Constructing PDFs of spatially dependent fields using finite elements
Fuente:
arXiv
Salvato in:
| Autori principali: | , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866909452498632704 |
|---|---|
| author | Mannix, Paul M. Ham, David A. Craske, John |
| author_facet | Mannix, Paul M. Ham, David A. Craske, John |
| contents | A probability density function (PDF) of a spatially dependent field provides a means of calculating moments of the field or, equivalently, the proportion of a spatial domain that is mapped to a given set of values. This paper describes a finite element approach to estimating the PDF of a spatially dependent field and its numerical implementation in the Python package NumDF. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_05115 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Constructing PDFs of spatially dependent fields using finite elements Mannix, Paul M. Ham, David A. Craske, John Fluid Dynamics Numerical Analysis A probability density function (PDF) of a spatially dependent field provides a means of calculating moments of the field or, equivalently, the proportion of a spatial domain that is mapped to a given set of values. This paper describes a finite element approach to estimating the PDF of a spatially dependent field and its numerical implementation in the Python package NumDF. |
| title | Constructing PDFs of spatially dependent fields using finite elements |
| topic | Fluid Dynamics Numerical Analysis |
| url | https://arxiv.org/abs/2501.05115 |