors on the middleware level managing these Ontology and IM, instead of the layer of user application programs.

A Survey of Web Information System and Applications

The fourth international conference on Web information systems and applications （WISA 2007） has received 409 submissions and has accepted 37 papers for publication in this issue. The papers cover broad research areas, including Web mining and data warehouse, Deep Web and Web integration, P2P networks, text processing and information retrieval, as well as Web Services and Web infrastructure. After briefly introducing the WISA conference, the survey outlines the current activities and future trends concerning Web information systems and applications based on the papers accepted for publication.

基于OPC UA的纤维缠绕机信息模型开发和应用

为实现对复合材料纤维缠绕机生产过程的监测,以缠绕机及其辅助设备为研究对象,针对实际加工设备的多样性造成的加工数据采集的异构性,基于OPC UA建立缠绕机的信息模型架构。根据OPC基金会发布的OPC UA规范和相关的行业标准,建立纤维缠绕机系统的信息模型和实例化。基于开源项目open62541,导入编译后的缠绕机的信息模型代码,自定义开发出符合使用规范的OPC UA服务器,然后利用UA客户端实现对服务器的连接,客户端能够通过服务器查询系统的加工数据,解决加工数据的异构性问题以达到监测缠绕机生产加工过程的目的;最后验证了建立的纤维缠绕机信息模型能够正确导入到开源项目open62541中,实现了加工数据监测。

基于文本数据的灾害信息风险监测与预警集成方法研究

基于灾害信息的文本数据,该文提出一种风险监测与预警集成方法,以提高灾害信息风险监测效率及监测支持预警的针对性。首先,运用八爪鱼数据采集器采集和处理灾害信息的文本数据;其次,运用BTM主题模型构建灾害信息风险监测模型,得到主题热度趋势并确定具有高风险且亟待预警的话题;然后,提出灾害信息风险预警指标体系和预警等级判定方法,计算所确定话题的风险综合指标预警加权值,并结合预警区间判定预警等级;最后,以2021年“7·20”郑州特大暴雨灾害信息的风险监测和预警为例进行实验分析,验证所提方法的可行性。研究表明,该方法可将灾害信息的文本数据贯穿于风险监测与预警两个过程,有助于为监测结果更有针对性地支持预警工作提供参考。

基于Wi-Fi Sensing的无感检测技术

随着智能家居的推广普及,对于移动物体的行为感知成为热点技术。相比于传统的信息检测技术,新型的基于Wi-Fi信号的设备无关被动入侵检测,能够在无需用户做任何干预也不影响人员隐私安全的情况下实现对于行为的检测判断,这和使用摄像头或红外检测形成显著差异,成为研究热点。该文基于Wi-Fi芯片平台采集物理层信道状态信息,构建与移动载体信息相关的检测模型,结合大数据分析和智能算法,给出相关的实现方案,并基于实验验证实现从无线信道中捕捉波形特征,验证方案的有效性,结合结果分析也为后续精度的进一步提升提供改进方向。

基于鲁棒学习方法的领域事件检测

针对缺乏高质量标注数据的高鲁棒性要求领域事件检测任务,提出了一个集成多种鲁棒学习方法与模型结构的模型。首先,使用数据清洗和数据增强技术,缓解了训练集明显噪声与类别严重不均衡问题;然后,尝试了对抗学习方法和多种鲁棒损失函数,并在带噪声数据上进行鲁棒学习;最后,集成多种预训练模型与pipeline、joint 2种模型结构,得到鲁棒的事件检测结果。检测结果表明,该模型在训练集质量不高的情况下具有较强的鲁棒性和普适性。

基于GIS+BIM的地铁工程实景三维可视化关键技术及应用

针对地铁工程项目可视化管理中存在的模型精细化不足、数据集成与展示不充分及真实性欠缺等问题,本研究提出了利用GIS和BIM技术作为解决方案,提升地铁工程实景三维建设的效果。首先研究构建了地铁工程实景三维平台的建设框架,分析了数据集成与融合、动态层次加载、模型轻量化与显示等关键技术。随后以深圳地铁14号线工程为案例,进行了实景三维可视化平台的建设与功能应用。案例涵盖了工程建设管理图、空间分析可视化、多视角场景漫游及BIM可视化与属性查询等内容,实现了地铁工程项目多源异构数据与模型的集成,提供了多尺度的实景三维可视化展示,为项目管理与决策提供了有力支持。

BIM技术在古建筑修复全流程中的应用

文章结合青岛江苏路教堂的修复工程,探讨数字模型在整个修复流程中的作用和意义。实践证明,建筑数字模型能够协助制定修复计划,合理安排工期;修复数据可以借助数字模型库进行系统整合,优化存取;在后期研究阶段,相关拓展技术也能够在性能化模拟方面发挥关键作用。同时,该经验对于其他类型建筑的保护性修复、老旧小区改造等也具有一定借鉴意义。

基于虚拟现实的纪念馆展厅空间展陈一体化系统

为优化纪念馆展陈布局,提升用户对纪念馆展厅空间展陈系统的体验感,设计基于虚拟现实的纪念馆展厅空间展陈一体化系统。纪念馆数据组织层利用摄像机与传感器等设备采集纪念馆展厅与展品图像数据,通过图像解析模块将采集的2维图像数据解析为DICOM3.0标准数据格式,并利用基于视觉感知的图像增强方法预处理图像,由此获取纪念馆场景数据;纪念馆展陈3维建模层基于场景数据,利用3D MAX软件,根据展厅空间布局陈列形状特征构建纪念馆展厅及展品的3维模型,实施模型渲染与烘焙处理;纪念馆虚拟展示层基于所构建的展厅与展品3维模型,利用3维展示与全景漫游等方式实现纪念馆可视化虚拟展示。实验结果表明:该系统模型构建精度较高,可为用户提供更优质的交互感与沉浸式体验感。

基于信息集成的海上油田精细注采实践

油田开发信息集成技术支撑下的精细注采是实现挖潜增产的有效手段。针对海上L油田开发面临的注采矛盾和复杂开发状况,按照标准化集成思路构建了复杂多层油藏三维信息模型。模型以井轨迹坐标点为载体将钻井、测井、完井、测试和产注量等5种数据类信息向井筒方向集成,以储层坐标点为载体将构造、地质和油藏研究成果等3种认识类信息向储层方向集成,利用节点连接实现了井筒信息和储层信息的智能匹配。通过目标函数的嵌入,对集成信息进行调用计算和可视化分析,上述模型可完成多层复杂油田的注采动态精细分析与指标预测。L油田实践表明,该技术可有效指导增产措施优选与开发方案优化,帮助提升油田开发决策水平。

建筑信息建模技术在轻型装配式建造过程中的应用研究

建筑信息建模(Building Information Modeling,BIM)技术,主要是通过数字信息仿真的方式来建立建筑模型,以此来还原其真实的信息,供相关部门参考。其具备信息完备性、关联性、一致性、可视化性、协调性、模拟性、优化性以及可出图性等特点,被广泛地应用在复杂型建筑、水电工程施工总布置、古典建筑中。近几年,随着BIM技术的不断完善,其被广泛地应用在轻型装配式的建造中,并且取得了显著应用效果。基于此,对建筑信息建模技术在轻型装配式建造过程中的应用进行研究,以此来为建筑信息建模技术的应用以及相关部门提供参考。

基于大数据的数字化系统一体化调度信息集成模型

由于已有集成模型分类过滤能力较差,因此提出一种基于大数据的数字化系统一体化调度信息集成模型。通过小波多窗谱特征提取数字化系统一体化调度信息并进行预处理。在二维空间中对最近邻点进行模糊搜索,获取数字化系统一体化调度信息模糊聚类中心,对信息聚类目标函数进行优化,完成调度信息分类过滤。结合大数据技术对调度信息结构层次进行分析,构建调度信息集成模型。实验结果表明,所提模型不仅能够提升调度信息分类过滤能力,同时还能够加强集成效率和容错性。

基于达索平台的雄安东西轴明挖隧道BIM技术研究

为提高雄安东西轴地下明挖隧道设计效率与质量,开展基于达索平台的BIM(Building Information Modeling)设计研究。提出明挖隧道BIM设计流程,对其主体结构、围护结构、防水、接口、钢筋等进行BIM参数化设计。采用Composer软件实现BIM设计交底,并对成果数据进行集成与共享,实现从设计阶段向施工阶段精度为LOD3.5的BIM成果交付,为后续相关工程的BIM设计应用提供参考。

矿山测量数据采集和处理一体化研究

矿山测量中,数据采集与处理的分散、不连贯及繁琐问题显著。本研究构建基于GIS的矿山测量一体化框架,整合数据采集、处理、存储与展示,消除数据冗余与丢失。深入探索数据预处理、校核、分析等核心环节,确保数据完整、准确、及时。实证表明,该一体化处理方式显著提升测量效率与精度,简化流程,减少数据丢失与冗余,节约资源。此研究为矿山测量现代化提供了技术支撑与实践新径,推动行业向更高效、精准方向发展。