Effect of blocked trash rack on open channel infrastructure

A_b

wetted area of the box-shaped plate

A_s

wetted area of the bars and supports

A_t

total wetted area of the rack field

B

blockage ratio as presented in Equation (2)

d

depth of box-plate blockage in the vertical direction

E_u

energy at upstream

F_o

approach flow Froude numbers

F_u

upstream Froude numbers in case of rack blockage

g

gravitational acceleration

h_d

downstream water depth

h_m

maximum depth of the depression

h_o

approach flow depth

h_u

upstream water depth

L_d

length of the free-surface depression

Q

flow discharge

R_o

approach Reynolds number

U_o

approach flow velocity

U_u

upstream mean velocity

α

rack angle

Δ E_ud

energy loss

Δh

hydraulic head loss

ξ

head loss coefficient

υ

kinematic viscosity

One main difficulty that confronts stream crossing structures is debris. This debris can accumulate at the openings and culverts of bridge structures, producing a damaging impact on the structure's operations (Chang & Shen 1979; Diehl 1997). The trash rack is one main countermeasure that is used to trap debris and stop it from entering open structures and causing undesirable outcomes (Bradley et al. 2005; EA 2009). However, debris racks face a major hazard with harmful consequences caused by rack clogging (EA 2009). Trash rack blockage can block the waterway openings and increase the backwater, thereby increasing the potential for flooding and destroying nearby infrastructure.

Many researchers have investigated the accumulation and impact of debris at river structures (Stockstill et al. 2009; Weitbrecht & Rüther 2009; Tamagni et al. 2010). In their field study, Ibrahim et al. (2015) investigated the debris accumulation upstream of the hydroelectric power station of New Naga Hammady Barrages in the Nile River. This research aimed to investigate the impact of debris accumulation at the trash racks of hydroelectric facilities and turbines, which negatively affected electricity production. In addition, the racks were designed for specific locations to counter transported debris from high-yield source areas before reaching the hydroelectric power station or turbine racks.

In most previous studies, the hydraulic conditions or head losses of racks were, for example, by using the effect of bar thickness, spacing, or blockage ratio (e.g. Kirschmer 1926; Osborn 1968; Clark et al. 2010; Raynal et al.2013a, 2013b; Albayrak et al. 2018). However, examining different bar thicknesses or spacings as blockages without attaching debris does not adequately represent the natural blockage effect on the trash racks because of the differences in the blockage locations and distributions. Josiah et al. (2016) examined an inclined trash rack with circular bars; they used clear bar spacings of 5 and 10 mm and bar diameters of 2, 3, 6, 8, 10 mm to obtain different blockage ratios that varied from 0.17 to 0.68 during the study. Based on their results, they proposed the head loss equation by using all possible parameters that affected rack losses, such as the blockage ratio, unit discharge, and inclination angle with the channel bed. Böttcher et al. (2019) experimentally compared the trash rack with circular bars and fish protection systems (flexible fish fence made using horizontal cables instead of bars for different bar and cable spacings). The results showed that the head loss coefficient was independent of the tested Bar–Reynolds number. In addition, a design equation was proposed to estimate the head loss for both rack options. A few studies have been performed for flow through bar racks using numerical analyses (e.g. Hermann et al. 1998; Meusburger et al. 1999), as exemplified by Tsikata et al. (2014).

Several studies have been performed to understand the characteristics of turbulent flow around cylinders (Nakagawa et al. 1999; Dutta et al. 2003; Agelinchaab et al. 2008). Agelinchaab et al. (2009) exemplified how Knisely (1990) and Matsumoto (1999) presented excellent reviews of flows around rectangular cylinders. Agelinchaab et al. (2009) studied the turbulence characteristics of pairs of identical rectangular and streamlined cylinders in an open channel of varying cylinder inclinations using particle image velocimetry. They observed that a strong asymmetric flow pattern occurred when the cylinder inclination increased. In addition, the induced asymmetric hydrodynamic loads could lead to more vibration problems and eventually to structural failures.

Most studies on rack hydraulic conditions, in particular, on head loss due to blockages have focused on the bar spacing or the thickness. However, a knowledge gap exists on the hydraulic rack losses related to the blockages from debris clogging; these blockages have been simplified into a horizontal box shape in this study. Furthermore, to the best of our knowledge, no former study has addressed detailed descriptions about the characteristics of free-surface depression using designing equations because of predefined horizontal blockages. Therefore, this experimental study is aimed at clarifying the effects of various rack blockages arising from debris on the head loss and the length and maximum depth of the free-surface depression downstream of the rack for a vertical trash rack with a fixed bed.

The flume experiments were conducted in a trapezoidal open channel at the Hydraulic Laboratory of Channel Maintenance Research Institute, National Water Research Center, Egypt. The channel was 16.22 m long, 0.42 m deep, and 0.6 m wide. The experimental equipment has been described in greater detail in Zayed et al. (2018a, 2018b).

To study the rack hydraulic behaviors, a rack was placed vertically and perpendicular to the channel within a fixed bed 8 m downstream of the intake. The rack always consists of vertical mild steel bars that are circular; they are 3 mm in diameter, 25 cm deep, and have a clear spacing of 20 mm. The welded rack bars were supported by outer bars and fixed to the flume side wall. The outer supporting structure was minimized, and consequently the rack itself (bars and outer supports) had hardly any influence on the head loss and approach flow conditions.

The effect of F_o and B on ξ was examined in the range of F_o = 0.06–0.12 and B = 0.08, 0.13, 0.25, 0.32, 0.45, 0.50, 0.64, and 0.69. In Figure 2, ξ is plotted as a function of B for various F_o. As shown by Zayed et al. (2018a, 2018b, 2020), the head loss coefficient increases strongly with B. This is because the increasing blockage ratio decreases the rack surface area, which results in an increased ξ value. Regarding the blockage ratio effect, the rack with B = 0.25, 0.32, 0.45, 0.50, 0.64, and 0.69 increases ξ by approximately 1.6, 5, 12, 20, 31, and 45.5 times, respectively, as compared with the rack with B = 0.08 (Figure 2). This means that the blockage ratios significantly affect the rack head loss coefficients and should not be larger than 25% for additional safety. In addition, large uncertainties are observed for F_o < 0.12, which correspond to the measurements of B< 0.32 based on the head loss coefficients, in which the head losses are so low that they cannot be accurately measured; this results in high relative uncertainties. It further proves that the development of head loss as a function of the blockage ratio is not linear.

Clearly, Equation (5) has been developed for the classical screen (perpendicular and vertical to the flow direction) with box-shaped plates, which is a concept different from the bar diameters and spacings. In particular, the proposed equation is valid for 0.06 ≤ F_o ≤ 0.12, 0.08 ≤ B ≤ 0.69 and circular bars. As presented in Equation (5), the largest effective factor on ξ is the blockage ratio with an exponent of 1.84. The fit of Equation (5) has a high adjusted R² value of 0.93, which indicates a good fit to the experimental data. Moreover, the standard errors of the independent coefficients are 0.07 and 0.21, whereas the highest value represents the approach Froude number F_o and the lowest value the blockage ratio. Actually, the high standard error for F_o is due to the low velocity, which results in a low drag force; therefore, the uncertainties for F_o increase in the experimental tests. Figure 5 shows a comparison between the measured and predicted head loss by Equation (5). In Figure 5, the coefficient of determination R² and the standard error are 0.95 and 0.13, respectively. Figure 5 shows that the uncertainty zone or overestimation of Δh (highlighted in red) for the measured Δh < 0.5 cm. These points refer to Δh recorded at B < 0.25 for F_o < 0.12. Actually, this zone is consistent with the results in Figures 2 and 3 because of the low drag force (as discussed previously). Besides the uncertainty zone, 88% of the data falls within the 25% predicted range, which implies that the results are within the acceptable band. Therefore, it is recommended to apply Equation (5) for Δh > 0.5 cm.

The investigations of (1) length of the free-surface depression L_d and (2) maximum depth of the depression h_m downstream of the rack were analyzed for various blockage ratios and approach Froude numbers.

Figure 6 depicts the depression (dip) in the free-surface through the vertical rack (α = 90°, F_o = 0.06–0.12, B = 0.08–0.69) at selected streamwise locations x/h_o between −4.8 and +15.4. The upstream flow of the rack is generally streamwise, but it is not exactly uniform. Actually, slight bends occur upward near the rack because of the flow deceleration caused by the rack obstruction. Figure 6 shows the variations in depression (dip) in the free surface immediately behind the rack for different blockage ratios and reference values (no rack). The presence of the rack substantially creates flow disturbances behind the rack because of the associated flow contraction, and the degree of this disturbance or free-surface depression depends on both the blockage ratios and approach Froude numbers. As the blockage ratio and Froude number increase, the downstream flow is severely disturbed, and the depression increases as well (Figure 7 and Table 2). Then, in a region far downstream the rack, the flow converts into a uniform condition. Regarding the bed stability and level measurements, it is recommended to consider the depression characteristics in the construction processes.

For a given blockage ratio, the resulting length of the free-surface depression [see Equation (6)] can be estimated for various approach flow conditions. This equation reveals that both the governing parameters have an exponential value of 1.87 for B, which is quite close to 2.05 for F_o at 95% probability limit; this shows that there is a significant impact on L_d/h_u. The adjusted coefficient of determination of the best fit is R² = 0.95, and the standard error is 0.14. Particularly, the standard errors of the governing parameter coefficients are 0.075 and 0.2; the highest value represents F_o, and the lowest value represents B. The measured relative length of the free-surface depression L_d /h_u is plotted against the relative predicted length of the free-surface depression using Equation (6) and ±30% prediction range in Figure 10. A majority of the data points fall within ±30%; therefore, Equation (6) can be applied to estimate the length of the free-surface depression downstream of a vertical rack due to blockage. Based on Equation (6), as B increases from 0.08 to 0.25 and 0.32, the equation yields an increase of approximately 7.4 and 12.4 times in L_d/h_u, respectively, for the average F_o.

From Equation (7), both B and F_o have an exponent value of 1.68 at 95% probability limit, which reveals significant predictive factors. The standard error of Equation (7) is 0.14, and the adjusted coefficient of determination of the best fit is R² = 0.94, which signifies a reliable fit of the experimental data. The standard errors of the B and F_o coefficients are 0.07 and 0.2, respectively, whereas the highest value represents F_o, and the lowest value represents B. Figure 12 shows the measured relative maximum depth of the depression h_m/h_u versus the relative predicted maximum depth of the depression using Equation (7) and ±20% prediction range. Actually, a majority of the data points are clustered in the prediction range, which presents a good fit to Equation (7) for describing the maximum depth of the depression for various blockages. For the average F_o, B increases from 0.08 to 0.25, whereas Equation (7) yields an increase of approximately 5.6 times in h_m/h_u. A further increase to B = 0.32, increases h_m/h_u by 9.2 times.

A majority of the previous reviews dealt with the rack blockage by changing the bar spacing or thickness and deduced the head loss equations based on this concept (Kirschmer 1926; Raynal et al. 2013a; Josiah et al. 2016). However, this concept did not consider three main critical issues. First, the independent variable in natural observation is the accumulated body of debris, which continuously changed over time at the bars rack; whereas, the bars spacing or thickness remained constant. Second, the location of the blockage can affect the rack backwater rise (Abt et al. 1992); therefore, the distribution of blockage using bar spacing or thickness differs from the natural blockage observations. Third, from practical application, the rack designer designs the bar rack for a minimum bar blockage to obtain negligible head loss; therefore, the bar shape (except for stiffness and fish-friendliness racks that require narrow bar spacing) will have limited benefits on the rack loss. The bar shape effect appears with the bar blockage ratio for bar configurations in the flow direction. In other words, the design of the high bar blockage is not useful for practical applications because the natural blockage arises from the accumulated body of debris. Hence, this study focused on the blockage resulting from the accumulation of debris at the bar racks for the different configurations to simulate natural performances.

Previous studies on backwater rise arising from large wood accumulations (Schalko et al. 2019a, 2019b) concentrated on the accumulation of volume characteristics (accumulation length, large wood diameter, compactness, and the organic fine material) at the racks. The introduction of clogging as an area of the accumulation body in this study simplifies the assessment of the blockage ratio because the evaluation of the effective debris volume or characteristics is associated with high uncertainties and estimation difficulties.

The experiments investigated the rack head loss and the characteristics of free-surface depression behind a vertical rack because of blockage by debris clogging; a horizontal box-shaped accumulation body was used. The experiments were conducted with varying blockage ratios and different approach flow conditions. The results can be summarized as follows:

• The main governing parameters to estimate ξ and the flow turbulence are B and F_o. As ξ increases with B and F_o, the relationship between ξ and B is not linear. The head loss coefficient ξ increases approximately 1.6, 5, 12, 20, 31, and 45.5 times at B = 0.25, 0.32, 0.45, 0.50, 0.64, and 0.69, respectively, compared with the rack with B = 0.08. However, at the examined range of B≤ 0.13 at F_o≤ 0.12, the rack head loss can be neglected because of the low rack blockage. Therefore, it is recommended to keep the rack with B< 25% at the range of F_o < 0.12 for additional safety.

• A design equation was deduced to estimate ξ [Equation (5)], and the application of this equation is recommended for a rack with horizontal box-shaped blockage as the clogging debris for Δh > 0.5 cm.

• The degree of flow disturbance behind the rack depends on both B and F_o. When the flow is severely disturbed, and the depression increases with increasing B and F_o. This may lead to vibration problems and consequently rack failures; therefore, increasing the rack stiffness should be considered in the design process.

• Based on the dimensionless terms, the design Equations (6,7) were deduced to estimate the length L_d and the maximum depth of the depression h_m downstream of the rack for the examined range of B and F_o; this simplified the practical applications.

This study was carried out at the Hydraulics Laboratory of Channel Maintenance Research Institute (CMRI), National Water Research Center. The authors would like to acknowledge CMRI for the technical support and cooperation.

All relevant data are included in the paper or its Supplementary Information.