Committee Chair

Wu, Weidong

Committee Member

Owino, Joseph; Fomunung, Ignatius; Onyango, Mbakisya

Department

Dept. of Civil and Chemical Engineering

College

College of Engineering and Computer Science

Publisher

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Abstract

Retaining walls are typically considered auxiliary assets within the global transportation asset management scheme. However, failure cases to this structure class have attracted more attention to retaining wall assets. The possibility of failure also helps validate Moving Ahead for Progress in the 21st Century (MAP-21) requirements that transportation agencies develop asset management plans. Consequently, this thesis represents the development of a framework that combines the Analytic Hierarchy Process (AHP) and Markov Chain to rate and predict the future condition of retaining walls respectively. Based on the Field Survey of candidate retaining walls, the research uses AHP for hierarchical configuration and pair-wise comparison of retaining wall elements (and sub-elements) – to generate relative weights. This process of relative weighting ultimately lends towards individual wall condition rating scores. This score, together with transition probabilities derived from historical condition data forms the basis of the dynamic service life prediction using the Markov chain.

Acknowledgments

Tennessee Department of Transportation (TDOT)

Degree

M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.

Date

8-2021

Subject

Asset-liability management; Mathematical models; Retaining walls

Keyword

AHP; Asset management; Markov chain; Retaining walls; Transportation agencies

Document Type

Masters theses

DCMI Type

Text

Extent

xii, 88 leaves

Language

English

Rights

http://rightsstatements.org/vocab/InC/1.0/

License

http://creativecommons.org/licenses/by/4.0/

Date Available

8-31-2022

Available for download on Wednesday, August 31, 2022

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