Structure · dataset · 2026
Replication Data for: A Mechanistic Process Model for Suspension Melt Crystallization
Listed in TUDOdata
PROJECT DESCRIPTION: The increasing global demand for freshwater, coupled with the challenges of climate change and declining groundwater resources, underscores the importance of effective water treatment methods.
Description
Suspension melt crystallization, also known as freeze concentration, is a promising technique due to its ability to produce high-purity water from aqueous solutions while maintaining lower energy requirements than traditional evaporation processes.
This work focuses on developing a mechanistic model that incorporates hydrodynamics and energy balances to elucidate crystallization phenomena, such as nucleation and crystal growth rates. The model is validated against experimental data derived from sodium chloride and magnesium sulfate water systems. With the model, key nucleation and growth kinetics parameters can be successfully predicted to simulate and optimize temperature trajectories and particle size distributions.
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This repository contains a structured research dataset developed using a modular workflow inspired by the gPROMS Process Builder Version 2.1.1. The project includes two main models, multiple process scenarios, and several optimization routines. Model Structure Mechanistic_Model model: Contains all equations and the defined parameters and variables.
Parameter_set model: References the Mechanistic_model to set global parameters. Used as the foundation for all process simulations and optimizations. Process Definitions For each experimental operating point (Impuritiy_scraper rotational rate_volume flow rate_cooling rate, example: NaCl_210_8_1), a dedicated process file (example: NaCl_210_8_1) is provided.
These include: Input specifications (e.g. feed concentrations, flow rates, temperature) Experimental results used for comparison and fitting For NaCl_210_8_3 additional implementation of the task for conti simulation Optimization Files Several optimization scripts are included to fit model parameters based on specific operating conditions (Name: fit_parameter_impurity_scraper rotational rate_volume flow rate_cooling rate, example: fit_fhet_NaCl_210_8_1): NaCl-tagged operating points: fhet fitting for all NaCl cases ksec fitting for all NaCl cases ksec and glim joint optimization, limited to the special case: NaCl_210_8_3 All model, process, and optimization components are included as plain-text .txt files for transparency, reproducibility, and ease of reuse.
Links
Where it is published
- Dataverse dataset page data.tu-dortmund.de/dataset.xhtml?persistentId=doi%3A10.17877%2FTUDODATA-2025-MBHV… ↗
landing page · from data tu dortmund de
- DOI doi.org/10.17877/tudodata-2025-mbhvtuuh ↗
DOI / persistent id · from data tu dortmund de
Catalogue records · 1
- Dataverse API data.tu-dortmund.de/api/datasets/:persistentId/?persistentId=doi%3A10.17877%2FTUDO… ↗
metadata API · from data tu dortmund de
Topics
- Stated by source
- Engineering
- From keywords
- Chemistry · Engineering · Humanities · Materials Science · Mathematics & Statistics · Physics · Social Science
- Inferred from text
- Chemical engineering 70% · Simulation 75%
Provenance · 1 source records, 16 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| TUDOdata | doi:10.17877/TUDODATA-2025-MBHVTUUH | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4004 | enrichment · data tu dortmund de | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].dataverse_subject:engineering | source · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /subjects |
| concepts[field].local:field:materials-science | mapping · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /subjects |
| concepts[field].local:field:mathematics-statistics | mapping · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /subjects |
| concepts[field].local:field:physics | mapping · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /subjects |
| concepts[method].local:method:simulation | enrichment · data tu dortmund de | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | |
| description | source · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /description |
| publication_date | source · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | |
| title | source · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | /name |
| updated_date | source · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 | |
| version_label | source · data tu dortmund de | connector:data_tu_dortmund_de@1.0.0 |