This section describes the common parts of the model with its experimental setup (i.e., the dynamic framework, turbulence model, and external forcing).
A new construction control method is presented using H∞ theory, considering uncertainties in the mechanics model and external noise in the construction site parameters.
Using an accurate bootstrap current model and external current drive profiles from ray tracing calculations in combination with optimized pressure profiles, βN values above 7.0 have been obtained.
"Static function" has an assessment is for static functions, "dynamic function" has an assessment that could vary based on the model and "external function" has an assessment that may change as a result of external factors independent from the model.
This finding is robust under both pooled time-series and cross-section data estimation and panel data analysis and for different types of patent applications (invention, utility model, and external design).
This chapter outlines some ways of performing schema abstraction, enabling the modeler to focus on various aspects of a schema by hiding other details and presents an overview of process modeling and external schema design.
Model performance was assessed using internal (from the data used to develop the model) and external (from an additional data set not used in the model development) validation.
Finally, we used internal validation to evaluate the accuracy of the model, and external validation based on independent data would be useful to validate the model further.
Strengths of the study included meticulous model structure, assumptions, model inputs, and external validation of the model; and the exceptional care taken to model the Dutch population.
Finally, the simulation results of the nonlinear approximate model, subjected to model uncertainties and external disturbances, with the designed model predictive controller are presented.
