Sensitive temperature gradiometer for use at low temperatures.
A device capable of very sensitive temperature gradient measurements in the presence of relatively large ambient temperature fluctuations is described. The device uses a pair of ''matched'' superconducting thin films in a bridge arrangement, with a SQUID magnetometer probe as the null detector.
DYNAMICS OF VORTEX LINES IN SUPERFLUID 4HELIUM *
Solid-body rotation, characteristic of a uniformly rotating ordinary fluid, is therefore clearly forbidden. It does not follow, however, that for superfluid contained within a cylindrical container rotating about the cylinder axis, the velocity itself is necessarily zero. Above some critical angular velocity (much smaller than the angular velocities investigated in the experiments discussed in this paper), the free energy of the system is decreased with the introduction of a filamentary discontinuity threading the fluid from container wall to container wall along the rotational axis. In the presence of this discontinuity (termed a vortex line), the superfluid executes azimuthal motion about the line, with a velocity given by
A Short-Term and High-Resolution Distribution System Load Forecasting Approach Using Support Vector Regression With Hybrid Parameters Optimization
This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of this paper.