Abstract
| Original language | English |
|---|---|
| Title of host publication | IMechE, Fuel Systems-Engines |
| Publisher | IMechE |
| Publication status | Published - 1 Dec 2018 |
| Event | Fuel Systems: Engines - Etc Venues, St Paul's, London, United Kingdom Duration: 4 Dec 2018 → 5 Dec 2018 https://events.imeche.org/ViewEvent?code=CON6597 |
Conference
| Conference | Fuel Systems |
|---|---|
| Country | United Kingdom |
| City | London |
| Period | 4/12/18 → 5/12/18 |
| Internet address |
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Predictive Engine Simulations based on a novel DoE/RANS approach with coefficient tabulation. / Nsikane, Daniel; Vogiatzaki, Konstantina; Morgan, Robert.
IMechE, Fuel Systems-Engines. IMechE, 2018. 0119.Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN
TY - GEN
T1 - Predictive Engine Simulations based on a novel DoE/RANS approach with coefficient tabulation
AU - Nsikane, Daniel
AU - Vogiatzaki, Konstantina
AU - Morgan, Robert
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Producing reliable in-cylinder simulations for quick turnaround engine development for industrial purposes is a challenging task. With the ongoing paradigm shift towards digital engineering, industry is forced to adjust its development and manufacturing processes away from prototyping and reliance on test bed results towards a virtual environment where optimization occurs before the actual hardware is available. In this work, an approach is presented, which can overcome one of the main disadvantages of RANS: the model coefficient tuning dependency. Using a Design of Experiments approach, it is shown that input parameters can be linked to ambient boundary conditions and therefore tabulated to eliminate lengthy tuning iterations between operating conditions.
AB - Producing reliable in-cylinder simulations for quick turnaround engine development for industrial purposes is a challenging task. With the ongoing paradigm shift towards digital engineering, industry is forced to adjust its development and manufacturing processes away from prototyping and reliance on test bed results towards a virtual environment where optimization occurs before the actual hardware is available. In this work, an approach is presented, which can overcome one of the main disadvantages of RANS: the model coefficient tuning dependency. Using a Design of Experiments approach, it is shown that input parameters can be linked to ambient boundary conditions and therefore tabulated to eliminate lengthy tuning iterations between operating conditions.
M3 - Conference contribution with ISSN or ISBN
BT - IMechE, Fuel Systems-Engines
PB - IMechE
ER -