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Data analysis and uncertainty estimation in supercontinuum laser absorption spectroscopy

Emmert, Johannes ; Blume, Niels Göran ; Dreizler, Andreas ; Wagner, Steven (2022):
Data analysis and uncertainty estimation in supercontinuum laser absorption spectroscopy. (Publisher's Version)
In: Scientific Reports, 8, Springer Nature, e-ISSN 2045-2322,
DOI: 10.26083/tuprints-00013404,
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Item Type: Article
Origin: Secondary publication
Status: Publisher's Version
Title: Data analysis and uncertainty estimation in supercontinuum laser absorption spectroscopy
Language: English
Abstract:

A set of algorithms is presented that facilitates the evaluation of super continuum laser absorption spectroscopy (SCLAS) measurements with respect to temperature, pressure and species concentration without the need for simultaneous background intensity measurements. For this purpose a non-linear model fitting approach is employed. A detailed discussion of the influences on the instrument function of the spectrometer and a method for the in-situ determination of the instrument function without additional hardware are given. The evaluation procedure is supplemented by a detailed measurement precision assessment by applying an error propagation through the non-linear model fitting approach. While the algorithms are tailored to SCLAS, they can be transferred to other spectroscopic methods, that similarly require an instrument function. The presented methods are validated using gas cell measurements of methane in the near infrared region at pressures up to 8.7 bar.

Journal or Publication Title: Scientific Reports
Volume of the journal: 8
Publisher: Springer Nature
Collation: 16 Seiten
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin, Gesundheit
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 16 Department of Mechanical Engineering > Institute of Reactive Flows and Diagnostics (RSM)
Date Deposited: 02 Mar 2022 13:11
Last Modified: 10 Mar 2022 09:43
DOI: 10.26083/tuprints-00013404
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-134040
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/13404
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