Abstract
We describe a virtual telemetry system that allows us to devise and augment dynamic data-driven application simulations (DDDAS). Virtual telemetry has the advantage that it is inexpensive to produce from real time simulations and readily transmittable using open source streaming software. Real telemetry is usually expensive to receive (if it is even available long term), tends to be messy, comes in no particular order, and can be incomplete or erroneous due to transmission problems or sensor malfunction. We will generate multiple streams continuously for extended periods (e.g., months or years): clean data, somewhat error prone data, and quite lossy or inaccurate data. By studying all of the streams at once we will be able to devise DDDAS components useful in predictive contaminant modeling.
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Keywords
- Data Stream
- Coarse Scale
- Real Time Simulation
- Heterogeneous Porous Medium
- Initial Boundary Value Problem
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Douglas, C.C. et al. (2003). Virtual Telemetry for Dynamic Data-Driven Application Simulations. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Gorbachev, Y.E., Dongarra, J.J., Zomaya, A.Y. (eds) Computational Science — ICCS 2003. ICCS 2003. Lecture Notes in Computer Science, vol 2660. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44864-0_29
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DOI: https://doi.org/10.1007/3-540-44864-0_29
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