Calibration and Characterization of a Reduced Form-Factor High Accuracy Three-Axis Teslameter

A new reduced form-factor three axes digital teslameter, based on the spinning current technique, has been developed. This instrument will be used to characterize the SwissFEL insertion devices at the Paul Scherrer Institute (PSI) for the ATHOS soft X-ray beamline. A detailed and standardized calibration procedure is critical to optimize the performance of this precision instrument. This paper presents the measurement techniques used for the corrective improvements implemented through non-linearity, temperature offset, temperature sensitivity compensation of the Hall probe and electronics temperature compensation. A detailed quantitative analysis of the reduction in errors on the application of each step of the calibration is presented. The percentage peak error reduction attained through calibration of the instrument for reference fields in the range of ±2 T is registered to drop from 1.94% down to 0.02%.

Experimental Determination of Thermal Conductivity of Cortical Bone With Heat Loss Estimation

This paper presents an experimental measurement of the thermal conductivity of bovine cortical bone by an improved parallel plate method to increase the accuracy of the measurement. An experimental apparatus was designed to measure the thermal conductivity of the cortical bone using a reference material with a known thermal conductivity by the heat transfer through the samples. To improve the measurement accuracy, a reference material was selected as quartz, which is of the same order of magnitude of the thermal conductivity of bovine cortical bone reported in the existing literature. Additionally, the temperatures at the heat source and heat sink were set to ±5°C from the ambient temperature to reduce the inevitable heat loss in the measurement. The temperature offset was determined numerically. The current experimental measurement was validated by an in-house finite-difference numerical program. The heat loss in the measurement was predicted from the numerical program. The thermal conductivity of the bovine cortical bone was then determined to be 0.55 ± 0.02 W/mK with compensating heat loss.

A Methodology to Determine Recipe Adjustments for Multispectral Composites Derived from Next-Generation Advanced Satellite Imagers

The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) began creating multispectral [i.e., red–green–blue (RGB)] composites in the early 2000s with the advent of the Meteosat-8 Spinning Enhanced Visible and Infrared Imager (SEVIRI). As new satellite sensors—for example, the Himawari-8 Advanced Himawari Imager (AHI) and the Geostationary Operational Environmental Satellite Advanced Baseline Imager (ABI)—become available, there is a need to adjust the EUMETSAT RGB standard thresholds (i.e., recipes) to account for differences in spectral characteristics, spectral response, and atmospheric absorption in order to maintain an interpretation consistent with legacy composites. For the purpose of comparing RGB composites derived from nonoverlapping geostationary sensors, an adjustment technique was applied to the Suomi National Polar-Orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) to create an intermediate reference sensor (i.e., SEVIRI proxy). Brightness temperature offset values between each AHI and SEVIRI proxy band centered near 3.9, 8.6, 11.0, and 12.0 µm were determined with this technique and through line-by-line radiative transfer model simulations. The relationship between measured brightness temperature of AHI and the SEVIRI proxy was determined though linear regression similar to research by the Japan Meteorological Agency. The linear regression coefficients were utilized to determine the RGB recipe adjustments. Adjusting the RGB recipes to account for the differences in spectral characteristics results in RGB composites consistent with legacy EUMETSAT composites. The methodology was applied to an example of the Nighttime Microphysics RGB, confirming the Japan Meteorological Agency adjustments and demonstrating a simple methodology to determine recipe adjustments for RGB composites derived with next-generation sensors.

Characterizations of YBa5Cu6Ox Superconductor Synthesized by Melt Process

The YBa5Cu6Ox (Y156) superconductors were synthesized by melt process method with sintering at 980 °C. The samples were characterized by the SEM, EDX, XRD and resistance measurement. The critical temperature onset () and the critical temperature offset () were found at 90 K and 80 K respectively. The crystal structures was orthorhombic performed by Rietveld full-profile analysis method with lattice parameter a = 3.80078 Å, b = 3.89068 Å and c = 22.94436 Å. The c/a ratio was 6.04 and the anisotropy was 2.33. The lower c/a ratio and higher anisotropic were found as increasing the sintering temperature with little change in a and b-axis value. We found that as increasing of sintering temperature, the critical temperature was decreased but the anisotropy was increased.

Rail Temperature Approximation and Heat Slow Order Best Practices

The railroad industry uses slow orders, sometimes referred to as speed restrictions, in areas where an elevated rail temperature is expected in order to minimize the risk and consequence of derailment caused by track buckling due to excessive rail temperature. Traditionally, rail temperature has been approximated by adding a constant offset, most often 30°F, to a peak ambient air temperature. When this approximated maximum rail temperature exceeds a given risk threshold, slow orders are usually issued for a predefined period of the day. This “one size fits all” approach, however, is not effective and suitable in all situations. On very warm days, the difference between rail temperature and ambient air temperature can exceed railroad-employed offsets and remain elevated for extended periods of time. A given temperature offset may be well suited for certain regions and track buckling risk-related rail temperature thresholds but less accurate for others. Almost 160,000 hours of rail temperature measurements collected in 2012 across the eastern United States by two Class I railroads and predicted ambient air temperatures based on the National Weather Service’s National Centers for Environmental Prediction (NCEP) data were analyzed using detection theory in order to establish optimal values of offsets between air and rail temperatures as well as times when slow orders should be in place based on geographical location and the track buckling risk rail temperature threshold. This paper presents the results of the analysis and describes an improved procedure to manage heat-related slow orders based on ambient air temperatures.