Deconstructing the empirical fixture unit method: a Monte Carlo–based paradigm for water-efficient wastewater piping design

Authors

  • Zufri Hasrudy Siregar Mechanical Engineering, Faculty of Engineering, Al-Azhar University Medan
  • Arif Fadillah Nasution Mechanical Engineering, Faculty of Engineering, Al-Azhar University Medan
  • Refiza Industrial Engineering, Faculty of Engineering, Al-Azhar University Medan

DOI:

https://doi.org/10.54123/vorteks.v6i2.480

Keywords:

monte carlo simulation, fixture unit, probabilistic design, hydraulic efficiency

Abstract

The empirical Fixture Unit (FU) method, which has been used for decades as the basis for wastewater pipe design, has now been proven obsolete and misleading. This deterministic approach is based on the false assumption that all sanitary fixtures flow simultaneously, whereas modern water user behavior is stochastic, intermittent, and never simultaneous. As a result, systems designed using the FU method are systematically overdesigned, leading to wasteful use of materials, energy, and construction costs. This study aims to deconstruct the empirical dogma of Fixture Unit and establish a new paradigm of hydraulic design based on Monte Carlo Simulation. The novelty of this research lies in the application of the Poisson–Lognormal–Truncated Normal stochastic model to predict the actual peak discharge of six types of plumbing fixtures (toilets, sinks, showers, floor drains, urinals, and kitchen sinks). The simulation was conducted for 24 hours with 100,000 iterations, using actual discharge, duration, and frequency-of-use parameters. The results show that the average empirical peak discharge value is 18.7% higher than the simulation results, with the highest deviations in urinals (?31.8%) and toilets (?22.9%). The coefficient of variation value of 10.9% confirms the stability of the stochastic model in describing hydraulic reality. This study concludes that the era of Fixture Units is over. Future wastewater system designs must abandon conventional empirical tables and shift to a more accurate, efficient, and water-conservation-aligned Monte Carlo-based probabilistic approach

Published

2025-10-28

Similar Articles

1 2 3 > >> 

You may also start an advanced similarity search for this article.