Post-Arc Characteristics of High-Current Arcs in Vacuum Circuit-Breakers

The post-arc (PA) characteristics of vacuum arcs in transverse magnetic field contacts are studied for short-circuit currents of up to 123 kA peak and transient recovery voltages below 875 V. The measured PA currents are interpreted in terms of an Electric Resistance Model and the models of Andrews-Varey, Langmuir-Child, and Slepian-Schmelzle. Whereas in the late PA period, the calculations do not agree well with the measurements, the PA behavior is well described in the early period after current-zero. It is concluded that the PA discharge is amplified by ionization of metal vapor particles in the boundary sheath due to electron impact

Decision-analytic frameworks for multi-hazard mitigation and adaptation

Developing effective decision-support for multiple hazards needs to build on a foundation of existing research into best practices for the management of single hazards analysis. This comes from the hazards literature, recent and ongoing EU research projects, and from the climate vulnerability literature, in which the theoretical focus on multiple drivers of vulnerability is already well established. The first part of this task will rely on a desk study of established management practices and decision-analytic methods. The latter include several standard methods for conducting sound formal decision-analysis, including cost-benefit analysis, risk- benefit analysis, and multi-criteria analysis. Each of these has its strengths, weaknesses, and set to best practices in particular contexts. The second part of this task will identify these in the case of multiple hazards, and appraise how they may differ in their application and appropriateness from the single-hazard case. It will rely on an application of these modeling methods to the simulated city case study

Load and Electricity Rates Prediction for Building Wide Optimization Applications

The reduction of energy consumption, use of renewable energy, and preservation of natural resources are becoming increasingly important. Several applications in the energy efficiency field aim at minimizing energy consumption and/or cost. To achieve this, these applications employ optimization techniques that require future prediction of the performance and various loads of a facility, campus, building, or an energy plant, such as hot water, cold water, and/or electric load. The prediction horizon may be as short as few hours to ten days into the future, depending on the application at hand. Furthermore, for the purpose of minimizing electricity cost, it is as necessary to know, as accurately as possible, what the electricity rates are over a given horizon. Therefore, a method for predicting hot water, cold water, and electric loads and electricity rates over a given horizon into the future has been developed (Load will be used to refer to hot water, cold water, and electric loads and electricity rates without loss of generality). The method developed takes into consideration the several factors contributing to the load value. These factors include time of day, day of week, schedules (in-session or out-of-session for a university campus for example), and weather (temperature and humidity). The load predicted consists of a deterministic term and a stochastic term. The deterministic term is calculated using linear regression models, whose coefficients are determined offline. These models rely on the typical load value for a given time of day and day-type (days with similar load profiles) and weather forecast. The latter is obtained from the National Oceanic and Atmospheric Administration (NOAA) through their National Digital Forecast Database (NDFD) service. The stochastic term is determined using an Auto-Regressive (AR) model, whose coefficients are determined offline. The AR model calculates future prediction errors based on the current prediction error. The stochastic element of the predicted load gives the method developed its adaptive property, and thus increases the accuracy of the prediction by updating the forecast using current measurements of the load. Historical weather and load data are used for determining the coefficients of the regression models and the AR model offline. For a given set of training data, the method developed generates a set of regression models for each day-type. Day-types are determined by a day-typing algorithm which specifies days with similar load profiles based on cluster analysis techniques. Outside air enthalpy and a typical load profile constitute the predictors variables in each set of regression models. Each day-type is characterized by a different typical load profile which is generated using an optimal data fitting technique. The AR model coefficients are determined using the residuals obtained from different sets of regression models. Given the determined models, the current load measurement, and weather forecast, the future load values are calculated by selecting the appropriate regression model and summing the deterministic and stochastic terms.

Beam Position Determination using Tracks

Track-based algorithms to determine the LHC beam position and profile at the CMS collision point are described. Only track information is used and no reconstruction of the primary event vertex is required. With only about thousand tracks, a statistical precision of 2 microns for the transverse beam position is achieved, assuming a well aligned detector. The algorithms are simple and fast, and can be used to monitor the beam in real time. A method to determine the track impact parameter resolution using the beam position and beam width calculation is also presented

Numerical investigation of the stability of stationary solutions in the theory of cathode spots in arcs in vacuum and ambient gas

The stability of stationary spots on cathodes of arcs in vacuum and ambient gas is investigated by means of the simulation of the temporal evolution of perturbations imposed over steady-state solutions. Two cases of loading conditions are considered, namely, spots operating at a fixed current (the case typical of small-scale experiments) and spots operating at a fixed voltage (the case typical of high-power circuit breakers). Results are reported on spots on large copper cathodes of vacuum arcs and on spots on tungsten cathodes of high-pressure argon arcs. It is shown, in particular, that if the ballast resistance in small-scale laboratory experiments with a high-current arc is insufficient, the potential consequence may be a thermal explosion of a spot, if the arc burns in vacuum, and massive melting of the cathode surface, if the arc burns in ambient gas. This conclusion conforms to trends observed in the experiment.info:eu-repo/semantics/publishedVersio

Simulation of thermal instability in non-uniformities on the surface of cathodes of vacuum arcs

Instability stemming from the strong dependence of electron emission current on the local surface temperature plays an important role in current transfer to hot cathodes of arc discharges. In the case of vacuum arcs, this instability may lead to micro explosions on cathode surface even if the surface is planar. This work is concerned with numerical simulation of effect produced by surface non-uniformities. It is found that the effect is non-trivial: the presence of surface non-uniformities can not only accelerate the development of the instability, which is what one would expect intuitively, but also slow it down and even suppress.info:eu-repo/semantics/publishedVersio

Phenomenological approach to simulation of propagation of spots over cathodes of high-power vacuum circuit breakers

A phenomenological description of an ensemble of a large number of spots on negative contacts of high-power vacuum circuit breakers is developed by means of generalization of the concept of random walk of a single cathode spot in low-current vacuum arcs. The model is formulated in terms of a convection-diffusion equation governing the evolution of the number of spots per unit area, taking into account the variation of the number of spots with the arc current and the “retrograde repulsion” between spots. The approach is applied to description of the distribution of cathode spots during the initial expansion process after arc ignition in conditions of two independent experiments simulating high-power switches. A reasonably good agreement between the theory and the experiment is found. The developed model can be used as a module of global numerical models of the interruption process in high-power vacuum circuit breakers.info:eu-repo/semantics/publishedVersio

Designable electron transport features in one-dimensional arrays of metallic nanoparticles: Monte Carlo study of the relation between shape and transport

We study the current and shot noise in a linear array of metallic nanoparticles taking explicitly into consideration their discrete electronic spectra. Phonon assisted tunneling and dissipative effects on single nanoparticles are incorporated as well. The capacitance matrix which determines the classical Coulomb interaction within the capacitance model is calculated numerically from a realistic geometry. A Monte Carlo algorithm which self-adapts to the size of the system allows us to simulate the single-electron transport properties within a semiclassical framework. We present several effects that are related to the geometry and the one-electron level spacing like e.g. a negative differential conductance (NDC) effect. Consequently these effects are designable by the choice of the size and arrangement of the nanoparticles.Comment: 13 pages, 12 figure