It was discovered that MgO or Mg(OH){sub 2} when it reacts with water is a very strong sorbent for arsenic. Distribution constants, or K{sub d} values, are as high as 1 x 10{sup 6} L/mole. In this work, Mg(OH){sub 2} and other compounds have been investigated as sorbents for arsenic and other contaminants. This work has resulted in several major accomplishments including: (1) design, construction, and testing of a pressure sand filter to remove Mg(OH){sub 2} after it has sorbed arsenic from water, (2) stabilization of Mg(OH){sub 2} as a Sorrel's cement against reaction with carbonate that results in MgCO{sub 3} formation decreasing the efficiency of Mg(OH){sub 2} to sorb arsenic, and (3) the development of a new, very promising sorbent for arsenic based on zirconium. Zirconium is an environmentally benign material found in many common products such as toothpaste. It is currently used in water treatment and is very inexpensive. In this work, zirconium has been bonded to activated carbon, zeolites, sand and montmorillonite. Because of its high charge in ionic form (+6), zirconium is a strong sorbent for many anions including arsenic. In equilibrium experiments arsenic concentrations in water were reduced from 200 ppb to less than 1 ppb in less than 1 minute of contact time. Additionally, analytical methods for detecting arsenic in water have also been investigated. Various analytical techniques including HPLC, AA and ICP-MS are used for quantification of arsenic. Due to large matrix interferences HPLC and AA techniques are not very selective and are time consuming. ICP-MS is highly efficient, requires a low sample volume and has a high tolerance for interferences. All these techniques are costly and require trained staff, and with the exception of ICP-MS, these methods cannot be used at low ppb arsenic concentration without using a pre-concentration step. An alternative to these traditional techniques is to use a colorimetric method based on leucocrystal violet dye interaction with iodine. This method has been adapted in our facility for quantifying arsenic concentrations down to 14 ppb.
Aspen, a powerful economic modeling tool that uses agent modeling and genetic algorithms, can accurately simulate the economy. In it, individuals are hired by firms to produce a good that households then purchase. The firms decide what price to charge for this good, and based on that price, the households determine which firm to purchase from. We will attempt to discover the Nash Equilibrium price found in this model under two different methods of determining how many orders each firm receives. To keep it simple, we will assume there are only two firms in our model, and that these firms compete for the sale of one identical good.
This report outlines our work on the integration of high efficiency photonic lattice structures with MEMS (MicroElectroMechanical Systems). The simplest of these structures were based on 1-D mirror structures. These were integrated into a variety of devices, movable mirrors, switchable cavities and finally into Bragg fiber structures which enable the control of light in at least 2 dimensions. Of these devices, the most complex were the Bragg fibers. Bragg fibers consist of hollow tubes in which light is guided in a low index media (air) and confined by surrounding Bragg mirror stacks. In this work, structures with internal diameters from 5 to 30 microns have been fabricated and much larger structures should also be possible. We have demonstrated the fabrication of these structures with short wavelength band edges ranging from 400 to 1600nm. There may be potential applications for such structures in the fields of integrated optics and BioMEMS. We have also looked at the possibility of waveguiding in 3 dimensions by integrating defects into 3-dimensional photonic lattice structures. Eventually it may be possible to tune such structures by mechanically modulating the defects.
The purpose of this review was to provide insights and information to Sandia National Laboratories' (SNL) Education Council on the state of technical education and training at SNL in order to address the concern that a change in philosophy surrounding education had occurred. To accomplish this, the status of current and past technical training and education programs were compared, and significant changes at SNL were assessed for their impact on education and training. Major changes in education and training are in the advertisement of course offerings, the course delivery methods, and the funding mechanisms for student and instructor time as well as course costs. The significant changes in SNL which influenced technical training and education are the considerable increase in mandatory or compliance training, a fundamental shift in SNL's management structure from an institutional structure to a more business-like, project-budgeted structure, and the change in SNL's mission at the end of the Cold War. These changes contributed to less time for technical training, reduction of training funds, elimination of some training, and a Service Center approach to paying for training. Most importantly, the overall combined effect has resulted in a shift from a strategic to a tactical training approach. The Corporate Training Department (CTD) has maneuvered to accommodate these changes and keep abreast of constantly changing needs.
Sandia National Laboratories has been investigating the use of remotely operated weapon platforms in Department of Energy (DOE) facilities. These platforms offer significant force multiplication and enhancement by enabling near instantaneous response to attackers, increasing targeting accuracy, removing personnel from direct weapon fire, providing immunity to suppressive fire, and reducing security force size needed to effectively respond. Test results of the Telepresent Rapid Aiming Platform (TRAP) from Precision Remotes, Inc. have been exceptional and response from DOE sites and the U.S. Air Force is enthusiastic. Although this platform performs comparably to a trained marksman, the target acquisition speeds are up to three times longer. TRAP is currently enslaved to a remote operator's joystick. Tracking moving targets with a joystick is difficult; it dependent upon target range, movement patterns, and operator skill. Even well-trained operators encounter difficulty tracking moving targets. Adding intelligent targeting capabilities on a weapon platform such as TRAP would significantly improve security force response in terms of effectiveness and numbers of responders. The initial goal of this project was to integrate intelligent targeting with TRAP. However, the unavailability of a TRAP for laboratory purposes drove the development of a new platform that simulates TRAP but has a greater operating range and is significantly faster to reposition.
The Global Energy Futures Model (GEFM) is a demand-based, gross domestic product (GDP)-driven, dynamic simulation tool that provides an integrated framework to model key aspects of energy, nuclear-materials storage and disposition, environmental effluents from fossil and non fossil energy and global nuclear-materials management. Based entirely on public source data, it links oil, natural gas, coal, nuclear and renewable energy dynamically to greenhouse-gas emissions and 12 other measures of environmental impact. It includes historical data from 1990 to 2000, is benchmarked to the DOE/EIA/IEO 2001 [5] Reference Case for 2000 to 2020, and extrapolates energy demand through the year 2050. The GEFM is globally integrated, and breaks out five regions of the world: United States of America (USA), the Peoples Republic of China (China), the former Soviet Union (FSU), the Organization for Economic Cooperation and Development (OECD) nations excluding the USA (other industrialized countries), and the rest of the world (ROW) (essentially the developing world). The GEFM allows the user to examine a very wide range of ''what if'' scenarios through 2050 and to view the potential effects across widely dispersed, but interrelated areas. The authors believe that this high-level learning tool will help to stimulate public policy debate on energy, environment, economic and national security issues.
Recent terrorist attacks in the United States have increased concerns about potential national security consequences from energy supply disruptions. The purpose of this Laboratory Directed Research & Development (LDRD) is to develop a high-level dynamic simulation model that would allow policy makers to explore the national security consequences of major US. energy supply disruptions, and to do so in a way that would integrate energy, economic and environmental components. The model allows exploration of potential combinations of demand-driven energy supplies that meet chosen policy objectives, including: Mitigating economic losses, measured in national economic output and employment levels, due to terrorist activity or forced outages of the type seen in California; Control of greenhouse gas levels and growth rates; and Moderating US. energy import requirements. This work has built upon the Sandia US. Energy and greenhouse Gas Model (USEGM) by integrating a macroeconomic input-output framework into the model, adding the capability to assess the potential economic impact of energy supply disruptions and the associated national security issues. The economic impacts of disruptions are measured in terms of lost US. output (e.g., GDP, sectoral output) and lost employment, and are assessed either at a broad sectoral level (3 sectors) or at a disaggregated level (52 sectors). In this version of the model, physical energy disruptions result in quantitative energy shortfalls, and energy prices are not permitted to rise to clear the markets.
This LDRD project has involved the development and application of Sandia's massively parallel materials modeling software to several significant biophysical systems. They have been successful in applying the molecular dynamics code LAMMPS to modeling DNA, unstructured proteins, and lipid membranes. They have developed and applied a coupled transport-molecular theory code (Tramonto) to study ion channel proteins with gramicidin A as a prototype. they have used the Towhee configurational bias Monte-Carlo code to perform rigorous tests of biological force fields. they have also applied the MP-Sala reacting-diffusion code to model cellular systems. Electroporation of cell membranes has also been studied, and detailed quantum mechanical studies of ion solvation have been performed. In addition, new molecular theory algorithms have been developed (in FasTram) that may ultimately make protein solvation calculations feasible on workstations. Finally, they have begun implementation of a combined molecular theory and configurational bias Monte-Carlo code. They note that this LDRD has provided a basis for several new internal (e.g. several new LDRD) and external (e.g. 4 NIH proposals and a DOE/Genomes to Life) proposals.
As demonstrated by the anthrax attack through the United States mail, people infected by the biological agent itself will give the first indication of a bioterror attack. Thus, a distributed information system that can rapidly and efficiently gather and analyze public health data would aid epidemiologists in detecting and characterizing emerging diseases, including bioterror attacks. We propose using clusters of adverse health events in space and time to detect possible bioterror attacks. Space-time clusters can indicate exposure to infectious diseases or localized exposure to toxins. Most space-time clustering approaches require individual patient data. To protect the patient's privacy, we have extended these approaches to aggregated data and have embedded this extension in a sequential probability ratio test (SPRT) framework. The real-time and sequential nature of health data makes the SPRT an ideal candidate. The result of space-time clustering gives the statistical significance of a cluster at every location in the surveillance area and can be thought of as a ''health-index'' of the people living in this area. As a surrogate to bioterrorism data, we have experimented with two flu data sets. For both databases, we show that space-time clustering can detect a flu epidemic up to 21 to 28 days earlier than a conventional periodic regression technique. We have also tested using simulated anthrax attack data on top of a respiratory illness diagnostic category. Results show we do very well at detecting an attack as early as the second or third day after infected people start becoming severely symptomatic.
Thermoluminescent dosimeters (TLDs), particularly CaF{sub 2}:Mn, are often used as photon dosimeters in mixed (n/{gamma}) field environments. In these mixed field environments, it is desirable to separate the photon response of a dosimeter from the neutron response. For passive dosimeters that measure an integral response, such as TLDs, the separation of the two components must be performed by post-experiment analysis because the TLD reading system cannot distinguish between photon and neutron produced response. Using a model of an aluminum-equilibrated TLD-400 chip, a systematic effort has been made to analytically determine the various components that contribute to the neutron response of a TLD reading. The calculations were performed for five measured reactor neutron spectra and one theoretical thermal neutron spectrum. The five measured reactor spectra all have dosimetry quality experimental values for aluminum-equilibrated TLD-400 chips. Calculations were used to determined the percentage of the total TLD response produced by neutron interactions in the TLD and aluminum equilibrator. These calculations will aid the Sandia National Laboratories-Radiation Metrology Laboratory (SNL-RML) in the interpretation of the uncertainty for TLD dosimetry measurements in the mixed field environments produced by SNL reactor facilities.
Buried landmines are often detected through the chemical signature in the air above the soil surface by mine detection dogs. Environmental processes play a significant role in the chemical signature available for detection. Due to the shallow burial depth of landmines, the weather influences the release of chemicals from the landmine, transport through the soil to the surface, and degradation processes in the soil. The effect of weather on the landmine chemical signature from a PMN landmine was evaluated with the T2TNT code for Kabul, Afghanistan. Results for TNT and DNT gas-phase and soil solid-phase concentrations are presented as a function of time of the day and time of the year.
This report describes research and development of methods to couple vastly different subsystems and physical models and to encapsulate these methods in a Java{trademark}-based framework. The work described here focused on developing a capability to enable design engineers and safety analysts to perform multifidelity, multiphysics analyses more simply. In particular this report describes a multifidelity algorithm for thermal radiative heat transfer and illustrates its performance. Additionally, it describes a module-based computer software architecture that facilitates multifidelity, multiphysics simulations. The architecture is currently being used to develop an environment for modeling the effects of radiation on electronic circuits in support of the FY 2003 Hostile Environments Milestone for the Accelerated Strategic Computing Initiative.
The quantitative analysis of microstructure and sequence distribution in polysiloxane copolymers using high-resolution solution {sup 29}Si NMR is reported. Copolymers containing dimethylsiloxane (DMS) and diphenysiloxane (DPS) monomer units prepared with either high vinyl content (HVM) or low vinyl content (LVM) were analyzed. The average run length (R{sub exp}), the number average sequence length (l{sub A}, l{sub B}), along with the various linkage probabilities (p{sub AA}, p{sub AB}, p{sub BA}, and p{sub BB}) were determined for different production lots of the LVM97 and HVM97 samples to address the lot variability of microstructure in these materials.
In an effort to recruit and retain skilled workers in the Manufacturing Science and Technology Center (14000), an innovative and highly diverse team at Sandia National Laboratories and the U.S. Department of Energy joined with concerned community constitutents, such as Albuquerque Technical Vocational Institute and the Albuquerque Public Schools, to offer mentoring and on-the-job training to qualified students in high schools and community colleges. Now, within several years of its inception, the educational program called the Advanced Manufacturing Trades Training Program is a model in the community and the nation, while enabling Sandia to have valuable trained and skilled employees to meet its national mission and workforce demands.
This manual describes the use of the Xyce Parallel Electronic Simulator code for simulating electrical circuits at a variety of abstraction levels. The Xyce Parallel Electronic Simulator has been written to support,in a rigorous manner, the simulation needs of the Sandia National Laboratories electrical designers. As such, the development has focused on improving the capability over the current state-of-the-art in the following areas: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers. (2) Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. (3) A client-server or multi-tiered operating model wherein the numerical kernel can operate independently of the graphical user interface (GUI). (4) Object-oriented code design and implementation using modern coding-practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. The code is a parallel code in the most general sense of the phrase--a message passing parallel implementation--which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Furthermore, careful attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved even as the number of processors grows. Another feature required by designers is the ability to add device models, many specific to the needs of Sandia, to the code. To this end, the device package in the Xyce Parallel Electronic Simulator is designed to support a variety of device model inputs. These input formats include standard analytical models, behavioral models and look-up tables. Combined with this flexible interface is an architectural design that greatly simplifies the addition of circuit models. One of the most important contribution Xyce makes to the designers at Sandia National Laboratories is in providing a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia now has an ''in-house''capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods) research and development can be performed. Furthermore, these capabilities will then be migrated to the end users.
Fixtures are tools used to hold parts in specific positions and orientations so that certain manufacturing steps can be carried out within required accuracies. Despite the importance of fixtures in the production of expensive devices at Sandia National Laboratories, there is little in-house expertise in mathematical design issues associated with fixtures. As a result, fixtures typically do not work as intended when they are first manufactured. Thus, an inefficient and expensive trial-and-error approach must be utilized. This design methodology adversely impacts important mission duties of Sandia National Laboratories, such as the production of neutron generators. The work performed under the support of this LDRD project took steps toward providing mechanical designers with software tools based on rigorous analytical techniques for dealing with fixture stability and tolerance stack-up.
This report presents a detailed multi-methods comparison of the spatial errors associated with finite difference, finite element and finite volume semi-discretizations of the scalar advection-diffusion equation. The errors are reported in terms of non-dimensional phase and group speeds, discrete diffusivity, artificial diffusivity, and grid-induced anisotropy. It is demonstrated that Fourier analysis (aka von Neumann analysis) provides an automatic process for separating the spectral behavior of the discrete advective operator into its symmetric dissipative and skew-symmetric advective components. Further it is demonstrated that streamline upwind Petrov-Galerkin and its control-volume finite element analogue, streamline upwind control-volume, produce both an artificial diffusivity and an artificial phase speed in addition to the usual semi-discrete artifacts observed in the discrete phase speed, group speed and diffusivity. For each of the numerical methods considered, asymptotic truncation error and resolution estimates are presented for the limiting cases of pure advection and pure diffusion. The Galerkin finite element method and its streamline upwind derivatives are shown to exhibit super-convergent behavior in terms of phase and group speed when a consistent mass matrix is used in the formulation. In contrast, the CVFEM method and its streamline upwind derivatives yield strictly second-order behavior. While this work can only be considered a first step in a comprehensive multi-methods analysis and comparison, it serves to identify some of the relative strengths and weaknesses of multiple numerical methods in a common mathematical framework.
BURNCAL is a Fortran computer code designed to aid in analysis, prediction, and optimization of fuel burnup performance in a nuclear reactor. The code uses output parameters generated by the Monte Carlo neutronics code MCNP to determine the isotopic inventory as a function of time and power density. The code allows for multiple fueled regions to be analyzed. The companion code, RELOAD, can be used to shuffle fueled regions or reload regions with fresh fuel. BURNCAL can be used to study the reactivity effects and isotopic inventory as a function of time for a nuclear reactor system. Neutron transmutation, fission, and radioactive decay are included in the modeling of the production and removal terms for each isotope of interest. For a fueled region, neutron transmutation, fuel depletion, fission-product poisoning, actinide generation, and burnable poison loading and depletion effects are included in the calculation. Fueled and un-fueled regions, such as cladding and moderator, can be analyzed simultaneously. The nuclides analyzed are limited only by the neutron cross section availability in the MCNP cross-section library. BURNCAL is unique in comparison to other burnup codes in that it does not use the calculated neutron flux as input to other computer codes to generate the nuclide mixture for the next time step. Instead, BURNCAL directly uses the neutron absorption tally/reaction information generated by MCNP for each nuclide of interest to determine the nuclide inventory for that region. This allows for the full capabilities of MCNP to be incorporated into the calculation and a more accurate and robust analysis to be performed.
An analysis was conducted of the potential for unmanned and unattended robotic technologies for forward-based, immediate response capabilities that enables access and controlled task performance. The authors analyze high-impact response scenarios in conjunction with homeland security organizations, such as the NNSA Office of Emergency Response, the FBI, the National Guard, and the Army Technical Escort Unit, to cover a range of radiological, chemical and biological threats. They conducted an analysis of the potential of forward-based, unmanned and unattended robotic technologies to accelerate and enhance emergency and crisis response by Homeland Defense organizations. Response systems concepts were developed utilizing new technologies supported by existing emerging threats base technologies to meet the defined response scenarios. These systems will pre-position robotic and remote sensing capabilities stationed close to multiple sites for immediate action. Analysis of assembled systems included experimental activities to determine potential efficacy in the response scenarios, and iteration on systems concepts and remote sensing and robotic technologies, creating new immediate response capabilities for Homeland Defense.
The SNL/NM FY2001 SWEIS Annual Review discusses changes in facilities and facility operations that have occurred in selected and notable facilities since source data were collected for the SNL/NM SWEIS (DOE/EIS-0281). The following information is presented: (1) An updated overview of SNL/NM selected and notable facilities and infrastructure capabilities. (2) An overview of SNL/NM environment, safety, and health programs, including summaries of the purpose, operations, activities, hazards, and hazard controls at relevant facilities and risk management methods for SNL/NM. (3) Updated base year activities data, projections of FY2003 and FY2008 activities, together with related inventories, material consumption, emissions, waste, and resource consumption. (4) Appendices summarizing activities and related hazards at SNL/NM individual special, general, and highbay laboratories, and chemical purchases.