Abstract
Population balance models are used because of different system heterogeneities due to complex prevailing phenomena governed by particle fusion, splitting and growth. We present a Minimum Relative Entropy Population Density Estimator (MREPDE) based on the fast Clenshaw algorithm for the evaluation of the Legendre series as the heart of our proposed scheme. The present MREPDE reduced the order of computational complexity from O(M2) to O(M) with an accelerated implementation due to the low rank of the particle fusion matrix because of its tensorial decomposition. We implement the PBE and the MREPDE in a fully vectorized form, which results in a linear scaling of the CPU time with respect to M, instead of a cubic scaling using conventional methods. Therefore, our method is suitable for solving large-scale problems involving particle size distributions.
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 3409-3414 |
| Seitenumfang | 6 |
| Fachzeitschrift | Computer Aided Chemical Engineering |
| Volume | 53 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 2024 |
Wissenschaftszweige
- 202029 Mikrowellentechnik
- 203024 Thermodynamik
- 203038 Lüftungstechnik
- 204 Chemische Verfahrenstechnik
- 204002 Chemische Reaktionstechnik
- 207106 Erneuerbare Energie
- 207111 Umwelttechnik
- 210006 Nanotechnologie
- 211203 Lebensmittelverfahrenstechnik
- 211908 Energieforschung
- 105109 Geothermik
- 502059 Kreislaufwirtschaft
- 509026 Digitalisierungsforschung
- 202034 Regelungstechnik
- 203016 Messtechnik
- 204003 Chemische Verfahrenstechnik
- 204008 Membrantechnologie
- 209006 Industrielle Biotechnologie
- 104027 Computational Chemistry
- 502058 Digitale Transformation
JKU-Schwerpunkte
- Sustainable Development: Responsible Technologies and Management
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