FNR - Attenuating the Environmental Impact of our Buildings through Semantic-based Dynamic Life cycle Assessment (SemanticLCA)

我们的愿景是，人类能够积极地减弱和控制他们的建筑对环境的影响，并减轻气候变化的影响。这可以通过基于模型的新一代生命周期评估方法和工具来实现，这些方法不断地从实时数据中学习，同时为建筑物和地区的有效运营和管理策略提供信息。在这方面，当前的生命周期评估方法存在重要的局限性和差距，包括：(A)缺乏推理和决策支持能力，例如探索用于评估替代设计方案和设计适应策略的假设情景，从而促进对建筑物和地区的主动控制。(B)缺乏与领域模型，如BIM(建筑信息建模)、GIS(地理信息系统)和LCA数据结构的协调。(C)缺乏时间信息的支持。有必要在生命周期清单(LCI)和影响评估(LCIA)阶段考虑时间信息，以处理维护、操作、拆卸、处置和回收阶段。拟议的研究通过使用语义网技术为我们的构建资产提供生命周期评估解决方案，解决了利用数字构建环境资源的挑战。我们的假设是：生命周期评估以语义为基础，由动态数据提供信息，为更准确的生命周期影响评估铺平了道路，同时支持生命周期决策和对建筑和区域的主动控制。简而言之，SemancLCA的目标是开发一种(接近)实时语义能力，该能力利用广泛的数字数据源并利用人工智能来评估已建成资产的全生命周期环境影响。提出了以下研究问题：RQ1：使用包括BIM(IFC)和地理信息系统(CityGML)在内的语义来整合现有的生命周期清单数据库并将其联系起来，能否为简化建筑物和地区的生命周期评估过程提供可靠的基础？RQ2：在BIM和地理信息系统友好的时间序列数据库中管理的动态数据访问能否提供更准确的施工和运营阶段环境影响的描述？RQ3：通过探索对环境影响最小的广泛选项和情景，同时就纠正计划提供建议，所产生的SemancLCA环境能否帮助非专家做出决策？我们的工作计划包括三个工作包(WP)，每个工作包解决我们提出的一个研究问题，第四个横跨领域的WP解决演示和验证活动。评估将在两个示范点进行：加的夫(英国)和贝尔瓦尔(卢森堡)。加的夫的演示将在女王的建筑(工程学院)进行，并扩大到加的夫大学拥有和管理的130座建筑，其中大部分位于市中心。名单展示将在贝尔瓦尔的L创新中心进行，并扩大到贝尔瓦尔的整个地区(由丰斯·贝尔瓦尔管理)。鉴于LCA在地区层面的复杂性，验证将使用基于模拟的方法，并在实际操作条件下演示和验证用例的子集。验证工作将利用加的夫和贝尔瓦尔城市平台正在进行的开发，如CUSP网站www.cupplform.com所示。SemancLCA得到来自加的夫大学的10个合作伙伴和经验丰富的调查团队的支持，并列出了在以下方面的互补专业知识：a)建筑环境中的人工智能应用，b)多尺度建筑环境数据的语义上下文，c)智能云/边缘计算，d)生命周期评估方法和工具，e)用于资产建模和能源效率的建筑信息建模。

Our vision is that humans can attenuate and control positively the impact of their buildings on the environment and mitigate the effects of climate change. This can be achieved by a new generation of life cycle assessment methods and tools that are model-based, continuously learn from real-time data, while informing effective operation and management strategies of buildings and districts.In that respect, current LCA methods present important limitations and gaps, including:(a) Lack of reasoning and decision support capabilities, such as exploring "what if" scenarios for the evaluation of alternative design options and devising adapted strategies, thus promoting active control of buildings and districts.(b) Lack of alignment with domain models, e.g. BIM (Building Information Modelling), GIS (Geographical Information Systems), and LCA data structures. (c) Lack of support of temporal information. There is a need to factor in temporal information in the life cycle inventory (LCI) and Impact Assessment (LCIA) phases to address maintenance, operation, deconstruction, disposal and recycling stages. The proposed research addresses the challenge of leveraging digital built environment resources by using semantic web technologies to deliver life cycle assessment solutions to our built assets. Our hypothesis is that: life cycle assessment underpinned by semantics and informed by dynamic data paves the way to more accurate life cycle impact assessment while supporting life cycle decision making and active control of buildings and districts. In a nutshell, the aim of SemanticLCA is the development of a (near) real-time semantic capability that exploits a wide range of digital data sources and leverages artificial intelligence to assess the whole-life cycle environmental impacts of built assets. The following research questions are posited: RQ1: Can the use of semantics, including BIM (IFC) and GIS (CityGML), to integrate and contextualise existing life cycle inventory databases, provide a sound basis to streamline the life cycle assessment process of buildings and districts? RQ2: Can access to dynamic data, managed in a BIM and GIS friendly time series database, provide more accurate accounts of environmental impacts during the construction and operation stages? RQ3: Can the resulting SemanticLCA environment assist in decision making by non-experts by exploring a wide range of options and scenarios with the least environmental impact, while also advising on corrective plans?Our work programme involves three Work-Packages (WP), each addressing one of our posited research questions, and a fourth cross-cutting WP addressing demonstration and validation activities. The evaluation will be carried out in two demonstration sites: Cardiff (UK) and Belval (Luxembourg). The Cardiff demonstration will be carried out in the Queen's building (School of Engineering) and scaled up to the 130 buildings owned and managed by Cardiff university, majority of which are located in the city centre. The LIST demonstration will be carried out in the Maison de l'Innovation in Belval and scaled up to the entire district of Belval (managed by Fonds Belval). Given the complexity of LCA at district level, validation will utilise a simulation based approach with a subset of use cases demonstrated and validated in real operation conditions. The validation work will leverage ongoing developments of city platforms for Cardiff and Belval, as illustrated on the CUSP website: www.cuspplatform.com.SemanticLCA is supported by 10 partners and an experienced team of investigators from Cardiff University and LIST bringing together complementary expertise in: a) AI applications in the built environment, b) semantic contextualisation of multi-scale built environment data, c) intelligent cloud/edge computing, d) Life cycle assessment methods and tools, e) Building Information Modelling for asset modelling and energy efficiency.