Study on the instantaneous and hourly maximum water supply prediction coefficients for hourly average predicted water supply based on the analysis of simulation technique in office buildings

Saburo Murakawa, Kazuhiko Sakamoto, Hiroshi Takata, Daisuke Ikeda

49th CIB W062 symposium in Northampton

ＣＩＢ 　Ｗ０６２

Northampton, UK

When designing water supply systems for buildings, it is essential to accurately predict the amount of water that will be used. In such cases, detailed design conditions are often unknown at the initial stage of basic planning, and the basic unit of water consumption per day is often used. Currently, the capacity of the receiving tank is calculated based on the basic unit of water usage per day. In addition, when planning the diameter of the lead-in pipe from the city water supply and the pumping pipe diameter of the building, the average predicted water supply amount per hour and the maximum predicted water supply amount per hour are used. However, direct water supply systems and booster pump supply systems, which are becoming more popular, require designs that can handle instantaneous water supply load fluctuations. Therefore, it is important to understand the instantaneous maximum flow rate.
In the case of water usage in office buildings, instantaneous water supply load fluctuations are greatly influenced by the number of people in the building, the gender composition, and the water usage characteristics of installed plumbing fixtures, etc. Conventionally, such hourly and instantaneous maximum water supply loads are predicted by assuming the average water supply amount per hour based on the basic unit per day and multiplying it by a set prediction coefficient. However, these coefficients are not taken into accounts the above-mentioned factors, and are currently shown within the certain range values.
In this paper, the authors used the MSWC program, which is provided for practical design as a dynamic water supply and hot water supply loads calculation method, to study water supply load fluctuations over a day in office buildings by changing the above-mentioned influencing factors. As a result, the authors compared the multiplication prediction coefficients with conventional values when changing the discharge characteristics of plumbing fixtures, the number of people in the building, and the gender composition ratio.