Spatial Flow-Field Approximation Using Few Thermodynamic Measurements Part II: Uncertainty Assessments

by   Pranay Seshadri, et al.

In this second part of our two-part paper, we provide a detailed, frequentist framework for propagating uncertainties within our multivariate linear least squares model. This permits us to quantify the impact of uncertainties in thermodynamic measurements---arising from calibrations and the data acquisition system---and the correlations therein, along with uncertainties in probe positions. We show how the former has a much larger effect (relatively) than uncertainties in probe placement. We use this non-deterministic framework to demonstrate why the well-worn metric for assessing spatial sampling uncertainty falls short of providing an accurate characterization of the effect of a few spatial measurements. In other words, it does not accurately describe the uncertainty associated with sampling a non-uniform pattern with a few circumferentially scattered rakes. To this end, we argue that our data-centric framework can offer a more rigorous characterization of this uncertainty. Our paper proposes two new uncertainty metrics: one for characterizing spatial sampling uncertainty and another for capturing the impact of measurement imprecision in individual probes. These metrics are rigorously derived in our paper and their ease in computation permits them to be widely adopted by the turbomachinery community for carrying out uncertainty assessments.



There are no comments yet.


page 3

page 13

page 14

page 16

page 18


Optimization of Model Parameters, Uncertainty Quantification and Experimental Designs for a Global Marine Biogeochemical Model

Methods for model parameter estimation, uncertainty quantification and e...

How certain are your uncertainties?

Having a measure of uncertainty in the output of a deep learning method ...

Shades of Dark Uncertainty and Consensus Value for the Newtonian Constant of Gravitation

The Newtonian constant of gravitation, G, stands out in the landscape of...

Environmental Economics and Uncertainty: Review and a Machine Learning Outlook

Economic assessment in environmental science concerns the measurement or...

Spatial Flow-Field Approximation Using Few Thermodynamic Measurements Part I: Formulation and Area Averaging

Our investigation raises an important question that is of relevance to t...

GOTM: a Goal-oriented Framework for Capturing Uncertainty of Medical Treatments

It has been widely recognized that uncertainty is an inevitable aspect o...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.