IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v211y2018icp854-864.html
   My bibliography  Save this article

A model for the improvement of thermal bridges quantitative assessment by infrared thermography

Author

Listed:
  • Baldinelli, Giorgio
  • Bianchi, Francesco
  • Rotili, Antonella
  • Costarelli, Danilo
  • Seracini, Marco
  • Vinti, Gianluca
  • Asdrubali, Francesco
  • Evangelisti, Luca

Abstract

The intervention on the existing building envelope thermal insulation is the main and effective solution in order to achieve a significant reduction of the building stock energy needs. The infrared technique is the methodology of the energy diagnosis aimed to identify qualitatively the principal causes of energy losses: the presence of thermal bridges. Those weak parts of the building envelope in terms of heat transfer result not easy to treat with an energy efficiency intervention, while they are gaining importance in the buildings total energy dispersion, as the level of insulation of opaque and transparent materials is continuously increasing. It is generally possible to evaluate the energy dispersions through these zones with a deep knowledge of the materials and the geometry using a numerical method. Besides, authors proposed in the past a methodology to assess the flux passing through thermal bridges with an infrared image correctly framed. The analysis of surface temperatures of the undisturbed wall and of the zone with thermal bridge, allows to define the Incidence Factor of the thermal Bridge (Itb). This parameter is strongly affected by the thermographic image accuracy, therefore, this paper deals with the development and validation of an innovative mathematical algorithm to enhance the image resolution and the consequent accuracy of the energy losses assessment. An experimental campaign in a controlled environment (hot box apparatus) has been conducted on three typologies of thermal bridge, firstly performing the thermographic survey and then applying the enhancement algorithm to the infrared images in order to compare the Itb and the linear thermal transmittance ψ values. Results showed that the proposed methodology could bring to an accuracy improvement up to 2% of the total buildings envelope energy losses evaluated by quantitative infrared thermography. Moreover, the proposed algorithm allows the implementation of a further process applicable to the images, in order to extract the physical boundaries of the hidden materials causing the thermal bridge, so revealing itself as a useful tool to identify exactly the suitable points of intervention for the thermal bridge correction. The application of the imaging process on the quantitative infrared thermography is an innovative approach that makes more accurate the evaluation of the actual heat loss of highly insulating buildings and reaching a higher detail on the detection and treating of thermal bridges.

Suggested Citation

  • Baldinelli, Giorgio & Bianchi, Francesco & Rotili, Antonella & Costarelli, Danilo & Seracini, Marco & Vinti, Gianluca & Asdrubali, Francesco & Evangelisti, Luca, 2018. "A model for the improvement of thermal bridges quantitative assessment by infrared thermography," Applied Energy, Elsevier, vol. 211(C), pages 854-864.
  • Handle: RePEc:eee:appene:v:211:y:2018:i:c:p:854-864
    DOI: 10.1016/j.apenergy.2017.11.091
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917316926
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2017.11.091?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ohlsson, K.E.A. & Olofsson, T., 2014. "Quantitative infrared thermography imaging of the density of heat flow rate through a building element surface," Applied Energy, Elsevier, vol. 134(C), pages 499-505.
    2. Fox, Matthew & Coley, David & Goodhew, Steve & de Wilde, Pieter, 2014. "Thermography methodologies for detecting energy related building defects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 296-310.
    3. Asdrubali, Francesco & Baldinelli, Giorgio & Bianchi, Francesco, 2012. "A quantitative methodology to evaluate thermal bridges in buildings," Applied Energy, Elsevier, vol. 97(C), pages 365-373.
    4. Albatici, Rossano & Tonelli, Arnaldo M. & Chiogna, Michela, 2015. "A comprehensive experimental approach for the validation of quantitative infrared thermography in the evaluation of building thermal transmittance," Applied Energy, Elsevier, vol. 141(C), pages 218-228.
    5. Fokaides, Paris A. & Kalogirou, Soteris A., 2011. "Application of infrared thermography for the determination of the overall heat transfer coefficient (U-Value) in building envelopes," Applied Energy, Elsevier, vol. 88(12), pages 4358-4365.
    6. Kylili, Angeliki & Fokaides, Paris A. & Christou, Petros & Kalogirou, Soteris A., 2014. "Infrared thermography (IRT) applications for building diagnostics: A review," Applied Energy, Elsevier, vol. 134(C), pages 531-549.
    7. Hong, Tianzhen & Piette, Mary Ann & Chen, Yixing & Lee, Sang Hoon & Taylor-Lange, Sarah C. & Zhang, Rongpeng & Sun, Kaiyu & Price, Phillip, 2015. "Commercial Building Energy Saver: An energy retrofit analysis toolkit," Applied Energy, Elsevier, vol. 159(C), pages 298-309.
    8. Khayatian, Fazel & Sarto, Luca & Dall'O', Giuliano, 2017. "Building energy retrofit index for policy making and decision support at regional and national scales," Applied Energy, Elsevier, vol. 206(C), pages 1062-1075.
    9. Lehmann, B. & Ghazi Wakili, K. & Frank, Th. & Vera Collado, B. & Tanner, Ch., 2013. "Effects of individual climatic parameters on the infrared thermography of buildings," Applied Energy, Elsevier, vol. 110(C), pages 29-43.
    10. Francesco Bianchi & Anna Laura Pisello & Giorgio Baldinelli & Francesco Asdrubali, 2014. "Infrared Thermography Assessment of Thermal Bridges in Building Envelope: Experimental Validation in a Test Room Setup," Sustainability, MDPI, vol. 6(10), pages 1-14, October.
    11. Capozzoli, Alfonso & Gorrino, Alice & Corrado, Vincenzo, 2013. "A building thermal bridges sensitivity analysis," Applied Energy, Elsevier, vol. 107(C), pages 229-243.
    12. Baldinelli, G. & Bianchi, F., 2014. "Windows thermal resistance: Infrared thermography aided comparative analysis among finite volumes simulations and experimental methods," Applied Energy, Elsevier, vol. 136(C), pages 250-258.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mingqian Guo & Yue Wu & Xinran Miao, 2023. "Thermal Bridges Monitoring and Energy Optimization of Rural Residences in China’s Cold Regions," Sustainability, MDPI, vol. 15(14), pages 1-25, July.
    2. Costarelli, Danilo & Seracini, Marco & Vinti, Gianluca, 2020. "A comparison between the sampling Kantorovich algorithm for digital image processing with some interpolation and quasi-interpolation methods," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    3. Tiziana Basiricò & Antonio Cottone & Daniele Enea, 2020. "Analytical Mathematical Modeling of the Thermal Bridge between Reinforced Concrete Wall and Inter-Floor Slab," Sustainability, MDPI, vol. 12(23), pages 1-21, November.
    4. Martin, Miguel & Chong, Adrian & Biljecki, Filip & Miller, Clayton, 2022. "Infrared thermography in the built environment: A multi-scale review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    5. Danilo Costarelli & Michele Piconi & Gianluca Vinti, 2023. "On the convergence properties of sampling Durrmeyer‐type operators in Orlicz spaces," Mathematische Nachrichten, Wiley Blackwell, vol. 296(2), pages 588-609, February.
    6. Cagini, C. & Costarelli, D. & Gujar, R. & Lupidi, M. & Lutty, G.A. & Seracini, M. & Vinti, G., 2022. "Improvement of retinal OCT angiograms by Sampling Kantorovich algorithm in the assessment of retinal and choroidal perfusion," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    7. Ioannis Atsonios & Ioannis Mandilaras & Maria Founti, 2019. "Thermal Assessment of a Novel Drywall System Insulated with VIPs," Energies, MDPI, vol. 12(12), pages 1-18, June.
    8. Theodosiou, Theodoros & Tsikaloudaki, Katerina & Kontoleon, Karolos & Giarma, Christina, 2021. "Assessing the accuracy of predictive thermal bridge heat flow methodologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    9. Garrido, I. & Lagüela, S. & Otero, R. & Arias, P., 2020. "Thermographic methodologies used in infrastructure inspection: A review—Post-processing procedures," Applied Energy, Elsevier, vol. 266(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lucchi, Elena, 2018. "Applications of the infrared thermography in the energy audit of buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3077-3090.
    2. Martin, Miguel & Chong, Adrian & Biljecki, Filip & Miller, Clayton, 2022. "Infrared thermography in the built environment: A multi-scale review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    3. O'Grady, Małgorzata & Lechowska, Agnieszka A. & Harte, Annette M., 2017. "Quantification of heat losses through building envelope thermal bridges influenced by wind velocity using the outdoor infrared thermography technique," Applied Energy, Elsevier, vol. 208(C), pages 1038-1052.
    4. Bienvenido-Huertas, David & Moyano, Juan & Marín, David & Fresco-Contreras, Rafael, 2019. "Review of in situ methods for assessing the thermal transmittance of walls," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 356-371.
    5. Fokaides, Paris A. & Jurelionis, Andrius & Gagyte, Laura & Kalogirou, Soteris A., 2016. "Mock target IR thermography for indoor air temperature measurement," Applied Energy, Elsevier, vol. 164(C), pages 676-685.
    6. Akkurt, G.G. & Aste, N. & Borderon, J. & Buda, A. & Calzolari, M. & Chung, D. & Costanzo, V. & Del Pero, C. & Evola, G. & Huerto-Cardenas, H.E. & Leonforte, F. & Lo Faro, A. & Lucchi, E. & Marletta, L, 2020. "Dynamic thermal and hygrometric simulation of historical buildings: Critical factors and possible solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    7. Aïssani, A. & Chateauneuf, A. & Fontaine, J.-P. & Audebert, Ph., 2016. "Quantification of workmanship insulation defects and their impact on the thermal performance of building facades," Applied Energy, Elsevier, vol. 165(C), pages 272-284.
    8. Kylili, Angeliki & Fokaides, Paris A. & Christou, Petros & Kalogirou, Soteris A., 2014. "Infrared thermography (IRT) applications for building diagnostics: A review," Applied Energy, Elsevier, vol. 134(C), pages 531-549.
    9. Blanca Tejedor & Eva Barreira & Vasco Peixoto de Freitas & Tomasz Kisilewicz & Katarzyna Nowak-Dzieszko & Umberto Berardi, 2020. "Impact of Stationary and Dynamic Conditions on the U-Value Measurements of Heavy-Multi Leaf Walls by Quantitative IRT," Energies, MDPI, vol. 13(24), pages 1-19, December.
    10. Doo Sung Choi & Myeong Jin Ko, 2017. "Comparison of Various Analysis Methods Based on Heat Flowmeters and Infrared Thermography Measurements for the Evaluation of the In Situ Thermal Transmittance of Opaque Exterior Walls," Energies, MDPI, vol. 10(7), pages 1-22, July.
    11. Bienvenido-Huertas, David & Moyano, Juan & Rodríguez-Jiménez, Carlos E. & Marín, David, 2019. "Applying an artificial neural network to assess thermal transmittance in walls by means of the thermometric method," Applied Energy, Elsevier, vol. 233, pages 1-14.
    12. David Bienvenido-Huertas & Juan Antonio Fernández Quiñones & Juan Moyano & Carlos E. Rodríguez-Jiménez, 2018. "Patents Analysis of Thermal Bridges in Slab Fronts and Their Effect on Energy Demand," Energies, MDPI, vol. 11(9), pages 1-18, August.
    13. Albatici, Rossano & Tonelli, Arnaldo M. & Chiogna, Michela, 2015. "A comprehensive experimental approach for the validation of quantitative infrared thermography in the evaluation of building thermal transmittance," Applied Energy, Elsevier, vol. 141(C), pages 218-228.
    14. Baldinelli, G. & Bianchi, F., 2014. "Windows thermal resistance: Infrared thermography aided comparative analysis among finite volumes simulations and experimental methods," Applied Energy, Elsevier, vol. 136(C), pages 250-258.
    15. Flores Larsen, Silvana & Hongn, Marcos, 2014. "Determining the infrared reflectance of specular surfaces by using thermographic analysis," Renewable Energy, Elsevier, vol. 64(C), pages 306-313.
    16. Carlos Morón & Pablo Saiz & Daniel Ferrández & Rubén Felices, 2018. "Comparative Analysis of Infrared Thermography and CFD Modelling for Assessing the Thermal Performance of Buildings," Energies, MDPI, vol. 11(3), pages 1-19, March.
    17. Iole Nardi & Elena Lucchi, 2023. "In Situ Thermal Transmittance Assessment of the Building Envelope: Practical Advice and Outlooks for Standard and Innovative Procedures," Energies, MDPI, vol. 16(8), pages 1-31, April.
    18. Luca Evangelisti & Leone Barbaro & Claudia Guattari & Edoardo De Cristo & Roberto De Lieto Vollaro & Francesco Asdrubali, 2024. "Comparison between Direct and Indirect Heat Flux Measurement Techniques: Preliminary Laboratory Tests," Energies, MDPI, vol. 17(12), pages 1-16, June.
    19. López-Ochoa, Luis M. & Las-Heras-Casas, Jesús & López-González, Luis M. & Olasolo-Alonso, Pablo, 2019. "Towards nearly zero-energy buildings in Mediterranean countries: Energy Performance of Buildings Directive evolution and the energy rehabilitation challenge in the Spanish residential sector," Energy, Elsevier, vol. 176(C), pages 335-352.
    20. Rasooli, Arash & Itard, Laure, 2019. "In-situ rapid determination of walls’ thermal conductivity, volumetric heat capacity, and thermal resistance, using response factors," Applied Energy, Elsevier, vol. 253(C), pages 1-1.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:211:y:2018:i:c:p:854-864. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.