Publications

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We present all-atom molecular dynamics simulations of biologically realistic transmembrane potential gradients across a DMPC bilayer. These simulations are the first to model this gradient in all-atom detail, with the field generated solely by explicit ion dynamics. Unlike traditional bilayer simulations that have one bilayer per unit cell, we simulate a 170 mV potential gradient by using a unit cell consisting of three salt-water baths separated by two bilayers, with full three-dimensional periodicity. The study shows that current computational resources are powerful enough to generate a truly electrified interface, as we show the predicted effect of the field on the overall charge distribution. Additionally, starting from Poisson's equation, we show a new derivation of the double integral equation for calculating the potential profile in systems with this type of periodicity.

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Sandia National Laboratories (SNL) has developed a number of security risk assessment methodologies (RAMs) for various infrastructures including dams, water systems, electrical transmission, chemical facilities and communities. All of these RAMs consider potential malevolent attacks from different threats, possible undesired events and consequences and determine potential adversary success. They focus on the assessment of these infrastructures to help identify security weaknesses and develop measures to help mitigate the consequences from possible adversary attacks. This paper will focus on RAM-C, the security risk assessment methodology for communities. There are many reasons for a community to conduct a security risk assessment. They include: providing a way to identify vulnerabilities, helping a community to be better prepared in the event of an adversary attack, providing justification for resources to address identified vulnerabilities and planning for future projects. RAM-C provides a systematic, risk-based approach useable by public safety and emergency planners to determine relative risk and provides useful information in making security risk decisions. RAM-C consists of a number of steps starting with a screening step which selects facilities based on a documented process; characterization of the community and facilities; determination of severity of consequences for identified undesired events; determination of the community protection goals and defining the threat; defining existing baseline safeguard measures; analyzing protection system effectiveness against identified scenarios, determining a relative risk and finally deciding if that risk is too high. If the risk is too high then possible countermeasures and mitigation measures are considered. RAM-C has been used by a number of communities within the United States. From these assessments there have been many results. Some communities have been surprised by the vulnerabilities that have been identified; have identified the need to test procedures and responses to many different situations; have identified the need to have redundancy in certain systems and have identified who within their community are valuable resources. The RAM-C process is a systematic way to assess vulnerabilities and make decisions based on risk. It has provided valuable information to community planners.

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We are extending the existing features of Aspen, a powerful economic modeling tool, and introducing new features to simulate the role of confidence in economic activity. The new model is built from a collection of autonomous agents that represent households, firms, and other relevant entities like financial exchanges and governmental authorities. We simultaneously model several interrelated markets, including those for labor, products, stocks, and bonds. We also model economic tradeoffs, such as decisions of households and firms regarding spending, savings, and investment. In this paper, we review some of the basic principles and model components and describe our approach and development strategy for emulating consumer, investor, and business confidence. The model of confidence is explored within the context of economic disruptions, such as those resulting from disasters or terrorist events.

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The authors provide a detailed overview of an on-going, multinational test program that is developing aerosol data for some spent fuel sabotage scenarios on spent fuel transport and storage casks. Experiments are being performed to quantify the aerosolized materials plus volatilized fission products generated from actual spent fuel and surrogate material test rods, due to impact by a high-energy-density device. The program participants in the United States plus Germany, France and the United Kingdom, part of the international Working Group for Sabotage Concerns of Transport and Storage Casks (WGSTSC) have strongly supported and coordinated this research program. Sandia National Laboratories has the lead role for conducting this research program; test program support is provided by both the US Department of Energy and the US Nuclear Regulatory Commission. The authors provide a summary of the overall, multiphase test design and a description of all explosive containment and aerosol collection test components used. They focus on the recently initiated tests on 'surrogate' spent fuel, unirradiated depleted uranium oxide and forthcoming actual spent fuel tests, and briefly summarize similar results from completed surrogate tests that used non-radioactive, sintered cerium oxide ceramic pellets in test rods.

We conducted sets of experiments with three diameters of concrete targets that had an average compressive strength of 23 MPa (3.3 ksi) and 76.2-mm-diameter, 3.0 caliber-radius-head, 13-kg projectiles. The three target diameters were D = 1.83, 1.37, and 0.91, so the ratios of the target diameters to the projectile diameter were D/d=24, 18, and 12. The ogive-nose projectiles were machined from 4340 R{sub c} 45 steel and designed to contain a single-channel acceleration data recorder. Thus, we recorded acceleration during launch and deceleration during penetration. An 83-mm-diameter powder gun launched the 13-kg projectiles to striking velocities between 160 and 340 m/s. Measured penetration depths and deceleration-time data were analyzed with a previously published model. We measured negligible changes in penetration depth and only small decreases in deceleration magnitude as the targets diameters were reduced.

As part of meeting the GRPA (Government Performance and Results Act) requirements and to provide input to Sandia's annual Performance Evaluation Assessment Report (PEAR) to the National Nuclear Security Administration in FY2004, a 14-member external review committee chaired by Dr. Alvin Trivelpiece was convened by Sandia National Laboratories (SNL) on May 4-6, 2004 to review Sandia National Laboratories' Pulsed Power Programs. The scope of the review included activities in high energy density physics (HEDP), inertial confinement fusion (ICF), radiation/weapon physics, the petawatt laser initiative (PW) and fast ignition, equation-of state studies, radiation effects science and lethality, x-ray radiography, ZR development, basic research and pulsed power technology research and development, as well as electromagnetics and work for others. In his charge to the Committee, Dr. Jeffrey P. Quintenz, Director of Pulsed Power Sciences (Org. 1600) asked that the evaluation and feedback be based on three criteria: (1) quality of technical activities in science, technology, and engineering, (2) programmatic performance, management, and planning, and (3) relevance to national needs and agency missions. In addition, the director posed specific programmatic questions. The accompanying report, produced as a SAND document, is the report of the Committee's finding.

This report presents a classification scheme for risk assessment methods. This scheme, like all classification schemes, provides meaning by imposing a structure that identifies relationships. Our scheme is based on two orthogonal aspects--level of detail, and approach. The resulting structure is shown in Table 1 and is explained in the body of the report. Each cell in the Table represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. This report imposes structure on the set of risk assessment methods in order to reveal their relationships and thus optimize their usage.We present a two-dimensional structure in the form of a matrix, using three abstraction levels for the rows and three approaches for the columns. For each of the nine cells in the matrix we identify the method type by name and example. The matrix helps the user understand: (1) what to expect from a given method, (2) how it relates to other methods, and (3) how best to use it. Each cell in the matrix represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. The matrix, with type names in the cells, is introduced in Table 2 on page 13 below. Unless otherwise stated we use the word 'method' in this report to refer to a 'risk assessment method', though often times we use the full phrase. The use of the terms 'risk assessment' and 'risk management' are close enough that we do not attempt to distinguish them in this report. The remainder of this report is organized as follows. In Section 2 we provide context for this report--what a 'method' is and where it fits. In Section 3 we present background for our classification scheme--what other schemes we have found, the fundamental nature of methods and their necessary incompleteness. In Section 4 we present our classification scheme in the form of a matrix, then we present an analogy that should provide an understanding of the scheme, concluding with an explanation of the two dimensions and the nine types in our scheme. In Section 5 we present examples of each of our classification types. In Section 6 we present conclusions.

Critical Infrastructures are formed by a large number of components that interact within complex networks. As a rule, infrastructures contain strong feedbacks either explicitly through the action of hardware/software control, or implicitly through the action/reaction of people. Individual infrastructures influence others and grow, adapt, and thus evolve in response to their multifaceted physical, economic, cultural, and political environments. Simply put, critical infrastructures are complex adaptive systems. In the Advanced Modeling and Techniques Investigations (AMTI) subgroup of the National Infrastructure Simulation and Analysis Center (NISAC), we are studying infrastructures as complex adaptive systems. In one of AMTI's efforts, we are focusing on cascading failure as can occur with devastating results within and between infrastructures. Over the past year we have synthesized and extended the large variety of abstract cascade models developed in the field of complexity science and have started to apply them to specific infrastructures that might experience cascading failure. In this report we introduce our comprehensive model, Polynet, which simulates cascading failure over a wide range of network topologies, interaction rules, and adaptive responses as well as multiple interacting and growing networks. We first demonstrate Polynet for the classical Bac, Tang, and Wiesenfeld or BTW sand-pile in several network topologies. We then apply Polynet to two very different critical infrastructures: the high voltage electric power transmission system which relays electricity from generators to groups of distribution-level consumers, and Fedwire which is a Federal Reserve service for sending large-value payments between banks and other large financial institutions. For these two applications, we tailor interaction rules to represent appropriate unit behavior and consider the influence of random transactions within two stylized networks: a regular homogeneous array and a heterogeneous scale-free (fractal) network. For the stylized electric power grid, our initial simulations demonstrate that the addition of geographically unrestricted random transactions can eventually push a grid to cascading failure, thus supporting the hypothesis that actions of unrestrained power markets (without proper security coordination on market actions) can undermine large scale system stability. We also find that network topology greatly influences system robustness. Homogeneous networks that are 'fish-net' like can withstand many more transaction perturbations before cascading than can scale-free networks. Interestingly, when the homogeneous network finally cascades, it tends to fail in its entirety, while the scale-free tends to compartmentalize failure and thus leads to smaller, more restricted outages. In the case of stylized Fedwire, initial simulations show that as banks adaptively set their individual reserves in response to random transactions, the ratio of the total volume of transactions to individual reserves, or 'turnover ratio', increases with increasing volume. The removal of a bank from interaction within the network then creates a cascade, its speed of propagation increasing as the turnover ratio increases. We also find that propagation is accelerated by patterned transactions (as expected to occur within real markets) and in scale-free networks, by the 'attack' of the most highly connected bank. These results suggest that the time scale for intervention by the Federal Reserve to divert a cascade in Fedwire may be quite short. Ongoing work in our cascade analysis effort is building on both these specific stylized applications to enhance their fidelity as well as embracing new applications. We are implementing markets and additional network interactions (e.g., social, telecommunication, information gathering, and control) that can impose structured drives (perturbations) comparable to those seen in real systems. Understanding the interaction of multiple networks, their interdependencies, and in particular, the underlying mechanisms for their growth/evolution is paramount. With this understanding, appropriate public policy can be identified to guide the evolution of present infrastructures to withstand the demands and threats of the future.

High-energy ion tracks (374 MeV Au{sup 26+}) in thin films were examined with transmission electron microscopy to investigate nanopore formation. Tracks in quartz and mica showed diffraction contrast. Tracks in sapphire and mica showed craters formed at the positions of ion incidence and exit, with a lower-density track connecting them. Direct nanopore formation by ions (without chemical etching) would appear to require film thicknesses less than 10 nm.

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The purpose of this presentation is to provide an overview of the science-based materials modeling activities at Sandia National Laboratories, California. The main mission driver for the work is the development of predictive modeling and simulation capabilities leveraging high performance computing software and hardware. Presentation will highlight research accomplishments in several specific topics of current interest. Sandia/California has been engaged in the development of high performance computing based predictive modeling and simulation capabilities in support of the Science-Based Stockpile Stewardship Program of the U. S. Department of Energy. Of particular interest is the development of constitutive models that can efficiently and accurately predict post-failure material response and load-redistribution in systems and components. Fracture and failure are inherently multi-scale and our philosophy is to include required physics in our models at all appropriate scales. We approach the problems from the continuum point of view and intend to provide continuum models that include dominant subscale mechanisms. Moreover, numerical algorithms are needed to allow implementation of physical models in high performance computing codes such that large-scale modeling and simulation can be conducted. Other drivers of our effort include the emerging application of micro- and nano-systems and the increasing interest in biotechnology. In this presentation, our research in fracture and failure modeling, atomic-continuum coupling code development, microstructure-material properties relationships exploration, and general continuum theories advancement will be presented. Where appropriate, examples will be given to demonstrate the utility of the models.

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{sm_bullet}HF/DFT are one-particle approximation to the Schrodinger equation {sm_bullet} The one-particle, mean field approaches are what lead to the nonlinear eigenvalue problem {sm_bullet} DFT includes a parameterized XC functional that reproduces many-electron effects -Very accurate ground state structures and energies - Problematic for excited states, band gaps