The redox (Reduction-Oxidation) flow battery is one of the most promising rechargeable batteries due to its ability to average loads and output of power sources. The transient characteristics are well known as the remarkable feature of the battery. Then it can also compensate for a sudden voltage drop. The dynamics are governed by the chemical reactions, fluid flow, and electrical circuit of its structure. This causes the difficulty of the analysis at transient state. This paper discusses the transient behavior of the redox flow battery based on chemical reactions. The concentration change of vanadium ions depends on the chemical reactions and the flow of electrolysis solution. The chemical reaction rate is restricted by the attached external electric circuit. In this paper, a model of the transient behavior is introduced. The validity of the derived model is examined based on experiments for a tested micro-redox flow battery system.

In this paper, we propose a novel analysis method for large-scale networks with consideration of the behavior of the congestion control mechanism of TCP. In the analysis, we model the behavior of TCP at end-host and network link as independent systems, and combine them into a single system in order to analyze the entire network. Using this analysis, we can analyze a large-scale network, i.e. with over 100/1,000/10,000 routers/hosts/links and 100,000 TCP connections very rapidly. Especially, a calculation time of our analysis, it is different from that of ns-2, is independent of a network bandwidth and/or propagation delay. Specifically, we can derive the utilization of the network links, the packet loss ratio of the link buffer, the round-trip time (RTT) and the throughput of TCP connections, and the location and degree of the network congestion. We validate our approximate analysis by comparing analytic results with simulation ones. We also show that our analysis method treats the behavior of TCP connection in a large-scale network appropriately.

This paper presents analysis of a congestion control scheme in which a multiplexer notifies upstream traffic sources when its buffer level crosses a preset threshold. Upon notification, the traffic streams are reshaped to a form less likely to cause overflow through rate or burstiness restrictions, or a combination of the two. For the analysis, the traffic is modeled by two Markov Modulated Rate Processes (MMRP's), one for above and one for below the threshold, and an iterative fluid approximation technique is used to determine the buffer occupancy distribution. Simulation results verify the accuracy of the approach, and the analysis is used to study the effect of varying the threshold and shaping function.