Educational: Analyzing the Sensitivity of Process Heat Transfer Models Webinar
June 21, 2023 | 9:00 AM CDT (UTC -05:00)
Process heat transfer models produce different results depending on the specific range(s) of input used. Ensuring that a model is robust and accurate across the range of inputs involves determining the amount or degree of that variation. This sensitivity analysis allows both physical and black-box models to be refocused or refined most effectively.
In the context of heat transfer applications, sensitivity analysis is an important preprocessing step to identify a subset of the many input variables for the initial model building effort. Further, input values, including measurements, often include some uncertainty that the models should take into account. In this webinar, we review common local and global approaches to determine the sensitivity of a model output to specific input.
Registration deadline: June 19, 2023 (11:59 PM US Central Time)
Facilitated by Parimah Kazemi
Numerical Analyst, earned a BS in Mathematics and Chemistry and a PhD in Mathematics from the University of North Texas, Denton, Texas, USA. Following graduation, she worked as a Postdoctoral, Visiting Assistant Professor, and Senior Analyst before joining HTRI. She has authored scientific publications in refereed journals on scientific computation, physics, and analysis, as well as given presentations both nationally and internationally. At HTRI, her expertise in mathematical modeling, numerical analysis, and scientific computing is focused on the solution of heat exchange problems using state-of-the-art and proven mathematical and numerical techniques. Her skills in data science—specifically, machine learning and artificial neural networks—have increased the usability and value of HTRI's extensive and growing empirical data sets.