Methodologies for service lfe predic...
Brito, Jorge de.

 

  • Methodologies for service lfe prediction of buildings[electronic resource] :with a focus on facade claddings /
  • 紀錄類型: 書目-語言資料,印刷品 : Monograph/item
    杜威分類號: 620.112
    書名/作者: Methodologies for service lfe prediction of buildings : with a focus on facade claddings // by Ana Silva, Jorge de Brito, Pedro Lima Gaspar.
    作者: Silva, Ana.
    其他作者: Brito, Jorge de.
    出版者: Cham : : Springer International Publishing :, 2016.
    面頁冊數: vii, 432 p. : : ill., digital ;; 24 cm.
    Contained By: Springer eBooks
    標題: Building materials - Service life
    標題: Engineering.
    標題: Nanotechnology and Microengineering.
    標題: Building Repair and Maintenance.
    標題: Simulation and Modeling.
    標題: Mathematical Modeling and Industrial Mathematics.
    標題: Industrial Design.
    標題: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
    ISBN: 9783319332901
    ISBN: 9783319332888
    內容註: Introduction -- Service life and durability of assemblies -- Deterministic models -- Stochastic models -- Computational models -- Factorial models -- Comparative analysis of service life prediction methods -- Conclusion.
    摘要、提要註: Presenting an analysis of different approaches for predicting the service life of buildings, this monograph discusses various statistical tools and mathematical models, some of which have rarely been applied to the field. It explores methods including deterministic, factorial, stochastic and computational models and applies these to facade claddings. The models allow (i) identification of patterns of degradation, (ii) estimation of service life, (iii) analysis of loss of performance using probability functions, and (iv) estimation of service life using a probability distribution. The final chapter discusses the differences between the different methodologies and their advantages and limitations. The authors also argue that a better understanding of the service life of buildings results in more efficient building maintenance and reduced environmental costs. It not only provides an invaluable resource to students, researchers and industry professionals interested in service life prediction and sustainable construction, but is also of interest to environmental and materials scientists.
    電子資源: http://dx.doi.org/10.1007/978-3-319-33290-1
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