The mathematical model of a rotating electrohydrodynamic flow in a thin suspended liquid film is proposed and studied. The motion is driven by the given difference of potentials in one direction and constant external electrical field Eout in another direction in the plane of a film. To derive the model we employ the spatial averaging over the normal coordinate to a film that leads to the averag...

This paper presents the heat transfer and pressure drop characteristics of a primary surface heat exchanger (PSHE) with corrugated surfaces. The PSHE was experimentally investigated for a Reynolds number range of 156–921 under various flow conditions on the hot and cold sides. The inlet temperature of the hot side was maintained at 40 ̋C, while that of the cold side was maintained at 20 ̋C. A c...

TWODEE-2 is a FORTRAN 90 code based on previous code (TWODEE). It is designed to solve the shallow water equations for fluid depth, depth-averaged horizontal velocities and depth-averaged fluid density. The shallow layer approach used by TWODEE-2 is a compromise between the complexity of CFD models and the simpler integral models. It can be used for forecasting gas dispersion near the ground an...

By exploiting an analogy with averaging procedures in fluid dynamics, we present a set of averaged template matching equations. These equations are analogs of the exact template matching equations that retain all the geometric properties associated with the diffeomorphism group, and which are expected to average out small scale features and so should, as in hydrodynamics, be more computationall...

Abstract Recurrence quantification analysis (RQA) is a well established method of nonlinear data analysis. In this work, we present new strategy for an almost parameter-free RQA. The approach finally omits the choice threshold parameter by calculating RQA measures range thresholds (in fact recurrence rates). Specifically, test ability measure determinism, to sort with respect their signal noise...

This paper studies combining `1 regularization and Markov chain Monte Carlo model composition techniques for Bayesian model averaging (BMA). The main idea is to resolve the model uncertainty issues arising from path point selection by treating the `1 regularization path as a model space for BMA. The method is developed for linear and logistic regression, and applied to sample classification in ...