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  • 1. Energy Technology & Innovation Initiative School Engineering Faculty ofof something FACULTY OF OTHER Optimisation of a gas-mixed anaerobic digester using a combined CFD and biochemical kinetic modelling approach International Conference on Advances in Energy Research 10-12th December 2013 Indian Institute of Technology Bombay Dr Mark Walker, Dr Lin Ma and Prof Mohamed Pourkashanian m.walker@leeds.ac.uk
  • 2. Introduction  Anaerobic Digestion (AD) is an attractive energy and waste management technology  At industrial scale AD plants consist of a mixed tank e.g. mechanical, gas, jet mixed  Small unmixed systems can digest a limited range of feedstocks  Mixing is parasitic to the energetic and economic feasibility of the biogas plant but allows a greater variety of substrates to be digester  Presented is a novel coupled CFD and AD model → optimisation of the mixing of based on biogas production  Mixing with biogas has low capital and operation cost relative to other mixing methods → potential to increase the efficiency of many thousands of small-scale digesters operated worldwide Mark Walker, ICAER, 10-12th December 2013, IITB
  • 3. Energy Technology & Innovation Initiative School Engineering Faculty ofof something FACULTY OF OTHER Model Description
  • 4. Modelling Scenario 14.7 m3 cylindrical tank Biogas recirculation Output digestate Biomass Biogas mixing Feedstock flow rate Biogas flow rate Working fluid (Digestate) Sparger Mark Walker, ICAER, 10-12th December 2013, IITB
  • 5. Geometry Free shear wall Geometry 1 Geometry 2 Draught tube Opening Gravity Geometry 1 Geometry 2 Mass inlet Gas sparger Ø 2.65 Ø 2.65 0.2 Ø 0.36 2.65 φ 0.2 1.325 2.65 Ø 0.2 Ø 0.2 1.325 1.325 0.2 Ø 0.3 Mark Walker, ICAER, 10-12th December 2013, IITB
  • 6. Model Structure     CFD  Laminar  Non-Newtonian  Multiphase (gas-liquid)  Steady Biochemical reactions  Contois kinetics  Microorganism (X) and 1 Substrate/Feedstock (S) Rheology  TS based formulation of nonNewtonian model parameters Non-Newtonian fluid (digestate)  Power law  Shear thinning/pseudoplastic Mark Walker, ICAER, 10-12th December 2013, IITB
  • 7. CSTR Model – Fully Mixed Q (m3 day-1) Biomass Inlet Conditions Xin = 0 Sin = Tsin = Q= Anaerobic Digester S, X Qbiogas Biogas Parameter Values V = 14.7 m3 β = 25 kg m-3 µm = 0.125 day-1 Ks = 12 Y = 0.1 α = 1 m3 kg-1 Initial Conditions S0 = 20 kg m-3 X0 = 5 kg m-3 Mark Walker, ICAER, 10-12th December 2013, IITB
  • 8. Model Comparison Phenomenon CFD + Contois Model Contois CSTR Model ✓✓ ✓ Hydraulic overload ✓✓ ✓ Microorganism growth kinetics ✓✓ ✓ Degree of Digestion ✓✓ ✓ Biogas Yield ✓✓ ✓ Effect of Mixing on other phenomena modelled ✓ ×× Short circuiting of biomass ✓ ×× Contact between microorganism and biomass ✓ ×× Other mixing related phenomena - Sedimentation, crust formation, foaming, gas entrainment, shear… × ×× Other biological phenomena - Organic overload, inhibition… × × CSTR Model Dilution/Washout - modelled (better) - modelled - not modelled - cannot be modelled Mark Walker, ICAER, 10-12th December 2013, IITB
  • 9. Energy Technology & Innovation Initiative School Engineering Faculty ofof something FACULTY OF OTHER Results and Discussion
  • 10. Results and Discussion TS Distributions G1 Increasing mixing flow rate 0 0.01 0.1 1 Approx. mixing energy (W m-3) 10 G2 Mark Walker, ICAER, 10-12th December 2013, IITB
  • 11. Results and Discussion Biogas Production  Compared with CSTR model and no mixing  Large process gain by a small mixing flow rate (x10+)  Above a threshold mixing rate system begins to act as a CSTR  G1 threshold lower than G2  Optimal mixing rate in G1 ~ 0.02 W m-3 (G1)  Slight predicted process gain by using threshold mixing (+1.8%)
  • 12. Discussion  Despite potential applications that this type of model requires further development and is not fully validated. Relevant input data would be required before the model could be used reliably in a predictive capacity  Validation;  Model converges to a CSTR model at higher mixing rates  The sub-models used have all been previously validated  Some issues regarding applicability of input data;  The rheological data did not span the expected strain rates found in anaerobic digesters  Contois parameters based on household solid waste, rheological data from cattle slurry  Model optimisation only addresses a subset of the phenomena relating to mixing in anaerobic digestion and does not account for;  Temperature and pH distribution  physical stratification through sedimentation  Foaming and gas entrainment  effect of shear on the microorganisms Mark Walker, ICAER, 10-12th December 2013, IITB
  • 13. Conclusion  3D coupled CFD and AD model developed  Optimisation of the biogas mixing of two idealised digester designs for biogas production and biomass degradation  An increase in biogas production from 2.6 to 33 m3 day-1 was predicted by the introduction of mixing (0.02 W m-3)  Potential applications include enhancing the design and operational characteristics of biogas plants  The model was partly validated using comparison with a CSTR case  For reliable predicative modelling more comprehensive biochemical and rheological data specific would be needed  The model does not include some of the phenomena relating to the mixing of anaerobic digesters Mark Walker, ICAER, 10-12th December 2013, IITB
  • 14. Energy Technology & Innovation Initiative School Engineering Faculty ofof something FACULTY OF OTHER Thank you! Any questions?