A decomposition model has been developed to predict the response of removable syntactic foam (RSF) exposed to fire-like heat fluxes. RSF consists of glass micro-balloons (GMB) in a cured epoxy polymer matrix. A chemistry model is presented based on the chemical structure of the epoxy polymer, mass transport of polymer fragments to the bulk gas, and vapor-liquid equilibrium. Thermophysical properties were estimated from measurements. A bubble nucleation, growth, and coalescence model was used to describe changes in properties with the extent of reaction. Decomposition of a strand of syntactic foam exposed to high temperatures was simulated.
A coupled Euler-Lagrange solution approach is used to model the response of a buried reinforced concrete structure subjected to a close-in detonation of a high explosive charge. The coupling algorithm is discussed along with a set of benchmark calculations involving detonations in clay and sand.
Genetic programming (GP) has proved to be a highly versatile and useful tool for identifying relationships in data for which a more precise theoretical construct is unavailable. In this project, we use a GP search to develop trading strategies for agent based economic models. These strategies use stock prices and technical indicators, such as the moving average convergence/divergence and various exponentially weighted moving averages, to generate buy and sell signals. We analyze the effect of complexity constraints on the strategies as well as the relative performance of various indicators. We also present innovations in the classical genetic programming algorithm that appear to improve convergence for this problem. Technical strategies developed by our GP algorithm can be used to control the behavior of agents in economic simulation packages, such as ASPEN-D, adding variety to the current market fundamentals approach. The exploitation of arbitrage opportunities by technical analysts may help increase the efficiency of the simulated stock market, as it does in the real world. By improving the behavior of simulated stock markets, we can better estimate the effects of shocks to the economy due to terrorism or natural disasters.
The primary goals of the present study are to: (1) determine how and why MEMS-scale friction differs from friction on the macro-scale, and (2) to begin to develop a capability to perform finite element simulations of MEMS materials and components that accurately predicts response in the presence of adhesion and friction. Regarding the first goal, a newly developed nanotractor actuator was used to measure friction between molecular monolayer-coated, polysilicon surfaces. Amontons law does indeed apply over a wide range of forces. However, at low loads, which are of relevance to MEMS, there is an important adhesive contribution to the normal load that cannot be neglected. More importantly, we found that at short sliding distances, the concept of a coefficient of friction is not relevant; rather, one must invoke the notion of 'pre-sliding tangential deflections' (PSTD). Results of a simple 2-D model suggests that PSTD is a cascade of small-scale slips with a roughly constant number of contacts equilibrating the applied normal load. Regarding the second goal, an Adhesion Model and a Junction Model have been implemented in PRESTO, Sandia's transient dynamics, finite element code to enable asperity-level simulations. The Junction Model includes a tangential shear traction that opposes the relative tangential motion of contacting surfaces. An atomic force microscope (AFM)-based method was used to measure nano-scale, single asperity friction forces as a function of normal force. This data is used to determine Junction Model parameters. An illustrative simulation demonstrates the use of the Junction Model in conjunction with a mesh generated directly from an atomic force microscope (AFM) image to directly predict frictional response of a sliding asperity. Also with regards to the second goal, grid-level, homogenized models were studied. One would like to perform a finite element analysis of a MEMS component assuming nominally flat surfaces and to include the effect of roughness in such an analysis by using a homogenized contact and friction models. AFM measurements were made to determine statistical information on polysilicon surfaces with different roughnesses, and this data was used as input to a homogenized, multi-asperity contact model (the classical Greenwood and Williamson model). Extensions of the Greenwood and Williamson model are also discussed: one incorporates the effect of adhesion while the other modifies the theory so that it applies to the case of relatively few contacting asperities.
This report discusses a set of verification test cases for the frequency-domain, boundary-element, electromagnetics code Eiger based on the analytical solution of plane wave scattering from a sphere. Three cases will be considered: when the sphere is made of perfect electric conductor, when the sphere is made of lossless dielectric and when the sphere is made of lossy dielectric. We outline the procedures that must be followed in order to carefully compare the numerical solution to the analytical solution. We define an error criterion and demonstrate convergence behavior for both the analytical and numerical cases. These problems test the code's ability to calculate the surface current density and secondary quantities, such as near fields and far fields.
In this paper we present an analysis of a new configuration for achieving spin stabilized magnetic levitation. In the classical configuration, the rotor spins about a vertical axis; and the spin stabilizes the lateral instability of the top in the magnetic field. In this new configuration the rotor spins about a horizontal axis; and the spin stabilizes the axial instability of the top in the magnetic field.
ML is a multigrid preconditioning package intended to solve linear systems of equations Ax = b where A is a user supplied n x n sparse matrix, b is a user supplied vector of length n and x is a vector of length n to be computed. ML should be used on large sparse linear systems arising from partial differential equation (PDE) discretizations. While technically any linear system can be considered, ML should be used on linear systems that correspond to things that work well with multigrid methods (e.g. elliptic PDEs). ML can be used as a stand-alone package or to generate preconditioners for a traditional iterative solver package (e.g. Krylov methods). We have supplied support for working with the Aztec 2.1 and AztecOO iterative package [16]. However, other solvers can be used by supplying a few functions. This document describes one specific algebraic multigrid approach: smoothed aggregation. This approach is used within several specialized multigrid methods: one for the eddy current formulation for Maxwell's equations, and a multilevel and domain decomposition method for symmetric and nonsymmetric systems of equations (like elliptic equations, or compressible and incompressible fluid dynamics problems). Other methods exist within ML but are not described in this document. Examples are given illustrating the problem definition and exercising multigrid options.
As technical knowledge grows deeper, broader, and more interconnected, knowledge domains increasingly combine a number of sub-domains. More often than not, each of these sub-domains has its own community of specialists and forums for interaction. Hence, from a generalist's viewpoint, it is sometimes difficult to understand the relationships between the sub-domains within the larger domain; and, from a specialist's viewpoint, it may be difficult for those working in one sub-domain to keep abreast of knowledge gained in another sub-domain. These difficulties can be especially important in the initial stages of creating new projects aimed at adding knowledge either at the domain or sub-domain level. To circumvent these difficulties, one would ideally like to create a map of the knowledge domain--a map which would help clarify relationships between the various sub-domains, and a map which would help inform choices regarding investing in the production of knowledge either at the domain or sub-domain levels. In practice, creating such a map is non-trivial. First, relationships between knowledge subdomains are complex, and not likely to be easily simplified into a visualizable 2-or-few-dimensional map. Second, even if some of the relationships can be simplified, capturing them would require some degree of expert understanding of the knowledge domain, rendering impossible any fully automated method for creating the map. In this work, we accept these limitations, and within them, attempt to explore semi-automated methodologies for creating such a map. We chose as the knowledge domain for this case study 'displacement damage phenomena in Si junction devices'. This knowledge domain spans a particularly wide range of knowledge subdomains, and hence is a particularly challenging one.
Microfluidic systems are becoming increasingly complicated as the number of applications grows. The use of microfluidic systems for chemical and biological agent detection, for example, requires that a given sample be subjected to many process steps, which requires microvalves to control the position and transport of the sample. Each microfluidic application has its own specific valve requirements and this has precipitated the wide variety of valve designs reported in the literature. Each of these valve designs has its strengths and weaknesses. The strength of the valve design proposed here is its simplicity, which makes it easy to fabricate, easy to actuate, and easy to integrate with a microfluidic system. It can be applied to either gas phase or liquid phase systems. This novel design uses a secondary fluid to stop the flow of the primary fluid in the system. The secondary fluid must be chosen based on the type of flow that it must stop. A dielectric fluid must be used for a liquid phase flow driven by electroosmosis, and a liquid with a large surface tension should be used to stop a gas phase flow driven by a weak pressure differential. Experiments were carried out investigating certain critical functions of the design. These experiments verified that the secondary fluid can be reversibly moved between its 'valve opened' and 'valve closed' positions, where the secondary fluid remained as one contiguous piece during this transport process. The experiments also verified that when Fluorinert is used as the secondary fluid, the valve can break an electric circuit. It was found necessary to apply a hydrophobic coating to the microchannels to stop the primary fluid, an aqueous electrolyte, from wicking past the Fluorinert and short-circuiting the valve. A simple model was used to develop valve designs that could be closed using an electrokinetic pump, and re-opened by simply turning the pump off and allowing capillary forces to push the secondary fluid back into its stowed position.
The goal of this study was to first establish the fitness for service of the carbon steel based oil coolers presently located at the Bryan Mound and West Hackberry sites, and second, to compare quantitatively the performance of two proposed corrosion mitigation strategies. To address these goals, a series of flow loops were constructed to simulate the conditions present within the oil coolers allowing the performance of each corrosion mitigation strategy, as well as the baseline performance of the existing systems, to be assessed. As prior experimentation had indicated that the corrosion and fouling was relatively uniform within the oil coolers, the hot and cold side of the system were simulated, representing the extremes of temperature observed within a typical oil cooler. Upon completion of the experiment, the depth of localized attack observed on carbon steel was such that perforation of the tube walls would likely result within a 180 day drawdown procedure at West Hackberry. Furthermore, considering the average rate of wall recession (from LPR measurements), combined with the extensive localized attack (pitting) which occurred in both environments, the tubing wall thickness remaining after 180 days would be less than that required to contain the operating pressures of the oil coolers for both sites. Finally, the inhibitor package, while it did reduce the measured corrosion rate in the case of the West Hackberry solutions, did not provide a sufficient reduction in the observed attack to justify its use.
The Seldon terrorist model represents a multi-disciplinary approach to developing organization software for the study of terrorist recruitment and group formation. The need to incorporate aspects of social science added a significant contribution to the vision of the resulting Seldon toolkit. The unique addition of and abstract agent category provided a means for capturing social concepts like cliques, mosque, etc. in a manner that represents their social conceptualization and not simply as a physical or economical institution. This paper provides an overview of the Seldon terrorist model developed to study the formation of cliques, which are used as the major recruitment entity for terrorist organizations.
Natural gas is a clean fuel that will be the most important domestic energy resource for the first half the 21st centtuy. Ensuring a stable supply is essential for our national energy security. The research we have undertaken will maximize the extractable volume of gas while minimizing the environmental impact of surface disturbances associated with drilling and production. This report describes a methodology for comprehensive evaluation and modeling of the total gas system within a basin focusing on problematic horizontal fluid flow variability. This has been accomplished through extensive use of geophysical, core (rock sample) and outcrop data to interpret and predict directional flow and production trends. Side benefits include reduced environmental impact of drilling due to reduced number of required wells for resource extraction. These results have been accomplished through a cooperative and integrated systems approach involving industry, government, academia and a multi-organizational team within Sandia National Laboratories. Industry has provided essential in-kind support to this project in the forms of extensive core data, production data, maps, seismic data, production analyses, engineering studies, plus equipment and staff for obtaining geophysical data. This approach provides innovative ideas and technologies to bring new resources to market and to reduce the overall environmental impact of drilling. More importantly, the products of this research are not be location specific but can be extended to other areas of gas production throughout the Rocky Mountain area. Thus this project is designed to solve problems associated with natural gas production at developing sites, or at old sites under redevelopment.
Nove, Charles E.; Maclin, Richard F.; Theuninck, Andrew K.; Newland, Jeremy L.; Torrey, Lisa A.; Robinson, Eric R.
A novel method employing machine-based learning to identify messages related to other messages is described and evaluated. This technique may enable an analyst to identify and correlate a small number of related messages from a large sample of individual messages. The classic machine learning techniques of decision trees and naive Bayes classification are seeded with few (or no) messages of interest and 'learn' to identify other related messages. The performance of this approach and these specific learning techniques are evaluated and generalized.
This report describes both a general methodology and specific examples of completely passive microwave tags. Surface acoustic wave (SAW) devices were used to make tags for both identification and sensing applications at different frequencies. SAW correlators were optimized for wireless identification, and SAW filters were developed to enable wireless remote sensing of physical properties. Identification tag applications and wireless remote measurement applications are discussed. Significant effort went into optimizing the SAW devices used for this work, and the lessons learned from that effort are reviewed.
Hydrogen has the potential to become an integral part of our energy transportation and heat and power sectors in the coming decades and offers a possible solution to many of the problems associated with a heavy reliance on oil and other fossil fuels. The Hydrogen Futures Simulation Model (H2Sim) was developed to provide a high level, internally consistent, strategic tool for evaluating the economic and environmental trade offs of alternative hydrogen production, storage, transport and end use options in the year 2020. Based on the model's default assumptions, estimated hydrogen production costs range from 0.68 $/kg for coal gasification to as high as 5.64 $/kg for centralized electrolysis using solar PV. Coal gasification remains the least cost option if carbon capture and sequestration costs ($0.16/kg) are added. This result is fairly robust; for example, assumed coal prices would have to more than triple or the assumed capital cost would have to increase by more than 2.5 times for natural gas reformation to become the cheaper option. Alternatively, assumed natural gas prices would have to fall below $2/MBtu to compete with coal gasification. The electrolysis results are highly sensitive to electricity costs, but electrolysis only becomes cost competitive with other options when electricity drops below 1 cent/kWhr. Delivered 2020 hydrogen costs are likely to be double the estimated production costs due to the inherent difficulties associated with storing, transporting, and dispensing hydrogen due to its low volumetric density. H2Sim estimates distribution costs ranging from 1.37 $/kg (low distance, low production) to 3.23 $/kg (long distance, high production volumes, carbon sequestration). Distributed hydrogen production options, such as on site natural gas, would avoid some of these costs. H2Sim compares the expected 2020 per mile driving costs (fuel, capital, maintenance, license, and registration) of current technology internal combustion engine (ICE) vehicles (0.55$/mile), hybrids (0.56 $/mile), and electric vehicles (0.82-0.84 $/mile) with 2020 fuel cell vehicles (FCVs) (0.64-0.66 $/mile), fuel cell vehicles with onboard gasoline reformation (FCVOB) (0.70 $/mile), and direct combustion hydrogen hybrid vehicles (H2Hybrid) (0.55-0.59 $/mile). The results suggests that while the H2Hybrid vehicle may be competitive with ICE vehicles, it will be difficult for the FCV to compete without significant increases in gasoline prices, reduced predicted vehicle costs, stringent carbon policies, or unless they can offer the consumer something existing vehicles can not, such as on demand power, lower emissions, or better performance.
Specimens of poled 'chem-prep' PNZT ceramic from batch HF803 were tested under hydrostatic, uniaxial, and constant stress difference loading conditions at three temperatures of -55, 25, and 75 C and pressures up to 500 MPa. The objective of this experimental study was to obtain the electro-mechanical properties of the ceramic and the criteria of FE (Ferroelectric) to AFE (Antiferroelectric) phase transformations so that grain-scale modeling efforts can develop and test models and codes using realistic parameters. The poled ceramic undergoes anisotropic deformation during the transition from a FE to an AFE structure. The lateral strain measured parallel to the poling direction was typically 35 % greater than the strain measured perpendicular to the poling direction. The rates of increase in the phase transformation pressures per temperature changes were practically identical for both unpoled and poled PNZT HF803 specimens. We observed that the retarding effect of temperature on the kinetics of phase transformation appears to be analogous to the effect of shear stress. We also observed that the FE-to-AFE phase transformation occurs in poled ceramic when the normal compressive stress, acting perpendicular to a crystallographic plane about the polar axis, equals the hydrostatic pressure at which the transformation otherwise takes place.
As part of the Arsenic Water Technology Partnership program, Sandia National Laboratories will carry out field demonstration testing of innovative technologies that have the potential to substantially reduce the costs associated with arsenic removal from drinking water. The scope for this work includes: (1) selection of sites for pilot demonstrations, (2) identification of candidate technologies through Vendor Forums, proof-of-principle bench-scale studies managed by the American Water Works Association Research Foundation (AwwaRF) or the WERC design contest, and (3) pilot-scale studies involving side-by-side tests of innovative technologies. The goal of site selection is identification of a suite of sites that exhibit a sufficiently wide range of groundwater chemistries to allow examination of treatment processes and systems under conditions that are relevant to different geochemical settings throughout the country. A number of candidate sites have been identified through reviews of groundwater quality databases, conference proceedings and discussions with state and local officials. These include sites in New Mexico, Arizona, Colorado, Oklahoma, Illinois, Michigan, Florida, Massachusetts and New Hampshire. In New Mexico, discussions have been held with water utility board staffs in Chama, Jemez Pueblo, Placitas, Socorro and several communities near Las Cruces to determine the suitability of those communities for pilot studies. The initial pilot studies will be carried at Socorro and Jemez Pueblo; other communities will be included as the program progresses. The proposed pilot test at a hot spring water source near Socorro will provide an opportunity to test treatment technologies at relatively high temperatures. If approved by the Tribal Government, the proposed pilot at the Jemez Pueblo would provide an opportunity to test technologies that will remove arsenic in the presence of relatively high concentrations of iron and manganese while leaving the beneficial levels of fluoride unchanged. Candidate technologies for the pilot tests are being reviewed by technical evaluation teams. The initial reviews will consider as many potential technologies and screen out unsuitable ones by considering data from past performance testing, expected costs, complexity of operation and maturity of the technology. The pilot test configurations will depend on the site-specific conditions such as access, power availability, waste disposal options and availability of permanent structures to house the test. Most of the treatment technologies that will be evaluated can be separated into two broad categories: (1) sorption processes that use fixed bed adsorbents and (2) membrane processes. The latter include processes that involve formation of a floc or precipitate that contains the arsenic in a reactor followed by separation of the solids from the water by filtration. Several innovations that could lead to lower treatment costs have been proposed for adsorptive media systems. These include: (1) higher capacity and selectivity using mixed oxides composed of iron and other transition metals, titanium and zirconium based oxides, or mixed resin-metal oxides composite media, (2) improved durability of virgin media and greater chemical stability of the spent media, and (3) use of inexpensive natural or recycled materials with a coating that has a high affinity for arsenic. Improvements to filtration-based treatment systems include: (1) enhanced coagulation with iron compounds or polyelectrolytes and (2) improved filtration with nanocomposite materials. In the pilot tests, the innovative technologies will be evaluated in terms of: (1) their ability to reduce arsenic to levels below the EPA Maximum Contaminant Level (MCL) of 10 ppb, (2) site-specific adsorptive capacity, robustness of performance with respect to likely changes in water quality parameters including pH, TDS, foulants such as Fe, Mn, silica, and organics, effect of competing ions such as other metals and radionuclides, and potentially deleterious effects on the water system such as pipe corrosion from low pH levels, fluoride removal, and generation of disinfection by-products. The new arsenic MCL will result in modification of many rural water systems that otherwise would not require treatment. Opportunities for improvement of water quality in systems that currently do not comply with other standards would be an added benefit from the new arsenic MCL that has both economic and public health value.
Understanding the dynamics of the membrane protein rhodopsin will have broad implications for other membrane proteins and cellular signaling processes. Rhodopsin (Rho) is a light activated G-protein coupled receptor (GPCR). When activated by ligands, GPCRs bind and activate G-proteins residing within the cell and begin a signaling cascade that results in the cell's response to external stimuli. More than 50% of all current drugs are targeted toward G-proteins. Rho is the prototypical member of the class A GPCR superfamily. Understanding the activation of Rho and its interaction with its Gprotein can therefore lead to a wider understanding of the mechanisms of GPCR activation and G-protein activation. Understanding the dark to light transition of Rho is fully analogous to the general ligand binding and activation problem for GPCRs. This transition is dependent on the lipid environment. The effect of lipids on membrane protein activity in general has had little attention, but evidence is beginning to show a significant role for lipids in membrane protein activity. Using the LAMMPS program and simulation methods benchmarked under the IBIG program, we perform a variety of allatom molecular dynamics simulations of membrane proteins.