Propagation of numerical noise in particle-in-cell tracking

Particle-in-cell (PIC) is the most used algorithm to perform self-consistent tracking of intense charged particle beams. It is based on depositing macro-particles on a grid, and subsequently solving on it the Poisson equation. It is well known that PIC algorithms occupy intrinsic limitations as they introduce numerical noise. Although not significant for short-term tracking, this becomes important in simulations for circular machines over millions of turns as it may induce artificial diffusion of the beam. In this work, we present a modeling of numerical noise induced by PIC algorithms, and discuss its influence on particle dynamics. The combined effect of particle tracking and noise created by PIC algorithms leads to correlated or decorrelated numerical noise. For decorrelated numerical noise we derive a scaling law for the simulation parameters, allowing an estimate of artificial emittance growth. Lastly, the effect of correlated numerical noise is discussed, and a mitigation strategy is proposed.Comment: 14 pages, 12 figure

An Open-Source Microscopic Traffic Simulator

We present the interactive Java-based open-source traffic simulator available at www.traffic-simulation.de. In contrast to most closed-source commercial simulators, the focus is on investigating fundamental issues of traffic dynamics rather than simulating specific road networks. This includes testing theories for the spatiotemporal evolution of traffic jams, comparing and testing different microscopic traffic models, modeling the effects of driving styles and traffic rules on the efficiency and stability of traffic flow, and investigating novel ITS technologies such as adaptive cruise control, inter-vehicle and vehicle-infrastructure communication

Automatic and efficient driving strategies while approaching a traffic light

Vehicle-infrastructure communication opens up new ways to improve traffic flow efficiency at signalized intersections. In this study, we assume that equipped vehicles can obtain information about switching times of relevant traffic lights in advance. This information is used to improve traffic flow by the strategies 'early braking', 'anticipative start', and 'flying start'. The strategies can be implemented in driver-information mode, or in automatic mode by an Adaptive Cruise Controller (ACC). Quality criteria include cycle-averaged capacity, driving comfort, fuel consumption, travel time, and the number of stops. By means of simulation, we investigate the isolated strategies and the complex interactions between the strategies and between equipped and non-equipped vehicles. As universal approach to assess equipment level effects we propose relative performance indexes and found, at a maximum speed of 50 km/h, improvements of about 15% for the number of stops and about 4% for the other criteria. All figures double when increasing the maximum speed to 70 km/h.Comment: Submitted to ITSC - 17th International IEEE Conference on Intelligent Transportation System

From Drivers to Athletes -- Modeling and Simulating Cross-Country Sking Marathons

Traffic flow of athletes in classic-style cross-country ski marathons, with the Swedish Vasaloppet as prominent example, represents a non-vehicular system of driven particles with many properties of vehicular traffic flow such as unidirectional movement, the existence of lanes, and, moreover, severe traffic jams. We propose a microscopic acceleration and track-changing model taking into account different fitness levels, gradients, and interactions between the athletes in all traffic situations. The model is calibrated on microscopic data of the $\textit{Vasaloppet 2012}$ Using the multi-model open-source simulator MovSim.org, we simulate all 15 000 participants of the Vasaloppet during the first ten kilometers.Comment: 8 pages, contribution to the conference Traffic and Granular Flow '13 in Juelich. Will be included in the Conference proceedings (Springer