Modeling and Simulation of Regenerative Braking Energy in DC Electric Rail Systems

Regenerative braking energy is the energy produced by a train during deceleration. When a train decelerates, the motors act as generators and produce electricity. This energy can be fed back to the third rail and consumed by other trains accelerating nearby. If there are no nearby trains, this energy is dumped as heat to avoid over voltage. Regenerative braking energy can be saved by installing energy storage systems (ESS) and reused later when it is needed. To find a suitable design, size and placement of energy storage, a good understanding of this energy is required. The aim of this paper is to model and simulate regenerative braking energy. The dc electric rail transit system model introduced in this paper includes trains, substations and rail systems

Ruin probabilities with dependence on the number of claims within a fixed time window

We analyse the ruin probabilities for a renewal insurance risk process with inter-arrival time distributions depending on the claims that arrived within a fixed (past) time window. This dependence could be explained through a regenerative structure. The main inspiration of the model comes from the Bonus-Malus feature. We discuss first asymptotic results of ruin probabilities for different regimes of claim distributions. For numerical results, we recognise an embedded Markov additive process. Via an appropriate change of measure, ruin probabilities could be computed to a closed form formulae. Additionally, we present simulated results via the importance sampling method, which further permit an in-depth analysis of a few concrete cases

Analytical prediction of chatter stability for variable pitch and variable helix milling tools

Regenerative chatter is a self-excited vibration that can occur during milling and other machining processes. It leads to a poor surface finish, premature tool wear, and potential damage to the machine or tool. Variable pitch and variable helix milling tools have been previously proposed to avoid the onset of regenerative chatter. Although variable pitch tools have been considered in some detail in previous research, this has generally focussed on behaviour at high radial immersions. In contrast there has been very little work focussed on predicting the stability of variable helix tools. In the present study, three solution processes are proposed for predicting the stability of variable pitch or helix milling tools. The first is a semi-discretisation formulation that performs spatial and temporal discretisation of the tool. Unlike previously published methods this can predict the stability of variable pitch or variable helix tools, at low or high radial immersions. The second is a time-averaged semi-discretisation formulation that assumes time-averaged cutting force coefficients. Unlike previous work, this can predict stability of variable helix tools at high radial immersion. The third is a temporal-finite element formulation that can predict the stability of variable pitch tools with a constant uniform helix angle, at low radial immersion. The model predictions are compared to previously published work on variable pitch tools, along with time-domain model simulations. Good agreement is found with both previously published results and the time-domain model. Furthermore, cyclic-fold bifurcations were found to exist for both variable pitch and variable helix tools at lower radial immersions

Regenerative Simulation for Queueing Networks with Exponential or Heavier Tail Arrival Distributions

Multiclass open queueing networks find wide applications in communication, computer and fabrication networks. Often one is interested in steady-state performance measures associated with these networks. Conceptually, under mild conditions, a regenerative structure exists in multiclass networks, making them amenable to regenerative simulation for estimating the steady-state performance measures. However, typically, identification of a regenerative structure in these networks is difficult. A well known exception is when all the interarrival times are exponentially distributed, where the instants corresponding to customer arrivals to an empty network constitute a regenerative structure. In this paper, we consider networks where the interarrival times are generally distributed but have exponential or heavier tails. We show that these distributions can be decomposed into a mixture of sums of independent random variables such that at least one of the components is exponentially distributed. This allows an easily implementable embedded regenerative structure in the Markov process. We show that under mild conditions on the network primitives, the regenerative mean and standard deviation estimators are consistent and satisfy a joint central limit theorem useful for constructing asymptotically valid confidence intervals. We also show that amongst all such interarrival time decompositions, the one with the largest mean exponential component minimizes the asymptotic variance of the standard deviation estimator.Comment: A preliminary version of this paper will appear in Proceedings of Winter Simulation Conference, Washington, DC, 201

An integrated methodology to assess the operational and environmental performance of a conceptual regenerative helicopter

This paper aims to present an integrated multidisciplinary simulation framework, deployed for the comprehensive assessment of combined helicopter powerplant systems at mission level. Analytical evaluations of existing and conceptual regenerative engine designs are carried out in terms of operational performance and environmental impact. The proposed methodology comprises a wide-range of individual modeling theories applicable to helicopter flight dynamics, gas turbine engine performance as well as a novel, physics-based, stirred reactor model for the rapid estimation of various helicopter emissions species. The overall methodology has been deployed to conduct a preliminary trade-off study for a reference simple cycle and conceptual regenerative twin-engine light helicopter, modeled after the Airbus Helicopters Bo105 configuration, simulated under the representative mission scenarios. Extensive comparisons are carried out and presented for the aforementioned helicopters at both engine and mission level, along with general flight performance charts including the payload-range diagram. The acquired results from the design trade-off study suggest that the conceptual regenerative helicopter can offer significant improvement in the payload-range capability, while simultaneously maintaining the required airworthiness requirements. Furthermore, it has been quantified through the implementation of a representative case study that, while the regenerative configuration can enhance the mission range and payload capabilities of the helicopter, it may have a detrimental effect on the mission emissions inventory, specifically for NOx (Nitrogen Oxides). This may impose a trade-off between the fuel economy and environmental performance of the helicopter. The proposed methodology can effectively be regarded as an enabling technology for the comprehensive assessment of conventional and conceptual helicopter powerplant systems, in terms of operational performance and environmental impact as well as towards the quantification of their associated trade-offs at mission level. Ali Fakhre, Ioannis Goulos, Vassilios Pachidis School of Engineering, Energy, Power and Propulsion Division, Cranfield University, Cranfield, Bedford, MK43 0AL, UK [email protected] The Aeronautical Journal, 2015, Vol 119, Issue 1211, pp1-24 Published by Cambridge University Press. This is the Author Accepted Manuscript. This article may be used for personal use only. The final published version (version of record) is available online at 10.1017/S0001924000010253. Please refer to any applicable publisher terms of use

Techniques for the Fast Simulation of Models of Highly dependable Systems

With the ever-increasing complexity and requirements of highly dependable systems, their evaluation during design and operation is becoming more crucial. Realistic models of such systems are often not amenable to analysis using conventional analytic or numerical methods. Therefore, analysts and designers turn to simulation to evaluate these models. However, accurate estimation of dependability measures of these models requires that the simulation frequently observes system failures, which are rare events in highly dependable systems. This renders ordinary Simulation impractical for evaluating such systems. To overcome this problem, simulation techniques based on importance sampling have been developed, and are very effective in certain settings. When importance sampling works well, simulation run lengths can be reduced by several orders of magnitude when estimating transient as well as steady-state dependability measures. This paper reviews some of the importance-sampling techniques that have been developed in recent years to estimate dependability measures efficiently in Markov and nonMarkov models of highly dependable system