1 GMUWCollaborative Research Lab Advanced Turbulence Modeling for engine applications Chan Hee Son University of Wisconsin, Engine Research Center Advisor:

Slides:

Advertisements

Similar presentations

Simulation of Turbulent Flows in Channel with Obstructions. Golovnya B. P. ISMEL, Cherkassy, Ukraine.

Advertisements

Introduction to Computational Fluid Dynamics

Instructor: André Bakker

Dominic Hudson, Simon Lewis, Stephen Turnock

Faculty of Mechanical Engineering Section Combustion Engines Seeding of air for PIV-measurements Ronald Kuunders Faculty of Mechanical Engineering, Eindhoven.

Turbulent Models.  DNS – Direct Numerical Simulation ◦ Solve the equations exactly ◦ Possible with today’s supercomputers ◦ Upside – very accurate if.

Gaseous And Particulate Dispersion In Street Canyons

Boundary Layer Flow Describes the transport phenomena near the surface for the case of fluid flowing past a solid object.

1 “CFD Analysis of Inlet and Outlet Regions of Coolant Channels in an Advanced Hydrocarbon Engine Nozzle” Dr. Kevin R. Anderson Associate Professor California.

LES Combustion Modeling for Diesel Engine Simulations Bing Hu Professor Christopher J. Rutland Sponsors: DOE, Caterpillar.

Computational Aeroacoustics Prof. S. H. Frankel, ME

Probabilistic Re-Analysis Using Monte Carlo Simulation

September, Numerical simulation of particle-laden channel flow Hans Kuerten Department of Mechanical Engineering Technische Universiteit.

Study of Liquid Breakup Process in Solid Rocket Motors Author: Michael Stefik & Bryan Sinkovec, Co-Author: Yi Hsin Yen, Faculty Advisor: Professor Ryoichi.

Combining the strengths of UMIST and The Victoria University of Manchester Aspects of Transitional flow for External Applications A review presented by.

Mark Claywell & Donald Horkheimer University of Minnesota

Introduction to surface ocean modelling SOPRAN GOTM School Warnemünde: Hans Burchard Baltic Sea Research Institute Warnemünde, Germany.

MECH 221 FLUID MECHANICS (Fall 06/07) Chapter 9: FLOWS IN PIPE

1 B. Frohnapfel, Jordanian German Winter Academy 2006 Turbulence modeling II: Anisotropy Considerations Bettina Frohnapfel LSTM - Chair of Fluid Dynamics.

Modelling of non-equilibrium turbulent flows Tania S. Klein Second Year PhD Student Supervisors: Prof. Iacovides and Dr. Craft School of MACE, The University.

DETAILED TURBULENCE CALCULATIONS FOR OPEN CHANNEL FLOW

Transport Equations for Turbulent Quantities

Recent Advances in Condensation on Tube Banks P M V Subbarao Professor Mechanical Engineering Department I I T Delhi Reduce the Degree of Over Design!!!

Large Eddy Simulation of Rotating Turbulence Hao Lu, Christopher J. Rutland and Leslie M. Smith Sponsored by NSF.

AIAA SciTech 2015 Objective The objective of the present study is to model the turbulent air flow around a horizontal axis wind turbine using a modified.

Lesson 12 Laminar Flow - Slot Flow

CHEMICAL REACTION ENGINEERING LABORATORY Characterization of Flow Patterns in Stirred Tank Reactors (STR) Aravind R. Rammohan Chemical Reaction Engineering.

CFD Modeling of Turbulent Flows

Modeling Turbulent Flows

The Dorr-Oliver Flotation cell

1 LES of Turbulent Flows: Lecture 11 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Fall 2014.

Nature of Heat Release Rate in an Engine

Fifth International Symposium on Turbulence and Shear Flow Phenomena A. Revell, The University of Manchester K. Duraisamy, The University of Glasgow G.

Chapter 9 Turbulence Introduction to CFX.

Design of Engine Cylinder for Creation of A Selected Turbulent Flow P M V Subbarao Professor Mechanical Engineering Department Geometry to create qualitatively.

1 Turbulence Characteristics in a Rushton & Dorr-Oliver Stirring Vessel: A numerical investigation Vasileios N Vlachakis 06/16/2006.

CONCLUSIONS 1. In curved ducts, the combination of advanced EARSM/EASFM allows to predict satisfactorily flow processes with heat transfer phenomena, in.

Dynamic subgrid-scale modeling in large- eddy simulation of turbulent flows with a stabilized finite element method Andrés E. Tejada-Martínez Thesis advisor:

PIPELINE DESIGN ‘ THE ENGINEERING APPROACH’ SESSION OBJECTIVES THE ENGINEERING EQUATIONS TRANSMISSION LINE GAS FLOW LIQUID SYSTEM.

Jet With No Cross Flow RANS Simulations of Unstart Due to Mass Injection J. Fike, K. Duraisamy, J. Alonso Acknowledgments This work was supported by the.

CITES 2005, Novosibirsk Modeling and Simulation of Global Structure of Urban Boundary Layer Kurbatskiy A. F. Institute of Theoretical and Applied Mechanics.

5/10/00 Integration of Advanced Automotive Simulation Methods Using ANN 1 Integration of Advanced Automotive Simulation Methods Using Artificial Neural.

Turbulence Models Validation in a Ventilated Room by a Wall Jet Guangyu Cao Laboratory of Heating, Ventilating and Air-Conditioning,

Lecture Objectives: Define 1) Reynolds stresses and

School of Aerospace Engineering MITE Numerical Simulation of Centrifugal Compressor Stall and Surge Saeid NiaziAlex SteinLakshmi N. Sankar School of Aerospace.

MODELING FLOW IN LOCK MANIFOLDS

Convergence Studies of Turbulent Channel Flows Using a Stabilized Finite Element Method Andrés E. Tejada-Martínez Department of Civil & Environmental Engineering.

Direct numerical simulation has to solve all the turbulence scales from the large eddies down to the smallest Kolmogorov scales. They are based on a three-dimensional.

Application of Compact- Reconstruction WENO Schemes to the Navier-Stokes Equations Alfred Gessow Rotorcraft Center Aerospace Engineering Department University.

Modeling of Pollutant Formation in a Spark Ignition Engine Using Forte Final Project ME 769: Combustion Processes Stephen Sakai, Alison Ferris, Mitchell.

Date of download: 6/21/2016 Copyright © ASME. All rights reserved. From: RANS and Large Eddy Simulation of Internal Combustion Engine Flows—A Comparative.

University of Wisconsin -- Engine Research Center slide 1 Investigation of Heat Transfer Correlations for HCCI Engines Eric Gingrich, Christopher Gross,

Computational Fluid Dynamics P AVEL P ETRUNEAC B ACHELOR OF S CIENCE D ISSERTATION R ENEWABLE E NERGY OF TURBULENCE EFFECTS ON THE SEABED Supervisor(s):

University of Wisconsin -- Engine Research Center slide 1 Counter-flow diffusion flame ME Project Chi-wei Tsang Longxiang Liu Krishna P.

The Standard, RNG, and Realizable k- Models. The major differences in the models are as follows: the method of calculating turbulent viscosity the turbulent.

1 Case 2: URANS Application with CFL3D Christopher L. Rumsey NASA Langley Research Center Hampton, VA CFDVAL2004 Workshop, March 29-31, 2004.

Simulation of a self-propelled wake with small excess momentum in a stratified fluid Matthew de Stadler and Sutanu Sarkar University of California San.

Date of download: 9/18/2016 Copyright © ASME. All rights reserved. From: Grid-Convergent Spray Models for Internal Combustion Engine Computational Fluid.

The Prediction of Low Frequency Rumble in Combustion Systems

A V&V Overview of the 31st Symposium on Naval Hydrodynamics

K-ε model, ASM model.

C. F. Panagiotou and Y. Hasegawa

The k-ε model The k-ε model focuses on the mechanisms that affect the turbulent kinetic energy (per unit mass) k. The instantaneous kinetic energy k(t)

Street Canyon Modeling

*supported by the Army Research Office

New insights into turbulence dynamics under stabilizing

Lecture Objectives: Boundary Conditions Project 1 (software)

Generation and Control of Turbulent Flames in SI Engine

Design rules to generate Turbulent Flame Speeds in SI Engines

Computational Fluid Dynamics Simulation of a Baffle Valve in OpenFoam

Presentation transcript:

1 GMUWCollaborative Research Lab Advanced Turbulence Modeling for engine applications Chan Hee Son University of Wisconsin, Engine Research Center Advisor: Professor Christopher J. Rutland Sponsor: General Motors

2 GMUWCollaborative Research Lab Motivation  Linear k-  model  widely used, but compromise between expense and accuracy  Inherently unable to account for secondary flows  Poor predictions for separated or curved streamline flows  Non-linear models  Able to predict secondary flow of the second kind  Numerical instability leads to excessive computational expense  Wallin-Johansson's explicit Algebraic Reynolds Stress Model as a representative case  v 2 -f model  Two turbulence scales are used  More accurate representation of the physics (eddy viscosity) close to the wall  Very good performance in flow separation regions

3 GMUWCollaborative Research Lab Model formulation  Turbulence governing equations of v 2 - f

4 GMUWCollaborative Research Lab Sandia National Lab Optical engine  Specifications  Bore – 79.5mm, Stroke – 85.0 mm  C R = 18.7  1500 RPM  R S = 1.5 ~ 3.5  Cold flow (no spray or combustion)  Measurement locations  3 clusters of 5 points located in a vertical plane bisecting the exhaust valves  The 3 center points are at r= 13.6 mm with all neighboring measurement points being 1mm away.

5 GMUWCollaborative Research Lab Radial and tangential 5 ATDC with swirl ratio 3.5 v 2 -fW-J

6 GMUWCollaborative Research Lab TKE history for case with swirl ratio = 3.5

7 GMUWCollaborative Research Lab Conclusion For the Sandia National lab optical engine simulation, W-J eARSM does not show any improvement for the mean flow. Even the k-  model is better. For the Sandia National lab optical engine simulation, W-J eARSM does not show any improvement for the mean flow. Even the k-  model is better. Potential reason: the W-J ARSM is originally derived for 2D flow. 3D version is quartic order. Thus, too complex for practical use. l Increased levels of turbulence is predicted by the WJ model. At swirl ratio 2.5 and 3.5, TKE prediction over time is very similar to k-  model in trend, but about 50% higher in turbulence level. This is not due to the ability of this model to capture turbulence anisotropy, as the trend is almost exactly the same as k-  t high swirl anisotropy increases. l The v 2 -f model consistently shows improved results. Still it fails to catch the trends of the experimental turbulent kinetic energy results.