Drawing induced texture and the evolution of superconductive properties with heat treatment time in powder-in-tube in-situ processed MgB2 strands

Monocore powder-in-tube MgB2 strands were cold-drawn and heat-treated at 600C and 700C for times of up to 71 hours and structure-property relationships examined. Drawing-induced elongation of the Mg particles led, after HT, to a textured macrostructure consisting of elongated polycrystalline MgB2 fibers separated by elongated pores. The superconducting Tc, Jc and Fp were correlated with the macrostructure and grain size. Grain size increased with HT time at both 600C and 700C. Jc and hence Fp decreased monotonically but not linearly with grain size. Overall, it was observed that at 700C, the MgB2 reaction was more or less complete after as little as 30 min; at 600C, full reaction completion did not occur until 71 h. into the HT. Transport, Jct(B) was measured in a perpendicular applied field, and the magnetic critical current densities, Jcm\bot(B) and Jcm{\phi}(B), were measured in perpendicular and parallel (axial) applied fields, respectively. Particularly noticeable was the premature dropoff of Jcm\bot(B) at fields well below the irreversibility field of Jct(B). This effect is attributed to the fibrous macrostructure and its accompanying anisotropic connectivity. Magnetic measurements with the field directed along the strand axis yielded a critical density, Jcm\bot(B), for current flowing transversely to the strand axis that was less than and dropped off more rapidly than Jct(B). In the conventional magnetic measurement, the loop currents that support the magnetization are restricted by the lower of Jct(B) and Jcm{\phi} (B). In the present case the latter, leading to the premature dropoff of the measured Jcm(B) compared to Jct(B) with increasing field. This result is supported by Kramer plots of the Jcm{\phi} (B) and Jct(B) data which lead to an irreversibility field for transverse current that is very much less than the usual transport-measured longitudinal one, Birr,t.Comment: 41 pages, 14 figure

Remote sensing analysis of changes in Chorabari glacier, Central Himalaya, India

In this study, mass balance for Chorabari glacier of the Central Himalaya, India has been estimated. This glacier has been considered for the case study as it feeds the Mandakini River and was one of the reasons for flash floods in Rudraprayag district, Uttarakhand in 2013. The observations are based on glacier area/length change and rate of melting in the multi-decade (1976-2016) using Landsat data. The study estimates an overall decrease in area at 0.8% per year. Elevation change has been studied using geodetic method utilizing shuttle radar topography mission and TanDEM-X datasets, which have shown a decrease in elevation in 16 years (2000-16). From these remotely observed parameters, a negative mass balance for the decade 2000-11 indicates glacier retreat. This study highlights the applicability of optical and radar remote sensing for the Himalayan glaciers, for better disaster management and understanding glacier dynamics in response to climate change

A Revised Glacier Inventory of Bhaga Basin Himachal Pradesh, India : Current Status and Recent Glacier Variations

Himalayan glaciers show large uncertainty regarding their present and future state due to their sensitive reaction towards change in climatic condition. Himalayan glaciers are unique as they are located in tropical, high altitude regions, predominantly valley type and many are covered with debris. The great northern plains of India sustain on the perennial melt of glaciers meeting the water requirements of agriculture, industries, domestic sector even in the months of summer when large tracts of the country go dry. Therefore, it is important to monitor and assess the state of snow and glaciers and to know the sustainability of glaciers in view of changing global scenarios of climate and water security of the nation. Any information pertaining to Himalayan glaciers is normally difficult to be obtained by conventional means due to its harsh weather and rugged terrains. Due to the ecological diversity and geographical vividness, major part of the Indian Himalaya is largely un-investigated. Considering the fact that Himalayan glaciers are situated in a harsh environment, conventional techniques of their study is challenging and difficult both in terms of logistics and finances whereas the satellite remote sensing offers a potential mode for monitoring glaciers in long term. In order to gain an updated overview of the present state of the glacier cover and its changes since the previous inventories, an attempt has been made to generate a new remotesensing- derived glacier inventory on 1:50,000 scale for Bhaga basin (N32°28'19.7'' - N33°0'9.9'' ; E76°56'16.3'' - E77°25'23.7'' ) Western Himalaya covering an area of 1695.63 km2. having 231 glaciers and occupying glacierized area of 385.17 ±3.71 km2. ranging from 0.03 km2. to 29.28 km2. Glacier inventory has been carried out using high resolution IRS P6 LISS III data of 2011, ASTER DEM and other ancillary data. Specific measurements of mapped glacier features are the inputs for generating the glacier inventory data sheet with 37 parameters as per the UNESCO/TTS format, 11 additional parameters associated with the de-glaciated valley as per the suggestions of Space Application Center Ahmadabad and 9 newly introduced parameters of present study. The data sheet provides glacier wise details for each glacier on the significant glacier parameters like morphology, dimensions, orientation, elevation, etc. for both the active glacier component as well as the associated de-glaciated valley features. Assessment of recent variation in the glacierized area between 2001 and 2011. Results indicate that 231 glaciers covering an area of 391.56 ±3.76 km2. in 2001 has been reduced to 385.17 ±3.71 km2. in 2011; a loss of 1.63 ±1.0% in glacierized area within a period of 10 years. The present paper brings out the methodology adopted and salient results of the glacier inventory carried out which will help to enrich the existing database required for water resources assessment of the country and also meet the requirements of various researches working on climate change related studies

Impeller fault detection under variable flow conditions based on three feature extraction methods and artificial neural networks

Nonstationary flow conditions can introduce complexities and nonlinear characteristics to pumping systems. This paper presents comparative studies of impeller fault detection techniques combined with artificial neural networks (ANNs) to propose the most appropriate diagnosis system. An experimental study, including seven impeller conditions, is performed to further explore the phenomena. Statistical parameters, frequency peaks, and wavelet packet energy present data feature sets, and a three-layer back-propagation ANN is used for fault recognition. The verification of the results proves that the detectability of the wavelet packet transform (WPT)-ANN model is considerably improved by using the energy of the decomposed vibration from WPT. This model can save computational time and provide superior diagnostic information. This study provides two key contributions. First, the feasibility and effectiveness of common monitoring techniques are compared. Second, the results demonstrate the accuracy of the proposed models for impellers operating under variable working conditions, which has not been previously addressed in the literature.The Rand Water Companyhttp://link.springer.com/journal/122062019-09-01hj2018Mechanical and Aeronautical Engineerin