Bienvenido-Huertas / Moyano-Campos New Technologies in Building and Construction
1. Auflage 2022
ISBN: 978-981-19-1894-0
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
Towards Sustainable Development
E-Book, Englisch, 439 Seiten
Reihe: Lecture Notes in Civil Engineering
ISBN: 978-981-19-1894-0
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book presents contributions on new technologies in building and construction. Buildings are complex elements that impact environment significantly. The sustainability of this sector requires a holistic and multidisciplinary approach that allows adequate strategies to be established to reduce its environmental impact. This heterogeneity is represented in these chapters, which have been developed by researchers from different countries. The book is divided into three sections: (i) analysis, (ii) design and modeling, and (iii) solutions. The book chapters together represent an advance in current knowledge about new technologies in building and construction, crucial for researchers, engineers, architects, policy makers, and stakeholders.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Weitere Infos & Material
Application of qualitative and quantitative infrared thermography at urban level: potential and limitations.- Temperature based approach for in-situ evaluation of thermal transmittance of building walls.- Combining characterization tests of building envelope thermal transmittance with the acoustic characterization through data mining approaches.- Methodology for the evaluation of an energetic model of thermal transmittance in a window by means of horizontal aggregation (HA) from short-range photogrammetry for model Digital Twin.- Comparative analysis of the influence of the convective term in the quantitative assessment by infrared thermography.- In situ methodology to assess the action of water-wind on building windows.- Outdoor microclimate influence on building performance: simulation tools, challenges, and opportunities.- Identifying and describing energy-poor household groups. A comparison between two different methods: conventional statistical characterization and artificial intelligence driven clusterization.