ELECTRIC MODELS OF LARGE-SCALE SYSTEMS AND THEIR ANALOGY TO THERMODYNAMIC SYSTEMS

2006 ◽  
Vol 15 (04) ◽  
pp. 505-519
Author(s):  
Y. BERKOVICH ◽  
G. GOLAN

The paper deals with electric models applied in the investigation of complex systems, such as transport, economic, and neuron systems. The increasing interest in such systems can be explained by the fact that they are characterized by parallel (collective) means of complex calculation processes, under the influence of inner information processes. Electric models can also be looked upon as original structures for neuron-like systems. The paper puts emphasis on comparison between the electric models suggested by the authors, on the one hand, and the mechanical and thermal models, on the other hand. It has been shown that entropy phenomena, typical for the latter, can be closely compared to those of electric models, which are distinguished by pure electric values. Also, it has been shown that irreversible processes of energy dissipation, e.g., entropy processes in mechanical models, are corresponded to processes of energy concentration, energy transfer, and/or energy exchange in electric models. This enables us to shed a new light on processes in electric circuit, especially those concerning with structural improvements of electric circuitry and their self-organization, meaning a neg-entropic information character of these processes. Models of two economic tasks have been considered, wherein the calculation process is characterized under the influence of these processes. Assumption on the importance of reactive elements such as carriers of neg-entropy in electric circuits was made as well.

Author(s):  
Gabriel Valencia-Ortega ◽  
Luis-Antonio Arias-Hernandez

AbstractElectric circuits with transient elements can be good examples of systems where non-steady irreversible processes occur; so in the same way as a steady-state energy converter, we use the formal construction of the first-order irreversible thermodynamic to describe the energetics of these circuits. In this case, we propose an isothermal model of two meshes with transient and passive elements, besides containing two voltage sources (which can be functions of time); this is a non-steady energy converter model. Through the Kirchhoff equations, we can write the circuit phenomenological equations. Then, we apply an integral transformation to linearize the dynamic equations and rewrite them in algebraic form, but in the frequency space. However, the same symmetry for steady states appears (cross effects). Thus, we can study the energetic performance of this converter model by means of two parameters: the “force ratio” and the “coupling degree”. Furthermore, it is possible to obtain characteristic functions (dissipation function, power output, efficiency, etc.). They allow us to establish a simple optimal operation regime of this energy converter. As an example, we obtain the converter behavior for the maximum efficient power regime.


1997 ◽  
Author(s):  
◽  
Boris R. Jankovic

In this study we propose a new concept and methodology of hierarchical identification. The need for such a methodology comes from the fact that identification of large-scale systems (LSSs) by one-shot approach may be numerically very complex. The analysis of LSSs is, in general, not approached by the one-shot methodologies normally associated with non-LSSs. The proposed method of hierarchical identification can be therefore viewed as an extension of LSS methodologies to system identification. LSS methodology aims at breaking up the initial, complex problem into a set of smaller size subproblems.


2009 ◽  
Vol 19 (03) ◽  
pp. 399-418 ◽  
Author(s):  
JENS GUSTEDT ◽  
EMMANUEL JEANNOT ◽  
MARTIN QUINSON

The increasing complexity of available infrastructures with specific features (caches, hyperthreading, dual core, etc.) or with complex architectures (hierarchical, parallel, distributed, etc.) makes it extremely difficult to build analytical models that allow for a satisfying prediction. Hence, it raises the question on how to validate algorithms if a realistic analytic analysis is not possible any longer. As for some many other sciences, the one answer is experimental validation. Nevertheless, experimentation in Computer Science is a difficult subject that today still opens more questions than it solves: What may an experiment validate? What is a "good experiment"? How to build an experimental environment that allows for "good experiments"? etc. In this paper we will provide some hints on this subject and show how some tools can help in performing "good experiments", mainly in the context of parallel and distributed computing. More precisely we will focus on four main experimental methodologies, namely in-situ (real-scale) experiments (with an emphasis on PlanetLab and Grid'5000), Emulation (with an emphasis on Wrekavoc) benchmarking and simulation (with an emphasis on SimGRID and GridSim). We will provide a comparison of these tools and methodologies from a quantitative but also qualitative point of view.


1984 ◽  
Author(s):  
Dipak C. Shah ◽  
Mahmoud E. Sawan ◽  
Minh T. Tran

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