The impact of accurately modelling corridor thermodynamics in the overheating risk assessment of multi-residential dwellings

Abstract Prolonged overheating can have serious cumulative effects on human health, resulting in heat exhaustion, heatstroke and even death. The frequency and severity of heatwaves will increase considerably in the future as a result of accelerating climatic changes compounded by increasing urbanisation. A recent overheating risk-assessment methodology, Technical Memorandum (TM)59: 2017 was developed by the Chartered Institution of Building Services Engineers (CIBSE) to address this problem, by providing a consistent framework for the evaluation of overheating risks in new homes. TM59 has for the first time highlighted the importance of including corridor heat transfer effects in the dynamic modelling of multi-residential dwellings. This paper investigates the strengths and limitations of current approaches to the modelling of corridors, based on a case study of three energy-efficient flats located in London. The results of modelling in accordance with TM59 guidance are compared with alternative approaches, using more realistic occupancy and weather information, and compared to empirically measured data. The findings of this study indicate that current practices in Building Performance Simulation (BPS) are likely to under-estimate the actual air temperatures in corridors. This study highlights the need for further research into the way in which corridors, flats and their interconnecting ventilation and heat transfer networks are commonly discretised in BPS models.

[1]  Kevin J. Lomas,et al.  Overheating in buildings: lessons from research , 2017 .

[2]  Phillip Biddulph,et al.  Mapping indoor overheating and air pollution risk modification across Great Britain: A modelling study , 2016 .

[3]  Robert S. McLeod,et al.  Forecasting indoor temperatures during heatwaves using time series models , 2018, Building and Environment.

[4]  Robert S. McLeod,et al.  Can semi-parametric additive models outperform linear models, when forecasting indoor temperatures in free-running buildings? , 2019, Energy and Buildings.

[5]  K. Lomas.  The U.K. applicability study: an evaluation of thermal simulation programs for passive solar house design , 1996 .

[6]  Christina J. Hopfe,et al.  The Passivhaus Designer’s Manual : A technical guide to low and zero energy buildings , 2015 .

[7]  Chris I. Goodier,et al.  Assessing the application and limitations of a standardised overheating risk-assessment methodology in a real-world context , 2020 .

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

[9]  Michael J. Davies,et al.  Can the choice of building performance simulation tool significantly alter the level of predicted indoor overheating risk in London flats? , 2018, Building Services Engineering Research and Technology.

[10]  K. Lomas,et al.  A new empirical model incorporating spatial interpolation of meteorological data for the prediction of overheating risks in UK dwellings , 2017 .

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

[12]  Zaid Chalabi,et al.  The impact of occupancy patterns, occupant-controlled ventilation and shading on indoor overheating risk in domestic environments , 2014 .

[13]  Manuel Herrera,et al.  Mitigation versus adaptation: Does insulating dwellings increase overheating risk? , 2018, Building and Environment.

[14]  Zaid Chalabi,et al.  Overheating in English dwellings: comparing modelled and monitored large-scale datasets , 2017 .

[15]  P. Symonds,et al.  Inhabitant actions and summer overheating risk in London dwellings , 2017 .

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

[17]  Jacqueline Glass,et al.  The modelling gap: Quantifying the discrepancy in the representation of thermal mass in building simulation , 2018 .

[18]  J. Mardaljevic,et al.  Balancing daylight and overheating in low-energy design using CIBSE improved weather files , 2020, Building Services Engineering Research and Technology.

[19]  Lukas H. Meyer,et al.  Summary for policymakers , 2007 .

[20]  C. Goodier,et al.  The importance of infiltration pathways in assessing and modelling overheating risks in multi-residential buildings , 2020 .

[21]  Chris I. Goodier,et al.  Heat wave adaptations for UK dwellings and development of a retrofit toolkit , 2013 .

[22]  Robert S. McLeod,et al.  Chronic overheating in low carbon urban developments in a temperate climate , 2017 .

[23]  Robert S. McLeod,et al.  A high-resolution indoor heat-health warning system for dwellings , 2020 .

[24]  Sandhya Patidar,et al.  Methods for assessing domestic overheating for future building regulation compliance , 2013 .

[25]  Yacine Rezgui,et al.  A proposed method for generating high resolution current and future climate data for Passivhaus design , 2012 .