The Role Of Numerical Simulation In Laboratory Uncertainty Assessment At The Introductory Engineering Physics Level
- Conference
- Location
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Chicago, Illinois
- Publication Date
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June 18, 2006
- Start Date
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June 18, 2006
- End Date
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June 21, 2006
- ISSN
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2153-5965
- Conference Session
- Tagged Division
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Division Experimentation & Lab-Oriented Studies
- Page Count
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10
- Page Numbers
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11.1328.1 - 11.1328.10
- DOI
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10.18260/1-2--219
- Permanent URL
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https://peer.asee.org/219
- Download Count
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415
Paper Authors
Charles Neuman Queensborough Community College
Charles Neuman is an Assistant Professor of Physics at Queensborough Community College of the City University of New York. His research interests include accelerator physics, free electron lasers, and education. He also serves as PI on a CUNY grant on education research.
David Lieberman Queensborough Community College
David Lieberman is a Professor of Physics at Queensborough Community College of the City University of New York. His research interests include bio-physics, laser, and education. He had several NSF grants and is currently serving as PI on a NSF grant on designing remote laser laboratory for teaching technicians
Don Engelberg Queensborough Community College
Don Engelberg is a Professor of Physics at Queensborough Community College of the City University of New York. His research interests include nuclear physics, laser physics, and education. He was awarded several NSF grants and is currently serving as PI on a NSF grant in laser physics education.
Alex Flamholz Queensborough Community College
Alex Flamholz is an Assistant Professor of Physics at Queensborough Community College of the City University of New York. His research interests include bio-physics, electronics, and education. He worked in photonics research and development at IBM for many years before returning to teaching recently.
Paul Marchese Queensborough Community College
Paul Marchese is an Assistant Professor of Physics at Queensborough Community College of the City University of New York. His research interests include geophysics, laser physics, and education. He also serves as PI on a NSF geophysics grant.
George Tremberger Queensborough Community College
George Tremberger, Jr. is a Lecturer in the Physics Department of Queensborough Community College of the City University of New York. His research interests include astronomy, anthropology, and education. He also serves as PI on a CUNY grant for exo-planet study.
Tak Cheung Queensborough Community College
Tak David Cheung is a Professor of Physics at Queensborough Community College of the City University of New York. His research interests include bio-physics, astronomy, and education. He also serves as PI on a CUNY grant in bio-physics.
Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract
The role of numerical simulation in laboratory uncertainty assessment at the introductory engineering physics level
Abstract
The teaching of laboratory uncertainty assessment via numerical simulation is used to supplement the pedagogy of discovery based learning at the introductory engineering level. The typical laboratory uncertainty assessment methods such as comparing the result to a directly measured quantity and assessing error bars on graph were extended to include the use of numerical simulation in more complex situations. In this paper, laboratory exercises in force- distance relationship, equipotential lines, RLC circuit with hysteresis loss, radiation, optics and null measurement were presented. Null measurement where the system approach to null is non- linear (the measured quantity is affected by the off-null condition) was also presented. The laboratory setups were analyzed using numerical stimulation in analogy to real situations where there are no closed form mathematical expressions. The effects on the numerical simulation given a range of input parameter changes were used to assess the laboratory exercise uncertainties. Besides the applicability to realistic situations in a workplace, the numerical simulation also has an advantage of setting the student’s attitude to understand the difficulties of the associated inverse problems, which usually are the problems that demand attention in a workplace. The disadvantage of the time-consuming repetitious computational tasks in the numerical simulation could be offset with well-designed computer techniques, using spreadsheets or introductory Visual Basic. The pedagogy of discovery base learning with this numerical simulation feature was shown to have a positive effect through the students' questions as well as grade improvement.
Introduction
One of the most important functions of an introductory engineering physics course is to provide a solid foundation for advancement into higher level courses in the various engineering disciplines. In fact, an engineering physics program, together with courses, could be viewed as a universal donor 1. Fundamental concepts are usually covered in introductory engineering physics course. However, it was reported in a recent 2005 case study that some 10 to 15% of senior engineering students still have confusion about the difference of energy and temperature 2. The finding is consistent with an earlier 2000 report that some students identify movement of electricity and energy transfer as material flows, completely missing the concepts of random diffusion and collision3. The concept of randomness is usually first taught as an uncertainty assessment in a laboratory setting. The typical laboratory uncertainty assessment methods such as comparing the result to a directly measured quantity (using a formula to express the deviation as percent difference) and assessing error bars on graph are usually taught in the first semester. Some aspects of uncertainty or error come from randomness. Randomness is more than a formula. Thus, sometimes a formula is not sufficient. We have extended these typical assessment methods to include the use of numerical simulation in more complex situations.
In this paper, laboratory exercises in force-distance relationship, equipotential lines, hystersis loss, radiation, optics and null measurement are presented. Null measurement where the system approach to null is non-linear (the measured quantity is affected by the off-null condition) is also
Neuman, C., & Lieberman, D., & Engelberg, D., & Flamholz, A., & Marchese, P., & Tremberger, G., & Cheung, T. (2006, June), The Role Of Numerical Simulation In Laboratory Uncertainty Assessment At The Introductory Engineering Physics Level Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--219
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