Szczegóły publikacji
Opis bibliograficzny
Shock waves generators: from prevention of hail storms to reduction of the smog in urban areas — experimental verification and numerical simulations / Marcin ŁOŚ, Leszek SIWIK, Maciej WOŹNIAK, Dominik GRYBOŚ, Paweł MACZUGA, Albert Oliver-Serra, Jacek LESZCZYŃSKI, Maciej PASZYŃSKI // Journal of Computational Science ; ISSN 1877-7503. — 2024 — vol. 77 art. no. 102238, s. 1-11. — Bibliogr. s. 11, Abstr. — Publikacja dostępna online od: 2024-02-29
Autorzy (8)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 152513 |
|---|---|
| Data dodania do BaDAP | 2024-04-19 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.jocs.2024.102238 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Journal of Computational Science |
Abstract
Hail cannoning is a technique of preventing cloud formation before hailstorms by creating a sequence of shock waves. So far, despite numerous experiments, there is no clear evidence that this technique actually works. This paper provides a detailed analysis of the hail cannoning technique and its impact on local weather conditions. Through mathematical modeling, numerical simulations, and systematic in-field experiments, we have proven that not only does it work, but it can also be successfully applied to solve the super-important, for many places all around the world, problem of smog. The main contributions of our study are as follows: we present a 3D mathematical model of propagation and the impact of the shock waves generated by the hail cannons on the local state of the atmosphere (1); we provide numerical experiments that prove that the technique interacts with and significantly impacts the local state of the atmosphere, and can be successfully applied to reduce the concentration of not only cloud vapor but also PM2.5 and PM10 particles, thus reducing smog (2); we also present systematic in-field experiments that confirm the findings of the mathematical modeling and numerical simulations (3), detailed scalability analysis of parallel implementation of the solver applied for numerical experiments (4).