The steepest-entropy-ascent quantum thermodynamic (SEAQT) framework is used to model the decoherence\ud
that occurs during the state evolution of two different microscopic composite systems. The test cases are a\ud
two-spin-1/2-particle composite system and a particle-photon field composite system like that experimentally\ud
studied in cavity quantum electrodynamics. The first system is used to study the characteristics of the nonlinear\ud
equation of motion of the SEAQT framework when modeling the state evolution of a microscopic composite\ud
system with particular interest in the phenomenon of decoherence. The second system is used to compare the\ud
numerical predictions of the SEAQT framework with experimental cavity quantum electrodynamic data available\ud
in the literature. For the two different numerical cases presented, the time evolution of the density operator of\ud
the composite system as well as that of the reduced operators belonging to the two constituents is traced from\ud
an initial nonequilibrium state of the composite along its relaxation towards stable equilibrium. Results show for\ud
both cases how the initial entanglement and coherence is dissipated during the state relaxation towards a state of\ud
stable equilibrium
This paper describes the upper level of a two-tiered sustainability assessment framework (SAF) for determining the optimal synthesis/design and operation of a power network and its associated energy production and storage technologies. The upper-level framework is described, and results for its application to a test bed scenario given by the Northwest European electricity power network presented. A brief description of the lower level of the SAF is given as well. In order to analyze the impact of microgrids (MGs) in the main network, two different scenarios are considered in the analysis, i.e., a network without MGs and a network with MGs. The optimization is carried out in a multi-objective, quasi-stationary manner with producer partial-load behavior taken into account via nonlinear functions for efficiency, cost, and emissions that depend on the electricity generated by each nonrenewable or renewable producer technology. Results indicate for the particular problem posed and for the optimal configurations found that including MGs improves the network relative to reductions in capital and operating costs and to increases in network resiliency. On the other hand, total daily SO2 emissions and network exergetic efficiency are not improved for the case when MGs are included.
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