Peak Factor Reduction

The design capacity of a water supply can be derived from the peak factor. In this research, four different methods were used to determine the peak factor more precisely. Applying Method 1 could result in the design capacity being underestimated, by designing the lower part of the pipeline to apply the peak factor to the whole area. Applying Method 2 could overestimate it by 10–30% in the upper part of the pipeline by dividing the sum of the regional peak factors according to the ratio of peak day demand to the region. Applying Method 3 underestimates the design capacity in small areas, while it could overestimate it in large areas. Finally, Method 4 gives optimum results for the peak factor for estimating the design capacity.

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Peak Factor–Based Modal Combination Rule of Response-Spectrum Method for Peak Floor Accelerations

Journal of Structural Engineering ◽

10.1061/(asce)st.1943-541x.0003044 ◽

2021 ◽

Vol 147 (7) ◽

Author(s):

Ashish Pal ◽

Vinay K. Gupta

Keyword(s):

Response Spectrum ◽

Combination Rule ◽

Response Spectrum Method ◽

Peak Factor ◽

Spectrum Method

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ESTIMATION OF PEAK FACTOR FOR NON-GAUSSIAN WIND PRESSURE

Journal of Structural and Construction Engineering (Transactions of AIJ) ◽

10.3130/aijs.67.79_3 ◽

2002 ◽

Vol 67 (557) ◽

pp. 79-84 ◽

Cited By ~ 2

Author(s):

Kazuyoshi NISHIJIMA ◽

Jun KANDA ◽

Hang CHOI

Keyword(s):

Wind Pressure ◽

Peak Factor ◽

Non Gaussian

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At-Site Assessment of a Regional Design Criterium for Water-Demand Peak Factor Evaluation

Water ◽

10.3390/w11010024 ◽

2018 ◽

Vol 11 (1) ◽

pp. 24 ◽

Cited By ~ 3

Author(s):

Gabriella Balacco ◽

Andrea Gioia ◽

Vito Iacobellis ◽

Alberto Piccinni

Keyword(s):

Water Demand ◽

Southern Italy ◽

Regional Distribution ◽

Gumbel Distribution ◽

Site Assessment ◽

Peak Factor ◽

Physically Based ◽

Distribution Parameters ◽

Factor Evaluation ◽

Regional Design

In this study an analysis of the water supply variability for three towns in Puglia (Southern Italy), Roccaforzata, Palagianello and Palagiano, was carried out, based on time series continuously recorded over two years. The towns’ population ranges between 1800 and 16,000 inhabitants and the flow data, collected with time steps of 10 min, are referred to drinking water in an urban environment. The frequency analysis was conducted on the hourly and instantaneous peak factors and confirmed that the Gumbel distribution is able to represent the stochastic behavior of the peak water demand. A physically based formulation of the distribution parameters was exploited in order to investigate the regional distribution of the peak factor for towns with a different population.

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