This book is about the optimization of the characterization of the thermal properties of building envelopes, through experimental tests and the use of artificial intelligence. It analyses periodic and stationary thermal properties using measurement approaches based on the heat flow meter method and the thermometric method. These measurements are then analysed using advanced artificial intelligence algorithms.
The book is structured in four parts, beginning with a discussion of the importance of thermal properties in the energy performance of buildings. Secondly, theoretical and experimental methods for characterizing thermal properties are analysed. Then, the methodology is developed, and the characteristics and properties of the algorithms used are explored. Finally, the results obtained with the algorithms are analysed and the most appropriate approaches are determined.
This book is of interest to researchers, civil and industrial engineers, energy auditors and architects, by providing a resource which improves energy audit tasks in existing buildings.
Presents an artificial intelligence based approach to characterise thermal properties of building envelopes
Explains the importance of thermal properties in the energy performance of buildings
Analyses several methods and algorithms to ensure the optimal approach is presented
Dr David Bienvenido-Huertas is a researcher in the Building Construction II Department at Universidad de Sevilla, Spain. He is an active member of the Research Group TEP970: Technological Innovation, 3d Modeling Systems and Energy Diagnosis in Heritage and Building at the Universidad de Sevilla, and is a visiting professor at both the University of Seville and the University of La Coruña. His area of expertise covers climate change in the building sector, adaptive thermal comfort, heat transfer, fuel poverty, energy conservation measures, and design of nearly zero energy buildings. He is an author of more than 30 papers and frequently a reviewer of international peer reviewed journals.
Professor Carlos Rubio-Bellido is a professor in the Department of Building Construction II at the University of Seville. His research is focused on energy efficiency in the building sector as well as building performance simulation. He is a visiting professor at the Bío-Bío University (Chile) and at Shiga Prefecture University (Japan). He is a member of the International Scientific Committee of various International Conferences supported by Wessex Institute of Technology. He is a recognized reviewer of various international indexed journals and international research projects.
Chapter 1 : The influence of the envelope thermal properties on building energy performance
Chapter 2 : Methods to assess the thermal properties of the building envelope
Chapter 3 : Methodological framework of artificial intelligence algorithms and generation of the dataset
Chapter 4 : Estimation of stationary thermal properties with artificial intelligence
Chapter 5 : Estimating periodic thermal properties with artificial intelligence
Chapter 6 : Analysing with artificial intelligence other approaches to experimental thermal characterization in existing buildings