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The design is carried out using a model specifically developed for this technology, and taking into account the parametric variability.
Different computational methodologies have been developed to quantify the uncertain response of a relatively simple aeroelastic system in limit-cycle oscillation, subject to parametric variability.
Problems such as parametric variability and reconfiguration making, which is responsible for deciding when an reconfiguration is required, which alternative best satisfies the overall system goal, and which reconfigurations are needed in order to drive the system to the next state (i.e., an optimal state or state with a new functionality), are not covered by our research.
In order to represent a plausible mechanistic description of a biological phenomenon, the model must also replicate an essential feature of biological systems, that is robustness against inter-individual parametric variability and in vivo fluctuating environmental conditions [ 9- 12].
Nevertheless, bringing metabolic engineering on par with traditional engineering disciplines will require thorough quantitative understanding of both system dynamics, and the effects of parametric variability beyond values that nature provides.
A crucial requirement for any plausible mechanistic model of this system is that it reproduces the robustness of the bistable response observed in vivo against inter-individual parametric variability and fluctuating environmental conditions.
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Finally, parametric studies are performed for a practical example to illustrate the influences of parametric variabilities on the dynamic behaviors.
The embedded model includes a stochastic disturbance dynamics capable of estimating and correcting the electromotive contribution together with parametric uncertainty, variability and state dependence.
To estimate step time variability, a parametric modulator was designed that allowed for the examination of brain regions associated with periods of decreased automaticity.
In order to speed up the gearbox design process and to strengthen its robustness regarding specifications variability, a parametric design methodology has been developed thanks to a close collaboration between the laboratories and Eurocopter.
Figures 3- 5 show the parametric distribution of timing variability, random missed doses, and drug holidays, respectively.
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