We extend the Slepyan solution of the problem of a steady-state crack in an infinite ideally brittle lattice model to include dissipation in the form of Kelvin viscosity. As a demonstration of this technique, based on the Wiener-Hopf method, we apply the method to mode III cracks in a square lattice. We use this solution to find the critical velocity at which the steady-state solution becomes i...

The basic creep of concrete is the time-dependent strain caused by a sustained stress in absence of moisture movements. It is the strain observed on sealed specimens. Similar to other properties of concrete, it is dependent on the age of concrete. as a consequence of long-time chemical reactions associated with the hydration of cement. This paper formulates the solidification theory with a cont...

In this work, a fully three-dimensional constitutive model suitable for the macroscopic description of unidirectional fibre-reinforced composites where the matrix exhibits a time-dependent viscoelastic behaviour is developed. Specifically, we consider a coordinate-free formulation where the stress and strain fields can be decomposed into fibre-directional and volumetric parts on the one hand, a...

The Kelvin equation, the Gibbs equation and the Gibbs-Thomson equation are compared. It is shown that the Kelvin equation (on equilibrium vapor pressure above nano-droplets) can be derived if the inner pressure due to the curvature (from the Laplace equation) is substituted incorrectly into the external pressure term of the Gibbs equation. Thus, the Kelvin equation is excluded in its present fo...

The aim of this research was to determine the variables that characterize slate exploitability and to model spatial distribution. A generalized linear spatialmodel (GLSMs)was fitted in order to explore relationship between exploitability and different explanatory variables that characterize slate quality.Modelling the influence of these variables and analysing the spatial distribution of themod...

Experimental neuroscience increasingly requires tractable models for analyzing and predicting the behavior of neurons and networks. The generalized linear model (GLM) is an increasingly popular statistical framework for analyzing neural data that is flexible, exhibits rich dynamic behavior and is computationally tractable (Paninski, 2004; Pillow et al., 2008; Truccolo et al., 2005). What follow...