B. Lastdrager. Numerical solution of mixed gradient-diffusion equations modelling axon growth. Technical Report MAS-R0203, Centrum voor Wiskunde en Informatica, P.O. Box 94079, 1090 GB Amsterdam, The Netherlands, January 2002. Home/Search Document Details and Download
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On the Dynamics of a Mixed Parabolic-Gradient System - Krottje (2002) (Correct)
....will be analytical work. Vetwet and Sommeijer [5] used the explicit Runge Kutta Chebyshev method and found that the system is highly sensitive in its parameters and source terms with respect to bundling and debundling. A similar conclusion was reported in a second numerical paper by Lastdrager [3]. Therefore we want to gain understanding on the relative importance of parameters, the sensitivity of the dynamics with respect to these parameters and the effects that the choice of used source functions has on the dynamics, where one can think of block, cone or even functions. Hentschel 85 Van ....
B. Lastdrager. Numerical solution of mixed gradient-diffusion equations modelling axon growth. Technical Report MAS-R0203, Centrum voor Wiskunde en Informatica, P.O. Box 94079, 1090 GB Amsterdam, The Netherlands, January 2002.
Parallel Simulation of Axon Growth in the Nervous System - Wensch, Sommeijer (2002) (Correct)
....specific chemical species. Coupled with these parabolic equations we have gradient equations, describing the positions of the axons. These gradient equations are ordinary differential equations (ODEs) The model will be solved numerically, using techniques similar to those used in [7] see also [3]) For the spatial discretization of the parabolic equations we use standard second order finite differences. The gradients are approximated by bilinear interpolation. The resulting semi discrete system will be integrated in time by a second order explicit method of Runge Kutta Chebyshev (RKC) ....
....interpolation procedure to approximate the gradients, the way the 5 function in the source terms has been implemented, the time integration technique, and a discussion of a phenomenon that we will call self boost . These issues will be discussed in the next subsections. Details can be found in [3] and [7] 3.1 Spatial discretization The problem will be solved on a square domain in lR . For the spatial discretization we use a uniform grid with mesh size h. The Laplacian in (1) is approximated by the standard second order difference stencil [1 2 1] h 2, applied in both spatial ....
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B. Lastdrager, Numerical solution of mixed gradient-diffusion equations modelling axon growth, CWI, Report MAS-R0203 (2002).
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