QUANTITATIVE ASSESSMENT OF HYDRAULIC MODELING TOOLS IN OPTIMIZING FIRE SPRINKLER SYSTEM EFFICIENCY

Abstract

This study addresses the persistent problem that, although automatic fire sprinkler systems are widely recognized as highly effective, there is limited quantitative evidence on how hydraulic modeling tools used at the design stage are associated with perceived sprinkler system efficiency in real projects. The purpose of the research is to quantify these relationships by linking practitioners’ perceptions of tool performance to perceived system outcomes. A quantitative cross-sectional, case-based survey design was employed, using a structured five-point Likert questionnaire administered to 180 practitioners, including fire protection engineers (42.2 percent), sprinkler design technicians (31.7 percent), consultants (15.6 percent), and facility or safety managers (10.5 percent) working on commercial, industrial, and institutional sprinkler systems. Key variables included perceived hydraulic accuracy (ACC), usability (USE), user expertise (EXP), input data quality (DATA), layout quality (LOUT), and perceived sprinkler system efficiency (EFF). All multi-item scales demonstrated strong reliability (Cronbach’s alpha 0.87-0.93). Descriptive results showed generally positive evaluations (means 3.61-3.92), and correlation analysis indicated strong positive associations between ACC, LOUT, USE, DATA, EXP and EFF (r = 0.58-0.71, p < .001). Multiple regression analysis confirmed that these factors jointly explained 62 percent of the variance in perceived efficiency, with ACC (β = 0.31, p < .001) and LOUT (β = 0.29, p < .001) emerging as the strongest predictors, followed by USE (β = 0.21, p = .002), DATA (β = 0.18, p = .006), and EXP (β = 0.12, p = .031). The findings imply that organizations seeking efficient, code compliant sprinkler systems should prioritize accurate and transparent modeling engines, invest in user training, and enforce robust data and layout quality practices within hydraulic design workflows.