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Experimental Cake Filtration Data and Code for Analysis, Graph Generation
Subtitle: Jupyter Notebooks for Data Regression and Graph Generation
Metadaten
| Ergänzende Titel | Subtitle: Jupyter Notebooks for Data Regression and Graph Generation | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Buchwald, Thomas - TU BAF (ORCID: 0000-0002-2953-0510) | |
| Beschreibung der weiteren Datenverarbeitung | 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. | |
| Kurzbeschreibung | 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. | |
| Angewendete Methoden oder Verfahren | Nonlinear Parameter Estimation | |
| Weitere erklärende Angaben zu den Daten | The experimental data was generated between 2010 and 2021 on two different pressure filtration apparatuses. | |
| Länder, auf die sich die Daten beziehen | GERMANY | de |
| Weitere Schlagwörter | Jupyter notebook | |
| Weitere Schlagwörter | Python | |
| Weitere Schlagwörter | Dataset | |
| Weitere Schlagwörter | Cake Filtration | |
| Sprache | eng | |
| Entstehungsjahr oder Entstehungszeitraum | 2010-2021 | |
| Veröffentlichungsjahr | 2021 | |
| Herausgeber | Technische Universität Bergakademie Freiberg | |
| Referenzen auf ergänzende Materialien | IsPartOf: 123456789/1955 (Handle) | |
| Inhalt der Forschungsdaten | 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. | |
| Inhaber der Nutzungsrechte | Technische Universität Bergakademie Freiberg | |
| Nutzungsrechte des Datensatzes | CC-BY-4.0 | |
| Eingesetzte Software | Resource Processing: Python 3.7 | |
| Nähere Beschreibung der/s Fachgebiete/s | Mechanical Solid/Liquid Separation, Cake Filtration | |
| Angabe der Fachgebiete | Engineering | de |
| Titel des Datensatzes | Experimental Cake Filtration Data and Code for Analysis, Graph Generation |
Dateien zu dieser Ressource
Die Datenpakete erscheinen in:
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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.