Sentence examples for a lineal path from inspiring English sources
In this paper, we focus on a lineal path function designed to capture short-range effects and phase connectedness, which can hardly be handled by the commonly used two-point probability function.
This allows us to present a unique comparison of the entire lineal path function with the commonly used rough approximation based on the Monte Carlo and/or sampling template.
The lineal path function L (z) defines probability that a randomly sampled line segment of the specified length lies inside the particular phase.
So as to examine the properties of the lineal path function during computationally exhaustive compression and reconstruction processes, we start with an acceleration of the lineal path evaluation, namely by porting part of its code to a graphics processing unit using the CUDA (Compute Unified Device Architecture) programming environment.
Usage of the lineal path function is, however, significantly limited because of huge computational requirements.
Void-phase two-point probability function produces slightly better reconstruction than the void-phase lineal path function.
Moreover, this accelerated version of the lineal path function is then compared to the two-point probability function during the compression and reconstruction of two-phase morphologies.
Imposing void-phase lineal path function results in slight improvement over what is achieved by using the void-phase two-point probability function as the only constraint.
The morphological descriptors considered are the void-phase two-point probability function and lineal path function computed with or without the application of periodic boundary conditions (PBC).
The results demonstrate that simulated annealing technique may be used to reconstruct chalk pore networks with reasonable accuracy using the void-phase two-point probability function and/or void-phase lineal path function.
The chord length distribution and the lineal path function are two common measures that contain information on particle (or grain) shape that is independent from spatial distribution.
