Multiscale integrated modeling

Figure 1.54. Multiscale, integrated modeling of HDI descriptive for Figure 1.53.

Figure 1 Integrated, high fidelity, multiscale process modeling of chemical supply chain.

Since the advent of efficient and robust simulation and optimization solution engines" and flowsheeting software packages that allow for relatively easy configuration of complex models, numerous integrated, high fidelity, and multiscale process model applications have been deployed in industrial plants to monitor performance and to determine and capture improvements in operating profit. 

Figure 3 Integrated, high fidelity, multiscale process modeling of C02 capture and storage. Modified based on Beyond the Molecular Frontier, NRC report (2003).

In most liquid- and solid-phase systems, the dilute approximation is typically invalid, and, as a result, many body effects play a significant role. Many body effects are manifested through the effect of solvent or catalyst on reactivity and through concentration-dependent reaction rate parameters. Under these conditions, the one-way coupling is inadequate, and fully coupled models across scales are needed, i.e., two-way information traffic exists. This type of modeling is the most common in chemical sciences and will be of primary interest hereafter. In recent papers the terms multiscale integration hybrid, parallel, dynamic,... 

Multiscale modeling of process operations. The description of process variables at different scales of abstraction implies that one could create models at several scales of time in such a way that these models communicate with each other and thus are inherently consistent with each other. The development of multiscale models is extremely important and constitutes the pivotal issue that must be resolved before the long-sought integration of operational tasks (e.g., planning, scheduling, control) can be placed on a firm foundation. 

This application illustrates that integrated, high fidelity, multiscale models from molecular level to site-wide complex can be deployed in nonideal online environments to deliver benefits and insight that cannot be elucidated with simpler, less rigorous, more empirical models. 

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