Numerical Study of Mixing Enhancement in 2D Supersonic Ejector

The main objective of the present study is the development of a new algorithm that can adapt to complex and changeable environments. An artificial fish swarm algorithm is developed which relies on a wireless sensor network (WSN) in a hydrodynamic background. The nodes of this algorithm are viscous fluids and artificial fish, while related 'events' are directly connected to the food available in the related virtual environment. The results show that the total processing time of the data by the source node is 6.661 ms, of which the processing time of crosstalk data is 3.789 ms, accounting for 56.89%. The total processing time of the data by the relay node is 15.492 ms, of which the system scheduling and the Carrier Sense Multiple Access (CSMA) rollback time of the forwarding is 8.922 ms, accounting for 57.59%. The total time for the data processing of the receiving node is 11.835 ms, of which the processing time of crosstalk data is 3.791 ms, accounting for 32.02%; the serial data processing time is 4.542 ms, accounting for 38.36%. Crosstalk packets occupy a certain amount of system overhead in the internal communication of nodes, which is one of the causes of node-level congestion. We show that optimizing the crosstalk phenomenon can alleviate the internal congestion of nodes to some extent.

Section: Node Deployment Resultsmentioning

confidence: 99%

Development of an Artificial Fish Swarm Algorithm Based on aWireless Sensor Networks in a Hydrodynamic Background

Bai¹,

Bao²,

Zhao³

et al. 2020

“…As shown in previous investigations, turbulence model plays very important roles in prediction of the flow field variables and the interaction between turbulence and combustion for supersonic combustion simulations. According to its good performance for less computational cost and more numerical robustness [11], Menter's shear stress transport (SST) model [12] has extensive applications in engineering and thus employed in this paper. The SST turbulence model introduces the original k À x model inside boundary layer region and switches into the standard k À E model outside boundary layer region as well as in free shear flows [12].…”

Section: Turbulence Modelmentioning

confidence: 99%

Numerical Investigations on the Impact of Turbulent Prandtl Number and Schmidt Number on Supersonic Combustion

Zheng¹,

Yan²

2020

The flow field inside the combustor of a scramjet is highly complicated and the related turbulent Prandtl and Schmidt numbers have a significant impact on the effective numerical prediction of such dynamics. As in many cases researchers set these parameters on the basis of purely empirical laws, assessing their impact (via parametric numerical simulations) is a subject of great importance. In the present work, in particular, two test cases with different characteristics are selected for further evaluation of the role played by these non-dimensional numbers: Burrows-Kurkov case and DLR case. The numerical results indicate that these parameters influence ignition location. Moreover, the temperature distribution is more sensitive to them than to H 2 O mass fraction and velocity distributions.

“…In view of the significant impact of CA50 on engine performance, each combustion mode is successively run at four different CA50 moments: 3°CA ATDC, 5°CA ATDC, 7°CA ATDC, and 9°CA ATDC, with a total of 12 calculation examples [15]. CA50 represents the crankshaft rotation angle corresponding to 50% of the combustion amount, which can indirectly reflect the phase of the combustion heat release curve, that is, "early" and "late" in the combustion heat release process [16].…”

Section: Thermodynamic Analysismentioning

confidence: 99%

On the Design and Optimization of a Clean and Efficient Combustion Mode for Internal Combustion Engines through a Computer NSGA-II Algorithm

Shu¹,

Ren²

2020

In order to address typical problems due to the huge demand of oil for consumption in traditional internal combustion engines, a new more efficient combustion mode is proposed and studied in the framework of Computational Fluid Dynamics (CFD). Moreover, a Non-dominated Sorting Genetic Algorithm (NSGA-II) is applied to optimize the related parameters, namely, the engine methanol ratio, the fuel injection time, the initial temperature, the Exhaust Gas Re-Circulation (EGR) rate, and the initial pressure. The so-called Conventional Diesel Combustion (CDC), Homogeneous Charge Compression Ignition (HCCI) and the Reactivity Controlled Compression Ignition (RCCI) combustion modes are compared. The results show that RCCI has a higher methanol ratio and an earlier injection timing with moderate EGR rate and higher initial pressure. The initial temperature increases as the methanol ratio increases. In comparison, CDC has the lowest hydrocarbon and CO emissions and the highest combustion efficiency. At different crankshaft rotation angles corresponding to 50% of the combustion amount (CA50), the combustion temperature and boundary layer temperature of HCCI change significantly, while those of RCCI undergo limited variations. At the same CA50, the exergy losses of HCCI and RCCI are lower than that of the CDC. On the basis of these findings, it can be concluded that the methanol/diesel RCCI engine can be used to obtain a clean and efficient combustion process, which should be regarded as a promising combustion mode.