A Review of Demand Models for Water Systems in Buildings including a Bayesian Approach

Abstract

Instantaneous flow rate estimation is essential for sizing pipes and other components of water systems in buildings. Although various demand models have been developed in line with design and technology trends, most water supply system designs are routinely and substantially over-sized to keep failure risks to a minimum. Three major types of demand models from the literature are reviewed in this paper: (1) deterministic approach; (2) probabilistic approach; and (3) demand time-series approach. As findings show some widely used model estimates are much larger than the field measurements, this paper proposes a Bayesian approach to bridge the gap between model-based and field-measured values for the probable maximum simultaneous water demand. The proposed approach is flexible to adopt estimates as its prior values from a wide range of existing water demand models for determining the Bayesian coefficients for reference models, codes, and design standards with relevant measurement data. The approach provides a useful method not only for evaluating the corresponding demand values from various design references, but also for responding to the call for sustainable building design.

Time-Variant Positive Air Pressure in Drainage Stacks as a Pathogen Transmission Pathway of COVID-19

“…Follow some design practices of WC, taking an example flow rate of one WC of q 1 = 1.8 L/s, the probably maximum simultaneous demands in the stack calculated by Equation (8) were used as the discharging flow rate in Equations (6) and (7) for the floor levels of H’ p & H’ d , with k = 0.5 the frequency factor for intermittent use (typical dwelling, guesthouse and office) [ 27 , 28 ]. The design flow rate q for intermittent use allows each installed WC to discharge once in every 20 min in the daily rush hour [ 27 , 28 ]. For frequent use like hotel, restaurant, school and hospital, k = 0.7, taking account of the discharge once every 10 min, is adopted.…”

“…For WCs uses of extra discharge frequency up to 100%, each WC would discharge in a manner of once in every 10–20 min in the daily rush hour. The corresponding frequency factor k = 0.7 [ 17 , 27 , 28 ]. Figure 10 shows the sensitivity of the risk indicators for a case of a 20%–80% ( k = 0.55–0.67) extra discharge frequency of WCs in two example buildings ( H = 79 m and 103 m).…”

“…For WCs uses of extra discharge frequency up to 100%, each WC would discharge in a manner of once in every 10-20 min in the daily rush hour. The corresponding frequency factor k = 0.7 [17,27,28]. Figure 10 Figure 9(ai,bi) shows the occurrence of predicted probabilistic positive air pressures at 0.02 ≤ Pmax ≤ 0.03 and 0.2 ≤ p ≤ 0.3.…”

Revealing Unreported Benefits of Digital Water Metering: Literature Review and Expert Opinions

“…Wong and Mui, in a review of water demand models for buildings, identified three model types, deterministic, probabilistic, and demand time-series and proposed a Bayesian approach [86]. After analysing the data from various studies across buildings in Europe, South Africa, and Japan, Wong and Mui concluded that, for maximum simultaneous flow rates, most designs are routinely and substantially oversized to minimize the chance of errors.…”

Evaluation of Design Flow Rate of Water Supply Systems with Low Flow Showering Appliances

“…The estimation of an instantaneous flow rate is necessary for sizing pipes and other components of water systems in buildings and, thus, models of design flow rate were reviewed [15]. The probability theory has been widely applied to estimate water demand and determine a design flow rate since its application by Hunter in 1940 [16,17].…”