Building a Simulation Community for Solving Exascale Problems: The Structural Simulation Toolkit (SST).
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In one embodiment, a system includes a signal generator operatively coupleable to one or more detectors; and a controller, the controller being both operably coupled to the signal generator and configured to cause the signal generator to: generate one or more signals each signal being representative of at least one emergency event; and communicate one or more of the generated signal(s) to a detector to which the signal generator is operably coupled. In another embodiment, a method includes: receiving data corresponding to one or more emergency events; generating at least one signal based on the data; and communicating the generated signal(s) to a detector.
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Wind plant performance depends on local environmental conditions—and understanding those conditions is crucial to research on wind plant dynamics. Factors such as sloping terrain, surface type and cover, atmospheric heating and cooling, and weather events all play a role in determining the winds that turbines convert into power. However, most models used for wind plant design and operation do not sufficiently account for environmental effects. This can limit our understanding of wind plant dynamics and, thus, our ability to design, site, and operate wind plants for maximum power production and reliability. To meet this challenge, Arthur and other LLNL researchers partnered with scientists at the National Center for Atmospheric Research; the University of California, Berkeley; the University of Colorado, Boulder; and Texas Tech University to develop and demonstrate a novel, mesoscale-tomicroscale wind plant modeling framework.