Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what-if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that attempts to strike a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors such as at the individual entity level. The mesoscopic approach offers the possibility of incorporating complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also provides an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple data (SIMD). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what-if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what-if scenario tree evaluation has been implemented in software on modern GPUs. Synthetic simulation scenarios are explored and presented here to demonstrate the basic feasibility and computational characteristics of our approach. Results from the experiments on large population data illustrate the overall modeling methodology and computational run time performance on large numbers of synthetically generated what-if scenarios.

Effects of Thickness Changes and Friction during the Thermoforming of Composite Sheets

In composite sheet preforming, the combination of binder-ring force and friction induce in-plane tension that mitigates the onset of wrinkling, but too much force can induce tearing. Thus, the processing conditions must be designed to strike a balance between these competing manufacturing-induced defects. Compounding the challenge to prescribe the appropriate processing conditions is the potential change in thickness of the sheets as a function of in-plane shear. The variation in the thickness from point to point in the ply stack will result in a nonuniform pressure under the binder ring. In the current research, the preforming step is simulated using a discrete mesoscopic modeling approach in LS-DYNA. Thickness-stretch shell elements are used to capture the evolution in the sheet thickness and the in-plane shear stiffness of the deformed sheet. Finite element simulations and preforming experiments are completed for the same processing conditions. The preliminary results for the punch force as a function of displacement, the state of shear over the part surface, and the distribution and magnitude of the wrinkles showed excellent correlation between the model and the experiment. The simulation results show that the shape of the punch force vs. tool depth curve gives insight into the onset of wrinkles. The simulation is then used to predict a binder-ring force that would mitigate wrinkle formation in a four-layer preform.