Computer Science – Artificial Intelligence
Scientific paper
May 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001agusm..sm21b12r&link_type=abstract
American Geophysical Union, Spring Meeting 2001, abstract #SM21B-12
Computer Science
Artificial Intelligence
2753 Numerical Modeling, 2756 Planetary Magnetospheres (5443, 5737, 6030)
Scientific paper
Instrumentation on scientific satellites is typically capable of high data rates, but only a fraction of this high resolution data is telemetered to ground. The scientific value of telemetered high resolution data can be extremely variable, depending on the chance that an event of scientific interest is captured during "burst mode" operations. For example, each of the four or five spacecraft of the proposed Magnetospheric Multi Scale (MMS) mission is projected to obtain 2 Gb per day and will be able to store 14 days of science data. However, the instrumentation on board is to be capable of burst mode operations that produce over four times as much data as normal mode operations. MMS focuses on the microphysics of magnetospheric dynamics and structure, therefore high resolution data acquired from boundary regions and sites of magnetospheric energy transfer are a mission priority. Just under half of MMS's mission will be spent in orbits with periods exceeding nine days. A considerable fraction of this time will be spent in the vicinity of apogee where key science operations occur. MMS therefore, will likely have ample opportunity to fill its data store with high resolution data and can do so in only 3.5 days. For the remaining six days of these orbits, data will either not be recorded or must necessarily write over more important data obtained at apogee. Furthermore, due to limited telemetry opportunities and lengthy orbits, the spacecraft must perform these operations essentially autonomously. These are unavoidable trade offs and constraints in the management of MMS science. In this paper we report on the initial progress of our implementation of a Science Agent or Virtual Principal Investigator for the MMS context. The SA is a prototype artificial intelligence that will reside in a high performance computing environment, like the environment provided by the proposed MMS High Performance Computing System being studied by NASA's Remote Exploration and Experimentation (REE) project. The SA will autonomously manage on board science processing, identify time intervals for the storage of selected high resolution data based on the science objectives, and triage these periods for memory management. Results of testing the SA on archived data sets will be presented.
Bhat M. K.
Boardsen Scott A.
Curtis Steven Andrew
Rilee Mike L.
No associations
LandOfFree
A Virtual Principal Investigator for on Board Space Science Data Analysis does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A Virtual Principal Investigator for on Board Space Science Data Analysis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Virtual Principal Investigator for on Board Space Science Data Analysis will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1276879