Associate Professor of Mechanical Engineering

Northern Illinois University

www.kostic.niu.edu

Uncertainty or error analysis of measurement results is not a deterministic (exact), but rather holistic and probabilistic in nature. Its complexity and ambiguity (not only what is measured, but what contributes to measurement errors and uncertainty, the latter being open ended), contributes that the uncertainty analysis is often misunderstood, misrepresented or even avoided. An almost impossible task is attempted here: to try to resolve existing confusion, to embrace the very concept of measurement uncertainty, and to provide effective guidelines to account for the most contributing sources of errors (which is important and possible!), since accounting for all sources of measurement errors is not necessary (and also impossible).

About the Presenter:

M. KOSTIC is an Associate Professor in the Department of Mechanical Engineering at Northern Illinois University. He received his Ph.D. from the University of Illinois, and then worked in industry for some time. Professor Kostic's teaching and research interests are Thermodynamics, Fluid Mechanics, Heat Transfer and related energy sciences; with emphases on new technologies, experimental methods, creativity, design, and computer applications (www.kostic.niu.edu ).

At Ohio Aerospace Institute Lecture Hall

Friday, August 1, 2003, 2:00 p.m.,

Refreshments Available at 1:30 p.m.

Presentation handouts:
http://www.kostic.niu.edu/NASA-FFP03Kostic(D).pdf

Manuscript:
http://www.kostic.niu.edu/Uncertainty%20Analysis%20of%20Measurement%20Results.pdf

References

[ 1] Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results, NIST Technical Note 1297, 1994 Edition
http://physics.nist.gov/Pubs/guidelines/TN1297/tn1297s.pdf , July 2003.

[ 2] Galleries of Probability Distributions: NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/eda/section3/eda366.htm , July 2003.

[ 3] R.H. Dieck, "Measurement Accuracy" a chapter in "The Measurement, Instrumentation and Sensors Handbook" (J.G. Webster, Editor-in-Chief), ISBN: 0-8493-8347-1, CRC Press, 1999.

[ 4] NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/, July 2003.

[ 5] Tables for Probability Distributions: NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/eda/section3/eda367.htm , July 2003.

[ 6] R.S. Figliola, and D.E. Beasley, Theory and Design for Mechanical Measurements - 3rd Edition, Wiley, 2000.