Experimental Cake Filtration Data and Code for Analysis, Graph Generation
Contributing person | Buchwald, Thomas (orcid: 0000-0002-2953-0510 | |
Documentation of the data | Methods: Nonlinear Parameter Estimation Resource Type: Experimental data and Jupyter notebooks which contain Python code that analyses the dataset and produces all the graphs contained in the PhD thesis. Data Processing: The experimental data (cake filtration experiments) has been analysed by different methods, most importantly nonlinear parameter estimation. Several different model equations have been used to derive additional theoretical insight. | |
Countries to which the data refer | GERMANY | |
Description of the data | The experimental data was generated between 2010 and 2021 on two different pressure filtration apparatuses. | |
Type of the data | Model | |
Type of the data | Text | |
Type of the data | Image | |
Type of the data | Dataset | |
Total size of the dataset | 50061759 | |
Author | Buchwald, Thomas | |
Upload date | 2021-12-08T12:23:39Z | |
Upload date | 2026-06-05T11:16:07Z | |
Publication date | 2021-12-08T12:23:39Z | |
Publication date | 2026-06-05T11:16:07Z | |
Data of data creation | 2010-2021 | |
Publication date | 2021-12-08 | |
Abstract of the dataset | This collection belongs to the doctoral thesis "Nonlinear Parameter Estimation of Experimental Cake Filtration Data". Most of the content are Jupyter notebooks which contain the Python code which reproduces graphs found in the thesis from the original experimental data. The lab practice dataset that contains 500 filtration experiments is contained in the folder for section 3.5. The notebooks are not strictly sorted by section. At any rate, the Readme will guide you to the notebook which produces a certain graph, if it is not part of the main notebook of that specific section. The original Python environment was set up with Anaconda. Please use the provided .yml file to create a Python environment which contains all the necessary packages. Some notebooks may not work with the most current versions of the packages, so updating is not necessarily a good idea. | |
Public reference to this page | https://opara.zih.tu-dresden.de/handle/123456789/2533 | |
Public reference to this page | https://doi.org/10.25532/OPARA-147 | |
dc.language | eng | |
Publisher | Technische Universität Bergakademie Freiberg | |
Licence | Attribution 4.0 International | |
URI of the licence text | http://creativecommons.org/licenses/by/4.0/ | |
Specification of the discipline(s) | 4 | |
Title of the dataset | Experimental Cake Filtration Data and Code for Analysis, Graph Generation | |
dc.title.alternative | Jupyter Notebooks for Data Regression and Graph Generation | |
Software | Python (Version 3.7) | |
Project abstract | This collection contains all necessary data and code to reproduce the graphs found in the main text of the PhD thesis (Dissertation) "Nonlinear Parameter Estimation of Experimental Cake Filtration Data" by Thomas Buchwald. | |
Project title | PhD thesis "Nonlinear Parameter Estimation of Experimental Cake Filtration Data" by Thomas Buchwald |
Files
Original bundle
- Name:
- Experimental_Data_and_Diagrams.zip
- Size:
- 47.74 MB
- Format:
- Description:
- Zip file contains all folders in the structure of the doctoral thesis.
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