DCHEMA Thermophysical Properties

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Dr. Richard SASS Reliable Process Modelling with Accurate Thermophysical Property Data and Models using DETHERM Workshop SFGP – 18 June 2010

Transcript of DCHEMA Thermophysical Properties

Page 1: DCHEMA Thermophysical Properties

Dr. Richard SASS

Reliable Process Modelling with AccurateThermophysical Property Data and Modelsusing DETHERM

Workshop SFGP – 18 June 2010

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Presentation Roadmap

• Importance of having accurateThermophysical Property Data andModels for the product design

• Workflow of an optimization withDETHERM

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Motivation

• Example: Modeling of a separation of anAcetone-Water mixture using a well-known simulator– Binary parameter are very good for

modeling the VLE

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Acetone/Water: VLE

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Motivation

• Example: Modelling of a separationof an Acetone-Water mixture usinga well-known simulator- Binary parameter are very good for

modeling the VLE- HE modeling with these parameters

can be improved

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Aceton/Wasser: HE

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Higher precision of models for physical properties

• Use of specifically adapted thermodynamic models,especially in the region of high or low temperature /pressure

• Modeling with reliable sets of parameters optimizedwith raw experimental data

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Important properties (1)

• Phase Equilibria– Boiling and melting points– vapor pressure– fugacity and activity coefficients– solubility (Henry's constants, Ostwald or Bunsen coefficients)

• P-V-T behavior– Density, volume, compressibility, critical constants

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What is DETHERM?

• One of the world’s largest factual databases for rawthermophysical property data

• 6.92 million data sets for 146,800 systems (31,600pure substances and 115,200 mixtures)

• updated yearly– Average growth last 10 years: 8 % p.a.

• parts are published in printed form as “DECHEMAChemistry Data Series”

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Content of database

• Phase Equilibria(VLE, LLE, SLE)

• PVT-Data• Thermodynamic Properties• Transport Properties• Interfacial Properties• Electrolyte data• Total: 211 Properties

Data for design and operationof chemical plants

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inventor question

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Motivation: Connecting two worlds

Measured data(discrete values)

Simulator(equation orientated,

model based)

Never forget : The reliability of a (process) simulation issubstantially based on the precision of the thermodynamic

models used ...

Regression andOptimizer

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DPP – Main objectives

• close the gap betweenraw thermophysical dataand process simulation

• optimized workflow

• pluggablethermodynamics

• compare models– with data– among each other

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Data Preparation Package

Objectives:• Selection

• Comparison• Analysis• Management

•• RegressionRegression

of thermophysical data and models

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The Architecture

Databases•DETHERM•DIPPR•NIST•TRC•...

Simulators•Aspen•ProSim •PRO II•...

Thermodynamic Modules•IK-CAPE•Aspen Properties•Simulis•Custom DPP GUI & COREDPP GUI & CORE

RawData

ModelParameters

End UserThermoInterface

ThermoInterface

OptimizerOptimizer

Graphicssubsystem

Graphicssubsystem

Neutral FileInterface

Neutral FileInterface

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The Optimizer

• Simultaneous correlation– of different data types / systems– with different error functions– e.g. VLE + LLE + HE + γ∞ + Azeotrops

• Model parameter transformation– 1:1– Different ranges -> equal ranges– Bounded -> Unbounded

• Equality constraints on parameters possible• Combination with Maximum Likelihood Algorithm (ML) possible

... is the ... is the ... is the ... is the corecorecorecore element of DPP element of DPP element of DPP element of DPP

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DETHERM Software SuiteDETHERM Software Suite

Process SimulatorProcess Simulator

DPP and DETHERM

• DPP regression tool couplesdatabase with simulator.

Data Preparation Package (DPP)

DETHERM InhouseDatabase

Thermo-dynamics module

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Regression: Result plot

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Simultaneaus VLE regression

γ∞

Isobaricvalues

Isothermalvalues Excess

Enthalpydata

Azeotropformation

T,X,Y

P,X,Y

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Binary LLE: Water/1-Butanol

Testing differentsetups/flavors of

NRTL over the fulltemperature range:

-30 – 130 °C

Testing differentsetups/flavors of

NRTL over the fulltemperature range:

-30 – 130 °C

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Binary LLE: THF/Water

System with twocritical points

System with twocritical points

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Ternary LLE

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Ternary LLE – Solutropic System

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GLE of CO 2 – Water up to 1600 bar

Simple Henry

Henry + NRTL

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GLE of CO 2 – Water, ambient pressure

Henry coefficient asfunction of temperature

Isopartial datawith p(CO 2) = 1 atm

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DETHERM

Example:Separation of the mixture:n-pentane/methanol

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Workflow (1)

• Example: Modelling of a separation of amixture n-pentane/Methanol

• Target temperature above 400 K• Maximum pressure approximately 25 bar

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Workflow (2) – n-pentane/methanol

• Approach:– NRTL activity coefficient model

together with• Peng-Robinson equation of state for

fugacity coefficients

• Data from DETHERM:• R.A. Wilsak et al. for VLE

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Workflow (3) – Data import from DETHERM

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Workflow (4) – Data import from DETHERM

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Workflow (5) – First regression

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Workflow (6) – First Thermodynamic consistency test – Improvement is necessary

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Workflow (6a) – First Thermodynamic consistency tes t – further improvement is necessary

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Workflow (7) – Optimization Results

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Workflow (8) – Optimization Results

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Workflow (9) – Deviation plot

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Workflow (10) – Optimization Results

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DETHERM

Merci de votre attention

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DETHERM – The history

1976BMFT-Study „Demand for PhysicalProperty Data and Calculation methodswithin the Chemical Industry“

1979-1985Two projects (BMFT/AiF) for collection ofdata & methods

� 25 partners (Universities & Industry)

� Extension of the UHDE thermo compiler

Since 1986single BMFT / AIF-Projects

� e.g. PURE

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DETHERM: Data Packages (2) – Status 2010

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Content of a dataset

• identification of substance(s)• systematical name,

synonyms

• sum formula, CAS-No.

• descriptors

• numerical data• description of data

• data, errors, remarks

• literature sources• bibliographic information,

abstract

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Producers of DETHERM

• DECHEMA

• DDBST

• FIZ CHEMIE

• Regensburg University

● property orientated packages

� maintained by independentexperts

� e.g. DDB, ELDAR, INFOTHERM

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What is the value of DETHERM?

• Extend the accuracy of yourprocess models

• Model components notavailable in your parameterdatabases

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Benefits using DETHERM

• Dependable and evaluated data

... independent and well known experts are collectingand evaluating the data packages.

... evaluated and checked data are guaranteed this way.

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Benefits using DETHERM

• Dependable and evaluated data• Completeness of data

... in the field of vapor-liquid-equilibrium data more than95 % of all data published worldwide are contained. IfDETHERM contains no data, it is not worth to check anyother source.

... yearly updates (in average 8 % per year)

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Benefits using DETHERM

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Benefits using DETHERM

• Dependable and evaluated data• Completeness of data• Inventor questions possible

... you need a component X with some specialproperties, for example a solvent with

- a boiling point bigger than 150 °C and- forming an azeotrope with component Y?- Searching a component having a given solubility in water

... just define the properties you need and search thedatabase, saving days of manual work.

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Benefits using DETHERM

• Dependable and evaluated data• Completeness of data• Inventor questions possible• Merging of data pools

... the inhouse systems allows to store own data sets.Customers can merge their own data pool with thedelivered one this way. All data can accessed andretrieved consistently the same way.

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