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Shiv Nadar University

A novel and strategic green energy production method that utilizes relative wind generated from moving vehicles is presented. A speeding train generates an enormous wake of wind around it, which stocks a substantial amount of kinetic energy. In this study, this freely accessible wind power is harvested by installing a modified savonius wind turbine within the slipstream region of the train. A computer-oriented fluid-solid integrate simulation of wind turbine propelled by train-induced wind is performed by executing all physically realistic boundary conditions. The numerical study is based on open-source CFD toolbox OPENFOAM, and the results were validated against benchmark experimental study. Parametric sensitivity analysis such as optimal turbine performance within the slipstream regime, torque prediction from express trains, two opposite crossing trains, tunnel condition, and turbine wind turbine clusters arrangement has been reported. This study enhances the understanding of the power generation by the turbine from the train slipstream which is not reported in any open literature as far as the authors’ present knowledge goes. Copyright © 2020 by ASME

Mathematics

(SoNS) School of Natural Sciences

Mechanical Engineering

(SoE) School of Engineering

Journal of Energy Resources Technology, Transactions of the ASME

A Numerical study toward harvesting power from train slipstream using savonius rotor

Here, an excellent cavitation erosion-corrosion resistance of stainless steel using a novel severe surface deformation technique, reciprocating friction processing (RFP) was demonstrated. The RFP treated stainless steel showed nano-grained, nano-twinned microstructure along with high dislocation density. The RFP treated steel significantly surpassed the performance of advanced structural materials including high entropy alloy (Al0.1CoCrFeNi) and complex concentrated alloy (SiC reinforced Al0.1CoCrFeNi), demonstrating the lowest cavitation erosion and cavitation erosion-corrosion rates for this class of materials. The RFP treated steel demonstrated outstanding corrosion behavior in 3.5\% NaCl solution as well. The unusual performance of RFP treated steel is attributed to its excellent mechanical strength and strong passivating behavior. © 2020 Elsevier B.V.

Wear

Cavitation erosion-corrosion resilient surfaces through reciprocating friction processing

Savonius wind turbines are special class of vertical axis wind turbines (VAWTs). These are low-cost drag-driven turbines and are known to be inefficient. It is proposed in this study that a simple modification to the turbine blade design can yield a significant improvement in power efficiency. The performance of the new design is extensively studied on OPENFOAMv1812, a popular open source computational fluid dynamics (CFD) library. The flow equations coupled with equations of rotation of the turbine are solved on an overset mesh framework. This study also serves as a validation of recently released overset support in OPENFOAM. The turbulence is incorporated by coupling Reynolds-averaged Navier-Stokes (RANS) with shear stress transport (SST) κ-ω eddy viscosity turbulence model. The turbulence parameters are set to produce a flow with the Reynolds number, Re=4.8 × 105. To have better confidence in simulations, this study also presents a comparison of numerical flow over conventional Savonius turbine designs with the published data. It is observed that a majority of CFD analysis on wind turbine designs are performed for the fixed tip speed ratio on a traditional static mesh structure. But, in this CFD study, a winddriven rotation of Savonius turbine is simulated on an overset dynamics approach. The results of the study are compared and discussed based on the predicted moment and power coefficients, pressure variation on the blades, flow velocity field, and wake analysis. The study indicates that the blade design presented here has a potential to increase the power efficiency of a Savonius wind turbine by 10-28\%. © 2020 American Society of Mechanical Engineers (ASME). All rights reserved.

World University root node

Improvement in savonius wind turbines efficiency by modification of blade designs - A numerical study

Models of biochemical networks are frequently complex and high-dimensional. Reduction methods that preserve important dynamical properties are therefore essential for their study. Interactions in biochemical networks are frequently modeled using Hill functions (xn/Jn+xn). Reduced ODEs and Boolean approximations of such model networks have been studied extensively when the exponent n is large. However, while the case of small constant J EquationSource&gt; appears in practice, it is not well understood. We provide a mathematical analysis of this limit and show that a reduction to a set of piecewise linear ODEs and Boolean networks can be mathematically justified. The piecewise linear systems have closed-form solutions that closely track those of the fully nonlinear model. The simpler, Boolean network can be used to study the qualitative behavior of the original system. We justify the reduction using geometric singular perturbation theory and compact convergence, and illustrate the results in network models of a toggle switch and an oscillator. © 2014, Society for Mathematical Biology.