cial neural networks have become a common tool for modeling complex “input–output” dependencies. In the past, neural network models have been used as a special class of pedotransfer functions (PTFs) using feed-forward back propagation or radial basis functions to approximate any continuous (nonlinear) function (Hecht-Nielsen, 1990; Pachepsky et al., 1996; Schaap and Bouten, 1996; Minasny and Mc...

Abstract Hydraulic impedance, as an efficient frequency-domain analysis alternative, has been widely utilized in hydraulic transient for decades. Since the mathematical expressions of systems with complicated pipe networks are usually rather complex, it is difficult traditional continuous impedance method to obtain analytical solutions system’s frequency responses directly. Therefore, equivalen...

Nowadays, hydropower plays an essential role in the energy market. Due to their fast response and regulation capacity, hydraulic turbines operate at off-design conditions with a high number of starts and stops. In this situation, dynamic loads and stresses over the structure are high, registering some failures over time, especially in the runner. Therefore, it is important to know the dynamic r...

Abstract: Solving or approximating the advection-diffusion/dispersion equation (ADE) is a challenging and important problem and has thus motivated a great deal of intense research. A specific complication arises from the nature of the governing partial differential equation: it is characterized by a hyperbolic non-dissipative advective transport term, a parabolic dissipative diffusive (dispersi...

At large scale, landscapes result from the combination of two major processes: tectonics which generate the main relief through crust uplift, and weather which accounts for erosion. This paper presents the first method in computer graphics that combines uplift and hydraulic erosion to generate visually plausible terrains. Given a user-painted uplift map, we generate a stream graph over the enti...