Now showing 1 - 10 of 31
  • Publication
    Data-Requirements Specification to Support BIM-Based HVAC-Definitions in Modelica
    Recent developments in Building Information Model (BIM) capable software are leading to increased interoperability among heterogeneous tools. The results are representing greater levels of data available for all stakeholders involved in the building industry. The increasing range of data within BIMs enables the reuse of data for downstream applications such as Building Energy Performance Simulation (BEPS). Current BEPS tools work well in many modeling scenarios, but fail to support innovative and flexible model configurations due to existing tool limitations. Modelica is an object-oriented, equation-based programming language used for detailed dynamic simulation purposes across different industries. The use of Modelica in the building industry is increasing and it is a promising and flexible tool to provide modeling solutions addressing the upcoming challenges in the building industry and beyond. This paper illustrates a method of using BIM based information as the primary data source for a flexible simulation application. It includes an implementation for a defined generic use case.
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  • Publication
    Operational characterisation of neighbourhood heat energy after large-scale building retrofit
    To achieve housing retrofit targets, traditional house-by-house approaches must scale. Neighbourhood retrofit also facilitates community participation. This paper aims to quantitatively characterise the heat energy demand of similar homes in a post-retrofit neighbourhood. The method employs the Modelica AixLib library, dedicated to building performance simulation. A modern semi-detached house is modelled as thermal network. The passive thermal network is calibrated against an equivalent EnergyPlus model. The developed Modelica model then generates time series heat energy demand to meet occupant comfort. This model separates heating for internal space and domestic hot water. Simulation results are gathered for a range of house occupancy profiles, with varying heating schedules and occupant quantities. The calibration results compare the time series of internal house temperature produced by the EnergyPlus and Modelica simulations. Modelica simulations of two heating schedules generate distinct annual demand curves against occupant quantity. As expected in a modern house, domestic hot water accounts for a relatively high proportion of heat energy. Over a year it ranges between 20% and 45% depending on occupant profile. Overall conclusions are threefold. Firstly, occupant profiles of a modern semidetached house increase annual heat energy demand by 77%, and the coincidence of daily peak demand persists across occupant profiles. Furthermore, percentages of domestic hot water demand start from 20% or 24% and plateau at 39% or 45% depending on space heating schedule. A statistical distribution of energy demand by neighbourhood homes is possible. Its curve plot is not perfectly normal, skewing to larger energy demands.
      413
  • 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.
      294
  • 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.
      329
  • Publication
    Dynamic District Information Server: On the Use of W3C Linked Data Standards to Unify Construction Data
    (European Council on Computing in Construction, 2019-07-12) ; ;
    The evolution of ICT and BIM systems in the construc- tion domain yield detailed views of buildings and their use throughout their lifespan. These systems also provide a structure around which information about buildings and their effect on surrounding infrastructure can be described in space and time. Thus, when aggregated, information provided by these systems can serve as a semantic structure through which other information can be stored and con- textualized. While bespoke systems have explored these approaches in particular contexts, few if any systems have been constructed to provide a flexible, semantically rich structure that can be used to structure information about any urban landscape at district and regional scales. This paper describes such a system. The Dynamic District Information Server (DDIS) provides a core information structure which can be extended to store as yet undefined information structures and allow these to be reasoned about in the contexts that range from neighbourhoods to regions. In addition, the paper describes how the DDIS can serve as a coordinating process in a tool chain by providing a semantically rich and flexible notification system that al- lows tools in the chain to notify one another when steps in some information process have been completed.
    Scopus© Citations 2  371
  • Publication
    A Data-Driven Modelling Approach for Large Scale Demand Profiling of Residential Buildings
    In this paper the traditional use of data-driven models (DDM) as forecasting tools is coupled with parametric simulation to create a building modelling framework for demand profiling of a large number of buildings of the same typology. Most studies to date utilising DDM have been conducted on single buildings, with less evidence of the role that DDM may have as a modelling technique for application at scale. The proposed methodology is based on the use of a simulation-based building energy modelling tool and a parametric simulator to create a large dataset consisting of 4096 different building model scenarios. Three DDM techniques are utilised; Support Vector Machines, Neural Networks and Generalised Linear Models, these are trained and tested using the generated simulation dataset. Results, at an hourly resolution, show that DDM approaches can correctly emulate the outputs of the building simulation software with mean absolute error ranging from 4 to 9 percent for different DDM algorithms.
    Scopus© Citations 2  142
  • Publication
    Model View Definition for Advanced Building Energy Performance Simulation
    Recent demand for higher energy efficiency within the building sector has led to the use of Building Energy Performance Simulation (BEPS) tools. These powerful predictive tools enable investigation of environmental and energy performance for different design and retrofit design alternatives. However, integrating BEPS with Building Information Modelling (BIM) based building design tools still experiences limitations due to a lack of standardised methods of information exchange between these domains. As a result, this paper presents a Model View Definition (MVD) for advanced BEPS. In doing so this work enables a standardised exchange of data from BIM to BEPS tools, such as Modelica, using the Industry Foundation Classes (IFC) standard. The entire process becomes available through the open source software framework emerged from the IEA EBC Annex 60.
      310
  • Publication
    A Review on Country Specific Data Availability and Acquisition Techniques for City Quarter Information Modelling for Building Energy Analysis
    (Verlag der Technischen Universität Graz, 2020-09-25) ; ; ; ;
    This paper addresses the increasing number of disparate data resources used for urban modelling. The objective of this work is to provide a standardized approach for processing these resources for urban energy modelling studies. This paper details the approach of a collaborative project to standardize categorization, acquisition and processing of diverse datasets for energy modelling and simulations are explained. Furthermore, based on the data categorization, this research provides an overview of the country-specific data availability and sources (for Austria, Germany and Switzerland) required for urban energy simulations. The result is a standardized structure for information exchange which is published in an extendable online template.
      222
  • 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.
      533
  • Publication
    Requirements for a BIM-Based Life-Cycle Performance Evaluation Framework to Enable Optimum Building Operation
    (Eindhoven University of Technology, 2015-10-29) ; ;
    Buildings rarely perform as well in practice as anticipated during design, and often consume 20-30% more energy than necessary. One of the main causes of inefficient operation is the lack of data integration and system interoperability inherent in the AEC/FM industry. In many cases, the assumptions and specifications defined during design are not transferred throughout the life-cycle of the building, and actual operation deviates from design intent. Building Information Modelling enables designers to create digital models of buildings. Theoretically, these models should be exchangeable between disciplines and over different life-cycle stages, but in practice the lack of information exchange protocols in the building performance area inhibits such exchanges. In order to improve building operation throughout the building life-cycle, this paper proposes a BIM-based performance evaluation framework to compare design intent with actual operation. The framework uses the IFC schema to facilitate the information exchange process for better qualification and validation of data.
      491