CC BY
56
гидравлика. инженерная гидрология.
гидротехническое строительство
УДК 628.1:532.595.2 DOI: 10.22227/1997-0935.2017.11.1299-1308
SIMULATION OF NEGATIVE PRESSURE WAVE PROPAGATION IN WATER PIPE NETWORK
Pham Ha Hai*, Pham Thi Minh Lanh**, Tang Van Lam, Pham Van Ngoc, V.V. Volshanik
Moscow State University of Civil Engineering (National Research University) (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; *Ho Chi Minh City University of Architecture, 196 Pasteur str., Ward 6, district 3, Ho Chi Minh City, 70000, Vietnam; **Ho Chi Minh City University of Technology, 268 Ly Thuong Kiet str., Ward 14, district 10,
Ho Chi Minh City, 70000, Vietnam;
Subject: factors such as pipe wall roughness, mechanical properties of pipe materials, physical properties of water affect the pressure surge in the water supply pipes. These factors make it difficult to analyze the transient problem of pressure evolution using simple programming language, especially in the studies that consider only the magnitude of the positive pressure surge with the negative pressure phase being neglected.
Research objectives: determine the magnitude of the negative pressure in the pipes on the experimental model. The propagation distance of the negative pressure wave will be simulated by the valve closure scenarios with the help of the HAMMER software and it is compared with an experimental model to verify the quality the results.
Materials and methods: academic version of the Bentley HAMMER software is used to simulate the pressure surge wave propagation due to closure of the valve in water supply pipe network. the method of characteristics is used to solve the governing equations of transient process of pressure change in the pipeline. this method is implemented in the HAMMER software to calculate the pressure surge value in the pipes.
Results: the method has been applied for water pipe networks of experimental model, the results show the affected area of negative pressure wave from valve closure and thereby we assess the largest negative pressure that may appear in water supply pipes.
Conclusions: the experiment simulates the water pipe network with a consumption node for various valve closure scenarios to determine possibility of appearance of maximum negative pressure value in the pipes. Determination of these values in real-life network is relatively costly and time-consuming but nevertheless necessary for identification of the risk of pipe failure, and therefore, this paper proposes using the simulation model by the HAMMER software. Initial calibration of the model combined with the software simulation results and with the model of experiment showed the differences in confidence intervals using a model that created valve closure scenarios.
KEY WORDS: water hammer, water distribution system, method of characteristics, pipe materials, negative pressure surge, water supply pipe
FOR CITATION: Pham Ha Hai, Pham Thi Minh Lanh, Tang Van Lam, Pham Van Ngoc, Volshanik V.V. Simulation of negative pressure wave propagation in water pipe network. Vestnik MGSU [Proceedings of Moscow State University of Civil Engineering]. 2017, vol. 12, issue 11 (110), pp. 1299-1308. до
№
моделирование отрицательного давления воды к
В СИСТЕМЕ ВОДОПРОВОДНых ТРУБ М
Фам Ха Хай*, Фам тхи Минь лань**, танг Ван лам, Фам Ван Нгок, В.В. Волшаник У
Национальный исследовательский Московский государственный Н строительный университет (НИУМГСУ), 129337, г. Москва, Ярославское шоссе, д. 26; *'Архитектурный университет Хошимина, 70000, Вьетнам,
Хошимин, район 3, Уорд 6, ул. Пастер, д. 196; М
**Технологический университет Хошимина, 70000, Вьетнам, И
Хошимин, район 10, Уорд 14, ул. Ли Тхуон Кит, д. 268; п
у
Предмет исследования: такие факторы, как шероховатость стенок труб, механические свойства материалов труб, к
физические свойства воды влияют на гидравлический удар в водопроводных трубах. Эти факторы затрудняют анализ 1
переходного процесса давления на простом языке программирования, особенно в исследованиях, изучающих только 1
положительный удар и не рассматривающих отрицательное давление. (
Цели исследования: определить значение отрицательного давления в трубах на экспериментальной модели. Рас- 1
стояние распространения волны отрицательного давления моделируется сценариями закрытия клапана с помощью q
программы HAMMER и сравнивается с экспериментальной моделью для проверки репрезентативности результатов. w
О 2
© Pham Ha Hai, Pham Thi Minh Lanh, Tang Van Lam, Pham Van Ngoc, V.V. Volshanik 1299
Материалы и методы: академическая версия программы Bentley HAMMER используется для моделирования распространения волны давления из-за закрытия клапана в трубах водопроводной сети. Применен метод характеристической теории для решения уравнений переходного процесса изменения давления в трубопроводе. Этот метод используется в программном обеспечении HAMMER для расчета давления в трубах.
Результаты: метод применяется для водопроводных сетей экспериментальной модели, результаты показывают область волны отрицательного давления от закрытия клапана. Таким образом, производится оценка наибольшего отрицательного давления на водопроводных трубах.
Выводы: эксперимент имитирует водопроводную сеть с узлом потребления с различными сценариями закрытия клапана, чтобы определить возможность появления максимального отрицательного значения давления в трубах. Определение этих значений в реальной сети является относительно дорогостоящим и трудоемким, но необходимым для выявления риска отказа трубопровода, поэтому в настоящем исследовании предлагается использовать имитационную модель. Первоначальная калибровка модели, объединенная с результатами моделирования с помощью программного обеспечения и с моделью эксперимента, показала различия в доверительных интервалах с использованием модели, которая создавала сценарии закрытия клапана.
КЛЮЧЕВЫЕ СЛОВА: гидравлический удар, система распределения воды, метод характеристик, материал трубы, отрицательный скачок давления, водопроводная труба
ДЛЯ ЦИТИРОВАНИЯ: Фам Ха Хай, Фам Тхи Минь Лань, Танг Ван Лам, Фам Ван Нгок, Волшаник В.В. Simulation of negative pressure wave propagation in water pipe network // Вестник МГСУ. 2017. Т. 12. Вып. 11 (110). С. 1299-1308.
INTRODUCTION
During the operation of water distribution systems, the water hammer on the pipe usually occurs due to the pump's sudden shut off or closure/opening of the valve on the pipes [1]. In the water supply networks, the number of valves on the pipe is much more than the number of pump stations, thus managing the water hammer and pressure wave propagation due to the valve closure in the pipes is relatively complex [2]. In addition, the water hammer due to pump power-off often has a high intensity and should be very tightly controlled [3], but the water hammer due to the valve closure is usually smaller and sometimes ignored during the pipe operation. However, the effect of water hammer due to the valve closure is wider because the pressure wave propagates all over the pipe network, while the pump's shut off interrupts only the first area of the network [4]. Therefore, in this study we will focus on analyzing the valve clo-© sure scenarios on the water supply pipe network.
When the water supply pipe is broken under-w ground, it causes a leakage in the water supply network systems [5] which not only results in economic loss [6] £ but also increases the risk of water contamination in the £ pipe during the period of negative pressure surge [7], £ which is unsafe for water users. Therefore, simulating the impact of negative pressure wave propagation, ^ which is a driving force for contamination of water ent vironment in the pipes [8] is necessary. !S
£ LITERATURE REVIEW
Water hammer is the pressure variation in pipes ■5 when the fluid motion is unsteady under the action of £ inertia force [9]. The methods of pressure surge calculation, both experimental and theoretical, have been |E gradually improved over time, especially with the de-q velopment of computer technology, which has led to 10 more diverse results in this research field.
Table 1 shows some research on water hammer performed from 1977 to 2015. The mathematical models are used to simulate the water hammer in simple pipes by the difference method [16], the method of characteristics or the method of algebra. Wylie used the method of characteristics and the graphical method to determine pressure surge values in simple pipes, some examples of water hammer in the pipelines which are of the same or different diameter, in branch pipes or the uniform pipes are programmed in Fortran language [10]. This paper concentrates on the methods that determine water hammer in the water distribution systems computationally.
The dynamic effect of pipe-wall viscoelasticity in hydraulic transients was investigated by D. Covas. The valve losses, the physical properties of water and the characteristics of the pipe material are taken into account, the magnitude of pressure surge values are determined and they are calibrated and verified by the experimental model and the mathematical model [11]. The material used for the experiment was Polyethylene but when setting up the experimental system, the mechanical properties of the material influenced the pressure surge to a lesser extent than the position of the pipe in the network, the history of pressure transient and prior deformation of the pipe. In the study [12] the authors found that the position of the pipe is more important than the mechanical properties of the material but the results have not been verified on the actual water distribution systems and the specific assessment of the area of the pressure surge wave propagation in the pipe network system was not carried out. This study provided a more comprehensive assessment of the potential for water hammer simulation in the water supply networks.
M.A. Bouaziz evaluated the effect of pressure transient on the wall of the valve when closing the valve on "Y" type water pipeline networks without pumps and with a pump. The results show that
Table 1. Literature review of the methods of water hammer simulations
Year Authors Research Title Methods Tools
1977 Wylie et al. Fluid Transients [10] Method of characteristics; graphical method Fortran
2004 Dídia Covas et al. The dynamic effect of pipe-wall viscoelasticity in hydraulic transients. Part I — experimental analysis and creep characterization [11] Experimental; model of unsteady flow Experimental model and mathematical equations
2005 Dídia Covas et al. The dynamic effect of pipe-wall viscoelasticity in hydraulic transients. Part II — experimental analysis and creep characterization [12] Method of characteristics Calibration model and comparing the results
2006 Roman Wichowski Hydraulic transients analysis in pipe networks by the method of characteristics (MOC) [13] Method of characteristics Experimental model and mathematical model
2014 M.A. Bouaziz et al. Predicting risk of water quality failures in distribution networks under uncertainties using fault-tree analysis [14] bifurcations and change of conducts characteristics. The numerical algorithm sustains the maximum pressure values and therefore, FEM ABAQUS simulation of gray cast iron pipes with a superficial defect gives the maximum stresses in the different network pipes. The severity of a corrosion crater defect was estimated by calculating the safety factor for the stress distribution at the tip of defects. It allows the acquisition of the applied notch intensity factor. To study the effects of the geometry defects, semi-elliptical defects are deemed to exist up to half the thickness of the pipe wall. To obtain the value of the safety factor, the results were fed into the assessment procedure for the structural integrity (SINTAP) Method of characteristics Fortran and ABAQUS software
2015 M. dallali et al. Accuracy and security analysis of transient flows in relatively long pipelines [15] Method of characteristics Fortran and ABAQUS software
in presence of the pump the positive pressure value increases by 30 % to 40 % and potentially damages the pipe structure [14] bifurcations and change of conducts characteristics. The numerical algorithm sustains the maximum pressure values and therefore, FEM ABAQUS simulation of gray cast iron pipes with a superficial defect gives the maximum stresses in the different network pipes. The severity of a corrosion crater defect was estimated by calculating the safety factor for the stress distribution at the tip of defects. It allows the acquisition of the applied notch intensity factor. To study the effects of the geometry defects, semi-elliptical defects are deemed to exist up to half the thickness of the pipe wall. To obtain the value of the safety factor, the results were fed into the assessment procedure for the structural integrity (SINTAP. The result of M.A. Bouaziz is continued by M. Dallali et al [15]. In this research, the author determines the propagation of pressure surge wave in a single pipeline which connects reservoir and a valve. Along the pipeline, pressure head due to closure of the valve is found
by using a program to assess the risk of the pipe failure
under the influence of maximum pressure. The study e
used the method of characteristics to calculate pressure o
surge but the simulation is valid only for a long pipe- j line because it does not account for the local losses due
to loops or branching with other pipes. ^
The graphical method used to calculate water ham- ^
mer provides the complete results. Using this method O
it is easier to observe the pressure transient process in ^
the pipe but it is only suitable for long pipes and non- o
branched pipelines because of the large volume of com- 2
putations and complexity of the boundary. One of the 2
methods that determines the pressure surge in pipes is ^
the method of characteristics and it has been used in re- £
cent times. differential equations can be solved by using y
finite element mesh of the pipe in which a water ham- o
mer occurs, however, the accuracy of results depends on 1
the number of finite elements used. In this study propose 1
how to improve this disadvantage by using the Bentley 1
software HAMMER to simulate the negative pressure 1
surge generated during the valve closure. 5
materials and methods
Water hammer was simulated by the method of characteristic, however, the negative pressure transient in water distribution systems was not determined. The direction of study is approached by simulation of water hammer in water pipe network with many loops and pipes have different diameters. In this research creates the valve closure scenarios on the HAMMER model to evaluate the propagation distance of the wave and determine negative pressure value due to closure of the valve and the maximum negative pressure value that may appear in the pipes.
The contents of research proposed and the implementation steps are shown in Fig. 1. Set up of the experimental model enables us to observe the negative pressure values generated by closing the valve in the model. We use these values to calibrate the HAMMER model setup in the HAMMER software from which the affected area and the magnitude of the negative pressure value in the system are evaluated through the valve closing scenarios. The results of research show the likelihood of occurrence of negative pressure values in the water distribution system and at the same time suggest appropriate pipeline operation conditions to protect the pipeline from the occurrence of this pressure.
1. Governing equations for the water hammer in pipes
Assuming that the water is a compressible fluid and material of the pipe in the network is elastic, pressure wave velocities are determined by formula (1). Considering the case of unsteady flow [17], the flow of water is often modeled using governing equations (2) and (3).
Continuity equation is
a2 dV Tr ÔH dH n
--+ V-+-= 0.
g dx dx dt
(1)
Momentum equations are
O >
dH JV\V\ dV „ g — + ——+— = 0, a* 2D, dt
(2)
where V — flow velocity, m/s; H — the piezometric head, m; f— Darcy—Weisbach friction factor; g — acceleration due to gravity, m/s2; t — the time of valve closure, s; x — length of pipe, m; a — wave speed, m/s,
a =
1+K D
with a = . —
(3)
E d„
where E — elastic modulus of pipe wall, MPa; K — elastic modulus of water, MPa; Dt — inner diameter, mm; d0 — thickness of pipe wall, mm; a0 — the acoustic velocity, m/s; p — mass density, kg/m3.
The equations (2), (3) are solved by using the finite element mesh of Wylie and Streeter. The water hammer appears during the valve closure. Pressure wave propagation in the pipe was divided into the meshes. Using the method of characteristics what is possible to determine the magnitude of piezometric head and flow velocity.
2. The scenarios of valve closure in the HAMMER model
We used the theory of water hammer due to the valve closure in the water distribution system and Bentley's HAMMER software (for academic edition only) [18]. An experimental model was simulated using the software as shown in Figure 2. Properties of pipes in the model are shown in Table 2. Hazen—Williams factors are set up according to hydraulic theory presented in Water distribution handbook [2], and these factors will change after calibration of the model.
The total length of the pipe network is 78.76 m, including the pipes with diameters from 15 mm to 140 mm, HDPE and PVC, with 4 loops and 22 branch pipes over the area of 70 m2. The underground reservoir supplies water to the network via pump and water is collected by canals systems to come back to the reservoir. Equipment used in the experimental model includes:
• two flow meters measure input and output flow in the model, their diameter is 30 mm;
• 6 pressure sensors including 4 positive pressure sensors and 2 negative pressure sensors. Two pressure sensors are set up at the first pipe and at the end of the
J tÛ
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o
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Simulation of negative pressure wave propagation in water
pipe network
Experimental model
Calibration model
1 L.................................................j
HAMMER model -J* Simulation of negative pressure wave propagation
_,
Determine negative pressure value
The scenarios ofvavle closure
Figure 1. Contents of research
Table 2. Properties of pipes in the HAMMER model
Pipe Length, m Diameter, mm Material Hazen—Williams factors Pipe Length, m Diameter, mm Material Hazen—Williams factors
1 2.64 131.80 PVC 110 P-34 0.60 20.40 HDPE 125
2 0.36 80.00 PVC 110 P-35 1.80 27.20 HDPE 125
P-1 0.40 65.00 PVC 110 P-36 1.50 27.20 HDPE 125
P-2 0.10 131.80 PVC 110 P-37 0.05 34.00 HDPE 125
P-3 4.02 131.80 PVC 110 P-38 1.20 34.00 HDPE 125
P-4 0.20 131.80 PVC 110 P-39 0.15 34.00 HDPE 125
P-5 0.70 84.20 PVC 110 P-40 0.40 15.40 HDPE 125
P-6 0.10 84.20 PVC 110 P-41 1.10 15.40 HDPE 125
P-7 0.10 84.20 HDPE 125 P-42 0.70 34.00 HDPE 125
P-8 0.30 15.40 PVC 110 P-43 0.14 27.20 HDPE 125
P-9 0.36 84.20 PVC 110 P-44 0.16 27.20 HDPE 125
P-10 1.00 84.20 PVC 110 P-45 1.00 34.00 HDPE 125
P-11 0.74 84.20 HDPE 125 P-46 1.00 34.00 HDPE 125
P-12 0.20 70.00 HDPE 125 P-47 0.20 34.00 HDPE 125
P-13 0.50 34.00 HDPE 125 P-48 1.16 20.40 HDPE 125
P-14 0.23 34.00 HDPE 125 P-49 1.16 20.40 HDPE 125
P-15 0.40 34.00 HDPE 125 P-50 1.16 20.40 HDPE 125
P-16 1.30 34.00 HDPE 125 P-52 0.05 20.40 HDPE 125
P-17 0.30 34.00 HDPE 125 P-53 0.25 20.40 HDPE 125
P-18 0.30 34.00 HDPE 125 P-54 1.35 20.40 HDPE 125
P-19 1.06 34.00 HDPE 125 P-55 1.30 20.40 HDPE 125
P-20 1.00 34.00 HDPE 125 P-56 1.50 34.00 HDPE 125
P-21 0.30 34.00 HDPE 125 P-57 1.20 34.00 HDPE 125
P-22 1.16 34.00 HDPE 125 P-58 0.30 34.00 HDPE 125
P-23 1.80 34.00 HDPE 125 P-59 2.25 34.00 HDPE 125
P-24 1.80 34.00 HDPE 125 P-60 2.20 34.00 HDPE 125
P-25 1.37 34.00 HDPE 125 P-61 1.50 15.40 HDPE 125
P-26 1.50 34.00 HDPE 125 P-62 1.08 15.40 HDPE 125
P-27 0.30 34.00 HDPE 125 P-63 0.24 20.40 HDPE 125
P-28 0.52 34.00 HDPE 125 P-64 0.10 34.00 HDPE 125
P-29 1.18 27.20 HDPE 125 P-65 0.08 34.00 HDPE 125
P-30 1.15 20.40 HDPE 125 P-66 1.00 34.00 HDPE 125
P-31 1.85 27.20 HDPE 125 P-67 1.34 34.00 HDPE 125
P-32 0.35 20.40 HDPE 125 P-68 1.78 34.00 HDPE 125
P-33 0.70 20.40 HDPE 125 P-69 0.62 27.20 HDPE 125
P-70 1.00 15.40 HDPE 125
m
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1
s
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1
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B
r
3
y
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pipe in the network to measure positive and negative pressures;
• 1 Grundfos pump with flow rate 60.3 m3/h, 11.4 meters head. It is set up after the reservoir.
• 26 gate valves of different diameters: 8 valves are set up on the main pipes and 18 valves are located on the branch pipes.
The HAMMER model is calibrated by the experimental model, the setup of which is shown in Figure 3,
and its results are compared with the information provided by sensors to verify the difference.
Typical head losses in the pipes are due to roughness of the pipe wall. The experimental model has four pressure sensors to measure the positive pressure values during the valve closure. These values serve as an input for the Darwin Calibrator tool of the WaterGEMs software to calibrate the HAMMER model [19]. Based on the values measured experimentally and after using the
figure 2. Simulation of water pipe network in the HAMMER software
O figure 3. Experimental model of water hammer due to valve closure
Table 3. The difference between negative pressure values obtained in the experiments and the results of HAMMER model
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to
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Valve closure Sensor node Experiment, m HAMMER, m Deviation, m
FCV-2 J-13 -9.98 -9.98 0.00
FCV-3 J-37 -9.35 -9.98 0.63
FCV-4 J-15 -9.35 -9.98 0.63
FCV-5 J-52 3.12 2.15 0.97
FCV-6 J-72 -7.28 -8.05 0.77
FCV-7 J-80 -8.52 -9.98 1.46
X
s
I h
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o 10
optimization tool, the results show that the roughness value for each pipe in the original HDPE pipe model is C = 150 and the original PVC pipes have the coefficient of roughness C = 120 [20]. Table 3 shows the deviation between the resulting pressure at the node, obtained
from the HAMMER model after calibration, and the pressure in the experimental model. The simulated error is about 2-5 %, which is an acceptable tolerance range between the HAMMER model and the actual hydraulic experimental model.
results
In the HAMMER model the water flowing from the reservoir through the FCV-2 valve diverges into two main water pipes by two FCV-3 and FCV-4 valves. The branch pipelines connecting these pipes have a diameter smaller than or equal to that of the main pipes. The distribution of flow in each pipe corresponds to color symbols of Figure 4. Red and pink colors correspond to the flow rates of 1.68 l/s to 2.8 l/s; blue color is a flow of about 1.12 l/s to 1.68 l/s, and green color has the lowest flow from 0.56 l/s to 1.12 l/s.
The time of valve closure is 5 s and the time report duration in the HAMMER model is 20 s. The valve closure on the first main pipe, the second main pipe and the branch pipes are simulated to determine the propagation distance of negative pressure wave. Figure 5 shows some of the possible scenarios in the pipes. The magnitudes of negative pressure values -9.98 m :-5.96 m : -1.94 m : 2.08 m : 10.12 m are shown in the contour plot with green:cyan:blue:pink:red colors, respectively. Note that the first pipe from the pump to FCV-2 valve always has a red color since the pump maintains the pressure put on the pipe network.
Figure 4. Color coding for flow and pressure in HAMMER model
00
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H
1
s
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T
2
1
ro
B
T 3
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figure 5. The propagation of the negative pressure wave during the valve closure: a — the first main pipelines; b — the second main pipelines; c — the branch pipelines
Table 4. The maximum negative pressure that may appear when closing the valve
Object The main pipes The branch pipes
Valve closure FCV-2 FCV-3 FCV-4 FCV-7 FCV-5 F9 F11 F13
D, mm* 34 34 34 34 20.4 34 20.4 15.4
Q, l/s* 2.8 1.76 1.04 1.11 0.18 0.24 0.18 0.1
P ,m* max' -9.98 -9.98 -9.98 -9.98 2.15 -4.87 -7.79 -9.98
Propagation-distance from valve, m 25 12 10 0.3 0.05 0.05 0.05 1.1
*D, Q — diameter and flow in pipes where valve closure takes place
*Pmax — maximum negative pressure value which may appear after valve closure
Table 4 shows some typical results in the valve closing scenarios in the main and branch pipes of the HAMMER model. On the first main pipeline, two closure scenarios for FCV-2 and FCV-3 valves are presented. A negative pressure of -9.98 m arises across the network after the FCV-2 valve with the longest transmission distance equal to 25 m, which is twice the effective distance (12 m) due to closure of the FCV-3 valve. The reason for this phenomenon is due to the fact that FCV-2 valve is on the first pipe of the network, so that, the flow in the network is zero when the vavle closure
When the FCV-4 valve is closed on P-19, the negative pressure is -9.98 m, the longest transmission is 10 m after the valve. As the flow of transport on this pipeline is smaller, the water pressure transmission distance is also smaller than in the first main pipeline. However, the extent of the wave propagation depends not only on the flow but also on the location of the valve closure in the network. This result can be seen from that data obtained when the FCV-7 valve is closed at the end of the network with a flow through the valve equivalent to P-19 but P = -9.98 m now appears only 0.3 m after
max A A J
the valve and drops to -6.89 m.
The FCV-5, F9, F11, and F13 valves are located on branches with different diameters in the middle of the network, with the same working pressure as in the main pipelines but the negative pressure values only appear in the short pipe after valve closure. The result of simulations show that the maximum negative pressure values in Table 5. This is especially true in case of closing the FCV-5 valve on P-52. Here the pressure drop is from 10.56 m to 2.15 m and it does not lead to negative pressure. This phenomenon is due to the smaller flow in P-52 (0.18 l/s) than in the nearby pipes (0.42 l/s). The pipe is connected to P-70, the initial working pressure is greater (11.02 m) and the flow direction goes to the P-52 pipe, and thus, when the valve is closed, the negative phase of water hammer is compensated by both the head and the flow from the rear pipes.
The above analysis shows that the area affected as well as the magnitude of negative pressure value after the valve closure depends on the flow in the pipe, the working position of the pipe in the network, the working conditions before closing the valve as well as the connection characteristics of the pipes that have valve closure. The valve closure scenarios of the HAMMER model are designed to determine the magnitude of the
Table 5. The maximum negative pressure value in the pipes P
Pipe P n Valve closure Pipe P n Valve closure Pipe P n Valve closure Pipe P n Valve closure
P-14 -9.98 FCV-2 P-22 -6.94 FCV-4 P-70 -9.98 F9 P-63 -2.13 F13
P-15 -9.98 FCV-2 P-25 -6.31 FCV-4 P-29 -4.87 F10 P-64 -1.15 F13
P-16 -9.98 FCV-2 P-26 -5.24 FCV-4 P-31 -3.72 F10 P-44 -9.37 F13
P-17 -9.98 FCV-2 P-39 -4.11 FCV-4 P-35 -2.31 F10 P-38 -9.98 F14
P-18 -9.98 FCV-2 P-69 -4.11 FCV-4 P-36 -0.65 F10 P-43 -9.98 F14
P-42 -9.98 FCV-3 P-52 -4.88 FCV-5 P-30 -8.00 F11 P-56 -9.98 F14
P-45 -9.98 FCV-3 P-32 -4.88 FCV-5 P-34 -5.39 F11 P-57 -9.98 F14
P-46 -9.98 FCV-3 P-65 -5.10 FCV-6 P-40 -5.39 F11 P-59 -8.81 F15
P-28 -9.98 FCV-3 P-27 -9.54 FCV-7 P-33 -9.98 F12 P-60 -6.77 F15
P-47 -9.98 FCV-3 P-58 -9.98 FCV-7 P-54 -7.02 F12 P-68 -9.98 F15
P-48 -9.98 FCV-3 P-20 -9.52 FCV-7 P-55 -3.48 F12 P-21 -5.10 F15
P-49 -9.98 FCV-3 P-66 -6.95 FCV-7 P-41 -9.98 F13 P-23 -3.56 F15
P-50 -9.98 FCV-3 P-37 -9.98 F9 P-61 -7.85 F13 P-24 -1.87 F15
P-19 -7.63 FCV-4 P-53 -9.98 F9 P-62 -4.15 F13 P-67 -4.74 F15
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maximum negative pressure value that can appear in each pipe of the water supply network in the model.
15 valve closing scenarios give 15 pressure values for each of the pipes. Usually the maximum negative pressure value occurs immediately after the valve closure, but for some pipes in the middle of the network this value occurs when closing the FCV-2 valve on the first main pipeline. In actual operation of the network, the FCV-2 valve closure occurs rarely.
conclusion
The experiment simulates the response of a water distribution system with a consumption node for different valve closure scenarios to determine the magnitude of the negative pressure value that may occur due to valve closure. Analysis of the results indicates that the negative pressure value may or may not appear at the water hammer phase in front of the valve, and this depends on the magnitude of the working pressure before closing the valve and, more importantly, the connection characteristics of the valve. After the valve closure the probability of appearance of the negative pressure value is higher than before the valve closure. However, the magnitude of negative pressure value is different.
According to (3) formulation, the magnitude of the negative pressure surge is inversely proportional to the pipe diameter, but the simulation on the HAMMER model indicates that this value depends not only on the diameter but also on the conditions of the pipes operation in the network. The negative pressure wave after valve closure in the main pipelines and in the first pipes in the network always has the highest and the largest propagation space. The connection pipes between the main pipelines are smaller and the propagation distance is not as wide as in the main pipelines.
The HAMMER software is an option for simulation of the water hammer in water distribution system. After calibration between software simulation and experiment, we showed that the negative pressure values are different by 0 m to 1 m, depending on reliability of the HAMMER model to represent the valve closure scenarios for the each of the pipes. The pipes can be protected from the water hammer and the negative pressure values can be reduced by increasing the time of valve closure and decreasing working pressure before closing the valve. The main pipelines in the water distribution systems have higher probability of appearance of negative pressure values than the branch pipelines. Therefore, these pipes need to be controlled for pressure and water quality when the valve closure occurs.
references
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Received June 10, 2017.
Adopted in revised form on September 1, 2017.
Approved for publication on October 27, 2017.
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About the authors: Pham Ha Hai — Candidate of Technical Sciences, Lectuer, Ho Chi Minh City University of Architecture, 196 Pasteur str., Ward 6, district 3, Ho Chi Minh City, 70000, Vietnam; vivmgsu_pham@mail.ru;
Pham Thi Minh Lanh — postdraduate student, Faculty of Civil Engineering, University of Technology, 268 Ly Thuong Kiet str., Ward 14, district 10, Ho Chi Minh City, 70000, Vietnam; phamthiminhlanh@gmail.com;
Tang Van Lam — Postgraduate Student, Department of Technology of Binders and Concretes, Moscow State University of Civil Engineering (National Research University) (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; lamvantang@gmail.com;
Pham Van Ngoc — Postgraduate Student, Department of Hydraulics and Hydraulic Construction, Moscow State University of Civil Engineering (National Research University) (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; pvngoc12@gmail.com;
Volshanik Valeriy Valentinovich — Doctor of Technical Sciences, Professor, Department of Hydraulics and Hydraulic Construction, National Research Moscow State University of Civil Engineering (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; tvg1806@gmail.com.
Поступила в редакцию 10 июня 2017 г.
Принята в доработанном виде 1 сентября 2017 г.
Одобрена для публикации 29 октября 2017 г.
Об авторах: Фам Ха Хай — кандидат технических наук, предподаватель кафедры воды и окружающей среды, Архитектурный университет Хошимина, 70000, Вьетнам, Хошимин, район 3, Уорд 6, ул. Пастер, д. 196; vivmgsu_pham@mail.ru;
Фам Тхи Минь Лань — аспирант кафедры гражданского строительства, Технологический университет Хошимина, 70000, Вьетнам, Хошимин, район 10, Уорд 14, ул. Ли Тхуон Кит, д. 268; phamthiminhlanh@gmail.com;
Танг Ван Лам — аспирант кафедры технологии вяжущих веществ и бетонов, Национальный исследовательский Московский государственный строительный университет (НИУ МГСУ), 129337, г. Москва, Ярославское шоссе, д. 26; lamvantang@gmail.com;
Фам Ван Гнок — аспирант кафедры гидравлики и гидротехнического строительства, Национальный исследовательский Московский государственный строительный университет (НИУ МГСУ), 129337, г Москва, Ярославское шоссе, д. 26; pvngoc12@gmail.com;
Волшаник Валерий Валентинович — доктор технических наук, профессор кафедры гидравлики и гидротехнического строительства, Национальный исследовательский Московский государственный строительный университет (НИУ МГСУ), 129337, г. Москва, Ярославское шоссе, д. 26; tvg1806@gmail.com.
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