CFD simulation of exhaust gases jet from aircraft engine

Synylo, Kateryna; Krupko, Andrii; Zaporozhets, Oleksandr; Макаренко, Р. Ю.

doi:10.1016/j.energy.2020.118610

Cited by 17 publications

(9 citation statements)

References 10 publications

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“…To intentionally increase the flow rate to the waterjet the following inlet designs for the duct pipe were proposed and tested via SolidWorks simulation tool. SolidWorks Flow simulation tool calculates the flow characteristics in the computational domain based on the solution of the Navier-Stokes equations [9] and compared to other existing simulation tools like OpenFOAM provides similar results [10]. For this study we used steady, incompressible and irrotational flow.…”

Section: Methodsmentioning

confidence: 99%

Modeling of water flow for waterjet propulsion system

Cerpinska

Irbe

Pupurs

et al. 2021

20th International Scientific Conference Engineering for Rural Development Proceedings

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The paper provides simulation results for water flow ratio in the waterjet attached to the SUP (Stand Up Paddle) board fin. The goal of the project is to attach the waterjet propulsion to the SUP board with maximum efficiency. To do it, the model of the person driving the board and waterjet was created in SolidWorks. In this paper the water flow rate depending on different nozzle and duct design was analysed. There are two conflicting requirements for the propulsion duct design. On the one hand, the duct must protect the propulsor from stones and water plants, because SUP boards travel on rivers, sometimes very close to stones. On the other hand, the efficiency of the waterjet requires maximum water flow rate available for a possibly greater Inlet Velocity Ratio. Finally, there should be enough place for the battery pack, which drives the waterjet, but it creates an additional barrier for the water flow. The flow rate at the outlet depends on the nozzle and is also important for the propulsor efficiency. Variable design options for the waterjet duct were proposed and tested in SolidWorks Flow simulation environment. At the beginning of the project there was an intention to create different ducts via 3D printing. The simulation showed that modification of the inlet duct results in minor (only 0.01%) increase of the flow rate, if the front panel remains closed due to the oblique stagnation point flow phenomenon, and 3D printing resources should not be wasted on this test.

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Section: Methodsmentioning

confidence: 99%

Modeling of water flow for waterjet propulsion system

Cerpinska

Irbe

Pupurs

et al. 2021

20th International Scientific Conference Engineering for Rural Development Proceedings

View full text Add to dashboard Cite

show abstract

“…2 Hartree Centre, STFC Daresbury Laboratory, Warrington, UK. 3 China Aerodynamics R&D Center, Mianyang, China.…”

Section: Availability Of Data and Materialsmentioning

confidence: 99%

Effects of Mesh Loop Modes on Performance of Unstructured Finite Volume GPU Simulations

Weng¹,

Zhang²,

Gu³

et al. 2021

Preprint

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In unstructured finite volume method, loop on different mesh components such as cells, faces, nodes, etc is used widely for the traversal of data. Mesh loop results in direct or indirect data access that affects data locality significantly. By loop on mesh, many threads accessing the same data lead to data dependence. Both data locality and data dependence play an important part in the performance of GPU simulations. For optimizing a GPU-accelerated unstructured finite volume Computational Fluid Dynamics (CFD) program, the performance of hot spots under different loops on cells, faces, and nodes is evaluated on Nvidia Tesla V100 and K80. Numerical tests under different mesh scales show that the effects of mesh loop modes are different on data locality and data dependence. Specifically, face loop makes the best data locality, so long as access to face data exists in kernels. Cell loop brings the smallest overheads due to non-coalescing data access, when both cell and node data are used in computing without face data. Cell loop owns the best performance in the condition that only indirect access of cell data exists in kernels. Atomic operations reduced the performance of kernels largely in K80, which is not obvious on V100. With the suitable mesh loop mode in all kernels, the overall performance of GPU simulations can be increased by 15%-20%. Finally, the program on a single GPU V100 can achieve 4.8 speed up comparing with 28 MPI tasks on two Intel CPUs Xeon Gold 6132.

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“…2 Hartree Centre, STFC Daresbury Laboratory, Warrington, UK. 3 China Aerodynamics Research and Development Center, Mianyang, China.…”

Section: Fundingmentioning

confidence: 99%

“…CFD plays an important part in the design of aircraft [1], which is applied in many scenarios including predicting aerodynamics of wing [2], analyzing combustion in engine [3], and so on. More and more computing resources are required, for high precision analysis.…”

Section: Introductionmentioning

confidence: 99%

Effects of mesh loop modes on performance of unstructured finite volume GPU simulations

et al. 2021

View full text Add to dashboard Cite

In unstructured finite volume method, loop on different mesh components such as cells, faces, nodes, etc is used widely for the traversal of data. Mesh loop results in direct or indirect data access that affects data locality significantly. By loop on mesh, many threads accessing the same data lead to data dependence. Both data locality and data dependence play an important part in the performance of GPU simulations. For optimizing a GPU-accelerated unstructured finite volume Computational Fluid Dynamics (CFD) program, the performance of hot spots under different loops on cells, faces, and nodes is evaluated on Nvidia Tesla V100 and K80. Numerical tests under different mesh scales show that the effects of mesh loop modes are different on data locality and data dependence. Specifically, face loop makes the best data locality, so long as access to face data exists in kernels. Cell loop brings the smallest overheads due to non-coalescing data access, when both cell and node data are used in computing without face data. Cell loop owns the best performance in the condition that only indirect access of cell data exists in kernels. Atomic operations reduced the performance of kernels largely in K80, which is not obvious on V100. With the suitable mesh loop mode in all kernels, the overall performance of GPU simulations can be increased by 15%-20%. Finally, the program on a single GPU V100 can achieve maximum 21.7 and average 14.1 speed up compared with 28 MPI tasks on two Intel CPUs Xeon Gold 6132.

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CFD simulation of exhaust gases jet from aircraft engine

Cited by 17 publications

References 10 publications

Modeling of water flow for waterjet propulsion system

Modeling of water flow for waterjet propulsion system

Effects of Mesh Loop Modes on Performance of Unstructured Finite Volume GPU Simulations

Effects of mesh loop modes on performance of unstructured finite volume GPU simulations

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