Influence of heating systems on thermal transmittance evaluations: Simulations, experimental measurements and data post-processing

Abstract Nowadays, understanding the actual performance of building components is one of the key factor to achieve energy savings. For this reason, on-site measurements are essential but the boundary conditions during surveys can affect the final results. This can occur during heat flow meter measurements, when the thermal transmittance value of a wall can be influenced by disturbing factors, such as the heating system power-on and off. Due to this, the aim of this study is to investigate the influence of these disturbing factors, moving away from steady-state conditions. This research is divided in two main steps: a first critical analysis of data obtained by in-situ measurements and an investigation of how the mentioned disturbing factors can affect the final results, employing a FEM code, where stationary conditions are not respected; a second analysis related to the data post-processing procedures, proposing a new supplementary approach able to exclude heat flow distortions and able to obtain measured U-values closer to the calculated ones, according to ISO 6946. Starting from simulations and on-site measurements, the proposed method was preliminary validated, analyzing actual case studies characterized by heating systems with radiators and obtaining preliminary satisfying results. The simulations allowed to assess a reduction in the difference between the measured and the calculated U-value that goes from +22.1% to +0.7%. Post processing of experimental data with the proposed methodology allowed to significantly reduce the difference between measured and calculated U-values (from +36.9% to −7.6% in the best case study). Starting from the preliminary results, the proposed approach seems to be promising with U-value corrections in accordance with the theoretical ones.

[1]  Yacine Rezgui,et al.  A novel concept to measure envelope thermal transmittance and air infiltration using a combined simulation and experimental approach , 2017 .

[2]  Hua Ge,et al.  Effect of dynamic modeling of thermal bridges on the energy performance of residential buildings with high thermal mass for cold climates , 2017 .

[3]  Hans Bloem,et al.  Energy Performance Assessment of Buildings and Building Components. Guidelines for Data Analysis from Dynamic Experimental Campaigns Part 1: Physical Aspects☆ , 2015 .

[4]  Daniel Feuermann Measurement of envelope thermal transmittances in multifamily buildings , 1989 .

[5]  G. M. Stavrakakis,et al.  Experimental and numerical assessment of cool-roof impact on thermal and energy performance of a school building in Greece , 2016 .

[6]  Yang Wang,et al.  Evaluation on energy performance in a low-energy building using new energy conservation index based on monitoring measurement system with sensor network , 2016 .

[7]  Luai M. Al-Hadhrami,et al.  In situ measurement of thermal transmittance and thermal resistance of hollow reinforced precast concrete walls , 2014 .

[8]  Elena Lucchi,et al.  Thermal transmittance of historical stone masonries: A comparison among standard, calculated and measured data , 2017 .

[9]  Dario Ambrosini,et al.  U-value assessment by infrared thermography: A comparison of different calculation methods in a Guarded Hot Box , 2016 .

[10]  Annette M. Harte,et al.  Infrared thermography technique as an in-situ method of assessing heat loss through thermal bridging , 2017 .

[11]  Giorgio Baldinelli,et al.  Evaluating in situ thermal transmittance of green buildings masonries—A case study , 2014 .

[12]  F. Asdrubali,et al.  Experimental investigation of the influence of convective and radiative heat transfers on thermal transmittance measurements , 2016 .

[13]  Marta Gangolells,et al.  A comparison of standardized calculation methods for in situ measurements of facades U-value , 2016 .

[14]  Changhai Peng,et al.  In situ measuring and evaluating the thermal resistance of building construction , 2008 .

[15]  Giorgio Baldinelli,et al.  A quantitative methodology to evaluate thermal bridges in buildings , 2012 .

[16]  J. Balado,et al.  Thermal-based analysis for the automatic detection and characterization of thermal bridges in buildings , 2018 .

[17]  Fabrizio Ascione,et al.  Historical buildings: Multidisciplinary approach to structural/energy diagnosis and performance assessment☆ , 2017 .

[18]  Roberto Ricciu,et al.  Comparing different approaches to in situ measurement of building components thermal resistance , 2011 .

[19]  Marijke Steeman,et al.  Assessing the thermal performance of insulating glass units with infrared thermography: Potential and limitations , 2017 .

[20]  Roberto Martinez,et al.  Full scale experimental performance assessment of a prefabricated timber panel for the energy retrofitting of multi-rise buildings , 2017 .

[21]  Luca Evangelisti,et al.  Influence of internal heat sources on thermal resistance evaluation through the heat flow meter method , 2017 .

[22]  Elvira Ianniello,et al.  U-value in situ measurement for energy diagnosis of existing buildings , 2015 .