Special Issue "Infrared Thermography Applications for Building Diagnostics"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: closed (30 June 2019).

Special Issue Editors

Dr. Eva Barreira
E-Mail Website
Guest Editor
Department of Civil Engineering, Universidade do Porto, Porto, Portugal
Interests: infrared thermography; image processing; hygrothermal performance of buildings; natural ventilation; energy efficiency; thermal comfort; indoor environmental quality
Special Issues and Collections in MDPI journals
Dr. Ricardo M. S. F. Almeida
E-Mail Website
Guest Editor
CONSTRUCT-LFC, University of Porto, Faculty of Engineering, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal and Polytechnic Institute of Viseu, School of Technology and Management, Department of Civil Engineering, Campus Politécnico de Repeses, 3504-510 Viseu, Portugal
Interests: natural ventilation and airtightness; energy efficiency; thermal comfort; indoor environmental quality; infrared thermography and in situ testing of buildings or building components; heat, air, and moisture transfer in buildings or building components; building simulation; multi-objective optimization

Special Issue Information

Dear Colleagues,

Infrared thermography (IRT) has been widely used during the past decade to evaluate the performance of buildings and building components. It has been applied both in laboratory and in situ, using passive and active approaches. The interpretation of the results was mainly qualitative at first, but quantitative analysis is now being implemented more often.

However, some issues remain a challenge for the technical and scientific community, namely, the influence of exterior parameters, test procedures to enhance the phenomena under study, the selection of the ideal method for the qualitative interpretation of the results, and the combined use of IRT and 2D/3D data acquisition techniques such as laser scanner, photogrammetry, etc.

This Special Issue aims at stimulating the exchange of ideas and knowledge on the application of IRT for buildings diagnostics. To this purpose, original contributions containing theoretical and experimental research, case studies, or a comprehensive state-of-the-art discussion are welcome for possible publication. Relevant topics to this Special Issue include, but are not limited to the following:

  • IRT for studying the energy efficiency of buildings;
  • IRT to assess the pathology of buildings and building materials;
  • IRT to detect moisture in building components;
  • IRT as a conservation evaluation tool for historic buildings;
  • IRT to assess thermal comfort;
  • Qualitative approaches vs. quantitative approaches;
  • Passive IRT vs. active IRT;
  • Combined use of IRT and 2D/3D data acquisition techniques.
Dr. Eva Barreira
Dr. Ricardo M. S. F. Almeida
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • infrared thermography
  • building diagnostics
  • qualitative approaches
  • quantitative approaches
  • passive IRT
  • active IRT

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Hygrothermal Behaviour of Continuous Air Chambers on Stone Panels Façades through CFD and IRT
Appl. Sci. 2019, 9(15), 3001; https://doi.org/10.3390/app9153001 - 26 Jul 2019
Abstract
Façades of buildings with stone cladding are widely used in contemporary architecture. This research work analyses the aerodynamic, thermal and relative humidity behaviour of this type of façade. One of the main novelties of the article is the analysis of air flow and [...] Read more.
Façades of buildings with stone cladding are widely used in contemporary architecture. This research work analyses the aerodynamic, thermal and relative humidity behaviour of this type of façade. One of the main novelties of the article is the analysis of air flow and temperature of the air chamber through finite elements with computational fluid dynamics (CFD). Ten three-dimensional models were designed to study the various parameters that influence the behaviour of the façade, including the thickness of the air chamber and the velocity of the outside air. A qualitative and quantitative analysis of temperature and humidity makes it possible to determine the areas susceptible to generating condensation. Infrared thermography (IRT) is used to obtain the actual outside temperature, which is used in the validation of finite element models. The temperature is reduced by 47% with air chambers of 3 cm instead of 1 cm with soft outside air velocity, and by up to 60% with moderate air velocity. In these cases, relative humidity increases by 96% and 74%, respectively. When the results obtained in CFD vary considerably in a particular area with respect to IRT, a possible pathology is identified. This work provides better knowledge on the durability of material and façades. Full article
(This article belongs to the Special Issue Infrared Thermography Applications for Building Diagnostics)
Show Figures

Figure 1

Open AccessArticle
Thermal Comfort-Based Personalized Models with Non-Intrusive Sensing Technique in Office Buildings
Appl. Sci. 2019, 9(9), 1768; https://doi.org/10.3390/app9091768 - 28 Apr 2019
Cited by 7
Abstract
Heating, ventilation and air-conditioning (HVAC) systems play a key role in shaping the built environment. However, centralized HVAC systems cannot guarantee the provision of a comfortable thermal environment for everyone. Therefore, a personalized HVAC system that aims to adapt thermal preferences has drawn [...] Read more.
Heating, ventilation and air-conditioning (HVAC) systems play a key role in shaping the built environment. However, centralized HVAC systems cannot guarantee the provision of a comfortable thermal environment for everyone. Therefore, a personalized HVAC system that aims to adapt thermal preferences has drawn much more attention. Meanwhile, occupant-related factors like skin temperature have not had standardized measurement methods. Therefore, this paper proposes to use infrared thermography to develop individual thermal models to predict thermal sensations using three different feature sets with the random forest (RF) and support vector machine (SVM). The results have shown the correlation coefficients between clothing surface temperature and thermal sensation are 11% and 3% higher than those between skin temperature and thermal sensation of two subjects, respectively. With cross-validation, SVM with a linear kernel and penalty number of 1, as well as RF with 50 trees and the maximum tree depth of 3 were selected as the model configurations. As a result, the model trained with the feature set, consisting of indoor air temperature, relative humidity, skin temperature and clothing surface temperature, and with linear kernel SVM has achieved 100% recall score on test data of female subjects and 95% recall score on that of male subjects. Full article
(This article belongs to the Special Issue Infrared Thermography Applications for Building Diagnostics)
Show Figures

Figure 1

Back to TopTop