Peak Water Demand Study:
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1 Peak Water Demand Study: Development of Metrics and Method for Estimating Design Flows in Buildings ACEEE 2016 HOT WATER FORUM: PORTLAND, OR TORITSEJU OMAGHOMI, STEVEN BUCHBERGER, TIMOTHY WOLFE, JASON HEWITT, AND DANIEL COLE FEBRUARY 22 ND,
2 Outline Background Task Group Water Use Database Key Parameters and Considerations Application Conclusion 2
3 BACKGROUND 3
4 GPM Hunter s Curve High efficiency fixtures = lower q 1940 Today, Hunter s curve is often faulted for giving overly conservative design.why? 2016 Uncongested use = lower p Fixture Units 4
5 Changing Times 5
6 Modified Hunter s Curve(s) Different curve for different end users 6
7 TASK GROUP 7
8 IAPMO Task Group Orders.will work singularly to develop the probability model to predict peak demands based on the number of plumbing fixtures of different kinds installed in one system. (Bring Hunter into 21 st Century) 8
9 Project Activities Acquire Data Analyze Data Develop Model Peer Review & Publication of Report 9
10 WATER USE DATABASE 10
11 Database: Location of Homes Over 1000 households Surveyed between ,800 residents 11,350 monitoring days 11
12 Percentage Database: Summary of Measured Data 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Water Use Event Duration Volume Bathtub Clothes washer Dishwasher Faucet Shower Toilet Others Leak Six unique fixtures 862,900 water use events (excluding leaks) 1,591,700 gallons 889,700 minutes -Evaporative Cooler 12
13 Database: Details of Water Use at Fixture FREQUENCY OF FIXTURE USE PER CAPITA PER DAY VOLUME OF WATER USE PER CAPITA Bathtub 0.5% Clothes washer 3.2% Toilet 25.8% Bathtub 5.2% Toilet 18.8% Dishwasher 1.5% Clothes washer 25.0% Dishwasher 1.9% Shower 2.5% Faucet 73.5% Shower 21.9% Faucet 20.2% 13
14 Database: Residential Fixture Classification Fixture* Ultra-Efficient Efficient Inefficient Clothes washer (gallons /load) Dishwasher (gallons/cycle) Shower (gallon/minute) Toilet (gallon/flush) *Bathtubs and faucets were excluded < > 30 < > 3.0 < > 2.5 < >
15 KEY PARAMETERS & CONSIDERATIONS 15
16 Key Fixture Characteristics n: q: Fixture Count Fixture flow rate x.... n 3 - p: Fixture Probability of use p T t i 16
17 Computed Fixture Flow Rate; q q Volumeof each pulse ( gallons) Duration of each pulse minutes ( ) 17
18 Flow rate (gpm) Clothes Washer Flow Rate Mean Outliers Recommended 0 Ultra C. (16.9%) Efficient C. (17.2%) Inefficient C. (65.9%) Fixture classification (Percentage of sampled homes) Clothes washer efficiency measured in gallons/load 18
19 Flow rate (gpm) Dishwasher Flow Rate Ultra D. (24.6%) Efficient D. (48.5%) Inefficient D. (26.9%) Mean Outliers Recommended Fixture classification (Percentage of sampled homes) Dishwasher efficiency measured in gallons/cycle 19
20 Flow rate (gpm) Shower Flow Rate Mean Outliers Recommended 0.0 Ultra S. (67.5%) Efficient S. (15.0%) Inefficient S. (17.5%) Fixture classification (Percentage of sampled homes) Shower efficiency measured in gallons/minute 20
21 Flow rate (gpm) Toilet (Water Closet) Flow Rate Mean Outliers Recommended 0.0 Ultra T. (21.5%) Efficient T. (24.9%) Inefficient T. (53.6%) Fixture classification (Percentage of sampled homes) Toilet efficiency measured in gallons/flush 21
22 Flow rate (gpm) Bathtub Flow Rate Bathtub (100%) Mean Outliers Recommended Fixture (Percentage of sampled homes) 22
23 Flow rate (gpm) Faucet Flow Rate Kitchen and Laundry sink Bathroom sink Mean Outliers Recommended 0.0 Faucet (100%) Fixture (Percentage of sampled homes) 23
24 Flow rate (gpm) Summary of Efficient Fixture Flow Rate Mean Outliers Recommended Bathtub Clothes Washer Toilet Shower Faucet Dishwasher Efficient = Ultra-efficient and Efficient Fixtures 24
25 Daily Volume (gallons) Peak Hour of Fixture Use (by Volume) Shower 07 Toilet 07 Clothes washer 10 Faucet 18 Bathtub 19 Dishwasher Hour of Day Average hourly volume of water use at a fixture per home per day 25
26 Volume (gallons) Single Home 12 Day Water Use Profile (10S761) Peak Hour Clothes washer Dishwasher Faucet Shower Toilet Total Volume Hour of Day 26
27 Average Volume daily (gallons) volume (gallons) Multiple Fixture peak Homes hour Water of water Use Profile use (by (by Volume) Home #1; Average hourly volume Home of water #2; consumed at each fixture Home #3; 10S761 10S764 Cal_Fed Clothes washer; Shower; 07 Dishwasher; Faucet; 18 Toilet; 07 Bathtub; Hour of Day Hour of Day 27
28 Percentage (%) Distribution of Peak Hour of Water Use homes (N = 1,038 Homes) homes 5 2 homes Hour of Day 28
29 Peak Hour Probability of Fixture Use Focused on only efficient fixtures t i i p n D T th ti Duration of i water use event n Number of fixtures D Number of observation days T 60 minutes ( 1hour observation window) 29
30 Probability of Fixture Use at Individual Homes p t i i n D T p 10 minutes 1 fixture 1day 60minutes 0.17 Considered only efficient fixtures 30
31 Probability of Fixture Use Group of Homes Number of residents Positive Correlation Number of bathrooms Number of bedrooms 31
32 Probability of Shower Use N = 100 N = 365 N = 142 N = 141 N = 58 N = 18 N = 13 Recommended Value = I Group weighted average 32
33 Frequency Distribution of Shower p values for Homes with 2 residents Recommended value (N = 365) Probability 33
34 Summary Probability of Fixture of Use Each fixture has a unique water use profile. Probability of fixture use does not dependent on how frequent a fixture used. Probability of fixture use increased as the number of residents increased. 34
35 Design Fixture Probability Values p = p = p = p =
36 APPLICATION 36
37 Binomial Model exactly xbusy n x Pr p (1 p ) out of nfixtures x n x *n in a big buildings Hunter did this 37
38 Frequency Factor Approach x Mean z Standard Deviation th Percentile 38
39 Normal Approximation of Peak Flow Q z 0.99 q 0.99 q K 1 2 Q n p q z n p p q 0.99 k k k 0.99 k k k k k 1 k 1 K - Wistort (1995) 39
40 Binomial Distribution *n in a small buildings 40
41 Zero Truncated Binomial Distribution (ZTBD) 41
42 Modified Wistort s Model 2 1 K K K 2 Q0.99 nk pkqk z P0 nk pk 1 pk qk P0 nk pkqk 1 P 0 k 1 k 1 k 1 Note: k P0 1 p k 1 n k K 1 2 Q n p q z n p p q 0.99 k k k 0.99 k k k k k 1 k 1 is probability of stagnation in a home (i.e. no water use) Addresses water demand in single family homes with high P 0 Transitions back to Wistort s model as P 0 approaches 0 K 42
43 Hypothetical Residential Building Pipe Layout 43
44 Peak Flow Calculations Example: 2.5 bath single family home Section UPC FU UPC Method (gpm) MW Method (gpm) gpm - gallons per minute 44
45 Sizing Pipes Example: 2.5 bath single family home Section UPC Method Pipe Size * MW Method Pipe Size * gpm gpm 3/4" gpm 3/4" 6.9 gpm 3/4" * Maximum flow rate at 8 f/s 45
46 Demand Sensitivity to p and q values 46
47 CONCLUSION 47
48 Conclusion Introduced a computational model to estimate peak water demand in single and multi-family dwellings. Recommended fixture p and q values. Model applicable to a wide spectrum of buildings. Single Family Homes 48
49 Questions? University of Cincinnati 49
50 50
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