The proliferation of sensor networks in various areas of technology has enabled real-time behavioral monitoring of various physical systems in various length and time scales. The opportunity to use these data dynamically for improving speed, accuracy, and general performance of predictive behavior modeling simulation is of paramount importance. The present paper identifies enabling modeling methods and computational strategies that are critical for achieving real-time simulation response of very large and complex systems. It also discusses our choices of these technologies in the context of sample multidisciplinary computational mechanics applications. © Springer-Verlag 2004.
CITATION STYLE
Michopoulos, J., Farhat, C., & Houstis, E. (2004). Dynamic-data-driven real-time computational mechanics environment. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3038, 693–700. https://doi.org/10.1007/978-3-540-24688-6_90
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