The main purpose of this contribution is to discuss the impact of Automatic Differentiation in the field of dynamic simulation of chemical engineering processes. The theoretical exactness of the AD comes from the fact that it uses the same rules of differentiation as in differential calculus, but these rules are applied to an algorithmic specification of the function rather than to a formula. The values for the derivatives obtained with AD are exact (to roundoff). That technique permits the automatization of the differentiation step, crucial for dynamic simulation and optimization of processes. ![]() Automatic Differentiation is a relatively recent technique developed for the differentiation of functions applicable directly to the source code to compute the function written in standard programming languages.
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