Sentence examples for simulation and nonlinear from inspiring English sources

As a result, the diagram of simulation and nonlinear regression (for m = 1) in Fig. 3, are slightly different from each other.

Based on Monte Carlo simulation and nonlinear finite element analyses, the code-based expression for B2 is revised with a random variable K replacing the constant numerator.

It can be figured out from these diagrams that the obtained data in simulations is perfectly coinciding with the proposed formula so that five out of six branches coincide in a way that almost no difference can be observed between simulation and nonlinear regression.

Dynamic simulations and nonlinear dynamic analysis are performed for recovery of acetic acid from waste waters by esterification with n-butanol, which is an interesting alternative to nonreactive separation processes.

Equivalent nonlinear fracture models for pristine and reconstructed one- and two-atom vacancy defected single wall carbon nanotubes are developed by using the molecular mechanics based models where the initial reconstructed nanotube models are obtained by using molecular dynamic simulations and nonlinear characteristic of the covalent bonds are obtained by using the modified Morse potential.

His areas of research include process modeling and simulation, linear and nonlinear intelligent adaptive control.

We present a novel Lagrangian particle method for the simulation of linear and nonlinear elastic models of soft tissue.

Efficient spectral and pseudospectral algorithms for simulation of linear and nonlinear 3D whistler waves in a cold electron plasma are developed.

To prove the tendency, simulations using linear and nonlinear dopant drift memristor models are performed in the Cadence simulation environment.

The model incorporates molecular simulations and a nonlinear, continuum mechanics-based, constitutive formulation that incorporates the behavior of the polymer materials as predicted from molecular simulations.

A multi-stage OP estimation approach was developed, including inverse NN models trained with data from two-layer Monte Carlo (MC) simulations and a nonlinear spectral fitting algorithm.