Committee Chair
Wu, Weidong
Committee Member
Owino, Joseph; Fomunung, Ignatius; Onyango, Mbakisya
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
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
2-10-2022
Recommended Citation
Lawal, Abdulazeez, "An analytic hierarchy process and Markov chain based approach for condition rating and dynamic service life prediction of retaining walls" (2021). Masters Theses and Doctoral Dissertations.
https://scholar.utc.edu/theses/731
Department
Dept. of Civil and Chemical Engineering