Modeling of a pressure modulated desalination system using bond graph methodology

A desalination system is a complex multi energy domain system comprising power/energy flow across several domains such as electrical, thermal, and hydraulic. The dynamic modeling of a desalination system that comprehensively addresses all these multi energy domains is not adequately addressed in the literature. This paper proposes to address the issue of modeling the various energy domains for the case of a single stage flash evaporation desalination system. This paper presents a detailed bond graph modeling of a desalination unit with seamless integration of the power flow across electrical, thermal, and hydraulic domains. The paper further proposes a performance index function that leads to the tracking of the optimal chamber pressure giving the optimal flow rate for a given unit of energy expended. The model has been validated in steady state conditions by simulation and experimentation.

Magnetic-properties of quasi-2-dimensional la1-xsr1+xmno4 and the evolution of itinerant electron ferromagnetism in the sro.(la1-xsrxmno3)n system

Quasi-two-dimensional oxides of the La,+,Sr,+,Mn04 system, possessing the KZNiF4 structure, show no evidence for ferromagnetic ordering in contrast to the corresponding three-dimensional La,+.Sr,MnO~ perovskites. Instead, there is an increasing tendency toward antiferromagnetic ordering with mcreasmg x m La,+,Sr,,, MnOp. Furthermore, these oxides are relatively high-resistivity materials over the entire compositional range. Substitution of Ba for Sr in La&r,.5Mn04 decreases the ferromagnetic interaction. Increasing the number of perovskite layers in SrO (La,-,Sr,MnO& causes an increase in electrical conductivity as well as ferromagnetic interaction. The oxide becomes a highly conducting ferromagnet when n 2 2.

Asymptotic behavior of a hierarchical system of learning automata

Learning automata arranged in a two-level hierarchy are considered. The automata operate in a stationary random environment and update their action probabilities according to the linear-reward- -penalty algorithm at each level. Unlike some hierarchical systems previously proposed, no information transfer exists from one level to another, and yet the hierarchy possesses good convergence properties. Using weak-convergence concepts it is shown that for large time and small values of parameters in the algorithm, the evolution of the optimal path probability can be represented by a diffusion whose parameters can be computed explicitly.