Abstract:The paper presents the results of an experimental study carried out to investigate the effect of geometric and hydraulic parameters on energy dissipation and location of the hydraulic jump, with a change in the height of roughness elements and the divergence of walls in different discharges. Experiments were conducted in a horizontal rectangular basin with gradual expansion 0.5 m wide and 10 m long. Four physical models were fixed in the flume. The measured characteristics of the hydraulic jump with different divergences ratio (B = b 1 /b 2 = 0.4, 0.6, 0.8, 1) and the inflow Froude numbers (6 < Fr 1 < 12) were compared with each other and with the corresponding values measured for the classical hydraulic jump. The results showed that the tailwater depth required to form a hydraulic jump and also the roller length of the hydraulic jump and the length of the hydraulic jump on a gradual expansion basin with the rough bed were appreciably smaller than that of the corresponding hydraulic jumps in a rectangular basin with smooth and rough bed. With the experimental data, empirical formulae were developed to express the hydraulic jump characteristics relating to roughness elements height and divergence ratio of wall. Also, the applicability of some empirical relationships for estimating the roller length was tested.

Pressure fluctuations are a key issue in hydraulic engineering. However, despite the large number of studies on the topic, their role in spatial hydraulic jumps is not yet fully understood. The results herein shed light on the formation of eddies and the derived pressure fluctuations in stilling basins with different expansion ratios. Laboratory tests are conducted in a horizontal rectangular flume with 0.5 m width and 10 m length. The range of approaching Froude numbers spans from 6.4 to 12.5 and the channel expansion ratios are 0.4, 0.6, 0.8, and 1. The effects of approaching flow conditions and expansion ratios are thoroughly analyzed, focusing on the dimensionless standard deviation of pressure fluctuations and extreme pressure fluctuations. The results reveal that these variables show a clear dependence on the Froude number and the distance to the hydraulic jump toe. The maximum values of extreme pressure fluctuations occur in the range 0.609<X<3.385, where X is dimensionless distance from the toe of the hydraulic jump, which makes it highly advisable to reinforce the bed of stilling basins within this range.

Low-crested and submerged breakwaters are frequently employed as coastal defence structures. Their efficiency is governed by wave energy dissipation, and the wave transmission coefficient can evaluate this parameter. The current study conducts experimental investigations on both low-crested and submerged breakwaters exposed to different wave conditions to compare their performance with that of emerged breakwaters. The current study provides a comprehensive review of existing formulae and highlights the impact of design variables. To evaluate the reliability of each existing formula, four “reference” configurations are used. Having these structures at the same overall volume, the results also provide a useful tool for engineers involved in the lowering operation of existing breakwaters. Nature and magnitude of governing parameters are investigated, and some points of criticism are outlined. The comparison results show that few of the existing equations give reliable estimates of the transmission coefficient for all the models tested in this study. Higher values of root mean square error are related to the emerged breakwater rather than the submerged ones. To obtain information about the transmitted wave energy, spectral analysis is applied as well. Different behaviours of the transmitted spectrum, n terms of shape and peak frequency, are highlighted. The results improve the overall knowledge on formulae that are in the literature, in order to make the user more aware.

The hydraulic behavior of a hydraulic jump can be challenging to estimate in order to design gradually expanding stilling basins with roughness elements on the bed. In this study, five dependent variables were identified that comprise: (i) the sequent depth ratio; (ii) the relative length of the jump; (iii) the relative roller length of the jump; (iv) the relative energy dissipation; and (v) the water surface profile. This study undertook a set of formulations based on the regression analysis and Sugeno Fuzzy Logic (SFL) to predict these variables based upon experimental data. Results demonstrate that the trained SFLs predicted the behavior of the dependent variables with the Nash–Sutcliffe Coefficient (NSC) greater than 0.96 in the testing phase. In contrast, the NSC values for the regression models are greater than 0.79. The higher accuracy of SFL is attributed to its capability in managing uncertainty and imprecise data owing to water surface profile oscillations of the hydraulic jump. Also, the results indicate that the prediction residuals for SFL are homoscedastic for all hydraulic parameters investigated except for the water surface profile, which prediction residuals for the regression equations are heteroscedastic.