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稳定性诱导的优化及在稳态附近的有限控制作用。

Optimization induced by stability and the role of limited control near a steady state.

机构信息

Departamento de Física Aplicada, Universidad de Salamanca, 37008 Salamanca, Spain.

Instituto Universitario de Física Fundamental y Matemáticas (IUFFyM), Universidad de Salamanca, 37008 Salamanca, Spain.

出版信息

Phys Rev E. 2019 Dec;100(6-1):062128. doi: 10.1103/PhysRevE.100.062128.

DOI:10.1103/PhysRevE.100.062128
PMID:31962470
Abstract

A relationship between stability and self-optimization is found for weakly dissipative heat devices. The effect of limited control on operation variables around an steady state is such that, after instabilities, the paths toward relaxation are given by trajectories stemming from restitution forces which improve the system thermodynamic performance (power output, efficiency, and entropy generation). Statistics over random trajectories for many cycles shows this behavior as well. Two types of dynamics are analyzed, one where an stability basin appears and another one where the system is globally stable. Under both dynamics there is an induced trend in the control variables space due to stability. In the energetic space this behavior translates into a preference for better thermodynamic states, and thus stability could favor self-optimization under limited control. This is analyzed from the multiobjective optimization perspective. As a result, the statistical behavior of the system is strongly influenced by the Pareto front (the set of points with the best compromise between several objective functions) and the stability basin. Additionally, endoreversible and irreversible behaviors appear as very relevant limits: The first one is an upper bound in energetic performance, connected with the Pareto front, and the second one represents an attractor for the stochastic trajectories.

摘要

在弱耗散热设备中发现了稳定性和自优化之间的关系。有限控制对稳定状态附近操作变量的影响是,在不稳定性之后,弛豫的路径由恢复力产生的轨迹给出,这些轨迹可以提高系统的热力学性能(功率输出、效率和熵产生)。在许多循环的随机轨迹上进行统计也表明了这种行为。分析了两种类型的动力学,一种是稳定盆地出现的动力学,另一种是系统全局稳定的动力学。在这两种动力学下,由于稳定性,控制变量空间中会出现一种诱导趋势。在能量空间中,这种行为转化为对更好热力学状态的偏好,因此在有限控制下稳定性可能有利于自优化。从多目标优化的角度进行了分析。结果表明,系统的统计行为受到 Pareto 前沿(在几个目标函数之间具有最佳折衷的点集)和稳定盆地的强烈影响。此外,内可逆和不可逆行为表现为非常相关的极限:第一个是与 Pareto 前沿相关的能量性能上限,第二个代表随机轨迹的吸引子。

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