Capturing Scientists’ Insight for DDDAS

Paul Reynolds1, David Brogan1, Joseph Carnahan1, Yannick Loitière1, and Michael Spiegel1

1 Computer Science Department, University of Virginia

Abstract. One of the intended consequences of utilizing simulations in dynamic, data-driven application systems is that the simulations will adjust to new data as it arrives. These adjustments will be difficult because of the unpredictable nature of the world and because simulations are so carefully tuned to model specific operating conditions. Accommodating new data may require adapting or replacing numerical methods, simulation parameters, or the analytical scientific models from which the simulation is derived. In this research, we emphasize the important role a scientist’s insight can play in facilitating the runtime adaptation of a simulation to accurately utilize new data. We present the tools that serve to capture and apply a scientist’s insight about opportunities for, and limitations of, simulation adaptation. Additionaly, we report on the two ongoing collaborations that serve to guide and evaluate our research.

LNCS 3993, pp. 570-577.

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