Presentation is loading. Please wait.

Presentation is loading. Please wait.

Tomasz Michałek, Tomasz A. Kowalewski Institute of Fundamental Technological Research Polish Academy of Sciences, Dept. of Mechanics and Physics of Fluids,

Published byElla Karin Lawrence Modified over 8 years ago

Similar presentations

Presentation on theme: "Tomasz Michałek, Tomasz A. Kowalewski Institute of Fundamental Technological Research Polish Academy of Sciences, Dept. of Mechanics and Physics of Fluids,"— Presentation transcript:

1 Tomasz Michałek, Tomasz A. Kowalewski Institute of Fundamental Technological Research Polish Academy of Sciences, Dept. of Mechanics and Physics of Fluids, Poland. NUMERICAL BENCHMARK BASED ON NATURAL CONVECTION OF FREEZING WATER

2 Building confidence to CFD results VerificationValidation Code/Program verification Verification of Calculation Validation of Idealized problems Method of manufactured solution [Roache] Analytical solutions Numerical benchmarks [Ghia, de Vahl Davis, Le Quere,…] Richardson extrapolation (RE) Generalized RE [Stern at all.] Grid Convergence Index (GCI) [Roache] sensitivity analysis Unit problems Benchmark cases Simplified/Partial Flow Path Actual Hardware [Sindir et al.] Validation of actual configuration

3  FRECON (FDM)  FLUENT (FVM)  FIDAP (FEM)  SOLVSTR (FDM)  SOLVMEF (MEF) Ra = 1.5 · 10 6 Pr = 13.31 BENCHMARK DEFINITION FOR THERMAL AND VISCOUS FLOWS 2D viscous, incompressible flow driven by natural convection Navier – Stokes equations with non-linear buoyancy term (water) coupled with heat transfer Temperature gradient ΔT = 10ºC Verified programs: T h = 10  CT c = 0  C

4 VERIFICATION PROCEDURE Compare profiles (not points!) Reference solution Error indicator for code comparisons CALCULATE: SOLUTION S, SOLUTION UNCERTAINTY U SN

5 INTER-CODE COMPARISONS using selected profiles Error U,W along Y=0.5LError U,W along X=0.5LError U,W along X=0.9L Details of the reference solutions w(x) Michalek T., Kowalewski T.A., Sarler B. ”Natural Convection for Anomalous Density Variation of Water: Numerical Benchmark” Progress in Computational Fluid Dynamics, 5 (3-5),pp 158-170,2005 FRECON3V (FRE) FLUENT 6.1. (FLU) FIDAP 8.7.0.(FID) SOLVSTR (STR) Mesh sensitivity

6 SENSITIVITY ANALYSIS Parameters and control points Boundary conditions T H, T C, T ext, Q 1, Q 2, Q 3 Initial conditions T init., v init Material properties , , , ,c p MODEL COMP. RESULTS INITIAL PARAMETERS SENSITIVITY MEASURES OUTPUT 1. Fundamental parameters for validation procedure 2. Precision of measurements necessary to validate calculations

7 EXPERIMENTAL SET-UP light sheet

8 CAVITY DETAILS Control points for monitoring internal and external temperatures CENTRAL CROS-SECTION ALUMINIUM WALL PLEXIGLASS WALL T7T7 T 10 T 14 T 15 ThTh TLTL TPTP TcTc T E1 T E2

9 Particle Image Velocimetry (PIV) Particle Image Thermometry (PIT) 2D Visualization Point temperature measurements EXPERIMENTAL TECHNIQUES correlation F(t 0 ) F(t 0 +  t )

10 ESTIMATION OF EXP. UNCERAINTY U D PIV Avg. FieldsN – length of series Std. Dev. Std. Dev. Error Experimental Data Uncertainty PIT Halcrest Inc. BM100 Temp. range [  C] HueColor UD[C]UD[C] 5.56.40.120.28Red1.0 6.46.50.280.35Yellow0.5 6.57.50.350.55Green1.0 7.59.50.550.70Blue1.5

11 EXPERIMENTAL BENCHMARK DEFINED Different liquid crystal tracers to cover entire color range T h = 10  C T c = 0  C PIV – velocity PIT - temperature Ra = 1.5*10 6 Pr = 11.78

12 EXPERIMENTAL BENCHMARK DEFINED Selected velocity and temperature profiles 2D Temp. Field Temp. along Y = 0.5L Temp. along X = 0.9L W along Y = 0.5LU along X = 0.5LW along X = 0.9L

13 EXPERIMENTAL UNCERTAINTY ESTIMATION N = 40,  t = 1s Mix C Temp. range [  C] HueColor UD[C]UD[C] 0.03.00.110.18Red1.0 3.03.50.180.25Yellow0.5 3.53.90.250.48Green0.5 3.98.00.480.66Blue3.0 BM100 5.56.40.120.28Red1.0 6.46.50.280.35Yellow0.5 6.57.50.350.55Green1.0 7.59.50.550.70Blue1.5 PIV PIT two sets of tracers

14 Validation error Validation metric VALIDATION METHODOLOGY Stern et all., Comprehensive approach to verification and validation of CFD simulations – Part 1: Methodology and procedures Journal of Fluids Engineering – Transactions of ASME, 123 (4), pp. 793-802,2001. In our example: for water

15 TUNNING NUMERICAL SOLUTION Effect of fluid variable properties and thermal boundary conditions Simulation A Variable liquid properties  (T),  (T),c p (T) Simulation B Const. liquid properties , ,c p = const. Simulation C Adiabatic and isothermal walls , ,cp = const Temperature fields Velocity fields

16 THERMAL BOUNDARY CONDITION Validation of the selected numerical model for Tc=-2 o C T h =10  C T c = - 2  C Computational Simulation Experiment

17 THERMAL BOUNDARY CONDITION Validation of the selected numerical model for Tc=-1 o C Computational Simulation Experiment T h =10  C T c = -1  C

18 THERMAL BOUNDARY CONDITION Validation of the selected numerical model for Tc=+1 o C T h =10  C T c =1  C Computational Simulation Experiment

19 THERMAL BOUNDARY CONDITION Validation of the selected numerical model for Tc=+2 o C T h =10  C T c =2  C Computational Simulation Experiment

20 VALIDATION – QUANTITATIVE COMPARISONS WITH THE EXPERIMENTAL BENCHMARK Temperature profiles Velocity profiles Y=0.5LX=0.5LX=0.9L

21 VALIDATION – QUANTITATIVE COMPARISONS ExperimentComp. Sim. AComp. Sim. B YDUDUD SU SN |E||E|UVUV S |E||E|Uv 0.84.501.04.610.020.111.0004.640.020.141.000 14.05.500.55.010.010.490.5004.840.010.660.500 36.26.400.56.120.010.280.5006.020.010.380.500 44.46.450.56.570.010.120.5006.460.01 0.500 49.47.001.06.900.010.101.0006.780.010.221.000 56.37.500.57.400.010.100.5007.270.010.230.500 63.38.001.07.950.020.051.0007.850.020.151.000 69.89.500.58.650.020.850.5008.600.020.900.500 ExperimentComp. Sim. AComp. Sim. B YDUDUD SU SN |E||E|UVUV S |E||E|Uv 4.93.951.03.630.10.321.0053.690.10.261.005 18.33.900.52.640.11.260.5102.690.11.210.510 37.22.001.01.650.20.351.0201.840.20.161.020 39.73.300.51.810.21.490.5391.590.21.710.539 41.63.900.52.970.20.930.5391.520.22.380.539 42.64.000.53.890.20.110.5391.650.22.350.539 45.76.500.56.390.20.110.5393.640.22.860.539 48.37.001.07.080.10.081.0055.650.11.351.005 58.17.500.57.650.10.150.5107.590.10.090.510 64.18.001.08.140.10.141.0058.060.20.061.020 71.79.500.58.900.10.600.5108.860.10.640.510 Validation error was assessed for both simulations Assessed discrepancy are solely due to modeling errors Comp. Sim. A. turned out to be closer to experimental results than comp. Sim. B according to applied validation technique

22 NATURAL CONVECTION AT HIGH RAYLEIGH NUMBER T h = 27.33  C T c = 6.87  C T h = 27.21  C T c = 6.77  C RaPr 13*10 7 9.53 21.5 *10 8 7.01 31.8*10 8 7.01 44.4*10 8 5.41 PIV PIT with two TLCs

23 Ra = 3. 10 7 Ra = 4.4. 10 8 NATURAL CONVECTION AT HIGH RAYLEIGH NUMBER control points and area selected for velocity measurements

24 Ra = 4.4x10 8 Ra = 1.5x10 8 Ra = 1.8x10 8 Ra = 3x10 7 Avg. Horizontal Velocity N = 150  t = 100 ms t = 15 sec HIGH RAYLEIGH NUMBER Mean velocity fields

25 Avg. Vertical Velocity N = 150  t = 100 ms t = 15 sec Ra = 4.4x10 8 Ra = 1.5x10 8 Ra = 1.8x10 8 Ra = 3x10 7 HIGH RAYLEIGH NUMBER Mean velocity fields

26 Skewness N = 150  t = 100 ms t = 15 sec Ra = 4.4x10 8 Ra = 1.5x10 8 Ra = 1.8x10 8 Ra = 3x10 7 HIGH RAYLEIGH NUMBER Velocity field statistics

27 Kurtozis N = 150  t = 100 ms t = 15 sec Ra = 4.4x10 8 Ra = 1.5x10 8 Ra = 1.8x10 8 Ra = 3x10 7 HIGH RAYLEIGH NUMBER Velocity field statistics

28 Turbulence Intensity N = 150  t = 100 ms t = 15 sec Ra = 4.4x10 8 Ra = 1.5x10 8 Ra = 1.8x10 8 Ra = 3x10 7 HIGH RAYLEIGH NUMBER Velocity field statistics

29 Ra = 3x10 7 N=150  t = 100 ms HIGH RAYLEIGH NUMBER Velocity histogram and time series

30 Ra = 1.5x10 8 N=120  t = 100 ms HIGH RAYLEIGH NUMBER Velocity histogram and time series

31 Ra = 1.8x10 8 N=134  t = 100 ms HIGH RAYLEIGH NUMBER Velocity histogram and time series

32 Ra = 4.4x10 8 N=138  t = 100 ms HIGH RAYLEIGH NUMBER Velocity histogram and time series

33 CONCLUSIONS Numerical benchmark based on natural convection of freezing water defined A sensitivity analysis proposed to evaluate effects of initial parameters and to identify fundamental (crucial) parameters => determination of measurement’s precision needed in the validation procedure. Uncertainty of experimental data assessed 2D Temperature field, 2D Velocity field obtained for defined configuration Validation procedure performed in order to assess modeling errors. Experimental benchmark defined High Rayleigh number natural convection resolved experimentally – Numerical solution … pending

34 Thank you for your attention!

Download ppt "Tomasz Michałek, Tomasz A. Kowalewski Institute of Fundamental Technological Research Polish Academy of Sciences, Dept. of Mechanics and Physics of Fluids,"

Similar presentations

Phoenics User Conference on CFD May 2004 Vipac Engineers & Scientists Ltd COMPUTATIONAL FLUID DYNAMICS Simulation of Turbulent Flows and Pollutant Dispersion.

Phoenics User Conference on CFD May 2004 Vipac Engineers & Scientists Ltd COMPUTATIONAL FLUID DYNAMICS Simulation of Turbulent Flows and Pollutant Dispersion.
HEAT TRANSFER Final Review # 1.

HEAT TRANSFER Final Review # 1.
Outline Overview of Pipe Flow CFD Process ANSYS Workbench

Outline Overview of Pipe Flow CFD Process ANSYS Workbench
Direct Forcing Immersed Boundary (DFIB) Method for Mixed Heat Transfer

Direct Forcing Immersed Boundary (DFIB) Method for Mixed Heat Transfer
© 2011 Autodesk Freely licensed for use by educational institutions. Reuse and changes require a note indicating that content has been modified from the.

© 2011 Autodesk Freely licensed for use by educational institutions. Reuse and changes require a note indicating that content has been modified from the.
Estimation of Convective Heat Transfer Coefficient

Estimation of Convective Heat Transfer Coefficient
2003 International Congress of Refrigeration, Washington, D.C., August 17-22, 2003 CFD Modeling of Heat and Moisture Transfer on a 2-D Model of a Beef.

2003 International Congress of Refrigeration, Washington, D.C., August 17-22, 2003 CFD Modeling of Heat and Moisture Transfer on a 2-D Model of a Beef.
Who Wants to Be a CFD Expert? In the ME 566 course title, CFD for Engineering Design, what does the acronym CFD stand for? A.Car Free Day B.Cash Flow Diagram.

Who Wants to Be a CFD Expert? In the ME 566 course title, CFD for Engineering Design, what does the acronym CFD stand for? A.Car Free Day B.Cash Flow Diagram.
MAE513 Spring 2001 Prof. Hui Meng & Dr. David Song Dept. of Mechanical & Aerospace Engineering Advanced Diagnostics for Thermo- Fluids Laser Flow Diagnostics.

MAE513 Spring 2001 Prof. Hui Meng & Dr. David Song Dept. of Mechanical & Aerospace Engineering Advanced Diagnostics for Thermo- Fluids Laser Flow Diagnostics.
Numerical Uncertainty Assessment Reference: P.J. Roache, Verification and Validation in Computational Science and Engineering, Hermosa Press, Albuquerque.

Numerical Uncertainty Assessment Reference: P.J. Roache, Verification and Validation in Computational Science and Engineering, Hermosa Press, Albuquerque.
Analysis of Simple Cases in Heat Transfer P M V Subbarao Professor Mechanical Engineering Department I I T Delhi Gaining Experience !!!

Analysis of Simple Cases in Heat Transfer P M V Subbarao Professor Mechanical Engineering Department I I T Delhi Gaining Experience !!!
Experimental and Numerical Study of the Effect of Geometric Parameters on Liquid Single-Phase Pressure Drop in Micro- Scale Pin-Fin Arrays Valerie Pezzullo,

Experimental and Numerical Study of the Effect of Geometric Parameters on Liquid Single-Phase Pressure Drop in Micro- Scale Pin-Fin Arrays Valerie Pezzullo,
Computer Aided Thermal Fluid Analysis Lecture 7 Dr. Ming-Jyh Chern ME NTUST.

Computer Aided Thermal Fluid Analysis Lecture 7 Dr. Ming-Jyh Chern ME NTUST.
Jordanian-German Winter Academy 2006 NATURAL CONVECTION Prepared by : FAHED ABU-DHAIM Ph.D student UNIVERSITY OF JORDAN MECHANICAL ENGINEERING DEPARTMENT.

Jordanian-German Winter Academy 2006 NATURAL CONVECTION Prepared by : FAHED ABU-DHAIM Ph.D student UNIVERSITY OF JORDAN MECHANICAL ENGINEERING DEPARTMENT.
St.-Petersburg State Polytechnic University Department of Aerodynamics, St.-Petersburg, Russia A. ABRAMOV, N. IVANOV & E. SMIRNOV Numerical analysis of.

St.-Petersburg State Polytechnic University Department of Aerodynamics, St.-Petersburg, Russia A. ABRAMOV, N. IVANOV & E. SMIRNOV Numerical analysis of.
Thermal Development of Internal Flows P M V Subbarao Associate Professor Mechanical Engineering Department IIT Delhi Concept for Precise Design ……

Thermal Development of Internal Flows P M V Subbarao Associate Professor Mechanical Engineering Department IIT Delhi Concept for Precise Design ……
Correlations for INTERNAL CONVECTION P M V Subbarao Associate Professor Mechanical Engineering Department IIT Delhi An Essential Part of Exchanging Heat……..

Correlations for INTERNAL CONVECTION P M V Subbarao Associate Professor Mechanical Engineering Department IIT Delhi An Essential Part of Exchanging Heat……..
Computation of FREE CONVECTION P M V Subbarao Associate Professor Mechanical Engineering Department IIT Delhi Quantification of Free …….

Computation of FREE CONVECTION P M V Subbarao Associate Professor Mechanical Engineering Department IIT Delhi Quantification of Free …….
ASEE Southeast Section Conference INTEGRATING MODEL VALIDATION AND UNCERTAINTY ANALYSIS INTO AN UNDERGRADUATE ENGINEERING LABORATORY W. G. Steele and J.

ASEE Southeast Section Conference INTEGRATING MODEL VALIDATION AND UNCERTAINTY ANALYSIS INTO AN UNDERGRADUATE ENGINEERING LABORATORY W. G. Steele and J.
Measurement of Kinematics Viscosity Purpose Design of the Experiment Measurement Systems Measurement Procedures Uncertainty Analysis – Density – Viscosity.

Measurement of Kinematics Viscosity Purpose Design of the Experiment Measurement Systems Measurement Procedures Uncertainty Analysis – Density – Viscosity.

Similar presentations

Ads by Google