The Relative Influence of Environmental Factors Compared to Age on Building Element DegradationSource: Journal of Performance of Constructed Facilities:;2023:;Volume ( 037 ):;issue: 006::page 04023053-1DOI: 10.1061/JPCFEV.CFENG-4521Publisher: ASCE
Abstract: Age has often been the only factor considered in predictive models of degradation. This study, however, assesses the influence on degradation of coastal exposure for concrete beams, level of utilization for rendered cement floors, and rainfall for timber windows. First, the difference between random data and data categorized on the basis of high or low levels of environmental factors was explored to establish whether they had a perceptible influence on degradation. Next, five types of models were explored for fitting the data and making predictions: namely Markov chain, multiple linear regression, simple neural network, deep neural network, and random forest. Among the environmental factors, coastal exposure on concrete beams had the greatest influence, while rainfall on timber windows the least. Random forest modeling was the most accurate and was also explored using the local interpretable model-agnostic explanation (LIME) technique, which revealed that the environmental factor effects were more evident during the mid-life of elements rather than at the early or late stages. Including environmental factors in degradation models in addition to element age will increase their accuracy and portability.
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contributor author | Vajira Wickramasinghe | |
contributor author | W. P. S. Dias | |
contributor author | Dilan Robert | |
contributor author | Sujeeva Setunge | |
date accessioned | 2024-04-27T20:53:52Z | |
date available | 2024-04-27T20:53:52Z | |
date issued | 2023/12/01 | |
identifier other | 10.1061-JPCFEV.CFENG-4521.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4296195 | |
description abstract | Age has often been the only factor considered in predictive models of degradation. This study, however, assesses the influence on degradation of coastal exposure for concrete beams, level of utilization for rendered cement floors, and rainfall for timber windows. First, the difference between random data and data categorized on the basis of high or low levels of environmental factors was explored to establish whether they had a perceptible influence on degradation. Next, five types of models were explored for fitting the data and making predictions: namely Markov chain, multiple linear regression, simple neural network, deep neural network, and random forest. Among the environmental factors, coastal exposure on concrete beams had the greatest influence, while rainfall on timber windows the least. Random forest modeling was the most accurate and was also explored using the local interpretable model-agnostic explanation (LIME) technique, which revealed that the environmental factor effects were more evident during the mid-life of elements rather than at the early or late stages. Including environmental factors in degradation models in addition to element age will increase their accuracy and portability. | |
publisher | ASCE | |
title | The Relative Influence of Environmental Factors Compared to Age on Building Element Degradation | |
type | Journal Article | |
journal volume | 37 | |
journal issue | 6 | |
journal title | Journal of Performance of Constructed Facilities | |
identifier doi | 10.1061/JPCFEV.CFENG-4521 | |
journal fristpage | 04023053-1 | |
journal lastpage | 04023053-10 | |
page | 10 | |
tree | Journal of Performance of Constructed Facilities:;2023:;Volume ( 037 ):;issue: 006 | |
contenttype | Fulltext |