- Tytuł:
- Extending the sheba propagatio model to reduce parameter-related uncertainties
- Autorzy:
-
Pierantoni, G.
Coghlan, B.
Kenny, E.
Gallagher, P.
Perez-Suarez, D. - Powiązania:
- https://bibliotekanauki.pl/articles/305331.pdf
- Data publikacji:
- 2013
- Wydawca:
- Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
- Tematy:
-
heliophysics
HELIO
SCI-BUS
distributed computation infrastructure
propagation models - Opis:
- Heliophysics is the branch of physics that investigates the interactions and correlation of different events across the Solar System. The mathematical models that describe and predict how physical events move across the solar system (ie. Propagation Models ) are of great relevance. These models depend on parameters that users must set, hence the ability to correctly set the values is key to reliable simulations. Traditionally, parameter values can be inferred from data either at the source (the Sun) or arrival point (the target) or can be extrapolated from common knowledge of the event under investigation. Another way of setting parameters for Propagation Models is proposed here: instead of guessing a priori parameters from scientific data or common knowledge, the model is executed as a parameter-sweep job and selects a posteriori the parameters that yield results most compatible with the event data. In either case ( a priori and a posteriori ), the correct use of Propagation Models requires information to either select the parameters, validate the results, or both. In order to do so, it is necessary to access sources of information. For this task, the HELIO project proves very effective as it offers the most comprehensive integrated information system in this domain and provides access and coordination to services to mine and analyze data. HELIO also provides a Propagation Model called SHEBA, the extension of which is currently being developed within the SCI-BUS project (a coordinated effort for the development of a framework capable of offering to science gateways seamless access to major computing and data infrastructures).
- Źródło:
-
Computer Science; 2013, 14 (2); 253-272
1508-2806
2300-7036 - Pojawia się w:
- Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł