Basic Project Information:
Title: Dynamic Simulation of Water Distribution
Systems with Instantaneous Demands
Project Number: B-02
Start Date: 03/01/1999
End Date: 05/01/2001
Research Category: Engineering
Focus Category 1: Water Supply
Focus Category 2: Water Use
Focus Category 3: Water Quantity
Lead Institution: University of Puerto Rico
Principal Investigators:
Walter F. Silva: Associate Professor, University of Puerto Rico, Order:
01
Noel Artiles: Associate Professor, University of Puerto Rico, Order:
02
Problem and Research Objectives:
Accurate predictions of water quantities are needed for efficient
city planning in regions where land is limited for an ever-increasing
population. The competition for water is intense and the water availability
problems are complex. Puerto Rico is suffering a water crisis caused
by inappropriate management of water infrastructure that has revealed
serious water allocation and distribution problems. These problem
are aggravated by frequent shut downs of water treatment facilities
due to poor quality of the effluents. Moreover, water quality in
residential distribution networks deteriorates between the treatment
plant and the consumer's tap. This fact has deep consequences for
the drinking-water utilities because the new regulations proposed
by the Safe Drinking Water Act (SDWA) require the fulfillment of
drinking water standards at the household entrance.
Therefore, efficient urban planning and development;
as well as the challenge propose by he SDWA motivate the creation
of a new generation of promising methodologies which combine a details
representation of water demand scenarios with time-dependent hydraulic
models for reliable predictions of water quantity and quality in
distribution systems.
Objectives:
To develop a micro-scale simulation algorithm for residential water
consumption.
The new model combines an unsteady flow model
with an instantaneous water demand model. The principal objectives
of this project are to develop a methodology to model instantaneous
residential water demands in a neighborhood and to provide a micro-scale
simulation algorithm that combines an unsteady flow model and the
instantaneous demand model. The instantaneous demand model will
be constructed from the statistical simulation by combining probability
distributions for the duration and time of apertures of faucets
inside a house.
Methodology:
The project involves three phases:
1) Collecting neighborhood data related to water consumption and field
measurements.
A part of the neighborhood Alturas de Algarrobo, located in the Municipality
of Mayaguez, in the west part of Puerto Rico, was selected for this
study. The site is representative of a typical middle-class, homogeneous
residential neighborhood. A questionnaire
about resident habits associated to water consumption was distributed
in a section of 360 households during the month of November 1999.
The information requested included number of persons in the house
throughout the day, frequency of use of water consumption devices
such as washing machines, habits related to car washing, use of
garden sprinklers and the availability water storage tanks. A total
of 136 questionnaires were answered and sent by mail to the Puerto
Rico Water Resources Institute. The information was analyzed using
statistical tools and the major findings are presented in this report.
The field measurements program consists of recording discharge and
pressures at the entrance of several households. The period of data
collection was determined by the results of the statistical analysis
of the questionnaire data. Even though the periods are already defined,
the data collection program has not been implemented yet. However,
the instrumentation is available and the program will begin in July
2000. Due to limitations in the number of instruments (one pressure
transducer with datalogger and one ultrasonic flow meter), the sample
program will have to go slow and might be extended for several months.
Flow data from several houses in the neighborhood will be analyzed
statistically to determine the best combination of probability distributions
and their parameters, to simulate the consumption patterns inside
the study area. Pressure data will be used to calibrate the unsteady
flow model and to run the simulations. By combining the instantaneous
demand model and running the simulations. By combining the instantaneous
demand model with the hydraulic model, a micro-scale simulation
of the water consumption in the neighborhood will be obtained
2)Experimental runs in a laboratory model
A total of eight experiments with duration of three hours were conducted
in the laboratory. The experiments reproduce the sequence of apertures
and closures of faucets in a water distribution line. The pipe system
consists of 94.94 feet long and 2.0 inches nominal diameter, PVC-SHC
40 pipe. Gluing uniform sand to the pipe wall using epoxy created
the roughness effect. Ten "household" connections
represented by 3/4 inch branch pipes are equally spaced along the
pipe system. The connections are separated 8.2m and each represents
a house along a distribution line. A flow meter before the faucet
was used to measure the water volumes consumed at each "house".
One pressure transducer was located at the upstream
end of the pipe, and the pressure transducer was located at the
upstream end of the pipe, and the pressure was recorded during the
experimental run. This data was collected using a Data Acquisition
System (DAS) and sample frequency of 10Hz. An ultrasonic flow meter
was installed at the downstream end of the pipe to measure the outflow
from the 2-inch pipe.
Discrete demand models were constructed from probability
distributions to sequence of closures of valves at each household.
The sequence of closure and openings of faucet were created using
different probabilistic distribution. The duration of each opening
was simulated using the exponential and the Weibull distribution
with mean duration times of 20 and 40 seconds. Two types of experiments
were performed. Four of them used five valves; the other four were
done with nine valves. The total volume of water was read directly
of the "household" water meter at the end of the experiment. The
experiments were finished in May 2000.
3)Development and verification of the computer algorithm.
A computer simulation is being prepared to predict the water consumption
in the households located in the water distribution line. The measured
and computed demand volumes will be compared to determine the capability
of the model for realistic micro-scale computer simulations. Experience
with laboratory experiments was useful to foresee and prevent possible
difficulties during full-scale field measurements in a real neighborhood.
A methodology to model residential water
consumption by using a micro-scale simulation algorithm is presented.
The new algorithm combines an unsteady flow model with an instantaneous
demand model. The instantaneous demand model was constructed from
probability distributions for the simulation of time of aperture
and the duration of valve openings inside a house. Several households
were represented on an experimental setup to verify the ability
of the model to respond to the dynamic nature of the instantaneous
water use. The input data for the model are pressure measurements
at the upstream end of the water distribution pipe and, the discharge
at the beginning of the simulation.
A comparison between measured and computed results
obtained with the new model are presented. An excellent prediction
of the time-dependent discharge along the distribution pipe was
obtained for different demand scenarios; therefore, the model is
capable of responding to the random components of the water use.
The new methodology has potential application in neighborhoods with
relatively homogeneous consumption patterns where a representative
set of statistical parameters for the probabilistic model can be
derived.
Hydraulic Model

- Unsteady flow equations
- Solved by the Method of Characteristics
- Boundary Conditions
- Pressure head measurements (upstream)
- On-off constant discharge (household connections)
- Orifice equations (downstream)
Probabilistic Model Discrete Demand Model
Principal Findings and Significance
The statistical analysis of the questionnaire
information revealed that occupation pattern in the neighborhood
is different during the weekdays and during the weekends. The average
number of persons is approximately constant during the weekdays;
however, significant differences occur during the hours of the day.
Based on the number of persons inside the house, three periods of
time could be considered as homogeneous: 9am to 5pm, 5pm to 7pm,
7pm to 9pm. This information will be useful during the field measurements.
The first period corresponds to an average of 1.23 persons in the
house with a standadr deviation of 1.51. A water consumption pattern
does not necessarily follow this dendency. The second period has
2.2 persons with a standard deviation of 1.56. The third period
has 2.82 persons with a standard deviation of 1.51. A water consumption
period exists between 5:00pm and 7:00pm. By the end of the project,
water consumption as a function of time will be available to supplement
and expand these findings.
There are no results from computer simulations at
this time. However, the discrepancies obtained between the measured
water volumes from the households water meters and those computed
by multiplying the constant outflow expected from each faucet, obtained
after calibration of the number of turns of the faucet key, by the
time of opening varies between 0.4% and 14%. At present a review
of the reasons for this discrepancy in undergoing. Possible reasons
for these differences are that the outflow is not constant during
the time of aperture and the time of closure of the valves. On the
other hand, the discharge at each faucet changes by the opening
or closing of the other valves in the same line. This effect seems
to be important under laboratory conditions because the water pressure
is relatively small. The significance of this fact under field conditions
will be studied. The final results and detailed analysis will be
done when the computer algorithm is finished. |