4 resultados para METER
em CentAUR: Central Archive University of Reading - UK
Resumo:
Kites offer considerable potential as wind speed sensors—a role distinct from their traditional use as instrument-carrying platforms. In the sensor role, wind speed is measured by kite-line tension. A kite tether line tension meter is described here, using strain gauges mounted on an aluminum ring in a Wheatstone bridge electronic circuit. It exhibits a linear response to tension 19.5 mV N−1 with good thermal stability mean drift of −0.18 N °C−1 over 5–45 °C temperature range and a rapid time response 0.2 s or better. Field comparisons of tether line tension for a Rokkaku kite with a fixed tower sonic anemometer show an approximately linear tension-wind speed relationship over the range 1–6 ms−1. © 2010 American Institute of Physics. doi:10.1063/1.3465560
Resumo:
Priming effects of cooperation vs. individualism were investigated on changeover speed within a 4 x 100-m relay race. Ten teams of four adult beginner athletes ran two relays, a pretest race and an experimental race 3 weeks later. Just before the experimental race, athletes were primed with either cooperation or individualism through a scrambled-sentence task. Comparing to the pretest performance, cooperation priming improved baton speed in the exchange zone (+30 cm/s). Individualism priming did not impair changeover performance. The boundary conditions of priming effects applied to collective and interdependent tasks are discussed within the implicit coordination framework.
Resumo:
An H-infinity control strategy has been developed for the design of controllers used in feedback controlled electrical substitution measurements (FCESM). The methodology has the potential to provide substantial improvements in both response time and resolution of a millimetre-wave absolute photoacoustic power meter.
Resumo:
Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.