Experimental Cake Filtration Data and Code for Analysis, Graph Generation
Subtitle: Jupyter Notebooks for Data Regression and Graph Generation
Metadata
| Additional title | Subtitle: Jupyter Notebooks for Data Regression and Graph Generation | |
| Person(s) who is (are) responsible for the content of the research data | Buchwald, Thomas - TU BAF (ORCID: 0000-0002-2953-0510) | |
| Description of further 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. | |
| Abstract | 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. | |
| Applied methods and techniques | Nonlinear Parameter Estimation | |
| Additional descriptive information to understand the data | The experimental data was generated between 2010 and 2021 on two different pressure filtration apparatuses. | |
| Counties, the data is referencing | GERMANY | de |
| Additional keywords | Jupyter notebook | |
| Additional keywords | Python | |
| Additional keywords | Dataset | |
| Additional keywords | Cake Filtration | |
| Language | eng | |
| Year or period of data production | 2010-2021 | |
| Publication year | 2021 | |
| Publisher | Technische Universität Bergakademie Freiberg | |
| References on related materials | IsPartOf: 123456789/1955 (Handle) | |
| Content of the research data | Text, Image, Dataset, Model: Experimental data and Jupyter notebooks which contain Python code that analyses the dataset and produces all the graphs contained in the PhD thesis. | |
| Holder of usage rights | Technische Universität Bergakademie Freiberg | |
| Usage rights of the data | CC-BY-4.0 | |
| Software | Resource Processing: Python 3.7 | |
| Additional precise description of discipline | Mechanical Solid/Liquid Separation, Cake Filtration | |
| Discipline(s) | Engineering | de |
| Title of the dataset | Experimental Cake Filtration Data and Code for Analysis, Graph Generation |
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Experimental Data and Diagrams [1]
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.