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Investigation of coupling effect on the evolution of Richtmyer-Meshkov instability at double heavy square bubbles 被引量:2
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作者 Satyvir Singh Dhouha Taib Jalleli 《Science China(Physics,Mechanics & Astronomy)》 SCIE EI CAS CSCD 2024年第1期52-70,共19页
This study investigates numerically the coupling effect on the evolution of Richtmyer-Meshkov instability at double heavy square bubbles.Five scenarios are considered,each with varying initial separations S/L(where L ... This study investigates numerically the coupling effect on the evolution of Richtmyer-Meshkov instability at double heavy square bubbles.Five scenarios are considered,each with varying initial separations S/L(where L demotes the side length of the square)ranging from 0.125 to 1.0.Squares are filled with SF6gas,and are enclosed by N2gas.The simulations of shock-induced multispecies flow are performed by solving the two-dimensional compressible Euler equations with a higher-order explicit modal discontinuous Galerkin solver.The simulations demonstrate that the flow morphology resulting from the coupling effect is highly dependent on the separation between two squares.When the separation is large,the squares experience a weaker coupling effect and evolve independently.While,as the separation reduces,the coupling effect manifests earlier in the interaction and becomes more substantial.As a result,this phenomenon greatly intensifies the motion of inner upstream/downstream vortex rings towards the symmetry axis,leading to the emergence of multiple jets such as the twisted downward,upward,and coupled jets.A thorough exploration of the coupling effect of double squares is conducted by analyzing the vorticity production.Notably,a significant quantity of vorticity is produced along the squares interface for smaller separation.Further,these coupling effects result in various interface features(upstream/downstream movement,and height/width evolution),and temporal variations of various spatially integrated fields.Finally,the analysis of the flow structure also considers the interaction between two more flow parameters,the Mach and Atwood numbers,in order to evaluate the coupling effects. 展开更多
关键词 RM instability shock wave double square bubbles coupling effect
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Modeling and optimization of industrial Fischer–Tropsch synthesis with the slurry bubble column reactor and iron-based catalyst 被引量:6
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作者 Chufu Li 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2018年第5期1102-1109,共8页
To optimize industrial Fischer-Tropsch (IT) synthesis with the slurry bubble column reactor (SBCR) and iron- based catalyst, a comprehensive process model for IT synthesis that includes a detailed SBCR model, gas ... To optimize industrial Fischer-Tropsch (IT) synthesis with the slurry bubble column reactor (SBCR) and iron- based catalyst, a comprehensive process model for IT synthesis that includes a detailed SBCR model, gas liquid separation model, simplified CO2 removal model and tail gas cycle model was developed. An effective iteration algorithm was proposed to solve this process model, and the model was validated by industrial demonstration experiments data (SBCR with 5.8 m diameter and 30 m height), with a maximum relative error 〈 10% for predicting the SBCR performances. Subsequently, the proposed model was adopted to optimize the industrial SBCR performances simultaneously considering process and reactor parameters variations. The results show that C5+yield increases as catalyst loading increases within 10-70 ton and syngas H2/CO value decreases within 1.3-1.6, but it doesn't increase obviously when the catalyst loading exceeds 45 ton (about 15 wt% concentration). Higher catalyst loading will result in higher difficulty for wax/catalyst separation and higher catalyst cost. There- fore, the catalyst loading (45 ton) is recommended for the industrial demonstration SBCR operation at syngas H2/ CO = 1.3, and the C5 + yield is about 402 ton" per day, which has an about 16% increase than the industrial dem- onstration run result. 展开更多
关键词 Fischer-Tropsch synthesis Slurry bubble column reactor double bubble model Process simulation and optimization
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