How do you validate and verify the aerothermodynamic data from hypersonic wind tunnel tests?

1 Validation vs Verification

Validation and verification are two related but distinct concepts in engineering. Validation means checking whether the data you obtain from the tests match the real-world phenomena you are trying to model. Verification means checking whether the data you obtain from the tests are consistent with the assumptions and methods you use to conduct the tests. Both validation and verification are essential for ensuring the quality and credibility of your aerothermodynamic data.

2 Uncertainty Analysis

One of the first steps in validating and verifying your data is to perform an uncertainty analysis. This involves quantifying the sources and magnitudes of errors and uncertainties that may affect your data, such as measurement errors, instrumentation errors, calibration errors, test conditions variations, and model uncertainties. By doing an uncertainty analysis, you can estimate the confidence intervals and error bounds of your data, as well as identify the most sensitive and influential parameters.

3 Data Reduction

Another step in validating and verifying your data is to perform a data reduction. This involves processing and transforming your raw data into meaningful and useful quantities, such as pressure, temperature, heat flux, drag, lift, and aerodynamic coefficients. Data reduction may require applying correction factors, scaling laws, dimensionless parameters, and curve fitting techniques. By doing a data reduction, you can simplify and standardize your data, as well as compare them with other sources of data.

4 Data Comparison

A key step in validating and verifying your data is to perform a data comparison. This involves comparing your data with other relevant data, such as theoretical predictions, numerical simulations, empirical correlations, or experimental results from other facilities or configurations. Data comparison may require using appropriate metrics, criteria, and statistical methods to assess the agreement or discrepancy between different data sets. By doing a data comparison, you can evaluate the validity and accuracy of your data, as well as identify the sources and causes of discrepancies.

5 Data Interpretation

The final step in validating and verifying your data is to perform a data interpretation. This involves analyzing and explaining your data in terms of the underlying physical phenomena, mechanisms, and principles that govern the aerothermodynamics of hypersonic flows. Data interpretation may require using relevant theories, models, and concepts, such as shock waves, boundary layers, viscous effects, chemical reactions, radiation, and ablation. By doing a data interpretation, you can understand the significance and implications of your data, as well as generate new insights and hypotheses.

6 Validation and Verification Tools

In order to facilitate the validation and verification process, there are a number of tools and software available. The Uncertainty Quantification Toolbox (UQT) is a MATLAB-based tool that can be used for uncertainty analysis, sensitivity analysis, and reliability analysis. The Data Reduction and Analysis Tool (DRAT) is a Python-based tool for data reduction, data visualization, and data comparison. Computational Fluid Dynamics (CFD) is a numerical method that can help simulate and predict the aerothermodynamics of hypersonic flows, as well as compare them with experimental data. The Aerothermodynamic Analysis System (AAS) is a software suite for data interpretation, correlation, and extrapolation.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?