Estimation | An-Najah Staff

Closed-Form Solutions for Bimodal Axle Load Spectra and Relative Pavement Damage Estimation

Sun, 2014-06-01 10:43 — Monther Dwaikat

Journal Title, Volume, Page:

Journal of Transportation Engineering, Vol. 135, No. 12, pp. 974-983

Year of Publication:

2009

Link:

http://ascelibrary.org/doi/abs/10.1061/(ASCE)TE.1943-5436.0000077

Authors:

Dwaikat M.B.

Assistant Professor, Dept. of Civil and Environmental Engineering, An–Najah National University, Nablus, Palestine

Current Affiliation:

Building Engineering Department, Faculty of Engineering and Information Technology, An-Najah National University, Nablus, Palestine

[email protected]

Haider S.W.

Assistant Professor, Dept. of Civil and Environmental Engineering, Michigan State Univ., East Lansing, MI 48824

Harichandran R.S.

Professor, Chairperson, Dept. of Civil and Environmental Engineering, Michigan State Univ., East Lansing, MI 48824

Preferred Abstract (Original):

The mechanistic-empirical (ME) design procedures utilize axle load spectra to characterize the individual traffic loadings for a site. These loading characteristics are employed to calculate pavement response and for subsequent damage computations. Generally, these axle load distributions exhibit a bimodal shape and a combination of two continuous statistical distributions can be used to model them. In this paper, closed-form solutions are developed to estimate the parameters of the bimodal distribution from data. A combination of two normal distributions is shown to reasonably fit observed axle spectra. Since it is anticipated that the AASHTO equivalent single-axle load (ESAL) concept will continue to be used by pavement engineers even after the full adoption of ME design methods, a closed-form statistical relationship between ESALs and axle load spectra is proposed. Such a relationship will be useful in estimating a traffic level index from an axle distribution. In addition, the relationship can provide an estimate of the relative pavement damage caused by axle distributions, and be used to rank axle load spectra within a geographical region, or between regions in order to identify heavier traffic loading corridors.

Shrinkage Estimators for Reliability Function

Thu, 2013-04-04 10:50 — Mohammed Qabaha

Journal Title, Volume, Page:

An-Najah Univ. J.Res.(N.Se)Vol .27, p141-151

Year of Publication:

2013

Link:

http://scholar.najah.edu/publication/journal-article/shrinkage-estimators-reliab...

Authors:

Mohammad Qabaha

Department of Mathematics, Faculty of Science, An-Najah National University, Palestine

Current Affiliation:

Department of Statistics, Faculty of Science, An-Najah National University , Nablus, Palestine

[email protected]

Preferred Abstract (Original):

A variety of shrinkage methods for estimating unknown parameters has been considered. We derive and compare the shrinkage estimators for the reliability function of the two-parameter exponential distribution. Simulation experiments are used to study the performances of these estimators.

Ordinary and Bayesian Shrinkage Estimation

Thu, 2013-04-04 10:47 — Mohammed Qabaha

Journal Title, Volume, Page:

An-Najah Univ. J.Res.(N.Se)Vol .21, 101-116

Year of Publication:

2007

Link:

http://scholar.najah.edu/publication/journal-article/ordinary-and-bayesian-shrin...

Authors:

Mohammad Qabaha

Department of Mathematics, Faculty of Science, An-Najah National University, Palestine

Current Affiliation:

Department of Statistics, Faculty of Science, An-Najah National University, Nablus, Palestine

[email protected]

Preferred Abstract (Original):

In this paper a variety of shrinkage methods for estimating unknown population parameters has been considered. Aprior distribution for the parameters around their natural origins has been postulated and the ordinary Bayes estimators are used in place of natural origins in the ordinary shrinkage estimators to obtain Bayesian shrinkage estimators. The results are applied to the problem of estimating the location and scale parameters and the reliability function of the two-parameter exponential distribution. Simulation experiments are used to study the performances of these estimators.