The Experts below are selected from a list of 4740 Experts worldwide ranked by ideXlab platform
Lorenzo Tocci - One of the best experts on this subject based on the ideXlab platform.
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a neural network approach to the combined multi objective optimization of the thermodynamic cycle and the Radial inFlow Turbine for organic rankine cycle applications
Applied Energy, 2019Co-Authors: Laura Palagi, Enrico Sciubba, Lorenzo TocciAbstract:Abstract An optimization model based on the use of Neural Network surrogate models for the multi-objective optimization of small scale Organic Rankine Cycles is presented, which couples the optimal selection of the thermodynamic parameters of the cycle with the main design parameters of In-Flow Radial Turbines. The proposed approach proved well suited in the resolution of the highly non-linear constrained optimization problems, typical of the design of energy systems. Indeed the use of a surrogate model allows to adopt gradient based methods that are computationally more efficient and accurate than conventional derivative-free optimization algorithms. The intensive numerical experiments demonstrate that assuming a constant efficiency for the In-Flow Radial Turbine leads to an error in the evaluation of the performance of the system of up to 50% and that the optimization approach proposed improves the accuracy of the solution and it reduces the computational time required to reach it by two orders of magnitude. An holistic approach in which the Turbine and the thermodynamic cycle are designed simultaneously and the use of multi-objective optimization proved to be essential for the design of Organic Rankine cycles that satisfy both size and performance criteria.
L Q Liu - One of the best experts on this subject based on the ideXlab platform.
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performance analysis of high speed cryogenic turbo expander at cooling process based on numerical and experimental study
International Journal of Refrigeration-revue Internationale Du Froid, 2020Co-Authors: L Y Xiong, Na Peng, I Dong, L Q LiuAbstract:Abstract In order to make a detailed understanding of the cryogenic turbo-expander off-design performance at cool-down procedure, an extensive experimental and numerical program have been carried out on a mixed and inward Flow Radial Turbine. According to the design and cooling process condition, just like pressure at stator inlet or brake power of the turbo-expander, a series of CFD simulations were carried out in order to guide design and off-design iterations towards achieving a matched Flow capacity for each situation. The analyses also include the study of the effect of different gas models on the CFD calculations. Through the results analysis it was concluded that the direct use of the Hepak database for the real gas properties in the CFD solver improve the prediction of the thermodynamic properties and so the performance of the turbo-expander. With experimental comparison, the cryogenic turbo-expander off-design performance at cooling process can be better known.
Laura Palagi - One of the best experts on this subject based on the ideXlab platform.
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a neural network approach to the combined multi objective optimization of the thermodynamic cycle and the Radial inFlow Turbine for organic rankine cycle applications
Applied Energy, 2019Co-Authors: Laura Palagi, Enrico Sciubba, Lorenzo TocciAbstract:Abstract An optimization model based on the use of Neural Network surrogate models for the multi-objective optimization of small scale Organic Rankine Cycles is presented, which couples the optimal selection of the thermodynamic parameters of the cycle with the main design parameters of In-Flow Radial Turbines. The proposed approach proved well suited in the resolution of the highly non-linear constrained optimization problems, typical of the design of energy systems. Indeed the use of a surrogate model allows to adopt gradient based methods that are computationally more efficient and accurate than conventional derivative-free optimization algorithms. The intensive numerical experiments demonstrate that assuming a constant efficiency for the In-Flow Radial Turbine leads to an error in the evaluation of the performance of the system of up to 50% and that the optimization approach proposed improves the accuracy of the solution and it reduces the computational time required to reach it by two orders of magnitude. An holistic approach in which the Turbine and the thermodynamic cycle are designed simultaneously and the use of multi-objective optimization proved to be essential for the design of Organic Rankine cycles that satisfy both size and performance criteria.
Post Graduate Scholar Edward A Brizuela - One of the best experts on this subject based on the ideXlab platform.
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A Contribution to the Study of Exit Flow Angle in Radial Turbines
2020Co-Authors: Post Graduate Scholar Edward A BrizuelaAbstract:ABSTRACT The emergence and evolution of relative whirling motions in the exducer region of an Inward Flow Radial Turbine is discussed. Existing models of relative motion are reviewed and expanded by consideration of the effect of centrifugal forces differences arising from velocity gradients. It is shown that the often observed phenomenon of outlet overturn/underturn is inherent to the use of straight-helix exducers. Explicit mathematical relationships between exit velocities and radius are not available. If, however, such relationships could be considered linear, it is shown that two new reference radii may be identified such that the net outlet properties can be measured or computed at these locations as lump parameters. These radii are different from the often used hydraulic radius. The new models and reference radii are verified using published experimental data
L Y Xiong - One of the best experts on this subject based on the ideXlab platform.
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performance analysis of high speed cryogenic turbo expander at cooling process based on numerical and experimental study
International Journal of Refrigeration-revue Internationale Du Froid, 2020Co-Authors: L Y Xiong, Na Peng, I Dong, L Q LiuAbstract:Abstract In order to make a detailed understanding of the cryogenic turbo-expander off-design performance at cool-down procedure, an extensive experimental and numerical program have been carried out on a mixed and inward Flow Radial Turbine. According to the design and cooling process condition, just like pressure at stator inlet or brake power of the turbo-expander, a series of CFD simulations were carried out in order to guide design and off-design iterations towards achieving a matched Flow capacity for each situation. The analyses also include the study of the effect of different gas models on the CFD calculations. Through the results analysis it was concluded that the direct use of the Hepak database for the real gas properties in the CFD solver improve the prediction of the thermodynamic properties and so the performance of the turbo-expander. With experimental comparison, the cryogenic turbo-expander off-design performance at cooling process can be better known.