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在数据丰富的环境中确保数据质量和相关性.pdf

上传人: 科*** 编号:713439 2025-06-08 35页 7.10MB

1、Ensuring data quality&relevance in a data-rich environmentSerryn EaglesonCredit:Azote for Stockholm Resilience Centre,Stockholm University.Based on Richardson et al.2023,Steffen et al.2015,and Rockstrm et al.2009Opportunities for data in the asset lifeDesign/ConstructionLegacy/Maintenance Strategic

2、PlanningOperational PlanningOperationsBusiness CasesWhole Life Costing Data&VisualisationOptimisation of Design Carbon trackingIncreased team coordination Fast track design program with early fabrication and manufacture input(DfMA)Accurate representation of the asset Scenario testing Resource optimi

3、sation and planning of staff Increased efficiency of handover into live operationsTwin of twinsRight time monitoring and Integrated feedback loop Increased efficiency of operational processesEnhanced engagement and experienceIncrease in asset performance Automated status collectionReal-time conditio

4、n monitoring and preventative and predictive maintenanceMore accurate and efficient planning of future renewals and enhancementsLegislationIn Australia,the Security of Critical Infrastructure Act 2018(SOCI)now requires private asset owners that are defined as critical infrastructure to minimise or e

5、liminate a material risk,and mitigate the impact,of natural hazards on the critical infrastructure.Mandatory climate-related financial disclosures,providing Australians and investors with greater transparency and more comparable information about an entity exposure to climate-related financial risks

6、 and opportunities and climate-related plans and strategies.(Mandatory climate-related financial disclosures-Policy position statement)SOCI Act sectors and asset classesUrban Heat Island(UHI)EffectContributing factorsx3 Height to area ratio of buildings Building density Sky view factorBuilding geome

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本文主要内容围绕资产全生命周期的数据质量和相关性保证。关键点如下: 1. 数据应用:数据在资产生命周期的设计、建设、维护和战略规划等方面发挥作用,如优化设计、碳跟踪、提高团队协调等。 2. 法规要求:澳大利亚关键基础设施法规要求私有资产所有者降低自然灾害对关键基础设施的影响。 3. 城市热岛效应:分析了城市热岛效应的影响因素,如建筑高度、密度和天空可视因子等。 4. 数据整合:通过自动化、AI和BIM技术实现资产信息的一致性传递,提高数据质量检查和整合。 5. 数字孪生:利用修正后的BIM模型和外部资产数据库实现资产数字孪生,结合物联网技术进行实时监控。 6. 自动化检测:利用机器学习实现自动化资产检查,降低时间和人力成本,提高运营和维护效率。 核心数据引用: - 资产信息整合涉及500多个IFC和Revit模型,定义20个数据质量检查规则,分析100多个参数。 - 自动化检查技术可减少70%的时间、50%的现场人员和最高40%的运营维护成本。
"资产数据如何优化设计?" "BIM如何助力智能资产管理?" "AI如何革新建筑检测?"
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