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HEAT EXCHANGER NETWORK SYNTHESIS

HEAT EXCHANGER NETWORK SYNTHESIS banner
Live online Intermediate

HEAT EXCHANGER NETWORK SYNTHESIS

4(14)
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$ 100
8 hrs
Next month
English
109 views
Enggenious (SAN Techno Mentors)
Enggenious (SAN Techno Mentors)
  • 7-day money-back guarantee
  • Session recordings included
  • Certificate of completion

Why enroll

  • Learn the techniques of heat exchanger network synthesis

  • Learn principles of optimization of processes by energy and resource analysis.

  • Learn how utility cost can be minimized

Is this course for you?

You should take this if

  • You work in Energy & Utilities or Nuclear & Power
  • You're a Chemical & Process / Mechanical Engineering professional
  • You have some foundational knowledge in the subject
  • You want to build skills in Corrosion, Energy efficiency optimization

You should skip if

  • You're looking for an introductory overview course
  • You need a different specialisation outside Chemical & Process
  • You need fully self-paced, on-demand content

Course details

Improving performance of a chemicals manufacturing facility is an ongoing process that must continue throughout the life of the plant.

Efficient use of heat can reduce the energy consumption which in turn reduces manufacturing costs. Networking of heat exchangers is a technique by which use of external utilities like, steam, cooling water, hot oil, chilled water, chilled brine etc., can be minimized. This can be achieved by exchanging heats of hot/cold of process streams with each other.

Network design methods are simple to understand and implement. Their main advantage is that they can be deployed prior to equipment design stage using only the process stream data. These methods can also be used in existing running plants under certain operating constraints. The network design provides optimum numbers and locations of heat exchangers within the processing train.

While designing the network, the optimization criteria used could be - minimization of external energy usage, minimization of heat transfer area or minimization of total annual cost.

This course also presents an example of optimization of number of effects of a multiple effect evaporator using the principles of optimization of processes by energy and resource analysis.

While the course presumes that the attendees possess Chemical Engineering background, other engineers from Process industries would also find the course useful.

Course suitable for

Key topics covered

Module 1 - Introduction, pinch technology, problem table algorithm, calculation of target area of heat exchanger networks

Module 2 - Countercurrent and mixed flow targets, cost targeting, rapid Sizing of heat exchangers, principles of optimization of Processes by energy and resource analysis

Opportunities that await you!

Skills & tools you'll gain

CorrosionEnergy efficiency optimizationEngineering & DesignGD&TPiping Layout

Career opportunities

Training details

This is a live course that has a scheduled start date.

Why people choose EveryEng

Industry-aligned courses, expert training, hands-on learning, recognized certifications, and job opportunities-all in a flexible and supportive environment.

$100

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Questions and Answers

A: Choosing A risks validating thermal performance on a configuration that may already violate the pinch intent due to misrouted lines. Choosing B can force heat across the pinch during warm-up and mask a permanent routing error. Choosing D gives you good data on a fundamentally wrong network topology. Choosing C prevents irreversible heat integration errors before any thermal assumptions are tested.

A: Choosing A assumes linear LMTD behavior and ignores pinch-limited matches. Choosing B confuses energy recovery targets with exchanger sizing drivers. Choosing D exaggerates the penalty and doesn't match typical counter-current exchanger physics. Choosing C reflects the reduced driving force concentration around the pinch where most area accumulates.

A: Choosing A usually shifts totals but doesn't create a structural HEN error. Choosing B introduces minor numerical noise without changing match feasibility. Choosing C is within typical targeting tolerance and rarely changes topology. Choosing D indicates a fundamental violation that invalidates the entire synthesis regardless of numbers.

A: Choosing A hides a physical measurement problem and feeds bad data into the network. Choosing B assumes a failure mode without evidence and can bias heat recovery. Choosing D forces process behavior to match faulty instrumentation. Choosing C checks that the temperature basis for the pinch is even real.