PRESENTATION SLIDES: Analytical Multi-Scale Methodology for Fluidization Systems - Retrospect and Prospect

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1 Refereed Proceedings The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering Engineering Conferences International Year 07 PRESENTATION SLIDES: Analytical Multi-Scale Methodology for Fluidization Syems - Retrospect and Prospect Jinghai Li Initute of Process Engineering Chinese Academy of Sciences, Beijing, jhli@home.ipe.ac.cn This paper is poed at ECI Digital Archives. xii/129

2 Li: Analytical Multi-Scale Methodology for Fluidization Syems Fluidization XII Challenge Analytical Multi-Scale Methodology for Fluidization ---- from a simple idea to indurial application Jinghai Li, Wei Ge, Jiayuan Zhang, Shiqiu Gao Wei Wang, Ning Yang, Qicheng Sun & Jian Gao National Key Laboratory of Multi phase Complex Syems Initute of Process Engineering, Chinese Academy of Sciences P. O. Box 353, Beijing 0080, P. R. China May 15, 07 1 Strategy Progress Conclusion Verification Solution Extension Application Limitation CFD Indury Future 2 1. Structure Heterogeneity Local Axial / Radial Challenge State Multiplicity 3. Scale-up Effect Jump Change (choking) With slight change of operation condition Co-exience At a critical condition Under the same operating conditions 5 6 Published by ECI Digital Archives, 07 11

3 The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 129 [07] 4. Critical influence of ructural changes on transport and reaction Structural influences on transport properties Meso-scale cluers C do Heterogeneity influence C d = C do Orientation influence C d =15.4 C do Local C D = 18.6 C D = 5.43 Local & Radial C D = 2.85 Same Volume of unit Number of particles Gas flow rate 7 8 Structural influences on transport properties Drag coefficients in different phases Challenge: Spatial Spatial-temporal temporal Multi- Scale Structure Dense-phase: C Dc 5 Interface: C Di < Dilute-phase: C Df 0 Interdependent How to formulate? What is the mechanism? What happens at meso-scale? scale? Key/Focus: Correlation and inter- dependence between different scales 9 Strategy Reductionism Holism Dependence between scales Average Dense-phase: Particle-doated Interface: Particle-fluid compromise Dilute-phase: Fluid-doated Heterogeneity Multi-Scale Multi-Physics Linear Non-linear d cl

4 Li: Analytical Multi-Scale Methodology for Fluidization Syems Descriptive Complex syem Correlative Complex syem Resolution Resolution Modeling With respect to scales Scale 1Scale 2... Scale n Modeling With respect to scales Scale 1Scale 2... Scale n Description of individual scales Description of individual scales Correlation between scales No correlation between scales 13 Lower scale Higher scale Closure without ability 14 Analytical (Variational) Modeling Complex syem Resolution With respect to scales Scale 1 Scale 2... Scale n Description of individual scales Correlation between scales With respect to doant mechs. Mech. 1 Mech. 2 Mech. k Identification of extremum tendencies of each doant mechanisms and their compromise Stability Insufficiency of conservation equations: Gas velocity U c Solid velocity U dc Dense phase Voidage ε c Volume fraction f Cluer diameter d cl 8 Variables Gas velocity U f Dilute phase Solid velocity U df Voidage ε f Particle-scale: in dense-phase in dilute-phase Cluer-scale 6 equations Stability? Closure with ability condition between doant mechanisms particle fluid Physical Concept of EMMS Model Dense phase Dilute phase Gas velocity Solid velocity U c U dc Energy-imization multi-scale Voidage ε c Volume fraction f Cluer diameter d cl 8 Variables 6 equations Gas velocity U f Solid velocity U df Voidage ε f Particle-scale: in dense-phase between doant mechanisms EMMS model Particle-doated ε = Particle-fluid compromising W = ε = Fluid-doated W = In dilute-phase Cluer-scale Correlation Stability? between scales Stability Condition: W N = = ( 1-ερ ) 17 Operating Conditions W = ε= N = 18 Published by ECI Digital Archives, 07 33

5 The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 129 [07] Mathematical Formulation To find:x={ U dc, U c, ε c, f, d cl, U df, U f, ε f } W Minimizing: N = (1- ε ) ρ s.t. F i (X)=0 F1 ( X) = mcfcf + mf i i f(1 ε c)( ρp ρf ) g = 0 F2 ( X) = mfff (1 ε f )( ρp ρ f ) g = 0 F3 ( X) = mfff + mf i i /(1 f) mcfc = 0 F4 ( X) = U U (1 f) U f = 0 p pf pc F ( X) = U U (1 f) U f = 0 5 g f c U U ε p p mf d ( ) p U + mf g 1 ε 1 ε max mf F6 ( X) = dcl = 0 ρ U ε p p mf N ( U + ) g ρ ρ 1 ε mf p f mf 19 Summary of the rategy: Applying the multi-scale method to udy the ability condition of complex syems by analyzing the compromise between doant mechanisms and correlation between different scales. Progress Verification Solution Extension Application Limitation 21 Roadmap: PetroChina Extension N = verification & Idea model method software indury SINOPEC Baoeel CFD Upgrading Studied Two-phase Turbulence Three phase N = verified 04 Granular flow Studying Emulsion Foam To be udied : Nano-ructure Catalysis Biological syem To be generalized Mathematics Physics 22 N =? Verification Whether or not? If yes, why? Stability criterion Equilibrium: Max. Entropy Non-Equilibrium Fluidization Verification Linear: Min. Entropy Production Non-linear: No theory available Impossible Possible: Discrete simulation

6 Time (s) p V Li: Analytical Multi-Scale Methodology for Fluidization Syems Pseudo-Particle Particle Strategy Objective Particles Gas Pseudo-particles Micro-scale description Macro-scale phenomena Generating meso-scale ructure with micro-phenomena: Solid particle 24 CPUs + PPM 24 particles Fluid (Pseudo-particles) Ge & Li: CFB5, 1996; Chem. Eng. Sci., 58, 03, Ma et al., Chem. Eng. Sci., 61(21), 06, N was verified N (J/(kg.s)) N (J/(kg.s)) Point A Point B W = temporal compromise (at any single point) regional ε = compromise spatial compromise (at any single inant) W= N (J/(kg.s)) N Region D N Time (s) W = = (1 ε) ρ global compromise N (J/(kg.s)) N Time (s) ε ) V 1 ( 1 ) d ε (v) N N v = = (v) (1 Solution Region D Fluid Particle-Fluid Syems Time (s) Local (micro-scale) ructure: Point A & B EMMS model Meso-scale ructure: Region D Radial EMMS model Global (macro-scale) ructure: Li et al., China Particuology, 05, 3, From complicated to simple 1988, Non-linear optimization program (difficult to use) 1998, Analytical solution (complicated) 02, Complete solution (simple and available from internet): 8 variables 6 equations searching in the parameter space N = Solutions ε c ε f ε c Dense only (ε f -ε c )/(ε max -ε c ) ε c Dense/Dilute Coexience U g =3.4m/s N =0.747(blue)~1(red) two roots at right top and right bottom (ε f -ε c )/(ε max -ε c ) Local ructural parameters Regime diagram Choking definition Radial and axial diribution ε c Dilute only (ε f -ε c )/(ε max -ε c ) Published by ECI Digital Archives, 07 55

7 surf surf The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 129 [07] Extension 1: Turbulent Flow between Viscosity and Inertia Extension to 6 different syems Viscosity W ν Point A temporal compromise W ν (at any point) Wν Wte spatial compromise Time ep (at any inant) Point B Wν Wte W te Inertia W te max Time ep Point A & B W v, W te fluctuating W v / W te Extension 2: Gas-Liquid Bubbly Flow between movement tendencies of bubbles and liquid Extension 3: Microemulsion Between Hydrophile and Lipophile Point A Region C 30 Point A E OH = Region C Surface tension N surf Point B N = N turb = Temporal (at any point) Spatial compromise (at any inant) Hydrophile EOH x 5 4x 5 5x 5 E WT = E OH = temporal compromise (at any single point) spatial compromise (at any single inant) x 5 4.0x 5 E = EWT + EOH repulse Viscosity Nturb Gas Point A & B N = N = Nsurf + Nturb N surf+turb fluctuating N surf+turb Lipophile EWT 3x 5 4x 5 5x 5 Point B Point A & B Region C E WT, E OH fluctuating E repulse 33 Denotations H: Hydrophile group (red) T: Lipophile group (blue) W: Water (green) O: Oil (yellow) 34 Extension 4: Granular Flow Between Two Streams of Granular Flow Extension 5: Foam Drainage Between Surface Energy and Viscosity Point A Stream a doant Stream b doant Fa Fb Fb H b H a Ha= temporal compromise (at any single point) Point B t Point A & B Hb= spatial compromise (at any single inant) Ha= ( Ha+Hb ) H a, H b fluctuating H a +H b H a +H b t Surface energy Es Viscous dissipation E μ Liquid E s / E μ E s / E μ Point A Time ep Point B Time ep Point A & B temporal compromise (at any single point) spatial compromise (at any single inant) E S, E μ fluctuating E s /E μ E s /E μ Time ep

8 surf OH Li: Analytical Multi-Scale Methodology for Fluidization Syems Extension 6: Nano Gas-liquid Flow Between Interfacial potential and Viscosity Summary: 1. Syems 2. Doant mechanisms 3. Local extremum exience indication 4. Global extremum exience indication Interfacial potential tends to imum S Flow dissipation tends to imum ϕ r Cross flow of granular materials Turbulent flow Gas-solid syem Turbulent gas-liquid flow Nano gas-liquid pipe flow Foam drainage Definition Definition ( H a = ) H b= H --- potential a a H b --- potential b ( W ν = ) W te=max W ν W te --- viscous dissipation --- turbulent dissipation ( W = ) ε = W --- volume specific energy consumption for transporting and Definition suspending particles ε--- local voidage of the identified area ( N turb = ) N = Nturb --- dissipation liquid in the Definition turbulent Nsurf --- surface dissipation ( ϕ r = ) S= ϕ --- dissipation associated with the r transportation of unit amount of Definition kinetic energy across unit length S --- surface energy in the syem ( E = s ) Eμ = E --- surface energy s Definition E --- viscous dissipation μ No No No No No No Yes Yes Yes Yes Yes Yes 37 Emulsion Definition ( E WT = ) E = EWT --- lipophilic potential EOH --- hydrophilic potential No Yes 38 between doant mechanisms Analytical Multi-scale Methodology Generality? Gas-solid syem Turbulence Gas-liquid syem Granular flow Emulsion Foam drainage Extremum tendency of mechanism 1 Particle Fluid Viscosity Inertia Surface tension Viscosity Stream A Stream B Hydrophile Lipophile Surface energy Viscous dissipation Extremum tendency of mechanism 2 39 Application verification modification Modeling Complex syem Resolution With respect to scales Scale 1 Scale 2... Scale n Description of individual scales Correlation between scales With respect to doant mechs. Mech. 1 Mech. 2 Mech. k Identification of extremum tendencies of each doant mechanisms and their compromise ability 40 Mathematical model of complex syems in general Multi-objective variational problem X = { x 1, x 2,, x n } E j (X) E k (X) s.t. F i (X)=0, i=1, 2,, m Applications in CFD J. Li et al., Chem. Eng. Sci., 03, 58, Published by ECI Digital Archives, 07 77

9 The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 129 [07] Computer capacity: dramatic increase CFD computation capability: gradual progress Mesh improvement FLUENT 2 Orthogonal FLUENT 4 Structured FLUENT 5 Tetrahedral FLUENT 6.3 Polyhedral :Vax 11/780 6 flops 7 times 05: Dawning flops Conitutive models K -ε KTGF DPM SGS VOF + LES 43 Adapted from T. Gessner et al., WCCM 06, Fluent Inc. & Fluent User Manuals 44 Why Computation capability is far behind computer capacity? Heterogeneity in a control volume! What is the key problem? Multi-scale CFD: Problem: average C D Two-fluid models Current Softwares FLUENT CFX PHOENICS Missing meso-ructure Start Local parameters Average approach C d for local cells Final EMMS C D considering ructure EMMS Structure parameters & acceleration 47 N. Yang et al., Chem. Eng. J., 03, 96,

10 Wen & Yu/Ergun EMMS Experimental Time (s) 26 粒子方法 割MD 等区域分解 PPM 边界条件处理 粒子生成 CAD 图形转换 AUTOCAD SPH DPD DEM 元胞列表 + 邻居列表 算 粒子类 动态负载平衡 法 数据结构 边界类 MaPPM 区域分解 通信模式 作用函数类 组织管理类通信类辅助类库 MPI STL Loki 计算与通信部分Li: Analytical Multi-Scale Methodology for Fluidization Syems Reproduced meso-scale ructures Solid output flux Simulation Output solid flux (kg/m 2 s) EMMS+CFD Output solid flux (kg/m 2 s) Empirical correlations+cfd Experimental Simulation Experimental Time (s) Time (s) CFX Only CFX + EMMS CFX CFX + EMMS Fluent Fluent + EMMS Yang, et al., Chem.Eng.J.,96, 03, 71 Wang, et al., Chem.Eng.Sci., 62, 07, Coexience of dilute and dense regions in a CFB riser Regime transition: Choking prediction 8 8 A B Height (m) 6 4 Height (m) 6 4 Experiments Voidage Voidage CFX Only CFX + EMMS CFD + EMMS Yang, et al., Ind. Eng. Chem. Res., 43, 04, 5548 Gidaspow & coworkers, Chem. Eng. Sci., 61, 06, 5544 Simulation Wang, et al., Chem.Eng.Sci., 62, 07, CFD + EMMS: software development Commercial Codes Interface: UDFs Software (regiered) EMMS/Global EMMS/Matrix EMMS/Axial. Spatial & temporal Flow in each grid 53 EMMS 软件包 物性参数结构参数操作条件 Computation platform 参数总体分布 新型计算流体力学方法 Outlet solid flux (kg/m 2s) Chem. Eng. J. 03, 96: I&EC Res. 04, 43: EMMS CFD+EMMS Particle Method CFX only CFX + EMMS 粒子方法通用软件平台的总体结构 据分处理数等负载分解构形前54 Published by ECI Digital Archives, 07 99

11 The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 129 [07] Software EMMS EMMS software package at website ( EMMS software package for calculating the axial and radial diribution of solid concentration, solid velocity and gas velocity in CFB Software EMMS+CFD Input window Input Interface Output figures Output tables Output Interface Bayer: Pressure profile in boiler Applications to induries height height pressure pressure a) CFB boiler b) EMMS calculation c) On site plant data printout SINOPEC Stage 1 : MIP (max. iso-paraffins paraffins) ) process SINOPEC Stage 2 : Further optimization of MIP process Novel FCC Riser Height: 40 m Diameter m Detere design parameter Diameter velocity Inventory Shade of color: concentration

12 Li: Analytical Multi-Scale Methodology for Fluidization Syems SINOPEC: the influence of orifice number SINOPEC: the influence of diributor shape 98 orifices 169 orifices 390 orifices Arc-shaped Basin-shaped Cone-shaped SINOPEC: the influence of outlets SINOPEC: CFB Boiler (Wuhan) 2500 Pressure drop (Pa/m) modeling measurement Height (m) 1.0 Relative solid concentration modeling measurement Upright outlet Sideward outlet Relative diance from the wall PetroChina: slurry bed loop reactor Baoeel: Simulation of ore preparation for Before optimization After optimization 65 Zhang et al. (04), Ind. & Eng. Chem. Res. 43: Published by ECI Digital Archives,

13 The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 129 [07] Common focus of chemiry and process engineering Applications in future Relative importance Chemiry Structure of Apatite Sphere Reaction - doated Reaction Structure Function Diffusiondoated H. Zhang et al., Chem. Mater., 05, 17, Transfer Properties Structure of Cu 2 O Chemical Engineering Reaction control Diffusion control 69 Qingshan Zhu s group, Initute of Process Engineering, CAS 70 Multi-scale mass transfer Comparison between CFD computation and experiments (Ouyang et al., 1995, AIChE J.) Meso-scale Averaged flow & averaged mass transfer Multi-scale flow & Averaged mass transfer Multi-scale flow multi-scale mass transfer Sh atic Sh dynamic c/c 0 c/c 0 c/c 0 r/r 0 r/r 0 r/r 0 Micro-scale Sh dilute Sh dense Multi-scale Structure-dependent Sh c/c 0 r/r 0 c/c 0 r/r 0 c/c 0 r/r

14 p s p Li: Analytical Multi-Scale Methodology for Fluidization Syems Limitation of the EMMS model: Limitations & Difficulties Dense phase Dilute phase Gas velocity U dc Solid velocity U c Voidage ε c Volume fraction f Cluer diameter d cl Gas velocity U df Solid velocity U f Voidage ε f Dense-phase: Particle-doated C Dc 5 8 Variables 6 equations between doant mechanisms EMMS model Interface: Particle-fluid compromise C Di < Correlation between scales U g G U = ρ Dilute-phase: Fluid-doated C Df 0 Stability Condition: W = ε= N = 73 Operating Conditions 74 Applicability of ability condition 2.5x -3 No, at local point 2.0x -3 A 1.5x -3 B N =? how big volume? σ N 1.0x -3 C 5.0x -4 D E F G Yes, at big volume L/D 76 Two-fluid: Conitutive model Multi-scale: Cluer diameter Discrete: Micro-mechanisms No be! But all useful! Individual Integration!! Conclusions Focus: Spatio-temporal multi-scale ructure Umbrella: Complex syems Methodology: Multi-scale method Tool: Computer simulation Nano-technology Highlights Material science Syems biology Published by ECI Digital Archives,

15 The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 129 [07] Acknowledgement Financial support NSFC (Natural Science Foundation of China) Prof. Mooson Kwauk and Coworkers Thank you! MOST (Miniry of Science and Technology) CAS (Chinese Academy of Sciences) ETH (Swiss Federal Initute of Technology) AvH (Alexander von Humboldt Foundation)