Numerical simulation for flow characteristics of axial flow hydraulic turbine runner

Prasad, Vishnu

doi:10.1016/j.egypro.2011.12.1208

Cited by 23 publications

(12 citation statements)

References 2 publications

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“…The 3D-flow modeling approach herein was primarily based on the abundant literature about CFD applications in hydroturbine flows. Steady-state Reynolds-Averaged Navier-Stokes (RANS) formulations are the core of industry practice for calculating flows around hydroturbines and supporting structures (Hellström, Marjavaara, & Lundström, 2007;Khan, Wicklein, Rashid, Ebner, & Richards, 2004;Maruzewski et al, 2010;Nennemann, Vu, & Farhat, 2005;Prasad, 2012;Roh, Suh, Jung, & Jh, 2010;Wu, Shimmei, Tani, Niikura, & Sato, 2007). Alternatives to RANS formulations are the so-called eddy-resolving techniques, e.g.…”

Section: Computational Fluid Dynamicsmentioning

confidence: 99%

The effects of sampling location and turbulence on discharge estimates in short converging turbine intakes

Romero-Gómez

Harding

Richmond

2017

Engineering Applications of Computational Fluid Mechanics

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Standards provide recommendations for best practice when installing current meters to measure fluid flow in closed conduits. A central guideline requires the velocity distribution to be regular and the flow steady. Because of the nature of the short converging intakes typical of low-head hydroturbines, these assumptions may be invalid if current meters are intended to be used to estimate discharge. Usual concerns are (1) the effects of the number of devices, (2) the sampling location and (3) the high turbulence caused by the presence of fish diversion screens. These three effects were examined in the present study by using 3D simulated flow fields in both steady-state and transient modes. In the process of describing an application at an existing hydroturbine intake at Ice Harbor Dam, the present work outlined the methods involved, which combined computational fluid dynamics, laboratory measurements in physical models of the hydroturbine, and current meter performance evaluations in experimental settings. The main conclusions in this specific application were that a steady-state flow field sufficed to determine the adequate number of meters and their location, and that both the transverse velocity and turbulence intensity had a small impact on estimate errors. However, while it may not be possible to extrapolate these findings to other field conditions and measuring devices, the study laid out a path to conduct similar assessments in other applications. ARTICLE HISTORY

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Section: Computational Fluid Dynamicsmentioning

confidence: 99%

The effects of sampling location and turbulence on discharge estimates in short converging turbine intakes

Romero-Gómez

Harding

Richmond

2017

Engineering Applications of Computational Fluid Mechanics

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“…CFD simulation provides detailed flow information inside turbine space effectively and performance characteristics of turbine in terms of global as well as local parameters (Chica et al, 2013 andPrasad, 2012). The application of CFD is steadily increasing to improve design of hydraulic turbines (Prasad, Sayann, & Krishnamachar, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Applying this method for different alternatives in design optimizations is extremely costly and time consuming. Computational fluid dynamics (CFD) has become a cost effective tool for predicting detailed flow information in turbine space to enable the selection of best design (Prasad, 2012;Prasad & Khare, 2012). Using CFD simulation on computers, the response time is very short and the modification can be investigated in a short time (Busea & Jianu, 2004).…”

Section: Introductionmentioning

confidence: 99%

CFD Simulation and Optimization of Very Low Head Axial Flow Turbine Runner

Tobo

Ancha

Tibba

2015

Int. J. Renew. Energy Dev.

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ABSTRACT:The main objective of this work is Computational Fluid Dynamics (CFD) modelling, simulation and optimization of very low head axial flow turbine runner to be used to drive a centrifugal pump of turbine-driven pump. The ultimate goal of the optimization is to produce a power of 1kW at head less than 1m from flowing river to drive centrifugal pump using mechanical coupling (speed multiplier gear) directly. Flow rate, blade numbers, turbine rotational speed, inlet angle are parameters used in CFD modeling, simulation and design optimization of the turbine runner. The computed results show that power developed by a turbine runner increases with increasing flow rate. Pressure inside the turbine runner increases with flow rate but, runner efficiency increases for some flow rate and almost constant thereafter. Efficiency and power developed by a runner drops quickly if turbine speed increases due to higher pressure losses and conversion of pressure energy to kinetic energy inside the runner. Increasing blade number increases power developed but, efficiency does not increase always. Efficiency increases for some blade number and drops down due to the fact that change in direction of the relative flow vector at the runner exit, which decreases the net rotational momentum and increases the axial flow velocity.

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“…The required output is 150 kW per unit under a head of 2.5 m. The main working parameters of the prototype turbine are runner diameter 1.6 m, 3 runner blades, 15 guide-vane blades, rated head 2.5 m, highest head 3.65 m, lowest head 2.0 m, average head 2.5 m, and design flow rate 8.0 m 3 /s. The flow field was calculated by CFD theory [14][15][16] to analyze the influence on turbine performance of unilateral and double guide vanes. Using a 1 : 8 ratio, the prototype turbine was scaled down to build a model turbine for model tests.…”

Section: Introductionmentioning

confidence: 99%

Bidirectional Power Performance of a Tidal Unit with Unilateral and Double Guide Vanes

Yang

Zheng²,

Zhou

et al. 2013

Advances in Mechanical Engineering

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To improve the bidirectional power performance of a tidal unit, two designs were investigated. The use of unilateral or double guide vanes in a tubular tidal unit influences the performance of the hydraulic unit. Based on the N-S equations and the RNGturbulence model, the SIMPLEC algorithm was used for 3D steady-state numerical simulation of the entire turbine flow passage with unilateral and double guide vanes. The internal flow condition under positive and reverse power generation conditions was also analyzed. At the same time, the turbine, with a runner 1.6 m in diameter, was scaled down to 0.35 m diameter for model tests. The model tests were based on a multifunction hydromechanical test bench at Hohai University. The water head, discharge, and torque of the tubular turbine were, respectively, tested using a pressure difference sensor, electromagnetic flow meter, and torque meter under different guide-vane openings. The results show that turbine efficiency in the model test is slightly lower than that predicted by numerical simulation under the same conditions. However, the difference is not large. With double side guide vanes, although the efficiency of positive power generation decreased, the efficiency of reverse power generation is greatly improved.

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Numerical simulation for flow characteristics of axial flow hydraulic turbine runner

Cited by 23 publications

References 2 publications

The effects of sampling location and turbulence on discharge estimates in short converging turbine intakes

The effects of sampling location and turbulence on discharge estimates in short converging turbine intakes

CFD Simulation and Optimization of Very Low Head Axial Flow Turbine Runner

Bidirectional Power Performance of a Tidal Unit with Unilateral and Double Guide Vanes

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