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“Intensified Heat Transfer Technologies for Enchanced Heat Recovery” INTHEAT (Grant Agreement 262205). Ji ří J KLEME Š, Petar S VARBANOV EC Marie Currie Chair (EXC) “INEMAGLOW” Research Institute of Chemical Technology and Process Engineering – CPI 2 , Faculty of Information Technology

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intensified heat transfer technologies for enchanced heat recovery intheat grant agreement 262205

“Intensified Heat Transfer Technologies for Enchanced Heat Recovery”INTHEAT (Grant Agreement 262205)

Jiří J KLEMEŠ, Petar S VARBANOV

EC Marie Currie Chair (EXC) “INEMAGLOW”

Research Institute of Chemical Technology

and Process Engineering – CPI2,

Faculty of Information Technology

University of Pannonia, Veszprém, Hungary

outline
Outline
  • CPI2 at the University of Pannonia
  • Research Background
  • P-graph for Process Synthesis
  • Books and Other Publications
  • Involvement of CPI2-UOP in INTHEAT
professor ferenc friedler dean faculty of information technology
Professor Ferenc Friedler, DeanFaculty of Information Technology

Development of P-graph and S-graph frameworks (Co-founder)

Process Network Synthesis

Batch Process Scheduling

Energy Saving and Pollution Reduction

Reaction Pathway Identification

Knight\'s Cross Order of Merit of the Republic of Hungary, Budapest, Hungary, 2003

László Kalmár Prize (John von Neumann Computer Science Society), Budapest, Hungary, 2003

Neumann Prize (John von Neumann Computer Science Society), Budapest, Hungary, 2007

Széchenyi Prize, Budapest, Hungary, 2010

cpi 2 centre for process integration and intensification
CPI2Centre for Process Integration and Intensification

Prof Jiří J Klemeš

Chair Holder

Prof Zdravko Kravanja,

University of Maribor

Assoc. Prof.

Dr Petar Varbanov

PhD Students

Dr László Sikos

CUM LAUDEGraduate

Andreja Nemet

Lidija Čuček

Luca De Benedetto

Hon LoongLam

Zsófia Fodor

slide9

UMIST: History

  • 1824 Created by industrialists as the Manchester Mechanics Institution
  • 1905 Faculty of Technology, University of Manchester
  • 1956 Royal Charter granted to Manchester College of Science and Technology
  • 1965 University of Manchester Institute of Science and Technology
  • 2004 Merged with University of Manchester
centre for process integration

Centre for Process Integration

World Leaders in Process Design Technology

most resent research
Most Resent Research

Cell-based dynamic heat exchanger models – direct determination of the cell number and size

Petar SabevVarbanov, Jiří JaromirKlemeš, Ferenc Friedler

heat exchange cell
Heat exchange cell
  • H=”Hot”, C=”Cold”;
  • HI=”Hot Inlet”, HO=”Hot Outlet”
  • CI=”Cold Inlet”, CO=”Cold Outlet”

Cell model: icon representation

Cell model: detailed picture

mH

hHI

mH

hHO

QCELL

mC

hCI

mC

hCO

Assumptions

Definition

  • Perfect mixing in the fluid cells
  • Constant fluid densities
  • The tanks are completely full
  • Constant specific heat capacities
  • The thermal resistance of the wall is neglected
  • The wall heat capacity is taken into account
  • Two perfectly stirred tanks, exchanging heat only with each other through a dividing wall
cell model of a heat exchanger
Cell model of a heat exchanger
  • A complete heat exchanger can be modelled by a number of cells
  • The cells are combined to reflect the internal flow arrangement in the exchanger

Single-pass (1-1) heat exchanger

mHOT,

hOUT,HOT

mHOT,

hIN,HOT

mCOLD,

hOUT,COLD

mCOLD,

hIN,COLD

cell model of a heat exchanger1
Cell model of a heat exchanger

1-2 shell-and-tube heat exchanger (no baffles)

cell model of a heat exchanger2
Cell model of a heat exchanger

1-2 shell-and-tube heat exchanger (with baffles)

minimum number of cells
Minimum number of cells

Derivation

Temperature

Heat exchange

summary on the cell model
Summary on the cell model
  • Distributed models become inefficient for complex heat exchangers
  • From the lumped– mostly cell models are employed
  • The cell parameters need to be carefully estimated accounting for the underestimation of the temperature differences
  • A method for direct identification of the number of cells has been developed
  • Mostly applicable to shell-and-tube heat exchangers
  • A useful visualisation of the cell number identification procedure is provided
  • The method can be further extended to the other kinds of heat exchangers
p graph for process synthesis
P-graph for Process Synthesis

Friedler, F., J.B. Varga, and L.T Fan. (1995), Decision-Mapping A Tool for Consistent and Complete Decisions in Process Synthesis, Chem. Eng. Sci., 50(11):1755-1768

p graph a rigorous mathematical tool
P-graph: a Rigorous Mathematical Tool

Suite of tools

Search space

  • Axioms for feasible networks
  • Algorithm MSG
  • Algorithm SSG

103–106 x

  • Exploit the problem structure
  • Much faster
  • Superior to direct Mathematical Programming
p graph algorithms maximal structure generation msg
P-graph algorithms:Maximal Structure Generation (MSG)

Problem Formulation

Reduction part

Consistent sets O & M

Composition part

Maximal Structure

  • Problem Formulation
    • set of raw materials
    • set of products
    • set of candidate operating units
  • Superstructure (Maximal)
    • Union of all combinatorially feasible structures
    • Rigorous super-structure

Legend:

O: set of operating units; M: set of materials

abb algorithm even faster search
ABB Algorithm – Even Faster Search
  • Employs the “branch-and-bound” strategy
  • Combines this with the P-graph logic (SSG algorithm)
  • Ensures combinatorial feasibility

Non-optimal decisions are eliminated from the search

configuration and setup
Configuration and Setup

Demands: 10 MW power and 15 MW heat

Power: 100 €/MWh

Heat: 30 €/MWh

Natural gas: 30 €/MWh

Fertiliser from biogas digestion: 50 €/t

Plant life: 10 y

Case studies

Limit the availability of the biomass to 30 MW

fuel preparation options
Fuel Preparation Options

Biomass

Gasifier

Syngas

Filter

Biogas

digester

Performance per unit input

Streams / Materials

AR: Agricultural residues PR: Particulates

BR: Biomass residues SG: Syngas

RSG: Raw syngas BG: Biogas

CO2: Carbon dioxideFRT: Fertiliser

energy conversion options
Energy Conversion Options

Fuel Cell

Combined Cycle

Biogas

Boiler

Natural Gas

Boiler

Performance per unit input

{F}: Fuels {FCCC} {Q}: steam Steam details {Q}: steam Steam details

NG: Natural gas MCFC-GT Q1 P = 1 bar Q20 P = 20 bar

BG: Biogas MCFC-ST Q2 P = 2 bar Q40 P = 40 bar

SG: Syngas SOFC-GT Q5 P = 5 bar

SOFC-ST Q10 P = 10 bar

results
Results

Case 4;

Biomass at 10 €/MWh

Profit: 5.51 MM€/y

Cases 1, 2, 3;

Biomass < 18 €/MWh

Profit: 10.05 / 6.48 / 6.23 MM€/y

Biomass

MAX 30 MW

results summary
Results Summary
  • Biomass is profitable over a wide price range
  • Topologies relatively robust until tipping point
  • Fertiliser – marginal significance

The trade-off between the Agricultural Residues – Natural Gas prices dominates the designs

p graph for fccc summary
P-graph for FCCC Summary
  • Biomass viable for FC
  • High efficiency  lower resource demand
  • Energy supply and conversion: complex systems
  • Synthesising : combinatorially difficult
  • P-Graph: appropriate tool effectively solving the task
  • Successfully applied to choosing FCCC - based system design
recent publication
Recent Publication

IF2008 = 1.712

IF2009 = 2.952

Citations: 10

recent publication1
Recent Publication

IF2009 = 1.987

Citations: 4

citations
Citations

2008

2009

2010

slide35

Handbook of Water and Energy Management in Food ProcessingEdited by J Klemeš, University of Pannonia R Smith and J-K Kim, University of Manchester, UK

contribution to work packages
Contribution to Work Packages
  • WP 1 (Months 1-12): Analysis of intensified heat transfer under fouling, 6 person-months, Task 1.1
  • WP 2 (Months 1-18): Combined tube-side and shell-side heat exchanger enhancement, 1 person-month, Task 2.2
  • WP 4 (Months 1-24): Design, retrofit and control of intensified heat recovery networks, 9.5 person-months, Tasks 4.1 and 4.3. This will be a development of the P-graph methodology using the ABB algorithm
  • WP 5 (Months 12-24): Putting into practice, 5 person-months, Tasks 5.2 and 5.3
leader of wp 6 technology transfer
Leader of WP 6 “Technology transfer”

Aim: Effective technology transfer to the wide range academic and industrial communities

  • Validation of the developed novel methodology with the SME partners.
  • Dissemination of the project results, aiming to achieve the best possible project recognition over a broad audience
  • Develop suitable training and support materials for SME partners
  • Establish an active community involving the INTHEAT partners and other users/experts for continuous knowledge management and improvement
wp 6 technology transfer
WP 6 “Technology Transfer”
  • Runs during months 6 – 24
  • Tasks:
    • 6.1. Technology transfer to SME consortium members
    • 6.2. Dissemination events
    • 6.3. Publications
    • 6.4. Training
task 6 1 technology transfer to sme consortium members
Task 6.1. Technology transfer to SME consortium members
  • Streamlined transfer of the developed and acquired technologies, licenses and know-how among the consortium all members
  • A special emphasis will be put on the technology transfer to the industrial partners

Principles

  • All outputs/deliverables from WPs 1 to 5 will be checked for documentation in such a way, as to enable technology users to obtain reproducible results
  • Additional application procedures may be needed
task 6 2 dissemination events
Task 6.2. Dissemination events

Intensified heat exchangers – Novel developments

Information day for major stakeholders

Organisers: UNIPAN, PIL, UNIMAN

Has to be delivered by Month 8

Suggested: PRES’11, 8-11 May 2011, Florence, Italy

slide45

14th Conference Process Integration, Modelling

and Optimisation for Energy Saving and

Pollution Reduction

8-11 May 2011, Florence, Italy

Organiser & Secretariat

Raffaella DAMERIO

The Italian Association of Chemical Engineering

Via Giuseppe Colombo 81A

20133 Milano (Italy)

Phone:+39-02-70608276

Fax:+39-02-59610042

Email: [email protected]

Hon Loong LAM

(Scientific Programme Secretary)

Phone: +36-88-421664

Fax: +44 871 244 774

Email: [email protected]

Website: www.conferencepres.com

task 6 2 dissemination events1
Task 6.2. Dissemination events

Enhanced heat transfer

Workshop/session at a recognised international conference

Organisers: UNIPAN, CALGAVIN, EMBAFFLE, SODRU

Has to be delivered by Month 12

Suggested: 6-th Dubrovnik Conference on Sustainable Development of Energy, Water and Environment Systems, September 25 - 29, 2011, Dubrovnik, Croatia

task 6 2 dissemination events2
Task 6.2. Dissemination events

Software Demonstration Workshop

Workshop/session at a recognised international conference

Organisers: UNIPAN, PIL, UNIMAN

Has to be delivered by Month 18

Suggested: A dedicated workshop to be held in the summer of 2012, at PRES 2012

task 6 2 dissemination events3
Task 6.2. Dissemination events

Joint Hub for Intensified Heat Exchangers

Workshop held by all academic partners with the support of the industrial partners

Has to be delivered by Month 22

Suggested: A dedicated workshop to be held in Veszprém in September-October 2012

task 6 3 publications
Task 6.3. Publications
  • Three major conferences will be held during the project execution: PRES’11 (May 2011), SDEWES 2011 (September 2011), PRES 2012. It is expected that at least 9 conference publications will be delivered
  • Scientific articles in refereed journals: minimum 4 papers are planned
  • Wider dissemination to the public, authorities, environmentalists and decision-making bodies
task 6 4 training
Task 6.4. Training
  • The major training will be carried out in form of workshop at UNIPAN, scheduled for delivery by Month 23 (October 2012).
  • Suggested venue: To be organised as a follow-up event after the workshop “Joint Hub for Intensified Heat Exchangers” from Task 6.2, Veszprém in September-October 2012
  • The relevant training materials have to be available before the workshops. Suggested delivery – by June-July 2012, to allow for testing and fine-tuning
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