Waste 2 Energy Labortory

Transcription

1 Weight ( %) Waste 2 Energy Labortory Prof. Isam Janajreh, Arnar, Fabian, Ilham, Rana, Liu, Syed, Mech. Eng. Program Main research activities Material Characterization: Proximate (TGA) Ultimate (CHNSO-Flash) Chemical Kinetics (TGA) Thermal properties: Bomb Cal/Cp(STA) Impurities (GC-MS, ICP) Species determination (Drop. Tube) von Mises Strain Temperature (C) Low Temp. Pathway: Transesterification Plastic recycling: -Decrossing-Extruding-Injection -Tensile testing &modeling/simulation 5 C/min 10 C/min 15 C/min 20 C/min Min=0.149 Max= von Mises Stress Min=35.0Mpa Max=165.5Mpa High Temp. high Temp. pathway: Incinerations/Combustion Pyrolysis (Buchi Reactor) Gasification (GEK)

2 WASTE 2 ENERGY: THERMOCHEMICAL PATHWAYS 1 st Arab-American Frontiers of Sciences, Engineering, and Medicine Symposium Kuwait Institute for Scientific Research * U.S. National Academies, October 17-19, 2011 in Kuwait City Outlines Overview, Challenges, Objectives Material characterization Proximate analysis Ultimate analysis Calorific value analysis Low fidelity simulation Equilibrium constant approach Gibbs energy minimization approach High fidelity simulation Reaction kinetics using Arrhenius equation Numerical simulation using CFD (Cold Flow Analysis) Numerical simulation using coupled CFD with Discrete particle in reactive flow Env. Wednesday, October 12, 2011

3 Overview : Advocating zero waste Country MSW Country MSW (Kg/person/day) (Kg/person/day) Bahrain 1.3 Austria 0.89 EU Belgium 0.93 India 0.45 Egypt 0.81 Italy 0.95 France 0.89 Japan 1.12 Jordan 0.6 Kuwait 1.4 Oman 0.7 Qatar 1.3 Portugal 0.7 Spain 0.88 Tunisia 0.41 UAE 1.2 Turkey US 2 UK 0.95 Type of Waste Thousands tons/year) Year Organics Fiber Wood Plastic Paper Glass Metal Others Total , , , ,661

4 Objectives: Provide sustainable routes to maximize resource utilization by converting waste to energy and Reduce MENA s emission foot print (CO2, NOX, SOX, CH4, etc) Fulfill the emerging stringent environmental regulations and reduce landfill deposits Promote IGCC as the cleanest and most efficient (50%) power generation technology amenable to CO 2 capturing Explore high temperature conversion including gasification and pyrolysis of waste stream into syngas Use trans and esterification of waste cooking and algae oil into biodiesel (2 nd and 3 rd Generation) Use fermentation processes to convert organic waste into bio-fuel and compost Clean Water Heat MSW* Gasification Syngas Waste Pre-treatment Homog. Ind. Waste Algae Culture Pyrolysis Oil Distillation P o Waste Oil Food/Organic Waste Trans-esterification Fermentation Glycerol Bio-diesel Phase-change Material Bio-fuel w e Composting r Waste Water Industry Waste Water Treatment Sludge Gray Water

5 To Gasify, or Not to Gasify? Definition: To convert carbonaceous solid material (CH x O y N z S m ) into a mixture of CO and H2 in an O2 deprived environment. Heat is provided by combusting part of the fuel. Gas cleaning CO shift and CO 2 removal CO 2 for storage H 2 CO Syngas Gas cooler Sulfur H 2 Stage 2: 2-4 burners O 2 CO 2 upper: Lean O 2 Syngas Gasifier O 2 Air Air Separation Unit Combustor N 2 Gas turbine Generator Electric Power C n H m O x Stage 1: 2-4 burners Advantages Slag CO 2, H 2 O - Control over produced energy Lower: Stoichiometric O 2 Ash Temperature, o C - Capability for carbon capture and storage. - Flexibility in feedstock and products. - Alternative to bury or burn policy. Coal T=1,000-1,500 C P=20-40bar Ash Steam Pump Heat recovery steam generator Steam turbine Condenser Generator Flue gas Electric Power - Hydrogen-based energy systems (near zero-co 2 emissions). - Small scale gasifiers for distributed generation. Gasification versus Combustion CO C CO 2 H 2 H H 2 O N 2 N No x H 2 S S SO x

6 To Gasify, or Not to Gasify? Challenges Current needs Physical aspect & technology challenges Feedstock flexibility Dynamic and intrinsic behavior Feedstock and char characterization proximate&ultimate analysis Modeling implementation Accurately models fuel switching and associated reactions Slag blockage/removal Downstream fouling and poisoning Wall/refractory failure Injector failure Space efficiency Turbulence-chemistry-radiation interactions Accurate Slag characterization Particle dispersion and inhomogeneous distribution Agglomeration, swelling and fragmentation particle mechanisms Nitrogen and sulfur production Particle dispersion and inhomogeneous heat distribution Turbulence-chemistry-radiation interactions Slag wall build up Turbulence-chemistry-radiation interactions Particle dispersion Turbulence-chemistry-radiation interactions Accurately models slag flow, composition and temperature distribution and turbulence Accurately flow modeling, conversion, ash distribution and pollutant formation Accurately model wall interactions, thermal stresses, pressure effects and abrasion Accurately model flow and temperature distribution Accurately model flow and conversion Cycle Fuel Temp low (oc) Temp High (oc) Carnot (h) Actual (h) Car(h)/Act(h)% Conventional Steam Power Plant Coal Ditto Ultra Super Critical Coal IGCC Coal Open Gas Turbine Cycle Gas Combined Cycle Gas Low Speed Marine Diesel (LSMD) Heavy Fuel Oil LSMD with Super Charger Heavy Fuel Oil

7 Material Characterization What does the feedstock compose of? Carbonaceous fuel is a complex collection of organic polymers consisting mainly of aromatic chains. Drying Pyrolysis Combustion Gasification

8 MATERIAL CHARACTERIZATION Proximate Analysis DSC/TGA curve of RTC-Coal with respect to time. Summary of the proximate analysis Composition Weight (%) Moisture Volatiles Fixed Carbon Ash Total 100 Simultaneous DSC/TGA Q600 Proximate analysis is used to calculate the weight percentage of moisture, volatiles, fixed carbon and Ash present in the sample. Wednesday, October 12, 2011

9 MATERIAL CHARACTERIZATION Ultimate analysis Sample ID Nitrogen Wt(%) Carbon Wt(%) Hydrogen Wt(%) Sulphur Wt(%) Oxygen Wt(%) Ash Balance Wt (%) Average Results of ultimate analysis for RTC-coal Flash 2000 CHNSO analyzer (TCD) Ultimate analysis is used to calculate the elemental composition of the sample Wednesday, October 12, 2011 Ultimate analysis Wt(%) Previous Wt(%) New Molar number Carbon normalization Nitrogen Carbon Hydrogen Sulfur Oxygen Total Empirical formula of RTC-coal using ultimate analysis C H O N0.0260

10 Atomic H/C Ratio Sample ID Calorific value analysis Weight (gms) HHV (MJ/Kg) Average HHV (MJ/Kg) Higher heating value of RTC-Coal HHV MJ Kg MATERIAL CHARACTERIZATION = 0.03 As 0.11 Moisture Volatiles Fixed Carbon HHV MJ Kg = C H S O N A Feedstock C %Wt H %Wt O %Wt N %Wt S %Wt RTC coal Pine needles Ply-wood Lignite Feedstock Empirical formula HHV KJ/Kmole HHV MJ/Kg RTC coal CH O N Pine needles CH O N Ply-wood CH O N Lignite CH O N Coal Anthracite Lignite Peat Biomass Pine needle & ply-wood Lignite RTC Coal Atomic O/C Ratio Parr 6100 Bomb calorimeter

11 Low Fidelity Model Can a zero dimensional model predict the gasifier performance? Simplest level of modeling. No dimension nor time is variable. Entrained flow gasifiers are amenable to equilibrium. Category Moving Bed Fluid Bed Entrained-Flow Ash condition Dry Ash Slagging Dry Ash Agglomerating Slagging Typical processes Lurgi BGL Winnkler, HTW, CFB KRW, U-Gas Shell, Texaco, E-Gas, Noell, KT Feed characteristics Size 6-50mm 6-50mm 6-10mm 6-10mm <100 m m Acceptability of fines Limitted Better than dry ash good better unlimitted Acceptability of caking coal yes (with stirrer) yes possibly yes yes Prefered coal rank any high low any any Operating characteristics l Outlet Gas Temperature low ( C) low ( C) moderate ( C) moderate ( C) high ( C) Oxidant demand low low moderate moderate high Steam demand high low moderate moderate low Other characteristics hydrocarbone in gas hydrocarbone in gas lower carbon lower carbon pure gas, high c conversion Source: Adapted from Simbeck et al. 1993

12 Kmole of product per Kmole of feedstock CGE(%) LOW FIDELITY SIMULATION Equilibrium constant approach Global Gasification reaction CH x O y N z + m O N 2 x 1 H 2 + x 2 CO + x 3 CO 2 + x 4 H 2 O + x 5 CH 4 + x 6 C + (z/ m) N 2 Elemental balance Carbon balance Hydrogen balance Oxygen balance Nitrogen balance Equilibrium constant equation For Bouduard reaction: C( s ) CO2 2 For CO shift reaction: CO H O CO For Methanation reaction: 2 CO CH Energy balance between reactant and product N i i _ prod1 n ( h Conversion Metrics o h ) Q CGE = x x x HHV feedstock Wednesday, October 12, 2011 s N i i _ react1 CO 2 2 H2 3 H O H 4 2 n ( h o h s ) Temperature (K)/1000 CH4 CGE Kmole of air input per Kmole of feedstock Equilibrium analysis for RTC coal showing CGE, Temperature and product gas composition C Maximum CGE 1530 K H2 CO H2O CO

13 Kmoles Temperature (K) PPM (mole) ΔG o fi + RT ln LOW FIDELITY SIMULATION Gibbs energy minimization approach t Gibbs Energy minimization using Lagrange : GT P g( n1, n2,..., n multiplier n i n total + λ k a ik k List of species considered in the model Species = 0, i = 1,2,, n C(g) CH CH 2 CH 3 CH 4 C 2 H 2 C 2 H 4 C 2 H 6 C 3 H 8 H H 2 O O 2 CO CO 2 OH H 2 O H 2 O 2 HCO HO 2 N N 2 NCO NH NH 2 NH 3 N 2 O NO NO 2 CN HCN HCNO S(g) S 2 (g) SO SO 2 SO 3 COS CS CS 2 HS H 2 S C(s) S(s) C(s) CO H 2 CO 2 Temperature (K) H 2 O, N CH Air ratio (Kmole/Kmole of RTC-coal) Air ratio (Kmole/Kmole of RTC-coal) ) NH 3 COS H 2 S CS 2 HCN SO 2 HS NO

14 Weight ( %) Heat flow (W) HIGH FIDELITY SIMULATION Reaction kinetics via Arrhenius equation Arrhenius Equation dx dt K(1 Integral method: Direct Arrhenius plot method: Method of approximate temperature integral: A and E can be used in high Fidelity simulation Wednesday, October 12, 2011 X ln(1 X ) E ln ln 2 T RT 1 n 1 x d ln P( u) du X T T 2 X T 1 T ) n ; E R A R E 1 T 2 1 b c u K A e ( E / RT) ln A Event 1 (drying/moisture release) METHODS: Event 2 (devolatization) INTEGRAL METHOD Temperature (C) 5 C/min 10 C/min 15 C/min 20 C/min Heat flow-10 C/min (W) Event 3 (Boudouard reaction/fixed carbon) DIRECT ARRHENIUS PLOT METHOD APPROX. TEMP. INTEGRAL METHOD Heating Rate Events E (KJ/mol) A (sec -1 ) E (KJ/mol) A (sec -1 ) E (KJ/mol) A (sec -1 ) Drying E E E K/min Devolatization E E E+02 Boudouard E E E+05 Drying E E E K/min Devolatization E E E+02 Boudouard E E E+06 Drying E E E K/min Devolatization E E E+02 Boudouard E E E+06 Drying E E E-02 5 K/min Devolatization E E E+02 Boudouard E E E

15 Inlet No slip Wall Symmetry (Axis) Out HIGH FIDELITY SIMULATION Coupled CFD and reaction kinetics Mathematical System: 1) Continuity, Momentum, Energy, TKE (k), TDR (e): ) ui) S t xi x i x i Time rate advective diffusion source 2) Transportation equation for m i species: t x x N i1 R i mi ) uimi ) Di, m mt / Sct ) Ri Si 3) Reaction kinetics: v i, r i, r S i k f, r kb, r M i i, r N i1 ( v v S i, r i, r Wednesday, October 12, 2011 i v i, r i ) k N *, rj C h j, r j1 ( E / RT) k Ae 4) Discrete Lagrangian particle: dup dxp FD u up ) g P ) P ; u p dt dt dmp ( E / RT) 0 0 Ae [ mp (1 fv ) mp] dt dtp dmp 4 mpcp hap ( T Tp) hfg e p Ap ( TR T dt dt 4 p m x ) i reductor diffuser throat (3) (2) combustor (1) D th D c 1.9 m 0.3 m 0.4 m 13 m The procedure (a) for the calculation (b) of pulverized feedstock conversion: Energy vol. 32 (2007) Pg Reductor (1) Combustor feedstock burner (2) Combustor char burner D (3) Reductor burner D th : throat diameter D c : combustor diameter (1.2 m) D swi : swirl diameter 13D D o Diffuser D swi Combustor Jet centerline Throat (a) Solve the continuous phase (b) Introduce and solve for the discrete phase (c) Recalculate the continuous phase flow, using the inter-phase exchange of momentum, heat, and mass determined during the previous particle calculation; (d) Recalculate the discrete phase trajectories in the modified continuous phase flow field; (e) Repeat the previous two steps until a convergence solution 1.6D D/4 D/3

16 HIGH FIDELITY SIMULATION Geometry & Mesh Generation Mesh Information Reductor Diffuser Throat D 1.6D Combustor D/4 Top view D/3 Figure 1: (a) 200t/d two-stage air blown gasifier and nozzle geometry showing blocking topology and the resulted 3D mesh. [Chen et al. and Bockelie et al] 13D Inputs Top view The 3D mesh consists of 1,427,896 finite volumes. Fitted within 30 volumes of surface sweep with appropriate axial scaling. Boundary layer adjacent to the gasifier refractory walls. Sufficient near-wall resolution to allow for wall-function rather than direct resolution (i.e. y + <20). Captures the exact gasifier topography.

17 Model Boundary and Operating Conditions Selected Model Parameters & Operating Conditions: Feedstock Composition Taiheiyo Bituminous Coal Ultimate (wt%) C 77.6 O 13.9 H 6.5 N 1.13 S 0.22 Proximate (wt%) FC 35.8 V 46.7 M 5.3 A 12.1 HHV (MJ/kg) 27.4 Gas flow rate (kg/s) Combustor burners Combustor burners Diffuser burners Particle loading (kg/s) Combustor burner Combustor burner Diffuser burner Wall Temperature (K) Combustor 1897 Diffuser 1073 Reductor 873 Pressure (MPa) 2.7 Turbulence Model K-e Standard Modeled Reactions:

18 Model Sample Results A B C Temperature field distribution. (a) Showing complete geometry. (b, C) Closer look at the combustor and diffuser. Average gasifier temperature = 1493 K

19 Model Sample Results a:t (K) b:co2 wt fraction c:h2o wt fraction d:co wt fraction e:h2 wt fraction

20 Model Sample Results a:t (K) b: Oxygen wt fraction c:velocity Magnitude (m/s) d: Volatiles wt fraction e: Char concentration (kg/s)

21 Model Sample Results Gasifier Height (m) Axial temperature and species profile along the center line of the gasifier. 0 Species % Mass fraction % Mole fraction CO H CO H 2 O CH Tar N Produced gas composition at gasifier exit. Particle temperature pathlines showing the effect of swirl.

22 What you need to know Gasification is making a strong comeback as sustainable energy source and efficiency enhancement. This technology can be deployed as renewable source for million of tons of waste streams disposed of at landfill and risking our ecological system. High fidelity analyses and simulations are needed at the conceptual level to increase the process efficiency and throughput.