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Temporal flow chart of the proposed algorithm, with spatial dependencies between steps omitted for clarity.
Source publication
The development and application of a compressible hybrid lattice Boltzmann method to high Mach number supercritical and dense gas flows are presented. Dense gases, especially in Organic Rankine Cycle turbines, exhibit nonclassical phenomena that offer the possibility of enhancing turbine efficiency by reducing friction drag and boundary layer separ...
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Citations
... 9,10 The efficiency of the ORC system can be maximized by carefully designing the system components and selecting the appropriate working fluid. [11][12][13] In the ORC system, the expander is one of the core components, which directly affects the energy conversion efficiency and output power of the system. 14,15 The expander is usually in the form of a turbine. ...
The organic Rankine cycle (ORC) represents an effective technology for the recovery of medium- and low-temperature waste heat. Within this system, the turbine expander plays a critical role in determining the reliability and efficiency of the overall process. This paper presents a structural optimization approach that integrates a radial basis function (RBF) neural network model with the nondominated sorting genetic algorithm II (NSGA-II), considering the isentropic efficiency and power of the ORC turbine expander using R1233zd(E) as the optimization objectives. Utilizing the design-of-experiments method in conjunction with simulation, a high-precision RBF neural network model was developed and trained. The external performance and internal flow characteristics of the original and optimized model are compared. In addition, the entropy production method is used to locate and quantitatively evaluate the energy losses. The results indicate that the RBF neural network model exhibits high predictive accuracy, with a correlation coefficient (R²) exceeding 0.9 for both objective functions. The optimization process significantly enhanced the performance of the ORC turbine expander. Under Q/Qd = 1.2, the isentropic efficiency and power are significantly improved by 6.13% and 33.96%. The optimized model can accommodate a larger range of flow variations, increasing the efficient operation region by 1.28 times. The energy loss of the ORC turbine expander decreases by an average of over 17% due to the effective suppression of vortices at the leading edge and outlet of the impeller. This work provides a valuable reference for improving the performance of radial turbine expanders for waste heat recovery and other application fields.
