Life-Cycle Cost Minimization Model of the Gravity Irrigation System

• Main Authors: Raphael Munthali, 莫德里
• Other Authors: Chung-We Feng
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/35754416843107087491

碩士 === 國立成功大學 === 土木工程學系碩博士班 === 97 === Achievement of sustainability in irrigation and drainage systems pose varying challenges to systems’ management authorities due to mismatching choices for maintenance strategies with expected levels of system service delivery. This gap is mostly attributed to input based decision making on choice of maintenance strategies. This research developed a life-cycle cost (LCC) minimization model of the gravity irrigation system to enable evaluation of alternative preventative maintenance (PM) strategies between two consecutive rehabilitations. The modeling framework, within the context of asset management, was developed. Concepts of Markov chains transitional probabilities, Genetic Algorithms and optimization were used to formulate and validate the model. Procedures in the developed modeling framework were applied to a case of Dingleydale gravity irrigation system in South Africa to evaluate assets’ costs, LCCs for the alternative PM strategies and minimization (using Evolver) of LCCs for PM plans to select the cost minimal strategy. Three alternative PM strategies were identified as candidates for the minimization and selection processes. The research found that the developed framework; Markov chains; and minimization can be feasible tools for selecting the cost minimal PM strategies for gravity irrigation systems. Consistent results were obtained for cases of minimization with and without budget limits. The sensitivity analysis showed that length of intervals for PM actions, maintenance intensities and transitional probabilities influenced choice of the optimal PM strategy. Changes in the discount rate did not impact choice of the optimal PM strategy; there was consistency in the choice made.