Analysis of Flow through Vaneless Contra-Rotating Turbine of Jet Propulsion Engine

As per the increasing demand of Jet propulsion Engine, it is required to improve the efficiency, reduction of weight and consideration of fuel consumption, which lead the researchers to arrive at an unconventional turbine known as vaneless contra rotating turbine (VCRT). The major advantage of this is in its compactness or in its ability to give high power/total weight. Research in this area is being pursued since many years. Scientists are putting their best to get the aim to its zenith. Such placement of flow path elements gives benefits, but needs special approach to organize flow inside the turbine. Modern aerodynamic designs, computational and optimization methodologies allow us to fulfill this task in the shortest period of time with the highest gain in turbine performance. The Aim of this topic is to understand the significance of blade design, geometries & domains and its effect in turbine efficiency & performance at various operating conditions. In this paper, three-dimensional multiblade row Navier-Stokes (3D RANS) simulations have been performed to investigate the flow characteristics of a VCRT. Bladegen modular are used to generate the Blades. TurboGrid modular is used for meshing. The turbine components are modeled for all the three spacing. In present work, 3D viscous flow simulation with SST k-? turbulence model is carried out in ANSYS CFX14.5. The flow in VCRT is very complex including several flow phenomena, such as turbulence, separation, swirling flow and unsteadiness flow. The variation of flow parameters from hub to tip of blades are presented in graphical form and average circumferential area (ACA) value of cascade parameters from inlet to outlet of the blades are computed at different operating regimes. The results of this analysis shows a good prediction of the flow behavior inside the blades and this lead to acceptable blade design, which can be used in VCRT

Isolation, Characterization and Purification of α-Galactosidase From Peas

In India, the peas are cultivated on a large scale. The α-galactosidase enzyme has principle applications in food industries and in the medical field. The α-galactosidase enzyme was purified from dry peas (Pisum sativum). The purification steps include acetone precipitation and DEAE-cellulose column chromatography. The enzyme has maximum activity at 40°C and optimum pH=7.5. The molecular weight of the enzyme was determined by using SDS-PAGE analysis and found to be 110 kDa. The purified enzyme was immobilized by sodium alginate and it was observed that the immobilized enzyme showed an increase in thermal tolerance

Vibration Analysis of Silencer Based on FEM and FFT Analyser

Silencer was considered with and without modifying in order to reduce the vibration. Design and modeling have been done with specifying different material properties. Finite Element Method was used for the modeling and simulations. The harmonic analysis has been performed by using ANSYS 18.0. The natural frequency and working frequency are the very important parameters to study the resonance. It is mandatory to avoid this resonating condition. These frequencies are distinguished with the help of ANSYS 18.0

INTEGRATION OF HUMAN PARTICIPATORY SENSING AND ARCHIVES OF REMOTE SENSING OBSERVATIONS FOR FIELD LEVEL CROP PHENOLOGY ESTIMATION

The rise in global population has increased food and water demand thereby causing excessive pressure on existing resources. In developing countries with fragmented land holdings there exists constant pressure on available water and land resources. Obtaining field scale crop specific information is challenging task. Advent of open freely available multi-temporal remote sensing observations with improved radiometric resolution the possibilities for near real / real time applications has increased. In this study and an attempt has been made to establish operational model for field level crop growth monitoring using integrated approach of crowd sourcing and time series of remote sensing observations. The time series of Sentinel 2 (A and B) satellite has been used to estimate crop growth related components such as vegetation indices and crop growth stage and crop phenology. In initial stage high valued cereal crop Wheat has been selected. The field level information (i.e. 108 Wheat fields) collected using mobile based agro-advisory platform mKRISHI® has been used to extract time series of Sentinel 2 observations (44 scenes for year 2016 and 2018). The moving average has been used for filling gaps in the time series of vegetation indices. The BFAST and GreenBrown package in R were used for detecting breaks in vegetation index time series and estimating crop growth stages. Analysis shows that the estimated crop phenology parameters were in better agreement with the field observations. In future more crops from different agro-climatic conditions will be considered for providing field level crop management advisory