Flow in a Counter Rotating Turbine (CRT) stage is composite and three dimensional due to the Blade geometry of nozzle, rotor 1 and rotor 2 that are twisted along the span, spacing between them, tip clearance provided on rotors and also because of oppositely rotating rotors. Present work analyzes the flow field through the nozzle and rotors at planes taken at various axial chord distances. Blade-to-Blade contours and the Hub-to-tip plots reveal the actual scenario of flow in the turbine stage. Nozzle and the two rotors are modeled in case of the CRT configuration. Boundary conditions are specified as pressure at inlet of the nozzle and flow rate at the outlet of rotor 2. Total pressure, velocity, entropy and TKE distribution through the Blades are used to identify the flow over CRT. Flow through the Blade rows is distinguished by effects of boundary layer, secondary flows near the Hub, pressure gradient effects, presence of vortical flow structures in the passage and near the tip. Total pressure distribution near the midspan in case of nozzle and rotors show the presence of boundary layers and wake regions. Entropy and TKE contours show the loss regions in all the Blade rows. Flow losses are more in rotor 2 than rotor 1. Secondary velocity vectors show the presence of vortex regions in the passage and tip clearance. Blade-to-Blade contours of CRT reveal the actual flow scenario surrounding the Blades. Hub-to-tip plots show the variations of flow parameters while moving from the bottom to top most position of Blade. Thus, the present work identifies the exact flow structure in a counter rotating turbine and paves the way for researchers to negotiate flow losses and improve the CRT performance further.

Most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. To solve the problem, this paper utilizes Zernike Moment (ZM) and Pseudo Zernike Moment (PZM) to extract object contour features in all situations such as rotation, scaling and shifting of object inside the image. The proposed method consist of three steps: first step employs Line Detection with contours (LDC) in order to find the object region based on the connected components objects inside the image. In the second step, PZM is applied on the detected object regions to extract feature vector. Regarding to investigate the effectiveness of classifier at the final stage, the SVM and KNN classifiers are employed to extract final object contours. Experimental results on Caltech-101 dataset shows that classification rate is improved to 96.46%. In comparison to the former contour detectors, that proves the ability of the proposed method to detect object boundary in the most of the contour’s changes such as rotation or scaling.

Impellers with splitter Blades are used for pumps and compressors in the design of turbomachines. Design parameters such as the number of Blades, Blade discharge angle and impeller discharge diameter impact affect pump performance and energy consumption. In this study, the effect of the number of Blades (z=5, 6, and 7), Blade discharge angles (β 2b=25 , and β 2b=35 ) and splitter Blade lengths (40, 55, 70, and 85% of the main Blade length) on Deep Well Pump (DWP) performance has been studied experimentally. In the experiments, pump casing, Blade inlet angle, Blade thickness, Blade width and impeller inlet and discharge diameters have been kept fixed while other parameters such as the number of Blades, Blade discharge angles and splitter Blade lengths have been allowed to vary. As a result of the experimental study, the highest efficiency of all the impellers for best efficiency point (b. e. p) has been obtained on the impeller with the number of Blades z=6, Blade discharge angle  2b=25 and 85% splitter Blade addition compared to impellers without splitter Blades.