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Eventually, simple models need to be translated to more robust ones where cells, tissues, and entire organisms are incorporated.
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The first simple models needed only in-cylinder pressure data but presented a great disadvantage: the assumption of a constant value for the polytrophic exponent [5].
Hence, a simple model needs to be used that requires minimum data inputs in determining fracture parameters.
LIDE with mixture of 10 components requires about 3 min. LIDE with simple model needs less than 3 s, that is more than 130 times faster than AHE.
A simple model needs to be accurate and quick to use, but most importantly should require a minimum amount of input data to construct the model.
When polymer molecules in solution begin to restrict the space available for movement of other chains, the solution is no longer dilute, and our simple model needs modification.
Relatively simple models are needed for the design of nonlinear model predictive controllers (NMPC) which are implemented on-line via repeated solution of a constrained nonlinear optimization problem.
Also, the uniaxial material models of steel and concrete in OpenSees are too simple, and more sophisticated models need to be created.
The optimum design of these structures needs simple models of the corrugated panels that may be incorporated into multi-disciplinary system models.
Therefore, there is also a need for simple models that are easy to apply but still capture the main features of the underlying processes.
The key motivation for model reduction is the need for simple models that nevertheless capture the important features of complex dynamic systems.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com