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Neetu Srivastava - IEEE Xplore Author Profile

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The present study utilizes the support vector regression (SVR) technique with a cubic kernel to forecast the performance of a double-pipe heat exchanger using T-W tape inserts with wing-width ratios of 0.31, 0.47, and 0.63. The SVR model that is established is applied to predict two key parameters, namely, the thermal performance (η) and the friction factor (f). Various scenarios are examined by c...Show More
Battery thermal management systems play a critical role in improving their power capability, extending lifetime, and minimizing the probability of thermal runaway. These systems aim to maintain a regulated operating temperature by removing heat from the battery pack and homogenizing the temperature within and between the cells. Precisely predicting the outlet fluid temperature is crucial to enhanc...Show More
This study provides a framework to predict the shear stress over a symmetrically stenosed arterial wall under the impact of magnetic field using machine learning algorithms. We investigated the magnetohydrodynamics blood flow with the help of machine learning techniques. The considered model is governed by the principles of MHD. To predict the flow patterns and velocity of the blood flow it is imp...Show More
Locking range of DLL (Delay Locked Loop) depends upon channel length modulation effect of CMOS. Via constant current source/sink Charge-pump adds/removes charges to/from a loop filter. A new feedback topology is used in proposed charge pump (CP) to reduce the current mismatch in charge pump mismatch for PET (Positron Emission Tomography) imaging applications. Simulations are performed in cadence s...Show More