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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.
In: Scientific Reports, 2018, 8
doi: 10.26083/tuprints-00013404
Article, Secondary publication, Publisher's Version

Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Type of entry: Secondary publication
Title: Data analysis and uncertainty estimation in supercontinuum laser absorption spectroscopy
Language: English
Date: 2022
Place of Publication: Darmstadt
Year of primary publication: 2018
Publisher: Springer Nature
Journal or Publication Title: Scientific Reports
Volume of the journal: 8
Collation: 16 Seiten
DOI: 10.26083/tuprints-00013404
Corresponding Links:
Origin: Secondary publication

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.

Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-134040
Classification DDC: 600 Technology, medicine, applied sciences > 610 Medicine and health
600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 16 Department of Mechanical Engineering > Institute of Reactive Flows and Diagnostics (RSM)
Date Deposited: 02 Mar 2022 13:11
Last Modified: 03 Mar 2023 09:47
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/13404
PPN: 505407817
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