Periodic forcing of multiple inputs and the role of binary interactions between multiple inputs are analyzed in detail.
Pertinent analytical observations, which are applicable to continuous processes in general, are made about operations involving periodic forcing of multiple inputs.
Mixing is controlled via periodic velocity forcing of one of the input streams, and is due to amplification of the perturbation as described by instability and receptivity theory.
In every damping state of each semi-active damper the method provides the optimal matching values of the active forcing inputs.
As the dampers switch during operation the whole system's structure differs, and then values of the active forcing inputs are adapted to match these rapid changes.
It is true that every commodity is produced along what economists call a "cost curve" — raising output may lower average or marginal unit costs by spreading overhead or achieving economies of scale, but it may also raise costs by forcing up the cost of inputs or incurring diseconomies of scale.
It is shown that the approach is robust to inherent modeling errors in the description of the system and forcing input, providing accurate prediction of the dynamic response when the excitation history is unknown.
This study presents an application of the artificial neural network (ANN) to assess salinity variation responding to the multiple forcing functions of freshwater input, tide, and wind in Apalachicola River, Florida.
More precisely, the conventional deterministic optimum design, based on the assumption that the only source of uncertainty concerns the forcing input, is compared to robust single-objective and multi-objective optimum design methods.
Theoretical and experimental trajectories are then compared, by way of time domain plots as well as via contour plots linking the amplitude of backlash oscillation to the amplitude and phase of input forcing.
The sequential DA procedure is based on (1) a multivariate rainfall ensemble generator, which provides spatial and temporal correlation error structures of input forcing, and (2) lagged particle filtering to update past and current state variables simultaneously in a lag-time window to consider the response times of internal hydrologic processes.
