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We apply artificial neural networks (ANNs) to improve the modeling of on-wafer open-short-load-thru (OSLT) standards used for calibrating vector network analyzers. The ANNs are trained with measurement data obtained from a benchmark multiline thru-reflect
Past uses of octrees have been for representing of static objects. We discuss extensions necessary to model dynamic surfaces. One particularly important aspect of this is the ability to represent expanding surfaces that grow to be arbitrarily large. Our
Cross-linked epoxy thermosets, like all glass-forming viscoelastic materials, show both a temperature and rate dependence in their thermo-mechanical properties. However, accounting for rate effects on these properties using molecular dynamics (MD)
Digital image correlation (DIC) data are being extensively used for many forming applications including constitutive law calibration, benchmark calibration, and for comparisons with finite element analysis (FEA) simulated results. The most challenging