A block ramp is an environmentally friendly stream restoration structure consisting of a base material of stone with minimal negative environmental impact. This not only decreases riverbed shear stress but also increases the flow resistance, thus reducing excess kinetic energy of the flow. This study used two mathematical models that were developed in a dimensionless form for smooth and rough-bed ramps. The models were calibrated and validated by two sets of experimental tests. A total of 308 experimental runs were done with eight different ramp slopes and six different gravel material sizes. The experimental results indicated that an increase in the relative roughness enhances energy dissipation. Additionally, energy dissipation increases along with an increase of ramp slope. Using a gene-expression programming soft computing model, two mathematical models were developed to estimate energy dissipation on smooth and rough-bed ramps. Additionally, the energy-loss performance of two configurations of interlocked and dumped blocks ramps was compared.

Leakages in pipes lead to water loss, so leak detection to prevent water loss is essential. Transient flow is a method to obtain a wide range of pipe flow data, but generally, signal data have various noises also related to leakages. One effective way to detect leaks is to use wavelet transform (WT). So, in this study, by conducting laboratory experiments and using WT, the behavior of the signal and the effectiveness of wavelet transform were investigated. Results of the research showed that WT is very effective for leak detection, noise reduction, and signal analysis for transient flow.