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Hu, Shushan
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Hu, Shushan
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Hu, Shushan
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Now showing 1 - 4 of 4
- PublicationBuilding Performance Optimisation: A Hybrid Architecture for the Integration of Contextual Information and Time Series DataBuildings tend to not operate as intended, and a pronounced gap often exists between measured and predicted environmental and energy performance. Although the causes of this ‘performance gap’ are multi-faceted, issues surrounding data integration are key contributory factors. The distributed nature of the Architecture, Engineering and Construction (AEC) industry presents many challenges to the effective capture, integration and assessment of building performance data. Not all building data can be described semantically, nor is it feasible to create adapters between many different software tools. Similarly, not all building contextual data can easily be captured in a single product-centric model. This paper presents a new solution to the problem based upon a hybrid architecture that links data which is retained in its original format. The architecture links existing and efficient relational databases storing time-series data and semantically-described building contextual data. The main contribution of this work is an original RDF syntax structure and ontology to represent existing database schema information, and a new mechanism that automatically prepares data streams for processing by rule-based performance definitions. Two test cases evaluate the concept by 1) applying the hybrid architecture to building performance data from an actual building, and 2) evaluating the efficiency of the architecture against a purely RDF-based solution that also stores all of the time-series data in RDF for a virtual building. The hybrid architecture also avoids the duplication of time-series data and overcomes some of the differences found in database schemas and database platforms.
969Scopus© Citations 34 - PublicationEnvironmental and energy performance assessment of buildings using scenario modelling and fuzzy analytic network processA well-recognised gap exists between measured and predicted building energy performance. Some practical assessment approaches offer the potential to reduce this gap using multiple indicators that evaluate building performance. Such approaches rely on subjective analysis of indicators’ relative weights but are typically limited to a fixed assessment structure. Scenario modelling is one method that enables flexible and multi-granular environmental and energy performance assessment by coupling building function with other pivotal aspects of building operation. However, this method weighs all performance criteria equally. The objective of this paper is to empower building managers with enhanced environmental and energy performance assessment by integrating scenario modelling with a Fuzzy Analytic Network Process. Scenario modelling decomposes environmental and energy performance assessment into a set of flexible mappings between performance indicators and multi-granular building objects while Fuzzy Analytic Network Process enables calculation of relative weights by encapsulating ambiguity in domain expertise and complex interactions among often conflicting criteria. A case study demonstrated the engineering value of this approach. The sports centre obtained an operational score of 56.9 out of 100, or level 4 of 6 (i.e. very good) in terms of operational performance classification using calculated relative weights and intermediate results for eight carefully-identified indicators. When compared to an equivalent assessment using equally weighted criteria, the proposed approach enables more informative and targeted evaluations. With these results, building managers can quickly identify inefficient areas of building operation and improve energy consumption while maintaining building function. The approach is applicable for a wide range of buildings.
426Scopus© Citations 22 - PublicationBuilding performance evaluation using OpenMath and Linked Data(Elsevier, 2018-09-01)
; ; ; ; ; A pronounced gap often exists between expected and actual building performance. The multi-faceted and cross lifecycle causes of this performance gap are found in design assumptions, construction issues and commissioning and operational compromises. Some important factors are firmly rooted in the lack of interoperability around building information. New solutions to the interoperability challenge offer the potential to leverage and reuse available heterogeneous data in a manner that can significantly assist building performance assessment. Linked data provides an open, modular and extensible solution for the challenge. However, in the buildings domain, the integration of rule-based performance metrics and contextual information has yet to be formally established. This paper describes an approach to the provision of in-depth building performance assessment through the integration of OpenMath and linked data. An ontology describing performance metrics in RDF is presented, together with an automated metric evaluation solution using multi-silo queries and computer algebra systems, providing a flexible, automated and extensible mechanism for the assessment of building performance. Building managers and engineers can simultaneously analyse time-series building performance at a range of levels, without burdensome manual intervention such as is the case with traditional solutions. A test implementation on a large university building highlights the potential of this solution.661Scopus© Citations 18 - PublicationA performance assessment ontology for the environmental and energy management of buildings(Elsevier, 2015-09)
; ; ; ; Narrowing the performance deficit between design intent and the real-time environmental and energy performance of buildings is a complex and involved task, impacting on all building stakeholders. Buildings are designed, built and operated with increasingly complex technologies. Throughout their life-cycle, they produce vast quantities of data. However, many commercial buildings do not perform as originally intended. This paper presents a semantic web based approach to the performance gap problem, describing how heterogeneous building data sources can be transformed into semantically enriched information. A performance assessment ontology and performance framework (software tool) are introduced, which use this heterogeneous data as a service for a structured performance analysis. The demonstrator illustrates how heterogeneous data can be published semantically and then interpreted using a life-cycle performance framework approach.1801Scopus© Citations 87