pinch analysis_a tool for efficient use of energy
TRANSCRIPT
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Staff Development Programme One week Jan 05t -09t, 200
Under the aegis of
All India Council of Technical Education
Pinch Analysis:A Tool for Efficient Use of Energy
Department of Chemical Engineering offers a one week Training Course on P
Technology which provides a basic grounding in Process Integration.
Learn the fundamental concepts of Pinch Technology and how these can be appliedreduce energy and capital costs and increase capacity. It is appropriate for candidates wwish to gain an understanding of how to achieve process energy efficiency improvemeand
Reduce utility costs
Remove energy & capacity bottlenecks
Avoid or reduce capital expenditure
Optimum practical design
Department of Chemical EngineeringNational Institute of Technology RourkelaRourkela769 008, Orissa
Coordinated by: Dr. Shabina Khanam
Co-coordinated by: Prof. K. C. Biswal
http://www.terragalleria.com/california/picture.usca9431.htmlhttp://www.terragalleria.com/california/picture.usca9425.html -
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ACKNOWLEDGEMENT
The AICTE sponsored short term course on Pinch Analysis: A Tool for Efficient Useof Energy is a culmination of Research and Teaching efforts of the Process Engineering
group of the Chemical Engineering Department, NIT Rourkela.
Thanks are also due to Prof. Sunil Kumar Sarangi, Director, NIT Rourkela for hisconsistent support and encouragement.
We would like to express my sincere gratitude to Prof. S. K. Jena, Dean (SRICCE), NITRourkela for his excellent cooperative attitude. I thank the staff of SRICCE to provideinvaluable help.
We extend our thanks to all faculty members of Department of Chemical Engineering fortheir cooperation and continuous encouragement.
We are also grateful to the Prof. Bikash Mohanty, Resource person from ChemicalEngineering Department, IIT Roorkee for his significant contribution in delivering thiscourse.
We take this opportunity to express our appreciation to the Post-Graduate students andNon-Teaching staff of Chemical Engineering Department for their support andassistance. Without their support this course could not have reached to this stage.
We also realize that without a high level of receptivity, active involvement, andcooperation from the participants, this course would not have accomplished its
objectives.
Last but not the least; we thank all those who have directly or indirectly contributedtowards the success of this course.
Dr. Shabina Khanam Prof. K.C. Biswal
Coordinator Co-CoordinatorHOD, CH
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COURSE OVERVIEW
Process Integration (PI) is a general approach for the design of energy efficient process
systems and Pinch Technology is a tool to achieve it. In the late 1970s Pinch Technology
emerged as a tool for the design of heat exchanger networks against the backdrop of
energy crisis. Its key contribution was to provide the engineers with simple concept of
heat, power and thermodynamics, which can be used interactively in each stage of design.
In 1980s, Pinch Technology received prime attention as a heat exchanger network design
tool and it was found that this technology could save around 2040% of energy bills of
the industry. Since then, the method has become broad based. However, its
thermodynamic principles, heuristic rules and its key strategy to set targets before design
remain intact. With time it has emerged as a powerful, matured integrated design and
retrofitting tool for overall process design.
The present course deals with concept to implementation of Pinch Technology in
integrated process design.
The one week duration course was specially tailored to provide enough resources to the
attending candidates to start a course on Process Integration in their respective
departments or to use it in the industries. This course is expected to be popular in near
future as it holds considerable promise for the conservation of energy in Chemical and
allied industries.
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LIST OF PARTICIPANTS
S. No. Participant Photograph
1 Dr. RaviShankar RProf. and Head
Chemical Engineering DepartmentDayananda Sagar College of EngineeringShavige Malleswara Hills.Kumaraswamy Layout, Bangalore 560078Ph: 9448327476Email:- [email protected]
2 Prof. Mahadeva Raju, G. K.Assistant ProfessorChemical Engineering DepartmentDayananda Sagar College of Engineering
Shavige Malleswara Hills.Kumaraswamy Layout, Bangalore 560078Ph: 9845772214Email:- [email protected]
3 Mr. Jagadish H PatilAssistant ProfessorChemical Engineering DepartmentR V College of Engineering,Mysore RoadBangalore 59
Ph: 080-67178046/67178109Email: [email protected]
4 Mr. Anil Kumar PrasadLecturer,Deptt. of Applied Mechanics,NIT Jamshedpur831014JharkhandPh: 9835314761Email: [email protected]
5 Mrs. Dipa DasLecturerChemical Engineering Dept.Indira Gandhi Institute of TechnologySarang, (Parjang) - 759146DistDhenkanalEmail: [email protected]
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6 Mr. Karthik S. P.Senior EngineerSanden Vikas India Ltd.Plot No. 65, Sector27AFaridabad121003, Haryana
Ph: 9958855998Email: [email protected]
7 Mr. Bhabani Prasanna PattnaikAssis. ProfessorMechanical Engineering Dept.KIIT UniversityBhubaneswar, OrissaPh: 9437169040Email: [email protected]
8 Dr. Shib Sankar SahaSr. LecturerElectrical EngineeringGovt. Gollege of Engg. and Textile TechnologyBerhampore742 101 W.B.Ph: 9434315226Email: [email protected]
9 Dr. S. K. AgarwalProfessorChemical Engineering Dept.NIT Rourkela769 008,OrissaPh: 9861386942Email: [email protected]
10 Dr. Basudeb MunshiAsstt. Professor
Chemical Engineering Dept.NIT Rourkela769 008, OrissaPh: 0661-2462265Email: [email protected]
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11 Dr. Arvind KumarAssistant ProfessorChemical Engineering Department.National Institute of Technology Rourkela769 008, Orissa
Ph: 9438348807e-mail:[email protected]://sites.google.com/site/arvindkumarnitr/
12 Dr. Mithilesh KumarAsstt. ProfessorDepartment of Met. & Materials Eng.NIT Rourkela769 008, OrissaPh: 0661-2463554Email: [email protected]
13 Mr. Binod Kumar SinghResearch ScholarDepartment of Met. & Materials Eng.NIT Rourkela769 008,OrissaEmail: [email protected]
14 Mr Achyut Kumar PandaSr. LecturerDepartment of ChemistryJagannath Institute for Tech. & Mgmt.Gajapati761211, OrissaPh: 9437132916Email: [email protected]
15 Mrs Hemalata Patra
Lecturer, G.I.E.T.,GunupurPh: 9437646933Email: [email protected]
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16 Dr. Sunil Kumar MaityAssit. ProfessorChemical Engineering Dept.NIT Rourkela769 008
Ph: 0661-2462266Email: [email protected]
17 Mr. Akshaya Kumar RoutSenior LecturerMechanical Engineering Dept.C.V. Raman College of EngineeringJanla, Bhubaneswar752054Ph: 9437756207
Email: [email protected]
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CONTENTS
S.No. Lecture(s) Speaker Page
1. Process Intensification Dr. B. Mohanty 9
2. Process Integration Dr. B. Mohanty 19
3. Pinch TechnologyAn Overview Dr. S. Khanam 28
4. Basic Elements of Pinch Technology Dr. B. Mohanty 37
5. Area Targeting Dr. B. Mohanty 49
6. Number of Unit, Shell and Cost Targeting Dr. S. Khanam 61
7. Pinch Design MethodsHeuristic Rules Dr. B. Mohanty 74
8. Design of HEN for Maximum Energy Recovery, Loop
Breaking & Path Relaxation
Dr. B. Mohanty 80
9. Driving Force Plot and Remaining Problem Analysis Dr. B. Mohanty 97
11. References 106
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Lectures 1 & 2
PROCESS INTENSIFICATION
Bikash Mohanty
ProfessorDepartment of Chemical EngineeringIndian Institute of Technology Roorkee, Roorkee247 667
Today, we are witnessing new developments that go beyond traditional chemical
engineering. Investigators at many universities and industrial research centers are
investigating on novel equipment and techniques that could transform our concept of
chemical plants and lead to compact, safe, energy-efficient and environment-friendly
sustainable processes. These developments share a common focus on Process
Intensification (PI) an approach that has been around for quite some time but has truly
emerged only in the past few years as a special and interesting discipline of Chemical
Engineering.
PI refers to the technologies and strategies that enable the physical sizes of conventional
process engineering unit operations to be significantly reduced.
The concept of PI was pioneered in late 70s by Colin Ramshaw, when the primary goal
was to reduce the capital cost of a production system. The virtue of PI approaches will be
recognized when it is appreciated that the main plant items involved in the process (i.e.
reactors, heat exchangers, separators etc.) only contribute around 20% of the cost of the
given plant. The balance is incurred by installation costs, which involve pipe work,
structural support, civil engineering and so on. A major reduction in equipment size,
coupled preferably with a degree of telescoping of equipment function for example
reactor / heat exchangers or combined condenser/distillation/re-boilers - could generate
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very significant cost savings by eliminating support structure, expensive column
foundations and long pipe runs.
Mercer, in 1993, defined the PI as PI is a design philosophy aiming at radical reduction
of physical size of the process equipment. These reductions can be a factor three to four
in magnitude. Because energy efficiency of a process is determined by the ability to
transfer the heat in a cost effective way, the design of processes using a small amount of
heat exchanger (using PI studies) or using innovative heat exchanger design (i.e compact
heat exchanger) can save energy.
In 1995, Ramshaw defined PI as a strategy for making dramatic reductions in the size of
a chemical plant so as to reach a given production objective. These reductions can come
from shrinking the size of individual pieces of equipment and also from cutting the
number of unit operations or apparatuses involved. Ramshaw speaks about volume
reduction of the order of 10 to 1000, which is quite a challenging number since then the
definition of PI has been enlarged considerably.
Benefits of Process Intensification
PI has a potential to deliver major benefits to the process industry and many other sectors,
by accelerating the response to market changes, facilitating scale-up and providing the
basis for rapid development of new products and processes. Additional benefits of PI
include reduced capital cost, improved intrinsic safety and reduce environmental impact.
Process Intensification and Its Components
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Process Intensification, being driven by the need for break through changes in operations,
focuses mainly on novel methods and equipments. PI consists of the development of
novel apparatuses and techniques that are compared to those commonly used today and
are expected to bring dramatic improvements in manufacturing and processing,
substantially decreasing equipment-size/production- capacity ratio, energy consumption
or waste production and ultimately resulting in cheaper, sustainable techniques.
As evident in Fig. 1, the whole field can generally be divided into two areas:
Process-Intensification equipments
Process-Intensification methods
Many industries offer emerging technologies that are designed for various segments of
the process industries having one common feature - Process Intensification. PI is the
miniaturization of unit operations and processes whereas a smaller compact piece of
equipment takes the place of a larger one at the same given capacity and mass flow rate.
Process Intensification Equipments
Static M ixer Reactor (SMR)
SMR has mixing elements made of heat transfer tubes (Fig. 2), can successfully be
applied in processes in which simultaneous mixing and intensive heat removal or supply
are necessary, such as in nitration or neutralization reactions.
The main disadvantage of SMRs is their relative high sensitivity to clogging by solids.
Therefore, their utility for reactions involving slurry catalysis is limited.
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Examples
Spinning disk reactor Static mixers Reverse-flowreactors
Membraneabsorption
Centrifugalfields
Supercriticalfluids
Static mixer reactor(SMR)
Compact heatexchanger
Reactivedistillation
Membranedistillation
Ultrasound Dynamic(periodic)reactoroperation
Static mixing catalysts(KATAPAKs)
Microchannel heatexchangers
Reactive extraction Adsorptivedistillation
Solar energy
Monolithic reactors Rotor/Stator mixers Reactivecrystallization
Microwaves
Microreactors Rotating packed beds Chromatographicreactors
Electricfields
Heat exchanger reactors(HEX)
Centrifugal adsorber Periodic separatingreactors
Plasmatechnology
Supersonic gas/liquidreactor
Membrane reactors
Jet-impingement reactor Reactive extrusionRotating packed-bedreactor
ReactivecomminutionFuel cells
Equipment Methods
Equipment forcarrying out
chemicalreactions
Equipment foroperations not
involving chemical
reactions
Multifunctionalreactors
Hybridseparations
Alternativeenergy
sources
Othermethods
Process Intensification
Fig. 1. Process Intensification and its components
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Monolithi c Catalysis
Monolithic substrates used for todays catalytic applications are metallic or nonmetallic
bodies providing a multitude of straight narrow channels of defined uniform cross-
sectional shapes.
To ensure sufficient porosity and enhance the catalytically active surface, the inner walls
of the monolith channels usually are covered with a thin layer of wash coat, which acts as
the support for the catalytically active species.
The most important features of monoliths are:
Very low pressure drop in single & two-phase flow
Fig. 2. Proprietary reactor-mixer is a classic example ofprocess intensifying equipment.
Fig. 3. Monolithic catalyst
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High geometric areas per reactor volume
High catalytic efficiency, practically 100 %
Exceptionally good performance in processes in which selectivity is hampered by
mass transfer resistances
Microchannel Heat Exchangers
The geometrical configuration of Microchannel heat exchangers given in Fig. 4
resembles that of the cross-flow monoliths, although the materials and fabrication
methods used differ.
The Microchannel heat exchangers exhibit high heat fluxes and convective-heat-transfer
coefficients. The reported values of heat transfer coefficients in Microchannel heat
exchangers range from 10000 to 35000 W/m2K.
Process Intensifying Methods
Reverse Flow Reactor
For exothermic processes, the periodic flow reversal in such units allows for almost
perfect utilization of the heat reaction by keeping it within the catalyst bed and after
reversion of the flow direction, using it for preheating the cold reactant gases.
Fig. 4. Microchannel heat exchanger
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These reactors are used in following industrial processes: SO2oxidation, total oxidation
of hydrocarbons in off-gases, and NOxreduction.
Reactive Di sti ll ation
Reactive distillation is one of the better-known examples of integrating reaction and
separation, and is used commercially.
In the column, reactants are converted on the catalyst while reaction products are
continuously separated by fractionation (thus overcoming equilibrium limitations).
The catalyst used for reactive distillation usually is incorporated into a fiberglass and
wire-mesh supporting structure, which also provides liquid redistribution and
disengagement of vapor.
Reactive Extr usion
Reactive extruders are being increasingly used in polymer industries.
They enable reactive processing of highly viscous materials without requiring the large
amounts of solvents that stirred-tank reactors do.
Particularly popular are twin-screw extruders, which offer effective mixing, the
possibility of operation at high pressure and temperatures, plug-flow characteristics, and
capability of multistaging.
Most of the reactions carried out in extruders are single- or two-phase reactions.
Sonochemistry
Sonochemistry is the use of ultrasound as a source of energy for chemical processing and
appears to be the most advanced. Formation of microbubbles (cavities) in the liquid
reaction medium via the action of ultrasound waves has opened new possibilities for
chemical syntheses. These cavities can be thought of as high-energy microreactors.
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Supercri tical F lu ids
Supercritical fluids (SCFs) are used industrially for the processing of natural products.
Because of their unique properties, SCFs are attractive media for mass transfer
operations, such as extraction and chemical reactions.
Many of the physical and transport properties of a SCF are intermediate between those of
a liquid and a gas. Diffusivity in an SCF, for example, falls between that in a liquid and a
gas; this suggests that reactions that are diffusion limited in the liquid phase could
become faster in a SCF phase.
SCFs already have been investigated for a number of systems, including enzymes
reactions, Diels-Alder reactions, organometallic reactions, heterogeneously catalyzed
reactions, oxidations and polymerizations.
Case Study of Process Intensification
The isomerisation of pinene oxide to campholenic aldehyde (Equation 1) is an important
reaction for the fragrance industry.
The reaction is complex, and a simplified schematic (Equation 2) shows how there are
four other major products, besides the desired campholenic aldehyde, are formed and
how this product (campholenic aldehyde) itself can react further to another five by-
products. A novel silica-supported zinc triflate catalyst was selected for the work. A
number of other heterogeneous catalysts are used for the reaction, though homogeneous
zinc halides are used commercially.
The results described below are expressed as percentage disappearance of the pinene
oxide (conversion), and efficiency of conversion of the disappeared pinene oxide to
desired campholenic aldehyde product (selectivity).
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An amount of optimization work was performed in stirred flasks. When stirring a 1 %
solution of pinene oxide in 1.2.dichloroethane solvent with catalyst at 85 C, conversion
achieved was 100 % after 5 min, with selectivity on a plateau of 63-65 % at between 3
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and 10 min reaction time, and a peak of 65 % at 5 min. Multiplying conversion and
selectivity together to give a product yield, we see a peak of 63-65 % at between 5 and 10
min.
Spinning disc work was first performed as a series of 15 two-minute runs at 25 to test
catalyst stability. The catalyst was attached to the disc surface with adhesive, the
conversion remained constant for each run at 20 %. Three consecutive passes with the
same material gave 55 % conversion at 84 % selectivitywhich was encouraging.
A range of runs was now performed at 85, varying disc. The disc residence times was
thus explored in the range 0.5 to 5 sec. The optimum condition proved to be using the
highest tested feed rate of 6 ml/s and a spin-speed of 1000-1200 rpm. Lower spin speeds
gave 100 % conversion and much reduced selectivity presumably attributable to over-
reaction of product with the longer residence time on the disc surface at lower rpm. Even
higher spin speeds gave up to 62 % selectivitybut at a reduced conversion of 75 %. The
optimum yield (conversion*selectivity) was stable at approximately 55 % at between
1000 and 1500 rpm.
The results show that the catalyst can be extremely effective on the disc, whilst avoiding
the filtration and recovery step required in stirred ranks. A bonus which is often
experienced with intensified devices is that the rate of data collection and process
optimization was enormous compared with stirred flask development. A new data point
could be generated every few minutes, a the generous equilibration time given after
adjusting feed-rate or spin-speed was a matter of 10-20 sec, and sample collection time
was only one minute.
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Lecture-3
PROCESS INTEGRATION
Bikash Mohanty
ProfessorDepartment of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee247 667
Process integration, a part of Process Intensification, is a fairly new term that emerged in
80s and has been extensively used in the 90s to describe certain systems oriented
activities related primarily to process design. It has incorrectly been interpreted as Heat
Integration by a lot of people, probably caused by the fact that Heat Recovery studies
inspired by Pinch Concept initiated the field and is still core elements of Process
Integration. It appears to be a rather dynamic field, with new method and application
areas emerging constantly. The Process Integration is defined as systematic and general
methods for designing integrated production systems, ranging from individual processes
to total sites, with special emphasis on the efficient use of energy and reducing
environmental effects.
This definition brings Process Integration very close to Process Synthesis, which is
another systems oriented technology. Process Integration and synthesis belongs to
process systems engineering. Process Integration has evolved from a heat recovery
methodology in the 80s to become what a number of leading industrial companies in
90s regarded as a major strategic design and planning technology. With this
technology, it is possible to significantly reduce the operating cost of existing plants,
while new processes often can be designed with reduction in both investment and
operating costs.
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Definition of Process Integration as per International Energy Agency (IEA)
Process Integration is the common term used for the application of methodologies
developed for System- oriented and Integrated approaches to industrial process
plant design for both new and retrofit applications.
Process Integration refers to Optimal Design; examples of aspects are: capital
investment, energy efficiency, emissions, operability, flexibility, controllability,
safety and yields. Process Integration also refers to some aspects of operation and
maintenance.
Process integration, combined with other tools such as process simulation, is a
powerful approach that allows engineers to systematically analyze an industrial
process and the interactions between its various parts.
Current Status of Process Integration
Process Integration is a strongly growing field of Process Engineering. It is now standard
curriculum for process engineers in both Chemical and Mechanical Engineering at most
universities around the world, either as a separate topic or as part of a Process Design or
Synthesis course. Research at UMIST has for 25 years been supported by a large number
of industrial companies through a Consortium that was established in 1984. As part of the
International Energy Agency (IEA) project on Process Integration, more than 50 other
universities around the world involved in research in this field have been identified.
From History to the Future
Process Design has evolved through distinct "generations". Originally (first generation),
inventions that were based on experiments in the laboratory by the chemists, were tested
in pilot plants before plant construction.
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The second generation of Process Design was based on the concept of Unit Operations,
which founded Chemical Engineering as a discipline. Unit Operations acted as building
blocks for the engineer in the design process.
The third generation considered integration between these units; for example heat
recovery between related process streams to save energy.
A strong trend today (fourth generation) is to move away from Unit Operations and focus
on Phenomena. Processes based on the Unit Operations concept tend to have many
process units with significant and complex piping arrangements between the units. By
allowing more than one phenomena (reaction, heat transfer, mass transfer, etc.) to take
place within the same piece of equipment, significant savings have been observed both in
investment cost and in operating cost (energy and raw materials).
Different Schools of Thoughts in Process Integration
The three major features of Process Integration methods are the use heuristics (insight),
about design and economy, the use of thermodynamics and the use of optimization
techniques. There is significant overlap between the various methods and the trend today
is strongly towards methods using all three features mentioned above. The large number
of structural alternatives in Process Design (and Integration) is significantly reduced by
the use of insight, heuristics and thermodynamics, and it then becomes feasible to address
the remaining problem and its multiple economic trade-offs with optimization techniques.
Despite the merging trend mentioned above, it is still valid to say that Pinch Analysis and
Exergy Analysis are methods with a particular focus on Thermodynamics. Hierarchical
Analysis and Knowledge Based Systems are rule-based approaches with the ability to
handle qualitative (or fuzzy) knowledge. Finally, Optimization techniques can be divided
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into deterministic (Mathematical Programming) and non-deterministic methods
(stochastic search methods such as Simulated Annealing and Genetic Algorithms). One
possible classification of Process Integration methods is to use the two-dimensional
(automatic vs. interactive and quantitative vs. qualitative) representation in Fig. 1.
Application of Process Integration
Process Integration can be applied in following fields of chemical engineering such as:
1. Heat integrationheat exchange network
2. Distillation column targeting
3. Cogeneration and total site targeting
4. Batch process targeting
5. Emission targeting
6. Mass exchange network (water and wastes water management & recovery of
valuable materials)
7. Hydrogen management in refineries
Hierarchical
Analysis
HeuristicRulesKnowledge
Based Systems
Thermodynamic
MethodsOptimization
Methods
qualitative
quantitative
interactiveautomatic
Fig. 1 One possible Classification of Process Integration
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Techniques Available for Process Integration
1. Pinch Technology Approach
2. MILP/MINLP Approach
3. State-Space Approach
4. Genetic Algorithm Approach
5. Process Graph Theory Approach
Concept of Pinch Technology
The term "Pinch Technology" was introduced by Linnhoff and Vredeveld to represent a
new set of thermodynamically based methods that guarantee minimum energy levels in
design of heat exchanger networks. Over the last two decades it has emerged as an
unconventional development in process design and energy conservation. The term Pinch
Technology is often used to represent the application of the tools and algorithms of
Pinch Technology for studying industrial processes.
Reactor
Separator
Heat exchange network
Utilities
The heat and materialbalance is at thisboundary
Site-Wide Utilities
Fig. 2 Onion Diagram
1
2
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Pinch technology provides a systematic methodology for energy saving in processes and
total sites. Fig. 2 illustrates the role of Pinch Technology in the overall process design.
The process design hierarchy can be represented by the onion diagram as shown below.
The design of a process starts with the reactors (in the core of the onion). Once feeds,
products, recycle concentrations and flow rates are known, the separators (the second
layer of the onion) can be designed. The network (the third layer) can be designed. The
remaining heating and cooling duties are handled by the utility system (the fourth layer).
The process utility system may be a part of a centralized site-wide utility system.
A Pinch Analysis starts with the heat and material balance for the process. Using Pinch
Technology, it is possible to identify appropriate changes in the core process conditions
that can have an impact on energy savings (onion layers one and two). After the heat and
material balance is established, targets for energy saving can be set prior to the design of
the heat exchanger network.
Data Extraction
The most time consuming and often most critical step is the identification of the need for
heating, cooling, boiling and condensation in the process. This task is more art than
science, and if not carried out properly, the final design will not be the best possible. It is
quite easy to accept too many feature of the proposed flow sheet, which inevitably results
in the situation where many good opportunities are excluded from the analysis.
In practice, there are a number of situations where heat integration is not desirable.
Examples include long distances (costly piping), safety (heat exchange between
hydrocarbon streams and oxygen rich streams), product purity (potential leakage in heat
exchangers), operability (start-up and shut-down), controllability and flexibility. A
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reasonable strategy is, however, to start by including all process streams and keep the
degrees of freedom open. Later, practical considerations can be used to exclude some of
these streams and degrees of freedom, and the engineer will then at any time be able to
establish the consequences with respect to energy consumption and total annual cost. A
central part of data extraction is the identification of heating and cooling requirements in
the process. The necessary data for each process stream are the following:
m = mass flowrate (kg/s, tons/h, etc.)
Cp= specific heat capacity (kJ/kgC)
Ts= supply temperature (C)
Tt= target temperature (C)
Hvap= heat of vaporization for streams with a phase change (kJ/kg)
Additionally, the following information must be collected on utilities and existing heat
exchangers for retrofit:
Existing heat exchanger area (m2)
Heat transfer coefficient for cold and hot sides of heat exchangers (kW / m2C).
Utilities available in the process (water temperature, steam pressure levels, etc),
Marginal utility costs, as opposed to average utility costs.
Data extraction must be preformed carefully as the results strongly depend on this step. A
key objective of data extraction is to recognize which parts of the flowsheet are subject to
change during the analysis (e.g. possibility of making modifications to the piping, or
adding new heat exchangers, possibility of making temperature changes in the process or
modifying the utility that heats a given piece of equipment (MP steam instead of HP
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steam for example), etc). If, during extraction, all features of the flowsheet are considered
to be fixed, there will clearly be no scope for improvement.
At the beginning of a project it is recommended that all process stream be included in the
data extraction. Constraints regarding issues such as distance between operations,
operability, control and safety concerns can be incorporated later on. By proceeding in
such a fashion, it is possible to have an objective evaluation of the costs of imposing such
constraints. PI specialists generally include some constraints form the beginning of the
data extraction procedure. This can speed up the overall analysis, but a lot of experience
is required to ensure that potentially interesting heat-recovery projects are not excluded.
There are a lot of sector specifics for data extraction. However, heuristic rules have been
developed as guidelines. The following are the most relevant:
Do not mix streams at different temperatures. Direct non-isothermal mixing acts as a heat
exchanger. Such mixing may involve cross-pinch heat transfer, and should not become a
fixed feature of the design. For example, if the pinch is located at 70C, mixing a stream
at 90C with a stream at 50C creates a cross pinch, and will increase the energy targets.
The way to extract these streams is to consider them independently, i.e., one stream with
a supply temperature of 50C and the required target temperature, and the other stream
with a supply temperature of 90C and the required temperature.
Do not include utility streams (stream, flu gas, cooling water, refrigerant, cooling air,
etc.) in the process data unless they are involved directly in the process or they cannot be
replaced. One of the goals of using pinch analysis is to reduce the usage of utilities.
Therefore, if utility streams are extracted in a similar way to process streams, they will be
considered as fixed requirements and no opportunities of reduction in utility use will be
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identified. In some cases, utility streams can be included because it is not practical to
replace them by any form of heat recovery. For example, this is often the case for stream
dryers, ejectors and turbine drives.
Do not consider the existing plant layout. When selecting the inlet and outlet parameters
for a process stream, existing heat exchange equipment and plant topology should not be
taken into account at first. True utility targets (for cooling and heating) should be set
regardless of the existing plant layout. Current plant energy consumption can then be
compared with minimum energy targets. In retrofit of existing facilities, once these
targets have been determined, plant layout (existing heat exchangers and piping,
distances, etc) needs to be taken into account in order to identify practical and cost-
effective projects to reach or approach these targets.
Identify hard and soft constraints on temperature levels. For example, a hard constraint
would be the inlet temperature of a reactor that cannot be changed in any way, while a
soft constraint would be the discharged temperature of a product going to storage, for
which the target temperature is often flexible.
Data extraction is a complex issue, and a significant part of the pinch specialists
expertise is related to building a good pinch model during the data extraction phase.
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Lecture4
PINCH TECHNOLOGYAN OVERVIEW
Shabina Khanam
LecturerDepartment of Chemical Engineering
National Institute of Technology Rourkela, Rourkela769 008
One of the most practical tools to emerge in the field of process integration in the past 20
years has been pinch analysis, which may be used to improve the efficient use of energy,
hydrogen and water in industrial processes. Pinch analysis is a recognized and well-
proven method in each of the following industry sectors:
Chemical
Petrochemical
Oil refinery
Pulp and paper
Steel and metallurgy
Food and drink
Over the past 20 years, pinch analysis has evolved and its techniques perfected. It
provides tools that allow us to investigate the energy flows within a process, and to
identify the most economical ways of maximizing heat recovery and of minimizing the
demand for external utilities (e.g., steam and cooling water). The approach may be used
to identify energy-saving projects within a process or utility systems.
Pinch technology analyses process utilities (particularly energy and water) to find the
optimum way to use them, resulting in financial savings. Pinch Technology does this by
making an inventory of all producers and consumers of these utilities and then
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systematically designing an optimal scheme of utility exchange between them. Energy &
water re-use are at the heart of pinch technology. With the application of pinch
technology, both capital investment and operating cost can be reduced. Emissions can be
minimised and throughput maximised.
The Pinch Concept
Pinch analysis (or pinch technology) is a rigorous, structured approach that may be used
to tackle a wide range of improvements related to process and site utility. This includes
opportunities such as reducing operating costs, debottlenecking processes, improving
efficiency, and reducing and planning capital investment.
Major reasons for the success of pinch analysis are the simplicity of the concepts behind
the approach, and the impressive results it has been obtained worldwide. It analyzes a
commodity, principally energy (energy pinch) hydrogen (hydrogen pinch), or water
(water pinch), in terms of its quality and quantity, recognizing the fact that the cost of
using that commodity will be a function of both.
In general, we are using high-value utilities in our process and rejecting waste at a low
value. For example, if we consider energy, we may be burning expensive natural gas to
provide the process with high temperatures heat, and are rejecting heat at low
temperatures to cooling water or air.
Pinch analysis now has an establishment track record in energy saving, water reduction,
and hydrogen system optimization. In all cases, the fundamental principle, behind the
approach is the ability to match individual demand for a commodity with suitable supply.
The suitability of the match depends on the quality required and the quality offered. In
the context of utility management, the commodity may be heat, with its quality measured
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as temperature. By maximizing the match between supplies and demands, we minimize
the import of purchased utilities (Fig. 1).
Pinch Technology Versus Process Engineering
Pinch Technology is a vital subdivision of process engineering.
WASTE
(a)
Process
HIGH QUALITY UTILITY
QUANTITY
QUALITIY
(b)
Process
HIGH QUALITY UTILITY
WASTE
QUANTITY
QUALITY
Pinch
Pinch
ENERGY: WATER:HYDROGEN
MINIMISE
MINIMISE
Fig.1 Schematic process utility use
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Carrying out a process engineering project without the input of a pinch study will
lead to a less efficient design.
Our engineers have specialized knowledge of thermodynamics and computer
analysis tools. They can communicate effectively with clients and undertake
conceptual designs. This explains why we are uniquely qualified to help you get
the most out of your pinch projects.
How is Pinch technology different from other energy audits?
Pinch technology reveals all the possible savings and their corresponding Financial
benefits.
It defines the maximum possible savings.
It looks at the overall site.
It does not bench-mark but takes into account all specific mill factors, age,
location, process equipment, operating preferences, product, etc.
It reveals the maximum cogeneration potential.
Role of Thermodynamic Laws in Pinch Technology
Pinch technology presents a simple methodology for systematically analyzing chemical
processes and the surrounding utility systems with the help of the First and Second Laws
of Thermodynamics. The First Law of Thermodynamics provides the energy equation for
calculating the enthalpy changes (dH) in the streams passing through a heat exchanger.
The Second Law determines the direction of heat flow. That is, heat energy may only
flow in the direction of hot to cold. This prohibits temperature crossoversof the hot and
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cold stream profiles through the exchanger unit. In a heat exchanger unit neither a hot
stream can be cooled below cold stream supply temperature nor a cold stream can be
heated to a temperature more than the supply temperature of hot stream. In practice the
hot stream can only be cooled to a temperature defined by the temperature approachof
the heat exchanger. The temperature approach is the minimum allowable temperature
difference Tmin) in the stream temperature profiles, for the heat exchanger unit. The
temperature level at which Tminis observed in the process is referred to as "pinch point"
or "pinch condition". The pinch defines the minimum driving force allowed in the
exchanger unit.
What Processes does Pinch Apply to?
Pinch applies to a wide range of processes. Pinch originated in the petrochemical sector
and is now widely accepted in mainstream chemical engineering. With a wealth of
applications experience, benefits can now be realized in many other process industries.
Wherever heating and cooling of process materials takes places there is a potential
opportunity. A realistic approach addresses the practical problems specific to each and
every site, leading to:
Meaningful targets
Feasible projects
Real savings
Essential strategic insights
Benefits of Pinch Technology
Pinch tells the best that can be achieved in a given system.
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Pinch gives the practical target to aim for that is less than this theoretical
maximum.
Both of the above are done before any detailed design. This target then set the
basis for the design. Most importantly, it gives clear rules about how to construct
a design to achieve the targets. It will also show where the inefficiency lie in the
existing design.
Pinch takes a system-wide view of the problem. This allows one to see interaction
that would be difficult to spot on a process flow diagram or a flow sheet of site
utility system.
Pinch can work with incomplete data. One can refine the data in the areas where
accuracy is most important. This is in the area around the pinch.
Pinch Technology is in contrast to other design tools, which require detailed
information about geometry, flow sheet structure, etc. Pinch technology is one of
the few tools that really can be used in conceptual design.
Problem Addressed by Pinch Technology
Generally two types of problem are addressed:
Creating new designs
This is related to the design of HEN for a new plant, which is in design stage.
The ideal time to apply pinch analysis is during the planning of process
modifications that will require major investments, and before the finalization of
process design. Maximum improvements in energy efficiency; along with reduced
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investments can be obtained in a new plant design, since many plant layout and
process constraints can be overcome by redesign.
RetrofitRevamping existing designs
This is related to the retrofitting of an already existing HEN in a plant to improve
its exchange efficiency.
However, in retrofit projects, energy efficiency improvements usually require
some capital expenditure. In this case, pinch analysis can be specifically aimed at
maximizing the return of investment. Pinch analysis techniques allow us to
evaluate combinations of project ideas simultaneously, in order to avoid double
counting savings, as well as conflicting projects. Indeed, the final investment
strategy for the available opportunities will ensure that site development is
consistent and synergistic.
Typical Savings
BASF AG (Ludwigshafen, Germany), for example, has completed more than 150
retrofit using pinch technology, achieving over 25 % in energy savings site wide.
In natural gas sweetening, for example, The Ralph M. Parsons Co. (Pasadena,
Calif.) says that pinch technology led to a 10% drop in capital costs and energy
use in its amine absorption column.
GE plastics was faced with a requirement of invest $15 million in doubling the
capacity of the wastewater handling system of its Silicones Production Facilities
in Netherlands. Linnhoff March aimed to avoid this investment cost by reducing
wastewater flow by 50 %.
The following benefits have been obtained for refinery retrofits:
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a) Energy reduced by 15-35 % through revamping of HENs based on
paybacks of 1.5-3 years.
b) Units debottlenecked by 10-20% without modifying fired heaters or major
pumps.
c) Lower fouling from improved understanding of the system dynamics.
d) Improved flexibility giving the lowest cost design for different operating
cases.
e) Reduced emissions at the source.
The potential energy and water consumption savings in major industries sectors
are given in Fig. 2 & 3.
Fig. 2 Potential energy savings
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Fig. 3 Potential water consumption savings
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Lecture5, 6, 7
BASIC ELEMENTS OF PINCH TECHNOLOGYPART I, II & III
Bikash Mohanty
ProfessorDepartment of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee247 667
KEY STEPS OF PINCH TECHNOLOGY
There are four key steps of pinch analysis in the design of heat recovery systems for both
new and existing processes:
1) Data Extraction, which involves collecting data for the process and the utility
system.
2) Targeting, which establishes figures for best performance in various respects.
3) Design, where an initial Heat Exchanger Network is established.
4) Optimization, where the initial design is simplified and improved economically.
Data Extraction
The details of data extraction are discussed in Lecture 3.
Targeting
An important feature of Process Integration is the ability to identify Performance Targets
before the design step is started. For heat recovery systems with a specified value for the
minimum allowable approach temperature (Tmin), targets can be established for
Minimum Energy Consumption (external heating and cooling), Fewest Number of Units
(process/process heat exchangers, heaters and coolers) and Minimum Total Heat Transfer
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Area. In addition, the corresponding calculations will also identify the Heat Recovery
Pinch, which acts as a bottleneck for heat recovery.
Designing
Design of Heat Exchanger Networks in various industries is primarily carried out using
the now classical Pinch Design Method(Linnhoff and Hindmarsh, 1983). While the
original method focused on minimum energy consumption and the fewest number of
units, later graphical and numerical additions made it possible also to consider heat
transfer area and total annual cost during design.
The basic Pinch Design Method respects the decomposition at Process and Utility Pinch
points and provides a strategy and matching rules that enable the engineer to obtain an
initial network, which achieves the minimum energy target.
The Pinch Design Method also indicates situations where stream splitting is required to
reach the minimum energy target. Stream splitting is also important in area
considerations and the optimal use of temperature driving forces.
The design strategy mentioned above is simply to start design at the Pinch, where driving
forces are limited and the critical matches for maximum heat recovery must be selected.
Optimization
Heat exchange network for maximum energy recovery established by pinch design
method, should only be regarded as initial designs and some final optimization is
required. The matches in the initial network depend on pinch location and since the pinch
point depends on the value of Tmin, this becomes a key parameter in the pinch design
method. By repeating all calculations, for synthesis of HEN, for different values of Tmin,
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it is possible to identify a good starting value for the level of heat recovery. This exercise
of pre-optimization has been referred to as Supertargeting. For a typical Problem, the
minimum total annual cost is obtained to be 240.42103 $/yr (Fig. 1). Thus, the optimum
Tminis 13 C.
BASIC ELEMENTS OF PINCH TECHNOLOGY
Grid Representation
The grid is used to represent heat exchange network more conveniently. The important
features of grid representations are:
Hot streams (streams which require cooling) are drawn at the top running let to
right.
Cold streams (streams which require heating) are drawn at the bottom running
right to left.
The Total Annual Cost Profile
0
50
100
150
200
250
300
350
400
0 20 40 60
Minimum temperature difference
TAC(
1000$/yr)
TminOptimum = 13
Fig. 1 The total annual cost profile
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A heat exchanger is represented by a vertical line joining two open circles on the
streams being matched. The heat exchanger load can conveniently be written
under the lower open circle.
Heaters (H) and coolers (C) can be represented in an open circle on the stream
being heated or cooled.
Temperatures can be put on the grid as shown to allow an easy check on the
terminal approach temperature for each unit.
The stream data for the typical process is shown in Table 1. The grid representation for
this process, which includes two hot, H1 & H2, and two cold, C3 & C4, streams, are
shown in Fig.2.
Table 1 The Stream Data for the Process
Stream Ts(oC) Tt(
oC) MCp(kW/ C)
H1 175 45 10
H2 125 65 40
C3 20 155 20
C4 40 112 15
H
2
3
C
175
125
112
1400
98
85
1080
1300
1320
45
65
20
40
MCp (kW/ C)
10
40
20
15
Stream
H1
H2
C3
C4 2
Fig. 2 The grid representation of the process
3
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Composite Curve
The Composite Curves (CCs) are constructed from stream data representing a process
heat and material balance. The CCs allow the designer to predict-optimized-hot and cold
utility targets ahead of design, to understand driving forces for heat transfer, and to locate
the heat recovery Pinch. CCs consist of temperature-enthalpy (T-H) profiles of heat
availability in the process (the hot composite curves) and heat demands in the process
(the cold composite curves) together in a graphical representation. CCs also provide the
minimum requirement of hot and cold utilities in the process.
The construction of the hot composite curves (as shown in Fig.3) simply involves the
addition of the enthalpy changes of the streams in the respective temperature intervals.
The CCs for the stream data, given in Table 1, are shown in Fig.3. The QHmin and QCmin
are minimum hot and cold utilities.
0
50
100
150
200
0 1000 2000 3000 4000 5000
Heat Content Q (kW)
T (oC)
HCCCCC
Region of heat recovery byprocess to process exchange
QHmin
QCmin
Tmin
Abovepinch
Below
pinch
Fig. 3 The hot composite curves (HCC) and cold composite curves (CCC) respectivelyshow the heat availability and heat requirement for the overall process.
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Problem Table Algorithm
This graphical manipulation of composite curves to generate minimum targets is time
consuming and clumsy. An alternative procedure is entirely based on simply arithmetic
and involves no trial and error.
The procedure is known as the problem table and is broken down into three stages.
1. Set up shifted temperature intervals from the stream supply and target
temperatures by subtracting Tmin/2 from the hot streams and adding Tmin/2 to
the cols streams.
It is important to note that shifting the curves vertically does not alter the
horizontal overlap between the curves. It therefore does not alter the amount by
which the cold composite curve extends beyond the start of hot composite curve
at the hot end of problem. Also, it does not alter the amount by which hot
composite curve extends beyond the start of cold composite curve at the cold end.
2. In each shifted temperature interval, calculate a simple energy balance from:
(1)
Where Hi = heat balance for shifted temperature interval i and Hi is the
temperature difference across it
CPc= specific heat capacity of a cold stream (MW/oC)
CPh= specific heat capacity of a hot stream (MW/oC).
If the cold streams dominate the hot streams in a temperature interval, then the
interval has a net deficit of heat, and His positive. If hot streams dominate cold
streams, the interval has a net surplus of heat, and His negative.
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3. Now, cascade any surplus heat down the temperature scale from interval to
interval. This is possible because any excess heat available from the hot streams
in an interval is hot enough to supply a deficit in the cold streams in the next
interval down. First, assume no heat is supplied to the first interval from hot
utility. As a consequence of it some of the heat flows are negative, which is
infeasible. Heat cannot be transferred up the temperature scale. To make the
cascade feasible, sufficient heat must be added from hot utility to make the heat
flows to be at least zero. The smallest amount of heat needed from hot utility is
the largest negative heat flow.
Example
The problem table algorithm is explained using the stream data of a typical process given
in Table 2. The minimum approach temperature is 10 C. The shifted temperatures for
each stream are detailed in Table 3.
Table 2 Stream data
StreamHeat capacity flow rate
(MW/C)Ts(C) Tt(C)
Cold (C1) 0.2 20 180
Hot (H1) 0.15 250 40
Cold (C2) 0.3 140 230
Hot (H2) 0.25 200 80
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Table 3 Stream Data with Shifted Temperature
StreamHeat capacity flow rate
(MW/C)T*s(C) T*t(C)
Cold (C1) 0.2 25 185
Hot (H1) 0.15 245 35
Cold (C2) 0.3 145 235
Hot (H2) 0.25 195 75
The shifted temperatures are arranged in decreasing order. The stream population is
shown in Fig. 4 with a vertical temperature scale. The interval temperatures shown in Fig.
4 are set to Tmin /2 below hot stream temperatures and Tmin /2 above cold stream
temperatures.
Fig. 4 The stream population for stream
data shown in Table 2
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Then a heat balance is carried out within each shifted temperature interval according to
Eq. 1. The result is given in Fig. 5, in which some of the shifted intervals are seen to have
a surplus of heat and some have a deficit.
Fig. 5 The temperature interval heat balances
Now, cascade any surplus heat down the temperature scale from interval to interval
assuming no heat is supplied to the first interval from hot utility (Fig. 6). The first interval
has a surplus of 1.5 MW, which is cascaded to the next interval. This second interval has
a deficit of 6 MW, which leaves the heat cascaded from this interval to be -4.5 MW and
so on. Some of the heat flows are negative, which is infeasible. To make the cascade
feasible, largest negative heat flow from Fig. 6 that is 7.5 MW is added from hot utility to
make the heat flows to be at least zero. The revised cascade is shown in Fig. 7 which
gives one heat flow of just zero at an interval temperature of 145 C.
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More than 7.5 MW could be added from hot utility to the first interval, but the objective
is to find minimum hot and cold utility. Thus, from Fig. 7 minimum hot and cold utilities
are 7.5 MW and 10 MW, respectively. The point where the heat flow goes to zero at
shifted temperature 145C corresponds to the pinch. Thus, the actual hot and cold stream
pinch temperatures are 150 C and 140 C, respectively.
The composite curves are useful in providing conceptual understanding of the process but
the problem table algorithm is a more convenient calculation tool.
Fig. 6 Cascaded surplus heat from high to
low temperature
Fig. 7 Add heat from hot utility to make
all heat flows zero or positive
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Grand Composite Curve
The grand composite curve (GCC) is a graphical representation of the heat cascade. GCC
is based on the same process stream data as Composite Curves. GCCs highlight the
process/utility interface. It gives clear visualization of hot and cold utility and provides an
easy approach to use multiple utilities in the process. For the stream data, shown in Table
1, the GCC is represented in Fig. 8.
Maximum Energy Recovery
The overlap between the hot and cold composite curves represents the maximum amount
of heat recovery possible within the process. The source/sink characteristics of process
heat exchange systems give five concepts.
Targets: Once the composite curves are known, we know exactly how much external
heating/cooling is required. Near-optimal processes are confirmed as such and non-
optimal processes are identified with great speed and confidence.
PinchHigh temperature processsink profile
Low temperature process
source profile
Hot utility
Cold Utility
Process to processheat exchan e
Above Pinch
Below Pinch
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The pinch: The process needs external heating above the pinch and external cooling
below the pinch. This tells us where to place furnaces, steam heaters, coolers etc.
More in, more out: An inefficient process requires more than the minimum external
heating and therefore more than the minimum external cooling. For every units of excess
external heat in a process one has to provide heat transfer equipment twice. This insight
helps us to improve both energy and capital cost.
Freedom of choice: The heat sink and the heat source in Fig. 8 are separate. This
constraint helps the designer to choose plant-layouts, control arrangements etc. If
designer violates this constraint, he can evaluate the pinch heat flow and therefore predict
what overall penalties will be involved.
Trade-offs: A simple relationship exists between the number of streams (process streams
plus utilities) in a problem and the minimum number of heat exchange units (i.e. heaters,
coolers and interchangers).
Thus if designer goes for best energy recovery, designing the heat source and heat
sink section separately, he or she will incur the need for more units than if the pinch
division had been ignored. Hence a new type of trade-off has been identified, between
energy recovery and number of units. This insight adds to the traditional concept of a
trade-off between energy and surface area.
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Lecture8
AREA TARGETING
Bikash Mohanty
ProfessorDepartment of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee247 667
Area is important in determining heat exchanger network capital cost. Before explaining
the complete procedure to computation of area it is necessary to discuss the principles for
minimum area in heat exchanger networks.
Start by considering the example in Fig. 1a, where two hot streams exchange heat against
a single cold stream. If we assume the overall heat transfer coefficient U is constant for
all exchangers and these exchangers are countercurrent units then the network has an area
of 88 m2.
Fig. 1b shows a different network with stream splitting. Its area is 84 m2. The reason is
that it has better countercurrent behavior in terms of the overall network. In Fig. 1a the
matches are in temperature sequence whereas in Fig. 1b the matches share more of the
available temperature differences by splitting the cold stream. Fig. 1c shows that we can
do better still. The network area is now 77 m2. This is the minimum area for the stream
set as defined. The network has been developed by stream-splitting only where streams
compete for the same driving forces by overlap in temperature.
The composite curve of the data for example, shown through Fig. 1, is drawn in Fig. 2.
Overall countercurrent heat exchange now appears as vertical heat transfer on the
composite curves. Partitioning of the stream data to follow the temperatures of the
vertical model then leads to the minimum area design for this example.
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Fig. 1 (a) network with exchangers in temperature sequence on cold stream; (b) networkwith exchangers sharing temperature span of cold stream; and (c) network with
exchangers showing correct distribution of temperatures for minimum area.
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Fig. 2 Resolving temperature contention using the composite curves: (a) overallcountercurrent heat exchange appears as vertical heat transfer on the composites; (b) thetemperatures of enthalpy intervals show where stream-splitting will be required, (c) these
temperatures can be marked on the grid; and (d) used to guide design for temperaturecontention.
To calculate the heat exchanger network area from composite curve, utility streams must
be included with the process streams in the composite curves to obtain the balanced
composite curves (BCC). The resulting BCC (Fig. 3a) should have no residual demand
for utilities. The BCC are divided into vertical enthalpy intervals. The intervals are
defined whenever a change in slope occurs in either balanced composite profile. Next, a
network design is considered within each enthalpy interval, which can satisfy vertical
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heat transfer. Fig. 3b demonstrates this for an interval, which contains two hot streams
and three cold streams. Each hot stream is split into the same number of branches as the
number of cold streams in that interval. Similarly, each cold stream is split into the same
number of branches as the number of hot streams in that interval. Hence, each hot stream
can be matched with each cold stream such that every match occurs between the corner
temperatures of the enthalpy interval. The heat exchanger of these matches must
therefore appear as vertical on the BCC.
Fig. 3. Example of general stream splitting and matching scheme for vertical heattransfer in an enthalpy interval of the balanced composite curves.
The minimum total area could be taken as the sum of the areas of all such exchangers
from all enthalpy intervals. However, this is not necessary if U = constant. From the
composite curves, the area from vertical heat transfer in interval i is simply:
(1)
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where Hi is the enthalpy width of interval i and TLM,i is the logarithmic mean
temperature difference of interval i.
Hence, the total minimum network area is given by:
(2)
This shows that in order to derive an area target based on U = constant no design is
required.
Different heat transfer coefficients in the model for minimum area
Consider again the design in Fig. 3 for vertical heat transfer in enthalpy interval i of the
composite curves. If the heat transfer coefficients differ then the total area of these
exchangers is:
(3)Where, Q13is the duty of the match between streams 1 and 3, U13its overall heat transfer
coefficient, etc.
Now,
(4)
where h1 is the heat transfer coefficient of stream 1 (including film, wall and fouling
resistances), etc.
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So,
(5)
But
(6)
where (qj)iis the enthalpy change of stream j in enthalpy interval i.
so,
(7)
The argument applies in general for other enthalpy intervals. Summing up over all
intervals on the composite curves gives:
(8)
This simple formula incorporates stream individual heat transfer coefficients and allows a
target for the minimum heat exchange area to be calculated from the composite curves.
Further, within ithenthalpy interval, all hot streams undergo the same temperature change
(dTh)ias do all the cold streams (dTc)i. As q = MCpdT, then
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(9)
Example:
Stream Data of a typical process with Tmin= 20 Cis given in following table.
Stream(s) Ts (C) Tt (C) MCp (kW/ C) h (kW/m2 C)
H1 175 45 10 0.2
C1 20 155 20 0.2
H2 125 65 40 0.2
C2 40 112 15 0.2
Steam (HU) 180 179 - 0.2
Cold Water (CU) 15 25 - 0.2
The step wise procedure is described below:
Calculation of min imum hot and cold uti li ties
Minimum hot and cold utilities are calculated by Problem Table Algorithm which are as
follows:
Hot utility, Qhu,min= 605 kW
Cold utility, Qcu,min= 525 kW
Calculation of uti li ty flow rates
The MCpvalues of hot utility (hu) and cold utility (cu) are given as:
(MCp)hu= Qhu,min/(Tin-Tout)hu= 605/(180-179) = 605 kW/ C
(MCp)cu= Qcu,min/(Tout-Tin)cu= 525/(25-15) = 52.5 kW/ C
jc jc
p
ic
jh jh
p
ih
ervals
i
iLMh
MCdT
h
MCdTTA )()(/1
int
min
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Plotting the Balanced Composite Cur ves
The procedure for plotting the Balanced Hot Composite Curve and Balanced Cold
Composite Curve is the same as the Hot Composite Curve and Cold Composite Curve,
except that the utilities are also considered as additional streams.
Balanced Hot composite Curve (BHCC)
For BHCC the temperatures of hot streams and hot utility are arranged in ascending order
(Fig. 4). The sum of the MCPvalues of hot streams and utility present in each interval is
calculated. Then this sum is multiplied by the temperature difference of each interval.
After that a cumulative enthalpy is calculated using the formula:
CumQhb, i= CumQhb, i-1+ Qint, hbi (10)
Fig. 4 Data for balanced hot composite curve
Now, BHCC is obtained by plotting temperature and CumQhb as shown in Fig. 5.
Similarly Balanced cold composite curve can be drawn. The two curves are
superimposed on each other to get BCC as shown in Fig. 6. The BCC are divided into
vertical enthalpy intervals. The intervals are defined whenever a change in slope
occurs in either balanced hot composite curve (BHCC) and balanced cold composite
CumQhbQhb45
65
125
175
179
180
2
3
4
5
H1
H2
H
10
40
605
10
50
10
0
605
MCp,hb
3000
500
0
605
200 200
3200
3700
3700
4305
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curve (BCCC) profiles. The BCC on being divided into enthalpy intervals, allow
calculation of the area target based on a model of vertical heat transfer.
Fig. 5 Data for balanced hot composite curve
Fig. 6 The balanced composite curve for the example
0
20
40
60
80
100
120
140
160
180
200
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
Heat Content Q (kW)
T
(C)
BHCC
BCCC
Interval iTh,i.-1
Tc,i.-1
Th,i.
Tc,i.
0
20
40
60
80
100
120
140
160
180
200
0 1000 2000 3000 4000 5000
Heat content Q, kW
Temperature,
DegC
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Determination of enthalpies for in tervals
CumQhband CumQcb(for BCCC) are merged by omitting cumulative enthalpies common
to both values and the entries are then sorted in ascending order. This identifies all points
where composite curve has a vertex (change in slope).
Calculation of interval temperatur es on BHCC
The following formula is used for calculation of interval temperature:
Th3= Thb,row r(CumQhb,row r- CumQ3)/MCp,hb row r
Where, Thb,row rand CumQhb,row rare temperature and CumQ in the row r (in which the
temperature is available), In this case, row r = 6
For CumQi= 262.5 kW, Thi= 125 - (3200-262.5)/50 = 66.25C.
For CumQi= 200 kW, Tci= 20 - (262.5-200)/52.5 = 18.81C.
Similarly other temperature intervals are found and shown in Fig. 7.
Fig. 7 Determination of the enthalpy intervals
Calculation of (MCp/h)hand (MCp/h)cfor each interval
66.25
73.5
79.5
149.5
18.81
105
124.5
124.5
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These are calculated in a manner similar to MCp,hb of Fig. 4. For example, consider first
interval of Fig. 7 where only stream H1 exists, therefore (MCp/h)h = 10/0.2 = 50. Next
four interval contain streams, H1 and H2, thus, (MCp/h)h = 50/0.2 = 50. These data are
shown in Table 1.
Calculation of (Q/h)
For first interval, (Q/h) = (65 - 45)50 + (18.81 - 15)262.5 = 2000
The complete data are shown in Table 1.
Calculation of log mean temperatu re dif ference, TLM
This is done by the following formula:
For first interval:
TLM, 1= [(65-18.81)-(45-15)]/[ln(65-8.81)/(45-15) = 37.51 C.
The complete data are shown in Table 1.
Calculation of countercur rent exchanger area in each interval
This is calculated by dividing the (Q/h) by the corresponding TLMin for the interval.
For first interval: A1=2000/37.51 = 53.31 m2
The complete data are shown in Table 1.
Based on above calculation the minimum area is found as 1312.57 m2 for the example
undertaken.
1,1,
,,
1,1,,,
ln
)()(
icih
icih
icihicih
LM
TT
TT
TTTTT
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Table 1 Calculation of countercurrent exchanger area
nt Thi Tci (MCp/h)h (MCp/h)c (Q/h) TLM, i Ai
0 45 15 0 0 0 0 0
1 65 18.81 50 262.5 2000 37.51 53.31
66.25 20 250 262.5 625 46.22 13.52
73.5 25 250 362.5 3625 47.37 76.53
79.5 40 250 100 3000 43.85 68.42
5 125 105 250 175 22750 28.65 794
149.5 112 50 175 2450 27.84 88.01
7 175 124.75 50 100 2550 43.56 58.53
179 124.75 0 100 0 52.22 0180 155 3025 100 6050 37.76 160.23
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Lecture9 & 10
NUMBER OF UNIT, SHELL AND COST TARGETING
Shabina Khanam
LecturerDepartment of Chemical Engineering
National Institute of Technology Rourkela, Rourkela769 008
Number of unit targeting
The capital cost of chemical processes tends to be dominated by the number of items on
the flowsheet. This is certainly true of heat exchanger networks and there is a strong
incentive to reduce the number of matches between hot and cold streams.
To understand the minimum number of matches or units in a heat exchanger network,
Fig. 1 is considered which shows the heat loads on one hot stream and three cold streams
written within the circles representing the streams. The predicted hot utility load is shown
similarly. In this process only hot utility is required but no cold utility. The total system is
in enthalpy balance i.e. the total hot plus utility is equal to the total cold.
Matching Steam with Cold1 and maximizing the load completely satisfies or tick off
Steam, leaving 1165 units of heating required by Cold1. Matching Cold1 with Hot and
Steam
1068Hot
2570
Cold1
2233
Cold2
413
Cold3
992
Fig. 1 Illustration of minimum number of units design.
1068
1165 413 992
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maximizing the load on this match so that it ticks off the 1165 residual requirement on
Cold1, leaves 1405 residual heat available from Hot.
So following the principle of maximizing loads, i.e. ticking off stream or utility loads
or residuals, leads to a design with a total of four matches. This is in fact the minimum
for this problem.
Thus, Umin= N1
Where, Umin= minimum number of units (including heaters and coolers)
N = total number of streams (including utilities)
Another problem, Fig. 2(a) having two hot streams and two cold streams. Both hot and
cold utility are required. For this problem 5 (N-1) [Where, N = 6.0] units are required
which is obtained by putting the matches using ticking off loads or residuals loads to a
design.
Fig. 2(a). Number of unit is one less than the number of streams included utilities
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Fig. 2(b). Same principle for separate componentsSubset Equality
Fig. 2(c). One unit more for every loop
Fig. 2(b) shows a design having one unit less than previous design. The subset of streams
H2, C1 and CW is in enthalpy balance. Similarly, ST, H1 and C2 are in enthalpy balance
(which they must be if the total problem is in balance). What this means is that for the
given data set we can design two completely separate networks, with the formula Umin=
N1 applying to each individually. The total for the overall system is therefore (3-1)+(3-
1) = 4 units. This situation is termed subset equality
The new unit is placed between ST and C2 as shown in Fig. 2(c). The extra units
introduces what is known as a loop into a system. At the hot utility ST, the loop can be
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traced through the connection to C1, from C1 to H1, from H1 to C2, and from C2 back to
ST.
Suppose the new match, which is between ST and C2, is given a load of X units. Then by
enthalpy balance the load on the match between ST and C1 is 30-X, between C1 and H1,
10 + X, and between H1 and C2, 60-X.
The features discussed above are described by a theorem from graph theory in
mathematics, known as Eulers general network theorem. This theorem translates into the
terminology of HEN, states that
Umin= N + Ls
Where, Umin= minimum number of units (including heaters and coolers)
N = total number of streams (including utilities)
L = number of loops
s = number of separate components.
Normally we want to avoid extra units, and so design for L=0. Also, if there will be no
subset equality in the data set and then minimum number of unit targets is
Umin = N1
Since the pinch divides the problem into two thermodynamically independent regions, the
targeting formula must applied to each separately.
Shell Targeting
The shell and tube heat exchanger (SHE) is most common type of heat transfer
equipments used in heat exchanger networks (HENs) of chemical process industries.
Generally multipass SHE is employed in these industries because of its following
advantages: (1) the configuration gives a large surface area in a small volume, (2) good
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mechanical layout: a good shape for pressure operation, (3) uses well established design
procedures and fabrication techniques, (4) can be constructed from a wide range of
materials and (5) easily cleaned.
Many HEN design methods described in literature make the simplifying assumption of
counter current exchanger. It has been seen that an optimal solution of the HEN problem
based on purely counter current heat exchanger only will remain optimal in practice if
each unit can be realized by one exchanger with single shell. However, it rarely occurs in
industry as multipass construction of SHE is used here. Therefore, it is practically
feasible to target number of shells than the units at the synthesis stage of HEN.
FTCorrection Factor
In case of the simplest multipass SHE, the 1-2 type, the liquid in one tube pass flows in
counter flow while in the other pass flows in parallel relative to shell fluid. To account
counter and parallel flows in 1-2 SHE, a correction factor FTis introduced into the basic
heat exchanger design equation, shown through Eq. 1, to take into account the above
phenomena,
Q = UA (Tln) FT where 0< FT
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The FT factor is represented as the ratio of actual mean temperature difference in a 1-2
SHE to counter flow Tln for the same terminal temperatures. FT is a function of
dimensionless ratios, R and P, where
Heat capacity ratio, R = CPH/ CPC = ((TCoTCi) ((THiTHo) (2a)
and thermal effectiveness, P = (THi- THO) / (THiTCi) (2b)
where THi= Hot stream inlet temperature (oC)
THo= Hot stream outlet temperature (oC)
TCi= cold stream inlet temperature (oC)
TCo= cold stream outlet temperature (
o
C)
Based on the value of FT, feasible design of heat exchanger is screened amongst different
alternative designs. For this purpose a rule of thumb i.e. FT > 0.8 is used and each design
with unacceptably low FTvalue is discarded.
It is well known fact that for multipass exchangers heat recovery is limited by Tln
correction factor, FT. If FT
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)112/(RP 2max R (3)
Practical designs will be limited to some fraction of Pmaxthat is:
P = XPPmax 0 < XP< 1 (4)
Where XP is a constant defined by the designer. The value of XP= 0.9 is sufficient to
satisfy FT0.75, while also avoiding regions of steep slope and therefore assuring a more
reliable design.
Situations are often encountered where FTis too low (or within the present context the FT
slope too steep) for a single shell. If this happens the designer may be forced to consider
an arrangement of multiple shells in series. If multiple shells are required then the most
common practice is to adopt a trial and error approach in which the number of shells in
series is progressively increased until a satisfactory value of FTis obtained for each shell.
Using the constant XPapproach any need for trial and error can be eliminated since an
explicit expression for the number of shells can be derived. This is done by using the
following equation for N number of 1-2 shells in series.
R 1
N
rP
RPYwhere
YR
YP )
1
1(
1
2
21
(5a)
R = 1
12121
21
PNP
NPP (5b)
P1-2is the effectiveness of each single 1-2 shell (given by XP* Pmax) whereas P applies
overall to the series of shells. Equations (3) and (4) which together relate P 1-2to XPand
R, can then be used to eliminate P1-2from equation (5) to give the following expressions:
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The real (non-integer) number of shells target is then simply the sum of the real number
of shells from all the enthalpy intervals:
M
i
iishell SNN1
)1( (8)
where M is the total number of enthalpy, intervals on the balanced composite curves.
Furthermore, actual designs will normally observe the pinch division. Hence, Nshell
should be evaluated and taken as the next largest integer for each side of the pinch. The
number of shells target is then:
])[(])[(][ belowpinchshellabovepinchshellshell NNN (9)
Where the symbol [N] represents the next largest integer to the real number N.
Example
The Stream Data, shown through Table 1, is considered for this purpose. Here Tmin=
20 C.
Table 1 Stream data for a typical process
Hot utility inlet and outlet temperature are 180 C and 179 C.
Cold utility inlet and outlet temperature are 15 C and 25 C.
Calculation of P and R for an in terval
Stream Type Supply temp.
TS(C)
Target temp.
TT(C)
Heat capacityflow rate MCp
(kW/ C)
H1 Hot 175 45 10
H2 Hot 125 65 40
C3 Cold 20 155 20
C4 Cold 40 112 15
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The temperature effectiveness, P, is defined as the ratio of the temperature change in one
of the streams to the maximum possible temperature difference.
Pi= (Th,i.Th,i.-1) / (Th,i.Tc,i.-1)
For i= 1, P1= (65 - 45) / (65 - 15) = 0.4
R is defined as the ratio of the heat capacity flow rates of the hot streams to the cold
streams.
Ri= (Tc,i.Tc,i.-1) / (Th,i.Th,i.-1)
For i=1, R1= (18.81 - 15) / (65 - 45) = 0.1905
The complete calculation is shown in Table 2.
Calculation of the temperature eff ectiveness of an i ndividual 1-2 exchanger
P12= XPPmax where )112/(RP2
max R
For i.=1 and XP= 0.9,
P12,i.=1 = 0.9 * 2 / (0.1905+1+(0.19052+1)1/2) = 0.815
Calculation of number of 1-2 shell s needed in ser ies
N = ln [(1-RP)/(1-P)]ln[(1-RP12)/(1-P12)] for R 1
And
N = [P/(1-P)]/[P12/(1-P12)] for R = 1
For i = 1,
N = ln [(1-0.1905*0.4) / ln [(1-0.1905*0.815) / (1-0.815)]
= 0.2841.
The complete calculation is shown in Table 3.
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Table 2 Determination of P and R for non countercurrent flow
Table 3 Determination of number of Shells for each enthalpy interval
Calculation of number of shells in an i nterval (Ni[Si1])
The minimum number of shells in an enthalpy interval, i, is Ni(