Optimization of spray break-up CFD simulations by combining Sigma-Y Eulerian atomization model with a response surface methodology under diesel engine-like conditions (ECN Spray A)
[EN] This work evaluates the performance of the Sigma-Y Eulerian atomization model at reproducing the internal structure of a diesel spray with a special focus on Sauter Mean Diameter (SMD) predictions. Modeling results have been compared to x-ray radiography measurements [21,24,38] which provided u...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/103507 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/103507 |
| Access Level: | acceso abierto |
| Palabra clave: | Eulerian Diesel spray Near-field SMD CFD Response Surface Method MAQUINAS Y MOTORES TERMICOS |
| Sumario: | [EN] This work evaluates the performance of the Sigma-Y Eulerian atomization model at reproducing the internal structure of a diesel spray with a special focus on Sauter Mean Diameter (SMD) predictions. Modeling results have been compared to x-ray radiography measurements [21,24,38] which provided unique data within dense spray region. The first step corresponds to accurately reproduce the large scale spray dispersion. Among different RANS turbulence models, the standard k-s with the round jet corrected CIE value (1.60), has shown the best performance, as shown in [12]. Then, the study is devoted to the application and optimization of the predicted interphase surface density (E). In this work, a combination of CFD modeling and the statistical Design of Experiments (DOE) technique known as Response Surface Method (RSM) is applied in order to improve Sauter Mean Diameter (SMD) predictions from E equation compared to experimental measurements. In the investigation, two different optimizations are conducted for the three modeling parameters involved in the equation, following a Central Composite Design (CCD), leading to 15 simulations for each one. After that, both optimum sets of values are validated to assure the accuracy of the method and it is decided the best choice. Finally, different injection and ambient conditions are simulated, with those selected values, providing a remarkable improvement in the modeling performance. |
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