From 35555b7bbb746bcd910dd2f42cf937e1f8f04b19 Mon Sep 17 00:00:00 2001 From: Christian Kolset Date: Wed, 5 Nov 2025 10:14:21 -0700 Subject: Added 1) Spectroscopy and 2) Schlieren imaging examples --- tutorials/module_4/Spectroscopy problem.md | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) create mode 100644 tutorials/module_4/Spectroscopy problem.md (limited to 'tutorials/module_4/Spectroscopy problem.md') diff --git a/tutorials/module_4/Spectroscopy problem.md b/tutorials/module_4/Spectroscopy problem.md new file mode 100644 index 0000000..d48eaba --- /dev/null +++ b/tutorials/module_4/Spectroscopy problem.md @@ -0,0 +1,22 @@ + +## Background + + + +Example problem on Data Processing - Optical Emission Spectroscopy + + +- Import xls data into Python +- Plot the Intensity [a.u.]  vs pixels +- Interpolate and convert x-axis from pixels to nm (true wavelength) using Hg lamp data (using data in file: Lampa_Calibrare_Mercur.xlsx) +- Find response function of the spectrometer using the tungsten lamp data from file: "Calibrare Intensitate Oxigen.xlsx)": R=I_measured/I_true (where True is computed by Planck's law of radiation (see notes in the pptx above) +- Convert y-axis from Intensity [a.u.] into Intensity in [W/(cm^2*sr*nm)] by dividing the measured Oxygen spectrum with the response function: I_oxygen_true=I_oxygen_measured/R +- Once the spectra is in real units: compute the density of one of the oxygen lines by integrating underneath one of the peaks (see equation from Slide 39 - bottom). We will give all of the constants that are in this equation (see the "Intensity_Calibration_Oxygen_Discharge_Solution.xlsx") + + + +Problem 1: Import the data as a pandas dataframe. + +Problem 2: Using the known wavelength intensities of mercury, identify the wavelengths. + +Problem 3: \ No newline at end of file -- cgit v1.2.3