Remote sensing of the light-obscuring smoke properties in real-scale fires using a photometric measurement method

This data set complements the article https://doi.org/10.1007/s10694-023-01470-z. The data set contains the raw image data of three representative experiments and the corresponding input configuration data files for the LEDSA simulations. The data set contains: - The processed LEDSA simulation data of all experiments, mainly consisting of the measured and normalized intensities of all LEDs and the computed extinction coefficients according to the applied layer discretization (ledsa_simulations.zip). - The recorded measurement data of all experiments from three MIREX devices (MIREX.zip). - An exemplary data set consisting of the LEDSA raw data as RAW image files from three representative experiments in shortened form, containing every third image (image_data_{...}.zip). - LEDSA Input and Config files for analysis and simulation of the provided exemplary image data (ledsa_simulations_short.zip). - Python scripts for reading and post-processing the LESDA simulation data (postprocessing_tools.zip) - Juptyter Lab Python scripts that have been used to create the plots in the associated paper (data_analysis.zip). - The figures from the associated paper (figures.zip). Notes In order to run the Python scripts in Juptyer Labs properly, the given directory structure must be maintained, resulting when all archives are unpacked on the same hierarchical level. The authors gratefully acknowledge the financial support of the German Federal Ministry of Education and Research. The extensive LEDSA computations were performed largely on the high-performance computer system funded as part of the CoBra project with the grant number 13N15497.

本数据集配套于论文https://doi.org/10.1007/s10694-023-01470-z。本数据集包含三个代表性实验的原始图像数据，以及对应发光二极管光谱吸收（LEDSA）模拟的输入配置数据文件。本数据集包含以下内容：
- 所有实验的经处理LEDSA模拟数据，主要涵盖所有发光二极管的实测归一化光强，以及基于所采用的层离散化方法计算得到的消光系数（压缩包ledsa_simulations.zip）。
- 三台MIREX设备采集的所有实验的记录测量数据（压缩包MIREX.zip）。
- 一个示例性数据集，包含经精简的三个代表性实验的LEDSA原始图像文件，仅保留每三张图像中的一张（压缩包image_data_{...}.zip）。
- 用于对提供的示例性图像数据进行分析与模拟的LEDSA输入与配置文件（压缩包ledsa_simulations_short.zip）。
- 用于读取与后处理LEDSA模拟数据的Python脚本（压缩包postprocessing_tools.zip）。
- 用于生成关联论文中插图的Jupyter Lab Python脚本（压缩包data_analysis.zip）。
- 关联论文中的全部插图（压缩包figures.zip）。
注意事项：若要正常运行Jupyter Lab中的Python脚本，需保持给定的目录结构——该结构在将所有压缩包解压至同一层级目录时即可自动生成。
作者衷心感谢德国联邦教育与研究部提供的经费支持。本研究中大量的LEDSA计算主要依托于CoBra项目资助的高性能计算系统，项目资助编号为13N15497。