In the previous example, the entropy gradient force drove the system to maximum entropy because it was unopposed in that isolated (no particle exchange with surroundings) system. Consider now a system that is open, with A particles per unit time introduced to the left-hand side and extracted from the right-hand side:Dysfonction érectile, the entropy gradient force drove the system to maximum entropy because it was unopposed in that isolated (no particle exchange with surroundings) system. Consider now a system that is
In this case, the randomization tendency generates entropy and disorder while the source/sink removes entropy and disorder. For this particular A, balance is achieved when <n1>=75.
This example illustrates how a system's randomizing internal dynamics can act as a "force", even when the ideal conditions that enable maximum entropy to be achieved are absent.
In much the same way, nonlinear interactions in a turbulent fluid drive the system toward higher entropy, even though forcing and dissipation may act oppositely. This property can be invoked in parameterizing effects of subgrid-scale turbulence in numerical models, and in forecasting statistically the evolution of chaotic flows.
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This page reflects contribution from Bill Merryfield.