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Atmaca, N (2017) Life-cycle assessment of post-disaster temporary housing. Building Research & Information, 45(05), 524-38.

Buswell, R, Webb, L, Mitchell, V and Leder Mackley, K (2017) Multidisciplinary research: Should effort be the measure of success?. Building Research & Information, 45(05), 539-55.

Dixit, M K (2017) Embodied energy and cost of building materials: Correlation analysis. Building Research & Information, 45(05), 508-23.

  • Type: Journal Article
  • Keywords: building materials; life cycle cost; input-output analysis; life cycle assessment; life cycle energy; embodied energy; design; carbon; paper; model; life-cycle energy; residential buildings; construction & building technology; construction materials;
  • ISBN/ISSN: 0961-3218
  • URL: https://doi.org/10.1080/09613218.2016.1191760
  • Abstract:
    The US building sector consumes 48% of the nation's annual energy as operating and embodied energy. Calculating embodied energy is difficult, complex and more resource-consuming than calculating operating energy due to a lack of complete, accurate and specific embodied energy data. One commonly used method to calculate embodied energy is input-output-based (IO) analysis, which utilizes economic data. The use of economic data indicates some relationship between embodied energy and cost. Some studies have investigated whether the embodied energy of a building can be predicted from its cost. These studies analyzed the relationship of the cost and embodied energy of a building and found a strong, positive correlation. However, when analyzed at the material level, the correlation weakened. This paper develops an improved input-output-based hybrid (IOH) model to calculate the complete, accurate and material-specific embodied energy of 21 commonly used building materials. After calculating and evaluating the embodied energy, the correlation of the embodied energy and cost of materials was analyzed. The results demonstrate a very strong and positive correlation between embodied energy and cost. In conclusion, more research may be required to predict embodied energy from cost data.;The US building sector consumes 48% of the nation's annual energy as operating and embodied energy. Calculating embodied energy is difficult, complex and more resource-consuming than calculating operating energy due to a lack of complete, accurate and specific embodied energy data. One commonly used method to calculate embodied energy is input-output-based (IO) analysis, which utilizes economic data. The use of economic data indicates some relationship between embodied energy and cost. Some studies have investigated whether the embodied energy of a building can be predicted from its cost. These studies analyzed the relationship of the cost and embodied energy of a building and found a strong, positive correlation. However, when analyzed at the material level, the correlation weakened. This paper develops an improved input-output-based hybrid (IOH) model to calculate the complete, accurate and material-specific embodied energy of 21 commonly used building materials. After calculating and evaluating the embodied energy, the correlation of the embodied energy and cost of materials was analyzed. The results demonstrate a very strong and positive correlation between embodied energy and cost. In conclusion, more research may be required to predict embodied energy from cost data.;The US building sector consumes 48% of the nation's annual energy as operating and embodied energy. Calculating embodied energy is difficult, complex and more resource-consuming than calculating operating energy due to a lack of complete, accurate and specific embodied energy data. One commonly used method to calculate embodied energy is input-output-based (IO) analysis, which utilizes economic data. The use of economic data indicates some relationship between embodied energy and cost. Some studies have investigated whether the embodied energy of a building can be predicted from its cost. These studies analyzed the relationship of the cost and embodied energy of a building and found a strong, positive correlation. However, when analyzed at the material level, the correlation weakened. This paper develops an improved input-output-based hybrid (IOH) model to calculate the complete, accurate and material-specific embodied energy of 21 commonly used building materials. After calculating and evaluating the embodied energy, the correlation of the embodied energy and cost of materials was analyzed. The results demonstrate a very strong and positive correlation between embodied energy and cost. In conclusion, more research may be required to predict embodied energy from cost data.;

Domínguez-Hernández, J, Pérez-Bella, J M, Alonso-Martínez, M, Cano-Suñén, E and del Coz-Díaz, J J (2017) Assessment of water penetration risk in building facades throughout Brazil. Building Research & Information, 45(05), 492-507.

Rockett, P and Hathway, E A (2017) Model-predictive control for non-domestic buildings: A critical review and prospects. Building Research & Information, 45(05), 556-71.

Saratsis, E, Dogan, T and Reinhart, C F (2017) Simulation-based daylighting analysis procedure for developing urban zoning rules. Building Research & Information, 45(05), 478-91.

Schweiker, M, Fuchs, X, Becker, S, Shukuya, M, Dovjak, M, Hawighorst, M and Kolarik, J (2017) Challenging the assumptions for thermal sensation scales. Building Research & Information, 45(05), 572-89.