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.
| Original language | English |
|---|---|
| Pages (from-to) | 3409-3414 |
| Number of pages | 6 |
| Journal | Computer Aided Chemical Engineering |
| Volume | 53 |
| DOIs | |
| Publication status | Published - 2024 |
Fields of science
- 202029 Microwave engineering
- 203024 Thermodynamics
- 203038 Ventilation technology
- 204 Chemical Process Engineering
- 204002 Chemical reaction engineering
- 207106 Renewable energy
- 207111 Environmental engineering
- 210006 Nanotechnology
- 211203 Food processing engineering
- 211908 Energy research
- 105109 Geothermics
- 502059 Circular economy
- 509026 Digitalisation research
- 202034 Control engineering
- 203016 Measurement engineering
- 204003 Chemical process engineering
- 204008 Membrane technology
- 209006 Industrial biotechnology
- 104027 Computational chemistry
- 502058 Digital transformation
JKU Focus areas
- Sustainable Development: Responsible Technologies and Management