Extending The Sheba Propagation Model To Reduce Parameter-Related Uncertainties
Heliophysics is the branch of physics that investigates the interactions and cor-relation of different events across the Solar System. The mathematical modelsthat describe and predict how physical events move across the solar system (ie.Propagation Models) are of great relevance. These models depend...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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AGH University of Science and Technology Press
2013-01-01
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| Series: | Computer Science |
| Online Access: | http://journals.agh.edu.pl/csci/article/download/281/180 |
| _version_ | 1819067367221624832 |
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| author | Gabriele Pierantoni Brian Coghlan Eamonn Kenny Peter Gallagher David Perez-Suarez |
| author_facet | Gabriele Pierantoni Brian Coghlan Eamonn Kenny Peter Gallagher David Perez-Suarez |
| author_sort | Gabriele Pierantoni |
| collection | DOAJ |
| description | Heliophysics is the branch of physics that investigates the interactions and cor-relation of different events across the Solar System. The mathematical modelsthat describe and predict how physical events move across the solar system (ie.Propagation Models) are of great relevance. These models depend on parame-ters that users must set, hence the ability to correctly set the values is key toreliable simulations. Traditionally, parameter values can be inferred from dataeither at the source (the Sun) or arrival point (the target) or can be extrapo-lated from common knowledge of the event under investigation. Another way ofsetting parameters for Propagation Models is proposed here: instead of guess-ing a priori parameters from scientific data or common knowledge, the model isexecuted as a parameter-sweep job and selects a posteriori the parameters thatyield results most compatible with the event data. In either case (a priori anda posteriori), the correct use of Propagation Models requires information toeither select the parameters, validate the results, or both. In order to do so, itis necessary to access sources of information. For this task, the HELIO projectproves very effective as it offers the most comprehensive integrated informationsystem in this domain and provides access and coordination to services to mineand 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 toscience gateways seamless access to major computing and data infrastructures). |
| first_indexed | 2024-12-21T16:17:07Z |
| format | Article |
| id | doaj.art-c4b7bfb17aa849048bb8c7c716da545d |
| institution | Directory Open Access Journal |
| issn | 1508-2806 |
| language | English |
| last_indexed | 2024-12-21T16:17:07Z |
| publishDate | 2013-01-01 |
| publisher | AGH University of Science and Technology Press |
| record_format | Article |
| series | Computer Science |
| spelling | doaj.art-c4b7bfb17aa849048bb8c7c716da545d2022-12-21T18:57:40ZengAGH University of Science and Technology PressComputer Science1508-28062013-01-0114225310.7494/csci.2013.14.2.253Extending The Sheba Propagation Model To Reduce Parameter-Related UncertaintiesGabriele PierantoniBrian CoghlanEamonn KennyPeter GallagherDavid Perez-SuarezHeliophysics is the branch of physics that investigates the interactions and cor-relation of different events across the Solar System. The mathematical modelsthat describe and predict how physical events move across the solar system (ie.Propagation Models) are of great relevance. These models depend on parame-ters that users must set, hence the ability to correctly set the values is key toreliable simulations. Traditionally, parameter values can be inferred from dataeither at the source (the Sun) or arrival point (the target) or can be extrapo-lated from common knowledge of the event under investigation. Another way ofsetting parameters for Propagation Models is proposed here: instead of guess-ing a priori parameters from scientific data or common knowledge, the model isexecuted as a parameter-sweep job and selects a posteriori the parameters thatyield results most compatible with the event data. In either case (a priori anda posteriori), the correct use of Propagation Models requires information toeither select the parameters, validate the results, or both. In order to do so, itis necessary to access sources of information. For this task, the HELIO projectproves very effective as it offers the most comprehensive integrated informationsystem in this domain and provides access and coordination to services to mineand 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 toscience gateways seamless access to major computing and data infrastructures).http://journals.agh.edu.pl/csci/article/download/281/180 |
| spellingShingle | Gabriele Pierantoni Brian Coghlan Eamonn Kenny Peter Gallagher David Perez-Suarez Extending The Sheba Propagation Model To Reduce Parameter-Related Uncertainties Computer Science |
| title | Extending The Sheba Propagation Model To Reduce Parameter-Related Uncertainties |
| title_full | Extending The Sheba Propagation Model To Reduce Parameter-Related Uncertainties |
| title_fullStr | Extending The Sheba Propagation Model To Reduce Parameter-Related Uncertainties |
| title_full_unstemmed | Extending The Sheba Propagation Model To Reduce Parameter-Related Uncertainties |
| title_short | Extending The Sheba Propagation Model To Reduce Parameter-Related Uncertainties |
| title_sort | extending the sheba propagation model to reduce parameter related uncertainties |
| url | http://journals.agh.edu.pl/csci/article/download/281/180 |
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