Now showing 1 - 8 of 8
  • Publication
    Requirements specification to support BIM-based Thermal Comfort analysis
    Traditionally and during a building's operation, thermal comfort levels are often evaluated using equipment that is expensive to purchase and maintain. Through advanced technologies, Building Information Model (BIM) and energy simulation tools, thermal comfort and its impacts can be evaluated at the conceptual and early design stages. The development of Building Energy Performance Simulation (BEPS) tools, through the implementation of BIM, will provide design teams with rich, comprehensive data to evaluate indoor thermal conditions in order to provide acceptable comfort levels. Current energy simulation models focus on entering data manually, increasing time and cost. BIM-based energy and thermal comfort analysis provides designers with the means to explore a variety of design alternatives, as well as avoiding the time-consuming process of re-entering all of the building's geometry and HVAC specifications to perform an analysis. However, integrating BEPS with BIM-based building design tools is still limited, with one of the key obstacles being the lack of standardised methods for information exchange between the two domains. To address the needs and bridge the gaps, this paper aims to improve the information exchange process by describing data and information needed to perform thermal comfort simulation using a standardised format in order to develop a Model View Definition (MVD) for thermal comfort. This approach represents the data needed by building designers or operators to provide an acceptable level of thermal comfort in a typical small, single occupant office. Through analysis of the performance of the proposed approach, this work provides a standardised exchange of data from BIM to BEPS tools, such as EnergyPlus, using the Industry Foundation Classes (IFC) standard.
  • Publication
    Application Of Intelligent Algorithms For Residential Building Energy Performance Rating Prediction
    Energy Performance Certificates (EPC) provide an indication of buildings’ energy use. The creation of an EPC for individual building requires information surveys. Hence, these ratings are typically non-existent for entire building stock. This paper addresses these information gaps using machine-learning models. Developed models were evaluated with Irish EPC data that included approximately 650,000 residential buildings with 199 inputs variables. Results indicate that the deep learning algorithm produces results with highest accuracy level of 88% when only 82 input variables are available. This identified approach will allow stakeholders such as authorities, policy makers and urban-planners to determine the EPC rating for the rest of the building stock using limited data.
  • Publication
    Uncertainty Quantification In Predictive Modelling Of Heat Demand Using Reduced-order Grey Box Models
    As building energy modelling becomes more sophisticated, the amount of user input and the number of parameters used to define the models continue to grow. There are numerous sources of uncertainty in these parameters especially when a modelling process is being performed before construction and commissioning. Therefore, uncertainty quantification is important in assessing and predicting the performance of complex energy systems, especially in absence of adequate experimental or real-world data.The main aim of this research is to formulate an uncertainty framework to identify and quantify different types of uncertainties associated with reduced-order grey box energy models used in heat demand prediction of the building stock. The uncertainties are characterized and then propagated using the Monte-Carlo sampling technique. Results signify the importance of uncertainty identification and propagation within a system and thus, an integrated approach to uncertainty quantification is necessary to maintain the relevance of developed models.
  • Publication
    Requirements for BIM-based thermal comfort analysis
    When designing and creating a working or living space, the provision of thermal comfort for a building’s occupants remains a key objective. However, energy consumption associated with the delivery of indoor environmental conditioning in the commercial building stock is not necessarily translated into improved thermal comfort conditions. When collaborative design utilises Building Information Models (BIMs), much of the data required for thermal comfort analysis is already defined by other project stakeholders. Furthermore, mechanical equipment such as HVAC and lighting fixtures, play a major role in functional performance, resultant thermal comfort and energy consumption. Monitoring building performance and thermal comfort requires additional representative data about indoor environmental conditions and energy consumption. This paper presents a holistic review of the data and information needed for the integration of BIM with thermal comfort modelling for commercial office spaces. Thermal comfort is dependent on multiple factors such as indoor environmental conditions, user behaviour, properties of building materials, etc. For inclusion in the design process this data must first be categorised in a standardised manner. The outputs of this work contribute to a Model View Definition (MVD) for thermal comfort using the IFC standard.
  • Publication
    A Framework To Assess The Interoperability Of Commercial Buildings At A District Scale
    (International Building Simulation Association England, 2018-09-12) ; ; ;
    Expensive control technology coupled with absence of a proper framework result in buildings that operate independently for their entire operating life. This paper introduces a framework to assess the potential of buildings to function together using heat load demand patterns and buildings thermal mass. Buildings are characterized as possessing variable and stable heat demand patterns and internal conditions are modified to achieve a peak heat demand reduction. Results indicate 8% reduction in overall peak heat demand when two buildings are operated together. The analysis clearly establishes the significance of an integrated energy system that leads to a reduction in peak loads.
  • Publication
    Development of a Model View Definition (MVD) for thermal comfort analysis in commercial buildings using BIM and EnergyPlus
    (Construction IT Allance of Ireland, 2017-11-24) ; ; ; ;
    Buildings are major consumers of global energy resources. Approximately 80% of the energy used in commercial office spaces, is typically used for maintaining optimal comfort levels through delivery of heating, cooling, ventilating, and lighting. Building Information Modelling (BIM) has seen a significant uptake by designers in pursuit of sustainable building designs. Furthermore, general BIM systems already contain much of the information that can be further reused for additional project tasks such as thermal comfort analysis. Integration and improvement of information flows between BIM and Building Energy Performance Simulation (BEPS) tools has the capacity to help designers assess building performance under various design conditions. In doing so, assessments of building performance and thermal comfort requires additional representative data about indoor environmental conditions and energy consumption. The process of connecting BIM to energy simulation tools, for the explicit purpose of thermal comfort analysis, requires a well-defined Model View Definition (MVD). MVDs define a subset of the Industry Foundation Classes (IFC) schema, which is needed to support a particular business process. This paper develops a MVD for thermal comfort that represents the data needed by building designers or operators to deliver a satisfactory level of thermal comfort in a typical small, single occupant office. The use case consists of a single thermal zone with a HVAC system. The detailed specification for these requirements is based on the IFC data representation. The IfcDoc application tool is used to improve the consistency and define computer-interpretable definition of the MVD. The outputs of this work will allow a standardised exchange of the necessary requirements from BIM to BEPS tools (e.g. EnergyPlus) for thermal comfort analysis.
  • Publication
    Comparative Analysis of Machine Learning Algorithms for Building Archetypes Development in Urban Building Energy Modeling
    The most common approach for urban building energy modeling (UBEM) involves segmenting a building stock into archetypes. Development Building archetypes for urban scale is a complex task and requires a lot of extensive data. The archetype development methodology proposed in this paper uses unsupervised machine learning approaches to identify similar clusters of buildings based on building specific features. The archetype development process considers four crucial processes of machine learning: data preprocessing, feature selection, clustering algorithm adaptation and results validation. The four different clustering algorithms investigated in this study are KMean, Hierarchical, Density-based, K-Medoids. All the algorithms are applied on Irish Energy Performance Certificate (EPC) that consist of 203 features. The obtained results are then used to compare and analyze the chosen algorithms with respect to performance, quality and cluster instances. The K-mean algorithm preforms the best in terms of cluster formation.
  • Publication
    Extending IFC to support thermal comfort prediction during design
    (European Council on Computing in Construction, 2019-07-12) ; ; ; ; ;
    During the early design stage, designers often rely on general rules of thumb to make critical decisions about the geometry, construction systems and materials without fully evaluating their effects on indoor thermal environment requirements and constraints. Currently, reviewing a design’s sustainability requires designers to spend a significant amount of time manually extracting Thermal Comfort (TC) data from BIMs because of the tedious nature of this task. This paper is motivated by the absence of a standard method and a schema for extracting the necessary data for an automated TC assessment of building designs. The aim is to generate a reusable and retrievable set of Exchange Requirement’s for BIM-based BTCS to facilitate efficient data extraction and exchanges from design models using the IFC file format. Furthermore, we develop an MVD mechanism that provides a structured framework for the definition and exchange of the target data as a step towards standardisation and production of BTCS related information, the results from which contribute to a proposed MVD. The application of the MVD in building design has the potential to improve the early-stage TC assessment of design alternatives. Further, it could reduce the time required to conduct the assessment, increase the reproducibility of results, and formalises the method used.