This book is structured in four parts: First, it analyzes the sustainability objectives established for the building stock and the importance of thermal comfort in this aspect. Second, the existing adaptive thermal comfort models and the main energy-saving measures associated with these models are analyzed. Third, the energy savings obtained with these measures are analyzed in several case studies, comparing the results obtained with other energy conservation measures, such as the improvement of the façade. The analysis is carried out from an energy and economic perspective. Finally, a decision‐making process based on fuzzy logic is established. As an expected result, the content of the book contributes to assist architects in designing more efficient buildings from the perspective of user behavior.
This book explains how energy demand and energy consumption in new buildings can be predicted and how these aspects and the resulting CO2 emissions can be reduced. It is based upon the authors’ extensive research into the design and energy optimization of office buildings in Chile. The authors first introduce a calculation procedure that can be used for the optimization of energy parameters in office buildings, and to predict how a changing climate may affect energy demand. The prediction of energy demand, consumption and CO2 emissions is demonstrated by solving simple equations using the example of Chilean buildings, and the findings are subsequently applied to buildings around the globe. An optimization process based on Artificial Neural Networks is discussed in detail, which predicts heating and cooling energy demands, energy consumption and CO2 emissions. Taken together, these processes will show readers how to reduce energy demand, consumption and CO2 emissions associated with office buildings in the future. Readers will gain an advanced understanding of energy use in buildings and how it can be reduced.
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.
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