FSG3130 Uncertainty Analysis 5.0 credits

Osäkerhetsanalys

The student will be able to discuss general issues regarding mainly experimental uncertainties relevant for measurements with special focus to fluid dynamic systems, the difference between systematic and random errors (bias and uncertainty), confidence intervals, calibration errors, error propagation in data reduction equations, regression analysis etc. There will also be a discussion about how to determine the uncertainty propagation by using Monte Carlo analysis. The uncertainty analysis will be exemplified through discussion of various real-life experiments (and to some extent simulations). Although many of the examples are taking from the fluid dynamics field, the discussion of the uncertainty analysis is general and can be applied to many other scientific fields.

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Course information

Content and learning outcomes

Course contents *

  1. Experimentation, Errors and Uncertainty
  2. Errors and Uncertainties in a Measured Variable
  3. Uncertainty in a Result Determined from Multiple Variables
  4. General Uncertainty Analysis. Planning an Experiment and Application in validation
  5. Detailed Uncertainty Analysis: Designing, Debugging, and Executing an Experiment
  6. Validation of Simulations
  7. Data Analysis, Regression, and Reporting of Results

Intended learning outcomes *

The student will be able to discuss general issues regarding mainly experimental uncertainties relevant for measurements with special focus to fluid dynamic systems, the difference between systematic and random errors (bias and uncertainty), confidence intervals, calibration errors, error propagation in data reduction equations, regression analysis etc. There will also be a discussion about how to determine the uncertainty propagation by using Monte Carlo analysis. The uncertainty analysis will be exemplified through discussion of various real-life experiments (and to some extent simulations). Although many of the examples are taking from the fluid dynamics field, the discussion of the uncertainty analysis is general and can be applied to many other scientific fields. After completing this course the student should be able to:

  • distinguish between random and systematic (uncertainty and bias) error.
  • understand basic statistical concepts and the meaning of confidence intervals.
  • calculate uncertainty in a measured variable based on the Taylor series method.
  • perform a Monte-Carlo based uncertainty analysis.
  • evaluate how long time a variable need to be sampled in order to obtain a certain accuracy in the measured/simulated statistics.
  • handle outliers in a reliable and systematic way.
  • design, debug and execute an experiment.
  • understand the difference between validation and verification of simulations, and how validation can be performed.
  • do an accurate regression analysis.

Course Disposition

The lecture part of the course is given in a compressed time scale with approximately 20h of lectures during 1-2 weeks.

Literature and preparations

Specific prerequisites *

A master degree in a mechanics related area is recommended.

Recommended prerequisites

A master degree in a mechanics related area.

Equipment

No information inserted

Literature

H.W. Coleman & W. Glenn Steele: Experimentation, validation, and Uncertainty Analysis for Engineers

(3rd Edition), Wiley

Examination and completion

Grading scale *

P, F

Examination *

  • DEL1 - Participation, 1.0 credits, Grading scale: P, F
  • INL1 - Assignment, 4.0 credits, Grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

DEL1 Participating 1,0 hp (P, F)

INL1 Assignment 4,0 hp (P, F)

Other requirements for final grade *

The following items have to be approved in order to obtain a pass on the course:

  • Compulsory and active attendance during at least 80% of the lecture time
  • Successful completion of homework assignment within given time frame

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

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Examiner

Henrik Alfredsson

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web FSG3130

Offered by

SCI/Mechanics

Main field of study *

No information inserted

Education cycle *

Third cycle

Add-on studies

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Contact

Henrik Alfredsson

Ethical approach *

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Supplementary information

The lecture part of the course is given in a compressed time scale with approximately 20h of lectures during 1-2 weeks.

Postgraduate course

Postgraduate courses at SCI/Mechanics