Passive scalar interface in a spatially evolving mixing layer (A. Attili and D. Denker)

Quartz nozzle sampling (D. Felsmann)

Dissipation element analysis of a planar diffusion flame (D. Denker)

Turbulent/non-turbulent interface in a temporally evolving jet (D. Denker)

Dissipation elements crossing a flame front (D. Denker and B. Hentschel)

Particle laden flow (E. Varea)

Turbulent flame surface in non-premixed methane jet flame (D. Denker)

DNS of primary break up (M. Bode)

Diffusion flame in a slot Bunsen burner (S. Kruse)

Various quantities in spatially evolving jet diffusion flame (D. Denker)

OH layer in a turbulent wall bounded flame (K. Niemietz)

Measurement Techniques and Data Analysis

The course takes place in the winter semester.


Dates

Lecture Professor Heinz Pitsch

Tuesday, 8:30 - 10:00, HKW 2 (15.10.2024 - 28.01.2025)

Exercise Christian Schwenzer

Wednesday, 14:30 - 15:15, BS 218 (23.10.2024 - 29.01.2025)

Exam

Friday, 06.02.2024, 11:30 - 13:00

Lecture and Exercise

For Lecture and Exercise, a joint moodle page (VO) is used.

Lecture and Exercise material: Opens external link in new windowRWTHmoodle

Content

Introduction to the meaning of measurement data, measurement uncertainty and data analysis.

  • Acquisition, presentation and management of measurement data
  • Challenges in the acquisition of measurement data based on examples
  • Introduction of statistical parameters
  • Data management and data life cycle
  • Measurement uncertainties
  • Introduction of different measurement uncertainties
  • Determination of measurement uncertainties and error propagation (Part 1)
  • Determination of measurement uncertainties and error propagation (part 2)
  • Calibration and verification of the measurement technique
  • Data analysis
  • Filtering of data and data visualization
  • Hypothesis testing and functional relationships by means of regression
  • Data analysis with machine learning methods (introduction)
  • Data analysis with machine learning methods (examples)
  • Application of the learned methods in MATLAB

Accompanying the lecture, exercises are offered in which the students apply the acquired
methods and concepts using real data sets.

Notice:

The lecture "Measurement Techniques and Data Analysis" has a scope of 3 ECTS.

Responsible


Consultation Hour

Individual arrangement. Contact Christian Schwenzer.


Exam

Freitag, 06.02.2025, 11:30 - 13:00, FT (2090|120) and II (1010|201)