Publications

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This study explores self-aligning patterns to achieve sub-micron alignment of die/wafers. We have patterned 2-d arrays of gold lines, whose width is half the periodicity, onto substrates. When commensurate patterns are brought into contact, the surface interactions between the Au lines enables high-resolution alignment, manually. Self-assembled monolayers of alkanethiols on the Au, further enhance the surface interactions, enabling alignment in less than half the time as for the uncoated die. A computation of the alignment force and torque between two featured surfaces illustrates how best to partern surfaces to maximize the tendency to align. An array of lines with a sinusoidal modulation in their spacing is more tolerant of initial misalignment, yet retains the high registration force of periodic line arrays. The optimal registration pattern might be a single spiral, as it generates both a radial force and a torque. Such patterns on die/wafers would enable precision device integration. ©The Electrochemical Society.

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When estimating parameters for a material model from experimental data collected during a separate effects physics experiment, the quality of fit is only a part of the required data. Also necessary is the uncertainty in the estimated parameters so that uncertainty quantification and model validation can be performed at the full system level. The uncertainty and quality of fit of the data are many times not available and should be considered when fitting the data to a specified model. There are many techniques available to fit data to a material model and a few of them are presented in this work using a simple acoustical emission dataset. The estimated parameters and the affiliated uncertainty will be estimated using a variety of techniques and compared.

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Infrastructure resilience is a priority for homeland security in many nations around the globe. This paper describes a new approach forquantitatively assessing the resilience of critical infrastructure systems. The mathematics of optimal control design provides the theoretical foundation for this methodology. This foundation enables the inclusion of recovery costs within the resilience assessment approach, a unique capability for quantitative esilience assessment techniques. This paper describes the formulation of the optimal control problem for a set of representative infrastructure models. Thisexample demonstrates the importance of recovery costs in quantitative resilience analysis, and the increased capability provided by this approach's ability to discern between varying levels of resilience. © 2011 Inderscience Enterprises Ltd.

This paper1 explores some of the important considerations in devising a practical and consistent framework and methodology for working with experiments and experimental data in connection with modeling and prediction. The paper outlines a pragmatic and versatile "real-space" approach within which experimental and modeling uncertainties (correlated and uncorrelated, systematic and random, aleatory and epistemic) are treated to mitigate risk in modeling and prediction. The elements of data conditioning, model conditioning, model validation, hierarchical modeling, and extrapolative prediction under uncertainty are examined. An appreciation can be gained for the constraints and difficulties at play in devising a viable end-to-end methodology. The considerations and options are many, and a large variety of viewpoints and precedents exist in the literature, as surveyed here. Rationale is given for the various choices taken in assembling the novel real-space end-to-end framework. The framework adopts some elements and constructs from the literature (sometimes adding needed refinement), rejects others (even some currently popular ones), and adds pivotal new elements and constructs. Crucially, the approach reflects a pragmatism and versatility derived from working many industrial-scale problems involving complex physics and constitutive models, steady-state and time-varying nonlinear behavior and boundary conditions, and various categories of uncertainty in experiments and models. The framework benefits from a broad exposure to integrated experimental and modeling activities in the areas of heat transfer, structural mechanics, irradiated electronics, and combustion in fluids and solids.2. © 2011 SAE International.

Power and signal cable harnesses on spacecraft are often at 10% of the total mass and can be as much as 30%. These cable harnesses can impact the structural dynamics of spacecraft significantly, specifically by damping the response. Past efforts have looked at how to calculate cable properties and the validation of these cable models on one-dimensional beam structures with uniform cable lengths. This paper looks at how to extend that process to two-dimensional spacecraftlike panels with nonuniform cable lengths. A shear beam model is used for cable properties. Two methods of calculating the tiedown stiffness are compared. Of particular interestis whetherornot handbooks of cable properties canbe created ahead of time and applied with confidence. There are three frequency bands inwhich cable effects canbe described. Before any cables become resonant, the cable effects are dominated by mass and static stiffness. After all the cables become resonant, the effect is dominated by increased damping in the structure. In between these two frequency cutoff points, there is a transition zone. The dynamic cable modeling methodis validated as a distinct improvement over the lumped-mass characterization of cables commonly used today. Copyright © 2011 by the American Institute of Aeronautics and Astronautics,.

Negative bias temperature instability (NBTI) is an issue of critical importance as tile space electronics industry evolves because it may dominate tile reliability lifetime of space based assets. Understanding its physical origin is therefore essential in determining how best to search for methods of mitigation. It has been suggested that the magnitude of the effect is strongly dependent on circuit operation conditions (static or dynamic modes). In the present work, we examine the time constants related to the charging and recovery of trapped charged induced by NBTI in HfSiON and SiO2 gate dielectric devices at room temperature. ©The Electrochemical Society.

Although interdisciplinary research attracts more and more interest and effort, the benefits of this type of research are not always realized. To understand when expertise diversity will have positive or negative effects on research efforts, we examine how expertise diversity and diversity salience affect task conflict and idea sharing in interdisciplinary research groups. Using data from 148 researchers in 29 academic research labs, we provide evidence on the importance of social categorization states (i.e., expertise diversity salience) in understanding both the information processes (i.e., task conflict) and the creativity processes (i.e., idea sharing) in groups with expertise diversity. We show that expertise diversity can either increase or decrease task conflict depending on the salience of group members' expertise in a curvilinear way: at a medium level of expertise diversity the moderating effect of diversity salience is strongest. Furthermore, enriched group work design can strengthen the benefits of task conflict for creative idea sharing only when expertise diversity salience is low. Finally, we show that idea sharing predicts group performance in interdisciplinary academic research labs over and above task conflict.

The process of rank aggregation is intimately intertwined with the structure of skew-symmetric matrices. We apply recent advances in the theory and algorithms of matrix completion to skew-symmetric matrices. This combination of ideas produces a new method for ranking a set of items. The essence of our idea is that a rank aggregation describes a partially filled skew-symmetric matrix. We extend an algorithm for matrix completion to handle skew-symmetric data and use that to extract ranks for each item. Our algorithm applies to both pairwise comparison and rating data. Because it is based on matrix completion, it is robust to both noise and incomplete data. We show a formal recovery result for the noiseless case and present a detailed study of the algorithm on synthetic data and Netix ratings. Copyright 2011 ACM.

We present a filter consisting of cascaded ring resonators with integrated SOAs. The filter demonstrates an extinction ratio ≥30 dB, a free spectral range of 56 GHz and a FWHM bandwidth of 3 GHz. © 2011 Optical Society of America.

This work presents a methodology based on the concept of error in constitutive equations for the inverse reconstruction of viscoelastic properties using steady-state dynamics. The ECE algorithm presented herein consists of two main steps. In the first step, kinematically admissible strains and dynamically admissible stresses are generated through two auxiliary forward problems. In the second step, a new update of the complex shear and bulk moduli as functions of frequency are obtained by minimizing an ECE functional that measures the discrepancy between the kinematically admissible strains and the dynamically admissible stresses. The feasibility of the methodology is demonstrated through two numerical experiments. It was found that the magnitude and phase of the complex shear modulus can be accurately reconstructed in the presence of noise, while the magnitude of the bulk modulus is more sensitive to noise and can be reconstructed with less accuracy, in general, than the shear modulus. Furthermore, the phase of the bulk modulus, which is related to energy dissipation, can be accurately reconstructed.

We present the first complete simulation of the dynamic range and noise of InGaAsP multi-ring channel-drop filters with internal SOAs. The results show gain saturation, and spontaneous emission noise limit the dynamic range. © 2011 Optical Society of America.

Transportation accidents frequently involve liquids dispersing in the atmosphere. An example is that of aircraft impacts, which often result in spreading fuel and a subsequent fire. Predicting the resulting environment is of interest for design, safety, and forensic applications. This environment is challenging for many reasons, one among them being the disparate time and length scales that must be resolved for an accurate physical representation of the problem. A recent computational method appropriate for this class of problems has been developed for modeling the impact and subsequent liquid spread. This involves coupling a structural dynamics code to a turbulent computational fluid mechanics reacting flow code. Because the environment intended to be simulated with this capability is difficult to instrument and costly to test, the existing validation data are of limited scope, relevance, and quality. A rocket sled test is being performed where a scoop moving through a water channel is being used to brake a pusher sled. We plan to instrument this test to provide appropriate scale data for validating the new modeling capability. The intent is to get high fidelity data on the break-up and evaporation of the water that is ejected from the channel as the sled is braking. These two elements are critical to fireball formation for this type of event involving fuel in the place of water. We demonstrate our capability in this paper by describing the pre-test predictions which are used to locate instrumentation for the actual test. We also present a sensitivity analysis to understand the implications of length scale assumptions on the prediction results. Copyright © 2011 by ASME.

There occasionally occur situations in field measurements where direct optical access to the area of interest is not possible. In these cases the borescope is the standard method of imaging. Furthermore, if shape, displacement, or strain are desired in these hidden locations, it would be advantageous to be able to do digital image correlation (DIC) through the borescope. This paper will present the added complexities and errors associated with imaging through a borescope for DIC. Discussion of non-radial distortions and their effects on the measurements, along with a possible correction scheme will be discussed.

Traditional grid models for large-scale simulations assume linear and quasi-static behavior allowing very simple models of the systems. In this paper, a scalable electric circuit simulation capability is presented that can capture a significantly higher degree of fidelity including transient dynamic behavior of the grid as well as allowing scaling to a regional and national level grid. A test case presented uses simple models, e.g. generators, transformers, transmission lines, and loads, but with the scalability feature it can be extended to include more advanced non-linear detailed models. The use of this scalable electric circuit simulator will provide the ability to conduct large-scale transient stability analysis as well as grid level planning as the grid evolves with greater degrees of penetration of renewables, power electronics, storage, distributed generation, and micro-grids. © 2011 AACC American Automatic Control Council.

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ODTLES is a novel multi-scale model for 3D turbulent flow based on the one-dimensional-turbulence model of Kerstein ["One-dimensional turbulence: Model formulation and application to homogeneous turbulence, shear flows, and buoyant stratified flows," J. Fluid Mech. 392, 277 (1999)]. Its key distinction is that it is formulated to resolve small-scale phenomena and capture some 3D large-scale features of the flow with affordable simulations. The present work demonstrates this capability by considering four types of wall-bounded turbulent flows. This work shows that spatial profiles of various flow quantities predicted with ODTLES agree fairly well with those from direct numerical simulations. It also shows that ODTLES resolves the near-wall region, while capturing the following 3D flow features: the mechanism increasing tangential velocity fluctuations near a free-slip wall, the large-scale recirculation region in lid-driven cavity flow, and the secondary flow in square duct flow. © 2011 American Institute of Physics.

This study explores self-aligning patterns to achieve sub-micron alignment of die/wafers. We have patterned 2-d arrays of gold lines, whose width is half the periodicity, onto substrates. When commensurate patterns are brought into contact, the surface interactions between the Au lines enables high-resolution alignment, manually. Self-assembled monolayers of alkanethiols on the Au, further enhance the surface interactions, enabling alignment in less than half the time as for the uncoated die. A computation of the alignment force and torque between two featured surfaces illustrates how best to partern surfaces to maximize the tendency to align. An array of lines with a sinusoidal modulation in their spacing is more tolerant of initial misalignment, yet retains the high registration force of periodic line arrays. The optimal registration pattern might be a single spiral, as it generates both a radial force and a torque. Such patterns on die/wafers would enable precision device integration. ©The Electrochemical Society.

We demonstrate a pump-probe approach for the detection of organophosphonate compounds on substrates, in which the pump pulse fragments the parent molecule and the released phosphorous monoxide (PO) fragment is probed using laser-induced fluorescence. © 2011 OSA.

A cantilever beam is released from an initial condition. The velocity at the tip is recorded using a laser Doppler vibrometer. The ring-down time history is analyzed using Hilbert transform, which gives the natural frequency and damping. An important issue with the Hilbert transform is vulnerability to noise. The proposed method uses curve fitting to replace some time-differentiation and suppress noise. Linear curve fitting gives very good results for linear beams with low damping. For nonlinear beams with higher damping, polynomial curve fitting captures the time variations. The method was used for estimating quality factors of a few shim metals and PZT bimorphs.

Automatic feature creation is a powerful tool for identifying and reaching goals in the natural world. This paper describes in detail a biologically-inspired method of feature creation that can be applied to sensory information of any modality. The algorithm is incremental and on-line; it enforces sparseness in the features it creates; and it can form features from other features, making a hierarchical feature set. Here it demonstrates the creation of both visual and auditory features. © 2011 The authors and IOS Press. All rights reserved.

Several commercial computational fluid dynamics (CFD) codes now have the capability to analyze Eulerian two-phase flow using the Rohsenow nucleate boiling model. Analysis of boiling due to one-sided heating in plasma facing components (pfcs) is now receiving attention during the design of water-cooled first wall panels for ITER that may encounter heat fluxes as high as 5 MW/m2. Empirical thermalhydraulic design correlations developed for long fission reactor channels are not reliable when applied to pfcs because fully developed flow conditions seldom exist. Star-CCM+ is one of the commercial CFD codes that can model two-phase flows. Like others, it implements the RPI model for nucleate boiling, but it also seamlessly transitions to a volume-of-fluid model for film boiling. By benchmarking the results of our 3d models against recent experiments on critical heat flux for both smooth rectangular channels and hypervapotrons, we determined the six unique input parameters that accurately characterize the boiling physics for ITER flow conditions under a wide range of absorbed heat flux. We can now exploit this capability to predict the onset of critical heat flux in these components. In addition, the results clearly illustrate the production and transport of vapor and its effect on heat transfer in pfcs from nucleate boiling through transition to film boiling. This article describes the boiling physics implemented in CCM+ and compares the computational results to the benchmark experiments carried out independently in the United States and Russia. Temperature distributions agreed to within 10 °C for a wide range of heat fluxes from 3 MW/m² to 10 MW/m² and flow velocities from 1 m/s to 10 m/s in these devices. Although the analysis is incapable of capturing the stochastic nature of critical heat flux (i.e., time and location may depend on a local materials defect or turbulence phenomenon), it is highly reliable in determining the heat flux where boiling instabilities begin to dominate. Beyond this threshold, higher heat fluxes lead to the boiling crisis and eventual burnout. This predictive capability is essential in determining the critical heat flux margin for the design of complex 3d components.

Let C be a depth-3 circuit with n variables, degree d and top fanin k (called ΣΠΣ(k,d,n) circuits) over base field FF. It is a major open problem to design a deterministic polynomial time blackbox algorithm that tests if C is identically zero. Klivans & Spielman (STOC 2001) observed that the problem is open even when k is a constant. This case has been subjected to a serious study over the past few years, starting from the work of Dvir & Shpilka (STOC 2005). We give the first polynomial time blackbox algorithm for this problem. Our algorithm runs in time poly(n)dk, regardless of the base field. The only field for which polynomial time algorithms were previously known is FF = QQ (Kayal & Saraf, FOCS 2009, and Saxena & Seshadhri, FOCS 2010). This is the first blackbox algorithm for depth-$3$ circuits that does not use the rank based approaches of Karnin & Shpilka (CCC 2008). We prove an important tool for the study of depth-3 identities. We design a blackbox polynomial time transformation that reduces the number of variables in a ΣΠΣ(k,d,n) circuit to k variables, but preserves the identity structure. © 2011 ACM.

Traditional parallel programming techniques will suffer rapid deterioration of performance scaling with growing platform size, as the work of coping with increasingly frequent failures dominates over useful computation. To address this challenge, we introduce and simulate a novel software architecture that combines a task dependency graph with a substitution graph. The role of the dependency graph is to limit communication and checkpointing and enhance fault tolerance by allowing graph neighbors to exchange data, while the substitution graph promotes fault oblivious computing by allowing a failed task to be substituted onthe- fly by another task, incurring a quantifiable error. We present optimization formulations for trading off substitution errors and other factors such as available system capacity and low-overlap task partitioning among processors, and demonstrate that these can be approximately solved in real time after some simplifications. Simulation studies of our proposed approach indicate that a substitution network adds considerable resilience and simple enhancements can limit the aggregate substitution errors. © Springer-Verlag 2011.

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We develop computable a posteriori error estimates for linear functionals of a solution to a general nonlinear stochastic differential equation with random model/source parameters. These error estimates are based on a variational analysis applied to stochastic Galerkin methods for forward and adjoint problems. The result is a representation for the error estimate as a polynomial in the random model/source parameter. The advantage of this method is that we use polynomial chaos representations for the forward and adjoint systems to cheaply produce error estimates by simple evaluation of a polynomial. By comparison, the typical method of producing such estimates requires repeated forward/adjoint solves for each new choice of random parameter. We present numerical examples showing that there is excellent agreement between these methods. © 2011 Society for Industrial and Applied Mathematics.

Data have been acquired from a spanwise array of fluctuating wall pressure sensors beneath a wind tunnel wall boundary layer at Mach 2, then invoking Taylor's Hypothesis allows the temporal signals to be converted into a spatial map of the wall pressure field. Improvements to the measurement technique were developed to establish the veracity of earlier tentative conclusions. An adaptive filtering scheme using a reference sensor was implemented to cancel effects of wind tunnel acoustic noise and vibration. Coherent structures in the pressure fields were identified using an improved thresholding algorithm that reduced the occurrence of broken contours and spurious signals. Analog filters with sharper frequency cutoffs than digital filters produced signals of greater spectral purity. Coherent structures were confirmed in the fluctuating wall pressure field that resemble similar structures known to exist in the velocity field, in particular by exhibiting a spanwise meander and merging of events. However, the pressure data lacked the common spanwise alternation of positive and negative events found in velocity data, and conversely demonstrated a weak positive correlation in the spanwise direction.

A unified creep plasticity damage (UCPD) model for Sn-Pb and Pb-free solders was developed and implemented into finite element analysis codes. The new model will be described along with the relationship between the model's damage evolution equation and an empirical Coffin-Manson relationship for solder fatigue. Next, two significant developments were needed to model crack initiation and growth in solder joints. First, an ability to accelerate the simulations such that the effects of hundreds or thousands of thermal cycles could be modeled in a reasonable amount of time was needed. This was accomplished by applying a user prescribed acceleration factor to the damage evolution; then, damage generated by an acceleration factor of cycles could be captured by the numerical simulation of a single thermal cycle. Second, an ability to capture the geometric effects of crack initiation and growth was needed. This was accomplished by replacing material in finite elements that had met the cracking failure criterion with very flexible elastic material. This diffuse crack modeling approach with local finite elements is known to generate mesh dependent solutions. However, introduction of an element size dependent term into the damage evolution equation was found to be effective in controlling mesh dependency. Finally, experimentally observed cracks in a typical solder joint subjected to thermal mechanical fatigue are compared with model predictions. Copyright © 2011 by ASME.

Flexible AC Transmission Systems (FACTS) use advanced power electronics to minimize reactive power loss on the grid. Power devices used in FACTS systems must be capable of switching several thousand amps at voltages of 1-10 kV. Traditionally, these systems have relied on silicon thyristors, but recently have also began to incorporate insulated gate bipolar transistors. FACTS systems present an opportunity for emerging SiC and GaN power transistors, which offer major efficiency gains. However, for these advanced materials to be considered for use in high consequence grid level systems like FACTS controllers, excellent reliability must be demonstrated. ©The Electrochemical Society.

Material control and accountability (MC&A) operations that track and account for critical assets at nuclear facilities provide a key protection approach for defeating insider adversaries. MC&A activities, from monitoring to inventory measurements, provide critical information about target materials and define security elements that are useful against insider threats. However, these activities have been difficult to characterize in ways that are compatible with the path analysis methods that are used to systematically evaluate the effectiveness of a site's protection system. The path analysis methodology focuses on a systematic, quantitative evaluation of the physical protection component of the system for potential external threats, and often calculates the probability that the physical protection system (PPS) is effective (PE) in defeating an adversary who uses that attack pathway. In previous work, Dawson and Hester observed that many MC&A activities can be considered a type of sensor system with alarm and assessment capabilities that provide reccurring opportunities for "detecting" the status of critical items. This work has extended that characterization of MC&A activities as probabilistic sensors that are interwoven within each protection layer of the PPS. In addition, MC&A activities have similar characteristics to operator tasks performed in a nuclear power plant (NPP) in that the reliability of these activities depends significantly on human performance. Many of the procedures involve human performance in checking for anomalous conditions. Further characterization of MC&A activities as operational procedures that check the status of critical assets provides a basis for applying human reliability analysis (HRA) models and methods to determine probabilities of detection for MC&A protection elements. This paper will discuss the application of HRA methods used in nuclear power plant probabilistic risk assessments to define detection probabilities and to formulate "timely detection" for MC&A operations. This work has enabled the development of an integrated path analysis methodology in which MC&A operations can be combined with traditional sensor data in the calculation of PPS effectiveness. Explicitly incorporating MC&A operations into the existing evaluation methodology provides the basis for an effectiveness measure for insider threats, and the resulting PE calculations will provide an integrated effectiveness measure that addresses both external and insider threats. The extended path analysis methodology is being further investigated as the basis for including the PPS and MC&A activities in an integrated safeguards and security system for advanced fuel cycle facilities. Copyright © 2011 by ASME.

In the present paper the act of learner reflection during training with an adaptive or predictive computer-based tutor is considered a learner-system interaction. Incorporating reflection and real-time evaluation of peer performance into adaptive and predictive computerbased tutoring can support the development of automated adaptation. Allowing learners to refine and inform student models from reflective practice with independent open learner models may improve overall accuracy and relevancy. Given the emphasis on selfdirected peer learning with adaptive technology, learner and instructor modeling research continue to be critical research areas for education and training technology.

The chemical industry is one of the largest industries in the United States and a vital contributor to global chemical supply chains. The U.S. Department of Homeland Security (DHS) Science and Technology Directorate has tasked Sandia National Laboratories (Sandia) with developing an analytical capability to assess interdependencies and complexities of the nation's critical infrastructures on and with the chemical sector. This work is being performed to expand the infrastructure analytical capabilities of the National Infrastructure Simulation and Analysis Center (NISAC). To address this need, Sandia has focused on development of an agent-based methodology towards simulating the domestic chemical supply chain and determining economic impacts resulting from large-scale disruptions to the chemical sector. Modeling the chemical supply chain is unique because the flow of goods and services are guided by process thermodynamics and reaction kinetics. Sandia has integrated an agent-based microeconomic simulation tool N-ABLETM with various chemical industry datasets to abstract the chemical supply chain behavior. An enterprise design within N-ABLETM consists of a collection of firms within a supply chain network; each firm interacts with others through chemical reactions, markets, and physical infrastructure. The supply and demand within each simulated network must be consistent with respect to mass balances of every chemical within the network. Production decisions at every time step are a set of constrained linear program (LP) solutions that minimize the difference between desired and actual outputs. We illustrate the methodology with examples of modeled petrochemical supply chains under an earthquake event. The supply chain impacts of upstream and downstream chemicals associated with organic intermediates after a short-term shutdown in the affected area are discussed.

Projection of molten salt performance in thermal storage systems, whether based on sensible heat or latent heat, is highly dependent on the predictions of thermophysical properties. In the absence of experimental data, heat transfer properties rely on theoretical estimations. This work focuses on thermodynamic predictions of mixture properties for molten salts supportive of ongoing advanced heat transfer fluid research at the Sandia National Laboratories. Thus far, the candidate mixtures studied experimentally and theoretically at Sandia are made up of either ternary or quaternary nitrate and mixed nitrate/nitrite salts of various compositions. Experimentally, mixture properties such as melting points and heat of fusion are obtained by thermal gravimetric analysis (TGA) and differential scanning calorimetry (DSC). Classical thermodynamics are applied to resolve phase transitions of molten salt mixtures as well as mixture properties. The Wilson equation, developed originally for organic mixtures, is used to study phase boundaries of molten salts in this work. Molecular thermodynamics (MD), where atomistic simulation forms the basis for constructing the equation of state, are conducted where our fundamental understanding and experimental knowledge are lacking.

An analytical expression for the pressure wavefield radiated from an explosion seismic source with an amplitude distribution in the form of a 3D Gaussian function is developed. This expression provides a useful reference solution for validating various numerical seismic wave propagation algorithms. © 2011 Society of Exploration Geophysicists.

Deep reactive ion etching (DRIE) of silicon enables high aspect ratio, deep silicon features that can be incorporated into the fabrication of microelectromechanical systems (MEMS) sensors and actuators. The DRIE process creates silicon structures and consists of three steps: conformal polymer deposition, ion sputtering, and chemical etching. The sequential three step process results in sidewalls with roughness that varies with processing conditions. This paper reports the sidewall roughness for DRIE etched MEMS as a function of trench width from 5 μm to 500 μm for a 125 μm thick device layer corresponding to aspect ratios from 25 to 0.25. Using a scanning electron microscope (SEM), the surfaces were imaged detecting an upper region exhibiting a scalloping morphology and a rougher lower region exhibiting a curtaining morphology. The height of rougher curtaining region increases linearly with aspect ratio when the etch cleared the entire device layer. The surface roughness for two trench widths: 15 μm and 100 μm were further characterized using an atomic force microscope (AFM), and RMS roughness values are reported as a function of height along the surface. The sidewall roughness varies with height and depends on the trench width. Copyright © 2011 by ASME.

For oxy-fuel combustion with substantial flue gas recirculation, as is commonly employed, pulverized coal combustion occurs in the presence of elevated CO2 levels. Our previous investigations of pulverized coal char combustion in such atmospheres have suggested, through computational modeling of the experimental results, that CO2 gasification rates are sufficiently high under oxy-fuel combustion conditions to significantly influence the char combustion process. Experimental measurements of such rates under the relevant conditions (1 atm, T > 1700 K) are lacking. To address this, we have measured both the char particle temperature statistics and the char mass loss when a high volatile bituminous coal char and a subbituminous coal char are introduced into a high-temperature optical flow reactor with nearly 100% CO2. The experimental measurements show a temperature decrease from the gasifying particles (consistent with the strong endothermicity of the char gasification reaction) and show increasing mass loss with increasing residence time and temperature, as expected.

Vertically aligned InGaN/GaN nanorod light emitting diode (LED) arrays were created from planar LED structures using a new top-down fabrication technique consisting of a plasma etch followed by an anisotropic wet etch. The wet etch results in straight, smooth, well-faceted nanorods with controllable diameters and removes the plasma etch damage. 94% of the nanorod LEDs are dislocation-free and a reduced quantum confined Stark effect is observed due to reduced piezoelectric fields. Despite these advantages, the IQE of the nanorod LEDs measured by photoluminescence is comparable to the planar LED, perhaps due to inefficient thermal transport and enhanced nonradiative surface recombination.

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A key challenge in developing complete human equivalence is how to ground a synoptic theory of cognition in neural reality. Both cognitive architectures and neural models provide insight into how biological brains work, but from opposite directions. Here the authors report on initial work aimed at interpreting connectomic data in terms of algorithms. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. © 2011 The authors and IOS Press. All rights reserved.

Past work has demonstrated the feasibility of pyrolyzing biomass and condensing the resulting vapor to form a low quality combustible liquid. The product, often termed pyrolysis oil, bio-oil, or bio-crude, can be refined to a transportation grade fuel. Because the pyrolysis process is comparatively simple, we speculate that a mobile pyrolysis system might be able to process the biomass at the site of harvest, generating a dense liquid for transportation. This would be expected to result in improved transportation economics compared to transporting the raw biomass fuel. This technology is being considered for northern New Mexico forests that are presently managed by periodic thinning efforts with little utilization of the products. We have designed a bench-scale system and pyrolyzed biomass pellets, which function in these tests as surrogate material for the forest trimmings. The system features controllable furnace temperatures, augur feed, gas recirculation, and multi-stage condensation. We have analyzed gases, chars, and liquids resulting from various operating conditions and report product quantities and qualities through various standard chemical methods. Good liquid mass yields of over 50% of the original material are typically found, with varying product quality and quantity depending on the operating temperature. Our results suggest the current configuration gives better yields and functions more optimally at pyrolysis temperatures around 525°C. For a practical system, combustion of the non-condensable fuel gases may be able to replace the electrically heated furnace used in these tests. Copyright © 2011 by ASME.

Fast neutron based inspection systems are of interest in many Homeland Security applications because they offer the potential for elemental identification particularly for low Z elements which are the prime constituents of explosives. We are investigating a resonance tomography technique which may address some of the current problems found in fast neutron based inspection systems. A commercial off-the-shelf DT generator is used with an array of detectors to probe materials simultaneously over a large energy range and multiple viewing angles allowing for simultaneous 3-D imaging and materials identification. A prototype system has been constructed and we present here recent results for the identification of materials with differing H, C, N, O compositions. © 2011 IEEE.

A unified creep plasticity damage (UCPD) model for Sn-Pb and Pb-free solders was developed and implemented into finite element analysis codes. The new model will be described along with the relationship between the model's damage evolution equation and an empirical Coffin-Manson relationship for solder fatigue. Next, two significant developments were needed to model crack initiation and growth in solder joints. First, an ability to accelerate the simulations such that the effects of hundreds or thousands of thermal cycles could be modeled in a reasonable amount of time was needed. This was accomplished by applying a user prescribed acceleration factor to the damage evolution; then, damage generated by an acceleration factor of cycles could be captured by the numerical simulation of a single thermal cycle. Second, an ability to capture the geometric effects of crack initiation and growth was needed. This was accomplished by replacing material in finite elements that had met the cracking failure criterion with very flexible elastic material. This diffuse crack modeling approach with local finite elements is known to generate mesh dependent solutions. However, introduction of an element size dependent term into the damage evolution equation was found to be effective in controlling mesh dependency. Finally, experimentally observed cracks in a typical solder joint subjected to thermal mechanical fatigue are compared with model predictions. Copyright © 2011 by ASME.

Passive detection of special nuclear material (SNM) at long range or under heavy shielding can only be directly achieved by observing the penetrating neutral particles that it emits: gamma rays and neutrons in the MeV energy range. The ultimate SNM standoff detector system would have sensitivity to both gamma and neutron radiation, a large area and high efficiency to capture as many signal particles as possible, and good discrimination against background particles via directional and energy information. We are exploring the use of time-modulated collimators that may lead to practical gamma-neutron imaging detector systems that are highly efficient with the potential to exhibit simultaneously high angular and energy resolution. We will present results from a large standoff SNM detection demonstration using a prototype high sensitivity time encoded modulation imager. © 2011 IEEE.

A critical stage in microstructurally small fatigue crack growth in AA 7075-T651 is the nucleation of cracks originating in constituent particles into the matrix material. Previous work has focused on a geometric approach to modeling microstruc-turally small fatigue crack growth in which damage metrics derived from an elastic-viscoplastic constitutive model are used to predict the nucleation event [1, 2]. While a geometric approach based on classical finite elements was successful in explicitly modeling the polycrystalline grain structure, singularities at the crack tip necessitated the use of a nonlocal sampling approach to remove mesh size dependence. This study is an initial investigation of the peridynamic formulation of continuum mechanics as an alternative approach to modeling microstructurally small fatigue crack growth. Peridy-namics, a nonlocal extension of continuum mechanics, is based on an integral formulation that remains valid in the presence of material discontinuities. To capture accurately the material response at the grain scale, a crystal elastic-viscoplastic constitutive model is adapted for use in non-ordinary state-based peri-dynamics through the use of a regularized deformation gradient. The peridynamic approach is demonstrated on a baseline model consisting of a hard elastic inclusion in a single crystal. Coupling the elastic-viscoplastic material model with peridynamics successfully facilitates the modeling of plastic deformation and damage accumulation in the vicinity of the particle inclusion. Lattice orientation is shown to have a strong influence on material response. Copyright © 2011 by ASME.

An ideal 3He detector replacement for the nearto medium-term future will use materials that are easy to produce and well understood, while maintaining thermal neutron detection efficiency and gamma rejection close to the 3He standard. Toward this end, we are investigating the use of standard alkali halide scintillators interfaced with 6Li and read out with photomultiplier tubes (PMTs). Thermal neutrons are captured on 6Li with high efficiency, emitting high-energy α and triton (3H) reaction products. These particles deposit energy in the scintillator, providing a thermal neutron signal; discrimination against gamma interactions is possible via pulse shape discrimination (PSD), since heavy particles produce faster pulses in inorganic scintillating crystals. We constructed and tested two classes of detectors based on this concept. In one case 6Li is used as a dopant in polycrystalline NaI; in the other case a thin Li foil is used as a conversion layer. We present results from these investigations, including measurements of the neutron efficiency and gamma rejection for the two detector types. © 2011 IEEE.

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Low temperature transport properties of high mobility two-dimensional electron systems placed in a weak perpendicular magnetic field can be modified dramatically by microwave or dc electric fields. This paper surveys recent experimental developments which include zero-differential resistance states, Hall field-induced resistance oscillations in tilted magnetic fields, nonlinear response of the Shubnikov-de Haas Oscillations, and a novel microwave photoconductivity peak near the second harmonic of the cyclotron resonance.

The Image Composition Engine for Tiles (IceT) is a high-performance sort-last parallel rendering library. In addition to providing accelerated rendering for a standard display, IceT provides the unique ability to generate images for tiled displays. The overall resolution of the display may be several times larger than any viewport that may be rendered by a single machine. This document is an overview of the user interface to IceT.

Key components of the nuclear fuel cycle are short-term storage and long-term disposal of nuclear waste. The latter encompasses the immobilization of used nuclear fuel (UNF) and radioactive waste streams generated by various phases of the nuclear fuel cycle, and the safe and permanent disposition of these waste forms in geological repository environments. The engineered barrier system (EBS) plays a very important role in the long-term isolation of nuclear waste in geological repository environments. EBS concepts and their interactions with the natural barrier are inherently important to the long-term performance assessment of the safety case where nuclear waste disposition needs to be evaluated for time periods of up to one million years. Making the safety case needed in the decision-making process for the recommendation and the eventual embracement of a disposal system concept requires a multi-faceted integration of knowledge and evidence-gathering to demonstrate the required confidence level in a deep geological disposal site and to evaluate long-term repository performance. The focus of this report is the following: (1) Evaluation of EBS in long-term disposal systems in deep geologic environments with emphasis on the multi-barrier concept; (2) Evaluation of key parameters in the characterization of EBS performance; (3) Identification of key knowledge gaps and uncertainties; and (4) Evaluation of tools and modeling approaches for EBS processes and performance. The above topics will be evaluated through the analysis of the following: (1) Overview of EBS concepts for various NW disposal systems; (2) Natural and man-made analogs, room chemistry, hydrochemistry of deep subsurface environments, and EBS material stability in near-field environments; (3) Reactive Transport and Coupled Thermal-Hydrological-Mechanical-Chemical (THMC) processes in EBS; and (4) Thermal analysis toolkit, metallic barrier degradation mode survey, and development of a Disposal Systems Evaluation Framework (DSEF). This report will focus on the multi-barrier concept of EBS and variants of this type which in essence is the most adopted concept by various repository programs. Empasis is given mainly to the evaluation of EBS materials and processes through the analysis of published studies in the scientific literature of past and existing repository research programs. Tool evaluations are also emphasized, particularly on THCM processes and chemical equilibria. Although being an increasingly important aspect of NW disposition, short-term or interim storage of NW will be briefly discussed but not to the extent of the EBS issues relevant to disposal systems in deep geologic environments. Interim storage will be discussed in the report Evaluation of Storage Concepts FY10 Final Report (Weiner et al. 2010).

Nanomaterials and nanotechnology methods have been an integral part of international research over the past decade. Because many traditional water treatment technologies (e.g. membrane filtration, biofouling, scale inhibition, etc.) depend on nanoscale processes, it is reasonable to expect one outcome of nanotechnology research to be better, nano-engineered water treatment approaches. The most immediate, and possibly greatest, impact of nanotechnology on desalination methods will likely be the development of membranes engineered at the near-molecular level. Aquaporin proteins that channel water across cell membranes with very low energy inputs point to the potential for dramatically improved performance. Aquaporin-laced polymer membranes and aquaporin-mimicking carbon nanotubes and metal oxide membranes developed in the lab support this. A critical limitation to widespread use of nanoengineered desalination membranes will be their scalability to industrial fabrication processes. Subsequent, long-term improvements in nanoengineered membranes may result in self-healing membranes that ideally are (1) more resistant to biofouling, (2) have biocidal properties, and/or (3) selectively target trace contaminants.

Operators interested in improving reliability should begin with a focus on the performance of the wind plant as a whole. To then understand the factors which drive individual turbine performance, which together comprise the plant performance, it is necessary to track a number of key indicators. Analysis of these key indicators can reveal the type, frequency, and cause of failures and will also identify their contributions to overall plant performance. The ideal approach to using data to drive good decisions includes first determining which critical decisions can be based on data. When those required decisions are understood, then the analysis required to inform those decisions can be identified, and finally the data to be collected in support of those analyses can be determined. Once equipped with high-quality data and analysis capabilities, the key steps to data-based decision making for reliability improvements are to isolate possible improvements, select the improvements with largest return on investment (ROI), implement the selected improvements, and finally to track their impact.

This Sandia supported research project evaluated the potential improvement that 'condensing' supercritical carbon dioxide (S-CO{sub 2}) power cycles can have on the efficiency of Light Water Reactors (LWR). The analytical portion of research project identified that a S-CO{sub 2} 'condensing' re-compression power cycle with multiple stages of reheat can increase LWR power conversion efficiency from 33-34% to 37-39%. The experimental portion of the project used Sandia's S-CO{sub 2} research loop to show that the as designed radial compressor could 'pump' liquid CO{sub 2} and that the gas-cooler's could 'condense' CO{sub 2} even though both of these S-CO{sub 2} components were designed to operate on vapor phase S-CO{sub 2} near the critical point. There is potentially very high value to this research as it opens the possibility of increasing LWR power cycle efficiency, above the 33-34% range, while lowering the capital cost of the power plant because of the small size of the S-CO{sub 2} power system. In addition it provides a way to incrementally build advanced LWRs that are optimally designed to couple to S-CO{sub 2} power conversion systems to increase the power cycle efficiency to near 40%.

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Truncated Gaussian fields provide a flexible model for defining binary media with dispersed (as opposed to layered) inclusions. General properties of excursion sets on these truncated fields are coupled with a distance-based upscaling algorithm and approximations of point process theory to develop an estimation approach for effective conductivity in two-dimensions. Estimation of effective conductivity is derived directly from knowledge of the kernel size used to create the multiGaussian field, defined as the full-width at half maximum (FWHM), the truncation threshold and conductance values of the two modes. Therefore, instantiation of the multiGaussian field is not necessary for estimation of the effective conductance. The critical component of the effective medium approximation developed here is the mean distance between high conductivity inclusions. This mean distance is characterized as a function of the FWHM, the truncation threshold and the ratio of the two modal conductivities. Sensitivity of the resulting effective conductivity to this mean distance is examined for two levels of contrast in the two modal conductances and different FWHM sizes. Results demonstrate that the FWHM is a robust measure of mean travel distance in the background medium. The resulting effective conductivities are accurate when compared to numerical results and results obtained from effective media theory, distance-based upscaling and numerical simulation.

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The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. To meet this objective, NEAMS Waste IPSC M&S capabilities will be applied to challenging spatial domains, temporal domains, multiphysics couplings, and multiscale couplings. A strategic verification and validation (V&V) goal is to establish evidence-based metrics for the level of confidence in M&S codes and capabilities. Because it is economically impractical to apply the maximum V&V rigor to each and every M&S capability, M&S capabilities will be ranked for their impact on the performance assessments of various components of the repository systems. Those M&S capabilities with greater impact will require a greater level of confidence and a correspondingly greater investment in V&V. This report includes five major components: (1) a background summary of the NEAMS Waste IPSC to emphasize M&S challenges; (2) the conceptual foundation for verification, validation, and confidence assessment of NEAMS Waste IPSC M&S capabilities; (3) specifications for the planned verification, validation, and confidence-assessment practices; (4) specifications for the planned evidence information management system; and (5) a path forward for the incremental implementation of this V&V plan.

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Power conversion systems for energy storage and other distributed energy resource applications are among the drivers of the important role that power electronics plays in providing reliable electricity. Wide band gap semiconductors such as silicon carbide (SiC) and gallium nitride (GaN) will help increase the performance and efficiency of power electronic equipment while condition monitoring (CM) and prognostics and health management (PHM) will increase the operational availability of the equipment and thereby make it more cost effective. Voltage and/or temperature stress testing were performed on a number of SiC devices in order to accelerate failure modes and to identify measureable shifts in electrical characteristics which may provide early indication of those failures. Those shifts can be interpreted and modeled to provide prognostic signatures for use in CM and/or PHM. Such experiments will also lead to a deeper understanding of basic device physics and the degradation mechanisms behind failure.

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Representative accident source terms patterned after the NUREG-1465 Source Term have been developed for high burnup fuel in BWRs and PWRs and for MOX fuel in a PWR with an ice-condenser containment. These source terms have been derived using nonparametric order statistics to develop distributions for the timing of radionuclide release during four accident phases and for release fractions of nine chemical classes of radionuclides as calculated with the MELCOR 1.8.5 accident analysis computer code. The accident phases are those defined in the NUREG-1465 Source Term - gap release, in-vessel release, ex-vessel release, and late in-vessel release. Important differences among the accident source terms derived here and the NUREG-1465 Source Term are not attributable to either fuel burnup or use of MOX fuel. Rather, differences among the source terms are due predominantly to improved understanding of the physics of core meltdown accidents. Heat losses from the degrading reactor core prolong the process of in-vessel release of radionuclides. Improved understanding of the chemistries of tellurium and cesium under reactor accidents changes the predicted behavior characteristics of these radioactive elements relative to what was assumed in the derivation of the NUREG-1465 Source Term. An additional radionuclide chemical class has been defined to account for release of cesium as cesium molybdate which enhances molybdenum release relative to other metallic fission products.

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This report summarizes the state of salt repository science, reviews many of the technical issues pertaining to disposal of heat-generating nuclear waste in salt, and proposes several avenues for future science-based activities to further the technical basis for disposal in salt. There are extensive salt formations in the forty-eight contiguous states, and many of them may be worthy of consideration for nuclear waste disposal. The United States has extensive experience in salt repository sciences, including an operating facility for disposal of transuranic wastes. The scientific background for salt disposal including laboratory and field tests at ambient and elevated temperature, principles of salt behavior, potential for fracture damage and its mitigation, seal systems, chemical conditions, advanced modeling capabilities and near-future developments, performance assessment processes, and international collaboration are all discussed. The discussion of salt disposal issues is brought current, including a summary of recent international workshops dedicated to high-level waste disposal in salt. Lessons learned from Sandia National Laboratories' experience on the Waste Isolation Pilot Plant and the Yucca Mountain Project as well as related salt experience with the Strategic Petroleum Reserve are applied in this assessment. Disposal of heat-generating nuclear waste in a suitable salt formation is attractive because the material is essentially impermeable, self-sealing, and thermally conductive. Conditions are chemically beneficial, and a significant experience base exists in understanding this environment. Within the period of institutional control, overburden pressure will seal fractures and provide a repository setting that limits radionuclide movement. A salt repository could potentially achieve total containment, with no releases to the environment in undisturbed scenarios for as long as the region is geologically stable. Much of the experience gained from United States repository development, such as seal system design, coupled process simulation, and application of performance assessment methodology, helps define a clear strategy for a heat-generating nuclear waste repository in salt.

Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD) project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.

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Spatially resolved measurements of electric fields at electrochemical interfaces would be a critical step toward further understanding and modeling the detailed structure of electric double layers. The goal of this project was to perform proof-of-principle experiments to demonstrate the use of field-sensitive dyes for optical measurements of fields in electrochemical systems. A confocal microscope was developed that provides sensitive detection of the lifetime and high resolution spectra of excited fluorescence for dyes tethered to electrically conductive surfaces. Excited state lifetimes for the dyes were measured and found to be relatively unquenched when linked to indium tin oxide, but strongly quenched on gold surfaces. However, our fluorescence detection is sufficiently sensitive to measure spectra of submonolayer dye coatings even when the fluorescence was strongly quenched. Further work to create dye labeled interfaces on flat, uniform and durable substrates is necessary to make electric field measurements at interfaces using field sensitive dyes.

An ideal red phosphor for blue LEDs is one of the biggest challenges for the solid-state lighting industry. The appropriate phosphor material should have good adsorption and emission properties, good thermal and chemical stability, minimal thermal quenching, high quantum yield, and is preferably inexpensive and easy to fabricate. Tantalates possess many of these criteria, and lithium lanthanum tantalate materials warrant thorough investigation. In this study, we investigated red luminescence of two lithium lanthanum tantalates via three mechanisms: (1) Eu-doping, (2) Mn-doping and (3) self-activation of the tantalum polyhedra. Of these three mechanisms, Mn-doping proved to be the most promising. These materials exhibit two very broad adsorption peaks; one in the UV and one in the blue region of the spectrum; both can be exploited in LED applications. Furthermore, Mn-doping can be accomplished in two ways; ion-exchange and direct solid-state synthesis. One of the two lithium lanthanum tantalate phases investigated proved to be a superior host for Mn-luminescence, suggesting the crystal chemistry of the host lattice is important.

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This report describes the conceptual design of a technology choice model for understanding strategies to reduce carbon intensity in the electricity sector. The report considers the major modeling issues affecting technology policy assessment and defines an implementable model construct. Further, the report delineates the basis causal structure of such a model and attempts to establish the technical/algorithmic viability of pursuing model development along with the associated analyses.

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Classical molecular dynamics simulations were used to investigate the formation of water droplets on two kaolinite surfaces: the gibbsite-like surface which is hydrophilic and the silica surface which is hydrophobic. Two methods for calculating contact angles were investigated in detail. The method of Giovambattista et al. was successful in calculating contact angles on both surfaces that compare well to the experimental data available. This is the first time that contact angles have been calculated for kaolinite surfaces from molecular simulations. This preliminary study provides the groundwork for investigating contact angles for more complex systems involving multiple fluids (water, CO{sub 2}, oil) in contact with different minerals in the subsurface environment.

The potential to treat non-traditional water sources using power plant waste heat in conjunction with membrane distillation is assessed. Researchers and power plant designers continue to search for ways to use that waste heat from Rankine cycle power plants to recover water thereby reducing water net water consumption. Unfortunately, waste heat from a power plant is of poor quality. Membrane distillation (MD) systems may be a technology that can use the low temperature waste heat (<100 F) to treat water. By their nature, they operate at low temperature and usually low pressure. This study investigates the use of MD to recover water from typical power plants. It looks at recovery from three heat producing locations (boiler blow down, steam diverted from bleed streams, and the cooling water system) within a power plant, providing process sketches, heat and material balances and equipment sizing for recovery schemes using MD for each of these locations. It also provides insight into life cycle cost tradeoffs between power production and incremental capital costs.

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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.

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The Power Systems L-CAT is a high-level dynamic model that calculates levelized production costs and tracks environmental performance for a range of electricity generation technologies: natural gas combined cycle (using either imported (LNGCC) or domestic natural gas (NGCC)), integrated gasification combined cycle (IGCC), supercritical pulverized coal (SCPC), existing pulverized coal (EXPC), nuclear, and wind. All of the fossil fuel technologies also include an option for including carbon capture and sequestration technologies (CCS). The model allows for quick sensitivity analysis on key technical and financial assumptions, such as: capital, O&M, and fuel costs; interest rates; construction time; heat rates; taxes; depreciation; and capacity factors. The fossil fuel options are based on detailed life cycle analysis reports conducted by the National Energy Technology Laboratory (NETL). For each of these technologies, NETL's detailed LCAs include consideration of five stages associated with energy production: raw material acquisition (RMA), raw material transport (RMT), energy conversion facility (ECF), product transportation and distribution (PT&D), and end user electricity consumption. The goal of the NETL studies is to compare existing and future fossil fuel technology options using a cradle-to-grave analysis. The NETL reports consider constant dollar levelized cost of delivered electricity, total plant costs, greenhouse gas emissions, criteria air pollutants, mercury (Hg) and ammonia (NH3) emissions, water withdrawal and consumption, and land use (acreage).

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