Fire testing is one of the most critical and expensive aspects when developing intumescent products to protect steel structures from fire. Understanding the nature and performance of a furnace during testing is imperative for reliably interpreting the results from formulation development.

In this case, the temperature data from sensors (thermocouples) in bespoke furnaces were utilised in JMP Pro to establish and understand positional temperature profiles while minimising test runs. The Functional Data Explorer was deployed as a dimension-reducing technique to describe temperature-time curves in terms of their principal components, enabling their positional element to be understood and compared directly. FPCA Score Plots showed clustering of positionally equivalent sensors with repeating tests, giving confidence in the reliability of consistent temperature profiles.

Furthermore, FDOE simulation in combination with a 3D scatter plot gave dynamic understanding of temperature distributions at varying time intervals making it easy for chemists and managers to communicate. This approach not only resulted in significant test cost savings, but allowed for greater insight into the trends of the furnace, which would have been impossible using conventional analysis techniques. Analysis aligned well with expectations of a temperature gradient towards the back of the furnace from air movement to smoke exhaust.

Presenter

Schedule

Wednesday, 12 Mar
15:30-16:15

Room: Salon 7-Vienna

Skill level

Intermediate
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Published on ‎12-15-2024 08:23 AM by Community Manager Community Manager | Updated on ‎01-16-2025 12:31 PM

Fire testing is one of the most critical and expensive aspects when developing intumescent products to protect steel structures from fire. Understanding the nature and performance of a furnace during testing is imperative for reliably interpreting the results from formulation development.

In this case, the temperature data from sensors (thermocouples) in bespoke furnaces were utilised in JMP Pro to establish and understand positional temperature profiles while minimising test runs. The Functional Data Explorer was deployed as a dimension-reducing technique to describe temperature-time curves in terms of their principal components, enabling their positional element to be understood and compared directly. FPCA Score Plots showed clustering of positionally equivalent sensors with repeating tests, giving confidence in the reliability of consistent temperature profiles.

Furthermore, FDOE simulation in combination with a 3D scatter plot gave dynamic understanding of temperature distributions at varying time intervals making it easy for chemists and managers to communicate. This approach not only resulted in significant test cost savings, but allowed for greater insight into the trends of the furnace, which would have been impossible using conventional analysis techniques. Analysis aligned well with expectations of a temperature gradient towards the back of the furnace from air movement to smoke exhaust.



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Starts:
Wed, Mar 12, 2025 10:30 AM EDT
Ends:
Wed, Mar 12, 2025 11:15 AM EDT
Salon 7-Vienna
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