Reliability Analysis of Flexible Pavement Using Crude Monte Carlo Simulation

Document Type : Original Article

Authors

1 Civil engineering, faculty of engineering, Menofia University, Tala, egypt

2 Civil Eng. Dept., Faculty of Eng., Menoufia University, Shebin El-kom, Egypt

Abstract

Flexible pavement design process is influenced by many parameters such as (traffic characterization, environmental conditions and structure materials…etc.). Several attempts have been carried out to add reliability concept to the mechanistic-empirical (M-E) design of pavements. In pavement structural design, it is common to consider the design input variables as fixed or deterministic. Also, the current design methodology used in many countries such as Egypt is ignoring the effect of temperature variation (despite its importance) on the pavement design. By using Minitab software this research aimed to assess the effect of variations in design parameters on pavement reliability and also predict the pavement reliability due to variation in pavement temperature using Monte Carlo simulation method (MCs) considering rutting and fatigue failures. Moreover, a comparison was performed between regressions models represented from different pavement agencies to recommend the most efficient one for Egyptian temperature. The results obtained that, considering design parameters variations (without temperature); the reliability based on Shell Research agency (86.57%) was the nearest one to the current design methodology in Egypt (91.0%). After adding temperature variations, the reliability was clearly affected but the regression model of Shell Research agency was still the most appropriate one to all Egyptian temperature zones as it achieved the lowest error mean (0.04) and the lowest error standard deviation (0.004). Moreover, the relation between air temperature and reliability was considered to confirm the first-order reliability method (FORM) results.

Keywords

ERJ. Engineering Research Journal
Volume 45, Issue 3
Vol. 45, No.3 issued on 1/7/2022 in 5 Parts: Part (1) Electrical Engineering, Part (2) Mechanical Engineering, Part (3): Production Engineering, Part (4): Civil Engineering, Part (5) Architectural Engineering.
July 2022
Pages 447-456

Files

Share

How to cite

Statistics