The modelling gap: Quantifying the discrepancy in the representation of thermal mass in building simulation

Enhanced fabric performance is fundamental to reduce the energy consumption in buildings. Research has shown that the thermal mass of the fabric can be used as a passive design strategy to reduce energy use for space conditioning. Concrete is a high density material, therefore said to have high thermal mass. Insulating concrete formwork (ICF) consists of cast in-situ concrete poured between two layers of insulation. ICF is generally perceived as a thermally lightweight construction, although previous field studies indicated that ICF shows evidence of heat storage effects. There is a need for accurate performance prediction when designing new buildings. This is challenging in particular when using advanced or new methods (such as ICF), that are not yet well researched. Building Performance Simulation (BPS) is often used to predict the thermal performance of buildings. Large discrepancies can occur in the simulation predictions provided by different BPS tools. In many cases assumptions embedded within the tools are outside of the modeller's control. At other times, users are required to make decisions on whether to rely on the default settings or to specify the input values and algorithms to be used in the simulation. This paper investigates the “modelling gap”, the impact of default settings and the implications of the various calculation algorithms on the results divergence in thermal mass simulation using different tools. ICF is compared with low and high thermal mass constructions. The results indicated that the modelling uncertainties accounted for up to 26% of the variation in the simulation predictions.

[1]  Stefano Paolo Corgnati,et al.  Thermal mass activation by hollow core slab coupled with night ventilation to reduce summer cooling loads , 2007 .

[2]  U. Magrini,et al.  The Influence of the Thermal Inertia of Building Structures On Comfort and Energy Consumption , 1981 .

[3]  Elias B. Kosmatopoulos,et al.  A roadmap towards intelligent net zero- and positive-energy buildings , 2011 .

[4]  Wahid Maref,et al.  Field energy performance of an insulating concrete form (ICF) wall , 2012 .

[5]  Richard Hyde,et al.  Quantifying useful thermal mass: how much thermal mass do you need? , 2014 .

[6]  Alan Shu Khen Kwan,et al.  An investigation into future performance and overheating risks in Passivhaus dwellings , 2013 .

[7]  Baruch Givoni,et al.  Passive cooling of buildings by natural energies , 1979 .

[8]  Lucélia Taranto Rodrigues An investigation into the use of thermal mass to improve comfort in British housing , 2010 .

[9]  Wahid Maref,et al.  Numerical simulations to predict the thermal response of insulating concrete form (ICF) wall in cold climate , 2011 .

[10]  A. Bejan,et al.  Thermal Energy Storage: Systems and Applications , 2002 .

[11]  S. A. Al-Sanea,et al.  Effect of thermal mass on performance of insulated building walls and the concept of energy savings potential , 2012 .

[12]  Gudni Jóhannesson,et al.  Accuracy of Energy Analysis of Buildings: A Comparison of a Monthly Energy Balance Method and Simulation Methods in Calculating the Energy Consumption and the Effect of Thermal Mass , 2008 .

[13]  Dandan Zhu Comparison of Building Energy Modeling Programs: Building Loads , 2014 .

[14]  Ian Beausoleil-Morrison,et al.  The adaptive coupling of heat and air flow modelling within dynamic whole-building simulation , 2000 .

[15]  R. Judkoff,et al.  International Energy Agency building energy simulation test (BESTEST) and diagnostic method , 1995 .

[16]  Melissa M. Bilec,et al.  Comparative life cycle assessment of insulating concrete forms with traditional residential wall sections , 2009, 2009 IEEE International Symposium on Sustainable Systems and Technology.

[17]  Malcolm J. Cook,et al.  Assessment of ICF energy saving potential in whole building performance simulation tools , 2015 .

[18]  Sylvain Robert,et al.  State of the art in building modelling and energy performances prediction: A review , 2013 .

[19]  A. D. Irving Validation of dynamic thermal models , 1988 .

[20]  P Pieter-Jan Hoes,et al.  The potential of lightweight low-energy houses with hybrid adaptable thermal storage: Comparing the performance of promising concepts , 2016 .

[21]  Georgios Kokogiannakis,et al.  Comparison of the simplified methods of the ISO 13790 standard and detailed modelling programs in a regulatory context , 2008 .

[22]  Zhiqiang Zhai,et al.  Advances in building simulation and computational techniques: A review between 1987 and 2014 , 2016 .

[23]  Dejan Mumovic,et al.  PERFORMANCE GAP AND THERMAL MODELLING: A COMPARISON OF SIMULATION RESULTS AND ACTUAL ENERGY PERFORMANCE FOR AN ACADEMY IN NORTH WEST ENGLAND , 2012 .

[24]  Paul Strachan,et al.  Whole model empirical validation on a full-scale building , 2016 .

[25]  Godfried Augenbroe,et al.  Analysis of uncertainty in building design evaluations and its implications , 2002 .

[26]  Malcolm J. Cook,et al.  Investigating the impact of modelling uncertainty on the simulation of insulating concrete formwork for buildings , 2016 .

[27]  Timothy Oluseun Adekunle,et al.  Thermal comfort summertime temperatures and overheating in prefabricated timber housing , 2016 .

[28]  Enedir Ghisi,et al.  Uncertainty analysis of the computer model in building performance simulation , 2014 .

[29]  Joseph Andrew Clarke,et al.  Energy Simulation in Building Design , 1985 .

[30]  Kaamran Raahemifar,et al.  Application of passive wall systems for improving the energy efficiency in buildings: A comprehensive review , 2016 .

[31]  Philip Haves,et al.  IMPACT OF MODELER DECISIONS ON SIMULATION RESULTS , 2014 .

[32]  Christina J. Hopfe,et al.  Hygrothermal implications of low and zero energy standards for building envelope performance in the UK , 2013 .

[33]  Wahid Maref,et al.  The impact of the thermal mass on field energy performance of insulating concrete form (ICF) wall in cold climate , 2011 .

[34]  Jlm Jan Hensen,et al.  Uncertainty analysis in building performance simulation for design support , 2011 .

[35]  Bje Bert Blocken,et al.  Review of external convective heat transfer coefficient models in building energy simulation programs: implementation and uncertainty , 2013 .

[36]  P Pieter-Jan Hoes,et al.  On the sensitivity to different aspects of occupant behaviour for selecting the appropriate modelling complexity in building performance predictions , 2017 .

[37]  Jacqueline Glass,et al.  Review of the Assessment of Thermal Mass in Whole Building Performance Simulation Tools , 2015, Building Simulation Conference Proceedings.

[38]  Jlm Jan Hensen,et al.  Simulation-based support for product development of innovative building envelope components , 2014 .

[39]  Xiaoxin Wang,et al.  Thermal mass in new build UK housing: A comparison of structural systems in a future weather scenario , 2012 .

[40]  P Pieter-Jan Hoes,et al.  Occupant behavior in building energy simulation: towards a fit-for-purpose modeling strategy , 2016 .

[41]  Jyotirmay Mathur,et al.  Development of mathematical correlations for indoor temperature from field observations of the performance of high thermal mass buildings in India , 2017 .

[42]  A. Hwang [Thermal comfort]. , 1990, Taehan kanho. The Korean nurse.

[43]  Alessandro Prada,et al.  On the effect of material uncertainties in envelope heat transfer simulations , 2014 .

[44]  P Pieter-Jan Hoes,et al.  Ultra-lightweight concrete: energy and comfort performance evaluation in relation to buildings with low and high thermal mass , 2017 .

[45]  Li Zhu,et al.  Detailed Energy Saving Performance Analyses on Thermal Mass Walls Demonstrated in a Zero Energy House , 2009 .

[46]  Jon Hand,et al.  CONTRASTING THE CAPABILITIES OF BUILDING ENERGY PERFORMANCE SIMULATION PROGRAMS , 2008 .

[47]  Ferenc Kalmár,et al.  Effects of thermal mass, ventilation, and glazing orientation on indoor air temperature in buildings , 2015 .

[48]  Christina J. Hopfe,et al.  Teaching building performance simulation: ever done an autopsy? , 2016 .

[49]  Luisa F. Cabeza,et al.  Thermal energy storage in building integrated thermal systems: A review. Part 2. Integration as passive system , 2016 .

[50]  Chris I. Goodier,et al.  The Role of Fabric Performance in the Seasonal Overheating of Dwellings , 2017, Building Simulation Conference Proceedings.

[51]  M. J. Holmes,et al.  Embodied and operational carbon dioxide emissions from housing: A case study on the effects of thermal mass and climate change , 2008 .

[52]  Katrin Becker,et al.  A Simulation Primer , 2009 .

[53]  Paul Strachan,et al.  Practical application of uncertainty analysis , 2001 .

[54]  Ambrose Dodoo,et al.  Effect of thermal mass on life cycle primary energy balances of a concrete- and a wood-frame building , 2012 .

[55]  Robert F. Boehm,et al.  Passive building energy savings: A review of building envelope components , 2011 .

[56]  S. J. Irving Energy program validation: conclusions of IEA Annex I , 1982 .

[57]  Aidan Reilly,et al.  The impact of thermal mass on building energy consumption , 2017 .