Aerodynamic Design and Off-design Performance Analysis of a Multi-Stage S-CO2 Axial Turbine Based on Solar Power Generation System

Shi, Dongbo; Zhang, Lei; Xie, Yuanyuan; Zhang, Di

doi:10.3390/app9040714

Cited by 26 publications

(13 citation statements)

References 19 publications

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“…Then, further 3-D aerodynamic optimization was carried out, mainly including inlet and outlet flow angle correction, flow matching of rotor and stator blades, blade profile optimization, etc. These optimization methods have achieved good results in previous research [24,44,45]. The detailed thermodynamic design parameters, geometric parameters, performance parameters, and blade profiles of the designed S-CO 2 turbine are shown in Table 2.…”

Section: Cfd Off-design Pre-analysismentioning

confidence: 88%

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Off-Design Performance Prediction of a S-CO2 Turbine Based on Field Reconstruction Using Deep-Learning Approach

2020

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The reliable design of the supercritical carbon dioxide (S-CO2) turbine is the core of the advanced S-CO2 power generation technology. However, the traditional computational fluid dynamics (CFD) method is usually applied in the S-CO2 turbine design-optimization, which is a high computational cost, high memory requirement, and long time-consuming solver. In this research, a flexible end-to-end deep learning approach is presented for the off-design performance prediction of the S-CO2 turbine based on physical fields reconstruction. Our approach consists of three steps: firstly, an optimal design of a 60,000 rpm S-CO2 turbine is established. Secondly, five design variables for off-design analysis are selected to reconstruct the temperature and pressure fields on the blade surface through a deconvolutional neural network. Finally, the power and efficiency of the turbine is predicted by a convolutional neural network according to reconstruction fields. The results show that the prediction approach not only outperforms five classical machine learning models but also focused on the physical mechanism of turbine design. In addition, once the deep model is well-trained, the calculation with graphics processing unit (GPU)-accelerated can quickly predict the physical fields and performance. This prediction approach requires less human intervention and has the advantages of being universal, flexible, and easy to implement.

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Section: Cfd Off-design Pre-analysismentioning

confidence: 88%

“…The general forms of the three control equations mass conservation equation, momentum conservation equation, and energy conservation equation can be expressed as follows [23,24]:…”

Section: Cfd Analysis Methodsmentioning

confidence: 99%

Off-Design Performance Prediction of a S-CO2 Turbine Based on Field Reconstruction Using Deep-Learning Approach

2020

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“…S-CO 2 was used as the working substance. According to the literature [18] and related data (NIST database), the thermal physical data of microsupercritical and microsubcritical CO 2 were integrated. The thermal physical property continuous function was constructed by the Kriging surrogate model.…”

Section: Boundary Conditonsmentioning

confidence: 99%

Aerodynamic Optimization Design of a 150 kW High Performance Supercritical Carbon Dioxide Centrifugal Compressor without a High Speed Requirement

Shi

Xie

2020

Applied Sciences

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Supercritical carbon dioxide (S-CO2) Brayton cycle technology has the advantages of excellent energy density and heat transfer. The compressor is the most critical and complex component of the cycle. Especially, in order to make the system more reliable and economical, the design method of a high efficiency compressor without a high speed requirement is particularly important. In this paper, thermodynamic design software of a S-CO2 centrifugal compressor is developed. It is used to design the 150 kW grade S-CO2 compressor at the speed of 40,000 rpm. The performance of the initial design is carried out by a 3-D aerodynamic analysis. The aerodynamic optimization includes three aspects: numerical calculation, design software and the flow part geometry parameters. The aerodynamic performance and the off-design performance of the optimal design are obtained. The results show that the total static efficiency of the compressor is 79.54%. The total pressure ratio is up to 1.9. The performance is excellent, and it can operate normally within the mass flow rate range of 5.97 kg/s to 11.05 kg/s. This research provides an intelligent and efficient design method for S-CO2 centrifugal compressors with a low flow rate and low speed, but high pressure ratio.

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“…In the field of new energy utilization, solar and wind power generation systems are severely affected by geographical distribution, seasonal variations, and day-night cycles. Shi et al [8] designed a 10 MW S-CO 2 three-stage axial turbine, which can adapt to the variable operating conditions of the solar power generation system and meet the accompanying design requirements. Wang et al [9] developed a hybrid fuzzy analytic hierarchy process (FAHP) and Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS) to select wind power plant sites in Vietnam, which also provided a useful guideline for wind power plant location selection in other countries.…”

Section: Sustainable Energy Developmentmentioning

confidence: 99%

Green Energy and Applications

Tsai

2019

Applied Sciences

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Sustainable energy is increasing in importance as Earth’s resources continue to be depleted in an ascending trend year by year. The utilization of sustainable energy is influenced by many factors, such as technology, the economy, and business management. Although it is unaffected by energy shortages, it is influenced by natural conditions—for example, hydraulic, wind, and solar power generation are all necessarily dependent on resource availability. In addition, investment and maintenance costs are high, which has been becoming an important obstacle to the utilization of sustainable resources. Therefore, a number of scientists are seeking new technologies and methods for improving renewable energy, to alleviate the impact of resource shortage on the world’s economy.

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Aerodynamic Design and Off-design Performance Analysis of a Multi-Stage S-CO2 Axial Turbine Based on Solar Power Generation System

Cited by 26 publications

References 19 publications

Off-Design Performance Prediction of a S-CO2 Turbine Based on Field Reconstruction Using Deep-Learning Approach

Off-Design Performance Prediction of a S-CO2 Turbine Based on Field Reconstruction Using Deep-Learning Approach

Aerodynamic Optimization Design of a 150 kW High Performance Supercritical Carbon Dioxide Centrifugal Compressor without a High Speed Requirement

Green Energy and Applications

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