A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Sensitivity Analyses for Selected Pavement Distresses
One of the Long-Term Pavement Performance (LTPP) objectives is to determine the effects of (1) loading, (2) environment, (3) material properties and variability, (4) construction quality, and (5) maintenance levels on pavement distress and performance. This volume reports the results of early sensitivity analyses on the National Information Management System to determine the effects of loading, pavement structure, environment, and material properties on pavement performance. In order to conduct the sensitivity analyses, it was first necessary to develop statistically linear regression equations to predict the occurrence of distresses. Once a predictive equation was available, the effects of variations in significant independent variables were quantified by calculating the change in the predicted distress as each significant variable was varied from one standard deviation above its mean to one standard deviation below its means, with all other variables held at their mean values. The sensitivities of the distress predictions to the individual variations in the significant variables were then plotted to display the relative significance of the independent variables in the equation to the prediction of the distress. (Copyright (c) 1994 National Academy of Sciences.)
Sensitivity Analyses for Selected Pavement Distresses
One of the Long-Term Pavement Performance (LTPP) objectives is to determine the effects of (1) loading, (2) environment, (3) material properties and variability, (4) construction quality, and (5) maintenance levels on pavement distress and performance. This volume reports the results of early sensitivity analyses on the National Information Management System to determine the effects of loading, pavement structure, environment, and material properties on pavement performance. In order to conduct the sensitivity analyses, it was first necessary to develop statistically linear regression equations to predict the occurrence of distresses. Once a predictive equation was available, the effects of variations in significant independent variables were quantified by calculating the change in the predicted distress as each significant variable was varied from one standard deviation above its mean to one standard deviation below its means, with all other variables held at their mean values. The sensitivities of the distress predictions to the individual variations in the significant variables were then plotted to display the relative significance of the independent variables in the equation to the prediction of the distress. (Copyright (c) 1994 National Academy of Sciences.)
Sensitivity Analyses for Selected Pavement Distresses
A. L. Simpson (author) / J. B. Rauhut (author) / P. R. Jordahl (author) / E. Owusu-Antwi (author) / M. I. Darter (author)
1994
360 pages
Report
No indication
English
Highway Engineering , Construction Equipment, Materials, & Supplies , Transportation & Traffic Planning , Transportation , Road Transportation , Sensitivity analysis , Pavement damage , Highway maintenance , Pavement condition , Asphalt pavements , Loads(Forces) , Regression analysis , Pavement joints , Concrete pavements , Mathematical models , Maintenance management
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