# Mitigating Scour at Bridge Abutments: An Experimental Investigation of Waste Material as an Eco-Friendly Solution

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## Abstract

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## 1. Introduction

_{a}(L

_{a}is the length of a short abutment) was placed, leading to the collar on a vertical wall beneath bed level. It was found that the height of the collar on the abutment concerning the sand bed elevation is a key scour depth reduction [16]. Collar installation was shown to be beneficial in preventing immediate collisions between downstream flows and the foundation material used. The impacts of erosive material were channeled away beyond the abutment, and the scour depth was reduced in the region of the abutment [17,18].

## 2. Material and Methods

#### 2.1. Flume Characteristic

#### 2.2. Sediment Size and Flow Condition

_{50}’ of 0.51 mm with the help of a sieve analysis test. The geometrical average deviation of the grain size transportation, given by the equation g = (d

_{84}/d

_{16})

^{0.5}, was 1.24, where d

_{84}and d

_{16}are the particle sizes at 84% and 16%, respectively. The flow was allowed to keep bed stress from shearing below a certain level. The flow rate or discharge was measured with the help of a trapezoidal, sharp-crested weir fixed at the end of the channel. Five distinct discharges (0.019, 0.021, 0.023, 0.027, and 0.033 m

^{3}/s) were used for the experiments. In each experimental examination, a flow level of 0.13 m was utilized across an abutment length of 0.30 m to meet the short abutment requirement, which is L

_{a}/Y ≤ 1 [15]. For calculating the Froude’s number, an average depth velocity was used, in which “V” is the flow velocity, “Y” is the water level in a flume, and F

_{r}= V/√gY was used for finding the Froude’s number. The experimental condition for each test is shown in Table 2. Scour depth in each experimental run was measured with the help of a rail-mounted point gauge with an accuracy of ±0.1 mm. According to this requirement (U/U

_{c}< 1 [1]), the value of U/U

_{c}is 0.92 for the present investigation, wherein U is the approaching velocity of flowing and U

_{c}is the critical velocity for all tests that took place in clear water. According to [1], the threshold velocity was estimated by using the velocity profile’s log shape, and a similar procedure was adopted in previous studies [3,10,14,15].

_{50}is the sediment size and Y is the depth of water in a flume.

#### 2.3. Abutment Specification

#### 2.4. Marble and Brick Condition

#### 2.5. Laboratory Work Procedure

- C
_{rd}= discharge coefficient of the rectangular, sharp-crested weir, - C
_{td}= discharge coefficient for triangular, sharp-crested weir - g = gravitational acceleration; h = water head on the weir crest; he = effective head

#### 2.6. Dimensional Analysis

_{50}; sediment particle size, V; an average flow velocity in a flume, U

_{c}; critical velocity of flow in a flume, A; the cross-sectional area of the flume, d

_{s}; the scour depth around the bridge abutment without and with countermeasures, $\mathsf{\rho}$ is the density of the water, d is the sediment bed depth, B is the width of the flume, L is the length of the flume, L

_{a}is the abutment length, T is the time noted for each experimental trial, and g is the gravitational acceleration.

## 3. Results

#### 3.1. Scour Depth around the Bridge Abutment without Countermeasures

#### 3.2. Scour Depth around Bridge Abutments with Marble Waste

#### 3.3. Scour Depth around the Bridge Abutment with Brick Waste

#### 3.4. Effect of Abutment Length and Water Depth on Scour

_{s}/L

_{a}) was observed to increase with increasing the initial Froude’s number, and the ratio of scour depth to water depth (d

_{s}/Y) increased with increasing the initial Froude’s number (Figure 9). For considering without countermeasure, the maximum d

_{s}/L

_{a}(4.55) and d

_{s}/Y (10.55) were observed for the Froude’s number of 0.22 (Figure 9). The result showed that the length of the abutment along the transverse direction of the flume and water depth have a greater influence on scouring around the abutment. Similarly, the effect of abutment length and initial water depth has also been investigated with countermeasures (bricks and marble waste). It was observed that d

_{s}/L

_{a}and d

_{s}/Y increase with increasing flow intensity (Froude’s number). The maximum d

_{s}/L

_{a}and d

_{s}/Y for Froude’s number are 0.22 (Figure 9). The maximum d

_{s}/L

_{a}and d

_{s}/Y for marble and brick waste were observed to be 2.30, 4.71, and 2.73, 6.3, respectively. The maximum reduction in d

_{s}/L

_{a}and d

_{s}/Y when marble waste was used as a countermeasure was 55%, and for brick waste, it reduced up to 40% and 57%, respectively (Figure 9). Based on the initial Froude’s number and water depth of flow, a Python code was run to generate Equations (4) and (5) for d

_{s}/L

_{a}and d

_{s}/Y to estimate the maximum scour depth around the abutment. To enhance the predictive power of the equations developed in this study, the valuable dataset, including the Froude’s number and water depth of the previous research [52,53,54], was also entertained through Equations (4) and (5). For each dataset from previous literature, a standard deviation was determined to determine which dataset fit well with the reference line and the current study. According to Hosseini et al. [52], the dataset has a standard deviation of 0.84 and 0.67 for d

_{s}/L

_{a}and d

_{s}/Y, respectively. According to Osroush et al. [53], the dataset has a standard deviation of 0.75 and 0.57 for d

_{s}/L

_{a}and d

_{s}/Y, respectively. According to Saad et al. [54], the dataset has a standard deviation of 0.52 and 0.58 for d

_{s}/L

_{a}and d

_{s}/Y, respectively. For the current study, the dataset has a standard deviation of 0.25 and 0.40 for d

_{s}/L

_{a}and d

_{s}/Y, respectively. It was noticed from the comparison that the developed equations can predict d

_{s}/L

_{a}and d

_{s}/Y significantly when required input parameters such as Froude’s number and water depth are known. When compared to previous research, the comparison between studies not only confirms the accuracy of the findings but also highlights the creative methodology used in this study. Based on a predictive equation derived from Python code, predictive values of scour depth are shown in Figure 10.

_{s}, L

_{a}, is the scour depth and length of abutment, and F

_{r}, Y, is the Froude’s number and water depth in a flume.

#### 3.5. Temporal Variation of Scour

## 4. Discussion

_{s}/L

_{a}and d

_{s}/Y were determined in each case, such as without and with countermeasures. It was noticed that the ratios d

_{s}/L

_{a}and d

_{s}/Y increased with increasing Froude’s number, and the maximum values were 4.55 and 10.55, respectively. Similarly, d

_{s}/L

_{a}and d

_{s}/Y were also determined using marble and brick waste, and the maximum reduction was noticed to be 55% and 57%, respectively. To examine the abutment length and water depth effects on the scour depth, an equation was developed. For this purpose, a Python code was generated considering three variables, including the Froude’s number, water depth as the independent variable, and d

_{s}/L

_{a}and d

_{s}/Y as the dependent variables. The equation was also used in previous research for comparison purposes [52,53,54]. It was noticed from the comparison that the developed equations can predict d

_{s}/L

_{a}and d

_{s}/Y significantly when required input parameters such as Froude’s number and water depth are known. When compared to previous research, the comparison between studies not only confirms the accuracy of the findings but also highlights the creative methodology used in this study.

## 5. Conclusions

- The scour depth around the bridge abutment increased by increasing the initial Froude’s number. The maximum increment in a scour depth without countermeasure for the range of Froude’s number from 0.13 to 0.22 was observed to be 40%. This was because increasing Froude’s number implies that an increase in a flow velocity that interacts with the exterior face of abutments directly results in significant scouring.
- When marble waste was used as a countermeasure, it was noticed that some particles (marble waste) flowed with water and some were deposited near the exterior face of an abutment, which caused resistance to the flow against scouring. Therefore, the maximum reduction in scouring around the abutment was noticed compared to without any countermeasure. The maximum reduction in scour depth was observed to be 55% when marble was used as a countermeasure. But scour depth increases with increasing flow discharge, and the minimum and maximum scour depths were 0.037 m and 0.062 m, respectively.
- The maximum reduction in scour depth was observed to be 40% when brick waste was used as a countermeasure. The scour depth increases with increasing flow discharge, and the minimum and maximum scour depths were 0.049 m and 0.083 m, respectively.
- In the case when marble waste was used as a countermeasure, it was noticed that scour reduction was 15% higher compared to the case when brick waste was used as a countermeasure. This difference in scour reduction was because of the sample size in both scenarios. The size of the marble waste was larger than the brick waste, which was retained near the exterior face of the abutment, which caused a greater reduction in scour depth, whereas most of the brick waste used to flow with water and exposed the exterior face of the abutment after some time, hence causing a smaller reduction in scour depth.
- For considering the case without countermeasure, the maximum d
_{s}/L_{a}(4.55) and d_{s}/Y (10.55) were observed for the Froude’s number of 0.22. The maximum d_{s}/L_{a}and d_{s}/Y for marble and brick waste were observed to be 2.30, 4.71, and 2.73, 6.3, respectively. The maximum reduction in d_{s}/L_{a}and d_{s}/Y when marble waste was used as a countermeasure was 55%, and for brick waste, it was reduced up to 40% and 57%, respectively.

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 1.**(

**a**) Schematic diagram of the channel with the abutment model. (

**b**) Abutment specification and schematic diagram. (

**c**) Selected marble waste for the present research. (

**d**) Selected brick waste for the present research.

**Figure 2.**Laboratory setup of abutment model (

**a**) Model setup in a flume (

**b**,

**c**) scour pattern around abutment (

**d**) abutment model with marble waste (

**e**) abutment model with brick waste (

**f**) scour profile around abutment.

**Figure 3.**Scour around abutment without countermeasure with different Froude’s numbers (

**a**) scour profile around abutment (

**b**) maximum scour depth around abutment without countermeasure.

**Figure 4.**Contour of different experimental cases without countermeasure with different Froude’s numbers (

**a**) F

_{r}= 0.13 (

**b**) F

_{r}= 0.14 (

**c**) F

_{r}= 0.16 (

**d**) F

_{r}= 0.18 (

**e**) F

_{r}= 0.22.

**Figure 5.**Scour around abutment under different flow conditions using marble waste as a countermeasure with different Froude’s numbers (

**a**) scour depth for different flow conditions (

**b**) maximum scour depth around abutment.

**Figure 6.**Contour of different experimental cases using marble waste as a countermeasure with different Froude’s numbers (

**a**) F

_{r}= 0.13 (

**b**) F

_{r}= 0.14 (

**c**) F

_{r}= 0.16 (

**d**) F

_{r}= 0.18 (

**e**) F

_{r}= 0.22.

**Figure 7.**(

**a**) Scour around abutment under different flow conditions with different Froude’s numbers using brick waste as a countermeasure (

**b**) maximum scour depth around abutment.

**Figure 8.**Contour of different experimental cases using brick waste as a countermeasure with different Froude’s numbers (

**a**) F

_{r}= 0.13 (

**b**) F

_{r}= 0.14 (

**c**) F

_{r}= 0.16 (

**d**) F

_{r}= 0.18 (

**e**) F

_{r}= 0.22.

**Figure 9.**Effect of abutment length and water depth on scour depth around the abutment with different Froude’s numbers (

**a**) Without countermeasure (

**b**) with brick waste (

**c**) with marble waste.

**Figure 11.**Temporal variation of scour around abutment with different Froude’s numbers (

**a**) without countermeasure (

**b**) with brick waste (

**c**) with marble.

Scour Countermeasures | Bridge Structure | Maximum % Age of Scour Reduction | References |
---|---|---|---|

Steel Collar and Geobags | Pier | 96 | [35] |

Combination of collar and bed sill | Pier | 68 | [13] |

Airfoil collar (Experimental) | Pier | 100 | [36] |

Airfoil collar (Numerical) | Pier | 11–100 | [37] |

Hooked collar | Lenticular Pier | 58 | [38] |

Octagonal Pier | 73 | [14] | |

Spur dike | Abutment | 47 | [39] |

Submerged vane | Abutment | 95 | [40] |

Riprap and submerged vane | Abutment | 54 | [28] |

Collar and slot | Abutment | 100 | [41] |

Collar | Abutment | 77 | [23] |

Collar | Abutment | 96 | [42] |

Collar | Abutment | 87 | [43] |

Collar | Abutment | 100 | [44] |

Collar | Abutment | 100 | [45] |

Collar | Abutment | 88 | [15,46] |

Q (m^{3}/s) | d_{50} | U (m/s) | Y (m) | F_{r} | U_{c} (m/s) | L_{a} (m) |
---|---|---|---|---|---|---|

0.019 | 0.00051 | 0.14 | 0.13 | 0.13 | 0.008 | 0.3 |

0.021 | 0.00051 | 0.16 | 0.13 | 0.14 | 0.009 | 0.3 |

0.023 | 0.00051 | 0.18 | 0.13 | 0.16 | 0.010 | 0.3 |

0.027 | 0.00051 | 0.21 | 0.13 | 0.18 | 0.012 | 0.3 |

0.033 | 0.00051 | 0.25 | 0.13 | 0.22 | 0.014 | 0.3 |

Froude’s Number (F_{r}) | d_{s} withoutCountermeasure (mm) | d_{s} with Bricks Waste (mm) | d_{s} with Marble Waste (mm) | d_{s}/Y & d_{s}/L_{a} (without Countermeasure) | d_{s}/Y & d_{s}/L_{a} (with Bricks Waste) | d_{s}/Y & d_{s}/L_{a} (with Marble Waste) |
---|---|---|---|---|---|---|

0.13 | 82 | 49 | 37 | 6.3 & 2.7 | 3.7 & 1.6 | 2.85 & 1.23 |

0.14 | 103 | 62 | 46 | 7.8 & 3.4 | 4.7 & 2 | 3.56 & 1.53 |

0.16 | 118 | 71 | 53 | 9.06 & 3.9 | 5.5 & 2.4 | 4.08 & 1.77 |

0.18 | 130 | 78 | 58 | 9.9 & 4.32 | 6 & 2.6 | 4.49 & 1.94 |

0.22 | 137 | 82 | 61 | 10.5 & 4.55 | 6.3 & 2.7 | 4.71 & 2.3 |

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## Share and Cite

**MDPI and ACS Style**

Murtaza, N.; Khan, Z.U.; Khedher, K.M.; Amir, R.A.; Khan, D.; Salem, M.A.; Alsulamy, S.
Mitigating Scour at Bridge Abutments: An Experimental Investigation of Waste Material as an Eco-Friendly Solution. *Water* **2023**, *15*, 3798.
https://doi.org/10.3390/w15213798

**AMA Style**

Murtaza N, Khan ZU, Khedher KM, Amir RA, Khan D, Salem MA, Alsulamy S.
Mitigating Scour at Bridge Abutments: An Experimental Investigation of Waste Material as an Eco-Friendly Solution. *Water*. 2023; 15(21):3798.
https://doi.org/10.3390/w15213798

**Chicago/Turabian Style**

Murtaza, Nadir, Zaka Ullah Khan, Khaled Mohamed Khedher, Rana Adnan Amir, Diyar Khan, Mohamed Abdelaziz Salem, and Saleh Alsulamy.
2023. "Mitigating Scour at Bridge Abutments: An Experimental Investigation of Waste Material as an Eco-Friendly Solution" *Water* 15, no. 21: 3798.
https://doi.org/10.3390/w15213798