Direct and large-eddy simulation of inert and reacting compressible turbulent shear layers

Size: px
Start display at page:

Download "Direct and large-eddy simulation of inert and reacting compressible turbulent shear layers"

Transcription

1 Technische Universität München Fachgebiet Strömungsmechanik Direct and large-eddy simulation of inert and reacting compressible turbulent shear layers Inga Mahle Vollständiger Abdruck der von der Fakultät für Maschinenwesen der Technischen Universität München zur Erlangung des akademischen Grades eines Doktor-Ingenieurs genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr.-Ing. habil. N. A. Adams Prüfer der Dissertation:. Univ.-Prof. Dr.-Ing., Dr.-Ing. habil. R. Friedrich i.r. 2. Univ.-Prof. W. H. Polifke Ph.D. (CCNY) Die Dissertation wurde am bei der Technischen Universität München eingereicht und durch die Fakultät für Maschinenwesen am.7.27 angenommen.

2

3 Abstract In the first part of the thesis, Direct Numerical Simulations (DNS) of temporally evolving, turbulent, compressible shear layers are discussed. Simulations at three different convective Mach numbers (.5,.7 and.) were performed for both, inert and infinitely fast reacting gases. All simulations were continued beyond the onset of a self-similar state in order to guarantee statistics of general value. Self-similarity manifested itself by a collapse of suitably normalized profiles of flow variables and a constant momentum thickness growth rate. During this state, the Reynolds number based on the vorticity thickness of the shear layers was between and 4 and therefore in a fully turbulent regime. The relevance of the achieved results and parameter ranges for practical applications can be seen from the fact that shear (or mixing) layers develop when injecting fuel into the combustion chamber of an engine. Here, a good mixing of fuel and oxidizer is of great interest for an efficient combustion process. The focus of the DNS data analyses was on the effects of compressibility and heat release due to combustion on turbulence and scalar mixing. Both phenomena, compressibility and heat release, were studied separately as well as in combination. Increasing compressibility, i.e. increasing convective Mach number, resulted in a stabilization of the mixing layers: Instantaneous fields of flow quantities became smoother, there were less turbulent fluctuations and the growth rate of the mixing layers reduced. The latter effect was related to a reduction in the production rate of the streamwise Reynolds stress and a reduction in the pressure-strain correlations caused by changes in the fluctuating pressure field. When heat release was present, the effects of compressibility were similar as for the inert mixing layers, but they were less distinct, e.g. the reduction of the growth rate with increasing Mach number was comparatively smaller. At first sight, heat release alone had similar consequences as compressibility: A stabilization of the shear layers, flow fields with lower levels of fluctuations and smaller spreading rates. However, when studied in more detail, it could be seen that the consequences of heat release, were mainly mean density effects, i.e. a result of the reduction of the mean density by the high temperatures in the vicinity of the flame sheets. This was not the case for the compressibility effects. Therefore, it is important to distinguish between compressibility and heat release effects, even though they share the property to be both detrimental for the turbulent mixing process. In the second part of the thesis, Large Eddy Simulations (LES) of shear layers at a convective Mach number of.5 were performed. By a coarsening of the grid, large reductions of computational time were achieved. A deconvolution approach in the form of a single explicit filtering step was validated successfully for inert and reacting mixing layers by comparison with DNS data. For the LES with chemical reactions, two differently detailed chemistry models were used for the filtered chemical source term: one model taking into account the same infinitely fast, irreversible, global reaction as in the DNS and one flamelet model. The particular formulation of the flamelet equations allowed not only to take into account multistep Arrhenius chemistry, but also detailed diffusion mechanisms. The evaluation of the results obtained with two different descriptions of these mechanisms - one with Soret and Dufour effects as well as multicomponent diffusion and

4 one without - showed differences for both, laminar flamelets and turbulent mixing layers, in quantities related to the flame dynamics and in the extinction behaviour.

5 Acknowledgements First of all, I would like to thank my supervisor Prof. Dr.-Ing. habil. Rainer Friedrich for the opportunity to perform this work at the Fachgebiet Strömungsmechanik. He gave me constant guidance and support and was always ready to answer questions or to discuss various aspects. I am also thankful to Prof. Dr. Joseph Mathew for giving me the opportunity to spend four months in his lab at the Indian Institute of Science in Bangalore. I appreciate his gracious hospitality and the fruitful discussions that we had. The final outcome of our joint work has been very rewarding. I would also like to thank Prof. W. Polifke Ph.D. (CCNY) for taking over the role of the second examiner and Prof. Dr.-Ing. habil. N. Adams for leading the board of examiners. My thanks go also to the High Performance Computing Group of the Leibniz Rechenzentrum (LRZ) for providing help and support at nearly all times of the day, all days of the week. The computations of this work were performed on the Hitachi-SR8 and the Altix 47 of the LRZ. Financial contributions came from the Federal Ministry of Education and Research (BMBF) under grant number 3FRAAC and from Bayerischer Forschungsverbund für Turbulente Verbrennung (FORTVER). Without my colleagues and the mutual support and encouragement within our group, this work would not have been imaginable. In this context, I would like to mention especially Dr.-Ing. Holger Foysi who gave me a lot of help and advice concerning the numerical codes and evaluation programs. I would also like to thank Prof. Alexandre Ern from CERMICS, ENPC (France) for providing the code EGlib. Last but not least, I am deeply grateful to my family, in particular to my parents and grandparents, for supporting me throughout the process of this work and throughout all my life. Garching, March 27 Inga Mahle

6

7 Contents Introduction 2 DNS of inert compressible turbulent shear layers 4 2. Introduction and literature survey The DNS code for inert gas mixtures Navier-Stokes equations for a gas mixture The numerical method Test cases Results and analysis The structure of the compressible shear layers Inert shear layer at M c = Inert shear layer at M c = Inert shear layer at M c = The self-similar state Check of resolution, domain sizes and filtering The effect of compressibility Turbulence characteristics Mean flow variables Reynolds stresses, turbulent kinetic energy and anisotropies Reynolds stress transport equations Analysis of the reduced growth rate Pressure-strain terms TKE transport equation Thermodynamic fluctuations Correlations of thermodynamic fluctuations Behaviour of the pressure-strain correlations Turbulent and gradient Mach numbers Spectra

8 II CONTENTS Scalar mixing Mean profile and variance Scalar pdfs Mixing efficiency Scalar variance transport equation Scalar fluxes Transport equations of scalar fluxes Behaviour of the pressure-scrambling terms Spectra Entrainment Measurement of volumes Visual thickness Measurement of densities Particle statistics Fractal nature of the mixing layer interface Shocklets Summary and conclusions DNS of infinitely fast reacting compressible turbulent shear layers Introduction and literature survey The DNS code with an infinitely fast chemical reaction Infinitely fast chemistry Transport equations for infinitely fast reacting flows The numerical method Test cases Results and analysis The structure of the infinitely fast reacting shear layers Infinitely fast reacting shear layer at M c = Infinitely fast reacting shear layers at M c =.7 and M c = The self-similar state Check of resolution and domain sizes Effects of compressibility and heat release Mean heat release term

9 CONTENTS III Turbulence characteristics Mean flow variables Reynolds stresses, turbulent kinetic energy and anisotropies Reynolds stress transport equations Analysis of the reduced growth rate Pressure-strain terms TKE transport equation Thermodynamic fluctuations Correlations of thermodynamic fluctuations Behaviour of the pressure-strain correlations Turbulent and gradient Mach numbers Spectra Scalar mixing Mean profile and variance Scalar pdfs Mixing efficiency Scalar variance transport equation Scalar fluxes Transport equations of scalar fluxes Spectra Entrainment Measurement of volumes Visual thickness Measurement of densities Particle statistics Fractal nature of the mixing layer interface Shocklets Summary and conclusions

10 IV CONTENTS 4 LES of inert and infinitely fast reacting mixing layers Introduction and literature survey Description of the LES method Implicit Modeling Approach Applied filters Filtered equations Modeling of the filtered heat release term The filtered density function The conditionally filtered scalar dissipation rate The filtered scalar dissipation rate Test cases Results and analysis Inert mixing layers Instantaneous fields Profiles of averaged flow variables Spectra Effect of filtering on dissipation rates Refinement of the grid Infinitely fast reacting mixing layers Instantaneous fields Profiles of averaged flow variables The filtered heat release term Spectra Effect of filtering on dissipation rates Refinement of the grid Summary and conclusions

11 CONTENTS V 5 LES of shear layers with chemical kinetic and detailed diffusion effects Introduction and literature survey LES approach LES equations and models Filtered heat release term and filtered species mass fractions The flamelet database Detailed reaction scheme and Arrhenius chemistry Computation of detailed diffusion fluxes and of heat flux by EGlib The mixture fraction and its diffusivity Steady flamelet solutions Test cases Results and analysis Flamelets with detailed and simplified diffusion Evaluation of the LES results Summary and conclusions Conclusions and outlook 86 A Appendix: The characteristic form of the Navier-Stokes equations 9 A. The one-dimensional equations A.2 The three-dimensional equations in Cartesian coordinates A.3 The source terms in the transport equations A.4 Specification of the transport equations for an ideal gas mixture A.5 Non-reflecting boundary conditions

12 List of Tables 2. Geometrical parameters of the simulations inert-.5, inert-.7, inert-.. The computational domain has the dimensions L, L 2 and L 3 with N, N 2 and N 3 grid points, respectively. The reference vorticity thickness δ ω, is chosen such that it results in Re ω, = Dimensionless times and Reynolds numbers at the beginning (index: B) and end (index: E) of the self-similar state Integral length scales Values used in the analysis linking momentum thickness growth rate with pressurestrain rate Π for the inert test cases Actual and approximated momentum thickness growth rates and relative errors for the inert test cases Particle parameters: N P particles are initialized at τ ω,p B. They are situated initially between x 3 = x 3,P and x 3,P 2 and between x 3 = x 3,P 3 and x 3,P Statistics of displacements and elapsed times for growth of vorticity and mixture fraction along particle pathlines Fractal dimensions D of isosurfaces determined from the slopes of the curves in Figs to 2.76 and corresponding ones for ω =.2 ω max and Y = Geometrical parameters of the simulations inf-.5, inf-.7, inf-.. The computational domain has the dimensions L, L 2 and L 3 with N, N 2 and N 3 grid points, respectively. The reference vorticity thickness δ ω, is chosen such that it results in Re ω, = Dimensionless times and Reynolds numbers at the beginning (index: B) and end (index: E) of the self-similar state Integral length scales Values used in the analysis linking momentum thickness growth rate with pressurestrain rate Π for the infinitely fast reacting test cases Actual and approximated momentum thickness growth rates and relative errors for the infinitely fast reacting test cases Averaged values (respective inert and reacting cases taken into account) used in the analysis for each convective Mach number Actual and approximated momentum thickness growth rates and relative errors.

13 LIST OF TABLES VII 3.8 Particle parameters: N P particles are initialized at τ ω,p B. They are situated initially between x 3 = x 3,P and x 3,P 2 and between x 3 = x 3,P 3 and x 3,P Statistics of displacements and elapsed times for growth of vorticity and mixture fraction along particle pathlines Fractal dimensions D of isosurfaces LES simulations Reaction scheme for H 2 /O 2 combustion with pre-exponential factors A, temperaturedependence coefficients β and activation energies E [3]

14 List of Figures 2. The configuration of temporally evolving shear layers Case inert-.5: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 83, isolines Y O2 =. and.9 are shown Case inert-.5: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 286, isolines Y O2 =. and.9 are shown Case inert-.5: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 49, isolines Y O2 =. and.9 are shown Case inert-.5: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 533, isolines Y O2 =. and.9 are shown Case inert-.5: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.5: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.5: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.5: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.5: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 83, isolines Y O2 =. and.9 are shown Case inert-.5: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 286, isolines Y O2 =. and.9 are shown Case inert-.5: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 49, isolines Y O2 =. and.9 are shown Case inert-.5: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 533, isolines Y O2 =. and.9 are shown Case inert-.7: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 46, isolines Y O2 =. and.9 are shown. 3

15 LIST OF FIGURES IX 2.5 Case inert-.7: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 48, isolines Y O2 =. and.9 are shown Case inert-.7: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 697, isolines Y O2 =. and.9 are shown Case inert-.7: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 98, isolines Y O2 =. and.9 are shown Case inert-.7: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.7: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.7: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.7: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.7: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 46, isolines Y O2 =. and.9 are shown Case inert-.7: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 48, isolines Y O2 =. and.9 are shown Case inert-.7: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 697, isolines Y O2 =. and.9 are shown Case inert-.7: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 98, isolines Y O2 =. and.9 are shown Case inert-.: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 62, isolines Y O2 =. and.9 are shown Case inert-.: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 38, isolines Y O2 =. and.9 are shown Case inert-.: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 735, isolines Y O2 =. and.9 are shown Case inert-.: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 98, isolines Y O2 =. and.9 are shown Case inert-.: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω =

16 X LIST OF FIGURES 2.33 Case inert-.: Instantaneous mass fraction field of O 2, x -x 2 -plane in the middle of the computational domain at τ ω = Case inert-.: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 62, isolines Y O2 =. and.9 are shown Case inert-.: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 38, isolines Y O2 =. and.9 are shown Case inert-.: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 735, isolines Y O2 =. and.9 are shown Case inert-.: Instantaneous mass fraction field of O 2, x 2 -x 3 -plane through a braid (left) and a roller (right) at τ ω = 98, isolines Y O2 =. and.9 are shown Temporal development of the momentum thickness, normalized by initial momentum thickness δ θ,, : inert-.5, : inert-.7, : inert-., dashed lines show linear regressions for the self-similar state Dependence of shear layer growth rate on M c : solid line: Langley curve, +: Debisschop & Bonnet [36], : Samimy & Elliot [55], : Chambres, Barre & Bonnet [25], : Papamoschou & Roshko [26], : Clemens & Mungal [27], : Hall, Dimotakis & Rosemann [7], : Pantano & Sarkar [23], : Present DNS Case inert-.5: Spatially averaged profiles of the Reynolds shear stress R 3 at different times, +: τ ω = 83, : τ ω = 23, : τ ω = 64, : τ ω = 24, : τ ω = 245, : τ ω = 286, : τ ω = 327, : τ ω = Case inert-.7: Spatially averaged profiles of the Reynolds shear stress R 3 at different times, +: τ ω = 39, : τ ω = 474, : τ ω = 557, : τ ω = 64, : τ ω = 725, : τ ω = 89, : τ ω = 866, : τ ω = Case inert-.: Spatially averaged profiles of the Reynolds shear stress R 3 at different times, +: τ ω = 735, : τ ω = 87, : τ ω = 878, : τ ω = 949, : τ ω = 23, : τ ω = 98, : τ ω = 74, : τ ω = Streamwise velocity, solid line: inert-.5, dashed line: DNS Pantano & Sarkar M c =.3 [23], [52], +: Experiments Bell & Mehta [7], : Experiments Spencer & Jones [72] Streamwise rms velocity, solid line: inert-.5, dashed line: DNS Pantano & Sarkar M c =.3 [23], dotted line: DNS Rogers & Moser, [52], +: Experiments Bell & Mehta [7], : Experiments Spencer & Jones [72] Spanwise rms velocity, curves as in Fig Transverse rms velocity, curves as in Fig Velocity computed from Reynolds shear stress, curves as in Fig Turbulent kinetic energy budget, +: production, : transport, : dissipation, normalized by u 3 δ θ, solid lines: inert-.5, dashed lines: DNS Pantano & Sarkar M c =.3 [23], dotted line: DNS Rogers & Moser, [52]

17 LIST OF FIGURES XI 2.49 Streamwise rms velocity, solid line: inert-.7, dashed line: DNS Pantano & Sarkar M c =.7 [23], +: Experiments Elliott & Samimy [49] Transverse rms velocity, curves as in Fig Velocity computed from Reynolds shear stress, curves as in Fig Turbulent kinetic energy budget, +: production, : transport, : dissipation, normalized by u 3 /δ θ, solid lines: inert-.7, dashed lines: DNS Pantano & Sarkar M c =.7 [23] Dimensionless momentum thickness growth rate of the inert-.7 case, computed with Eq. (2.2) Turbulent kinetic energy budget, +: production, : transport, : dissipation, normalized by u 3 /δ θ, solid lines: inert-., dashed lines: DNS Pantano & Sarkar M c =. [23] Two-point correlation R with f = u, in the middle of the computational domain, averaged over the self-similar state, : inert-.5, : inert-.7, : inert Two-point correlation R 2 with f = u, in the middle of the computational domain, averaged over the self-similar state, symbols as in Fig Two-point correlation R with f = u 3, in the middle of the computational domain, averaged over the self-similar state, symbols as in Fig Two-point correlation R 2 with f = u 3, in the middle of the computational domain, averaged over the self-similar state, symbols as in Fig Two-point correlation R with f = Y O2, in the middle of the computational domain, averaged over the self-similar state, symbols as in Fig Two-point correlation R 2 with f = Y O2, in the middle of the computational domain, averaged over the self-similar state, symbols as in Fig Test of compact filter, solid: filter dissipation, dashed: ɛ Test of compact filter, solid: filter scalar dissipation, dashed: ɛ Y Averaged temperature, normalized by T =.5 (T + T 2 ), : inert-.5, : inert-.7, : inert Averaged density, normalized by ρ, symbols as in Fig Averaged pressure, normalized by ρ u 2, symbols as in Fig Favre averaged streamwise velocity, normalized by u, symbols as in Fig Reynolds stress ρ R, normalized by ρ u 2, curves as in Fig Reynolds stress ρ R 22, normalized by ρ u 2, curves as in Fig Reynolds stress ρ R 33, normalized by ρ u 2, curves as in Fig Reynolds stress ρ R 3, normalized by ρ u 2, curves as in Fig

18 XII LIST OF FIGURES 2.7 Turbulent kinetic energy ρ k, normalized by ρ u 2, curves as in Fig Reynolds shear stress anisotropy, b 3, curves as in Fig Streamwise Reynolds stress anisotropy, b, curves as in Fig Spanwise Reynolds stress anisotropy, b 22, curves as in Fig Transverse Reynolds stress anisotropy, b 33, curves as in Fig Budget of R, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: production, dashed: dissipation rate Budget of R, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: pressurestrain rate, dashed: turbulent transport Budget of R 22, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: production, dashed: dissipation rate Budget of R 22, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: pressurestrain rate, dashed: turbulent transport Budget of R 33, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: production, dashed: dissipation rate Budget of R 33, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: pressurestrain rate, dashed: turbulent transport Budget of R 3, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: production, dashed: dissipation rate Budget of R 3, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: pressurestrain rate, dashed: turbulent transport Production, integrated in transverse direction, normalized by ρ u 3 : +: P, : P 22, : P 33, : P Pressure-strain rate, integrated in transverse direction, normalized by ρ u 3 : +: Π, : Π 22, : Π 33, : Π Dissipation rate, integrated in transverse direction, normalized by ρ u 3 : +: ɛ, : ɛ 22, : ɛ 33, : ɛ Ratios of integrated budget terms: +: Π / P, : Π 3 / P 3, : P3 / Π, : Π 3 / Π Reynolds stress ρ R, normalized by ρ u 2, curves as in Fig Rms value of p, normalized by ρ u 2, curves as in Fig Rms value of u / x, normalized by δ ω, / u, curves as in Fig Correlation coefficient R (p, u / x ) between pressure and density fluctuations, curves as in Fig

19 LIST OF FIGURES XIII 2.92 Suppression of integrated p rms (+), integrated ( u / x ) rms ( ) and integrated pressure-strain rate Π ( ), normalized by the respective incompressible value at M c = Budget of ρ k, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: production, dashed: dissipation rate Budget of ρ k, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: pressure dilatation, dashed: turbulent transport Ratio of the integrated pressure dilatation and the TKE production versus M c Ratio of the integrated dissipation rate and the TKE production versus M c Decomposition of TKE dissipation rate, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: ɛ, dashed: ɛ 2, dotted: ɛ Decomposition of ɛ, normalized by ρ u 3 /δ ω, symbols as in Fig. 2.63, solid: ɛ s, dashed: ɛ d, dotted: ɛ I Ratio of the integrated compressible and solenoidal dissipation rates versus M c Ratio of the integrated dilatational and total dissipation rates versus M c Rms value of the density fluctuations, normalized by ρ, symbols as in Fig Rms value of the pressure fluctuations, normalized by p, symbols as in Fig Rms value of the temperature fluctuations, normalized by T, symbols as in Fig Rms value of the molecular weight fluctuations, normalized by W, symbols as in Fig Integrated rms values, +: p rms / p, : ρ rms / ρ, : T rms / T, : W rms / W Acoustic (solid line) and entropic part (dashed line) of the density fluctuations, normalized by ρ, symbols as in Fig Acoustic (solid line) and entropic part (dashed line) of the temperature fluctuations, normalized by T, symbols as in Fig Correlation coefficient R (ρ, p) between pressure and density fluctuations, symbols as in Fig Correlation coefficient R (ρ, W ) between pressure and molecular weight fluctuations, symbols as in Fig Case inert-.5: Parts of the pressure-strain correlation Π computed with the Green function, normalized by ρ u 3 /δ ω, +: f = f (A ), : f = f (A 2 ), : f = f (A 3 ), : f = f (A 4 ), : f = f (B ), : f = f (B 2 ), : f = f (B 3 ), : f = f (C ), : f = f (C 2 ), : f = f (C 3 ), : f = f (C 4 ), : f = f (C 5 ) Case inert-.5: Pressure-strain correlation Π, normalized by ρ u 3 /δ ω, solid: computed with the help of the Green function with f = f ( 4 i= A i + 3 i= B i + 5 i= C i), dashed: computed exactly

20 XIV LIST OF FIGURES 2.2Case inert-.7: Parts of the pressure-strain correlation Π computed with the Green function, normalized by ρ u 3 /δ ω, symbols as in Fig Case inert-.7: Pressure-strain correlation Π, normalized by ρ u 3 /δ ω, solid: computed with the help of the Green function with f = f ( 4 i= A i + 3 i= B i + 5 i= C i), lines as in Fig Case inert-.: Parts of the pressure-strain correlation Π computed with the Green function, normalized by ρ u 3 /δ ω, symbols as in Fig Case inert-.: Pressure-strain correlation Π, normalized by ρ u 3 /δ ω, solid: computed with the help of the Green function with f = f ( 4 i= A i + 3 i= B i + 5 i= C i), lines as in Fig Case inert-.5: Parts of the pressure-strain correlation Π computed with the Green function and with constant density ρ, normalized by ρ u 3 /δ ω, symbols as in Fig Case inert-.7: Parts of the pressure-strain correlation Π computed with the Green function and with constant density ρ, normalized by ρ u 3 /δ ω, symbols as in Fig Case inert-.: Parts of the pressure-strain correlation Π computed with the Green function and with constant density ρ, normalized by ρ u 3 /δ ω, symbols as in Fig Turbulent Mach number M t, symbols as in Fig Gradient Mach number M g, symbols as in Fig Turbulent Mach number M t plotted as a function of the gradient Mach number M g. Symbols as in Fig. 2.63, solid line: M t =.286M g, dashed line: M t =.59M g One-dimensional, streamwise spectrum of u / u at the beginning of the selfsimilar state, solid: inert-.5, dashed: inert-.7, dotted: inert One-dimensional, streamwise spectrum of TKE k/ u 2 at the beginning of the self-similar state, solid: inert-.5, dashed: inert-.7, dotted: inert-., the straight line has 5/3 slope One-dimensional, streamwise dissipation spectrum (spectrum of u / u multiplied with (k δ ω, ) 2 ) at the beginning of the self-similar state, solid: inert-.5, dashed: inert-.7, dotted: inert Favre averaged oxygen mass fraction, : inert-.5, : inert-.7, : inert Scalar variance, symbols as in Fig Case inert-.5: pdfs of oxygen mass fraction in planes with various Y, +:., :.2, :.3, :.4, :.5, :.6, :.7, :.8, : Case inert-.7: pdfs of oxygen mass fraction in planes with various Y, +:., :.2, :.3, :.4, :.5, :.6, :.7, :.8, :

21 LIST OF FIGURES XV 2.29Case inert-.: pdfs of oxygen mass fraction in planes with various Y, +:., :.2, :.3, :.4, :.5, :.6, :.7, :.8, : Pdfs of oxygen mass fraction in the plane with Y =.3 (solid) and Y =.5 (dashed), symbols as in Fig Mixing efficiency, : ɛ =.2, : ɛ = Major terms in the scalar variance transport equation, normalized by ρ u/δ ω, solid: turbulent production, dashed: turbulent transport, dotted: dissipation rate, symbols as in Fig Parts of the scalar dissipation rate, solid: ρy α V αi Y α x i, dashed: ρy α V αi Yα f x i, normalized by ρ u/δ ω, symbols as in Fig Scalar flux ρu Y α of oxygen, normalized by ρ u, symbols as in Fig Scalar flux ρu 3 Y α of oxygen, normalized by ρ u, symbols as in Fig Part of the streamwise scalar flux production, normalized by ρ u 2 /δ ω, symbols as in Fig Part of the streamwise scalar flux production, normalized by ρ u 2 /δ ω, symbols as in Fig Part of the transverse scalar flux production, normalized by ρ u 2 /δ ω, symbols as in Fig Major part of the diffusion of the transverse scalar flux, normalized by ρ u 2 /δ ω, symbols as in Fig Part of the dissipation rate of the streamwise scalar flux, normalized by ρ u 2 /δ ω, symbols as in Fig Part of the dissipation rate of the transverse scalar flux, normalized by ρ u 2 /δ ω, symbols as in Fig Part of the dissipation rate of the streamwise scalar flux, normalized by ρ u 2 /δ ω, symbols as in Fig Part of the dissipation rate of the transverse scalar flux, normalized by ρ u 2 /δ ω, symbols as in Fig Turbulent transport of the streamwise scalar flux, normalized by ρ u 2 /δ ω, symbols as in Fig Turbulent transport of the transverse scalar flux, normalized by ρ u 2 /δ ω, symbols as in Fig Pressure-scrambling term in streamwise direction, Π Y, normalized by ρ u 2 /δ ω, symbols as in Fig Pressure-scrambling term in transverse direction, Π Y 3, normalized by ρ u 2 /δ ω, symbols as in Fig

22 XVI LIST OF FIGURES 2.48Case inert-.5: Parts of the pressure-scrambling term Π Y 3 computed with the Green function, normalized by ρ u/δ ω, +: f = f (A ), : f = f (A 2 ), : f = f (A 3 ), : f = f (A 4 ), : f = f (B ), : f = f (B 2 ), : f = f (B 3 ), : f = f (C ), : f = f (C 2 ), : f = f (C 3 ), : f = f (C 4 ), : f = f (C 5 ) Case inert-.5: Pressure-scrambling term Π Y 3, normalized by ρ u/δ ω, solid: computed with the help of the Green function with f = f ( 4 i= A i + 3 i= B i + 5 i= C i), dashed: computed exactly Case inert-.7: Parts of the pressure-scrambling term Π Y 3 computed with the Green function, normalized by ρ u/δ ω, symbols as in Fig Case inert-.7: Pressure-scrambling term Π Y 3, normalized by ρ u/δ ω, solid: computed with the help of the Green function with f = f ( 4 i= A i + 3 i= B i + 5 i= C i), lines as in Fig Case inert-.: Parts of the pressure-scrambling term Π Y 3 computed with the Green function, normalized by ρ u/δ ω, symbols as in Fig Case inert-.: Pressure-scrambling term Π Y 3, normalized by ρ u/δ ω, solid: computed with the help of the Green function with f = f ( 4 i= A i + 3 i= B i + 5 i= C i), lines as in Fig Case inert-.5: Parts of the pressure-scrambling term Π Y 3 computed with the Green function and with constant density ρ, normalized by ρ u/δ ω, symbols as in Fig Case inert-.7: Parts of the pressure-scrambling term Π Y 3 computed with the Green function and with constant density ρ, normalized by ρ u/δ ω, symbols as in Fig Case inert-.: Parts of the pressure-scrambling term Π Y 3 computed with the Green function and with constant density ρ, normalized by ρ u/δ ω, symbols as in Fig One-dimensional, streamwise spectrum of the oxygen mass fraction Y, solid: inert-.5, dashed: inert-.7, dotted: inert-., the straight line has 5/3 slope One-dimensional dissipation spectrum of the oxygen mass fraction Y (spectrum of Y multiplied with (k δ ω, ) 2 ), solid: inert-.5, dashed: inert-.7, dotted: inert Case inert-.5: Instantaneous vorticity field, normalized by ω max, x -x 3 -plane in the middle of the computational domain at τ ω = 286, isoline at. is shown Case inert-.5: Instantaneous mass fraction field of O 2, x -x 3 -plane in the middle of the computational domain at τ ω = 286, isolines Y O2 =.5 and.95 are shown Based on vorticity thresholds: Mixing layer volume V ml (solid) and engulfed volume V en (dashed) vs. the normalized time passed since the beginning of the self-similar state at t B. Volumes are normalized with the mixing layer volume at the beginning of the self-similar state, V ml,b, : inert-.5, : inert-.7, : inert-. 62

23 LIST OF FIGURES XVII 2.62Based on mass fraction thresholds: Mixing layer volume V ml (solid) and engulfed volume V en (dashed) vs. the normalized time passed since the beginning of the self-similar state at t B. Volumes are normalized with the mixing layer volume at the beginning of the self-similar state, V ml,b. Symbols as in Fig Based on vorticity thresholds: Thickness computed from mixing layer volume δ vol (solid) and visual thickness δ vis (dashed). Thicknesses are normalized by the visual thickness at the beginning of the self-similar state, δ vis,b. Symbols as in Fig Based on mass fraction thresholds: Thickness computed from mixing layer volume δ vol (solid) and visual thickness δ vis (dashed). Thicknesses are normalized by the visual thickness at the beginning of the self-similar state, δ vis,b. Symbols as in Fig Based on vorticity thresholds: Mixing layer density ρ ml /ρ (solid), density of the engulfed volume, ρ en /ρ (dashed), and density of the mixed volume, ρ mix /ρ (dotted), vs. the normalized time passed since the beginning of the self-similar state at t B. Symbols as in Fig Based on mass fraction thresholds: Mixing layer density ρ ml /ρ (solid), density of the engulfed volume, ρ en /ρ (dashed), and density of the mixed volume, ρ mix /ρ (dotted), vs. the normalized time passed since the beginning of the selfsimilar state at t B. Symbols as in Fig Particle tracks in the upper half of the computational domain during the selfsimilar state of inert Pdfs of the local Mach number magnitude at the time when the particles are crossing the upper vorticity threshold. Symbols as in Fig Case inert-.5: Instantaneous isosurface of vorticity ω =.2 ω max at τ ω = Case inert-.7: Instantaneous isosurface of vorticity ω =.2 ω max at τ ω = Case inert-.: Instantaneous isosurface of vorticity ω =.2 ω max at τ ω = Case inert-.5: Instantaneous isosurface of oxygen mass fraction Y =.9 at τ ω = Case inert-.7: Instantaneous isosurface of oxygen mass fraction Y =.9 at τ ω = Case inert-.: Instantaneous isosurface of oxygen mass fraction Y =.9 at τ ω = Number of squares N covering the interface ω =. ω max vs. δ ω, /r, averaged over the self-similar state, solid: inert-.5, dashed: inert-.7, dotted: inert Number of squares N covering the interface Y =.95 vs. δ ω, /r, averaged over the self-similar state, solid: inert-.5, dashed: inert-.7, dotted: inert Temporal development of the maximum pressure gradient, normalized by p av /δ ω,, : inert-.5, : inert-.7, : inert

24 XVIII LIST OF FIGURES 2.78Case inert-.: Pressure gradient normalized by p av /δ ω, on a line parallel to the x -axis through x 2 =.3L 2 and x 3 =.32L 3 at τ ω = 23. Every 4th grid point is shown Case inert-.: Pressure normalized by p av on a line parallel to the x -axis through x 2 =.3L 2 and x 3 =.32L 3 at τ ω = 23. Every 4th grid point is shown Case inert-.: Density in x -direction normalized by ρ on a line parallel to the x -axis through x 2 =.3L 2 and x 3 =.32L 3 at τ ω = 23. Every 4th grid point is shown Case inert-.: Temperature normalized by T on a line parallel to the x -axis through x 2 =.3L 2 and x 3 =.32L 3 at τ ω = 23. Every 4th grid point is shown Case inert-.: Dilatation normalized by u/δ ω, on a line parallel to the x -axis through x 2 =.3L 2 and x 3 =.32L 3 at τ ω = 23. Every 4th grid point is shown Case inert-.: Vorticity normalized by u/δ ω, on a line parallel to the x -axis through x 2 =.3L 2 and x 3 =.32L 3 at τ ω = 23. Every 4th grid point is shown Case inert-.: Pressure gradient normalized by p av /δ ω, on a line through x =.2L 2, x 2 =.38 and x 3 =.3L 3 (in x -x 2 -plane, inclined 45 to the x -x 3 - plane) at τ ω = 295. Every 4th grid point is shown Case inert-.: Pressure normalized by p av on a line through x =.2L 2, x 2 =.38 and x 3 =.3L 3 (in x -x 2 -plane, inclined 45 to the x -x 3 -plane) at τ ω = 295. Every 4th grid point is shown Case inert-.: Density in x -direction normalized by ρ on a line through x =.2L 2, x 2 =.38 and x 3 =.3L 3 (in x -x 2 -plane, inclined 45 to the x -x 3 - plane) at τ ω = 295. Every 4th grid point is shown Case inert-.: Temperature normalized by T on a line through x =.2L 2, x 2 =.38 and x 3 =.3L 3 (in x -x 2 -plane, inclined 45 to the x -x 3 -plane) at τ ω = 295. Every 4th grid point is shown on Case inert-.: Dilatation normalized by u/δ ω, on a line through x =.2L 2, x 2 =.38 and x 3 =.3L 3 (in x -x 2 -plane, inclined 45 to the x -x 3 -plane) at τ ω = 295. Every 4th grid point is shown Case inert-.: Vorticity normalized by u/δ ω, on a line through x =.2L 2, x 2 =.38 and x 3 =.3L 3 (in x -x 2 -plane, inclined 45 to the x -x 3 -plane) at τ ω = 295. Every 4th grid point is shown Case inert-.: Instantaneous dilatation field and pressure isolines, x -x 2 -plane through x 3 =.49L 3 at τ ω = 295. Dilatation is normalized by δ ω, / u Case inert-.: Instantaneous magnitude of vorticity and velocity vectors, x -x 2 - plane through x 3 =.49L 3 at τ ω = 295. Vorticity is normalized by δ ω, / u.. 74

25 LIST OF FIGURES XIX 2.92Case inert-.: Instantaneous dilatation field and pressure isolines, x -x 3 -plane through x 2 =.59L 2 at τ ω = 295. Scale as in Fig Case inert-.: Instantaneous magnitude of vorticity and velocity vectors, x -x 3 - plane through x 2 =.59L 2 at τ ω = 295. Scale as in Fig Case inert-.: Instantaneous dilatation field and pressure isolines, x 2 -x 3 -plane through x =.3L at τ ω = 295. Scale as in Fig Case inert-.: Instantaneous magnitude of vorticity and velocity vectors, x 2 -x 3 - plane through x =.3L at τ ω = 295. Scale as in Fig Case inert-.: Instantaneous dilatation field, x -x 3 -plane through x 2 =.59L 2 at τ ω = 295. Dilatation is normalized by δ ω, / u Case inert-.: Instantaneous pressure gradient field, x -x 3 -plane through x 2 =.59L 2 at τ ω = 295. Pressure gradient is normalized by δ ω, / p av Burke-Schumann relations, : Y O, : Y F, : Y P Frozen chemistry, : Y O, : Y F Case inf-.5: Instantaneous mixture fraction field, x -x 3 -plane in the middle of the computational domain at τ ω = 573, isolines z =., z s =.3 and z =.9 are shown Case inf-.5: Instantaneous temperature field, x -x 3 -plane in the middle of the computational domain at τ ω = 573, isolines z =., z s =.3 and z =.9 are shown Case inf-.7: Instantaneous mixture fraction field, x -x 3 -plane in the middle of the computational domain at τ ω = 76, isolines z =., z s =.3 and z =.9 are shown Case inf-.7: Instantaneous temperature field, x -x 3 -plane in the middle of the computational domain at τ ω = 76, isolines z =., z s =.3 and z =.9 are shown Case inf-.: Instantaneous mixture fraction field, x -x 3 -plane in the middle of the computational domain at τ ω = 83, isolines z =., z s =.3 and z =.9 are shown Case inf-.: Instantaneous temperature field, x -x 3 -plane in the middle of the computational domain at τ ω = 83, isolines z =., z s =.3 and z =.9 are shown Temporal development of the momentum thickness, normalized by the initial momentum thickness δ θ,, : inf-.5, : inf-.7, : inf-., dashed lines show linear regressions for the self-similar state Temporal development of the product mass thickness, normalized by the initial product mass thickness δ θ,, symbols as in Fig. 3.9, dashed lines show linear regressions for the self-similar state

Buyout and Distressed Private Equity: Performance and Value Creation

Buyout and Distressed Private Equity: Performance and Value Creation TECHNISCHE UNIVERSITAT MUNCHEN Lehrstuhl fur Betriebswirtschaftslehre - Finanzmanagement und Kapitalmarkte (Univ.-Prof. Dr. Christoph Kaserer) Buyout and Distressed Private Equity: Performance and Value

More information

Lecture 3 Fluid Dynamics and Balance Equa6ons for Reac6ng Flows

Lecture 3 Fluid Dynamics and Balance Equa6ons for Reac6ng Flows Lecture 3 Fluid Dynamics and Balance Equa6ons for Reac6ng Flows 3.- 1 Basics: equations of continuum mechanics - balance equations for mass and momentum - balance equations for the energy and the chemical

More information

A subgrid-scale model for the scalar dissipation rate in nonpremixed combustion

A subgrid-scale model for the scalar dissipation rate in nonpremixed combustion Center for Turbulence Research Proceedings of the Summer Program 1998 11 A subgrid-scale model for the scalar dissipation rate in nonpremixed combustion By A. W. Cook 1 AND W. K. Bushe A subgrid-scale

More information

for High Performance Computing

for High Performance Computing Technische Universität München Institut für Informatik Lehrstuhl für Rechnertechnik und Rechnerorganisation Automatic Performance Engineering Workflows for High Performance Computing Ventsislav Petkov

More information

Targeted Advertising and Consumer Privacy Concerns Experimental Studies in an Internet Context

Targeted Advertising and Consumer Privacy Concerns Experimental Studies in an Internet Context TECHNISCHE UNIVERSITAT MUNCHEN Lehrstuhl fur Betriebswirtschaftslehre - Dienstleistungsund Technologiemarketing Targeted Advertising and Consumer Privacy Concerns Experimental Studies in an Internet Context

More information

NUMERICAL ANALYSIS OF THE EFFECTS OF WIND ON BUILDING STRUCTURES

NUMERICAL ANALYSIS OF THE EFFECTS OF WIND ON BUILDING STRUCTURES Vol. XX 2012 No. 4 28 34 J. ŠIMIČEK O. HUBOVÁ NUMERICAL ANALYSIS OF THE EFFECTS OF WIND ON BUILDING STRUCTURES Jozef ŠIMIČEK email: jozef.simicek@stuba.sk Research field: Statics and Dynamics Fluids mechanics

More information

INTRODUCTION TO FLUID MECHANICS

INTRODUCTION TO FLUID MECHANICS INTRODUCTION TO FLUID MECHANICS SIXTH EDITION ROBERT W. FOX Purdue University ALAN T. MCDONALD Purdue University PHILIP J. PRITCHARD Manhattan College JOHN WILEY & SONS, INC. CONTENTS CHAPTER 1 INTRODUCTION

More information

ME6130 An introduction to CFD 1-1

ME6130 An introduction to CFD 1-1 ME6130 An introduction to CFD 1-1 What is CFD? Computational fluid dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions, and related phenomena by solving numerically

More information

Express Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology

Express Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology Express Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology Dimitrios Sofialidis Technical Manager, SimTec Ltd. Mechanical Engineer, PhD PRACE Autumn School 2013 - Industry

More information

Basic Equations, Boundary Conditions and Dimensionless Parameters

Basic Equations, Boundary Conditions and Dimensionless Parameters Chapter 2 Basic Equations, Boundary Conditions and Dimensionless Parameters In the foregoing chapter, many basic concepts related to the present investigation and the associated literature survey were

More information

Chapter 2. Derivation of the Equations of Open Channel Flow. 2.1 General Considerations

Chapter 2. Derivation of the Equations of Open Channel Flow. 2.1 General Considerations Chapter 2. Derivation of the Equations of Open Channel Flow 2.1 General Considerations Of interest is water flowing in a channel with a free surface, which is usually referred to as open channel flow.

More information

TFAWS AUGUST 2003 VULCAN CFD CODE OVERVIEW / DEMO. Jeffery A. White. Hypersonic Airbreathing Propulsion Branch

TFAWS AUGUST 2003 VULCAN CFD CODE OVERVIEW / DEMO. Jeffery A. White. Hypersonic Airbreathing Propulsion Branch TFAWS AUGUST 2003 VULCAN CFD CODE OVERVIEW / DEMO Jeffery A. White Hypersonic Airbreathing Propulsion Branch VULCAN DEVELOPMENT HISTORY Evolved from the LARCK code development project (1993-1996). LARCK

More information

Purdue University - School of Mechanical Engineering. Objective: Study and predict fluid dynamics of a bluff body stabilized flame configuration.

Purdue University - School of Mechanical Engineering. Objective: Study and predict fluid dynamics of a bluff body stabilized flame configuration. Extinction Dynamics of Bluff Body Stabilized Flames Investigator: Steven Frankel Graduate Students: Travis Fisher and John Roach Sponsor: Air Force Research Laboratory and Creare, Inc. Objective: Study

More information

Abaqus/CFD Sample Problems. Abaqus 6.10

Abaqus/CFD Sample Problems. Abaqus 6.10 Abaqus/CFD Sample Problems Abaqus 6.10 Contents 1. Oscillatory Laminar Plane Poiseuille Flow 2. Flow in Shear Driven Cavities 3. Buoyancy Driven Flow in Cavities 4. Turbulent Flow in a Rectangular Channel

More information

Lecture 6 - Boundary Conditions. Applied Computational Fluid Dynamics

Lecture 6 - Boundary Conditions. Applied Computational Fluid Dynamics Lecture 6 - Boundary Conditions Applied Computational Fluid Dynamics Instructor: André Bakker http://www.bakker.org André Bakker (2002-2006) Fluent Inc. (2002) 1 Outline Overview. Inlet and outlet boundaries.

More information

Aerodynamic Department Institute of Aviation. Adam Dziubiński CFD group FLUENT

Aerodynamic Department Institute of Aviation. Adam Dziubiński CFD group FLUENT Adam Dziubiński CFD group IoA FLUENT Content Fluent CFD software 1. Short description of main features of Fluent 2. Examples of usage in CESAR Analysis of flow around an airfoil with a flap: VZLU + ILL4xx

More information

CHEMICAL ENGINEERING AND CHEMICAL PROCESS TECHNOLOGY - Vol. I - Interphase Mass Transfer - A. Burghardt

CHEMICAL ENGINEERING AND CHEMICAL PROCESS TECHNOLOGY - Vol. I - Interphase Mass Transfer - A. Burghardt INTERPHASE MASS TRANSFER A. Burghardt Institute of Chemical Engineering, Polish Academy of Sciences, Poland Keywords: Turbulent flow, turbulent mass flux, eddy viscosity, eddy diffusivity, Prandtl mixing

More information

Differential Relations for Fluid Flow. Acceleration field of a fluid. The differential equation of mass conservation

Differential Relations for Fluid Flow. Acceleration field of a fluid. The differential equation of mass conservation Differential Relations for Fluid Flow In this approach, we apply our four basic conservation laws to an infinitesimally small control volume. The differential approach provides point by point details of

More information

Ravi Kumar Singh*, K. B. Sahu**, Thakur Debasis Mishra***

Ravi Kumar Singh*, K. B. Sahu**, Thakur Debasis Mishra*** Ravi Kumar Singh, K. B. Sahu, Thakur Debasis Mishra / International Journal of Engineering Research and Applications (IJERA) ISSN: 48-96 www.ijera.com Vol. 3, Issue 3, May-Jun 3, pp.766-77 Analysis of

More information

Coupling Forced Convection in Air Gaps with Heat and Moisture Transfer inside Constructions

Coupling Forced Convection in Air Gaps with Heat and Moisture Transfer inside Constructions Coupling Forced Convection in Air Gaps with Heat and Moisture Transfer inside Constructions M. Bianchi Janetti 1, F. Ochs 1 and R. Pfluger 1 1 University of Innsbruck, Unit for Energy Efficient Buildings,

More information

Hollow Cone Spray Characterization and Integral Modeling

Hollow Cone Spray Characterization and Integral Modeling Technische Universität München Institut für Energietechnik Lehrstuhl für Thermodynamik Hollow Cone Spray Characterization and Integral Modeling Peter Bollweg Vollständiger Abdruck der von der Fakultät

More information

Part IV. Conclusions

Part IV. Conclusions Part IV Conclusions 189 Chapter 9 Conclusions and Future Work CFD studies of premixed laminar and turbulent combustion dynamics have been conducted. These studies were aimed at explaining physical phenomena

More information

AN EFFECT OF GRID QUALITY ON THE RESULTS OF NUMERICAL SIMULATIONS OF THE FLUID FLOW FIELD IN AN AGITATED VESSEL

AN EFFECT OF GRID QUALITY ON THE RESULTS OF NUMERICAL SIMULATIONS OF THE FLUID FLOW FIELD IN AN AGITATED VESSEL 14 th European Conference on Mixing Warszawa, 10-13 September 2012 AN EFFECT OF GRID QUALITY ON THE RESULTS OF NUMERICAL SIMULATIONS OF THE FLUID FLOW FIELD IN AN AGITATED VESSEL Joanna Karcz, Lukasz Kacperski

More information

HEAT TRANSFER ANALYSIS IN A 3D SQUARE CHANNEL LAMINAR FLOW WITH USING BAFFLES 1 Vikram Bishnoi

HEAT TRANSFER ANALYSIS IN A 3D SQUARE CHANNEL LAMINAR FLOW WITH USING BAFFLES 1 Vikram Bishnoi HEAT TRANSFER ANALYSIS IN A 3D SQUARE CHANNEL LAMINAR FLOW WITH USING BAFFLES 1 Vikram Bishnoi 2 Rajesh Dudi 1 Scholar and 2 Assistant Professor,Department of Mechanical Engineering, OITM, Hisar (Haryana)

More information

ACETYLENE AIR DIFFUSION FLAME COMPUTATIONS; COMPARISON OF STATE RELATIONS VERSUS FINITE RATE KINETICS

ACETYLENE AIR DIFFUSION FLAME COMPUTATIONS; COMPARISON OF STATE RELATIONS VERSUS FINITE RATE KINETICS ACETYLENE AIR DIFFUSION FLAME COMPUTATIONS; COMPARISON OF STATE RELATIONS VERSUS FINITE RATE KINETICS by Z Zhang and OA Ezekoye Department of Mechanical Engineering The University of Texas at Austin Austin,

More information

Free Convection Film Flows and Heat Transfer

Free Convection Film Flows and Heat Transfer Deyi Shang Free Convection Film Flows and Heat Transfer With 109 Figures and 69 Tables < J Springer Contents 1 Introduction 1 1.1 Scope 1 1.2 Application Backgrounds 1 1.3 Previous Developments 2 1.3.1

More information

Customer Training Material. Lecture 2. Introduction to. Methodology ANSYS FLUENT. ANSYS, Inc. Proprietary 2010 ANSYS, Inc. All rights reserved.

Customer Training Material. Lecture 2. Introduction to. Methodology ANSYS FLUENT. ANSYS, Inc. Proprietary 2010 ANSYS, Inc. All rights reserved. Lecture 2 Introduction to CFD Methodology Introduction to ANSYS FLUENT L2-1 What is CFD? Computational Fluid Dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions,

More information

Lecture 8 - Turbulence. Applied Computational Fluid Dynamics

Lecture 8 - Turbulence. Applied Computational Fluid Dynamics Lecture 8 - Turbulence Applied Computational Fluid Dynamics Instructor: André Bakker http://www.bakker.org André Bakker (2002-2006) Fluent Inc. (2002) 1 Turbulence What is turbulence? Effect of turbulence

More information

Lecturer, Department of Engineering, ar45@le.ac.uk, Lecturer, Department of Mathematics, sjg50@le.ac.uk

Lecturer, Department of Engineering, ar45@le.ac.uk, Lecturer, Department of Mathematics, sjg50@le.ac.uk 39 th AIAA Fluid Dynamics Conference, San Antonio, Texas. A selective review of CFD transition models D. Di Pasquale, A. Rona *, S. J. Garrett Marie Curie EST Fellow, Engineering, ddp2@le.ac.uk * Lecturer,

More information

Keywords: CFD, heat turbomachinery, Compound Lean Nozzle, Controlled Flow Nozzle, efficiency.

Keywords: CFD, heat turbomachinery, Compound Lean Nozzle, Controlled Flow Nozzle, efficiency. CALCULATION OF FLOW CHARACTERISTICS IN HEAT TURBOMACHINERY TURBINE STAGE WITH DIFFERENT THREE DIMENSIONAL SHAPE OF THE STATOR BLADE WITH ANSYS CFX SOFTWARE A. Yangyozov *, R. Willinger ** * Department

More information

Adaptation of General Purpose CFD Code for Fusion MHD Applications*

Adaptation of General Purpose CFD Code for Fusion MHD Applications* Adaptation of General Purpose CFD Code for Fusion MHD Applications* Andrei Khodak Princeton Plasma Physics Laboratory P.O. Box 451 Princeton, NJ, 08540 USA akhodak@pppl.gov Abstract Analysis of many fusion

More information

Indiana's Academic Standards 2010 ICP Indiana's Academic Standards 2016 ICP. map) that describe the relationship acceleration, velocity and distance.

Indiana's Academic Standards 2010 ICP Indiana's Academic Standards 2016 ICP. map) that describe the relationship acceleration, velocity and distance. .1.1 Measure the motion of objects to understand.1.1 Develop graphical, the relationships among distance, velocity and mathematical, and pictorial acceleration. Develop deeper understanding through representations

More information

CBE 6333, R. Levicky 1 Review of Fluid Mechanics Terminology

CBE 6333, R. Levicky 1 Review of Fluid Mechanics Terminology CBE 6333, R. Levicky 1 Review of Fluid Mechanics Terminology The Continuum Hypothesis: We will regard macroscopic behavior of fluids as if the fluids are perfectly continuous in structure. In reality,

More information

SCALAR MIXING AND DISSIPATION RATE IN LARGE-EDDY SIMULATIONS OF NON-PREMIXED TURBULENT COMBUSTION

SCALAR MIXING AND DISSIPATION RATE IN LARGE-EDDY SIMULATIONS OF NON-PREMIXED TURBULENT COMBUSTION Proceedings of the Combustion Institute, Volume 28, 2000/pp. 41 49 SCALAR MIXING AND DISSIPATION RATE IN LARGE-EDDY SIMULATIONS OF NON-PREMIXED TURBULENT COMBUSTION HEINZ PITSCH and HELFRIED STEINER Center

More information

O.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM. Darmstadt, 27.06.2012

O.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM. Darmstadt, 27.06.2012 O.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM Darmstadt, 27.06.2012 Michael Ehlen IB Fischer CFD+engineering GmbH Lipowskystr. 12 81373 München Tel. 089/74118743 Fax 089/74118749

More information

1. Fluids Mechanics and Fluid Properties. 1.1 Objectives of this section. 1.2 Fluids

1. Fluids Mechanics and Fluid Properties. 1.1 Objectives of this section. 1.2 Fluids 1. Fluids Mechanics and Fluid Properties What is fluid mechanics? As its name suggests it is the branch of applied mechanics concerned with the statics and dynamics of fluids - both liquids and gases.

More information

Basic Principles in Microfluidics

Basic Principles in Microfluidics Basic Principles in Microfluidics 1 Newton s Second Law for Fluidics Newton s 2 nd Law (F= ma) : Time rate of change of momentum of a system equal to net force acting on system!f = dp dt Sum of forces

More information

Graduate Certificate Program in Energy Conversion & Transport Offered by the Department of Mechanical and Aerospace Engineering

Graduate Certificate Program in Energy Conversion & Transport Offered by the Department of Mechanical and Aerospace Engineering Graduate Certificate Program in Energy Conversion & Transport Offered by the Department of Mechanical and Aerospace Engineering Intended Audience: Main Campus Students Distance (online students) Both Purpose:

More information

CFD Simulation of HSDI Engine Combustion Using VECTIS

CFD Simulation of HSDI Engine Combustion Using VECTIS CFD Simulation of HSDI Engine Combustion Using VECTIS G. Li, S.M. Sapsford Ricardo Consulting Engineer s Ltd., Shoreham-by-Sea, UK ABSTRACT As part of the VECTIS code validation programme, CFD simulations

More information

11 Navier-Stokes equations and turbulence

11 Navier-Stokes equations and turbulence 11 Navier-Stokes equations and turbulence So far, we have considered ideal gas dynamics governed by the Euler equations, where internal friction in the gas is assumed to be absent. Real fluids have internal

More information

Figure 1.1 Vector A and Vector F

Figure 1.1 Vector A and Vector F CHAPTER I VECTOR QUANTITIES Quantities are anything which can be measured, and stated with number. Quantities in physics are divided into two types; scalar and vector quantities. Scalar quantities have

More information

Fundamentals of Fluid Mechanics

Fundamentals of Fluid Mechanics Sixth Edition. Fundamentals of Fluid Mechanics International Student Version BRUCE R. MUNSON DONALD F. YOUNG Department of Aerospace Engineering and Engineering Mechanics THEODORE H. OKIISHI Department

More information

Introduction to CFD Analysis

Introduction to CFD Analysis Introduction to CFD Analysis 2-1 What is CFD? Computational Fluid Dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions, and related phenomena by solving numerically

More information

du u U 0 U dy y b 0 b

du u U 0 U dy y b 0 b BASIC CONCEPTS/DEFINITIONS OF FLUID MECHANICS (by Marios M. Fyrillas) 1. Density (πυκνότητα) Symbol: 3 Units of measure: kg / m Equation: m ( m mass, V volume) V. Pressure (πίεση) Alternative definition:

More information

MEL 807 Computational Heat Transfer (2-0-4) Dr. Prabal Talukdar Assistant Professor Department of Mechanical Engineering IIT Delhi

MEL 807 Computational Heat Transfer (2-0-4) Dr. Prabal Talukdar Assistant Professor Department of Mechanical Engineering IIT Delhi MEL 807 Computational Heat Transfer (2-0-4) Dr. Prabal Talukdar Assistant Professor Department of Mechanical Engineering IIT Delhi Time and Venue Course Coordinator: Dr. Prabal Talukdar Room No: III, 357

More information

CONVERGE Features, Capabilities and Applications

CONVERGE Features, Capabilities and Applications CONVERGE Features, Capabilities and Applications CONVERGE CONVERGE The industry leading CFD code for complex geometries with moving boundaries. Start using CONVERGE and never make a CFD mesh again. CONVERGE

More information

Numerical simulations of heat transfer in plane channel

Numerical simulations of heat transfer in plane channel Numerical simulations of heat transfer in plane channel flow Najla El Gharbi, Rafik Absi, Ahmed Benzaoui To cite this version: Najla El Gharbi, Rafik Absi, Ahmed Benzaoui. Numerical simulations of heat

More information

Fluid Mechanics Prof. S. K. Som Department of Mechanical Engineering Indian Institute of Technology, Kharagpur

Fluid Mechanics Prof. S. K. Som Department of Mechanical Engineering Indian Institute of Technology, Kharagpur Fluid Mechanics Prof. S. K. Som Department of Mechanical Engineering Indian Institute of Technology, Kharagpur Lecture - 20 Conservation Equations in Fluid Flow Part VIII Good morning. I welcome you all

More information

Modelling and Computation of Compressible Liquid Flows with Phase Transition

Modelling and Computation of Compressible Liquid Flows with Phase Transition JASS 2009 - Joint Advanced Student School, Saint Petersburg, 29. 03. - 07. 04. 2009 Modelling and Simulation in Multidisciplinary Engineering Modelling and Computation of Compressible Liquid Flows with

More information

CHAPTER 4 CFD ANALYSIS OF THE MIXER

CHAPTER 4 CFD ANALYSIS OF THE MIXER 98 CHAPTER 4 CFD ANALYSIS OF THE MIXER This section presents CFD results for the venturi-jet mixer and compares the predicted mixing pattern with the present experimental results and correlation results

More information

Effect of Pressure Ratio on Film Cooling of Turbine Aerofoil Using CFD

Effect of Pressure Ratio on Film Cooling of Turbine Aerofoil Using CFD Universal Journal of Mechanical Engineering 1(4): 122-127, 2013 DOI: 10.13189/ujme.2013.010403 http://www.hrpub.org Effect of Pressure Ratio on Film Cooling of Turbine Aerofoil Using CFD Vibhor Baghel

More information

Kinetic effects in the turbulent solar wind: capturing ion physics with a Vlasov code

Kinetic effects in the turbulent solar wind: capturing ion physics with a Vlasov code Kinetic effects in the turbulent solar wind: capturing ion physics with a Vlasov code Francesco Valentini francesco.valentini@fis.unical.it S. Servidio, D. Perrone, O. Pezzi, B. Maruca, F. Califano, W.

More information

Adaptation and validation of OpenFOAM CFD-solvers for nuclear safety related flow simulations

Adaptation and validation of OpenFOAM CFD-solvers for nuclear safety related flow simulations Adaptation and validation of OpenFOAM CFD-solvers for nuclear safety related flow simulations SAFIR2010 Seminar, 10.-11.3.2011, Espoo Juho Peltola, Timo Pättikangas (VTT) Tomas Brockmann, Timo Siikonen

More information

OpenFOAM Opensource and CFD

OpenFOAM Opensource and CFD OpenFOAM Opensource and CFD Andrew King Department of Mechanical Engineering Curtin University Outline What is Opensource Software OpenFOAM Overview Utilities, Libraries and Solvers Data Formats The CFD

More information

CFD Application on Food Industry; Energy Saving on the Bread Oven

CFD Application on Food Industry; Energy Saving on the Bread Oven Middle-East Journal of Scientific Research 13 (8): 1095-1100, 2013 ISSN 1990-9233 IDOSI Publications, 2013 DOI: 10.5829/idosi.mejsr.2013.13.8.548 CFD Application on Food Industry; Energy Saving on the

More information

Turbulent mixing in clouds latent heat and cloud microphysics effects

Turbulent mixing in clouds latent heat and cloud microphysics effects Turbulent mixing in clouds latent heat and cloud microphysics effects Szymon P. Malinowski1*, Mirosław Andrejczuk2, Wojciech W. Grabowski3, Piotr Korczyk4, Tomasz A. Kowalewski4 and Piotr K. Smolarkiewicz3

More information

4.What is the appropriate dimensionless parameter to use in comparing flow types? YOUR ANSWER: The Reynolds Number, Re.

4.What is the appropriate dimensionless parameter to use in comparing flow types? YOUR ANSWER: The Reynolds Number, Re. CHAPTER 08 1. What is most likely to be the main driving force in pipe flow? A. Gravity B. A pressure gradient C. Vacuum 2.What is a general description of the flow rate in laminar flow? A. Small B. Large

More information

FLUID FLOW STREAMLINE LAMINAR FLOW TURBULENT FLOW REYNOLDS NUMBER

FLUID FLOW STREAMLINE LAMINAR FLOW TURBULENT FLOW REYNOLDS NUMBER VISUAL PHYSICS School of Physics University of Sydney Australia FLUID FLOW STREAMLINE LAMINAR FLOW TURBULENT FLOW REYNOLDS NUMBER? What type of fluid flow is observed? The above pictures show how the effect

More information

Lecture 3. Turbulent fluxes and TKE budgets (Garratt, Ch 2)

Lecture 3. Turbulent fluxes and TKE budgets (Garratt, Ch 2) Lecture 3. Turbulent fluxes and TKE budgets (Garratt, Ch 2) In this lecture How does turbulence affect the ensemble-mean equations of fluid motion/transport? Force balance in a quasi-steady turbulent boundary

More information

Simulation at Aeronautics Test Facilities A University Perspective Helen L. Reed, Ph.D., P.E. ASEB meeting, Irvine CA 15 October 2014 1500-1640

Simulation at Aeronautics Test Facilities A University Perspective Helen L. Reed, Ph.D., P.E. ASEB meeting, Irvine CA 15 October 2014 1500-1640 Simulation at Aeronautics Test A University Perspective Helen L. Reed, Ph.D., P.E. ASEB meeting, Irvine CA 15 October 2014 1500-1640 Questions How has the ability to do increasingly accurate modeling and

More information

Chapter 5 MASS, BERNOULLI AND ENERGY EQUATIONS

Chapter 5 MASS, BERNOULLI AND ENERGY EQUATIONS Fluid Mechanics: Fundamentals and Applications, 2nd Edition Yunus A. Cengel, John M. Cimbala McGraw-Hill, 2010 Chapter 5 MASS, BERNOULLI AND ENERGY EQUATIONS Lecture slides by Hasan Hacışevki Copyright

More information

How To Run A Cdef Simulation

How To Run A Cdef Simulation Simple CFD Simulations and Visualisation using OpenFOAM and ParaView Sachiko Arvelius, PhD Purpose of this presentation To show my competence in CFD (Computational Fluid Dynamics) simulation and visualisation

More information

1 The basic equations of fluid dynamics

1 The basic equations of fluid dynamics 1 The basic equations of fluid dynamics The main task in fluid dynamics is to find the velocity field describing the flow in a given domain. To do this, one uses the basic equations of fluid flow, which

More information

How To Write A Program For The Pd Framework

How To Write A Program For The Pd Framework Enhanced divergence-free elements for efficient incompressible flow simulations in the PDE framework Peano, Miriam Mehl, Christoph Zenger, Fakultät für Informatik TU München Germany Outline Derivation

More information

CFD Grows Up! Martin W. Liddament Ventilation, Energy and Environmental Technology (VEETECH Ltd) What is Computational Fluid Dynamics?

CFD Grows Up! Martin W. Liddament Ventilation, Energy and Environmental Technology (VEETECH Ltd) What is Computational Fluid Dynamics? CIBSE/ASHRAE Meeting CFD Grows Up! Martin W. Liddament Ventilation, Energy and Environmental Technology (VEETECH Ltd) 10 th December 2003 What is Computational Fluid Dynamics? CFD is a numerical means

More information

Laminar Flow and Heat Transfer of Herschel-Bulkley Fluids in a Rectangular Duct; Finite-Element Analysis

Laminar Flow and Heat Transfer of Herschel-Bulkley Fluids in a Rectangular Duct; Finite-Element Analysis Tamkang Journal of Science and Engineering, Vol. 12, No. 1, pp. 99 107 (2009) 99 Laminar Flow and Heat Transfer of Herschel-Bulkley Fluids in a Rectangular Duct; Finite-Element Analysis M. E. Sayed-Ahmed

More information

High Speed Aerodynamics Prof. K. P. Sinhamahapatra Department of Aerospace Engineering Indian Institute of Technology, Kharagpur

High Speed Aerodynamics Prof. K. P. Sinhamahapatra Department of Aerospace Engineering Indian Institute of Technology, Kharagpur High Speed Aerodynamics Prof. K. P. Sinhamahapatra Department of Aerospace Engineering Indian Institute of Technology, Kharagpur Module No. # 01 Lecture No. # 06 One-dimensional Gas Dynamics (Contd.) We

More information

CFD SIMULATION OF SDHW STORAGE TANK WITH AND WITHOUT HEATER

CFD SIMULATION OF SDHW STORAGE TANK WITH AND WITHOUT HEATER International Journal of Advancements in Research & Technology, Volume 1, Issue2, July-2012 1 CFD SIMULATION OF SDHW STORAGE TANK WITH AND WITHOUT HEATER ABSTRACT (1) Mr. Mainak Bhaumik M.E. (Thermal Engg.)

More information

Aeroacoustic simulation based on linearized Euler equations and stochastic sound source modelling

Aeroacoustic simulation based on linearized Euler equations and stochastic sound source modelling Aeroacoustic simulation based on linearized Euler equations and stochastic sound source modelling H. Dechipre a, M. Hartmann a, J. W Delfs b and R. Ewert b a Volkswagen AG, Brieffach 1777, 38436 Wolfsburg,

More information

APPLICATION OF TRANSIENT WELLBORE SIMULATOR TO EVALUATE DELIVERABILITY CURVE ON HYPOTHETICAL WELL-X

APPLICATION OF TRANSIENT WELLBORE SIMULATOR TO EVALUATE DELIVERABILITY CURVE ON HYPOTHETICAL WELL-X PROCEEDINGS, Thirty-Third Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 8-30, 008 SGP-TR-185 APPLICATION OF TRANSIENT WELLBORE SIMULATOR TO EVALUATE DELIVERABILITY

More information

Notes on Polymer Rheology Outline

Notes on Polymer Rheology Outline 1 Why is rheology important? Examples of its importance Summary of important variables Description of the flow equations Flow regimes - laminar vs. turbulent - Reynolds number - definition of viscosity

More information

A Contribution to Fire Detection Modelling and Simulation

A Contribution to Fire Detection Modelling and Simulation A Contribution to Fire Detection Modelling and Simulation Der Fakultät für Ingenieurwissenschaften der Universität Duisburg-Essen zur Erlangung des akademischen Grades eines Doktor-Ingenieurs genehmigte

More information

TWO-DIMENSIONAL FINITE ELEMENT ANALYSIS OF FORCED CONVECTION FLOW AND HEAT TRANSFER IN A LAMINAR CHANNEL FLOW

TWO-DIMENSIONAL FINITE ELEMENT ANALYSIS OF FORCED CONVECTION FLOW AND HEAT TRANSFER IN A LAMINAR CHANNEL FLOW TWO-DIMENSIONAL FINITE ELEMENT ANALYSIS OF FORCED CONVECTION FLOW AND HEAT TRANSFER IN A LAMINAR CHANNEL FLOW Rajesh Khatri 1, 1 M.Tech Scholar, Department of Mechanical Engineering, S.A.T.I., vidisha

More information

Distinguished Professor George Washington University. Graw Hill

Distinguished Professor George Washington University. Graw Hill Mechanics of Fluids Fourth Edition Irving H. Shames Distinguished Professor George Washington University Graw Hill Boston Burr Ridge, IL Dubuque, IA Madison, Wl New York San Francisco St. Louis Bangkok

More information

Dimensional analysis is a method for reducing the number and complexity of experimental variables that affect a given physical phenomena.

Dimensional analysis is a method for reducing the number and complexity of experimental variables that affect a given physical phenomena. Dimensional Analysis and Similarity Dimensional analysis is very useful for planning, presentation, and interpretation of experimental data. As discussed previously, most practical fluid mechanics problems

More information

Introduction to CFD Analysis

Introduction to CFD Analysis Introduction to CFD Analysis Introductory FLUENT Training 2006 ANSYS, Inc. All rights reserved. 2006 ANSYS, Inc. All rights reserved. 2-2 What is CFD? Computational fluid dynamics (CFD) is the science

More information

NUMERICAL STUDY OF FLOW AND TURBULENCE THROUGH SUBMERGED VEGETATION

NUMERICAL STUDY OF FLOW AND TURBULENCE THROUGH SUBMERGED VEGETATION NUMERICAL STUDY OF FLOW AND TURBULENCE THROUGH SUBMERGED VEGETATION HYUNG SUK KIM (1), MOONHYEONG PARK (2), MOHAMED NABI (3) & ICHIRO KIMURA (4) (1) Korea Institute of Civil Engineering and Building Technology,

More information

Fundamentals of THERMAL-FLUID SCIENCES

Fundamentals of THERMAL-FLUID SCIENCES Fundamentals of THERMAL-FLUID SCIENCES THIRD EDITION YUNUS A. CENGEL ROBERT H. TURNER Department of Mechanical JOHN M. CIMBALA Me Graw Hill Higher Education Boston Burr Ridge, IL Dubuque, IA Madison, Wl

More information

The Viscosity of Fluids

The Viscosity of Fluids Experiment #11 The Viscosity of Fluids References: 1. Your first year physics textbook. 2. D. Tabor, Gases, Liquids and Solids: and Other States of Matter (Cambridge Press, 1991). 3. J.R. Van Wazer et

More information

Introduction to COMSOL. The Navier-Stokes Equations

Introduction to COMSOL. The Navier-Stokes Equations Flow Between Parallel Plates Modified from the COMSOL ChE Library module rev 10/13/08 Modified by Robert P. Hesketh, Chemical Engineering, Rowan University Fall 2008 Introduction to COMSOL The following

More information

Reynolds Stress Model for Hypersonic Flows

Reynolds Stress Model for Hypersonic Flows Reynolds Stress Model for Hypersonic Flows Von der Fakultät für Maschinenwesen der Rheinisch-Westfälischen Technischen Hochschule Aachen zur Erlangung des akademischen Grades einer Doktorin der Ingenieurwissenschaften

More information

Status quo of stress simulation for hot and warm work piece temperatures in forging

Status quo of stress simulation for hot and warm work piece temperatures in forging Status quo of stress simulation for hot and warm work piece temperatures in forging Dipl.-Ing. Johannes Knust, Dr.-Ing. Malte Stonis, Prof. Dr.-Ing. Bernd-Arno Behrens IPH - Institute of Integrated Production

More information

Diffusion and Fluid Flow

Diffusion and Fluid Flow Diffusion and Fluid Flow What determines the diffusion coefficient? What determines fluid flow? 1. Diffusion: Diffusion refers to the transport of substance against a concentration gradient. ΔS>0 Mass

More information

Customer Training Material. Lecture 5. Solver Settings ANSYS FLUENT. ANSYS, Inc. Proprietary 2010 ANSYS, Inc. All rights reserved.

Customer Training Material. Lecture 5. Solver Settings ANSYS FLUENT. ANSYS, Inc. Proprietary 2010 ANSYS, Inc. All rights reserved. Lecture 5 Solver Settings Introduction to ANSYS FLUENT L5-1 Solver Settings - Introduction So far we have looked at how to setup a basic flow simulation in FLUENT. However you should not assume that just

More information

A Study of the Influence of the Reynolds Number on Jet Self-Similarity Using Large-Eddy Simulation

A Study of the Influence of the Reynolds Number on Jet Self-Similarity Using Large-Eddy Simulation A Study of the Influence of the Reynolds Number on Jet Self-Similarity Using Large-Eddy Simulation Christophe Bogey 1 and Christophe Bailly 2 1 Laboratoire de Mécanique des Fluides et d Acoustique, UMR

More information

Gas Dynamics Prof. T. M. Muruganandam Department of Aerospace Engineering Indian Institute of Technology, Madras. Module No - 12 Lecture No - 25

Gas Dynamics Prof. T. M. Muruganandam Department of Aerospace Engineering Indian Institute of Technology, Madras. Module No - 12 Lecture No - 25 (Refer Slide Time: 00:22) Gas Dynamics Prof. T. M. Muruganandam Department of Aerospace Engineering Indian Institute of Technology, Madras Module No - 12 Lecture No - 25 Prandtl-Meyer Function, Numerical

More information

Science Standard Articulated by Grade Level Strand 5: Physical Science

Science Standard Articulated by Grade Level Strand 5: Physical Science Concept 1: Properties of Objects and Materials Classify objects and materials by their observable properties. Kindergarten Grade 1 Grade 2 Grade 3 Grade 4 PO 1. Identify the following observable properties

More information

Eco Pelmet Modelling and Assessment. CFD Based Study. Report Number 610.14351-R1D1. 13 January 2015

Eco Pelmet Modelling and Assessment. CFD Based Study. Report Number 610.14351-R1D1. 13 January 2015 EcoPelmet Pty Ltd c/- Geoff Hesford Engineering 45 Market Street FREMANTLE WA 6160 Version: Page 2 PREPARED BY: ABN 29 001 584 612 2 Lincoln Street Lane Cove NSW 2066 Australia (PO Box 176 Lane Cove NSW

More information

Electrochemical Kinetics ( Ref. :Bard and Faulkner, Oldham and Myland, Liebhafsky and Cairns) R f = k f * C A (2) R b = k b * C B (3)

Electrochemical Kinetics ( Ref. :Bard and Faulkner, Oldham and Myland, Liebhafsky and Cairns) R f = k f * C A (2) R b = k b * C B (3) Electrochemical Kinetics ( Ref. :Bard and Faulkner, Oldham and Myland, Liebhafsky and Cairns) 1. Background Consider the reaction given below: A B (1) If k f and k b are the rate constants of the forward

More information

Keywords: Heat transfer enhancement; staggered arrangement; Triangular Prism, Reynolds Number. 1. Introduction

Keywords: Heat transfer enhancement; staggered arrangement; Triangular Prism, Reynolds Number. 1. Introduction Heat transfer augmentation in rectangular channel using four triangular prisms arrange in staggered manner Manoj Kumar 1, Sunil Dhingra 2, Gurjeet Singh 3 1 Student, 2,3 Assistant Professor 1.2 Department

More information

4.3 Results... 27 4.3.1 Drained Conditions... 27 4.3.2 Undrained Conditions... 28 4.4 References... 30 4.5 Data Files... 30 5 Undrained Analysis of

4.3 Results... 27 4.3.1 Drained Conditions... 27 4.3.2 Undrained Conditions... 28 4.4 References... 30 4.5 Data Files... 30 5 Undrained Analysis of Table of Contents 1 One Dimensional Compression of a Finite Layer... 3 1.1 Problem Description... 3 1.1.1 Uniform Mesh... 3 1.1.2 Graded Mesh... 5 1.2 Analytical Solution... 6 1.3 Results... 6 1.3.1 Uniform

More information

The simulation of machine tools can be divided into two stages. In the first stage the mechanical behavior of a machine tool is simulated with FEM

The simulation of machine tools can be divided into two stages. In the first stage the mechanical behavior of a machine tool is simulated with FEM 1 The simulation of machine tools can be divided into two stages. In the first stage the mechanical behavior of a machine tool is simulated with FEM tools. The approach to this simulation is different

More information

NUMERICAL ANALYSES IN SIMILAR CONDITONS WITH COMBUSTION CHAMBERS OF RAMJET ENGINES

NUMERICAL ANALYSES IN SIMILAR CONDITONS WITH COMBUSTION CHAMBERS OF RAMJET ENGINES JESTECH, 15(4), 163-182, (2012) JESTECH NUMERICAL ANALYSES IN SIMILAR CONDITONS WITH COMBUSTION CHAMBERS OF RAMJET ENGINES Mehmet Altug Yavuz *, Ali Kodal ** * Technical Universtiy of Eindhoven, Physics

More information

Experimental Wind Turbine Aerodynamics Research @LANL

Experimental Wind Turbine Aerodynamics Research @LANL Experimental Wind Turbine Aerodynamics Research @LANL B. J. Balakumar, Los Alamos National Laboratory Acknowledgment: SuhasPol(Post-doc), John Hoffman, Mario Servin, Eduardo Granados (Summer students),

More information

How To Model An Ac Cloud

How To Model An Ac Cloud Development of an Elevated Mixed Layer Model for Parameterizing Altocumulus Cloud Layers S. Liu and S. K. Krueger Department of Meteorology University of Utah, Salt Lake City, Utah Introduction Altocumulus

More information

Interactive simulation of an ash cloud of the volcano Grímsvötn

Interactive simulation of an ash cloud of the volcano Grímsvötn Interactive simulation of an ash cloud of the volcano Grímsvötn 1 MATHEMATICAL BACKGROUND Simulating flows in the atmosphere, being part of CFD, is on of the research areas considered in the working group

More information

NUCLEAR ENERGY RESEARCH INITIATIVE

NUCLEAR ENERGY RESEARCH INITIATIVE NUCLEAR ENERGY RESEARCH INITIATIVE Experimental and CFD Analysis of Advanced Convective Cooling Systems PI: Victor M. Ugaz and Yassin A. Hassan, Texas Engineering Experiment Station Collaborators: None

More information

Physics 9e/Cutnell. correlated to the. College Board AP Physics 1 Course Objectives

Physics 9e/Cutnell. correlated to the. College Board AP Physics 1 Course Objectives Physics 9e/Cutnell correlated to the College Board AP Physics 1 Course Objectives Big Idea 1: Objects and systems have properties such as mass and charge. Systems may have internal structure. Enduring

More information

Plate waves in phononic crystals slabs

Plate waves in phononic crystals slabs Acoustics 8 Paris Plate waves in phononic crystals slabs J.-J. Chen and B. Bonello CNRS and Paris VI University, INSP - 14 rue de Lourmel, 7515 Paris, France chen99nju@gmail.com 41 Acoustics 8 Paris We

More information