NUMERICAL SIMULATION OF METAMORPHIC CRYSTALLIZATION

Numerical models of metamorphic crystallization have as their ultimate goal the creation of a comprehensive theory describing a rock's textural development, given knowledge of its thermal history, its burial history, and its kinematic history. With such a theory, one could derive tectonometamorphic information from measurable textural features; one could also extract rates of heating and compression, and insights into the character and mechanisms of deformation and chemical reaction. Numerical simulations of crystallization allow the validity of such theories to be assessed, by evaluating whether or not our conceptualizations of crystallization processes constitute a mutually consistent and geologically reasonable whole.

A comprehensive theory of this type remains a distant goal, but notable successes have been achieved by modelers who have broken the problem down into simpler processes that are treated as if they were unconnected and independent of one another. Models of intracrystalline diffusion allow chemical zoning patterns in minerals to be interpreted in light of possible thermal histories. Models simulating deformation at the grain scale capture many aspects of the mechanisms of fabric development. Models of chemical exchange via intergranular diffusion explain the evolution of complex reaction textures and provide estimates of rates of metamorphic reaction and equilibration. Models of grain coarsening constrain thermal histories and discriminate among possible mechanisms for textural development. Models of crystal nucleation and growth identify mechanisms and quantify rates of metamorphic reactions. Recently, approaches that link two or more of these techniques have begun to appear.

Our work has focused on simulating porphyroblast nucleation and growth, seeking to identify the dominant reaction mechanisms in metamorphic rocks and to constrain values for the critical kinetic parameters governing reaction rates. The most recent model calculates, via a 3-D finite-difference method, the diffusional transport of inhomogeneously distributed nutrients for crystal growth; nucleation probability is an exponential function of compositional disequilibrium in the fluid, which is buffered locally by dissolving reactants and varies over space and time as the reaction progresses.