Publications

@inproceedings{Howley2013,
title = {Are You Sitting Comfortably? Towards Engineering Fundamental Thermal Comfort},
author = {Martin Howley and Daniel Coakley and Marcus M Keane and Rory F D Monaghan},
url = {http://ilta.ie/edtech/edtech-2013/},
year = {2013},
date = {2013-05-01},
booktitle = {Educational Technology (EdTech)},
address = {Cork, Ireland},
abstract = {This paper discusses an engineering fundamentals lab, which forms part of the undergraduate engineering course at NUI, Galway [1]. The lab aims to introduce the concept of Thermal Comfort utilising a novel data driven approach.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Coakley2013b,
title = {Are You Sitting Comfortably? A novel approach to teaching and assessing laboratory-based thermal comfort},
author = {Daniel Coakley and Martin Howley and Rory F D Monaghan and Marcus M Keane},
editor = {Michael G Madden and Conch{ú}r Ó Bradaigh},
url = {http://hdl.handle.net/10379/},
year = {2013},
date = {2013-04-01},
booktitle = {NUIG-UL Alliance - Engineering, Informatics & Science Research Day},
pages = {93},
publisher = {National University of Ireland Galway},
address = {Galway, Ireland},
abstract = {Thermal comfort is a key indicator of building performance and is proven to have a strong correlation with concentration and productivity under laboratory conditions. Typically, thermal comfort is defined using the Predicted Mean Vote (PMV) / Predicted Percentage Dissatisfied (PPD) [1]. This paper proposes a novel approach to teaching the concept of thermal comfort by linking prior knowledge with strong measurementbased analysis. This work aims to advance fundamental understanding of comfort criteria as a core element of building design and operation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{McCaffrey2013,
title = {Using WebGL to Visualise Building Energy System Information},
author = {Ronan McCaffrey and Hugh Melvin and Marcus M Keane and Daniel Coakley},
editor = {Michael G Madden and Conch{ú}r Ó Bradaigh},
url = {http://hdl.handle.net/10379/3345},
year = {2013},
date = {2013-04-01},
booktitle = {NUIG-UL Alliance - Engineering, Informatics & Science Research Day},
pages = {19},
address = {Galway, Ireland},
organization = {National University of Ireland, Galway},
abstract = {Web browsers have developed greatly over the past 5- 10 years in terms of technical ability. They are no longer just responsible for displaying static web pages, but are competing with desktop specific applications. In parallel, Building Management Systems are becoming more complex and generate large volumes of data. An interesting development in modern browsers is the advent of plugin-free 3d graphics which can be used to help people visualize complex imagery and data such as building usage statistics in a user friendly and intuitive way. It is my aim to use this technology to further advance the work of the BEMSAA project [1]. The aim is to use the latest HTML5 and JavaScript technologies to enable Building Managers, Engineering Students and interested Stakeholders to interact with building information models and performance data.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Bruton2013a,
title = {Results from testing of an online automated fault detection and diagnosis tool for AHU's},
author = {Ken Bruton and Daniel Coakley and Peter O'Donovan and Marcus M Keane and Dominic O'Sullivan},
year = {2013},
date = {2013-01-01},
booktitle = {Emerging Technology & Factory Automation (EFTA)},
address = {Cagliari, Italy},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Coakley2013a,
title = {Calibration of a Detailed Building Energy Simulation (BES) Model to Measured Data using an Analytical Optimisation Approach},
author = {Daniel Coakley and Paul Raftery and Padraig Molloy},
year = {2013},
date = {2013-01-01},
booktitle = {NUIG-UL Alliance - Engineering, Informatics & Science Research Day},
pages = {83},
abstract = {This paper outlines a methodology for the calibration of detailed building energy simulation (BES) models using an analytical optimisation approach. The approach combines evidence-based model development with statistical Monte-Carlo based optimisation techniques. The first stages of the proposed calibration methodology are applied to a 700m2 naturallyventilated library building using short-term monitored BMS and sensor data. The paper concludes with a discussion of how this methodology differs from existing approaches and the benefits it offers over traditional calibration techniques.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Corry2013b,
title = {The role of Linked Data and the Semantic Web in Building Operation},
author = {Edward Corry and Daniel Coakley and James O'Donnell and Marcus M Keane},
year = {2013},
date = {2013-01-01},
booktitle = {NUIG-UL Alliance - Engineering, Informatics & Science Research Day},
pages = {70},
abstract = {Effective Decision Support Systems (DSS) for building service managers require adequate performance data from many building data silos in order to deliver a complete view of building performance. Current performance analysis techniques tend to focus on a limited number of data sources, such as BMS measured data (temperature, humidity, C02), excluding a wealth of other data sources increasingly available in the modern building, including weather data, occupant feedback, mobile sensors & feedback systems, schedule information, equipment usage information. This paper investigates the potential for using Linked Data and Semantic Web technologies to improve interoperability across AEC domains, overcoming many of the roadblocks hindering information transfer currently.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Coakley2013d,
title = {Smart and Sustainable Buildings},
author = {Daniel Coakley and Marcus M Keane.},
editor = {Dr. Roger Bentley},
year = {2013},
date = {2013-01-01},
booktitle = {Global Energy Systems Conference},
address = {Edinburgh, Scotland},
abstract = {Buildings consume 40% of the overall energy, both in EU and US, and are responsible for an excess of 30% of CO2 emissions. Future smart & sustainable buildings, which optimise the performance and energy use at all stages of building life cycle, are therefore a key priority. In sustainable buildings, aspects such as external climate, building envelope, internal environment and building energy management systems must be considered. As buildings and systems grow more complex, so too does the need to use advanced simulation techniques to analyse these systems. There are three major types of numerical methods to support this analysis: (i) building performance simulation (ii) computational fluid dynamics (CFD) and (iii) reduced order models. The different types of numerical models and their possible coupling has been proven to be an effective tool for the development, commissioning and operational optimisation of sustainable buildings. The IRUSE research group is currently working on providing research which formalises methods for creating and calibrating models of the built environment. This work aims to provide models which are capable of delivering more accurate prediction of energy performance in buildings as well as a means of optimising comfort and efficiency.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Coakley2012b,
title = {Calibration of a Building Energy Simulation (BES) Model to Energy Monitoring System Data Using an Analytical Optimisation Approach},
author = {Daniel Coakley and Paul Raftery and Padraig Molloy},
year = {2012},
date = {2012-10-01},
booktitle = {Intel European Research and Innovation Conference (ERIC)},
address = {Dublin, Ireland},
abstract = {Globally buildings consume more than 40% of primary energy and are responsible for in excess of 30% CO2 emissions. Building Energy Simulation (BES) models can play a significant role in the design and optimisation of buildings. Simulation models may be used to assess the cost-effectiveness of Energy-Conservation Measures (ECMs) in the design stage as well as various performance optimisation measures during the operational stage. However, due to the complexity of the built environment and prevalence of large numbers of independent inter-acting variables, it is often difficult to achieve an accurate representation of real-world building operation. Therefore, by reconciling model outputs with measured data, we can achieve more accurate and reliable results. This research focuses on the development of a novel evidenced-based analytical optimisation methodology for the calibration of Building Energy Simulation (BES) models.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Coakley2012e,
title = {Calibration of Whole Building Energy Simulation Models: Detailed Case Study of a Naturally Ventilated Building Using Hourly Measured Data},
author = {Daniel Coakley and Paul Raftery and Padraig Molloy},
editor = {Jonathan Wright and Malcolm Cook},
url = {www.ibpsa-england.org/resources/files/bso-2012/1C2.pdf},
isbn = {978-1-897911-42-6},
year = {2012},
date = {2012-09-01},
booktitle = {Building Simulation and Optimization},
number = {September},
pages = {57--64},
address = {Loughborough, UK},
abstract = {This paper describes the calibration of a detailed whole-building energy simulation model of a naturally ventilated building to hourly measured data. This demonstrates the application of an evidence-based analytical optimisation approach described in a previous paper (Coakley et al. 2011). The methodology is applied to the following case study, naturally-ventilated library building at the National University of Ireland, Galway. The simulation model is calibrated to measured builing data for electrical energy consumption and zone temperatures. This is achieved by assigning probability distribution functions to continuous model parameters, generating simulation trials based on random sampling of these distributions and ranking solutions based on a calculated goodness-of-fit. The paper concludes with a discussion of the key findings of this study and future work.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Coakley2012d,
title = {Calibration of a Detailed Building Energy Simulation (BES) Model to Measured Data using an Analytical Optimisation Approach},
author = {Daniel Coakley and Paul Raftery and Padraig Molloy},
year = {2012},
date = {2012-01-01},
booktitle = {NUIG-UL Alliance - Engineering, Informatics & Science Research Day},
abstract = {This paper outlines a methodology for the calibration of detailed building energy simulation (BES) models using an analytical optimisation approach. The approach combines evidence-based model development with statistical Monte-Carlo based optimisation techniques. The first stages of the proposed calibration methodology are applied to a 700m2 naturally-ventilated library building using short-term monitored BMS and sensor data. The paper concludes with a discussion of how this methodology differs from existing approaches and the benefits it offers over traditional calibration techniques.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Coakley2011b,
title = {Calibration of a Detailed BES Model to Measured Data Using an Evidence-Based Analytical Optimisation Approach},
author = {Daniel Coakley and Paul Raftery and Padraig Molloy and Gearoid White},
url = {http://www.bounceinteractive.com/bs2011/bs2011/pdf/P_1222.pdf},
year = {2011},
date = {2011-11-01},
booktitle = {Proceedings of the 12th International IBPSA Conference},
address = {Sydney, Australia},
abstract = {This paper outlines a methodology for the calibration of detailed building energy simulation (BES) models using an analytical optimisation approach. The approach combines evidence-based model development with statistical Monte-Carlo based optimisation techniques. The first stages of the proposed calibration methodology are applied to a 700m2 naturally-ventilated library building using short-term monitored BMS and sensor data. The paper concludes with a discussion of how this methodology differs from existing approaches and the benefits it offers over traditional calibration techniques.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{White2011,
title = {A Systematic Methodology to Underpin the CC Process Using Calibrated BES Models},
author = {Gearoid White and Marcus M Keane and Paul Raftery and Daniel Coakley},
url = {http://repository.tamu.edu/handle/1969.1/128806},
year = {2011},
date = {2011-09-01},
booktitle = {ICEBO - International Conference for Enhanced Building Operations},
address = {New York, NY, U.S.A.},
abstract = {This paper describes a theoretical framework for utilizing whole building and reduced order calibrated BES models to underpin a systematic Continuous Commissioningtextregistered (CCtextregistered) process for building environmental optimisation and effective energy conservation. An investigation will be carried out focusing on all the stages of the CC process detailed in the CC handbook. A calibrated EnergyPlus Building Energy Simulation (BES) model will be developed initially to underpin the implementation of the CC process on a demonstrator building based in the National University of Galway (NUI Galway), Ireland. A process for reducing the calibrated EnergyPlus BES model to a reduced order Modelica based BES model that will support near real time analysis and provide functional support to the CC process during building operation is described.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Coakley2011,
title = {Calibration of a Detailed BES Model to Measured Data Using an Evidence-Based Analytical Optimisation Approach},
author = {Daniel; Coakley and Paul; Raftery and Padraig; Molloy and Gearoid; White},
url = {http://www.bounceinteractive.com/bs2011/bs2011/pdf/P_1222.pdf},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings of Building Simulation 2011: 12th Conference of International Building Performance Simulation Association},
pages = {374--381},
abstract = {This paper outlines a methodology for the calibration of detailed building energy simulation (BES) models using an analytical optimisation approach. The approach combines evidence-based model development with statistical Monte-Carlo based optimisation techniques. The first stages of the proposed calibration methodology are applied to a 700m2 naturally-ventilated library building using short-term monitored BMS and sensor data. The paper concludes with a discussion of how this methodology differs from existing approaches and the benefits it offers over traditional calibration techniques.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}