Numerical Simulation of Hydraulic Jump over Rough Beds

Abstract

In this study, the hydraulic jumps over rough beds are numerically simulated. In order to calibrate the numerical model, the experimental data were used, which performed in a rectangular flume in various roughness arrangements and different Froude numbers. The effect of the distance (s) and the height (t) of the roughness on different characteristics of the hydraulic jump, including the sequent depth ratio, water surface profile, jump’s length, roller’s length, and velocity distribution were evaluated and compared. The results showed that the numerical model is fairly well able to simulate the hydraulic jump characteristics. The results also showed that the height and distance of roughness slightly reduced the sequent depth ratios for all Froude numbers. Also, the hydraulic jump length is reduced at the presence of the rough bed. Velocity profiles in different experiments were similar and there was a good agreement between simulated and measured results. Also, increasing the distance and the height of the roughness will slow down the velocity near the bed, increase the shear stress, and increase the gradient of the velocity distribution near the bed.

Numerical Investigation of Critical Hydraulic Parameters Using FLOW-3D: A Case Study of Taunsa Barrage, Pakistan

“…However, as compared with lower tailwater levels, the values for TKEs in 129.40 m tailwater were found to be lower and the TKEs levelled off earlier within and after the HJ. In the HJ regions, following the similar trends for the 129.10 and 129.40 m tailwater levels, the TKEs in the 129.70, 129.99, and 130.30 m tailwater levels reached 3.20, 3.15, and 2.90 m 2/ s 2 , respectively, and their values decreased after the HJ, as illustrated in Figure 15c-e. Additionally, the results for the TKEs showed a trend that was noted in the numerical studies (Nikmehr and Aminpour [71]; Soori et al [76]). Figure 16 shows 2D illustrations of turbulent kinetic energies captured using RNG-K-ε at five different tailwater levels.…”

“…The above-mentioned turbulence models were applied by Bayon-Barrachina and Lopez-Jimenez [4], Macián-Pérez [9], and Bayon et al [50] to investigate the HJ characteristics and the results showed that RNG K-ε produced reasonable accuracy for the efficiency of the HJ, sequent depths, roller lengths, and turbulent kinetic energy. Similarly, Nikmehr and Aminpour [71] also used RNG K-ε to investigate the free surface profile, flow rate, and Fr 1 on the corrugated bed and the model results were well in agreement with the compared experiments. Furthermore, studies such as those by Carvalho et al [56], Savage and Johnson [72], and Johnson and Savage [73] investigated HJ characteristics within the stilling basins of spillways and indicated that the RNG K-ε turbulence model produced free surface, velocity, pressure profiles, and turbulent kinetic energy that were well in agreement with the experimental results.…”

Numerical and analysis effects of rectangular prism rough beds on hydraulic jumps in open channels

“…The RNG k- turbulent model is more accurate than the standard k- model for simulating hydraulic jumps on rough beds. This is because it can consider the effect of small-scale vortex motion [12,15]. The VOF approach was used to track the free water surface.…”

Experimental investigation of hydraulic jump characteristics in sloping rough surfaces for sustainable development

“…Their findings showed that when bed roughness rises, the depth ratio does as well. A lot of work by many researchers has been performed experimentally [18][19][20][21][22][23] as well as numerically [24][25][26][27][28][29] to predict the jump behaviour in rough sloping surfaces.…”