A CFD-Based Shape Design Optimization Process of Fixed Flow Passages in a Francis Hydro Turbine

Shrestha, Ujjwal; Choi, Young Do

doi:10.3390/pr8111392

Cited by 15 publications

(6 citation statements)

References 33 publications

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“…The response functions of standard response surface functions and Kriging function are Equations ( 11) and (12). Commonly used metrics for surrogate model error analysis include coefficient of determination R 2 , root mean square error (RMSE), and maximum relative error (MRE), which are calculated by the following Equations ( 13)-( 15) [26,27]:…”

Section: Research Methods Of Draft Tubementioning

confidence: 99%

Study of Draft Tube Optimization Using a Neural Network Surrogate Model for Micro-Francis Turbines Utilized in the Water Supply System of High-Rise Buildings

Xin,

Wu,

et al. 2024

Processes

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With the increasing popularity of clean energy, the use of micro turbines to recover surplus energy in the water supply pipelines of high-rise buildings has attracted more attention. This study adopts a predictor model based on Radial Basis Function Neural Network (RBFNN) to optimize the draft tube shape for micro-Francis turbines. The predictor model is formed on a dataset provided by numerical simulations, which are validated by lab tests. Specifically, numerical investigations are carried out in the shape of a draft tube to determine an optimal model. Additionally, the superiority of the RBFNN model in nonlinear optimization is verified by comparing it with other models under the same date sets. After that, the design parameters are optimized using RBFNN and sequential quadratic programming algorithm (SQPA). Finally, the turbine prototype is fabricated and tested on a lab test rig. The experimental results indicate that the numerical method adopted in this research is accurate enough for such a micro-Francis turbine performance prediction. Under the design conditions, the proposed micro-Francis turbine produces a power of 147 W with an efficiency of over 29%, which shows a considerable improvement compared to the initial prototype.

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Section: Research Methods Of Draft Tubementioning

confidence: 99%

Study of Draft Tube Optimization Using a Neural Network Surrogate Model for Micro-Francis Turbines Utilized in the Water Supply System of High-Rise Buildings

Xin,

Wu,

et al. 2024

Processes

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“…The results after fluid dynamics were analyzed were used to compare efficiency between the gaseous nitrogen turbines and the steam turbines. Then, internal centrifuge systems such as shafts, turbines, and axles were altered in accordance with analysis by the (CFD) program as shown in Figure 6 [69,70]. After the machine was modified in line with advanced engineering principles, it could be used more practically in a variety of new scenarios.…”

Section: Computational Fluid Dynamics (Cfd)mentioning

confidence: 99%

“…The energy consumption rate in the system was measured and it was found to be practical when adopted in industries. In addition to magnetic bearings, artificial intelligence (AI) and CFD programs should be applied to the system as well [69,[79][80][81]. They are used with this technology to analyze and control nitrogen gas flow in the turbine to provide a more precise evaluation and change materials resulting in a more efficient technology.…”

Section: Efficiency Comparison Of N 2 Generator and With Injection Steam Turbine Enginementioning

confidence: 99%

Advanced Power Generation Using a Nitrogen Turbine Engine Instead of a Conventional Injection Steam Turbine Engine

et al. 2021

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An ever-increasing demand for electrical power and soaring levels of energy consumption around the world have led to an energy crisis. Thus, this paper aims to review the conventional technologies against those of newer developments in electrical power generation such as using nitrogen generators. The nitrogen generator method is most appealing as it is a seemingly free energy already existing in nature. A nitrogen generator with a 5000 (Nm3/h) capacity has the potential to be used to analyze gas composition and the results are compared with the gas composition of a conventional steam turbine, which is used to pressurize 6000 (kWh) injection steam turbines. The magnetic bearing must be installed in both systems to modify all centrifuged systems which reduces all energy consumption in all systems by more than 50%. Artificial intelligence is used with the machine to analyze and control nitrogen gas flow to provide a more precise evaluation resulting in a more efficient technology. It should further be noted that the nitrogen turbine is superior to the steam turbine because it does not require the burning of fossil fuel to generate power. Hence, it is crucial to modify conventional technologies to improve energy sustainability and begin the long task of tackling environmental issues.

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“…The main hydro passage parts of the Francis turbine are composed of a spiral casing, stay vane, guide vane, runner, and draft tube. The flow instabilities in the fixed-flow passages can cause failure in the whole hydraulic turbine system [11], which will affect the power generation efficiency and stability of the whole power station. The performance of the hydraulic turbine determines whether the hydraulic turbine can work normally, which affects the utilization rate of water energy.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation and Analysis of Hydraulic Turbines Based on BIM for Sustainable Development

Sun,

Liu,

Zhang

et al. 2023

Sustainability

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Hydropower is considered to be an important way to achieve the sustainable development goal of human progress. The performance of turbines is very important to the safety and stability of hydropower stations. Most of the hydraulic turbine performance studies only use Computational Fluid Dynamics (CFD) for performance simulation, lacking the integration of Building Information Modeling (BIM) technology and CFD. Therefore, a performance analysis model of a Francis turbine based on BIM was put forward in this paper. The BIM software OpenBuildings Designer CONNECT Edition Update 10 was used to build the hydraulic turbine model, and then the BIM model was transferred to the CFD numerical simulation platform ANSYS through the intermediate format conversion. In the ANSYS environment, the numerical simulation of different working conditions was carried out with the help of Fluent 2021 R1 software. The numerical simulation results show that the fluid velocity gradient in the volute was 2~3 m/s under the three working conditions, which was relatively stable. The water flow could progress the guide vane mechanism at a higher speed, and the drainage effect of the volute was better. There were some negative pressure areas at the back of the runner blades and the inlet of draft tube, and the negative pressure value was as high as −420,000 Pa and −436,842 Pa under maximum head conditions, which were prone to cavitation erosion. It is proven that BIM supported the hydraulic turbine performance analysis and provided a geometric information model for hydraulic turbine CFD numerical simulation, meaning that the performance analysis model based on BIM is feasible. This study can expand the application value of BIM and provide guidance for the study of hydraulic turbine numerical simulation using BIM technology in combination with CFD methods.

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A CFD-Based Shape Design Optimization Process of Fixed Flow Passages in a Francis Hydro Turbine

Cited by 15 publications

References 33 publications

Study of Draft Tube Optimization Using a Neural Network Surrogate Model for Micro-Francis Turbines Utilized in the Water Supply System of High-Rise Buildings

Study of Draft Tube Optimization Using a Neural Network Surrogate Model for Micro-Francis Turbines Utilized in the Water Supply System of High-Rise Buildings

Advanced Power Generation Using a Nitrogen Turbine Engine Instead of a Conventional Injection Steam Turbine Engine

Numerical Simulation and Analysis of Hydraulic Turbines Based on BIM for Sustainable Development

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