Contribution of cellular automata to the understanding of corrosion phenomena

We present a stochastic CA modelling approach of corrosion based on spatially separated electrochemical half-reactions, diffusion, acido-basic neutralization in solution and passive properties of the oxide layers. Starting from different initial conditions, a single framework allows one to describe generalised corrosion, localised corrosion, reactive and passive surfaces, including occluded corrosion phenomena as well. Spontaneous spatial separation of anodic and cathodic zones is associated with bare metal and passivated metal on the surface. This separation is also related to local acidification of the solution. This spontaneous change is associated with a much faster corrosion rate. Material morphology is closely related to corrosion kinetics, which can be used for technological applications.Comment: 13 pages, 9 figure

Model-based prognosis for intergranular corrosion

Among the advantages of Aluminium-based alloys for structural use is their corrosion resistance. However, while Aluminium alloys are highly resistant to uniform (general) corrosion, they are much more susceptible to types of localised corrosion, especially intergranular corrosion, which is a localised attack along the grain boundaries which leaves the grains themselves largely unaffected. In order to estimate the progress of such corrosion in a given sample, it is considered possible to generate a numerical model of some sort. While there has been much effort spent in the development of electrochemistry-based models, the use of grey and black-box models remains largely unexplored. One exception to this is the use of Cellular Automata (CA) models which have recently been exploited to model the progression of uniform corrosion. The object of the current paper is to apply the CA methodology to the case of intergranular corrosion. The first phase of the work has been concerned with generating appropriate CA rules which can qualitatively reproduce observed physics, and this work is reported here. A model is proposed which shows qualitative agreement with experimental data on the advance of the corrosion front

COMPUTER SIMULATION AND COMPUTABILITY OF BIOLOGICAL SYSTEMS

The ability to simulate a biological organism by employing a computer is related to the ability of the computer to calculate the behavior of such a dynamical system, or the "computability" of the system.* However, the two questions of computability and simulation are not equivalent. Since the question of computability can be given a precise answer in terms of recursive functions, automata theory and dynamical systems, it will be appropriate to consider it first. The more elusive question of adequate simulation of biological systems by a computer will be then addressed and a possible connection between the two answers given will be considered. A conjecture is formulated that suggests the possibility of employing an algebraic-topological, "quantum" computer (Baianu, 1971b) for analogous and symbolic simulations of biological systems that may include chaotic processes that are not, in genral, either recursively or digitally computable. Depending on the biological network being modelled, such as the Human Genome/Cell Interactome or a trillion-cell Cognitive Neural Network system, the appropriate logical structure for such simulations might be either the Quantum MV-Logic (QMV) discussed in recent publications (Chiara, 2004, and references cited therein)or Lukasiewicz Logic Algebras that were shown to be isomorphic to MV-logic algebras (Georgescu et al, 2001)

Mathematical models of avascular cancer

This review will outline a number of illustrative mathematical models describing the growth of avascular tumours. The aim of the review is to provide a relatively comprehensive list of existing models in this area and discuss several representative models in greater detail. In the latter part of the review, some possible future avenues of mathematical modelling of avascular tumour development are outlined together with a list of key questions

The identification of cellular automata

Although cellular automata have been widely studied as a class of the spatio temporal systems, very few investigators have studied how to identify the CA rules given observations of the patterns. A solution using a polynomial realization to describe the CA rule is reviewed in the present study based on the application of an orthogonal least squares algorithm. Three new neighbourhood detection methods are then reviewed as important preliminary analysis procedures to reduce the complexity of the estimation. The identification of excitable media is discussed using simulation examples and real data sets and a new method for the identification of hybrid CA is introduced