SOLAR predictor: A knowledge management tool supporting long-term console operations
| dc.contributor.author | Diaz, A. | |
| dc.contributor.author | Wislez, J.-M. | |
| dc.contributor.author | Klaï, S. | |
| dc.contributor.author | Jacobs, C. | |
| dc.contributor.author | Van Hoof, D. | |
| dc.contributor.author | Sela, A. | |
| dc.contributor.author | Karl, A. | |
| dc.contributor.author | Michel, A. | |
| dc.contributor.author | This, N. | |
| dc.contributor.author | Moreau, D. | |
| dc.date | 2014 | |
| dc.date.accessioned | 2021-07-22T07:47:57Z | |
| dc.date.available | 2021-07-22T07:47:57Z | |
| dc.identifier.uri | https://orfeo.belnet.be/handle/internal/7900 | |
| dc.description | The Solar Monitoring Observatory (SOLAR) is a payload of the European Space Agency (ESA) mounted on the zenith-pointing external platform of the Columbus module of the International Space Station (ISS) and is designed to track the Sun in order to perform quasi-continuous measurements of the solar irradiance. SOLAR is operational and returning science since February 2008 and its mission is supported until February 2017. This paper presents the "SOLAR" Predictor, a web-based knowledge management tool. The tool has been developed by the operator team at the Belgian User Support and Operations Centre (B.USOC) in 2012 to support the operations of SOLAR within the team and it was further fine-tuned in 2013. The SOLAR Predictor aims to collect and combine all the latest information relevant to SOLAR operations at a single location, in order to support and facilitate routine operator tasks The SOLAR Predictor tool automatically fetches and parses information from a series of sources relevant to SOLAR Operations, like real-time planning, attitude timeline and vehicle traffic, orbit-related data and of course the SOLAR telemetry data. The tool also links to a database containing SOLAR specific command schedules. These command scripts are used on-board to execute the science activities. The implementation in the Predictor is as such that it provides a means of configuration control, on-board file management, and support for file uplink and transfer. The algorithms implemented in the Predictor tool process the data feed in order to provide predictions of Sun observation conditions and operations constraints based on the latest available information. The information is graphically visualised, highlighting possible conflicts in the planning, allowing the operators to easily fine-tune the planning. The tool facilitates the long-term planning and real-time rescheduling of the science activities, based on the input from the science teams. At the time of activity execution, the operator is warned through an audible alarm. The daily timeline reviews are supported by automatically checking the differences between the desired planning and the published Onboard Short Term Plan data, and by automatically generating the input files for the various operational counterparts. Finally, the tool automatically creates detailed and accurate Daily Operations Reports, which are distributed to the SOLAR stakeholders. The SOLAR Predictor tool helps maximizing the scientific return of operations within the existing external constraints impacting SOLAR operations, such as loss of signal, South Atlantic Anomaly passes, Sun Visibility Windows, attitude control and orbital control of the station using propellant, visiting vehicles, etc. On console, the tool provides support for the real-time operations as well as to routine tasks that used to involve a lot of repetitive manual cut-and-/paste and comparison work. As a result, the amount of operator inaccuracies and errors in routine tasks is dramatically reduced. | |
| dc.language | eng | |
| dc.title | SOLAR predictor: A knowledge management tool supporting long-term console operations | |
| dc.type | Conference | |
| dc.subject.frascati | Physical sciences | |
| dc.audience | Scientific | |
| dc.source.title | Proceedings of the 13th International Conference on Space Operations (SpaceOps 2014), Pasadena, CA, United States, 5-9 May 2014 | |
| dc.source.page | AIAA 2014-1652 | |
| Orfeo.peerreviewed | No | |
| dc.identifier.doi | 10.2514/6.2014-1652 |
