Publications

Abstract not provided.

Abstract not provided.

Abstract not provided.

This document describes the form and use of three supplemental capabilities added to Goma during 1998 -- augmenting conditions, automatic continuation and linear stability analysis. Augmenting conditions allow the addition of constraints and auxiliary conditions which describe the relationship between unknowns, boundary conditions, material properties and post-processing extracted quantities. Automatic continuation refers to a family of algorithms (zeroth and first order here, single and multi-parameter) that allow tracking steady-state solution paths as material parameters or boundary conditions are varied. The stability analysis capability in Goma uses the method of small disturbances and superposition of normal modes to test the stability of a steady- state flow, i.e., it determines if the disturbance grows or decays in time.

The potential impacts of man-made and natural disasters on chemical plants, complexes, and supply chains are of great importance to homeland security. To be able to estimate these impacts, we developed an agent-based chemical supply chain model that includes: chemical plants with enterprise operations such as purchasing, production scheduling, and inventories; merchant chemical markets, and multi-modal chemical shipments. Large-scale simulations of chemical-plant activities and supply chain interactions, running on desktop computers, are used to estimate the scope and duration of disruptive-event impacts, and overall system resilience, based on the extent to which individual chemical plants can adjust their internal operations (e.g., production mixes and levels) versus their external interactions (market sales and purchases, and transportation routes and modes). To illustrate how the model estimates the impacts of a hurricane disruption, a simple example model centered on 1,4-butanediol is presented. © 2013 Elsevier Ltd.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Water resource management requires collaborative solutions that cross institutional and political boundaries. This work describes the development and use of a computer-based tool for assessing the impact of additional water allocation from the Gila River and the San Francisco River prescribed in the 2004 Arizona Water Settlements Act. Between 2005 and 2010, Sandia National Laboratories engaged concerned citizens, local water stakeholders, and key federal and state agencies to collaboratively create the Gila-San Francisco Decision Support Tool. Based on principles of system dynamics, the tool is founded on a hydrologic balance of surface water, groundwater, and their associated coupling between water resources and demands. The tool is fitted with a user interface to facilitate sensitivity studies of various water supply and demand scenarios. The model also projects the consumptive use of water in the region as well as the potential CUFA (Consumptive Use and Forbearance Agreement which stipulates when and where Arizona Water Settlements Act diversions can be made) diversion over a 26-year horizon. Scenarios are selected to enhance our understanding of the potential human impacts on the rivers ecological health in New Mexico; in particular, different case studies thematic to water conservation, water rights, and minimum flow are tested using the model. The impact on potential CUFA diversions, agricultural consumptive use, and surface water availability are assessed relative to the changes imposed in the scenarios. While it has been difficult to gage the acceptance level from the stakeholders, the technical information that the model provides are valuable for facilitating dialogues in the context of the new settlement.

In this work, we analyze solid–liquid phase equilibria of molten nitrate salt mixtures. Molten salts are used as heat transfer fluids within concentrated solar power systems. Further understanding of the thermophysical properties of the salt solutions is integral to designing the newest generation of solar power systems. We make use of classical thermodynamics to quickly model the phase equilibrium of mixtures of nitrate salts. This modeling work can serve as a complement to existing experimental efforts in identifying appropriate multicomponent salt mixtures for solar power applications. We present phase calculations of ternary and quaternary mixtures of LiNO3, NaNO3, KNO3, and CsNO3 modeled using the Wilson equation for liquid phase activity coefficients and binary solid–liquid equilibrium data.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Sandia National Laboratories and General Motors Global Energy Systems team conducted a joint biofuels systems analysis project from March to November 2008. The purpose of this study was to assess the feasibility, implications, limitations, and enablers of large-scale production of biofuels. 90 billion gallons of ethanol (the energy equivalent of approximately 60 billion gallons of gasoline) per year by 2030 was chosen as the book-end target to understand an aggressive deployment. Since previous studies have addressed the potential of biomass but not the supply chain rollout needed to achieve large production targets, the focus of this study was on a comprehensive systems understanding the evolution of the full supply chain and key interdependencies over time. The supply chain components examined in this study included agricultural land use changes, production of biomass feedstocks, storage and transportation of these feedstocks, construction of conversion plants, conversion of feedstocks to ethanol at these plants, transportation of ethanol and blending with gasoline, and distribution to retail outlets. To support this analysis, we developed a 'Seed to Station' system dynamics model (Biofuels Deployment Model - BDM) to explore the feasibility of meeting specified ethanol production targets. The focus of this report is water and its linkage to broad scale biofuel deployment.

This study assesses the energy and water use of saltcedar (or tamarisk) as biomass for biofuel production in a hypothetical sub-region in New Mexico. The baseline scenario consists of a rural stretch of the Middle Rio Grande River with 25% coverage of mature saltcedar that is removed and converted to biofuels. A manufacturing system life cycle consisting of harvesting, transportation, pyrolysis, and purification is constructed for calculating energy and water balances. On a dry short ton woody biomass basis, the total energy input is approximately 8.21 mmBTU/st. There is potential for 18.82 mmBTU/st of energy output from the baseline system. Of the extractable energy, approximately 61.1% consists of bio-oil, 20.3% bio-char, and 18.6% biogas. Water consumptive use by removal of tamarisk will not impact the existing rate of evapotranspiration. However, approximately 195 gal of water is needed per short ton of woody biomass for the conversion of biomass to biocrude, three-quarters of which is cooling water that can be recovered and recycled. The impact of salt presence is briefly assessed. Not accounted for in the baseline are high concentrations of Calcium, Sodium, and Sulfur ions in saltcedar woody biomass that can potentially shift the relative quantities of bio-char and bio-oil. This can be alleviated by a pre-wash step prior to the conversion step. More study is needed to account for the impact of salt presence on the overall energy and water balance.

Abstract not provided.

Carbon capture and sequestration (CCS) is an option to mitigate impacts of atmospheric carbon emission. Numerous factors are important in determining the overall effectiveness of long-term geologic storage of carbon, including leakage rates, volume of storage available, and system costs. Recent efforts have been made to apply an existing probabilistic performance assessment (PA) methodology developed for deep nuclear waste geologic repositories to evaluate the effectiveness of subsurface carbon storage (Viswanathan et al., 2008; Stauffer et al., 2009). However, to address the most pressing management, regulatory, and scientific concerns with subsurface carbon storage (CS), the existing PA methodology and tools must be enhanced and upgraded. For example, in the evaluation of a nuclear waste repository, a PA model is essentially a forward model that samples input parameters and runs multiple realizations to estimate future consequences and determine important parameters driving the system performance. In the CS evaluation, however, a PA model must be able to run both forward and inverse calculations to support optimization of CO{sub 2} injection and real-time site monitoring as an integral part of the system design and operation. The monitoring data must be continually fused into the PA model through model inversion and parameter estimation. Model calculations will in turn guide the design of optimal monitoring and carbon-injection strategies (e.g., in terms of monitoring techniques, locations, and time intervals). Under the support of Laboratory-Directed Research & Development (LDRD), a late-start LDRD project was initiated in June of Fiscal Year 2010 to explore the concept of an enhanced performance assessment system (EPAS) for carbon sequestration and storage. In spite of the tight time constraints, significant progress has been made on the project: (1) Following the general PA methodology, a preliminary Feature, Event, and Process (FEP) analysis was performed for a hypothetical CS system. Through this FEP analysis, relevant scenarios for CO{sub 2} release were defined. (2) A prototype of EPAS was developed by wrapping an existing multi-phase, multi-component reservoir simulator (TOUGH2) with an uncertainty quantification and optimization code (DAKOTA). (3) For demonstration, a probabilistic PA analysis was successfully performed for a hypothetical CS system based on an existing project in a brine-bearing sandstone. The work lays the foundation for the development of a new generation of PA tools for effective management of CS activities. At a top-level, the work supports energy security and climate change/adaptation by furthering the capability to effectively manage proposed carbon capture and sequestration activities (both research and development as well as operational), and it greatly enhances the technical capability to address this national problem. The next phase of the work will include (1) full capability demonstration of the EPAS, especially for data fusion, carbon storage system optimization, and process optimization of CO{sub 2} injection, and (2) application of the EPAS to actual carbon storage systems.

Abstract not provided.

Abstract not provided.

Analysis of chemical supply chains is an inherently complex task, given the dependence of these supply chains on multiple infrastructure systems (e.g. transportation and energy). This effort requires data and information at various levels of resolution, ranging from network-level distribution systems to individual chemical reactions. The U.S. Department of Homeland Security (DHS) has tasked the National Infrastructure Simulation and Analysis Center (NISAC) with developing a chemical infrastructure analytical capability to assess interdependencies and complexities of the nation's critical infrastructure, including the chemical sector. To address this need, the Sandia National Laboratories (Sandia)1 component of NISAC has integrated its existing simulation and infrastructure analysis capabilities with various chemical industry datasets to create a capability to analyze and estimate the supply chain and economic impacts resulting from large-scale disruptions to the chemical sector. This development effort is ongoing and is currently being funded by the DHS's Science and Technology Directorate. This paper describes the methodology being used to create the capability and the types of data necessary to exercise the capability, and it presents an example analysis focusing on the ethylene portion of the chemical supply chain.

Chlorinated hydrocarbons represent the precursors for products ranging from polyvinyl chloride (PVC) and refrigerants to pharmaceuticals. Natural or manmade disruptions that affect the availability of these products nationally have the potential to affect a wide range of markets, from healthcare to construction. Analysis of chemical supply chains is an inherently complex task, given the dependence of these supply chains on multiple infrastructure systems (e.g. transportation and energy). This effort requires data and information at various levels of resolution, ranging from network-level distribution systems to individual chemical reactions. The U.S. Department of Homeland Security (DHS) has tasked the National Infrastructure Simulation and Analysis Center (NISAC) with developing a chemical infrastructure analytical capability to assess interdependencies and complexities of the nation's critical infrastructure, including the chemical sector. To address this need, the Sandia National Laboratories (Sandia) component of NISAC has integrated its existing simulation and infrastructure analysis capabilities with various chemical industry datasets to create a capability to analyze and estimate the supply chain economic impacts resulting from large-scale disruptions to the chemical sector. This development effort is ongoing and is currently being funded by the DHS's Science and Technology Directorate. This paper describes the methodology being used to create the capability and the types of data necessary to exercise the capability, and it presents an example analysis focusing on the chlorinated hydrocarbon portion of the chemical supply chain.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Biofouling, the unwanted growth of biofilms on a surface, of water-treatment membranes negatively impacts in desalination and water treatment. With biofouling there is a decrease in permeate production, degradation of permeate water quality, and an increase in energy expenditure due to increased cross-flow pressure needed. To date, a universal successful and cost-effect method for controlling biofouling has not been implemented. The overall goal of the work described in this report was to use high-performance computing to direct polymer, material, and biological research to create the next generation of water-treatment membranes. Both physical (micromixers - UV-curable epoxy traces printed on the surface of a water-treatment membrane that promote chaotic mixing) and chemical (quaternary ammonium groups) modifications of the membranes for the purpose of increasing resistance to biofouling were evaluated. Creation of low-cost, efficient water-treatment membranes helps assure the availability of fresh water for human use, a growing need in both the U. S. and the world.

Abstract not provided.

Abstract not provided.

The objective of this project is to analyze the potential for hydrogen co-production within high-temperature stationary fuel cell systems (H2-FCS) and identify novel designs with minimum CO2 and cost. Specific objectives are to (1) develop novel H2-FCS designs that release low greenhouse gas emissions; and (2) develop novel H2-FCS designs with low hydrogen production cost.

Abstract not provided.

Abstract not provided.

The goal of this study is to model the electrical response of gold plated copper electrical contacts exposed to a mixed flowing gas stream consisting of air containing 10 ppb H{sub 2}S at 30 C and a relative humidity of 70%. This environment accelerates the attack normally observed in a light industrial environment (essentially a simplified version of the Battelle Class 2 environment). Corrosion rates were quantified by measuring the corrosion site density, size distribution, and the macroscopic electrical resistance of the aged surface as a function of exposure time. A pore corrosion numerical model was used to predict both the growth of copper sulfide corrosion product which blooms through defects in the gold layer and the resulting electrical contact resistance of the aged surface. Assumptions about the distribution of defects in the noble metal plating and the mechanism for how corrosion blooms affect electrical contact resistance were needed to complete the numerical model. Comparisons are made to the experimentally observed number density of corrosion sites, the size distribution of corrosion product blooms, and the cumulative probability distribution of the electrical contact resistance. Experimentally, the bloom site density increases as a function of time, whereas the bloom size distribution remains relatively independent of time. These two effects are included in the numerical model by adding a corrosion initiation probability proportional to the surface area along with a probability for bloom-growth extinction proportional to the corrosion product bloom volume. The cumulative probability distribution of electrical resistance becomes skewed as exposure time increases. While the electrical contact resistance increases as a function of time for a fraction of the bloom population, the median value remains relatively unchanged. In order to model this behavior, the resistance calculated for large blooms has been weighted more heavily.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The goal of this LDRD involves development of a system dynamics model to understand the interdependencies between water resource availability and water needs for production of biofuels. Specifically, this model focuses on availability and feasibility of non-traditional water sources from dairy wastewater, produced water from crude oil production and from coal-bed methane gas extraction for the production of algal-based biofuel. The conceptual simulation framework and historical data are based on two locales within New Mexico, the San Juan basin in the northwest and the Permian basin in the southeast, where oil and gas drilling have increased considerably in the last ten years. The overall water balance ignores both transportation options and water chemistry and is broken down by county level. The resulting model contains an algal growth module, a dairy module, an oil production module, and a gas production module. A user interface is also created for controlling the adjustable parameters in the model. Our preliminary investigation indicates a cyclical demand for non-fresh water due to the cyclical nature of algal biomass production and crop evapotranspiration. The wastewater from the dairy industry is not a feasible non-fresh water source because the agricultural water demand for cow's dry feed far exceeds the amount generated at the dairy. The uncertainty associated with the water demand for cow's dry matter intake is the greatest in this model. The oil- and gas-produced water, ignoring the quality, provides ample supply for water demand in algal biomass production. There remains work to address technical challenges associated with coupling the appropriate non-fresh water source to the local demand.

Abstract not provided.

This paper presents continuum simulations of viscous polymer flow during nanoimprint lithography (NIL) for embossing tools having irregular spacings and sizes. Simulations varied non-uniform embossing tool geometry to distinguish geometric quantities governing cavity filling order, polymer peak deformation, and global mold filling times. A characteristic NIL velocity predicts cavity filling order. In general, small cavities fill more quickly than large cavities, while cavity spacing modulates polymer deformation mode. Individual cavity size, not total filling volume, dominates replication time, with large differences in individual cavity size resulting in non-uniform, squeeze flow filling. High density features can be modeled as a solid indenter in squeeze flow to accurately predict polymer flow and allow for optimization of wafer-scale replication. The present simulations make it possible to design imprint templates capable of distributing pressure evenly across the mold surface and facilitating symmetric polymer flow over large areas to prevent mold deformation and non-uniform residual layer thickness.

As part of an effort to reduce costs and improve quality control in encapsulation and potting processes the Technology Initiative Project ''Defect Free Manufacturing and Assembly'' has completed a computational modeling study of flows representative of those seen in these processes. Flow solutions are obtained using a coupled, finite-element-based, numerical method based on the GOMA/ARIA suite of Sandia flow solvers. The evolution of the free surface is solved with an advanced level set algorithm. This approach incorporates novel methods for representing surface tension and wetting forces that affect the evolution of the free surface. In addition, two commercially available codes, ProCAST and MOLDFLOW, are also used on geometries representing encapsulation processes at the Kansas City Plant. Visual observations of the flow in several geometries are recorded in the laboratory and compared to the models. Wetting properties for the materials in these experiments are measured using a unique flowthrough goniometer.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

This SAND report describes progress made during a Sandia National Laboratories sponsored graduate fellowship. The fellowship was funded through an LDRD proposal. The goal of this project is development and characterization of mixing strategies for polymeric microfluidic devices. The mixing strategies under investigation include electroosmotic flow focusing, hydrodynamic focusing, physical constrictions and porous polymer monoliths. For electroosmotic flow focusing, simulations were performed to determine the effect of electroosmotic flow in a microchannel with heterogeneous surface potential. The heterogeneous surface potential caused recirculations to form within the microchannel. These recirculations could then be used to restrict two mixing streams and reduce the characteristic diffusion length. Maximum mixing occurred when the ratio of the mixing region surface potential to the average channel surface potential was made large in magnitude and negative in sign, and when the ratio of the characteristic convection time to the characteristic diffusion time was minimized. Based on these results, experiments were performed to evaluate the manipulation of surface potential using living-radical photopolymerization. The material chosen to manipulate typically exhibits a negative surface potential. Using living-radical surface grafting, a positive surface potential was produced using 2-(Dimethylamino)ethyl methacrylate and a neutral surface was produced using a poly(ethylene glycol) surface graft. Simulations investigating hydrodynamic focusing were also performed. For this technique, mixing is enhanced by using a tertiary fluid stream to constrict the two mixing streams and reduce the characteristic diffusion length. Maximum mixing occurred when the ratio of the tertiary flow stream flow-rate to the mixing streams flow-rate was maximized. Also, like the electroosmotic focusing mixer, mixing was also maximized when the ratio of the characteristic convection time to the characteristic diffusion time was minimized. Physical constrictions were investigated through simulations. The results show that the maximum mixing occurs when the height of the mixing region is minimized. Finally, experiments were performed to determine the effectiveness of using porous polymer monoliths to enhance mixing. The porous polymer monoliths were constructed using a monomer/salt paste. Two salt crystal size ranges were used; 75 to 106 microns and 53 to 180 microns. Mixing in the porous polymer monoliths fabricated with the 75 to 106 micron salt crystal size range was six times higher than a channel without a monolith. Mixing in the monolith fabricated with the 53 to 180 micron salt crystal size range was nine times higher.

Abstract not provided.

Abstract not provided.

This article presents continuum simulations of viscous polymer flow during nanoimprint lithography (NIL) for embossing tools having irregular spacings and sizes. Simulations vary nonuniform embossing tool geometry to distinguish geometric quantities governing cavity filling order, polymer peak deformation, and global mold filling times. A characteristic NIL velocity predicts cavity filling order. In general, small cavities fill more quickly than large cavities, while cavity spacing modulates polymer deformation mode. Individual cavity size, not total filling volume, dominates replication time, with large differences in individual cavity size resulting in nonuniform, squeeze flow filling. High density features can be modeled as a solid indenter in squeeze flow to accurately predict polymer flow and allow for optimization of wafer-scale replication. The present simulations make it possible to design imprint templates capable of distributing pressure evenly across the mold surface and facilitating symmetric polymer flow over large areas to prevent mold deformation and nonuniform residual layer thickness.

This paper presents continuum simulations of polymer flow during nanoimprint lithography (NIL). The simulations capture the underlying physics of polymer flow from the nanometer to millimeter length scale and examine geometry and thermophysical process quantities affecting cavity filling. Variations in embossing tool geometry and polymer film thickness during viscous flow distinguish different flow driving mechanisms. Three parameters can predict polymer deformation mode: cavity width to polymer thickness ratio, polymer supply ratio and capillary number. The ratio of cavity width to initial polymer film thickness determines vertically or laterally dominant deformation. The ratio of indenter width to residual film thickness measures polymer supply beneath the indenter which determines Stokes or squeeze flow. The local geometry ratios can predict a fill time based on laminar flow between plates, Stokes flow, or squeeze flow. A characteristic NIL capillary number based on geometry-dependent fill time distinguishes between capillary- or viscous-driven flows. The three parameters predict filling modes observed in published studies of NIL deformation over nanometer to millimeter length scales. The work seeks to establish process design rules for NIL and to provide tools for the rational design of NIL master templates, resist polymers and process parameters.

The investigation of the liquefaction and flow behavior of a thermally decomposing removable epoxy foam (REF) was discussed. It was concluded that the behavior of REF, can vary greatly depending on both physical and thermal boundary conditions as well as on decomposition chemistry. It was shown that the foam regression away from a heated surface generally involves two moving boundaries, a fluid-solid interface and a fluid-vapor interface. During thermal decomposition, the physical and chemical behaviors of the foams were coupled and can significantly affect heat transfer rates to the encapsulated units.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.