Evaluation of Diesel Spray-Wall Interaction and Morphology around Impingement Location

Zhao, Longmao; Torelli, Roberto; Zhu, Xiucheng; Naber, Jeffrey; Lee, Seong-Young; Som, Sibendu; Scarcelli, Riccardo; Raessi, Mehdi

doi:10.4271/2018-01-0276

Cited by 20 publications

(13 citation statements)

References 30 publications

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“…Figure 9, left) for the radial radii, R f , and (3) the impinged wall for the axial and radial heights, H s and H f . The experimental data shown in Figure 14 were published in previous work by Zhao et al 17 For the radial quantities (i.e. right column of Figure 14), the CFD results were reported as the average of the results collected from the two sides.…”

Section: Resultsmentioning

confidence: 99%

“…The front camera was a Photron Fastcam-APX RS high-speed camera and used a 52 mm lens with an f-stop of 1.8. The fps was the same as the side camera while the exposure time was set to 27.77 ms. 17 The analysis of the free-spray and impinged spray quantities was carried out by converting the sequence of captured frames into binary images using Otsu's 44 methodology. MATLAB's built-in morphological tools 41 were leveraged to extract the abovementioned global parameters.…”

Section: Experimental Setup and Methodsmentioning

confidence: 99%

“…The physical properties of diesel #2 fuel were selected from the CONVERGE database. 28 The injection profile and injected mass (28.39 mg) are the same as the ones used in previous work by Zhao et al 17 Numerical modeling of SWI This section will briefly introduce two SWI models proposed by O'Rourke and Amsden 8,22 and Stanton and Rutland. 10,25,26 The main focus will be on the differences between the two models and on the aspects that motivated the implementation of a new methodology for the calculation of the impingement frequency.…”

Section: Computational Fluid Dynamics Setupmentioning

confidence: 99%

“…The CFD code has been extensively validated in the past under non-reacting and reacting conditions. 16,17,28,29 An unsteady Reynolds-averaged Navier–Stokes (URANS) framework was employed to model the effects associated with turbulence by means of the re-normalization group (RNG) k–ε model. 30 The choice of a URANS methodology for the current work is based on the necessity to develop models that can support large numbers of simulations within a reasonable computational time frame, while reducing the need for model parameter tuning to a minimum.…”

Section: Computational Fluid Dynamics Setupmentioning

confidence: 99%

“…[2][3][4][5] Because more and more research is constantly directed to the understanding and control of pollutant formation, 6 the majority of the spray and ICE communities has dedicated considerable effort toward improving the knowledge of SWI both experimentally and numerically. 4,5,[7][8][9][10][11][12][13][14][15][16][17][18][19][20] The literature presents numerous studies that have addressed SWI from fundamental or applied standpoints. Within the former category, there has been a multitude of studies that focused on single droplet impingement or a train of droplets impacting on rigid surfaces.…”

Section: Introductionmentioning

confidence: 99%

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Toward predictive and computationally affordable Lagrangian–Eulerian modeling of spray–wall interaction

Torelli

Scarcelli

Som

et al. 2019

International Journal of Engine Research

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The work presented in this article focuses on improving the understanding of spray–wall interaction phenomena and the predictivity of computational models for modern internal combustion engine–like conditions. Previous work from the authors highlighted some of the limitations of the currently available spray–wall interaction sub-models, especially those based on experimental observations carried out on single droplet impingement of non-hydrocarbon fluids. Previous experimental observations and direct numerical simulations provided unique qualitative and quantitative details that were leveraged to improve Lagrangian–Eulerian simulations of spray–wall interaction. In this work, Yarin and Weiss’ theory for droplet train impingements, as interpreted by Stanton and Rutland, was implemented in the CONVERGE software. A novel and mathematically rigorous calculation of the impingement frequency for Lagrangian parcels was proposed to replace the zero-droplet-spacing assumption present in the original model and improve the prediction of droplet splash. Preliminary testing and validation of the new formulation against experiments carried out in a constant volume vessel showed encouraging results. The feedback loop between experiments, Lagrangian–Eulerian simulations, and direct numerical simulations also motivated the investigation of the surface roughness model available in the Lagrangian–Eulerian framework. This part of the study pointed out the importance of correctly predicting the interaction between liquid and surrounding gas in the near-wall region. Overall, the results shown indicate that correctly capturing the pre-impingement physics and liquid–gas interaction, together with improving splash predictions, was key for improving the accuracy of Lagrangian–Eulerian computational fluid dynamics simulations of spray–wall impingement.

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Section: Resultsmentioning

confidence: 99%

Section: Experimental Setup and Methodsmentioning

confidence: 99%