01333125

Component

https://doi.org/10.3141/2226-14

http://scholar.google.com...+Lea&publication_year=2011

Monte Carlo simulations are routinely performed in many branches of engineering to determine the distribution of possible system performance. In particular, Monte Carlo simulation, or a variant of it, is the most likely candidate for realistic simulation of reliability in mechanistic–empirical pavement design methods. However, it is common to find no justification for the number of simulations run or any analysis to determine whether, in fact, the distribution has converged. Although standard sampling rules can be applied to the estimate of the performance of the mean, especially in the presence of distributions that are approximately normal, they are difficult to apply to full distributions or percentiles. This paper presents a simple method for using statistical bootstrapping techniques to improve the quality of distributions estimated by Monte Carlo simulation, especially the quality of the estimates for percentiles in the tail of the distribution. This method is applied to the results of a mechanistic–empirical simulation of rutting on an asphalt pavement to demonstrate the issues and the procedure. However, the procedure is applicable to any type of performance model.

01353811

11-2966

English

pp 127-134

2011

Transportation Research Record: Journal of the Transportation Research Board

9780309167369

Print

Figures (9) ; References (8)

Asphalt pavements; Mechanistic-empirical pavement design; Monte Carlo method; Pavement design; Pavement performance; Rutting; Simulation; Statistical analysis

Bootstrap analysis; Convergence

Design; Highways; Pavements; I22: Design of Pavements, Railways and Guideways; I23: Properties of Road Surfaces

TRIS, TRB, ATRI

Feb 17 2011 6:21PM

• Analysis of Perpetual Pavement Experiment Sections in China
• Calibration of Distress Models from the "Mechanistic–Empirical Pavement Design Guide" for Rigid Pavement Design in Argentina
• Calibration of the "Mechanistic–Empirical Pavement Design Guide" for Flexible Pavement Design in Arkansas
• Continuously Reinforced Concrete Pavement: Identification of Distress Mechanisms and Improvement of Mechanistic–Empirical Design Procedures
• Effect of Concrete Strength and Stiffness Characterization on Predictions of Mechanistic–Empirical Performance for Rigid Pavements
• Enhancing "Mechanistic–Empirical Pavement Design Guide" Rutting-Performance Predictions with Hamburg Wheel-Tracking Results
• Estimation and Validation of Gaussian Process Surrogate Models for Sensitivity Analysis and Design Optimization: Based on the "Mechanistic–Empirical Pavement Design Guide"
• Finite Element Model for Rutting Prediction of Flexible Pavement with Cementitiously Stabilized Base–Subbase
• Improvements to Modeling of Concrete Slab Curling by Using NIKE3D Finite Element Program
• Minnesota Road Research Data for Evaluation and Local Calibration of the "Mechanistic–Empirical Pavement Design Guide"’s Enhanced Integrated Climatic Model
• New Laboratory-Based Mechanistic–Empirical Model for Faulting in Jointed Concrete Pavement
• Sampling-Based Sensitivity Analysis of the "Mechanistic–Empirical Pavement Design Guide" Applied to Material Inputs
• Structural Analysis of Pervious Concrete Pavement
• Thirty-Year Performance Evaluation of Two-Layer Concrete Pavement System
• Toward Implementation of the "Mechanistic–Empirical Pavement Design Guide" in Latin America: Preliminary Work in Chile