## Abstract

The log-wake law for turbulent current has been developed and tested with laboratory data on turbulent flow in smooth pipes. However, flow with turbulence and vortices in a stepped spillway have not been described. Therefore, in this study, a log-wake law has been developed for use in stepped spillway systems. It can be divided into three parts. The first part, a logarithmic equation, describes the effect of shear stress between the flow layers with a von Kármán constant of 0.41. The second part, a third-degree polynomial, describes the effect of the shear stress on the wall. The last part, a fourth-degree polynomial, describes the effect of changing the flow pressure distribution, similar to the wall-free shear stress. Calibration tests (68 datasets) are used with a flow rate between 0.0233 and 3.285 m^{3}/s, a spillway slope of 14–30°, and a step height of 0.0380–0.610 m. The developed log-wake law characterized the flow in a stepped spillway well. The limitation of the equation is a maximum flow velocity of 4 m/s; the accuracy of this equation decreases as the step height increases.

## HIGHLIGHTS

The developed log-wake law for the spillway is provided.

Related experimental data are included.

## INTRODUCTION

River mechanics are complex processes consisting of flow and sediment transport. Flow in rivers is generally variable in time and is typically unsteady. Sections of rivers can be classified into two types: steep slope upriver and mild slope downstream or at the estuary, and the flow characteristics in each type are different. Moreover, the flow velocity at steep slopes upriver is always higher than downstream. The equation used to explain the flow velocity profile is assumed to be in accordance with the classic logarithmic law of the wall (Cheng & Gulliver 2011). Hence, the flow velocity profile has been explained using a power law for a long time.

Recently, a study comparing the basic logarithmic equation and the power law equation to clarify the flow velocity profile of a stepped spillway has shown that the basic logarithmic equation is more accurate than the power law equation (George 2007; Cheng & Gulliver 2011). The basic logarithmic equation, developed from the flow in a smooth pipe, is widely used to calculate the flow velocity profile and the variables related to the flow. However, the actual flow is non-ideal as there is friction between the flow surface and the eddy viscosity of the flow layer. For this reason, the basic logarithmic equation has been developed to simulate the flow (Cheng & Gulliver 2011). This equation is referred to as the ‘log-wake law equation’ and is first found and applied to the flow in a smooth pipe.

Turbulent flow is characterized by irregularities or disturbances, which lead to the formation of eddies and diffuses across the flow, as well as moving in the mean direction of the flow. Pulsing cross-current velocity fluctuations cause individual fluid parcels to move in irregular patterns, while the overall flow moves downstream. Turbulent flow can be considered a complex motion where random velocity fluctuations are superimposed on the average motion of translation. Turbulent eddies can transfer momentum normal to the flow boundary at a rate much higher than the molecular transfer that occurs in laminar flows. In this case, additional resistance to the flow arises, expressed by the eddy viscosity, which is not constant for a given fluid and temperature. In the turbulent flow, the water particles move in very irregular paths, causing an exchange of momentum from one portion of the fluid to another, and hence, the turbulent shear (Reynolds) stress.

The spillway is the important facility designed to prevent the overtopping of dams and release flood flow. An appropriate design of spillways for both drought and rainy seasons is another idea for preventing overtopping flow. To be safe, the spillway must allow a high flow without jeopardizing the dam. Although the general spillway shape and its flow are well-studied, it is also understood that even small changes to the design can change the flow properties. When a large flow is required, a specific spillway must be designed. Due to the high flow over the spillway, the design can be very complicated, introducing cavitation and high-flow kinetic energy problems. Some structural forms along the spillway, such as a stepped spillway, have been used for energy dissipation. A good energy-dissipating design should reduce the flow velocity without destroying other hydraulic structures. One recent popular approach to energy reduction is a spillway with high bed roughness rather than a smooth spillway with baffles or a stilling basin (Cheng & Gulliver 2011). This kind of spillway can also reduce velocities at the toe of the spillway.

A log-wake law equation aligned with the theory of a stepped spillway, or the high flow velocity, has not yet been proposed. Therefore, this research develops a log-wake law equation and the turbulent flow equation for a stepped spillway. Then, the collected data are analysed to determine the Coles wake strength (Π) suitable for such a flow pattern.

## RELATED LITERATURE

### Velocity profile for a stepped spillway

*W*is the wake function and

*x*is the direction of the flow. The wake function distribution is shown in Figure 2.

*H*is the depth of the flow,

*y*is the depth perpendicular to the flow,

*l*is the horizontal length of the steps,

*h*is the height of the steps,

*θ*is the slope angle of the stepped spillway, is the height of the steps in the same direction as the flow or the roughness height of the spillway, is the displacement height, is the turbulent shear stress, is the bed shear stress, and is the surface roughness length. The roughness height is the reference bottom level; thus, the displacement height is used as the mean roughness because the pseudo-bottom layer is not affected by the roughness height of the spillway (Jackson 1981). A study by Perry

*et al.*(1969) using the equation of Millikan (1938) with the logarithmic flow equation has described the turbulent flow that occurs above the steps. This test revealed that the equation is related to the displacement height and can be expressed as Equation (1):where is the flow velocity according to the flow depth, is the depth perpendicular to the flow,

*k*is the von Kármán constant, is the shear velocity, is the displacement height, and is the surface roughness length. From the study of a flow on a rough surface, the most important variables in applying these logarithmic equations were and (Jackson 1981).

### Log-wake law equation

*u*is the flow velocity at the depth of flow, is the shear velocity, is the von Kármán constant, is the depth perpendicular to the flow,

*ν*is the kinematic viscosity, and

*B*is the flow integration constant related to the bed roughness. Later, a basic logarithmic equation was developed to suit the actual flow under the condition that the flow is influenced by the variables related to the wake flow at the wall (Coles 1956). This equation is as follows:where Π is the Coles wake strength, is the boundary layer thickness, and is the wake function. From the study of the wake function (Hinze 1975), it is written as follows:where

*ξ*is the normalized distance from the wall . Thus, the logarithmic equation, including the wake function based on the flow in a smooth pipe, is as follows:

*et al*. 2005). This equation is as follows:

Guo & Julien (2008) have studied Equation (7), the log-wake law equation, to model open channel flow with sediments using data from Coleman (1986), Kironoto & Graf (1994), Lyn (1986), and Sarma *et al*. (2000). Moreover, Guo (2022) has re-derived the log-law of the wall in the overlap using pure dimensional analysis and a functional equation. This study reveals three important variables in the functional equation of any turbulence model: (i) the log-law of the wall, which is a pure mathematical law and is independent; (ii) the von Kármán constant, a pure mathematical constant that is independent of the Reynolds number; and (iii) a wake law correction, which is necessary in the outer flow region.

As mentioned earlier, the Coles log-wake law is often suitable for use with the velocity distribution of turbulent pipe flow. However, it lacks consideration for the pipe symmetry principle and the effect of wall-induced turbulence at the obvert. It only includes the effects of wall-induced turbulence at the invert (the log-law) and free turbulence at the pipe centreline (the wake law). To address this limitation, Guo (2020) proposed an application of the log-wake law for mean velocity distributions. This innovation involves adding an additional log term due to the pipe obvert, resulting in a second log-wake law that can be effectively used with data from pipes, symmetric channel flow, and antisymmetric channel flow. This enhancement allows for a more comprehensive and accurate modelling of turbulent flows in these different scenarios. Patel *et al*. (2021) applied the second log-wake law to an open channel flow study. The research focused on understanding the impact of water surface shear stress and wind-induced turbulent mixing on velocity distributions in open channels. The study observed both laboratory flumes and natural rivers, as they have similarities near the channel beds but exhibit differences near the water surfaces. The findings indicated distinct velocity distributions between laboratory flow and natural river flow. In laboratory flumes, water surface shear stress was present, but wind-induced turbulent mixing was negligible. In contrast, natural river flow experienced both water surface shear stress and wind-induced turbulent mixing. The second log-wake law demonstrated its applicability to both types of open channel flow, although some parameters varied depending on the specific scenario. This research sheds light on the differences between laboratory and natural river flow dynamics, providing valuable insights for future studies in open channel hydraulics.

Shan *et al*. (2022) studied the effects of ice cover and wind-induced water surface shear stress through laboratory experiments. The second log-wake law is a tool used for wall-bounded turbulent open channel flows. The velocity distributions obtained from the experiments exhibit three distinct patterns: a bowl-shaped velocity distribution with a dip phenomenon, a typical boundary layer velocity distribution, or an S-shaped velocity distribution with an inflection. Based on these findings, it can be concluded that the second log-wake law, an innovative three-point method, can be utilized for estimating river discharge using three-point velocity measurements.

### Physical model of flow in a stepped spillway

This study collected and used data from the experiments of Frizell (1992), Ruff & Ward (2002), Boes & Hager (2003), Hunt & Kadavy (2008), and Lurker *et al*. (2008) to understand the flow behaviour and propose a new equation. Each dataset has a different step angle and height for various analysis criteria.

Frizell (1992) used a physical model with a length of 4.72 m, a total height of 2.36 m, anda width of 0.457 m. The angle of the gutter was 26.6°, the height of the steps was 0.051 m, and the width of the steps was 0.102 m. The flow rate used in the test was 0.245 m^{3}/s. The results showed that steps with a slope of 0° were better able to dissipate energy than steps with a slope of 15°.

Ruff & Ward (2002) used a physical model with a length of 34.14 m, a total height of 15.24 m, and a track width of 1.22 m. The angle was 26.6°, the height of the steps was 0.61 m, the length of the steps was 0.305 m, and the flow rate used ranged from 0.57 to 3.28 m^{3}/s. The results showed that the flow energy of the open-stepped waterway could dissipate up to 32% of the input energy.

Boes & Hager (2003) used a physical model with a length of 5.7 m and a width of 0.5 m. The heights of the steps were 23.10, 46.20, and 92.40 mm for a spillway slope of 30°. The heights of the steps were 31.10 and 93.30 mm for a spillway slope of 50°, and the height of the step was 26.10 mm for a spillway slope of 40°. The flow rate in the experiment was between 0.023 and 0.19 m^{3}/s. This study proposed a power equation to describe the flow velocity distribution, which has an accuracy of 80%.

Hunt & Kadavy (2008) used a physical model with a length of 10.82 m and a width of 1.8 m. The total height of the 40-step spillway was 1.52 m; each step was 3.8 cm high and 15.2 cm wide. The slope of the gutter was 14°. The flow rate in the experiment was between 0.18 and 1.48 m^{3}/s. The test results showed that the energy loss from the flow was about 30%.

Lurker *et al*. (2008) studied a physical model with a length of 40.2 m and a width of 2.74 m, consisting of a flume with a slope of 22°, a length of 23.46 m, and steps with a total length of 2.35 m. The flow rate in the experiment was between 0.19 and 2.56 m^{3}/s. The results showed that the overflow channel dissipated up to 45% of the energy. All of the data are shown in Table 1.

Physical model . | Discharge . | Specific discharge . | Slope . | Spillway . | Step . | Maximum roughness . | Number of steps . |
---|---|---|---|---|---|---|---|

Q (m^{3}/s)
. | q (m^{3}/s/m)
. | (degree) . | Height H (m)
. | Height h (m)
. | K_{s}hcosθ (m)
. | N
. | |

Frizell (1992) | 0.245 | 0.577 | 26.6 | 0.051 | 0.046 | 47 | |

Ruff & Ward (2002) | 0.5663 | 0.4645 | 26.6 | 15.24 | 0.61 | 0.545 | 25 |

1.1327 | 0.9291 | 26.6 | 15.24 | 0.61 | 0.545 | ||

1.699 | 1.3935 | 26.6 | 15.24 | 0.61 | 0.545 | ||

2.2653 | 1.858 | 26.6 | 15.24 | 0.61 | 0.545 | ||

2.8317 | 2.3226 | 26.6 | 15.24 | 0.61 | 0.545 | ||

3.2848 | 2.6942 | 26.6 | 15.24 | 0.61 | 0.545 | ||

Boes & Hager (2003) | 0.0233 | 0.0466 | 30 | 2.85 | 0.0231 | 0.02 | |

0.066 | 0.1319 | 30 | 2.85 | 0.0462 | 0.04 | ||

0.1866 | 0.3732 | 30 | 2.85 | 0.0924 | 0.08 | ||

0.0328 | 0.0656 | 50 | 4.36 | 0.0311 | 0.02 | ||

0.1705 | 0.3409 | 50 | 4.36 | 0.0933 | 0.06 | ||

Hunt & Kadavy (2008) | 0.18 | 0.1 | 14 | 1.52 | 0.038 | 0.037 | 40 |

0.378 | 0.21 | 14 | 1.52 | 0.038 | 0.037 | ||

0.504 | 0.28 | 14 | 1.52 | 0.038 | 0.037 | ||

0.756 | 0.42 | 14 | 1.52 | 0.038 | 0.037 | ||

1.116 | 0.62 | 14 | 1.52 | 0.038 | 0.037 | ||

1.476 | 0.82 | 14 | 1.52 | 0.038 | 0.037 | ||

Lurker et al. (2008) | 0.19 | 0.07 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 | 68 |

0.74 | 0.27 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 | ||

0.94 | 0.34 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 | ||

1.31 | 0.48 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 | ||

2.56 | 0.94 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 |

Physical model . | Discharge . | Specific discharge . | Slope . | Spillway . | Step . | Maximum roughness . | Number of steps . |
---|---|---|---|---|---|---|---|

Q (m^{3}/s)
. | q (m^{3}/s/m)
. | (degree) . | Height H (m)
. | Height h (m)
. | K_{s}hcosθ (m)
. | N
. | |

Frizell (1992) | 0.245 | 0.577 | 26.6 | 0.051 | 0.046 | 47 | |

Ruff & Ward (2002) | 0.5663 | 0.4645 | 26.6 | 15.24 | 0.61 | 0.545 | 25 |

1.1327 | 0.9291 | 26.6 | 15.24 | 0.61 | 0.545 | ||

1.699 | 1.3935 | 26.6 | 15.24 | 0.61 | 0.545 | ||

2.2653 | 1.858 | 26.6 | 15.24 | 0.61 | 0.545 | ||

2.8317 | 2.3226 | 26.6 | 15.24 | 0.61 | 0.545 | ||

3.2848 | 2.6942 | 26.6 | 15.24 | 0.61 | 0.545 | ||

Boes & Hager (2003) | 0.0233 | 0.0466 | 30 | 2.85 | 0.0231 | 0.02 | |

0.066 | 0.1319 | 30 | 2.85 | 0.0462 | 0.04 | ||

0.1866 | 0.3732 | 30 | 2.85 | 0.0924 | 0.08 | ||

0.0328 | 0.0656 | 50 | 4.36 | 0.0311 | 0.02 | ||

0.1705 | 0.3409 | 50 | 4.36 | 0.0933 | 0.06 | ||

Hunt & Kadavy (2008) | 0.18 | 0.1 | 14 | 1.52 | 0.038 | 0.037 | 40 |

0.378 | 0.21 | 14 | 1.52 | 0.038 | 0.037 | ||

0.504 | 0.28 | 14 | 1.52 | 0.038 | 0.037 | ||

0.756 | 0.42 | 14 | 1.52 | 0.038 | 0.037 | ||

1.116 | 0.62 | 14 | 1.52 | 0.038 | 0.037 | ||

1.476 | 0.82 | 14 | 1.52 | 0.038 | 0.037 | ||

Lurker et al. (2008) | 0.19 | 0.07 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 | 68 |

0.74 | 0.27 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 | ||

0.94 | 0.34 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 | ||

1.31 | 0.48 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 | ||

2.56 | 0.94 | 22 | 3.66 | 0.241–0.031 | 0.223–0.029 |

Ikinciogullari (2022, 2023) conducted a study on different types of stepped spillways, utilizing both experimental data from previous research and numerical models, including trapezoidal and circular designs. The primary objective was to evaluate the energy dissipation rate and propose new designs for enhanced energy dissipation. The study found that the trapezoidal stepped spillway proved to be more effective, providing up to 30% more energy dissipation compared to classical stepped spillways. Additionally, the circular stepped spillway performed better when the step radius was smaller. For models with step depths of 0.50, 1.50, and 2.50 cm, energy dissipation increased by 21.4, 38, and 50.7%, respectively, compared to the flat stepped spillway.

## RESEARCH METHODOLOGY

### Data analysis of flow on a stepped spillway

*x*-axis and the flow velocity along the depth of flow as the

*y*-axis. It can be written as follows:where

*B*,

_{1}*B*, and

_{2}*C*are constants. Thus, the vertex, maximum, and minimum points of the parabola can be determined to identify the boundary layer thickness and the maximum velocity as shown in the following equations:

The results of studying the layer of turbulent flow on smooth and rough surfaces indicated that (Krogstad *et al.* 1992) where is the height of steps in the same direction with the flow . The flow data analysis from Equations (8) to (14) using some data (Frizell 1992) shows an example and exhibits the calculation steps by arranging some data collected from the experiment into Table 2.

0.019 | 0.021 | 0.027 | 0.034 | 0.039 | 0.046 | 0.052 | 0.064 | 0.077 | 0.090 | 0.102 | 0.115 | 0.127 | 0.140 | |

2.055 | 2.247 | 2.700 | 3.083 | 3.274 | 3.449 | 3.605 | 4.058 | 4.110 | 4.145 | 4.163 | 4.215 | 4.337 | 4.389 |

0.019 | 0.021 | 0.027 | 0.034 | 0.039 | 0.046 | 0.052 | 0.064 | 0.077 | 0.090 | 0.102 | 0.115 | 0.127 | 0.140 | |

2.055 | 2.247 | 2.700 | 3.083 | 3.274 | 3.449 | 3.605 | 4.058 | 4.110 | 4.145 | 4.163 | 4.215 | 4.337 | 4.389 |

Equations (8)–(10) have been used to calculate the boundary layer thickness and the maximum flow velocity (*u _{m}*) from the data of Frizell (1992), Ruff & Ward (2002), Boes & Hager (2003), Hunt & Kadavy (2008), and Lurker

*et al*. (2008), as shown in Table 3.

Physical model . | Dataset . | Boundary layer thickness . | Maximum flow velocity . | Physical model . | Dataset . | Boundary layer thickness . | Maximum flow velocity . |
---|---|---|---|---|---|---|---|

δ (m)
. | (m/s) . | δ (m)
. | (m/s) . | ||||

Frizell (1992) | 1 | 0.117 | 4.436 | Boes & Hager (2003) | 1 | 0.688 | 15.777 |

2 | 0.101 | 5.134 | 2 | 0.685 | 15.665 | ||

3 | 0.103 | 5.467 | 3 | 0.604 | 16.547 | ||

Ruff & Ward (2002) | 1 | 0.455 | 6.869 | 4 | 0.488 | 15.032 | |

2 | 0.379 | 6.639 | 5 | 0.428 | 15.010 | ||

3 | 0.377 | 7.346 | 6 | 0.517 | 17.416 | ||

4 | 0.362 | 7.069 | 7 | 0.545 | 18.312 | ||

5 | 0.326 | 7.582 | Hunt & Kadavy (2008) | 1 | 0.080 | 3.204 | |

6 | 0.450 | 5.783 | 2 | 0.086 | 4.020 | ||

7 | 0.494 | 8.087 | Lurker et al. (2008) | 1 | 0.165 | 7.354 | |

8 | 0.518 | 10.028 | 2 | 0.232 | 12.170 | ||

9 | 0.461 | 9.401 | 3 | 0.255 | 13.060 | ||

10 | 0.419 | 11.418 | 4 | 0.316 | 14.244 | ||

11 | 0.336 | 6.569 | 5 | 0.507 | 15.735 | ||

12 | 0.463 | 8.566 | 6 | 0.168 | 7.308 | ||

13 | 0.519 | 12.184 | 7 | 0.293 | 13.345 | ||

14 | 0.494 | 9.571 | 8 | 0.331 | 13.900 | ||

15 | 0.474 | 11.360 | 9 | 0.389 | 15.305 | ||

16 | 0.380 | 7.502 | 10 | 0.667 | 16.701 | ||

17 | 0.558 | 10.833 | 11 | 0.134 | 7.365 | ||

18 | 0.572 | 14.525 | 12 | 0.291 | 13.235 | ||

19 | 0.535 | 16.415 | 13 | 0.318 | 13.907 | ||

20 | 0.545 | 16.484 | 14 | 0.419 | 15.160 | ||

21 | 0.504 | 8.263 | 15 | 0.648 | 16.827 | ||

22 | 0.710 | 10.298 | 16 | 0.162 | 7.302 | ||

23 | 0.682 | 15.674 | 17 | 0.289 | 13.119 | ||

24 | 0.662 | 17.723 | 18 | 0.319 | 13.851 | ||

25 | 0.590 | 16.871 | 19 | 0.399 | 15.092 | ||

26 | 0.689 | 9.596 | 20 | 0.651 | 16.832 | ||

27 | 0.676 | 11.824 | 21 | 0.154 | 7.019 | ||

28 | 0.639 | 16.267 | 22 | 0.258 | 11.920 | ||

29 | 0.689 | 15.908 | 23 | 0.279 | 12.673 | ||

30 | 0.696 | 13.494 | 24 | 0.369 | 13.938 | ||

31 | 0.663 | 15.167 | 25 | 0.560 | 15.256 |

Physical model . | Dataset . | Boundary layer thickness . | Maximum flow velocity . | Physical model . | Dataset . | Boundary layer thickness . | Maximum flow velocity . |
---|---|---|---|---|---|---|---|

δ (m)
. | (m/s) . | δ (m)
. | (m/s) . | ||||

Frizell (1992) | 1 | 0.117 | 4.436 | Boes & Hager (2003) | 1 | 0.688 | 15.777 |

2 | 0.101 | 5.134 | 2 | 0.685 | 15.665 | ||

3 | 0.103 | 5.467 | 3 | 0.604 | 16.547 | ||

Ruff & Ward (2002) | 1 | 0.455 | 6.869 | 4 | 0.488 | 15.032 | |

2 | 0.379 | 6.639 | 5 | 0.428 | 15.010 | ||

3 | 0.377 | 7.346 | 6 | 0.517 | 17.416 | ||

4 | 0.362 | 7.069 | 7 | 0.545 | 18.312 | ||

5 | 0.326 | 7.582 | Hunt & Kadavy (2008) | 1 | 0.080 | 3.204 | |

6 | 0.450 | 5.783 | 2 | 0.086 | 4.020 | ||

7 | 0.494 | 8.087 | Lurker et al. (2008) | 1 | 0.165 | 7.354 | |

8 | 0.518 | 10.028 | 2 | 0.232 | 12.170 | ||

9 | 0.461 | 9.401 | 3 | 0.255 | 13.060 | ||

10 | 0.419 | 11.418 | 4 | 0.316 | 14.244 | ||

11 | 0.336 | 6.569 | 5 | 0.507 | 15.735 | ||

12 | 0.463 | 8.566 | 6 | 0.168 | 7.308 | ||

13 | 0.519 | 12.184 | 7 | 0.293 | 13.345 | ||

14 | 0.494 | 9.571 | 8 | 0.331 | 13.900 | ||

15 | 0.474 | 11.360 | 9 | 0.389 | 15.305 | ||

16 | 0.380 | 7.502 | 10 | 0.667 | 16.701 | ||

17 | 0.558 | 10.833 | 11 | 0.134 | 7.365 | ||

18 | 0.572 | 14.525 | 12 | 0.291 | 13.235 | ||

19 | 0.535 | 16.415 | 13 | 0.318 | 13.907 | ||

20 | 0.545 | 16.484 | 14 | 0.419 | 15.160 | ||

21 | 0.504 | 8.263 | 15 | 0.648 | 16.827 | ||

22 | 0.710 | 10.298 | 16 | 0.162 | 7.302 | ||

23 | 0.682 | 15.674 | 17 | 0.289 | 13.119 | ||

24 | 0.662 | 17.723 | 18 | 0.319 | 13.851 | ||

25 | 0.590 | 16.871 | 19 | 0.399 | 15.092 | ||

26 | 0.689 | 9.596 | 20 | 0.651 | 16.832 | ||

27 | 0.676 | 11.824 | 21 | 0.154 | 7.019 | ||

28 | 0.639 | 16.267 | 22 | 0.258 | 11.920 | ||

29 | 0.689 | 15.908 | 23 | 0.279 | 12.673 | ||

30 | 0.696 | 13.494 | 24 | 0.369 | 13.938 | ||

31 | 0.663 | 15.167 | 25 | 0.560 | 15.256 |

*x*-axis is the normalized distance from the wall and the

*y*-axis is the flow velocity as shown in Figure 4.

Equations (12)–(14) have been used to calculate the shear velocity ( ) and the Coles wake strength (Π) using data from the experiments of Frizell (1992), Ruff & Ward (2002), Boes & Hager (2003), Hunt & Kadavy (2008), and Lurker *et al*. (2008). The results are shown in Table 4.

Physical model . | Dataset . | Shear velocity (m/s) . | Coles' wake strength . | Physical model . | Dataset . | Shear velocity (m/s) . | Coles’ wake strength . |
---|---|---|---|---|---|---|---|

Frizell (1992) | 1 | 0.507 | 0.139 | Boes & Hager (2003) | 1 | 1.536 | 0.127 |

2 | 0.547 | 0.125 | 2 | 1.020 | 0.112 | ||

3 | 0.561 | 0.128 | 3 | 1.290 | 0.121 | ||

Ruff & Ward (2002) | 1 | 1.719 | 0.088 | 4 | 1.071 | 0.138 | |

2 | 1.406 | 0.106 | 5 | 1.140 | 0.109 | ||

3 | 1.739 | 0.118 | 6 | 1.313 | 0.143 | ||

4 | 1.885 | 0.110 | 7 | 1.332 | 0.139 | ||

5 | 1.860 | 0.106 | Hunt & Kadavy (2008) | 1 | 0.243 | 0.117 | |

6 | 0.711 | 0.139 | 2 | 0.370 | 0.125 | ||

7 | 1.409 | 0.167 | Lurker et al. (2008) | 1 | 1.055 | 0.124 | |

8 | 1.795 | 0.113 | 2 | 1.334 | 0.088 | ||

9 | 1.506 | 0.124 | 3 | 1.195 | 0.108 | ||

10 | 2.179 | 0.108 | 4 | 1.218 | 0.124 | ||

11 | 0.071 | 0.527 | 5 | 1.020 | 0.0627 | ||

12 | 1.710 | 0.127 | 6 | 0.948 | 0.102 | ||

13 | 2.700 | 0.190 | 7 | 1.189 | 0.125 | ||

14 | 1.889 | 0.126 | 8 | 1.273 | 0.118 | ||

15 | 1.939 | 0.159 | 9 | 1.234 | 0.158 | ||

16 | 1.115 | 0.122 | 10 | 0.829 | 0.132 | ||

17 | 1.809 | 0.143 | 11 | 1.114 | 0.162 | ||

18 | 2.951 | 0.220 | 12 | 1.139 | 0.127 | ||

19 | 4.027 | 0.179 | 13 | 1.140 | 0.115 | ||

20 | 3.318 | 0.150 | 14 | 1.119 | 0.144 | ||

21 | 0.874 | 0.117 | 15 | 0.900 | 0.160 | ||

22 | 1.227 | 0.088 | 16 | 1.005 | 0.117 | ||

23 | 2.977 | 0.188 | 17 | 1.166 | 0.132 | ||

24 | 3.797 | 0.137 | 18 | 1.210 | 0.117 | ||

25 | 2.668 | 0.173 | 19 | 1.163 | 0.142 | ||

26 | 1.154 | 0.158 | 20 | 0.787 | 0.176 | ||

27 | 1.717 | 0.157 | 21 | 0.875 | 0.111 | ||

28 | 2.742 | 0.181 | 22 | 1.113 | 0.113 | ||

29 | 2.187 | 0.106 | 23 | 0.882 | 0.116 | ||

30 | 2.729 | 0.193 | 24 | 0.803 | 0.166 | ||

31 | 3.171 | 0.192 | 25 | 1.067 | 0.095 |

Physical model . | Dataset . | Shear velocity (m/s) . | Coles' wake strength . | Physical model . | Dataset . | Shear velocity (m/s) . | Coles’ wake strength . |
---|---|---|---|---|---|---|---|

Frizell (1992) | 1 | 0.507 | 0.139 | Boes & Hager (2003) | 1 | 1.536 | 0.127 |

2 | 0.547 | 0.125 | 2 | 1.020 | 0.112 | ||

3 | 0.561 | 0.128 | 3 | 1.290 | 0.121 | ||

Ruff & Ward (2002) | 1 | 1.719 | 0.088 | 4 | 1.071 | 0.138 | |

2 | 1.406 | 0.106 | 5 | 1.140 | 0.109 | ||

3 | 1.739 | 0.118 | 6 | 1.313 | 0.143 | ||

4 | 1.885 | 0.110 | 7 | 1.332 | 0.139 | ||

5 | 1.860 | 0.106 | Hunt & Kadavy (2008) | 1 | 0.243 | 0.117 | |

6 | 0.711 | 0.139 | 2 | 0.370 | 0.125 | ||

7 | 1.409 | 0.167 | Lurker et al. (2008) | 1 | 1.055 | 0.124 | |

8 | 1.795 | 0.113 | 2 | 1.334 | 0.088 | ||

9 | 1.506 | 0.124 | 3 | 1.195 | 0.108 | ||

10 | 2.179 | 0.108 | 4 | 1.218 | 0.124 | ||

11 | 0.071 | 0.527 | 5 | 1.020 | 0.0627 | ||

12 | 1.710 | 0.127 | 6 | 0.948 | 0.102 | ||

13 | 2.700 | 0.190 | 7 | 1.189 | 0.125 | ||

14 | 1.889 | 0.126 | 8 | 1.273 | 0.118 | ||

15 | 1.939 | 0.159 | 9 | 1.234 | 0.158 | ||

16 | 1.115 | 0.122 | 10 | 0.829 | 0.132 | ||

17 | 1.809 | 0.143 | 11 | 1.114 | 0.162 | ||

18 | 2.951 | 0.220 | 12 | 1.139 | 0.127 | ||

19 | 4.027 | 0.179 | 13 | 1.140 | 0.115 | ||

20 | 3.318 | 0.150 | 14 | 1.119 | 0.144 | ||

21 | 0.874 | 0.117 | 15 | 0.900 | 0.160 | ||

22 | 1.227 | 0.088 | 16 | 1.005 | 0.117 | ||

23 | 2.977 | 0.188 | 17 | 1.166 | 0.132 | ||

24 | 3.797 | 0.137 | 18 | 1.210 | 0.117 | ||

25 | 2.668 | 0.173 | 19 | 1.163 | 0.142 | ||

26 | 1.154 | 0.158 | 20 | 0.787 | 0.176 | ||

27 | 1.717 | 0.157 | 21 | 0.875 | 0.111 | ||

28 | 2.742 | 0.181 | 22 | 1.113 | 0.113 | ||

29 | 2.187 | 0.106 | 23 | 0.882 | 0.116 | ||

30 | 2.729 | 0.193 | 24 | 0.803 | 0.166 | ||

31 | 3.171 | 0.192 | 25 | 1.067 | 0.095 |

### Development of the log-wake law equations for flow in a stepped spillway

A study to develop the log-wake law equations for flow in stepped spillway can be summarized as:

– An incompressible flow has been used with the continuity and momentum equations.

– Wall-free shear stress analysis was performed by considering the extent of the pressure distribution of the flow on the step. The boundary of the wake function of the stepped spillway () can be analysed using the direct approach. This is because the pressure distribution of the flow on the step is not very complicated.

– Shear stress analysis near the wall was conducted by considering the influence of the shear stress on the wall or the surface of the flow on the step. The boundary of the wake function of the stepped spillway () can be analysed using the Newton-like approach, an accurate interpolation theory. It is more accurate than the direct approach because it uses the second derivative to analyse the equation.

### Comparison of the observed and calculated values

After the development of the log-wake law equation in Section 3.2, the results from the modified log-wake law equations for a stepped spillway proposed in this study and the log-wake law equations for flow in smooth pipes were compared with the experimentally observed values to prove that the log-wake law equations for a stepped spillway are accurate. This study uses the correlation coefficient (*R*_{cc}) and *R*^{2} as statistical values for comparison.

## RESULTS AND DISCUSSION

### Data analysis of the Coles wake strength

*u*is the flow velocity, is the boundary layer thickness, is the dynamic viscosity, and is the kinematic viscosity. Therefore, from the calculation using all datasets to determine the Coles wake strength, when the von Kármán constant was set at 0.41, the Coles wake strength was found to be 0.126.

### Development of the log-wake law equations for a stepped spillway

#### Theoretical analysis of a stepped spillway

This study considers a turbulent flow to be incompressible. The flow through the cross-section was steady along the *x*-axis, and the variables did not vary on the *z*-axis. The continuity and momentum equations were applied as follows:

- 1.
- 2.

^{23}. This can be written as:where , is the viscosity of dimensionless flow, and is the eddy viscosity. From Equation (26), the shear velocity is related to the bed shear stress. Therefore, the shear stress of the channel should be determined by integrating Equation (25) to define the constant of integration, which was . Then, the constant was substituted into Equation (25), which was arranged into a new equation, as shown in Equation (27).

#### Boundary condition for wall-free shear stress analysis

The analysis results from these boundary conditions using the direct approach showed that the wall-free shear stress equation was similar to the equation proposed by White (1991).

#### 4.2.3. Boundary conditions for the near*-*wall shear stress analysis

### Comparison of data using the developed log-wake law equation

*et al*. (2008) compare the results of the log-wake law equation of Guo & Julien (2008), Equation (11) and the developed log-wake law equation proposed in this study, Equation (45). Example results are shown in Figures 8–12.

Thus, the log-wake law (Equation (11)) and the developed log-wake law equation from this study (Equation (45)) could be compared using statistics, as shown in Table 5.

Authors . | Modified log-wake law Equation (11) . | Modified log-wake law Equation (45) . | ||
---|---|---|---|---|

Correlation coefficient (R_{cc})
. | R^{2}
. | Correlation coefficient (R_{cc})
. | R^{2}
. | |

Frizell (1992) | 0.947 | 0.992 | 0.993 | 0.992 |

Ruff & Ward (2002) | 0.873 | 0.927 | 0.948 | 0.938 |

Boes & Hager (2003) | 0.966 | 0.977 | 0.975 | 0.978 |

Hunt & Kadavy (2008) | 0.950 | 0.972 | 0.994 | 0.975 |

Lurker et al. (2008) | 0.910 | 0.964 | 0.951 | 0.961 |

Authors . | Modified log-wake law Equation (11) . | Modified log-wake law Equation (45) . | ||
---|---|---|---|---|

Correlation coefficient (R_{cc})
. | R^{2}
. | Correlation coefficient (R_{cc})
. | R^{2}
. | |

Frizell (1992) | 0.947 | 0.992 | 0.993 | 0.992 |

Ruff & Ward (2002) | 0.873 | 0.927 | 0.948 | 0.938 |

Boes & Hager (2003) | 0.966 | 0.977 | 0.975 | 0.978 |

Hunt & Kadavy (2008) | 0.950 | 0.972 | 0.994 | 0.975 |

Lurker et al. (2008) | 0.910 | 0.964 | 0.951 | 0.961 |

## CONCLUSIONS

From the study on the log-wake law equation with the turbulent flow equation for the simulation of stepped spillway applying the theoretical, physical and mathematic analysis, it was discovered that the flow in the stepped spillway was affected by two factors, the wall shear stress and the pressure gradient (wall-free shear). Thus, in order to adjust the basic logarithmic equation and log-wake law equation to fit well with the flow in stepped spillway, Equation (45) is proposed as the modified log-wake law equation. From the analysis results, it could be summarized as follows:

– The proposed equation comprised of three parts,

- (i)
the logarithmic part where the von Kármán constant was set at 0.41,

- (ii)
the polynomial cube equation where the Coles wake strength was 0.126, and

- (iii)
the adjustment to explain the flow in the stepped spillway which was the polynomial to the fourth power equation.

- (i)

It was obvious that the equation contained the Coles wake strength to be consistent with the flow in stepped spillway, which was influenced by the wake flow on the step area.

– From the statistical comparison result of log-wake law equation, which was the cosine equation and the developed log-wake law equation, Equation (45) which was the polynomial equation, with a total of 68 sets of data, it was found out that the correlation coefficient (

*R*_{cc}) of the developed log-wake law equation was higher than that of Equation (11) about 2–10% as shown in Table 5. It could be concluded that the use of developed log-wake law equation for calculation would obtain the data that was consistent with the observed data. Moreover, the calculated data are also getting closer to the observed data than that from the log-wake law equation. Consequently, the application of modified log-wake law equation is more appropriate for the stepped spillway.

Therefore, from the above conclusions, it was found that for flow in open channel, Equation (45) shows more accurate computational results than the logarithmic Equation (11). The introduction of the swirling flow equations presented in this research to be used to calculate the vertical flow velocity distribution or variables related to flow in open-stepped waterways. The flow data should have a water flow rate in the range of 0.0233–3.285 m^{3}/s or a flow velocity of not more than 4 m/s for the accuracy of the calculations. The Coles wake strength (Π) presented in this paper is suitable for flow in open-stepped waterways only.

## FUNDING

This research was funded by Petchra Pra Jom Klao master's Degree Research Scholarship from King Mongkut's University of Technology Thonburi

## DATA AVAILABILITY STATEMENT

All relevant data are available from an online repository or repositories. Frizell (1992): https://www.usbr.gov/tsc/techreferences/hydraulics_lab/pubs/PAP/PAP-0596.pdf; Ruff & Ward (2002): https://www.usbr.gov/tsc/techreferences/hydraulics_lab/pubs/PAP/PAP-0951.pdf; Boes & Hager (2003): https://www.researchgate.net/profile/Robert-Boes/publication/239389377_Two-Phase_Flow_Characteristics_of_Stepped_Spillways/links/5589436508ae6d4f27ea4314/Two-Phase-Flow-Characteristics-of-Stepped-Spillways.pdf; Hunt & Kadavy (2008): https://elibrary.asabe.org/pdfviewer.asp?param1=s:/8y9u8/q8qu/tq9q/5tv/L/574BIGGO/GOKHLH.5tv¶m2=HG/IN/IGIJ¶m3=H.KN.HLN.KI¶m4=24919; Lurker *et al*. (2008): https://conservancy.umn.edu/bitstream/handle/11299/115338/pr511.pdf?sequence=1&isAllowed=y.

## CONFLICT OF INTEREST

The authors declare there is no conflict.

## REFERENCES

*Turbulent Velocity Profiles in Clear Water and Sediment-Laden Flows*. PhD Dissertation, Colorado State University, USA

*Turbulence and Turbulent Transport in Sediment-Laden Open-Channel Flows*

*PhD Dissertation*