W. Glenn Steele

A Methodology for Determining Experimental Uncertainties in Regressions

A methodology to determine the experimental uncertainties associated with regressions is presented. When a regression model is used to represent experimental information, the uncertainty associated with the model is affected by random, systematic, and correlated systematic uncertainties associated with the experimental data. The key to the proper estimation of the uncertainty associated with a regression is a careful, comprehensive accounting of systematic and correlated systematic uncertainties. The methodology presented in this article is developed by applying uncertainty propagation techniques to the linear regression analysis equations. The effectiveness of this approach was investigated and proven using Monte Carlo simulations. The application of that methodology to the calibration of a venturi flowmeter and its subsequent use to determine flowrate in a test is demonstrated. It is shown that the previously accepted way of accounting for the contribution of discharge coefficient uncertainty to the overall flowrate uncertainty does not correctly account for all uncertainty sources, and the appropriate approach is developed, discussed, and demonstrated.

Performance comparison of high‐temperature packed bed operation with PCM and sensible‐heat pellets

A comparison is made between two specific thermal energy storage materials, zirconium oxide (ZrO 2 ) as a sensible-heat material and a salt/ceramic composite (Na 2 SO 4 /SiO 2 ) as a phase change material, for high-temperature applications. Second-law thermodynamic analyses along with material stability tests are employed as criteria for the assessment of these materials. To facilitate the analysis, case studies are presented, and the thermal behaviour of the packed bed for each scenario is simulated by an experimentally validated computational model. The case studies are designed to examine the role of the heat of fusion and the material quantity in the thermal performance of the packed bed. For stability evaluation, these materials are exposed to a number of thermal cycles in a high temperature test environment. The zirconium oxide pellets not only offer excellent physical stability but prove to be thermodynamically promising as well.

Implications of Correlated Bias Uncertainties in Single and Comparative Tests

The effects of correlated bias uncertainties are considered for both single and comparative tests, and the implications of these effects on experimental results and their uncertainties are investigated. In single tests, correlated bias uncertainties can cause a significant increase or a significant decrease in uncertainty in the result as compared to the uncertainty when there are no correlation effects. In comparative tests, the experimental result is the difference of two test results or the ratio of two test results. If the same test apparatus and instrumentation are used to obtain the two test results, the systematic uncertainty in the difference or the ratio can be significantly less than the systematic uncertainty in the individual test results. However, the effects of systematic uncertainties do not cancel out in comparative tests in which the result is the difference in the results of two tests, contrary to assertions made in some engineering standards.

Uncertainty Analysis of the Mechanical Response of Porcine Brain at High Strain Rate Compression

The Split-Hopkinson Pressure Bar (SHPB) apparatus presents a unique capability in studying the dynamic response of a material, but it is accompanied with a moderately high noise level, giving a rather large standard deviation for the stress-strain behavior of the soft biological material being tested [1]. Compounding the errors in a SHPB setup is the uncertainty arising from sample-to-sample variability in a soft biological material. Uncertainties arise in a measured variable through a vast number of sources such as an imperfect instrument calibration process, standards used for calibration, and the influence of the measured variable due to inconsistencies in ambient temperature, pressure, humidity and vibrations.Copyright

Implementing New Uncertainty Guidelines and Standards in Turbine Testing

The use and application of uncertainty analysis in engineering has evolved considerably over the past decade. The methods formulated in the 1970’s and 1980’s that were incorporated into ANSI/ASME Standards and that were used during the AGARD-sponsored Uniform Engine Test Programme (UETP) have been superseded by more rigorous approaches. In this paper, the uncertainty methodogy used in the UETP is compared with the newer approaches that will need to be implemented in future turbine test programs.Copyright

Uncertainty analysis of rocket motor thrust measurements with correlated biases

Abstract The uncertainty analysis of a rocket motor thrust measurement and calibration system is presented. The thrust measurement system has 10 load cells with 5 in tension and 5 in compression, and the calibration system has 6 load cells. The elemental sources of load-cell random uncertainty considered are excitation voltage, amplifier stability and noise, and analog-to-digital conversion resolution. The elemental sources of load-cell systematic uncertainty (bias) considered are calibration, excitation voltage, nonlinearity, hysteresis, system alignment, and other mechanical sources such as friction. The calibration hierarchy and excitation systematic uncertainties are correlated since they have a common source. These correlation effects dominate the resulting thrust measurement uncertainties and form the focus of this study. The trust measurement uncertainty is up to three and a half times larger when correlation effects are considered relative to the case where correlation is neglected.