Statistical Modeling for Climate Matching between Some Saudi Cities and Some Cities in the United States of America

Abstract

In a research project entitled "Structural Pavement Design for Saudi Arabian Roads", the researchers aimed to suggesting a complete structural pavement design system for the highway network of The Kingdom of Saudi Arabia (KSA). This main objective took into consideration changes of the materials along with prevailing environmental and traffic loading in various regions of KSA. The importance of this research project came from the fact that structural design techniques of flexible pavements focus in selections of materials and layer thicknesses, so the pavement can withstand the traffic and environmental loading for the design period. The research team found that the Mechanistic-Empirical Pavement Design Guide (MEPDG) and its software known as “AASHTOW” are developed in United States of America (USA) to be one of the largest and recent efforts in this regard in the international know how. Therefore, the research team; recommended implementing MEPDG in KSA for the structural design of pavement in Saudi Arabia, but, after being calibrated to the local Saudi conditions. As “AASHTOW” software was designed for the climate of cities in the USA, therefore, in order to use it for cities in Saudi Arabia, the researchers were required to determine for each of city in Saudi Arabia a city in the USA that has a similar climate. This paper summarizes the statistical methods, analysis and results that were used to accomplish this task based on the available climate data in KSA and USA for the selected cities.

Keywords: AASHTOW, pavement Mechanistic-Empirical (ME) design, MEPDG, structural design techniques

Cite this Article
Abdullah Al-Shiha, Ibrahim A. Aldubabe,
Khaled Galal, Abdulhadi Al-Shafi, Ayed
Al-Shehri, Sarah Al-Suhali, Sarah Al-
Dosari. Statistical Modeling for Climate
Matching between Some Saudi Cities and
Some Cities in the United States of
America. Research & Reviews: Journal of
Statistics. 2019; 8(3): 32–40p.