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.