This 3-year research and development effort focused on what we believe is a significant technical gap in existing modeling and simulation capabilities: the representation of plausible human cognition and behaviors within a dynamic, simulated environment. Specifically, the intent of the Simulating Human Behavior for National Security Human Interactions project was to demonstrate initial simulated human modeling capability that realistically represents intra-and inter-group interaction behaviors between simulated humans and human-controlled avatars as they respond to their environment. Significant process was made towards simulating human behaviors through the development of a framework that produces realistic characteristics and movement. The simulated humans were created from models designed to be psychologically plausible by being based on robust psychological research and theory. Progress was also made towards enhancing Sandia National Laboratories' existing cognitive models to support culturally plausible behaviors that are important in representing group interactions. These models were implemented in the modular, interoperable, and commercially supported Umbra ® simulation framework.4
The intent of Sandia National Laboratories' Human Interactions (HI) project is to demonstrate initial virtual human interaction modeling capability. To accomplish this, we have begun the process of simulating human behavior in a manner that produces life-like characteristics and movement, as well as creating the framework for models that are based on the most current experimental research in cognition, perception, physiology, and cognitive modeling. Currently the simulated human models can sense each other, react to each other, and move about in a simulated 3D environment. A preliminary action generation or motor-level cognition model, which transforms abstract actions generated by high-level cognition to actions that can be carried out by a simulated physical human model, has also been developed. Our work has yielded models of perceptual, spatial, and motor functioning and memory that will be embedded in upgrades to the cognitive framework.
The Exascale Computing Project (ECP) provides a unique opportunity to advance computational science and engineering (CSE) through an accelerated growth phase in extreme-scale computing. Central to the project is the development of next-generation applications and software technologies that can exploit emerging architectures for optimal performance and provide high-fidelity, multiphysics, multiscale capabilities. However, disruptive changes in computer architectures and the complexities of tackling new frontiers in extreme-scale modeling, simulation, and analysis present daunting challenges to the productivity of software developers and the sustainability of software artifacts. Members of the CSE community-especially at extreme scales but more broadly at all scales of computing-face an urgent need to improve developer productivity, positively impacting product quality, development time, and staffing resources, and software sustainability, reducing the cost of maintaining, sustaining, and evolving software capabilities.This report summarizes technical and cultural challenges in scientific software productivity and sustainability. We introduce work by the IDEAS project within ECP (called IDEAS-ECP, https://ideas-productivity. org) to foster and advance software productivity and sustainability for extreme-scale CSE, including partnerships with complementary groups. IDEAS goals are to qualitatively change the culture of extreme-scale computational science and to provide a foundation (through software productivity methodologies and an extreme-scale software ecosystem) that enables transformative and reliable next-generation predictive science and decision support. Work spans four synergistic strategies: (1) curating methodologies to improve software practices of individuals and teams, (2) incrementally and iteratively upgrading software practices, (3) establishing software communities, and (4) engaging in community outreach. Because these issues are relevant throughout all scales of scientific computing, we aim for broad readership-and we hope that these experiences and resources may be useful in other contexts, as individuals and teams work within their own projects, institutions, and communities to advance software practices and overall productivity.Members of the IDEAS-ECP project serve as catalysts to address the challenges facing ECP teams by focusing on improving how teams conduct software efforts. A central activity is productivity and sustainability improvement planning (PSIP)-a lightweight, iterative workflow where teams identify their most urgent software bottlenecks and work to overcome them. We explain how teams are more productively tackling science goals through PSIP advances in areas such as software builds, testing, refactoring, and onboarding. As the ECP community works toward an extreme-scale scientific software ecosystem composed of high-quality, reusable software components and libraries, we are advancing methodologies to support Software Development Kits and to improve transparency and reproducibil...
Design and operation of the electric power grid (EPG) relies heavily on computational models. High-fidelity, full-order models are used to study transient phenomena on only a small part of the network. Reduced-order dynamic and power flow models are used when analysis involving thousands of nodes are required due to the computational demands when simulating large numbers of nodes. The level of complexity of the future EPG will dramatically increase due to large-scale deployment of variable renewable generation, active load and distributed generation resources, adaptive protection and control systems, and price-responsive demand. High-fidelity modeling of this future grid will require significant advances in coupled, multi-scale tools and their use on high performance computing (HPC) platforms.
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