Anaerobic Digestion Model with Multi-Dimensional Architecture (ADM-MDA)

Ph.D. Candidacy exam2011-04-27

David L. F. Gaden

Outline

Introduction

Problem

Proposed solution

Literature review

Methodology

Code development

Results

Tasks remaining

Introduction

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

Applications◦ Industrial wastewater treatment

◦ Municipal wastewater treatment

◦ Agricultural wastewater treatment

Introduction

Stages of anaerobic digestion

1. Disintegration

Introduction

Stages of anaerobic digestion

2. Hydrolysis

Introduction

Stages of anaerobic digestion

3. Acidogenesis

Introduction

Stages of anaerobic digestion

4. Acetogenesis

Introduction

Stages of anaerobic digestion

5. Methanogenesis

Introduction

Types of digesters

Influent Effluent

Biogas

Plug flow digester

Introduction

Types of digesters

Influent

Effluent

Biogas

STR digester

Introduction

Types of digesters

Influent

Effluent

Biogas

Upflow anaerobic sludge blanket digester

Introduction

Types of digesters

Influent

Effluent Biogas

Anaerobic clarigester

Problem

Reliability issues

Unreliable

Well established

Problem

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.. 2002. "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.. 2006. “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

Blumensaat, F.; Keller, J.. 2005. "Modelling of two-stage anaerobic digestion using the IWA Anaerobic Digestion Model No. 1 (ADM1)," Water Research, v. 39, pp. 171-183.

Problem

Ozkan-Yucel, U. G.; Gökçay, C. F.. 2010. "Application of ADM1 model to a full-scale anaerobic digester under dynamic organic loading conditions," Environment Technology, v. 31, n. 6, pp. 633-640.

Problem

Modelling anaerobic digesters◦ Current state of the art is ADM1:

◦ A bulk model

0z

S

y

S

x

S

o No spatial variation

o Uniform properties

Proposed solution

Objective: a spatially-resolved ADM1

ADM-MDA – Anaerobic Digestion Model with Multi-Dimensional Architecture

Methodology – Theory – ADM1

Liquid volume

Gas volume

Sgas,var (3)

Svar (21)Xvar (12)

Qliq

Qliq

Qgas

Methodology – Theory – ADM1

reacvaroutvarinvarvar mmm

dt

dm,,,

varliqoutvarliqinvarliqvar

liq rVSQSQdt

dSV ,,

varvarinvar

liq

liqvar rSSQ

V

dt

dS,

Methodology – Theory – ADM1

Methodology – Theory – ADM1

lilihydlifachchhydS XkfXkrsu ,,, 1

Methodology – Theory – ADM1

Ssu

Saa

Sfa

Sch4

Sh2

SI

Scat

San

Xc

Xch

Xpr

Xli

Xsu

Xaa

Xfa

Xc4

Xpro

Xac

Xh2

XI

Sgas,h2

Sgas,ch4

Sgas,co2

Sbu Shbu

Sbu-

Sva Shva

Sva-

Spro Shpro

Spro-

Sac Shac

Sac-

SIC SCO2

SHCO3-

SIN SNH3

SNH4+

Sh+ Soh-

pgas,h2

pgas,ch4

pgas,co2

pgas,total Qgas

pH

ODE variables

Derived variables

Methodology – Theory – ADM1

Ssu

Saa

Sfa

Sch4

Sh2

SI

Scat

San

Xc

Xch

Xpr

Xli

Xsu

Xaa

Xfa

Xc4

Xpro

Xac

Xh2

XI

Sbu Shbu

Sbu-

Sva Shva

Sva-

Spro Shpro

Spro-

Sac Shac

Sac-

SIC SCO2

SHCO3-

SIN SNH3

SNH4+

Sh+ Soh-

pH

Sgas,h2

Sgas,ch4

Sgas,co2

pgas,h2

pgas,ch4

pgas,co2

pgas,total Qgas

ODE variables

Derived variables

Algebraic variables

Methodology – Theory - CFD

Governing equations:◦ Conservation of mass:

◦ Conservation of momentum:

◦ Conservation of energy:

0U

refref TTpDt

DU

U 2

0TTt

TU

Methodology – Theory – ADM-MDA

Two options:1. Start with ADM1 and write CFD into it; or

2. Start with CFD and write ADM1 into it.

ODE:

PDE:

varvarinvar

liq

liqvar rSSQ

V

dt

dS,

varvarvarvar rSSt

SU

Methodology – Theory – ADM-MDA

Three biochemistry strategies:1. Source term solver

2. ODE solver

3. Coupled solver

Methodology – Theory – ADM-MDA

Three biochemistry strategies:1. Source term solver

varvarvarvar rSSt

SU

varvarinvar

liq

liqvar rSSQ

V

dt

dS,

Methodology – Theory – ADM-MDA

Three biochemistry strategies:2. ODE solver

Transport variables (CFD)

Solve biochemistry (ODE)

Methodology – Theory – ADM-MDA

Three biochemistry strategies:3. Coupled solver

Methodology – Theory – ADM-MDA

Three biochemistry strategies:3. Coupled solver

Methodology – Theory – ADM-MDA

Time scale issue◦ ADM1:

◦ CFD: s 1dt

min 15dt

Transient solver (flow)

Steady state solver (biochemistry)

Boundary

conditio

ns c

hange

“multiSolver”

Methodology – Theory – ADM-MDA

Length scale issue

ADM1 CFD

Prolongation

Restriction

“dualGrid”

Methodology – Theory – ADM-MDA

Accessibility◦ “equationReader”

◦ The ability to read equations from a text file

Code development

Flow

Biochemistry

Transient solver

Steady state solver

Scalar transport

Non-Newtonian

Buoyancy

Particle model

PISO

Temperature

RANS turbulence

Steady state detection

Scalar transport

Particle model

Gas model

ODE solver

Implicit solver (Sh2)

Implicit solver (ions)

multiSolver

dualGrid

equationReader

Framework

Control

Code development

Scalar transport

Non-Newtonian

Buoyancy

Particle model

PISO

Temperature

RANS turbulence

Transient solver

Steady state detection

Scalar transport

Particle model

Gas model

ODE solver

Implicit solver (Sh2)

Implicit solver (ions)

Flow

Biochemistry

Steady state solver

multiSolver

dualGrid

equationReader

Control

?

?

Framework

Code development

Scalar transport

Non-Newtonian

Buoyancy

Particle model

PISO

Temperature

RANS turbulence

Transient solver

Steady state detection

Scalar transport

Particle model

Gas model

ODE solver

Implicit solver (Sh2)

Implicit solver (ions)

Flow

Biochemistry

Steady state solver

multiSolver

dualGrid

equationReader

Control

?

?

Framework

Code development

Bulk model◦ Written in Excel + Visual Basic macros

Post processing routines◦ Instantly produce comparisons between bulk model & ADM-MDA

◦ Written in Python

Results

Bulk model verification

Results

Boussinesqbuoyancy

model validation

Results

Two problems with the model:◦ Efficiency

◦ Transport deviation

Results

ChangeSimulation

TimeReal Time

Benchmark Estimate

Initial 27 [s] 6 [hr] >100,000 [yr]

(1000 cells, 1000 days)

Results

transS00 r

transr

trans SS

= +

Results

ChangeSimulation

TimeReal Time

Benchmark Estimate

Initial 27 [s] 6 [hr] >100,000 [yr]

Segregated flow

1 [dy] 18 [hr] 128 [yr]

(1000 cells, 1000 days)

Results

Semi-implicit Bulirsch Stoer

ddt

Solve derived

ODE ddt

Implicit Sh2 solver

Implicit ion solver

“innerLoops”

Results

ChangeSimulation

TimeReal Time

Benchmark Estimate

Initial 27 [s] 6 [hr] >100,000 [yr]

Segregated flow

1 [dy] 18 [hr] 128 [yr]

Inner loops1 [dy]

100 [dy]12 [min]

5:32[hr:min]144 [dy]

(1000 cells, 1000 days)

Results

Results

ChangeSimulation

TimeReal Time

Benchmark Estimate

Initial 27 [s] 6 [hr] >100,000 [yr]

Segregated flow

1 [dy] 18 [hr] 128 [yr]

Inner loops1 [dy]

100 [dy]12 [min]

5:32[hr:min]144 [dy]

Static yields 1 [dy] 62 [s] 12.5 [dy]

(1000 cells, 1000 days)

Results

Results

ChangeSimulation

TimeReal Time

Benchmark Estimate

Initial 27 [s] 6 [hr] >100,000 [yr]

Segregated flow

1 [dy] 18 [hr] 128 [yr]

Inner loops1 [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]

(1000 cells, 1000 days)

The solver is now parallelized!

Results

1 day (with flow)

Results

100 days (with flow)

Results

100 days (no flow)

Transport Error

Quad precision

Pseudo-coupled solver

Mini timesteps for transport

Improve ADM1 numerical stability

Averaged noisy transport

Agglomeration

Timeline

Timeline

Judgement day ... (May 21st)

Solve transport error ... (June 1st)

Gas model ... (June 22nd)

Particle model ... (July 15th)

Dual-grid ... (August 1st)

Validate model ... (Octobruary 15th)

Write thesis ... (Novembgust 30th)