The engineering analysis community at Sandia National Laboratories uses a number of internal and commercial software codes and tools, including mesh generators, preprocessors, mesh manipulators, simulation codes, post-processors, and visualization packages. We define an analysis workflow as the execution of an ordered, logical sequence of these tools. Various forms of analysis (and in particular, methodologies that use multiple function evaluations or samples) involve executing parameterized variations of these workflows. As part of the DART project, we are evaluating various commercial workflow management systems, including iSIGHT-FD from Engineous. This report documents the results of a scalability test that was driven by DAKOTA and conducted on a parallel computer (Thunderbird). The purpose of this experiment was to examine the suitability and performance of iSIGHT-FD for large-scale, parameterized analysis workflows. As the results indicate, we found iSIGHT-FD to be suitable for this type of application.
Tsao, Jeffrey Y.; Huey, Mark C.; Boyack, Kevin W.; Miksovic, Ann E.
We present an analysis of the literature of solid-state lighting, based on a comprehensive dataset of 35,851 English-language articles and 12,420 U.S. patents published or issued during the years 1977-2004 in the foundational knowledge domain of electroluminescent materials and phenomena. The dataset was created using a complex, iteratively developed search string. The records in the dataset were then partitioned according to: whether they are articles or patents, their publication or issue date, their national or continental origin, whether the active electroluminescent material was inorganic or organic, and which of a number of emergent knowledge sub-domains they aggregate into on the basis of bibliographic coupling. From these partitionings, we performed a number of analyses, including: identification of knowledge sub-domains of historical and recent importance, and trends over time of the contributions of various nations and continents to the knowledge domain and its sub-domains. Among the key results: (1) The knowledge domain as a whole has been growing quickly: the average growth rates of the inorganic and organic knowledge sub-domains have been 8%/yr and 25%/yr, respectively, compared to average growth rates less than 5%/yr for English-language articles and U.S. patents in other knowledge domains. The growth rate of the organic knowledge sub-domain is so high that its historical dominance by the inorganic knowledge sub-domain will, at current trajectories, be reversed in the coming decade. (2) Amongst nations, the U.S. is the largest contributor to the overall knowledge domain, but Japan is on a trajectory to become the largest contributor within the coming half-decade. Amongst continents, Asia became the largest contributor during the past half-decade, overwhelmingly so for the organic knowledge sub-domain. (3) The relative contributions to the article and patent datasets differ for the major continents: North America contributing relatively more patents, Europe contributing relatively more articles, and Asia contributing in a more balanced fashion. (4) For the article dataset, the nations that contribute most in quantity also contribute most in breadth, while the nations that contribute less in quantity concentrate their contributions in particular knowledge sub-domains. For the patent dataset, North America and Europe tend to contribute improvements in end-use applications (e.g., in sensing, phototherapy and communications), while Asia tends to contribute improvements at the materials and chip levels. (5) The knowledge sub-domains that emerge from aggregations based on bibliographic coupling are roughly organized, for articles, by the degree of localization of electrons and holes in the material or phenomenon of interest, and for patents, according to both their emphasis on chips, systems or applications, and their emphasis on organic or inorganic materials. (6) The six 'hottest' topics in the article dataset are: spintronics, AlGaN UV LEDs, nanowires, nanophosphors, polyfluorenes and electrophosphorescence. The nine 'hottest' topics in the patent dataset are: OLED encapsulation, active-matrix displays, multicolor OLEDs, thermal transfer for OLED fabrication, ink-jet printed OLEDs, phosphor-converted LEDs, ornamental LED packages, photocuring and phototherapy, and LED retrofitting lamps. A significant caution in interpreting these results is that they are based on English-language articles and U.S. patents, and hence will tend to over-represent the strength of English-speaking nations (particularly the U.S.), and under-represent the strength of non-English-speaking nations (particularly China).
A loose two-way coupling of SNL's Presto v2.8 and CTH v8.1 analysis code has been developed to support the analysis of explosive loading of structures. Presto is a Lagrangian, three-dimensional explicit, transient dynamics code in the SIERRA mechanics suite for the analysis of structures subjected to impact-like loads. CTH is a hydro code for modeling complex multi-dimensional, multi-material problems that are characterized by large deformations and/or strong shocks. A fundamental assumption in this loose coupling is that the compliance of the structure modeled with Presto is significantly smaller than the compliance of the surrounding medium (e.g. air) modeled with CTH. A current limitation of the coupled code is that the interaction between CTH and thin structures modeled in Presto (e.g. shells) is not supported. Research is in progress to relax this thin-structure limitation.
This report documents a demonstration model of interacting insurgent leadership, military leadership, government leadership, and societal dynamics under a variety of interventions. The primary focus of the work is the portrayal of a token societal model that responds to leadership activities. The model also includes a linkage between leadership and society that implicitly represents the leadership subordinates as they directly interact with the population. The societal model is meant to demonstrate the efficacy and viability of using System Dynamics (SD) methods to simulate populations and that these can then connect to cognitive models depicting individuals. SD models typically focus on average behavior and thus have limited applicability to describe small groups or individuals. On the other hand, cognitive models readily describe individual behavior but can become cumbersome when used to describe populations. Realistic security situations are invariably a mix of individual and population dynamics. Therefore, the ability to tie SD models to cognitive models provides a critical capability that would be otherwise be unavailable.
Hexanitrostilbene (HNS) is a widely used explosive, due in part to its high thermal stability. Degradation of HNS is known to occur through UV, chemical exposure, and heat exposure, which can lead to reduced performance of the material. Common methods of testing for HNS degradation include wet chemical and surface area testing of the material itself, and performance testing of devices that use HNS. The commonly used chemical tests, such as volatility, conductivity and contaminant trapping provide information on contaminants rather than the chemical stability of the HNS itself. Additionally, these tests are destructive in nature. As an alternative to these methods, we have been exploring the use of vibrational spectroscopy as a means of monitoring HNS degradation non-destructively. In particular, infrared (IR) spectroscopy lends itself well to non-destructive analysis. Molecular variations in the material can be identified and compared to pure samples. The utility of IR spectroscopy was evaluated using pressed pellets of HNS exposed to DETA (diethylaminetriamine). Amines are known to degrade HNS, with the proposed product being a {sigma}-adduct. We have followed these changes as a function of time using various IR sampling techniques including photoacoustic and attenuated total reflectance (ATR).