has been adopted by every model code, as well as by state- adopted plumbing codes, in the United States and other countries. Regardless of the recent criticism it has received, it is an ingenious method and has withstood the trial of time in successful plumbing systems. The criticism of Hunter’s Curve over-estimating the water
demand is not because of the mathematical probability used in his computations. Rather, it is because the variables have changed over time. Plumbing fixtures have changed. Toilet performance no longer requires four to five gallons of water per flush, and toilet-flushing curves now display one maxi- ma rather than two. Showers are used more frequently than bathtubs. Faucets and showerheads have flow restrictions. Since Hunter’s day, clothes washers have placed a signifi- cant impact on water demand. Toilet behavioral practices have changed. In residential
applications, the bathroom has taken on a completely new dimension as compared to what it was in Hunter’s day. More time is spent in the bathroom, for all kinds of cosmetic and therapeutic purposes. The master bathroom, for two-plus occupants, would have been a novel concept to the NBS investigations. The rush-hour concept in public buildings and factories, where the clock regulated people’s toilet breaks, has changed over the years. Building types have diversified; there are approximately
eight different building classifications, along with sub-cate- gories, required on architectural plans to determine occupant loads and egress necessities. Each requires different needs assessment for water usage. An assembly-type building will have different water demands than a business building. Residential needs are different from mercantile needs. Occupant loads, fixture requirements and frequency of usage are all factors to consider for each building classifica- tion. So, what has the Pipe Sizing Task Group done? First, as
already indicated, we have determined not to fault the math- ematical probability that Dr. Hunter created. We shall con- tinue to use the binomial distribution method. In fact, we have re-created Hunter’s method, as published in BMS65, step-by-step, with corresponding tables and graphs in a com- puter program for the manipulation of the variables. We have gathered current fixture performance data from manu- facturers to determine flow rates, amount of water used and the time the fixture is in service. These variables have been applied to derive new probability data points for a true curve revision. We can also accurately weight the fixtures anew as we
generate new curves for each fixture. To date, we have eval- uated eleven different plumbing fixtures and have weighted them with new fixture units. The task group is looking for water-use specifications from manufacturers for clothes washers, dishwashers and tub fillers. We are also mindful of the different building classifica-
tions and of the toilet behavioral practices of the occupants. Having the ability to generate new curves, we can weight the fixtures in varying ranges, according to the needs of the building classifications. In other words, we can weight the fixtures for residential applications on the low end of the curves, between 5 to 45 gallons per minute; whereas, for assembly type applications we can weight the fixtures on the
Plumbing Engineer
high end of the curves. Thus, we can generate a family of curves, using the same probability data for fixture perfor- mance. In this regard, though, there is a rub. The conundrum is in
determining the frequency of use for each building type application. How often will the fixtures be used in a stadi- um? At “rush hour,” almost all fixtures are in use simultane- ously. What about a residence? What about a place of busi- ness or a restaurant? Are there “peak” times in every build- ing type? If so, what are they? Aquacraft data shows that there are two peak times in residences; one in the morning and one in the evening hours. One of the task group’s press-
Hunter Fixture Units revisions study was initiated for IAPMO code pipe sizing tabulations to water/energy con- serving fixtures/appliances.
ing needs is for field data showing peak values for various types of buildings, including the number and types of fix- tures and occupancy levels in each building that is field-test- ed. We can then evaluate the data against the newly generat- ed curves and fixture units for correspondence. Finally, we are mindful of the revision efforts and re-eval-
uation of Hunter’s Curve that have occurred before our group worked on this issue. We have collected documents (and continue to do so) of our predecessors, namely French and Wyly, NBS 1946; Connor and Severo, Research Triangle Institute and University of Buffalo, 1962; the American Water Works Association, M22, 1975 ; Breese, James Breese and Company, 1980; Thomas Konen, Stevens Institute, 1980 – 1994; ASHRAE’s modified Hunter’s Curve,1987; Wistort, ASPE Convention, 1994; Larry Galowin, NIST and John Swaffield, Hariot Watt University,
Continued on page 44 March 2011/Page 43
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