Traditional heat exchanger design and monitoring methodologies rely on the use of fixed fouling factors to account for the reduced thermal performance of heat exchangers operating in non-clean services. This practice has been criticised in the past as it does not account for the dependency of the underlying fouling mechanisms on process conditions and time, often leading to oversized equipment that exacerbates fouling.
Neglecting fouling dynamics and its dependence on process conditions at the design stage has also been identified as the cause of major failures. In recognition of these limitations, much research effort has been put in recent years to improve the fundamental understanding of the various fouling mechanisms and industry has started shifting to a different paradigm which involves the use of system-specific models to account for the fouling dynamics at the design stage.
This webinar will point out severe limitations of the fouling factor approach and will propose novel methodologies for the design and predictive maintenance of heat exchanger networks. These methods leverage the combination of big data, advanced analytics and multi-scale modelling to improve design, optimise operations, maximise production and minimise maintenance, resulting in significant economic and environmental benefits.
Industrial case studies will be shown to illustrate methodology and benefits.
Attend this webinar to:
- Grain an awareness of limitations of current heat exchanger design and monitoring practice and new approaches available to overcome them
- Knowledge of causes and mechanisms of fouling and possible mitigation solutions
- Understanding of benefits associated with improved design and monitoring methodologies of heat exchangers and heat exchangers networks
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