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Main Authors: Ries, Hans-Christoph, Krieger, Keno, Meyer, Florian, Eigenbrod, Christian
Format: Recurso digital
Language:English
Published: Zenodo 2025
Online Access:https://doi.org/10.5281/zenodo.14959942
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author Ries, Hans-Christoph
Krieger, Keno
Meyer, Florian
Eigenbrod, Christian
author_facet Ries, Hans-Christoph
Krieger, Keno
Meyer, Florian
Eigenbrod, Christian
contents <h2>About</h2> <p>This dataset contains infra red recordings from a series of drop tower experiment conducted at <a href="https://zarm.uni-bremen.de/en" target="_blank" rel="noopener">ZARM</a>. Thin PMMA samples were combusted under controlled atmospheric conditions and forced opposed flow. An overview of all experiment conditions and sample types is given in the index.csv file. Two kinds of samples were investigated: "full samples", i.e. continuous fuel strips, and "gap samples", i.e. fuel strips separated by air gaps of different widths. Consequently, if the `Gaps [Sequence]` or `Gap Material [Material]` fields are empty, the "full sample" was tested. For the "gap samples" the sequence of gaps is given as the individual widths of each gap in mm separated by slashes, e.g. '3/4/5' to refer to a sample with 3, 4 and 5 mm gaps.</p> <p>The radial lens distortion of the individual frames was corrected as well as the temperature. The frames are stored as 3 dimensional arrays with the first two dimensions being the spatial and the third the time (or frame count) dimension. The value of each pixel corresponds to the measured temperature in °C at the pixel's location.</p> <h2>Usage</h2> <h3>Experiment Overview</h3> <p>The experiment overview is given in the index.csv file. Here, the metadata for each experiment is given. The corresponding IR data can be found in the `Data Location [File]` column. </p> <h3>Loading the frames</h3> <p>The frames are stored in hdf5 files as the 'data' dataset. The corresponding metadata is given as serialized JSON as the 'metadata' dataset. An example for loading the files in Python is given below:</p> <pre><code>import json import h5py import numpy as np data_file = "exp0.hdf5" with h5py.File(data_file, 'r') as f: metadata = json.loads(f["metadata"][()]) # dictionary with date, sample and experiment conditions data = np.array(f["data"]) # individual IR frames as a 3 dimensional array of shape (x, y, t)</code></pre> <h2>Acknowledgments</h2> <p>The authors thank Jan Heißmeier and Michael Peters for technical support during the design phase and the experimental campaigns. This research has been funded by the German Federal Ministry for Economic Affairs and Climate Action through the German Space Agency at DLR in the framework of FLARE-G II & III (grants 50WM2160 & 50WM2456).</p>
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language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Infra Red Recordings of Opposed-Flow Flame Propagation on Discrete PMMA Sheets Under Exploration Atmospheres in Microgravity
Ries, Hans-Christoph
Krieger, Keno
Meyer, Florian
Eigenbrod, Christian
<h2>About</h2> <p>This dataset contains infra red recordings from a series of drop tower experiment conducted at <a href="https://zarm.uni-bremen.de/en" target="_blank" rel="noopener">ZARM</a>. Thin PMMA samples were combusted under controlled atmospheric conditions and forced opposed flow. An overview of all experiment conditions and sample types is given in the index.csv file. Two kinds of samples were investigated: "full samples", i.e. continuous fuel strips, and "gap samples", i.e. fuel strips separated by air gaps of different widths. Consequently, if the `Gaps [Sequence]` or `Gap Material [Material]` fields are empty, the "full sample" was tested. For the "gap samples" the sequence of gaps is given as the individual widths of each gap in mm separated by slashes, e.g. '3/4/5' to refer to a sample with 3, 4 and 5 mm gaps.</p> <p>The radial lens distortion of the individual frames was corrected as well as the temperature. The frames are stored as 3 dimensional arrays with the first two dimensions being the spatial and the third the time (or frame count) dimension. The value of each pixel corresponds to the measured temperature in °C at the pixel's location.</p> <h2>Usage</h2> <h3>Experiment Overview</h3> <p>The experiment overview is given in the index.csv file. Here, the metadata for each experiment is given. The corresponding IR data can be found in the `Data Location [File]` column. </p> <h3>Loading the frames</h3> <p>The frames are stored in hdf5 files as the 'data' dataset. The corresponding metadata is given as serialized JSON as the 'metadata' dataset. An example for loading the files in Python is given below:</p> <pre><code>import json import h5py import numpy as np data_file = "exp0.hdf5" with h5py.File(data_file, 'r') as f: metadata = json.loads(f["metadata"][()]) # dictionary with date, sample and experiment conditions data = np.array(f["data"]) # individual IR frames as a 3 dimensional array of shape (x, y, t)</code></pre> <h2>Acknowledgments</h2> <p>The authors thank Jan Heißmeier and Michael Peters for technical support during the design phase and the experimental campaigns. This research has been funded by the German Federal Ministry for Economic Affairs and Climate Action through the German Space Agency at DLR in the framework of FLARE-G II & III (grants 50WM2160 & 50WM2456).</p>
title Infra Red Recordings of Opposed-Flow Flame Propagation on Discrete PMMA Sheets Under Exploration Atmospheres in Microgravity
url https://doi.org/10.5281/zenodo.14959942