Model coupling is a well-known method employed to simulate complex multiphysics and multiscale phenomena. Approaches have concentrated on coupling parallel models involving static data distribution among processes without the consideration of top-level dynamic load balancing. Malleability, the ability to change during execution the number of processes in an application, allows applications to c...

Drying represents one of the oldest unit operations employed in industrial processes. Drying is viewed as a process of simultaneous heat and mass transfer. Porous Clay-like material undergoes stresses due to non-uniform distribution of temperature and moisture induced by heat and mass transfer respectively. The aim of this work is to simulate the stresses induced by heat and mass transfer durin...

Bursting neurons are characterized by an alternation of active and inactive state, during the active state they exhibit train of spikes and quiescent behavior in the inactive state.When bursting neurons are coupled they can synchronize depending on the coupling strength. If the coupling strength is increased above a critical value, a transition from an asynchronous state to a partial synchroniz...

simulation of groundwater fluctuations plays a crucial role in management of watersheds and water demand balancing. recently, wavelet analysis has been used widely in time series decomposition and coupling with neural networks for hydrological modeling. in this paper, the ability of the wavelet-dynamic artificial neural networks (w-ann) model was applied in forecasting one-month-ahead of ground...

The effect of adding extra inlet channels on the operation of the Stairmand Cyclone has been investigated numerically. The Reynolds stress model (RSM) and Eulerian-Lagrangian method were used to investigate the complex turbulent flow and cyclone performance. The impacts of one-way coupling and two-way coupling models on the cyclone efficiency and the calculation of cut-off size diameter were ex...