Fuzzy logic index for subsurface utility engineering

Al-Tofan, Mohammed Hameed Sabhan; Alawadi, Wisam; Khudier, Ahmed; Khilqa, Sahad

doi:10.30772/qjes.2025.154127.1412

	Fuzzy logic index for subsurface utility engineering
Al-Qadisiyah Journal for Engineering Sciences
Volume 18, Issue 3, September 2025, Pages 312-319 PDF (6.95 M)
Document Type: Research Paper
DOI: 10.30772/qjes.2025.154127.1412
Authors
Mohammed Hameed Sabhan Al-Tofan^* ¹; Wisam Alawadi¹; Ahmed Khudier²; Sahad Khilqa³
¹Department of Civil Engineering, College of Engineering, University of Basrah, Basrah, Iraq.
²Department of Architectural Engineering, College of Engineering, University of Basrah, Basrah, Iraq.
³Department of Utilities, Richland County, South Carolina, the USA.
Abstract
Conflict with subsurface utilities during project implementation is a growing concern for many municipalities as it increases time and budget. Subsurface utilities refer to buried infrastructures such as water, gas, and electric lines, which vary in material, size, and configuration. Many existing subsurface utility studies proposed to assist in decision-making use traditional computer or paper log methods, exhausting time and affecting accuracy. In this study, a fuzzy logic model is used to develop a complexity number named Fuzzy Logic Index for Subsurface Utility Engineering (FLI-SUE) to determine the appropriate investigation level of subsurface utilities for engineering project implementation. This complexity number does not have units, and its value spans between 0 and 100. The higher the FLI-SUE number, the higher the investigation level of subsurface utilities. FLI-SUE number may assist planners, operators, engineers and decision-makers in determining the most appropriate response to the subsurface utility conflicts in projects construction. A set of input parameters presented in the literature were considered in the current fuzzy logic model.
Keywords
Infrastructure conflict mitigation; Buried asset evaluation; Fuzzy decision support system; Construction cost optimization; Subsurface risk assessment

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