This report presents a initial validation strategy for specific SNL pulsed power program applications of the ALEGRA-HEDP radiation-magnetohydrodynamics computer code. The strategy is written to be (1) broadened and deepened with future evolution of particular specifications given in this version; (2) broadly applicable to computational capabilities other than ALEGRA-HEDP directed at the same pulsed power applications. The content and applicability of the document are highly constrained by the R&D thrust of the SNL pulsed power program. This means that the strategy has significant gaps, indicative of the flexibility required to respond to an ongoing experimental program that is heavily engaged in phenomena discovery.
Constitutive models for chemically reacting networks are formulated based on a generalization of the independent network hypothesis. These models account for the coupling between chemical reaction and strain histories, and have been tested by comparison with microscopic molecular dynamics simulations. An essential feature of these models is the introduction of stress transfer functions that describe the interdependence between crosslinks formed and broken at various strains. Efforts are underway to implement these constitutive models into the finite element code Adagio. Preliminary results are shown that illustrate the effects of changing crosslinking and scission rates and history.
Chemical/Biological/Radiological (CBR) contamination events pose a considerable threat to our nation's infrastructure, especially in large internal facilities, external flows, and water distribution systems. Because physical security can only be enforced to a limited degree, deployment of early warning systems is being considered. However to achieve reliable and efficient functionality, several complex questions must be answered: (1) where should sensors be placed, (2) how can sparse sensor information be efficiently used to determine the location of the original intrusion, (3) what are the model and data uncertainties, (4) how should these uncertainties be handled, and (5) how can our algorithms and forward simulations be sufficiently improved to achieve real time performance? This report presents the results of a three year algorithmic and application development to support the identification, mitigation, and risk assessment of CBR contamination events. The main thrust of this investigation was to develop (1) computationally efficient algorithms for strategically placing sensors, (2) identification process of contamination events by using sparse observations, (3) characterization of uncertainty through developing accurate demands forecasts and through investigating uncertain simulation model parameters, (4) risk assessment capabilities, and (5) reduced order modeling methods. The development effort was focused on water distribution systems, large internal facilities, and outdoor areas.
We demonstrate use of a Jacobian-Free Newton-Krylov solver to enable strong thermal coupling at the interface between a solid body and an external compressible fluid. Our method requires only information typically used in loose coupling based on successive substitution and is implemented within a multi-physics framework. We present results for two external flows over thermally conducting solid bodies obtained using both loose and strong coupling strategies. Performance of the two strategies is compared to elucidate both advantages and caveats associated with strong coupling.
This report summarizes the results of an effort to establish a framework for assigning and communicating technology readiness levels (TRLs) for the modeling and simulation (ModSim) capabilities at Sandia National Laboratories. This effort was undertaken as a special assignment for the Weapon Simulation and Computing (WSC) program office led by Art Hale, and lasted from January to September 2006. This report summarizes the results, conclusions, and recommendations, and is intended to help guide the program office in their decisions about the future direction of this work. The work was broken out into several distinct phases, starting with establishing the scope and definition of the assignment. These are characterized in a set of key assertions provided in the body of this report. Fundamentally, the assignment involved establishing an intellectual framework for TRL assignments to Sandia's modeling and simulation capabilities, including the development and testing of a process to conduct the assignments. To that end, we proposed a methodology for both assigning and understanding the TRLs, and outlined some of the restrictions that need to be placed on this process and the expected use of the result. One of the first assumptions we overturned was the notion of a ''static'' TRL--rather we concluded that problem context was essential in any TRL assignment, and that leads to dynamic results (i.e., a ModSim tool's readiness level depends on how it is used, and by whom). While we leveraged the classic TRL results from NASA, DoD, and Sandia's NW program, we came up with a substantially revised version of the TRL definitions, maintaining consistency with the classic level definitions and the Predictive Capability Maturity Model (PCMM) approach. In fact, we substantially leveraged the foundation the PCMM team provided, and augmented that as needed. Given the modeling and simulation TRL definitions and our proposed assignment methodology, we conducted four ''field trials'' to examine how this would work in practice. The results varied substantially, but did indicate that establishing the capability dependencies and making the TRL assignments was manageable and not particularly time consuming. The key differences arose in perceptions of how this information might be used, and what value it would have (opinions ranged from negative to positive value). The use cases and field trial results are included in this report. Taken together, the results suggest that we can make reasonably reliable TRL assignments, but that using those without the context of the information that led to those results (i.e., examining the measures suggested by the PCMM table, and extended for ModSim TRL purposes) produces an oversimplified result--that is, you cannot really boil things down to just a scalar value without losing critical information.
Processing-in-Memory (PIM) technology encompasses a range of research leveraging a tight coupling of memory and processing. The most unique features of the technology are extremely wide paths to memory, extremely low memory latency, and wide functional units. Many PIM researchers are also exploring extremely fine-grained multi-threading capabilities. This paper explores a mechanism for leveraging these features of PIM technology to enhance commodity architectures in a seemingly mundane way: accelerating MPI. Modern network interfaces leverage simple processors to offload portions of the MPI semantics, particularly the management of posted receive and unexpected message queues. Without adding cost or increasing clock frequency, using PIMs in the network interface can enhance performance. The results are a significant decrease in latency and increase in small message bandwidth, particularly when long queues are present.
This paper is about making reversible logic a reality for supercomputing. Reversible logic offers a way to exceed certain basic limits on the performance of computers, yet a powerful case will have to be made to justify its substantial development expense. This paper explores the limits of current, irreversible logic for supercomputers, thus forming a threshold above which reversible logic is the only solution. Problems above this threshold are discussed, with the science and mitigation of global warming being discussed in detail. To further develop the idea of using reversible logic in supercomputing, a design for a 1 Zettaflops supercomputer as required for addressing global climate warming is presented. However, to create such a design requires deviations from the mainstream of both the software for climate simulation and research directions of reversible logic. These deviations provide direction on how to make reversible logic practical. Copyright 2005 ACM.
This paper provides an overview of several approaches to formulating and solving optimization under uncertainty (OUU) engineering design problems. In addition, the topic of high-performance computing and OUU is addressed, with a discussion of the coarse- and fine-grained parallel computing opportunities in the various OUU problem formulations. The OUU approaches covered here are: sampling-based OUU, surrogate model-based OUU, analytic reliability-based OUU (also known as reliability-based design optimization), polynomial chaos-based OUU, and stochastic perturbation-based OUU.
We performed molecular dynamics simulations of beta-amyloid (A{beta}) protein and A{beta} fragment(31-42) in bulk water and near hydrated lipids to study the mechanism of neurotoxicity associated with the aggregation of the protein. We constructed full atomistic models using Cerius2 and ran simulations using LAMMPS. MD simulations with different conformations and positions of the protein fragment were performed. Thermodynamic properties were compared with previous literature and the results were analyzed. Longer simulations and data analyses based on the free energy profiles along the distance between the protein and the interface are ongoing.