Ensemble average method for runtime saving in Large Eddy Simulation of free and Ducted Fuel Injection (DFI) sprays. (15th July 2023)
- Record Type:
- Journal Article
- Title:
- Ensemble average method for runtime saving in Large Eddy Simulation of free and Ducted Fuel Injection (DFI) sprays. (15th July 2023)
- Main Title:
- Ensemble average method for runtime saving in Large Eddy Simulation of free and Ducted Fuel Injection (DFI) sprays
- Authors:
- Segatori, C.
Piano, A.
Peiretti Paradisi, B.
Millo, F.
Bianco, A. - Abstract:
- Highlights: A runtime saving method is presented for ensemble averaging spray LES. The method exploits axial symmetry of the computational domain. Velocity, mixture fraction, and turbulent kinetic energy fields are analysed. The computational cost is curtailed by 50–75% maintaining similar accuracy. This method works properly for both conventional and DFI spray configurations. Abstract: Computational Fluid Dynamics (CFD) with Large Eddy Simulation (LES) turbulence model is a valuable tool to investigate complex problems. However, for high Reynolds number problems, the associated huge computational cost often leads researchers to the use of more simplified and less accurate approaches, especially if statistics is needed for the generalization of the results and comparison against experimental data. Therefore, the introduction of innovative methodologies to reduce the computational cost maintaining results reliability would be of paramount importance for LES-based investigation. In this context, the aim of this work is to assess a runtime saving methodology to ensemble average several axial symmetric spray simulations obtained with LES. In particular, the number of independent samples for the average procedure has been increased by exploiting the axial symmetry characteristics of a diesel spray case study, extracting more realizations from a single simulation. This ensemble average approach was compared with the standard one, based on one realization per simulation, at equalHighlights: A runtime saving method is presented for ensemble averaging spray LES. The method exploits axial symmetry of the computational domain. Velocity, mixture fraction, and turbulent kinetic energy fields are analysed. The computational cost is curtailed by 50–75% maintaining similar accuracy. This method works properly for both conventional and DFI spray configurations. Abstract: Computational Fluid Dynamics (CFD) with Large Eddy Simulation (LES) turbulence model is a valuable tool to investigate complex problems. However, for high Reynolds number problems, the associated huge computational cost often leads researchers to the use of more simplified and less accurate approaches, especially if statistics is needed for the generalization of the results and comparison against experimental data. Therefore, the introduction of innovative methodologies to reduce the computational cost maintaining results reliability would be of paramount importance for LES-based investigation. In this context, the aim of this work is to assess a runtime saving methodology to ensemble average several axial symmetric spray simulations obtained with LES. In particular, the number of independent samples for the average procedure has been increased by exploiting the axial symmetry characteristics of a diesel spray case study, extracting more realizations from a single simulation. This ensemble average approach was compared with the standard one, based on one realization per simulation, at equal statistical sample size. Main spray physical quantities and turbulence characteristics were examined, both globally and locally. The same procedure was also applied to a different diesel-relevant spray configuration, known as ducted fuel injection. The reliability of this ensemble average methodology has been herein proven for both spray configurations, highlighting a dramatic runtime saving without any worsening of the accuracy level. In particular, this approach, as applied in this work, guaranteed a computational cost reduction of 50–75%. Thereby, the present methodological assessment could motivate researchers involved in the investigation of spray processes to undertake the path of statistically significant LES analysis. … (more)
- Is Part Of:
- Fuel. Volume 344(2023)
- Journal:
- Fuel
- Issue:
- Volume 344(2023)
- Issue Display:
- Volume 344, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 344
- Issue:
- 2023
- Issue Sort Value:
- 2023-0344-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-07-15
- Subjects:
- Computational Fluid Dynamics -- Large Eddy Simulation (LES) -- Turbulence modelling -- Spray -- Ducted Fuel Injection
AMR Adaptive Mesh Refinement -- aSOI after Start of Injection -- CFD Computational Fluid Dynamics -- CFL Courant-Friedrichs-Lewy -- CVV Constant-Volume Vessel -- DFI Ducted Fuel Injection -- DNS Direct Numerical Simulation -- LES Large Eddy Simulation -- LES-NWM Large Eddy Simulation with Near Wall Modelling -- LOL Lift-Off Length -- LSR Length Scale Resolution -- MSI Magnitude Similarity Index -- RANS Reynolds-Averaged Navier-Stokes -- RMS Root Mean Square -- SGS Sub-Grid Scale -- SMD Sauter Mean Diameter -- SSI Structure Similarity Index -- TKE Turbulent Kinetic Energy -- TRI Turbulence Resolution Index -- |V| Velocity magnitude -- η Kolmogorov length scale -- ϕ Equivalence ratio -- < > Ensemble average
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662.6 - Journal URLs:
- http://www.sciencedirect.com/science/journal/latest/00162361 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.fuel.2023.128110 ↗
- Languages:
- English
- ISSNs:
- 0016-2361
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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