Anaerobic Digestion Model with Multi- Dimensional Architecture (ADM-MDA) Ph.D. Candidacy exam David L. F. Gaden

Transcription

1 Anaerobic Digestion Model with Multi- Dimensional Architecture (ADM-MDA) Ph.D. Candidacy exam David L. F. Gaden

2 Introduction Problem Proposed solution Literature review Methodology Code development Results Tasks remaining Outline

3 What is anaerobic digestion? The breaking down of biomass in the absence of oxygen Treats waste products while simultaneously producing renewable energy (biogas) Primary purpose: Waste treatment Energy production Pollution reduction Odour mitigation Introduction

4 Applications Industrial wastewater treatment Municipal wastewater treatment Agricultural wastewater treatment Introduction

5 Stages of anaerobic digestion 1. Disintegration Introduction

6 Stages of anaerobic digestion 2. Hydrolysis Introduction

7 Stages of anaerobic digestion 3. Acidogenesis Introduction

8 Stages of anaerobic digestion 4. Acetogenesis Introduction

9 Stages of anaerobic digestion 5. Methanogenesis Introduction

10 Types of digesters Biogas Influent Effluent Plug flow digester Introduction

11 Types of digesters Biogas Influent Effluent STR digester Introduction

12 Types of digesters Biogas Effluent Influent Introduction Upflow anaerobic sludge blanket digester

13 Types of digesters Effluent Biogas Influent Introduction Anaerobic clarigester

14 Reliability issues Unreliable Well established Problem

15 Modelling anaerobic digesters Current state of the art is ADM1: Batstone, D. J.; Keller, J.; Angelidaki, I.; Kalyuzhni, S. V.; Pavlostathis, S. G.; Rozzi, A.; Sanders, W. T. M.; Siegrist, H.; Vavlin, V. A "Anaerobic Digester Model No.1 (ADM1)", Scientific and Technical Report No.13, IWA Task Group for Mathematical Modelling of Anaerobic Digestion Processes. IWA Publishing, London, United Kingdom. Rosen, C.; Jeppsson, U Aspects on ADM1 implementation within the BSM2 framework, Technical Report No. LUTEDX/(TEIE- 7224)/1-35/(2006). Department of Industrial Electrical Engineering and Automation, Lund University, Lund, Sweden. Problem

16 Blumensaat, F.; Keller, J "Modelling of two-stage anaerobic digestion using the IWA Anaerobic Digestion Model No. 1 (ADM1)," Water Research, v. 39, pp Problem

17 Ozkan-Yucel, U. G.; Gökçay, C. F "Application of ADM1 model to a full-scale anaerobic digester under dynamic organic loading conditions," Environment Technology, v. 31, n. 6, pp Problem

18 Modelling anaerobic digesters Current state of the art is ADM1: A bulk model o No spatial variation S x S y S z 0 o Uniform properties Problem

19 Objective: a spatially-resolved ADM1 ADM-MDA Anaerobic Digestion Model with Multi-Dimensional Architecture Proposed solution

20 Gas volume S gas,var (3) Q gas Liquid volume S var (21) X var (12) Q liq Qliq Methodology Theory ADM1

21 dm dt var m var in m var out m,, var, reac ds dt var V liq QliqS var, in QliqS var, out V liq r var ds dt var V Q liq liq S var, in S var r var Methodology Theory ADM1

22 Methodology Theory ADM1

23 rs su k X 1 hyd, ch ch f fa, li k hyd, li X li Methodology Theory ADM1

24 S su X pr S va S hva S bu S hbu S h+ S oh- S aa X li S va- S bu- ph S fa S ch4 X su X aa S ac S hac S IC S CO2 S pro S hpro S h2 X fa S ac- S HCO3- S pro- S I S cat S an X c4 X pro X ac S IN S NH4+ S NH3 ODE variables Derived variables X c X h2 S gas,h2 p gas,h2 X ch X I S gas,ch4 S gas,co2 p gas,ch4 p gas,total Q gas p gas,co2 Methodology Theory ADM1

25 S su X pr S va S hva S bu S hbu S h+ S oh- S aa X li S va- S bu- ph S fa S ch4 X su X aa S ac S hac S IC S CO2 S pro S hpro S h2 X fa S ac- S HCO3- S pro- S I S cat S an X c4 X pro X ac S IN S NH3 S NH4+ ODE variables Derived variables Algebraic variables X c X h2 S gas,h2 p gas,h2 X ch X I S gas,ch4 S gas,co2 p gas,ch4 p gas,total Q gas p gas,co2 Methodology Theory ADM1

26 Governing equations: Conservation of mass: U 0 Conservation of momentum: DU 2 p U ref T T ref Dt Conservation of energy: T t UT T 0 Methodology Theory - CFD

27 Two options: 1. Start with ADM1 and write CFD into it; or 2. Start with CFD and write ADM1 into it. ODE: ds dt var V Q liq liq S var, in S var r var PDE: S t var US var S var r var Methodology Theory ADM-MDA

28 Three biochemistry strategies: 1. Source term solver 2. ODE solver 3. Coupled solver Methodology Theory ADM-MDA

29 Three biochemistry strategies: 1. Source term solver S t var ds dt var US V Q liq liq var S var, in S var S var r r var var Methodology Theory ADM-MDA

30 Three biochemistry strategies: 2. ODE solver Transport variables (CFD) Solve biochemistry (ODE) Methodology Theory ADM-MDA

31 Three biochemistry strategies: 3. Coupled solver Methodology Theory ADM-MDA

32 Three biochemistry strategies: 3. Coupled solver Methodology Theory ADM-MDA

33 Boundary conditions change Time scale issue ADM1: CFD: dt 15 min dt 1s Transient solver (flow) multisolver Steady state solver (biochemistry) Methodology Theory ADM-MDA

34 Length scale issue Prolongation ADM1 Restriction CFD dualgrid Methodology Theory ADM-MDA

35 Accessibility equationreader The ability to read equations from a text file Methodology Theory ADM-MDA

36 Steady state solver Transient solver PISO RANS turbulence Temperature Scalar transport Non-Newtonian Buoyancy Particle model Steady state detection Control multisolver dualgrid equationreader Framework Flow Scalar transport Particle model Gas model Biochemistry ODE solver Implicit solver (S h2 ) Implicit solver (ions) Code development

37 Steady state solver Transient solver PISO RANS turbulence Temperature Control Flow Scalar transport Particle model Gas model? Scalar transport Non-Newtonian Buoyancy Particle model Steady state detection? multisolver dualgrid equationreader Framework Biochemistry ODE solver Implicit solver (S h2 ) Implicit solver (ions) Code development

38 Steady state solver Transient solver PISO RANS turbulence Temperature Control Flow Scalar transport Particle model Gas model? Scalar transport Non-Newtonian Buoyancy Particle model Steady state detection? multisolver dualgrid equationreader Framework Biochemistry ODE solver Implicit solver (S h2 ) Implicit solver (ions) Code development

39

40 Bulk model Written in Excel + Visual Basic macros Post processing routines Instantly produce comparisons between bulk model & ADM-MDA Written in Python Code development

41 Results Bulk model verification

42 Boussinesq buoyancy model validation Results

43 Two problems with the model: Efficiency Transport deviation Results

44 (1000 cells, 1000 days) Change Simulation Time Real Time Benchmark Estimate Initial 27 [s] 6 [hr] >100,000 [yr] Results

45 = + S S S trans trans r 0 trans r 0 Results

46 (1000 cells, 1000 days) Change Simulation Time Real Time Benchmark Estimate Initial 27 [s] 6 [hr] >100,000 [yr] Segregated flow 1 [dy] 18 [hr] 128 [yr] Results

47 Semi-implicit Bulirsch Stoer ddt Solve derived ODE ddt Implicit S h2 solver Implicit ion solver innerloops Results

48 (1000 cells, 1000 days) Change Simulation Time Real Time Benchmark Estimate Initial 27 [s] 6 [hr] >100,000 [yr] Segregated flow Inner loops 1 [dy] 18 [hr] 128 [yr] 1 [dy] 100 [dy] 12 [min] 5:32[hr:min] 144 [dy] Results

49 Results

50 (1000 cells, 1000 days) Change Simulation Time Real Time Benchmark Estimate Initial 27 [s] 6 [hr] >100,000 [yr] Segregated flow Inner loops 1 [dy] 18 [hr] 128 [yr] 1 [dy] 100 [dy] 12 [min] 5:32[hr:min] 144 [dy] Static yields 1 [dy] 62 [s] 12.5 [dy] Results

51 Results

52 (1000 cells, 1000 days) Change Simulation Time Real Time Benchmark Estimate Initial 27 [s] 6 [hr] >100,000 [yr] Segregated flow Inner loops 1 [dy] 18 [hr] 128 [yr] 1 [dy] 100 [dy] 12 [min] 5:32[hr:min] 144 [dy] Static yields 1 [dy] 62 [s] 12.5 [dy] Function Pointers 1[dy] 100 [dy] 58 [s] 7 [min] 3.17 [dy] The solver is now parallelized! Results

53 1 day (with flow) Results

54 100 days (with flow) Results

55 100 days (no flow) Results

56 Quad precision Pseudo-coupled solver Mini timesteps for transport Improve ADM1 numerical stability Averaged noisy transport Agglomeration Transport Error

57 Timeline

58 Judgement day... (May 21 st ) Solve transport error... (June 1 st ) Gas model... (June 22 nd ) Particle model... (July 15 th ) Dual-grid... (August 1 st ) Validate model... (Octobruary 15 th ) Write thesis... (Novembgust 30 th ) Timeline