Design, Development and Calibration of HTS Wire Based LOX Level Sensor Probe

For space applications, the weight of the liquid level sensors are of major concern as they affect the payload fraction and hence the cost. An attempt is made to design and test a light weight High Temperature Superconductor (HTS) wire based liquid level sensor for Liquid Oxygen (LOX) tank used in the cryostage of the spacecraft. The total resistance value measured of the HTS wire is inversely proportional to the liquid level. A HTS wire (SF12100) of 12mm width and 2.76m length without copper stabilizer has been used in the level sensor. The developed HTS wire based LOX level sensor is calibrated against a discrete diode array type level sensor. Liquid Nitrogen (LN2) and LOX has been used as cryogenic fluid for the calibration purpose. The automatic data logging for the system has been done using LabVIEW11. The net weight of the developed sensor is less than 1 kg.

Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

Development and Evaluation of Prussian Blue Mediated Glucose Sensor for Reverse Iontophoresis Application

The screen printed electrochemical glucose sensor is developed suitable for revere iontophoresis (RI) application. Glucose oxidase is immobilized on screen printed sensor using crosslinking method. Electrochemical and material characterization studies are conducted on the developed sensor and the obtained results confirm the suitability of the developed sensor for RI application. The developed sensor is validated by conducting clinical investigations on 10 human subjects through RI. A correlation is established between the blood glucose and extracted glucose, and correlation is found to be 0.73. (C) 2015 The Electrochemical Society. All rights reserved.