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Corry, Edward
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Corry, Edward
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Corry, Edward
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- 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 - PublicationLiDAR point-cloud mapping of building façades for building energy performance simulationCurrent processes that create Building Energy Performance Simulation (BEPS) models are time consuming and costly, primarily due to the extensive manual inputs required for model population. In particular, generation of geometric inputs for existing building models requires significant manual intervention due to the absence, or outdated nature of available data or digital measurements. Additionally, solutions based on Building Information Modelling (BIM) also require high quality and precise geometrically-based models, which are not typically available for existing buildings. As such, this work introduces a semi-automated BEPS input solution for existing building exteriors that can be integrated with other related technologies (such as BIM or CityGML) and deployed across an entire building stock. Within the overarching approach, a novel sub-process automatically transforms a point cloud obtained from a terrestrial laser scanner into a representation of a building's exterior façade geometry as input data for a BEPS engine. Semantic enrichment is performed manually. This novel solution extends two existing approaches: (1) an angle criterion in boundary detection and (2) a voxelisation representation to improve performance. The use of laser scanning data reduces temporal costs and improves input accuracy for BEPS model generation of existing buildings. The approach is tested herein on two example cases. Vertical and horizontal accuracies of 1% and 7% were generated, respectively, when compared against independently produced, measured drawings. The approach showed variation in accuracy of model generation, particularly for upper floors of the test case buildings. However, the energy impacts resulting from these variations represented less than 1% of the energy consumption for both cases.
384Scopus© Citations 23 - 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 - PublicationBuilding performance optimization using cross-domain scenario modeling, linked data, and complex event processingThe scenario modeling method empowers building managers by enabling comprehensive performance analysis in commercial buildings, but is currently limited to data from the building management domain. This paper proposes that Linked Data and Complex Event Processing can form the basis of an interoperability approach that would help to overcome technical and conceptual barriers to cross-domain scenario modeling. In doing so, this paper illustrates the cross-domain potential of scenario modeling to leverage data from different information silos within organizations and demonstrates how to optimize the role of a building manager in the context of his or her organization. Widespread implementations of cross-domain scenario models require a solution that efficiently manages cross-domain data acquisition and post processing underpinned by the principles of linked data combined with complex event processing. An example implementation highlights the benefits of this new approach. Cross-domain scenario models enhance the role of the building manager within an organization and increase the importance of information communicated by building managers to other organizational stakeholders. In addition, new information presented to stakeholders such as facilities managers and financial controllers can help to identify areas of inefficiency while still maintaining building function and optimized energy consumption. Two key challenges to implementing cross-domain scenario modeling are: the data integration of the different domains' sources, and the need to process scenarios in real-time. This paper presents an implementation approach based on linked data to overcome interoperability issues, and Complex Event Processing to handle real-time scenarios.
880Scopus© Citations 38 - 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.1802Scopus© Citations 88