A multi-objective optimisation model for a general polymer electrolyte membrane fuel cell system

This paper presents an optimisation model for a general polymer electrolyte membrane (PEM) fuel cell system Suitable for efficiency and size trade-offs investigation. Simulation of the model for a base case shows that for a given output power, a more efficient system is bigger and vice versa. Using the weighting method to perform a multi-objective optimisation, the Pareto sets were generated for different stack output powers. A Pareto set, presented as a plot of the optimal efficiency and area of the membrane electrode assembly (MEA), gives a quantitative description of the compromise between efficiency and size. Overall, our results indicate that, to make the most of the size-efficiency trade-off behaviour, the system must be operated at an efficiency of at least 40% but not more than 47%. Furthermore, the MEA area should be at least 3 cm(2) W-1 for the efficiency to be practically useful. Subject to the constraints imposed on the model, which are based on technical practicalities, a PEM fuel cell system such as the one presented in this work cannot operate at an efficiency above 54%. The results of this work, specifically the multi-objective model, will form a useful and practical basis for subsequent techno-economic studies for specific applications. (C) 2009 Elsevier B.V. All rights reserved

When Backpressure Meets Predictive Scheduling

Motivated by the increasing popularity of learning and predicting human user behavior in communication and computing systems, in this paper, we investigate the fundamental benefit of predictive scheduling, i.e., predicting and pre-serving arrivals, in controlled queueing systems. Based on a lookahead window prediction model, we first establish a novel equivalence between the predictive queueing system with a \emph{fully-efficient} scheduling scheme and an equivalent queueing system without prediction. This connection allows us to analytically demonstrate that predictive scheduling necessarily improves system delay performance and can drive it to zero with increasing prediction power. We then propose the \textsf{Predictive Backpressure (PBP)} algorithm for achieving optimal utility performance in such predictive systems. \textsf{PBP} efficiently incorporates prediction into stochastic system control and avoids the great complication due to the exponential state space growth in the prediction window size. We show that \textsf{PBP} can achieve a utility performance that is within $O(\epsilon)$ of the optimal, for any $\epsilon>0$, while guaranteeing that the system delay distribution is a \emph{shifted-to-the-left} version of that under the original Backpressure algorithm. Hence, the average packet delay under \textsf{PBP} is strictly better than that under Backpressure, and vanishes with increasing prediction window size. This implies that the resulting utility-delay tradeoff with predictive scheduling beats the known optimal $[O(\epsilon), O(\log(1/\epsilon))]$ tradeoff for systems without prediction

Prediction of extreme events in the OFC model on a small world network

We investigate the predictability of extreme events in a dissipative Olami-Feder-Christensen model on a small world topology. Due to the mechanism of self-organized criticality, it is impossible to predict the magnitude of the next event knowing previous ones, if the system has an infinite size. However, by exploiting the finite size effects, we show that probabilistic predictions of the occurrence of extreme events in the next time step are possible in a finite system. In particular, the finiteness of the system unavoidably leads to repulsive temporal correlations of extreme events. The predictability of those is higher for larger magnitudes and for larger complex network sizes. Finally, we show that our prediction analysis is also robust by remarkably reducing the accessible number of events used to construct the optimal predictor.Comment: 5 pages, 4 figure

Condensation Transition in Polydisperse Hard Rods

We study a mass transport model, where spherical particles diffusing on a ring can stochastically exchange volume $v$, with the constraint of a fixed total volume $V=\sum_{i=1}^N v_i$, $N$ being the total number of particles. The particles, referred to as $p$-spheres, have a linear size that behaves as $v_i^{1/p}$ and our model thus represents a gas of polydisperse hard rods with variable diameters $v_i^{1/p}$. We show that our model admits a factorized steady state distribution which provides the size distribution that minimizes the free energy of a polydisperse hard rod system, under the constraints of fixed $N$ and $V$. Complementary approaches (explicit construction of the steady state distribution on the one hand ; density functional theory on the other hand) completely and consistently specify the behaviour of the system. A real space condensation transition is shown to take place for $p>1$: beyond a critical density a macroscopic aggregate is formed and coexists with a critical fluid phase. Our work establishes the bridge between stochastic mass transport approaches and the optimal polydispersity of hard sphere fluids studied in previous articles

Modelling of a roof runoff harvesting system: The use of rainwater for toilet flushing

The water balance of a four-people family rainwater harvesting system was calculated in a case study. The experimental water saving efficiency (WSE) was calculated as 87 %. A simple computer model was implemented to simulate the behaviour of the rainwater harvesting system. In general, the rainwater collector volumes predicted by the daily model had shown a good correlation with the experimental values. The difference between the experimental and the predicted values for the stored volume can be explained by the lack of maintenance of the system that can affect its performance. On the basis of a long-term simulation of 20-year rainfall data, the following parameters were calculated: rainfall, water demand, mains water, rainwater used, over-flow and WSE. The collection of rainwater from roofs, its storage and subsequent use for toilet flushing can save 42 m3 of potable water per year for the studied system. The model was also used to find the optimal size of the tank for the single-family household: a storage capacity of approximately 5 m3 was found to be appropriate. The storage capacity and tank size were distinguished. The importance to take into account the dead volume of the tank for the sizing was indeed highlighted