An optimization model for subsurface utility engineering during the design process

Implementation of Subsurface Utility Engineering (SUE) during the design process is becoming more and more of a mainstream operational standard for civil engineering projects. Many states are developing systems of implementation within their Department of Transportation (DOT) for SUE to become part of the highway and roadway design process. However, there are still traditional sequences of design development that exist which do not consider the benefits of SUE early enough in the design process or not at all. The proper application to optimize the use of SUE by the Quality Level (QL) of information, the timing, and the designer decision based on project complexity is still needed. This research found a correlation between SUE investment on projects and the cost growth due to utility relocations and conflicts. Understanding that relationship, it was possible to identify an optimization of an investment level. The results helped to create a scoring system that could be used for all types of civil engineering projects which is parallel to the Utility Impact Rating system (Sinha 2008) that was developed for highway projects. The scoring is linked to a decision matrix. The purpose of the matrix is to guide SUE use during the design to result in optimum results. The research demonstrated that an increase in SUE investment would lead to less cost contribution due to subsurface utility conflicts and proposed an optimization model for the use of SUE. The research identified an average cost increase across projects that did not utilize SUE in their design and referred to this percentage increase as a baseline in project cost. Then, looking at projects that involved SUE, the difference was found between the cost contribution and the baseline cost. The cost contribution became negative, representing a cost savings on projects. The data trend confirmed the initial statement of this research – an increase in SUE expense above the quality level associated with typical topographic survey information would positively affect a project by reducing potential cost contributions due to utilities. Also, there is an optimized amount of SUE to be used on each project which can be estimated based on these assessments.