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Buildings Condition under Climate Change Effects

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

Deadline for manuscript submissions: closed (30 December 2022) | Viewed by 9402
Related Special Issue: Impact Assessment of Climate Change on Buildings

Special Issue Editors


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Guest Editor
RISCO, Civil Engineering Department, University of Aveiro, 3810-193 Aveiro, Portugal
Interests: energy efficiency; BIM; buildings degradation assessment; buildings conservation and maintenance
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Geology and Engineering Department, University G. d’Annunzio of Chieti-Pescara, 42-65127 Pescara, Italy
Interests: climate change; building sustainability; nZEB design; renewable energies; cultural heritage preservation; building acoustics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In December 2019, the European Commission defined the European Green Deal, establishing an ambitious set of measures for the European Union and its citizens to face the challenges brought forth by climate change and making Europe free of net emissions of greenhouse gases by 2050. Considering the impact of the built environment and particularly that of buildings, identifying an efficient way to build and renovate is an important element of the Green Deal. A bit mor recently, in October 2020, the Renovation Wave for Europe was also published, aiming at “breaking down long-standing barriers to energy and resource-efficient renovation, supporting fresh investment over a sustained period starting from public and less efficient buildings, spurring digitalisation and creating employment and growth opportunities across the renovation supply chain”. In the context of the COVID-19 pandemic, it has been further recognized that that building renovation can lead to healthier, greener buildings that are more resilient to extreme natural events.

It is our pleasure to announce that we are organizing a Special Issue entitled “Condition of Buildings under Climate Change Effects”, aimed at reporting the most recent findings from researchers and professionals of the AECO sector in the scope of the following themes.

  • Resource-efficient renovation;
  • Indoor housing health and comfort;
  • Social housing degradation and performance;
  • Degradation and durability of the built environment under the influence of climate change;
  • Climate change risks: built environment risk assessment;
  • The impact of climate change on comfort: building level;
  • The impact of climate change on comfort: city level;
  • Climate change impact on the energy efficiency of buildings;
  • Climate change impact on the durability of the built environment;
  • Durability of energy retrofit interventions;
  • Maintenance and refurbishment measures to avoid the impact of climate change;
  • BIM as a tool for built environment risk assessment;
  • HBIM in heritage renovation;
  • Sustainability with BIM methodology;
  • Approaches for the simulation of climate impacts on the built environment;
  • Case studies and other related topics.

Prof. Dr. Fernanda Rodrigues
Prof. Dr. Sergio Montelpare
Guest Editors

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Keywords

  • buildings
  • resource-efficient renovation
  • risks
  • resilience
  • durability
  • maintenance, assessment, climate change

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Published Papers (3 papers)

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Research

18 pages, 25802 KiB  
Article
Application of Deep Learning Approach for the Classification of Buildings’ Degradation State in a BIM Methodology
by Fernanda Rodrigues, Victoria Cotella, Hugo Rodrigues, Eugénio Rocha, Felipe Freitas and Raquel Matos
Appl. Sci. 2022, 12(15), 7403; https://doi.org/10.3390/app12157403 - 23 Jul 2022
Cited by 22 | Viewed by 3133
Abstract
Currently, there is extensive research focused on automatic strategies for the segmentation and classification of 3D point clouds, which can accelerate the study of a landmark and integrate it with heterogeneous data and attributes, useful to facilitate the digital management of architectural heritage [...] Read more.
Currently, there is extensive research focused on automatic strategies for the segmentation and classification of 3D point clouds, which can accelerate the study of a landmark and integrate it with heterogeneous data and attributes, useful to facilitate the digital management of architectural heritage data. In this work, an automated image-based survey has been exploited a Region- Based Convolutional Neural Network. The training phase has been executed providing examples of images with the anomalies to be detected. At the same time, a laser scanning process was conducted to obtain a point cloud, which acts as a reference for the BIM process. In a final step, a process of projecting information from the images onto the BIM recreates the pathology shapes on the model’s objects, which generates a decision support system for the built environment. The innovation of this research concerns the development of a workflow in which it is possible to automatize the recognition and classification of defects in historical buildings, to finally interpolate this geometric and numerical information with a BIM methodology, obtaining a representation and quantification of the information adapted to the facility management process. The use of innovative techniques such as artificial intelligence algorithms and different plug-ins becomes the main strength of this project. Full article
(This article belongs to the Special Issue Buildings Condition under Climate Change Effects)
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16 pages, 8288 KiB  
Article
Estimation Method of Wind-Induced Fatigue of Metal Roof Claddings under Typhoon: Numerical Analysis and Experimental Comparison
by Ying Xuan, Zhuangning Xie, Lele Zhang and Qiusheng Li
Appl. Sci. 2022, 12(13), 6785; https://doi.org/10.3390/app12136785 - 4 Jul 2022
Cited by 3 | Viewed by 2196
Abstract
Equivalent load cycle sequence (ELCS) is important basic information to know that affects the reliability of the evaluation of wind-induced fatigue on metal roof claddings. In this study, an estimation method of wind-induced fatigue of metal roof claddings is proposed. Based on the [...] Read more.
Equivalent load cycle sequence (ELCS) is important basic information to know that affects the reliability of the evaluation of wind-induced fatigue on metal roof claddings. In this study, an estimation method of wind-induced fatigue of metal roof claddings is proposed. Based on the measured wind pressure–time history data of the roof claddings on a full-scale low-rise building located along the coast of South China during a typhoon, a new ELCS (NELCS) that reflects typhoon and actual structure wind pressure characteristics in China’s coastal areas is obtained by using the rainflow counting method. The locations of fatigue hot spots of metal roof panels are analyzed by using the finite element analysis method, and the relationship between hot spot stress and wind pressure is obtained. The fatigue damage accumulation of metal roof claddings under the ELCS of a typhoon process is counted by the linear cumulative fatigue theory, commonly known as Miner’s rule. The fatigue damage accumulation of roof claddings with different purlin distances and design wind loads is analyzed using this method and then compared with the results from the dynamic loading test of an air chamber. Results show that the physical test findings are close to the numerical calculation results, which proves that the numerical calculation method has high accuracy and reliability. The comparison between NELCS in this study and the Australian standard low-high-low (LHL) sequence shows that the LHL loading sequence is conservative. Full article
(This article belongs to the Special Issue Buildings Condition under Climate Change Effects)
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11 pages, 7914 KiB  
Article
Analysis on the Exhaust Air Recirculation of the Ventilation System in Multi-Story Building
by Seonghyun Park, Hyungyu Park and Janghoo Seo
Appl. Sci. 2021, 11(10), 4441; https://doi.org/10.3390/app11104441 - 13 May 2021
Cited by 3 | Viewed by 3384
Abstract
In South Korea, the installation of a mechanical ventilation system is mandatory for the management of indoor air quality, and various studies concerning the ventilation rate and performance of the ventilation system have been conducted. However, only a few studies have been conducted [...] Read more.
In South Korea, the installation of a mechanical ventilation system is mandatory for the management of indoor air quality, and various studies concerning the ventilation rate and performance of the ventilation system have been conducted. However, only a few studies have been conducted regarding the recirculation rate of the ventilation system. If the appropriate arrangement of intake and exhaust vents in the ventilation system is not considered, the pollutants emitted from the circulation movement may be recirculated into the indoor environment and cause the degradation of the performance of the ventilation system. Therefore, this study aimed to quantitatively analyze the recirculation rate of pollutants emitted from a kindergarten building with an installed mechanical ventilation system in Seoul, South Korea, using computational fluid dynamics (CFD) analysis, and analyze the effectiveness of the guide panel installed for the prevention of the pollutants’ recirculation. The number of cases for the CFD analysis was set to a total of ten based on the ventilation rate in a mechanical ventilation system, external wind direction, and the existence of the guide panel for preventing the recirculation of exhaust air. The maximum recirculation rate of exhaust air without the installation of a guide panel was shown to be 20.0%. The maximum recirculation rate in the case where the external wind speed, direction of wind, and the ventilation rate were assumed to be identical to the other case but the guide panel for preventing the recirculation of exhaust air was assumed to be installed was 7.7%, 12.3% lower compared with the case with maximum recirculation rate. Full article
(This article belongs to the Special Issue Buildings Condition under Climate Change Effects)
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