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mendeley.com
article
https://www.mendeley.com/catalogue/a33e4916-7667-32ed-9d2a-93ffad537dd5
# Francis turbine blade design on the basis of port area and loss analysis. In this study, a Francis turbine with specific speed of 130 m-kW was designed on the basis of the port area and loss analysis. The meridional shape of the runner was designed focusing mainly on the combination of the guide vane loss analysis and experience. The runner blade inlet and outlet angles were designed by calculation of Euler's head, while the port area of blade was modified by keeping constant angles of the blade at inlet and outlet. The results show that the effect of the port area of runner blade on the flow exit angle from runner passage is significant. A correct flow exit angle reduces the energy loss at the draft tube, thereby improving the efficiency of the turbine. The best efficiency of 92.6% is achieved by this method, which is also similar to the design conditions by the one dimension loss analysis.
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empoweringpumps.com
article
https://empoweringpumps.com/cfturbo-francis-turbine-design-for-hydropower-gen…
# Francis Turbine Design for Hydropower Generation. Home » Francis Turbine Design for Hydropower Generation. CFTurbo Francis Turbine Design for Hydropower Generation. As the world shifts to greater reliance on sustainable energy sources, the design and optimization of relevant turbomachinery devices are imperative. The CFturbo software allows its users to build and optimize all components of Hydro Turbines, as shown in this introductory case study of a Francis turbine. The Francis turbine is a longstanding monument in the world of turbomachinery, dating back to the mid-19th century. The Francis turbine was invented in the mid-19th century by engineer James Bichens Francis to produce hydroelectric power. A baseline geometry was prepared using the Hydro Turbine module within the CFturbo software. Figure 2 Francis Turbine Design – CFturbo, 3D View. Using a CFturbo engineered Python script solution in conjunction with the Replace Part Operation within Star-CCM+, 25 unique Francis Turbine CFturbo designs were created and simulated using a mesh of approximately 8.5 million polyhedral cells and a steady-state solver.
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asmedigitalcollection.asme.org
article
https://asmedigitalcollection.asme.org/fluidsengineering/article/142/10/10121…
Previous studies suggested variable speed operation (VSO) of Francis turbines as a measure to improve the efficiency at off-design operating conditions.
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blog.adtechnology.com
article
https://blog.adtechnology.com/machine-learning-hydraulic-turbine-francis-runn…
# Machine Learning for Hydraulic Francis Runner Design Optimization. A new methodology uses **3D Inverse Design** technology coupled with **Reactive Response Surface (RRS) Machine Learning** to rapidly optimize Francis hydraulic turbine runners. This approach requires only **10 input parameters** to explore a vast design space and, in just a few hours, discovered optimized designs that showed significant performance gains, including **5-9 percentage points higher efficiency** and an **8-28% increase in shaft power** over the baseline model. In this blog we look at how ADT’s Reactive Response Surface + CAE technology (RRS+CAE) is driving better hydraulic turbine design through Machine Learning. ## • The Francis Runner performance challenge - and the solution • Where to start - Generate a meanline Francis runner design • 3D Inverse Design is the enabling technology for Machine Learning • How to establish a baseline for turbine performance • Optimization of a Francis runner via Machine Learning • RRS gives design choices and performance gains • Final validation of the Machine Learning solution • Conclusions.
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pubs.aip.org
article
https://pubs.aip.org/aip/adv/article/13/7/075208/2901828/Numerical-study-of-t…
The Francis turbine is designed in accordance with the rated head H (m), rated flow rate Q (m), and rated speed n (rpm) within the constraints
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sciencedirect.com
article
https://www.sciencedirect.com/science/article/abs/pii/S0960148115303761
This paper reports on methodology for designing Francis runner blade. This involves finding best outlet angle (β2) and blade angle distribution (β-distribution)
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mdpi.com
article
https://www.mdpi.com/1996-1073/9/3/164
Evaluation of the Fluid Model Approach for the Sizing of Energy Storage in Wave-Wind Energy Systems. Analysis of the Potential for Use of Floating Photovoltaic Systems on Mine Pit Lakes: Case Study at the Ssangyong Open-Pit Limestone Mine in Korea. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal. In this study, a Francis turbine with specific speed of 130 m-kW was designed on the basis of the port area and loss analysis. The results show that the effect of the port area of runner blade on the flow exit angle from runner passage is significant. In this study, a new method on basis of the port area and loss analysis to design a Francis turbine runner was developed for the Miryang power station in Korea. The meridional shape of the runner was designed on the basis of the combination of the guide vane loss analysis and experience.
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youtube.com
video
https://www.youtube.com/watch?v=CavfXOt3Dew
How to Design Wind Turbine Blade Geometry for Optimal Aerodynamic Efficiency
Engineering with Rosie
122000 subscribers
2388 likes
101573 views
10 Nov 2020
This is part 3 of my series: “How Does a Wind Turbine Work?” In this video I show you how to use the blade element momentum theory, BEM, that we discussed in the last videos, to design an efficient wind turbine rotor.
Topics include:
00:33 Lift equation
00:47 Optimum aerodynamic conditions with constant circulation along the span
01:05 How the local wind speed and angle vary along the length of the blade
01:22 How to change the chord and twist angle along the blade span
01:50 Why designers normally modify the chord distribution to have smaller chords at the root
02:28 The torque equation and why the tip's aerodynamics is more important than the root
02:52 What happens if you use a turbine at a different wind speed than it was designed for
03:46 How variable speed turbines can operate efficiently over a wind range of wind speeds
04:18 What is tip speed ratio (TSR) and why is it important to wind turbine designers?
04:48 Blade solidity
06:07 How to find a starting point in the wind turbine blade design process
07:22 Why are wind turbine blades getting so skinny?
07:54 Reducing wind turbine noise by limiting rotational speed
08:29The different requirements of aerofoils at the root versus tip of the blade
Check out part one and two of my “How Does a Wind Turbine Work?” series where I go through the mechanical engineering and aerodynamic theory needed to understand how a wind turbine works and design a wind turbine blade:
How Much Energy is in the Wind?
https://www.youtube.com/watch?v=7-awFXqisYA&t=7s
How to Calculate Wind Turbine Power Output: Blade Element Momentum Method
https://youtu.be/o6BCnhubbiQ
If you want to follow the derivations I mentioned in this video then check out section 3.7.2 of Burton's "Wind Energy Handbook."
Available to buy from Amazon (affiliate link), or your university library probably has it!
https://amzn.to/32Pb1fh
The optimum aerodynamic design equation at 6:10 has the following parameters:
sigma_r = chord solidity at the radial location (chord length divided by swept circumference at that radial location)
lambda = tip speed ratio (tip speed due to blade rotation (radial location times rotational speed) divided by wind speed)
C_l = local lift coefficient
mu = r/R (radial location divided by radius)
133 comments