A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators
Not Available
97 MATHEMATICS AND COMPUTING↗
Engineering topics
Williams, Alan
Publications and source records attributed to Williams, Alan.
Advancing the mechanical integrity and fragmentation behavior of reactive projectiles
A multivariant statistical approach was used to identify treatment conditions that improve the survivability of structural reactive material (SRM) projectiles upon launch and enhance energy release upon impact. The study included both mechanical testing of projectiles as well as their reactive characterization. The projectiles were launched in a high-velocity impact-ignition testing system and impacted an anvil for vented chamber calorimetry. This study examined a link between ultimate compressive stress and combustion performance. Two treatments were applied to consolidated aluminum projectiles including annealing and addition of silica (SiO 2 ) inclusions. Results showed annealing at moderate temperatures resulted in intact SRM projectiles upon launch. Adding small concentrations (1–2 wt. %) of SiO 2 to the SRM promoted fragmentation and combustion performance upon impact. Compared to the untreated projectiles, annealing with SiO 2 inclusion processing treatments improved the energy conversion efficiency from 37–84% (for untreated projectiles) up to 54–98%. In conclusion, increasing interparticle dislocation recovery by annealing while balancing inclusions promoting fragmentation upon impact was the key to optimizing combustion performance for SRM ballistic impact applications.
42 ENGINEERING↗
ExaWind: Then and Now
The scientific goal of the ExaWind project is to advance our fundamental understanding of the flow physics governing whole wind plant performance, including wake formation, complex terrain impacts, and turbine-turbine-interaction effects. The primary application codes in the ExaWind environment are Nalu-Wind, an unstructured-grid computational fluid dynamics (CFD) code, AMR-Wind, a structured-grid CFD code, and OpenFAST, a whole-turbine simulation code. In this poster we present the current status of the ExaWind software stack in the context of the modeling and simulation capabilities when the project started in 2016.
computational fluid dynamics↗
Demonstrate multi-turbine simulation with hybrid-structured / unstructured-moving-grid software stack running primarily on GPUs and propose improvements for successful KPP-2
The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, capturing the thin boundary layers, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources.
17 WIND ENERGY↗
ExaWind: Exascale Predictive Wind Plant Flow Physics Modeling.
Abstract not provided.
Sprague, Michael A.↗