Impact of rotor geometry optimization on the off-design ORC turbine performance

Witanowski, Łukasz; Klonowicz, Piotr; Lampart, Piotr; Klimaszewski, Piotr; Suchocki, Tomasz; Jędrzejewski, Łukasz; Zaniewski, Dawid; Ziółkowski, Paweł

doi:10.1016/j.energy.2022.126312

Cited by 9 publications

(3 citation statements)

References 40 publications

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“…A technique described in previous articles by the authors [44,61,62] for the optimization of the shape has been used for the optimization of the axial and radial turbine stage. The flow efficiency of the last stage was improved by utilizing a hybrid algorithm termed HNMPSO.…”

Section: Discussionmentioning

confidence: 99%

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Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine

Ziółkowski,

Witanowski,

Głuch

et al. 2024

Energies

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This article focuses principally on the comparison baseline and the optimized flow efficiency of the final stage of an axial turbine operating on a gas–steam mixture by applying a hybrid Nelder–Mead and the particle swarm optimization method. Optimization algorithms are combined with CFD calculations to determine the flowpaths and thermodynamic parameters. The working fluid in this study is a mixture of steam and gas produced in a wet combustion chamber, therefore the new turbine type is currently undergoing theoretical research. The purpose of this work is to redesign and examine the last stage of the gas–steam turbine’s flow characteristics. Among the optimized variables, there are parameters characterizing the shape of the endwall contours within the rotor domain. The values of the maximized objective function, which is the isentropic efficiency of the turbine stage, are found from the 3D RANS computation of the flowpath geometry changing during the improvement scheme. The optimization process allows the stage efficiency to be increased by almost 4 percentage points. To achieve high-quality results, a mesh of over 20 million elements is used, where the percentage error in efficiency between the previous and current mesh sizes drops below 0.05%.

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Section: Discussionmentioning

confidence: 99%

“…In this work, the CFD calculation methodology follows the same published approach in our previous works [61,62]. Additionally, as mentioned earlier, mesh testing was conducted to ensure the accuracy of the results.…”

Section: Methods Validationmentioning

confidence: 99%

Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine

Ziółkowski,

Witanowski,

Głuch

et al. 2024

Energies

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“…Xu, G., et al [13] optimized a radial-axial two-stage turbine using GA for supercritical conditions. Witanowski, Ł. et al [14] optimized an axial turbine with R7100 using the Nelder-Mead method. Variable impact comparison revealed a 30% performance decrease with a 60% computation time reduction.…”

Section: Introductionmentioning

confidence: 99%

A Design Optimization of Organic Rankine Cycle Turbine Blades with Radial Basis Neural Network

Seo,

Lee,

Han

2023

Energies

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In the present study, a 100 kW organic Rankine cycle is suggested to recover heat energy from commercial ships. A radial-type turbine is employed with R1233zd(E) and back-to-back layout. To improve the performance of an organic Rankine power system, the efficiency of the turbine is significant. With the conventional approach, the optimization of a turbine requires a considerable amount of time and involves substantial costs. By combining design of experiments, an artificial neural network, and Latin hypercube sampling, it becomes possible to reduce costs and achieve rapid optimization. A radial basis neural network with machine learning technique, known for its advantages of being fast and easily applicable, has been implemented. Using such an approach, an increase in efficiency greater than 1% was achieved with minimal design changes at the first and second turbines.

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Organic Rankine cycle turbogenerator cooling – Optimization of the generator water jacket heat exchange surface

Zaniewski¹,

Klimaszewski

Klonowicz

et al. 2023

Applied Thermal Engineering

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Impact of rotor geometry optimization on the off-design ORC turbine performance

Cited by 9 publications

References 40 publications

Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine

Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine

A Design Optimization of Organic Rankine Cycle Turbine Blades with Radial Basis Neural Network

Organic Rankine cycle turbogenerator cooling – Optimization of the generator water jacket heat exchange surface

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