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Multi-objective optimization of CO2 ejector by combined significant variables recognition, ANN surrogate model and multi-objective genetic algorithm
G Liu, L Pu, H Zhao, Z Chen, G Li - Energy, 2024 - Elsevier
The ejectors are crucial in enhancing the efficiency of the CO 2-based refrigeration cycle.
Although the ejector can be optimized by experimental and computational fluid dynamic …
Although the ejector can be optimized by experimental and computational fluid dynamic …
Thermodynamic performance evaluation of an ejector-enhanced transcritical CO2 parallel compression refrigeration cycle
T Bai, R Shi, J Yu - International Journal of Refrigeration, 2023 - Elsevier
A parallel compression cycle is one efficient approach to improving the transcritical CO 2
refrigeration cycle performance. This paper proposes a modified parallel compression …
refrigeration cycle performance. This paper proposes a modified parallel compression …
Performance improvement of CO2 two-phase ejector by combining CFD modeling, artificial neural network and genetic algorithm
G Liu, H Zhao, J Deng, L Wang, H Zhang - International Journal of …, 2023 - Elsevier
The ejector, as one of the core components of the CO 2 trans-critical ejection refrigeration
system, plays an important role in improving refrigeration capacity and reducing compressor …
system, plays an important role in improving refrigeration capacity and reducing compressor …
[HTML][HTML] Performance evaluation of supersonic flow for variable geometry radial ejector through CFD models based on DES-turbulence models, GPR machine …
This study aims to derive valuable insights for utilizing computational fluid dynamics (CFD)
based on reynolds-averaged navier–stokes (RANS) and detached eddy simulation (DES) …
based on reynolds-averaged navier–stokes (RANS) and detached eddy simulation (DES) …
A review of axial and radial ejectors: Geometric design, computational analysis, performance, and machine learning approaches
This review examines the critical role of ejectors in refrigeration systems, emphasizing the
need for a deeper understanding of their performance characteristics, particularly through a …
need for a deeper understanding of their performance characteristics, particularly through a …
Advanced exergy analysis of a CO2 two-phase ejector
L Zheng, Y Hu, C Mi, J Deng - Applied Thermal Engineering, 2022 - Elsevier
Ejector is meaningful and valuable to improve the transcritical CO 2 refrigeration system. To
study in-depth on the exergy destruction is significant for the performance enhancement of …
study in-depth on the exergy destruction is significant for the performance enhancement of …
Large Eddy Simulation of a supersonic air ejector
This paper presents a study on the flow topology in the mixing chamber of a supersonic
ejector using Large Eddy Simulation (LES). To this end, a supersonic air ejector of squared …
ejector using Large Eddy Simulation (LES). To this end, a supersonic air ejector of squared …
State of the Art of Modelling and Design Approaches for Ejectors in Proton Exchange Membrane Fuel Cell
C Antetomaso - Modelling and Simulation in Engineering, 2024 - Wiley Online Library
Proton exchange membrane fuel cell (PEMFC) has a promising future in the power
generation and transportation fields. Recirculation of unused anodic gases is fundamental to …
generation and transportation fields. Recirculation of unused anodic gases is fundamental to …
Numerical study on the interaction of geometric parameters of a transcritical CO2 two-phase ejector using response surface methodology and genetic algorithm
Y Li, J Deng, Y He - Applied Thermal Engineering, 2022 - Elsevier
In this study, the effect of the interaction of geometric parameters on the performance of the
rectangular transcritical CO 2 two-phase ejector was investigated, and a geometric …
rectangular transcritical CO 2 two-phase ejector was investigated, and a geometric …
Deep neural network modeling for CFD simulations: Benchmarking the Fourier neural operator on the lid-driven cavity case
In this work we present the development, testing and comparison of three different physics-
informed deep learning paradigms, namely the ConvLSTM, CNN-LSTM and a novel Fourier …
informed deep learning paradigms, namely the ConvLSTM, CNN-LSTM and a novel Fourier …