QoI - OH structures

DOI

This dataset contains a curated database of OH structures extracted from OH-PLIF measurements. The database is utilised for the generation of synthetic, automatically annotated training data via physics-informed domain randomisation. The resulting synthetic dataset is subsequently used for training of DL-based semantic segmentation models for transferable OH-LIF flame detection.

For further details and citation, please refer to the submitted paper: B. Jose, D. Greenblatt, R. P. Lindstedt, A. Breicher, D. Geyer, O. Lammel, F. Hampp, Transferable DL for in-situ validated LIF segmentation, submitted to the Proceedings of the Combustion Institute (2026)

Data Samples:

Identifier
DOI https://doi.org/10.18419/DARUS-5961
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-5961
Provenance
Creator Jose, Basil ORCID logo; Greenblatt, Daniel ORCID logo; Lindstedt, Rune Peter ORCID logo; Hampp, Fabian ORCID logo
Publisher DaRUS
Contributor Jose, Basil; Hampp, Fabian
Publication Year 2026
Funding Reference DFG 456687251
Rights MIT License; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/MIT.html
OpenAccess true
Contact Jose, Basil (University of Stuttgart); Hampp, Fabian (University of Stuttgart)
Representation
Resource Type Dataset
Format image/png; application/zip; text/markdown
Size 133522; 134293; 137687; 170951786; 841
Version 1.0
Discipline Chemistry; Construction Engineering and Architecture; Engineering; Engineering Sciences; Fluid Mechanics; Heat Energy Technology, Thermal Machines, Fluid Mechanics; Mechanical and industrial Engineering; Mechanics; Mechanics and Constructive Mechanical Engineering; Natural Sciences; Thermal Engineering/Process Engineering