thermodynamic property models for transport and …€¦ · · 2016-05-30thermodynamic property...

RUHR-UNIVERSITÄT BOCHUM

Thermodynamic Property Models for

Transport and Storage of CO2

Roland Span

UKCCS Research Centre Meeting, York 2014

2 Span | UKCCS Research Centre Meeting | York 2014

Options for CCS

Pre-Combustion Process

(IGCC / NGRCC)

Category

Lignite

Fuel

Hard Coal

Cryogenic

O2 Supply

OTM / ITM

Physical Absorpt.

CO2 Separation

Chemical Absorpt.

H2 Membrane

CO2 Membrane

Integrated Process

(Oxy-Fuel) Cryogenic

OTM / ITM

Condensation

Chemical Looping

Post-Combustion Process

(exhaust gas cleaning) Chemical Absorpt.

Chilled Ammonia

Solid Adsorbents

Conditioning

Natural Gas

Lignite

Hard Coal

Natural Gas

Lignite

Hard Coal

Natural Gas

Membrane Reactor

Compression, Transport and Storage of CO2


Multi-Disciplinary Property Research


(IGCC / NGRCC)

Category

Lignite

Fuel

Hard Coal

Cryogenic

O2 Supply

OTM / ITM

Physical Absorpt.

CO2 Separation

Chemical Absorpt.

H2 Membrane

CO2 Membrane

Integrated Process


OTM / ITM

Condensation

Chemical Looping



Chilled Ammonia

Solid Adsorbents

Natural Gas

Lignite

Hard Coal

Natural Gas

Lignite

Hard Coal

Natural Gas

Membrane Reactor

Conditioning Compression, Transport and Storage of CO2

Property models typical for chemical engineering



(IGCC / NGRCC)

Category

Lignite

Fuel

Hard Coal

Cryogenic

O2 Supply

OTM / ITM

Physical Absorpt.

CO2 Separation

Chemical Absorpt.

H2 Membrane

CO2 Membrane

Integrated Process


OTM / ITM

Condensation

Chemical Looping



Chilled Ammonia

Solid Adsorbents

Natural Gas

Lignite

Hard Coal

Natural Gas

Lignite

Hard Coal

Natural Gas

Membrane Reactor


Property models typical for geology / geo sciences




(IGCC / NGRCC)

Category

Lignite

Fuel

Hard Coal

Cryogenic

O2 Supply

OTM / ITM

Physical Absorpt.

CO2 Separation

Chemical Absorpt.

H2 Membrane

CO2 Membrane

Integrated Process


OTM / ITM

Condensation

Chemical Looping



Chilled Ammonia

Solid Adsorbents

Natural Gas

Lignite

Hard Coal

Natural Gas

Lignite

Hard Coal

Natural Gas

Membrane Reactor


Property models typical for energy technologies




(IGCC / NGRCC)

Category

Lignite

Fuel

Hard Coal

Cryogenic

O2 Supply

OTM / ITM

Physical Absorpt.

CO2 Separation

Chemical Absorpt.

H2 Membrane

CO2 Membrane

Integrated Process


OTM / ITM

Condensation

Chemical Looping



Chilled Ammonia

Solid Adsorbents

Natural Gas

Lignite

Hard Coal

Natural Gas

Lignite

Hard Coal

Natural Gas

Membrane Reactor



Oxyflame – DFG Collaborative Research Centre

RUB with RWTH Aachen and TU Darmstadt



(IGCC / NGRCC)

Category

Lignite

Fuel

Hard Coal

Cryogenic

O2 Supply

OTM / ITM

Physical Absorpt.

CO2 Separation

Chemical Absorpt.

H2 Membrane

CO2 Membrane

Integrated Process


OTM / ITM

Condensation

Chemical Looping



Chilled Ammonia

Solid Adsorbents

Natural Gas

Lignite

Hard Coal

Natural Gas

Lignite

Hard Coal

Natural Gas

Membrane Reactor



Develop a model / a set of models which …

• describes homogeneous states with high

(reference) accuracy

• consistently describes VLE / LLE equilibria

• consistently describes equilibria with solid phases

(ice, dry ice, hydrates)


Thermodynamic Properties of Pure CO2

Span and Wagner (2003), fundamental EOS with 12 fitted coefficients (high technical quality)

Span and Wagner (1996), fundamental EOS with 42 fitted coefficients (reference quality)


Helmholtz-model for mixtures (fundamental equation of state!)

Introduced independently by Lemmon & Tillner-Roth in mid 90’s

1

0 r r

m m m m

1 1 1 1

, , , ln , ,

N N N N

i oi i i oi i j ij ij

i i i j i

x x T x x x x F

The GERG-2008 Model by Kunz and Wagner




Pure fluid equations of state (EOS)

1

0 r r

m m m m

1 1 1 1

, , , ln , ,

N N N N


i i i j i

x x T x x x x F






Mixing rules for reduced input parameters m and m

Two options:

• Mixing rules with four adjustable, binary specific parameters

• Combination rules

1

0 r r

m m m m

1 1 1 1

, , , ln , ,

N N N N


i i i j i

x x T x x x x F


0.5

rm r , , , ,2

1 1 ,

( )with ( )

N Ni j

i j T ij T ij c i c j

i j T ij i j

x xTT x x T T

T x x

xx

3

m , , 2 1 3 1 31 1r r , , ,

1 1 1 1with

( ) ( ) 8

N Ni j

i j ij ij

i j ij i j c i c j

x xx x

x x

x x






Binary excess functions

Two options:

• Binary specific excess function – Fij = 1, parameter in ij fitted

• Generalized excess function – Fij fitted, parameter in ij generalized


1

0 r r

m m m m

1 1 1 1

, , , ln , ,

N N N N


i i i j i

x x T x x x x F


, , ,

,

2

m m m m m m m m

1 1

( , ) expPol ij Pol ij Exp ij

k k k k

Pol ij

K K K

d t d t

ij k k k k k k

k k K

n n






Four levels of accuracy, depending on available experimental data and relevance of the binary subsystem

• Only combination rules for Tr, r

• Mixing rules with four adjustable parameters for Tr, r

• Adjusted mixing rules & generalized excess function

• Adjusted mixing rules & binary specific excess function


1

0 r r

m m m m

1 1 1 1

, , , ln , ,

N N N N


i i i j i

x x T x x x x F


UNIQUE!






1

0 r r

m m m m

1 1 1 1

, , , ln , ,

N N N N


i i i j i

x x T x x x x F


Methane (CH4) n-Pentane (n-C5H12) Hydrogen (H2)

Nitrogen (N2) Isopentan (i-C5H12) Carbon monoxide (CO)

Carbon dioxide (CO2) n-Hexane (n-C6H14) Hydrogen sulphide (H2S)

Ethane (C2H6) n-Heptane (n-C7H16) Water (H2O)

Propane (C3H8) n-Octane (n-C8H18) Oxygen (O2)

n-Butane (n-C4H10) n-Nonane (n-C9H20) Argon (Ar)

Isobutane (i-C4H10) n-Decane (n-C10H22) Helium (He)


5 mixtures: new excess functions

5 mixtures: new reducing parameters

EOS-CG – Improving GERG-2008 for CO2-Rich Mixtures

O 2

N 2

CO 2

CO

Ar

Binary specific excess function

r ij

Adjusted reducing functions for r and Tr

Lorentz-Berthelot combining rules for r and Tr


Property Models for CO2-Rich Mixtures – EOS-CG

Example CO2 – Ar: Phase boundaries

Improvements compared to GERG-2008 at high pressure


Example H2O – CO2: Phase Boundaries



Example H2O – CO2: Densities



Numerically stable (phase-equilibrium) algorithms available



Much Room for Improvement: IMPACTS

Binary systems for experimental work within IMPACTS

EOS

Ch

lori

ne

Hyd

roge

n C

hlo

rid

e

Die

than

ola

min

e

Mo

no

eth

ano

lam

ine

Me

than

ol

Am

mo

nia

Sulp

hu

r Tr

ioxi

de

Sulp

hu

r D

ioxi

de

Nit

roge

n D

ioxi

de

Nit

roge

n O

xid

e

Hyd

roge

n S

ulf

ide

Me

than

e

Hyd

roge

n

Car

bo

n M

on

oxi

de

Arg

on

Oxy

gen

Nit

roge

n

Wat

er

Carbon Dioxide

Water

Nitrogen

Oxygen

Argon

Carbon Monoxide

Hydrogen

Methane

Hydrogen Sulfide

Nitrogen Oxide

Nitrogen Dioxide

Sulphur Dioxide

Sulphur Trioxide

Ammonia

Methanol

Monoethanolamine Probably covered quite well by existing Helmholtz models

Diethanolamine Helmholtz models available, but accuracy unclear

Hydrogen Chloride Current work at RUB

Chlorine

Maj

or

Co

mp

on

en

tsM

ino

r C

om

po

ne

nts

NIST & WSU


• CO2 in pipelines is liquid

• Pressure loss (leaks or flooding of

evacuated pipeline segments)

results in liquid / vapor system

• Further expansion leads to

formation of a dry ice / vapor

system at about 195 K

• For a description of the process

(enthalpy) flash calculation with

solid phase

• Similar effects for low tempera-

ture transport / capture

Consistent fundamental equation

for dry ice required!

Low-Temperature Phase Equilibria for CO2


Phase Equilibria with Solid Phases – Dry Ice

Fundamental equations for solid CO2 (dry ice) developed

Jäger and Span (2010, 2012): Gibbs enthalpy as a function of pressure and temperature

Approach by Tillner-Roth (1998) adapted

Fitted only to data for solid CO2

Trusler (2011): Helmholtz energy as a function of molare volume and temperature

Fitted also phase equilibrium with adjacent fluid-phase

0 0 0

0

0 0 0

( , )( , ) ( , )d d ( , )d

pT Tp

p

T T p

c T pg p T h Ts c T p T T T v p T p

T


Phase Equilibria with Solid Phases – Dry Ice

Intersection with Gibbs enthalpies from EOS for fluid states yields consistent SVE / SLE data (sublimation / melting pressure)

Allows for flash calculations into the melting / sublimation region

The property model used for the fluid phases has a significant impact!

Intersection with

Span and Wagner (1996)

Intersection with

Ely (1987)


Phase Equilibria in the System CO2 / H2O

Solid H2O: Feistel and Wagner (2006)

Solid CO2: Trusler (2011) / Jäger and Span (2010, 2012)

Hydrates: Jäger, Vinš, Hrubý, and Span, R. (2013)

Fluid region:

H2O: Wagner and Pruss (2002)

CO2: Span and Wagner (1996)

Mixing rules: Gernert and Span (2013)


• The model of Ballard und Sloan (2002) was chosen and

slightly modified:

,, , , ln 1 ,H

w J w i i J J

i J

T p f g T p RT v C T p f

Phase Equilibria with Solid Phases – Hydrates


• The model of Ballard und Sloan (2002) was chosen and

slightly modified:

• Adjustable parameters of the model:

,, , , ln 1 ,H

w J w i i J J

i J

T p f g T p RT v C T p f

1 2, ,0 ,0,w wg h ,

Reference state Pressure dependence

of the molar volume

Potential-

parameters


fitted but almost

unchanged fitted to (T,p)-data generated from

experimental data & fluid model

consistency to reference

state of fluid model



Accurate description of CO2 / H2O hydrate formation

Consistent to accurate VLE / LLE / homogeneous phase model

Intersection with EOS-CG yields

equilibrium temperatures with

deviations < 1 K to exp. data

LcH

VH

VIw

HIc

VLc

VLw


Allowable Water Content in CO2


TREND – Software Made Available

• TREND 1.1 was made available early in 2014

• Launch of TREND 2.0 is expected by the end of 2014

Preview

TREND 2.0


Other Hydrates

• Hydrate models (consistent to accurate multiparam. mixture

models for fluid phase) will soon be published for water with

- Nitrogen

- Oxygen

- Argon

- Carbon monoxide

- Methane

- Ethane

- Propane

• A corresponding model for mixed hydrates is still pending


Avoiding Inconsistencies – Injection of CO2

• Engineers working on pipelining of CO2 use GERG-2008 / EOS-CG

• Reservoir engineers use cubic EOS (+ hydrate / electrolyte models)

• Severe inconsistencies, e.g., for injection of CO2 (-rich mixtures)

Pipeline engineer delivers

500 to/h 577 m3/h at 19.6 MPa

Reservoir engineer receives

577 m3/h at 18.1 MPa 440 to/h


Avoiding Inconsistencies

• CO2 in geological storage

Mixtures with brines instead of water

• CO2 capture from natural gas / two phase gas pipelines

Mixed hydrates

Mixtures with hydrate inhibitors

• CO2 scrubbing from flue gas / natural gas

Systems containing scrubbing agents

• CO2 ….

In the long run the main challenge will

be to ensure that property models used

in adjacent process steps are consistent

to accurate models applied for CO2 transport


Thank you for your attention!

The author is grateful to all organizations that

contributed funding to the presented work, namely to

- E.ON for awarding an E.ON Research Award

- E.ON Ruhrgas for the contract "Calculation of Complex

Phase Equilibria"

- the federal government of Nordrhein Westfalen in

conjunction with EFRE for funding under contract

315-43-02/2-005-WFBO-011Z

- the European Commission for the contract

"Seventh Framework Program, Nr. 308809, IMPACTS“

- the DFG for the framework of the collaborative research

centre ”Oxyflame“


The „Killer Application“

• If a CO2 pipeline leaks, the

mantle cools down drastically, the

material becomes brittle

• The crack propagates in both

directions

• The pressure loss propagates

with about speed of sound

• If the crack propagates faster

than speed of sound, small

cracks result in a disaster

The issue is a safety issue,

accurate properties required for

homogeneous, VLE, VLSE states

• Accurate properties are certainly

more important for other

applications, but who cares …

liquid CO2 in the pipeline

cold CO2 escapes

Pipeline wall

SINTEF


International Cooperation

Focus on CO2-rich mixtures

• Measurement of thermodynamic properties (pvT, w)

• Measurement of phase equilibria (VLE, LLE, VLSE)

• Measurement of transport properties (viscosity)

• Accurate property models for CO2-rich mixtures

• Description of phase equilibria including solid phases

• Improvement of phase equilibrium algorithms

• Test of new property models for various applications

thermodynamic property models for transport and …€¦ · · 2016-05-30thermodynamic property...

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