2019 IEEE Electric Ship Technologies Symposium, ESTS 2019
Weaver, Wayne W.; Bijaieh, Mehrzad M.; Robinett, Rush D.; Wilson, David G.
Pulsed power loads (PPLs) are highly non-linear and can cause significant stability and power quality issues in a microgrid. One way to mitigate many of these issues is by designing an Energy Storage System (ESS) to offset the PPL. This paper provides a baseline for ESS control and specifications to mitigate the effects of PPL's. ESS will maintain a constant bus voltage and decouple the generation sources from the PPL. The ESS specifications are realized with ideal, band-limited hybrid battery and flywheels models and simulated to demonstrate the efficacy of the control system.
Carey, Ph; Ren, Fan; Baca, Albert G.; Klein, Brianna A.; Allerman, Andrew A.; Armstrong, Andrew M.; Douglas, Erica A.; Kaplar, Robert J.; Kotula, Paul G.; Pearton, Stephen J.
High Aluminum content channel (Al0.85Ga0.15N/Al-0.7Ga0.3N) High Electron Mobility Transistors (HEMTs) were operated from room temperature to 500°C in ambient. The devices exhibited only moderate reduction, 58%, in on-state forward current. Gate lag measurements at 100 kHz and 10% duty only showed a slight reduction in pulsed current from DC at 500°C and high gate voltages. Interfacial trap densities were 2 × 1011 over the range 25-300°C and 3 × 1012 cm-2 from 300-500°C from the subthreshold swing. These low interfacial trap densities and the near ideal gate lag measurement indicate high-quality epi layers. The insulating properties of the barrier layer led to low gate induced drain leakage current of ~10-12 A/mm and ~10-8 A/mm at 25 and 500°C, respectively. Low leakage current was enabled by the high Schottky barrier of the Ni/Au gate, 1.1 eV and 3.3 eV at 25 and 500°C, respectively. These properties of the AlGaN channel HEMTs demonstrate their potential for high power and high temperature operation.
Analyses have disagreed on whether the velocity uT of bulk advancement of a Huygens front in turbulence vanishes or remains finite in the limit of vanishing local front propagation speed u. Here, a connection to the large-deviation statistics of log-correlated random processes enables a definitive determination of the correct small-u asymptotics. This result reconciles several theoretical and phenomenological perspectives with the conclusion that uT remains finite for vanishing u, which implies a propagation anomaly akin to the energy-dissipation anomaly in the limit of vanishing viscosity. Various leading-order structural properties such as a novel u dependence of a bulk length scale associated with front geometry are predicted in this limit. The analysis involves a formal analogy to random advection of diffusive scalars.
The following summaries are provided as fulfillment of milestone M4SF-19SN10307022 and represent international coordination activities in disposal research funded by the US DOE Spent Fuel and Waste Storage and Technologies (SFWST) Campaign during Fiscal Year 2019.
Using a multiscale blood flow solver, the complete diffusion tensor of nanoparticles (NPs) in sheared cellular blood flow is calculated over a wide range of shear rate and haematocrit. In the short-time regime, NPs exhibit anomalous dispersive behaviors under high shear and high haematocrit due to the transient elongation and alignment of the red blood cells (RBCs). In the long-time regime, the NP diffusion tensor features high anisotropy. Particularly, there exists a critical shear rate around which the shear-rate dependence of the diffusivity tensor changes from linear to nonlinear scale. Above the critical shear rate, the cross-stream diffusivity terms vary sublinearly with shear rate, while the longitudinal term varies superlinearly. The dependence on haematocrit is linear in general except at high shear rates, where a sublinear scale is found for the vorticity term and a quadratic scale for the longitudinal term. Through analysis of the suspension microstructure and numerical experiments, the nonlinear haemorheological dependence of the NP diffusion tensor is attributed to the streamwise elongation and cross-stream contraction of RBCs under high shear, quantified by a capillary number. The RBC size is shown to be the characteristic length scale affecting the RBC-enhanced shear-induced diffusion (RESID), while the NP submicrometre size exhibits negligible influence on the RESID. Based on the observed scaling behaviours, empirical correlations are proposed to bridge the NP diffusion tensor to specific shear rate and haematocrit. The characterized NP diffusion tensor provides a constitutive relation that can lead to more effective continuum models to tackle large-scale NP biotransport applications.
A set of on-sun experiments was performed on a 1 MWth cavity-type falling particle receiver at Sandia National Laboratories. A computational model of the receiver was developed to evaluate its ability to predict the receiver performance during these experiments and to quantify the thermal losses from different mechanisms. Mean particle outlet temperatures and the experimental receiver thermal efficiencies were compared against values computed in the computational model. External winds during the experiments were found to significantly affect the receiver thermal efficiency, and advective losses from hot air escaping the receiver domain were found to be the most significant contribution to losses from the receiver. Losses from all other mechanisms including radiative losses amounted to less than 10% of the total incident thermal power.
Pyromark® 2500, manufactured by Tempil, is currently the industry standard for high solar absorptive receiver coatings for concentrating solar power towers. However, Pyromark has been reported to degrade if not applied properly or exposed to temperatures exceeding 700 °C over a period of time. However, it is not apparent if such degradation is due to a particular aspect or aspects of the deposition process, which may vary from plant to plant. Many variables factor in to the performance of Pyromark, e.g. deposition method, drying time, curing parameters (ramp rate, homogeneous heating, time at temperature.), and coating thickness. Identifying the factors with the most influence on coating performance and durability will help guide the application of Pyromark to receivers to minimize degradation over time. The relationships between coating quality and optical properties with deposition/curing parameters on Haynes 230 substrates were assessed using statistical analysis of variance (ANOVA) techniques for repeated measures. These ANOVA techniques were designed to detect differences in treatment effects on the response at each of the aging cycles. The analyses found that coating thickness, curing ramp rate, and dwell time had the most effect on coating quality.
MgO is a major constituent of the MgO-FeO-SiO2 system that comprises the Earth's mantle and that of super-Earth exoplanets. Knowledge of its high-pressure behavior is important for modeling the more complex compounds. This paper presents measurements of the principal Hugoniot, sound velocity, and temperature of MgO, shocked to pressures of 710 to 2300 GPa using laser-driven compression. The Hugoniot and temperature measurements compare favorably to previous results constraining the shock response of MgO at extreme conditions. The Grüneisen parameter was calculated from the Hugoniot and sound velocity data and was found to be underpredicted by tabular models. The sound velocity of liquid MgO is overpredicted by models implying that the quantity of partial melt required to match decreased wave speeds in ultralow velocity zones in the lower mantle may be less than previously assumed and experiments at lower-mantle pressures are needed.
Neuromorphic hardware architectures represent a growing family of potential post-Moore's Law Era platforms. Largely due to event-driving processing inspired by the human brain, these computer platforms can offer significant energy benefits compared to traditional von Neumann processors. Unfortunately there still remains considerable difficulty in successfully programming, configuring and deploying neuromorphic systems. We present the Fugu framework as an answer to this need. Rather than necessitating a developer attain intricate knowledge of how to program and exploit spiking neural dynamics to utilize the potential benefits of neuromorphic computing, Fugu is designed to provide a higher level abstraction as a hardware-independent mechanism for linking a variety of scalable spiking neural algorithms from a variety of sources. Individual kernels linked together provide sophisticated processing through compositionality. Fugu is intended to be suitable for a wide-range of neuromorphic applications, including machine learning, scientific computing, and more brain-inspired neural algorithms. Ultimately, we hope the community adopts this and other open standardization attempts allowing for free exchange and easy implementations of the ever-growing list of spiking neural algorithms.
Multi-fluid plasma models, where an electron fluid is modeled in addition to multiple ion and neutral species as well as the full set of Maxwell's equations, are useful for representing physics beyond the scope of classic MHD. This advantage presents challenges in appropriately dealing with electron dynamics and electromagnetic behavior characterized by the plasma and cyclotron frequencies and the speed of light. For physical systems, such as those near the MHD asymptotic regime, this requirement drastically increases runtimes for explicit time integration even though resolving fast dynamics may not be critical for accuracy. Implicit time integration methods, with efficient solvers, can help to step over fast time-scales that constrain stability, but do not strongly influence accuracy. As an extension, Implicit-explicit (IMEX) schemes provide an additional mechanism to choose which dynamics are evolved using an expensive implicit solve or resolved using a fast explicit solve. In this study, in addition to IMEX methods we also consider a physics compatible exact sequence spatial discretization. Here, this combines nodal bases (H-Grad) for fluid dynamics with a set of vector bases (H-Curl and H-Div) for Maxwell's equations. This discretization allows for multi-fluid plasma modeling without violating Gauss' laws for the electric and magnetic fields. This initial study presents a discussion of the major elements of this formulation and focuses on demonstrating accuracy in the linear wave regime and in the MHD limit for both a visco-resistive and a dispersive ideal MHD problem.
Neuromorphic architectures are represented by a broad class of hardware, with artificial neural network (ANN) architectures at one extreme and event-driven spiking architectures at another. Algorithms and applications efficiently processed by one neuromorphic architecture may be unsuitable for another, but it is challenging to compare various neuromorphic architectures among themselves and with traditional computer architectures. In this position paper, we take inspiration from architectural characterizations in scientific computing and motivate the need for neuromorphic architecture comparison techniques, outline relevant performance metrics and analysis tools, and describe cognitive workloads to meaningfully exercise neuromorphic architectures. Additionally, we propose a simulation-based framework for benchmarking a wide range of neuromorphic workloads. While this work is applicable to neuromorphic development in general, we focus on event-driven architectures, as they offer both unique performance characteristics and evaluation challenges.
In this paper we present a design concept for 3D plasmonic scatterers as high-efficiency transmissive metasurface (MS) building blocks. A genetic algorithm (GA) routine partitions the faces of the walls inside an open cavity into a M x N grid of voxels which can be either covered with metal or left bare, and optimizes the distribution of metal coverage needed to generate electric and magnetic modes of equal strength with a targeted phase delay (Φt) at the design wavelength. Even though the electric and magnetic modes can be more complicated than typical low order modes, with their spectral overlap and equal strengths, they act as a Huygens source, with the accompanying low reflection magnitude. Square/hexagonal voxels inside square/rectangular cavities are thoroughly analyzed for operation at 8 µm, although the technique can be applied to different cavity geometries for operation across the electromagnetic spectrum. Results from full-wave simulations show the GA routine can repeatedly pinpoint scatterer geometries emitting at any Φt value across 2π phase space with transmittances of at least 60%, making these MS building blocks an attractive plasmonic alternative for practical optical applications. Full-scale metasurface devices are calculated from near-fields of the individual elements to validate the optical functionality.
The characterization of a steam impulse Terry turbine operating with single- and two-phase air–water ingestion has been performed; the air mass fraction ranged from 1.0 (single-phase air) down to 0.05. The two-phase characteristics were obtained over a range of turbine inlet pressures and turbine rotational speeds. Here, the torque produced and the mixture flow rate through the turbine were recorded. Based upon experimental air/water measurements, the turbine Affinity Laws have been modified to include the effects of two-phase flow.
In this work, we examine metal electrode-ionomer electrolyte systems at high voltage (negative surface charge) and at high pH to assess factors that influence hydrogen production efficiency. We simulate the hydrogen evolution electrode interface investigated experimentally in the work of Bates et al. [J. Phys. Chem. C 119, 5467 (2015)] using a combination of first principles calculations and classical molecular dynamics. With this detailed molecular information, we explore the hypotheses posed in the work of Bates et al. In particular, we examine the response of the system to increased bias voltage and oxide coverage in terms of the potential profile, changes in solvation and species concentrations away from the electrode, surface concentrations, and orientation of water at reactive surface sites. We discuss this response in the context of hydrogen production.
Benchmarking methods that can be adapted to multiqubit systems are essential for assessing the overall or "holistic" performance of nascent quantum processors. The current industry standard is Clifford randomized benchmarking (RB), which measures a single error rate that quantifies overall performance. But, scaling Clifford RB to many qubits is surprisingly hard. It has only been performed on one, two, and three qubits as of this writing. This reflects a fundamental inefficiency in Clifford RB: the n-qubit Clifford gates at its core have to be compiled into large circuits over the one- and two-qubit gates native to a device. As n grows, the quality of these Clifford gates quickly degrades, making Clifford RB impractical at relatively low n. In this Letter, we propose a direct RB protocol that mostly avoids compiling. Instead, it uses random circuits over the native gates in a device, which are seeded by an initial layer of Clifford-like randomization. We demonstrate this protocol experimentally on two to five qubits using the publicly available ibmqx5. We believe this to be the greatest number of qubits holistically benchmarked, and this was achieved on a freely available device without any special tuning up. Our protocol retains the simplicity and convenient properties of Clifford RB: it estimates an error rate from an exponential decay. But, it can be extended to processors with more qubits - we present simulations on 10+ qubits - and it reports a more directly informative and flexible error rate than the one reported by Clifford RB. We show how to use this flexibility to measure separate error rates for distinct sets of gates, and we use this method to estimate the average error rate of a set of cnot gates.
DeRosa, Sean D.; Kimura, Yosuke; Stadtherr, Mark A.; Mcgaughey, Gary; Mcdonald-Buller, Elena; Allen, David T.
A geographically resolved network model of the U.S. chemical industry in 2017 is constructed, and optimal chemical flows between units are calculated using linear programming. A baseline solution and three disruption scenarios (primary raw material disruptions, reported Hurricane Harvey ethylene cracker disruptions, and assumed capacity disruptions based on the Hurricane Harvey geographic storm track) are studied to determine how the structure of the industry is modified to adapt to widespread and geographically specific disruptions. The calculated impacts of the assumed Hurricane Harvey disruption include 170 chemical units in 26 states that change production level as a result of supply chain disruptions during the storm. The systemic impact for the assumed Hurricane Harvey disruption is 19.3 million tonnes of gross chemical production. The day with the largest impact on gross chemical production shows a reduction from baseline operations of 1.3 million tonnes (42% of baseline). This model can be used for analysis of future disruption scenarios and to test resilience strategies, including impacts of new manufacturing configurations or technologies.
Geophysical observations show spatial and temporal variations in fault slip style on shallow subduction thrust faults, but geological signatures and underlying deformation processes remain poorly understood. International Ocean Discovery Program (IODP) Expeditions 372 and 375 investigated New Zealand’s Hikurangi margin in a region that has experienced both tsunami earthquakes and repeated slow-slip events. We report direct observations from cores that sampled the active Papaku splay fault at 304 m below the seafloor. This fault roots into the plate interface and comprises an 18-m-thick main fault underlain by ~30 m of less intensely deformed footwall and an ~10-m-thick subsidiary fault above undeformed footwall. Fault zone structures include breccias, folds, and asymmetric clasts within transposed and/or dismembered, relatively homogeneous, silty hemipelagic sediments. The data demonstrate that the fault has experienced both ductile and brittle deformation. As a result, this structural variation indicates that a range of local slip speeds can occur along shallow faults, and they are controlled by temporal, potentially far-field, changes in strain rate or effective stress.
This document outlines the approach used for interpolation of a dataset provided by the Jet Propulsion Laboratory (JPL) which contains failure predictions of the Mars 2020 entry vehicle (EV). JPL used Navier-Stokes simulations to predict the failure altitude of the EV, along with a corresponding velocity and flight path angle at failure. These simulations were executed for several initial trajectory points in the entry envelope (the V-Gamma map).
Transient simulations of linear viscoelastically damped structures require excessive computational resources to directly integrate the full-order finite element model with time-stepping algorithms. Traditional modal reduction techniques are not directly applicable to these systems since viscoelastic materials depend on time and frequency. A more appropriate reduction basis is obtained from the nonlinear, complex eigenvalue problem, whose eigenvectors capture the appropriate kinematics and enable frequency-based mode selection; unfortunately, the computational cost is prohibitive for computing these modes from large-scale engineering models. To address this shortcoming, this work proposes a novel two-tier reduction procedure to reduce the upfront cost of solving the complex, nonlinear eigenvalue problem. The first reduction step reduces the full-order model with real mode shapes linearized about various centering frequencies to capture the kinematics over a full range of viscoelastic material behavior (glassy, rubbery, and glass-transition zones). This tier-one reduction preserves time-temperature superposition and allows the equations to depend parametrically on operating temperature. The second-level reduction then solves the complex, nonlinear eigenmode solutions in the tier-one reduced space about a fixed temperature to further reduce the equations-of-motion. The method is demonstrated on a cantilevered sandwich plate to showcase its accuracy and efficiency in comparison to full-order model predictions.
In this paper we present an adjustment to traditional ALE discretizations of resistive MHD where we do not neglect the time derivative of the electric displacement field. This system is referred to variously as a perfect electromagnetic fluid or a single fluid plasma although we refer to the system as Full Maxwell Hydrodynamics (FMHD) in order to evoke its similarities to resistive Magnetohydrodynamics (MHD). Unlike the MHD system the characteristics of this system do not become arbitrarily large in the limit of low densities. In order to take advantage of these improved characteristics of the system we must tightly couple the electromagnetics into the Lagrangian motion and do away with more traditional operator splitting. We provide a number of verification tests to demonstrate both accuracy of the method and an asymptotic preserving (AP) property. In addition we present a prototype calculation of a Z-pinch and find very good agreement between our algorithm and resistive MHD. Further, FMHD leads to a large performance gain (approximately 4.6x speed up) compared to resistive MHD. We unfortunately find our proposed algorithm does not conserve charge leaving us with an open problem.
Traditional explicit partitioned schemes exchange boundary conditions between subdomains and can be related to iterative solution methods for the coupled problem. As a result, these schemes may require multiple subdomain solves, acceleration techniques, or optimized transmission conditions to achieve sufficient accuracy and/or stability. We present a new synchronous partitioned method derived from a well-posed mixed finite element formulation of the coupled problem. We transform the resulting Differential Algebraic Equation (DAE) to a Hessenberg index-1 form in which the algebraic equation defines the Lagrange multiplier as an implicit function of the states. Using this fact we eliminate the multiplier and reduce the DAE to a system of explicit ODEs for the states. Explicit time integration both discretizes this system in time and decouples its equations. As a result, the temporal accuracy and stability of our formulation are governed solely by the accuracy and stability of the explicit scheme employed and are not subject to additional stability considerations as in traditional partitioned schemes. We establish sufficient conditions for the formulation to be well-posed and prove that classical mortar finite elements on the interface are a stable choice for the Lagrange multiplier. We show that in this case the condition number of the Schur complement involved in the elimination of the multiplier is bounded by a constant. The paper concludes with numerical examples illustrating the approach for two different interface problems.
Using random walk analyses we explore diffusive transport on networks obtained from contacts between isotropically compressed, monodisperse, frictionless sphere packings generated over a range of pressures in the vicinity of the jamming transition p→0. For conductive particles in an insulating medium, conduction is determined by the particle contact network with nodes representing particle centers and edges contacts between particles. The transition rate is not homogeneous, but is distributed inhomogeneously due to the randomness of packing and concomitant disorder of the contact network, e.g., the distribution of the coordination number. A narrow escape time scale is used to write a Markov process for random walks on the particle contact network. This stochastic process is analyzed in terms of spectral density of the random, sparse, Euclidean and real, symmetric, positive, semidefinite transition rate matrix. Results show network structures derived from jammed particles have properties similar to ordered, euclidean lattices but also some unique properties that distinguish them from other structures that are in some sense more homogeneous. In particular, the distribution of eigenvalues of the transition rate matrix follow a power law with spectral dimension 3. However, quantitative details of the statistics of the eigenvectors show subtle differences with homogeneous lattices and allow us to distinguish between topological and geometric sources of disorder in the network.
Irradiation resistance of metallic nanostructured multilayers is determined by the interactions between defects and phase boundaries. However, the dose-dependent interfacial morphology evolution can greatly change the nature of the defect-boundary interaction mechanisms over time. In the present study, we used atomistic models combined with a novel technique based on the accumulation of Frenkel pairs to simulate irradiation processes. We examined dose effects on defect evolutions near zirconium-niobium multilayer phase boundaries. Our simulations enabled us to categorize defect evolution mechanisms in bulk phases into progressing stages of dislocation accumulation, saturation, and coalescence. In the metallic multilayers, we observed a phase boundary absorption mechanism early on during irradiation, while at higher damage levels, the increased irradiation intermixing triggered a phase transformation in the Zr-Nb mixture. This physical phenomenon resulted in the emission of a large quantity of small immobile dislocation loops from the phase boundaries.
This report discusses several possible sources of water that could persist in SNF dry storage canisters through the drying cycle. In some cases, the water is trapped in occluded geometries in the cask such as dashpots or damaged fuel. Persistence of water or ice in such locations seems unlikely, given the high heat load of the canistered fuel; this is especially true in the case of vacuum drying, where a strong driver exists to remove water vapor from the headspace of such occluded geometries. Water retention in Boral® core material is a known problem, that has in the past resulted in the need for much extended drying times. Since the shift to slightly higher porosity "blister resistant" Boral®, water drainage appears to be less of a problem. However, high surface areas for the Boral® core material will provide a trap for significant amounts of adsorbed water, at least some of which is certain to survive the drying process. Moreover, if corrosion within the cores produces hydrous aluminum corrosion products, these may also survive.
When modeling thin structures, some analysts use shell elements. Others choose hex elements. Both element types have their advantages and disadvantages. This memo describes a weakness of using hex elements to model bending. Specifically, the accuracy degrades as the element aspect ratio increases. This study illustrates this effect for the mean quadrature and the selective deviatoric formulations. For the test case considered, the selective deviatoric formulation produces larger errors.
Lithium-ion battery safety is prerequisite for applications from consumer electronics to grid energy storage. Cell and component-level calorimetry studies are central to safety evaluations. Qualitative empirical comparisons have been indispensable in understanding decomposition behavior. More systematic calorimetry studies along with more comprehensive measurements and reporting can lead to more quantitative mechanistic understanding. This mechanistic understanding can facilitate improved designs and predictions for scenarios that are difficult to access experimentally, such as system-level failures. Recommendations are made to improve usability of calorimetry results in mechanistic understanding. From our perspective, this path leads to a more mature science of battery safety.
One of the main advantages of using tungsten (W) as a plasma facing material (PFM) is its low uptake and retention of tritium. However, in high purity (ITER grade) W, hydrogenic retention increases significantly with neutron-induced displacement damage in the W lattice. This experiment examines an alternative W grade PFM, ultra-fine grain (UFG) W, to compare its retention properties with ITER grade W after 12 MeV Si ion displacement damage up to 0.6 dpa (displacements per atom.) Following exposure to plasma in the DIII-D divertor, D retention was then assessed with Nuclear Reaction Analysis (NRA) depth profiling up to 3.5 µm and thermal desorption spectrometry (TDS). Undamaged specimens were also included in our test matrix for comparison. For all samples, D release peaks were observed during TDS at approximately 200 °C and 750 °C. For the ITER-grade W specimens, the intensity of the 750 °C release peak was more pronounced for specimens that had been pre-damaged.
Strong coupling of an intersubband (ISB) electron transition in quantum wells to a subwavelength plasmonic nanoantenna can give rise to intriguing quantum phenomena, such as ISB polariton condensation, and enable practical devices including low threshold lasers. However, experimental observation of ISB polaritons in an isolated subwavelength system has not yet been reported. Here, we use scanning probe near-field microscopy and Fourier-transform infrared (FTIR) spectroscopy to detect formation of ISB polariton states in a single nanoantenna. We excite the nanoantenna by a broadband IR pulse and spectrally analyze evanescent fields on the nanoantenna surface. We observe the distinctive splitting of the nanoantenna resonance peak into two polariton modes and two ?-phase steps corresponding to each of the modes. We map ISB polariton dispersion using a set of nanoantennae of different sizes. This nano-FTIR spectroscopy approach opens doors for investigations of ISB polariton physics in the single subwavelength nanoantenna regime.
Tungsten, the material used in the plasma-facing components (PFCs) of nuclear fusion reactors, develops a fuzz-like surface morphology under typical reactor operating conditions. This fragile 'fuzz' surface nanostructure adversely affects reactor performance and operation. Developing predictive models, capable of simulating the spatiotemporal scales relevant to the fuzz formation process is essential for understanding the growth of such extremely complex surface features and improving PFC and reactor performance. Here, we report the development of an atomistically-informed, continuous-domain model for the onset of fuzz formation in helium plasma-irradiated tungsten and validate the model by comparing its predictions with measurements from carefully designed experiments. Our study demonstrates that fuzz forms in response to stress induced in the near-surface region of PFCs as a result of plasma exposure and helium gas implantation. Our model sets the stage for detailed descriptions of this complex fuzz formation phenomenon and similar phenomena observed in other materials.
Here in the present study, we propose a novel multiphysics model that merges two time-dependent problems – the Fluid-Structure Interaction (FSI) and the ultrasonic wave propagation in a fluid-structure domain with a one directional coupling from the FSI problem to the ultrasonic wave propagation problem. This model is referred to as the “eXtended fluid-structure interaction (eXFSI)” problem. This model comprises isothermal, incompressible Navier-Stokes equations with nonlinear elastodynamics using the Saint-Venant Kirchhoff solid model. The ultrasonic wave propagation problem comprises monolithically coupled acoustic and elastic wave equations. To ensure that the fluid and structure domains are conforming, we use the ALE technique. The solution principle for the coupled problem is to first solve the FSI problem and then to solve the wave propagation problem. Accordingly, the boundary conditions for the wave propagation problem are automatically adopted from the FSI problem at each time step. The overall problem is highly nonlinear, which is tackled via a Newton-like method. The model is verified using several alternative domain configurations. To ensure the credibility of the modeling approach, the numerical solution is contrasted against experimental data.
Sandia National Laboratories is one of the most technologically advanced and resourceful national laboratories in the United States. Their mission is to use science and technology, innovative research, and global engagement to counter threats, reduce dangers, and respond to disasters. To achieve this mission, Sandia is divided into ten divisions that are overlooked by Dr. Stephen Younger, the Laboratories Director. Amongst the ten divisions, the internship will take place in Division 8000, which is Integrated Security Solutions. Inside this division, the internship will be a Structural and Thermal Analysis R&D. Apart from being strictly focused on security, the division performs research for small companies that do not count with the resources to perform it themselves. During the summer internship, one of these cases is being attended. A small company invented an insulating cover that is supposed to be placed over the top of a cooking pot lid. They claim that the insulating cover helps in the saving of energy. As an intern and researcher, the task is to determine how much energy is effectively saved by placing the insulating cover over the cooking pot. To achieve the goal, mathematical analyses, experiments and simulations will be done. Then, if appropriate, a better design will be made to increase the energy saved by the insulating cover. For the mathematical analysis, the thermal resistance method was used, resulting in energy saved at a rate of 14.2795 W. After the mathematical analysis was done, a test plan was developed and presented to the supervisor for approval. After some recommendations, the test plan will be modified accordingly.
Tang, Qi; Klein, Stephen A.; Xie, Shaocheng; Lin, Wuyin; Golaz, Jean C.; Roesler, Erika L.; Taylor, Mark A.; Rasch, Philip J.; Bader, David C.; Berg, Larry K.; Caldwell, Peter; Giangrande, Scott E.; Neale, Richard B.; Qian, Yun; Riihimaki, Laura D.; Zender, Charles S.; Zhang, Yuying; Zheng, Xue
Climate simulations with more accurate process-level representation at finer resolutions (<100 km) are a pressing need in order to provide more detailed actionable information to policy makers regarding extreme events in a changing climate. Computational limitation is a major obstacle for building and running high-resolution (HR, here 0.25° average grid spacing at the Equator) models (HRMs). A more affordable path to HRMs is to use a global regionally refined model (RRM), which only simulates a portion of the globe at HR while the remaining is at low resolution (LR, 1°). In this study, we compare the Energy Exascale Earth System Model (E3SM) atmosphere model version 1 (EAMv1) RRM with the HR mesh over the contiguous United States (CONUS) to its corresponding globally uniform LR and HR configurations as well as to observations and reanalysis data. The RRM has a significantly reduced computational cost (roughly proportional to the HR mesh size) relative to the globally uniform HRM. Over the CONUS, we evaluate the simulation of important dynamical and physical quantities as well as various precipitation measures. Differences between the RRM and HRM over the HR region are predominantly small, demonstrating that the RRM reproduces the precipitation metrics of the HRM over the CONUS. Further analysis based on RRM simulations with the LR vs. HR model parameters reveals that RRM performance is greatly influenced by the different parameter choices used in the LR and HR EAMv1. This is a result of the poor scale-aware behavior of physical parameterizations, especially for variables influencing sub-grid-scale physical processes. RRMs can serve as a useful framework to test physics schemes across a range of scales, leading to improved consistency in future E3SM versions. Applying nudging-to-observations techniques within the RRM framework also demonstrates significant advantages over a free-running configuration for use as a test bed and as such represents an efficient and more robust physics test bed capability. Our results provide additional confirmatory evidence that the RRM is an efficient and effective test bed for HRM development.
Antonov, Ivan; Voronova, Krisztina; Chen, Ming W.; Sztaray, Balint; Hemberger, Patrick; Bodi, Andras; Osborn, David L.; Sheps, Leonid S.
We investigate the gas-phase photochemistry of the enolone tautomer of acetylacetone (pentane-2,4-dione) following S2(ππ∗) → S0 excitation at λ = 266 and 248 nm, using three complementary time-resolved spectroscopic methods. Contrary to earlier reports, which claimed to study one-photon excitation of acetylacetone and found OH and CH3 as the only important gas-phase products, we detect 15 unique primary photoproducts and demonstrate that five of them, including OH and CH3, arise solely by multiphoton excitation. We assign the one-photon products to six photochemical channels and show that the most significant pathway is phototautomerization to the diketone form, which is likely an intermediate in several of the other product channels. Furthermore, we measure the equilibrium constant of the tautomerization of the enolone to diketone on S0 from 320 to 600 K and extract ΔH = 4.1 ± 0.3 kcal·mol-1 and ΔS = 6.8 ± 0.5 cal·mol-1·K-1 using a van't Hoff analysis. We correct the C-OH bond dissociation energy in acetylacetone, previously determined as 90 kcal·mol-1 by theory and experiment, to a new value of 121.7 kcal·mol-1. Our experiments and electronic structure calculations provide evidence that some of the product channels, including phototautomerization, occur on S0, while others likely occur on excited triplet surfaces. Although the large oscillator strength of the S2 → S0 transition results from the (ππ∗) excitation of the C=C - C=O backbone, similar to conjugated polyenes, the participation of triplets in the dissociation pathways of acetylacetone appears to have more in common with ketone photochemistry.
A molecular-scale understanding of the transition between hydration states in clay minerals remains a challenging problem because of the very fast stepwise swelling process observed from X-ray diffraction (XRD) experiments. XRD profile modeling assumes the coexistence of multiple hydration states in a clay sample to fit the experimental XRD pattern obtained under humid conditions. While XRD profile modeling provides a macroscopic understanding of the heterogeneous hydration structure of clay minerals, a microscopic model of the transition between hydration states is still missing. Here, for the first time, we use molecular dynamics simulation to investigate the transition states between a dry interlayer, one-layer hydrate, and two-layer hydrate. We find that the hydrogen bonds that form across the interlayer at the clay particle edge make an important contribution to the energy barrier to interlayer hydration, especially for initial hydration.
Barnhart-Dailey, Meghan C.; Ye, Dongmei; Hayes, Dulce C.; Maes, Danae; Simoes, Casey T.; Appelhans, Leah; Carroll-Portillo, Amanda; Kent, Michael S.; Timlin, Jerilyn A.
Background: Valorization of lignin has the potential to significantly improve the economics of lignocellulosic biorefineries. However, its complex structure makes conversion to useful products elusive. One promising approach is depolymerization of lignin and subsequent bioconversion of breakdown products into value-added compounds. Optimizing transport of these depolymerization products into one or more organism(s) for biological conversion is important to maximize carbon utilization and minimize toxicity. Current methods assess internalization of depolymerization products indirectly - for example, growth on, or toxicity of, a substrate. Furthermore, no method has been shown to provide visualization of depolymerization products in individual cells. Results: We applied mass spectrometry to provide direct measurements of relative internalized concentrations of several lignin depolymerization compounds and single-cell microscopy methods to visualize cell-to-cell differences in internalized amounts of two lignin depolymerization compounds. We characterized internalization of 4-hydroxybenzoic acid, vanillic acid, p-coumaric acid, syringic acid, and the model dimer guaiacylglycerol-beta-guaiacyl ether (GGE) in the lignolytic organisms Phanerochaete chrysosporium and Enterobacter lignolyticus and in the non-lignolytic but genetically tractable organisms Saccharomyces cerevisiae and Escherichia coli. The results show varying degrees of internalization in all organisms for all the tested compounds, including the model dimer, GGE. Phanerochaete chrysosporium internalizes all compounds in non-lignolytic and lignolytic conditions at comparable levels, indicating that the transporters for these compounds are not specific to the lignolytic secondary metabolic system. Single-cell microscopy shows that internalization of vanillic acid and 4-hydroxybenzoic acid analogs varies greatly among individual fungal and bacterial cells in a given population. Glucose starvation and chemical inhibition of ATP hydrolysis during internalization significantly reduced the internalized amount of vanillic acid in bacteria. Conclusions: Mass spectrometry and single-cell microscopy methods were developed to establish a toolset for providing direct measurement and visualization of relative internal concentrations of mono- and di-aryl compounds in microbes. Utilizing these methods, we observed broad variation in intracellular concentration between organisms and within populations and this may have important consequences for the efficiency and productivity of an industrial process for bioconversion. Subsequent application of this toolset will be useful in identifying and characterizing specific transporters for lignin-derived mono- and di-aryl compounds.
This report summarizes Sandia National Laboratories (SNL) contribution to ATA Engineering, Inc's (ATA) project for the Naval Air Systems Command (NAVAIR), entitled "Optimization of Fatigue Test Signal Compression Using the Wavelet Transform." Sandia National Laboratories were a subcontractor to ATA. We were involved because this was a Small Business Technology Transfer (STTR) project that required ATA to partner with a national laboratory or academic institution. ATA selected SNL, and specifically the Environments Engineering Department (1557) because ATA has a long-standing working relationship with this department and the department staff have experience in environment definition, signal processing, fatigue testing protocols and traditional methods of generating inputs for accelerated fatigue testing.
The traditional scientific process has been revolutionized by the advent of computational modeling, but the nuclear industry generally uses “legacy codes,” which were developed early in the evolution of computers. One example of a legacy code, the thermal hydraulic subchannel code CTF, is modernized in this work through the development of a novel residual-based version, CTF-R. Unlike its predecessor, CTF-R is not limited by the strict computational limitations of the early 1980's, and can therefore be designed such that it is inherently flexible and easy to use. A case study is examined to demonstrate how the flexibility of the code can be used to improve simulation results. In this example, the coupling between the solid and liquid fields is examined. Traditionally, this coupling is modeled explicitly, which imposes numerical stability limits on the time step size. These limits are derived and it is shown that they are removed when the coupling is made implicit. Further, the development of CTF-R will enable future improvements in next generation reactor modeling, numerical methods, and coupling to other codes. Through the further development of CTF-R and other residual-based codes, state-of-the-art simulation is possible.
In the realm of information extraction from text data, there exists a number of tools with the capability of extracting entities and their relationships with one another. Such information has endless uses in a number of domains, however, the solutions to getting this information is still in early stages and has room for improvement. The topic has been explored from a research perspective by academic institutions, as well as formal tool creation from corporations. Overall, entity extraction is common among these tools, though with varying degrees of accuracy, while relationship extraction is more difficult to find. In this report, we take a look at the top state of the art tools currently available and identify their capabilities, strengths, and weaknesses. We explore the common algorithms in the successful approaches and their ability to efficiently handle both structured and unstructured text data. Finally, we highlight some of the common issues among these tools and summarize the current status in the area of entity-relationship extraction.
Polynomial chaos expansions (PCE) are well-suited to quantifying uncertainty in models parameterized by independent random variables. The assumption of independence leads to simple strategies for building multivariate orthonormal bases and for sampling strategies to evaluate PCE coefficients. In contrast, the application of PCE to models of dependent variables is much more challenging. Three approaches can be used to construct PCE of models of dependent variables. The first approach uses mapping methods where measure transformations, such as the Nataf and Rosenblatt transformation, can be used to map dependent random variables to independent ones; however we show that this can significantly degrade performance since the Jacobian of the map must be approximated. A second strategy is the class of dominating support methods. In these approaches a PCE is built using independent random variables whose distributional support dominates the support of the true dependent joint density; we provide evidence that this approach appears to produce approximations with suboptimal accuracy. A third approach, the novel method proposed here, uses Gram–Schmidt orthogonalization (GSO) to numerically compute orthonormal polynomials for the dependent random variables. This approach has been used successfully when solving differential equations using the intrusive stochastic Galerkin method, and in this paper we use GSO to build PCE using a non-intrusive stochastic collocation method. The stochastic collocation method treats the model as a black box and builds approximations of the input–output map from a set of samples. Building PCE from samples can introduce ill-conditioning which does not plague stochastic Galerkin methods. To mitigate this ill-conditioning we generate weighted Leja sequences, which are nested sample sets, to build accurate polynomial interpolants. We show that our proposed approach, GSO with weighted Leja sequences, produces PCE which are orders of magnitude more accurate than PCE constructed using mapping or dominating support methods.
This project addresses the important issue of validating the integrity of spent nuclear fuel storage for extended periods of time, followed by transportation. While it is believed that this fuel is safe in its current condition for long periods of time, confirmatory data and analyses need to be obtained to validate our understanding of used fuel degradation mechanisms that may impinge on the integrity of the fuel to withstand long term storage and transportation conditions. This is especially true for high burnup fuel (> 45 GWD/MTU) that is currently being discharged. The international community recognizes the importance of these issues. Moreover, several European countries now envisage to subject mixed oxide (MOX) fuel to extended storage and direct disposal. The institutes collaborating on this proposal all have active programs focused on resolving these very issues. Collaborating together provides a leverage of programs and funding that will benefit each program individually as well as the commercial nuclear industry, as a whole.
Sandia National Laboratories (SNL) is developing a low-cost, environmentally safe, and weather-proof sensor system that can be deployed offshore for extended periods of time for wind resource monitoring. The system has clear economic benefits over meteorological (met) tower approaches and is easily relocated to multiple locations across a project site. The end development goal is a buoy or barge-based, balloon-borne atmospheric measurement platform that operates autonomously in all but the most severe weather conditions, provides data of comparable accuracy to a met tower, and provides more accurate wind data at higher altitudes than floating lidar at half the cost.
Atmospheric measurements are collected from anemometer modules (cup-version pictured) that are attached to a tether line between a balloon and barge at user-specified intervals. Each module samples wind speed, wind direction, pressure, temperature, relative humidity, and GPS-derived latitude, longitude, and altitude in situ at 1 Hz or faster and transmits the data wirelessly to a base station on a barge. Fiber-optic based distributed temperature sensing (DTS) also provides an almost continuous atmospheric temperature profile with a vertical spatial resolution of 0.25 m.
During CED-3a, the following information is required, as specified in the April 1,2016 revision of the CEdT process manual: A detailed cost estimate; and, A resource loaded(baseline) schedule for execution of the experiment, data analysis, and publication. Appendix I is a Gantt chart or various phases of the project.
This report documents recent code verification exercises for a warm electron diode problem using the EMPIRE plasma code. This computationally expensive test was performed three times, including two different code versions and two different time integration algorithms, and the resulting code responses were analyzed for convergence to the analytical solution and orders-of-convergence using the StREEQ numerical error estimation tool. Significant deviations from the exact solution and expected orders-of-convergence, as well as changes in code behavior over time and due to choice of time integration algorithm were observed, illustrating the need to fix fundamental code issues as well as additional code verification testing before the code can be relied upon to accurately solve critical problems within its application space.
This report details the background, design, and initial results for wave energy converter design optimization tool. This tool is intended to provide researchers and developers with a means of optimizing existing wave energy converter designs by including realistic dynamics and control algorithms early in the design cycle.
The work for Step 1 performed at Sandia National Laboratories and reported in Section 7 has been updated to incorporate new data and to conduct new simulations using a new larger base case domain. The new simulations also include statistical analysis for different fracture realizations. A sensitivity analysis was also conducted to the study of the effect of domain size. A much larger mesh was selected to minimize boundary effects. The DFN model was upscaled to the new base case domain and the much larger domain to generate relevant permeability and porosity fields for each case. The calculations updated for Step 2 are described in Section 12.1. New calculations have also been conducted to model the flooding of the CTD and the resulting pressure recovery. The modeling includes matching of pressure and chloride experimental data at the six observation locations in Well 12M133. The modeling was done for the 10 fracture realizations. The Step 2 recovery simulations are described in Section 12.2. The Step 2 work is summarized in Section 12.3.
EMPHASIS™/NEVADA is the SIERRA/NEVADA toolkit implementation of portions of the EMPHASIS TM code suite. The purpose of the toolkit implementation is to facilitate coupling to other physics drivers such as radiation transport as well as to better manage code design, implementation, complexity, and important verification and validation processes. This document describes the theory and implementation of the unstructured finite- element method solver, associated algorithms, and selected verification and validation.
Cell testing is an important part of understanding the performance and life capabilities of state-of-the art energy storage technologies, particularly with respect to the distinct technical and functional requirements posed by the BTMS program. In order to test energy storage components and systems against these requirements, test procedures must be created. System usage scenarios are concurrently being developed with testing of baseline cells intended to illustrate their capabilities relative to a broad set of initial system assumptions. The results from these early performance tests and aging procedures, though only loosely framed by a baseline 1 MWh BTMS system supporting six 350kW DCFC units, will produce both slow and accelerated cycle-life aging information through a mix of empirical observations and modeling.
The facility described here within as well as associated documented Target Folder information is hypothetical in nature and provided only to serve as an example of the type and detail of information that should be collected to generate a thorough Target Folder.
The CABle ANAlysis (CABANA) portion of the EMPHASIS™ suite is designed specifically for the simulation of cable SGEMP. The code can be used to evaluate the response of a specific cable design to threat or to compare and minimize the relative response of difference designs. This document provides user-specific information to facilitate the application of the code to cables of interest.
The Unstructured Time-Domain ElectroMagnetics (UTDEM) portion of the EMPHASIS suite solves Maxwell's equations using finite-element techniques on unstructured meshes. This document provides user-specific information to facilitate the use of the code for applications of interest.
NNSA policy requires that personnel working in the Nuclear Security Enterprise (NSE) receive comprehensive training to be fully capable before they begin their work and that personnel receive ongoing training to maintain their capability and competence. However, the loss of experienced NSE staff through retirements and the influx of personnel who are inexperienced and untrained in nuclear weapons technology make these training requirements difficult to achieve. This paper presents an approach for developing and delivering a nuclear deterrent (ND) fundamentals curriculum to respond to these challenges. The training approach leverages existing material already used by Sandia National Laboratories in the ND training arena and proposes to deliver the material in an e-learning format as much as possible. The approach also seeks to maximize the amount of material to be delivered in an unclassified setting.
The supercritical CO2 (sCO2) Brayton Economics Tool (sBET) was developed to evaluate and perform sensitivity studies on recompression closed Brayton cycles (RCBCs). This integrated techno-economic tool calculates key system performance and levelized cost of energy (LCOE) based on user-defined input on key variables such as system size, recuperator effectiveness, turbine inlet temperature, etc. The goal of this integrated tool is to allow system designers to understand the tradeoffs associated with various key design decisions, such as recuperator effectiveness and overall system cost. This work includes a description of LCOE calculation methodology, component system cost models for turbomachinery and heat exchangers based on vendor quotes and published literature, and the results of several parameter studies to identify desirable system parameters.
Sandia has a history of testing supercritical CO2 Brayton Cycles to explore operation fundamentals and provide validation data for computer models. These systems have always had data acquisition and controls features. The Development Platform (DP) has been a flagship system for loop testing and operation but has been limited to manual control of many systems. Manual operation has increased operating complexity and reduced stability and repeatability. This work documents automated control development by linearizing otherwise non-linear valves, addition of closed-loop proportional-integral control software that has been tuned to the Sandia DP. It also describes testing of control methods that have improved test quality and reliability as shown in actual test data.
Four Hellma visible grade glass samples were irradiated at the following radiation doses: 0 rads Baseline; 100 — 200 Krads; 300 — 400 Krads; 1.0 — 1.1 Mrads; 3.0 — 3.1 Mrads; and, 10 — 10.1 Mrads. Note that exact irradiation values are still be calculated based on the TLD measured values but the range is expected to be close to what is listed above . A fifth sample was utilized as a control sample where it's transmission was measured with the other samples but this sample was never exposed to radiation.
This report was developed to help the U.S. Defense Threat Reduction Agency understand the radionuclide detection requirements necessary to establish air monitoring systems that can detect airborne radionuclide activity at levels that could warrant protective actions.. The report provides representative integrated air activity derived response levels that correspond to the U.S. Environmental Protection Agency's protective action guidelines for the Early Phase (0-96 h) following a release to the environment. Environmental releases from nuclear fallout, nuclear power plants, and radiological dispersal devices are considered.
A parallel, adaptive overlay grid procedure is proposed for use in generating all-hex meshes for stochastic (SVE) and representative (RVE) volume elements in computational materials modeling. The mesh generation process is outlined including several new advancements such as data filtering to improve mesh quality from voxelated and 3D image sources, improvements to the primal contouring method for constructing material interfaces and pillowing to improve mesh quality at boundaries. We show specific examples in crystal plasticity and syntactic foam modeling that have benefitted from the proposed mesh generation procedure and illustrate results of the procedure with several practical mesh examples.
The transport properties of porous geological media are of fundamental importance when modeling the migration of chemical and radiological species in subterranean systems. Due to their relatively high mobility, short-lived noble gas species are of particular interest as detection of these species at the surface is a tell-tale indicator of recent nuclear activity. However, determining the diffusivity of these species is challenging due to their inert and transparent nature, requiring chemically insensitive techniques, such as mass spectroscopy, to quantify noble gas concentrations. The work described herein details recent advances in the methodology for determining diffusivity on porous media and results obtained on samples relevant to the UNESE project.
Hydrogen Risk Assessment Models (HyRAM) is a software toolkit that provides a basis for quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM integrates validated, analytical models of hydrogen behavior, statistics, and a standardized QRA approach to generate useful, repeatable data for the safety analysis of various hydrogen systems. HyRAM is a software developed by Sandia National Laboratories for the U.S. Department of Energy. This document demonstrates how to use HyRAM to recreate a hydrogen system and obtain relevant data regarding potential risk. Specific examples are utilized throughout this document, providing detailed tutorials of HyRAM features with respect to hydrogen system safety analysis and risk assessment.
This Sandia National Laboratories, New Mexico Environmental Restoration Operations (ER) Consolidated Quarterly Report (ER Quarterly Report) fulfills all quarterly reporting requirements set forth in the Compliance Order on Consent. Table I-1 lists the six sites remaining in the corrective action process. This ER Quarterly Report presents activities and data as follows: SECTION I: Environmental Restoration Operations Consolidated Quarterly Report, January — March 2019 SECTION II: Because there is no perchlorate sampling collection to report this quarter, this edition of the ER Quarterly Report does not include any analysis of data in Section II "Perchlorate Screening Quarterly Groundwater Monitoring Report." SECTION III: Technical Area-V In-Situ Bioremediation Treatability Study Full-Scale Operation, January — March 2019.
Discharge Permit (DP)-1845 was issued by the New Mexico Environment (NMED) Ground Water Quality Bureau (GWQB) for discharges via up to three injection wells in a phased Treatability Study of in-situ bioremediation of groundwater at the Sandia National Laboratories, New Mexico, Technical Area-V Groundwater Area of Concern. This report fulfills the quarterly reporting requirements set forth in DP-1845, Section IV.B, Monitoring and Reporting. The reporting period is January 1 through March 31, 2019. All applicable terms and conditions were met for this reporting period. The report is due to NMED GWQB by August 1, 2019.
This report presents results of a study of the dielectric properties of several high explosive materials, including Composition B, C-4, Detasheet, Semtex 1A, Semtex 1H, and Semtex 10. The capacitance and dispersion of samples up to ten mm thick were measured at 24 and 65°C using a parallel plate test fixture. In this configuration, capacitance is proportional to the real component of the complex dielectric constant (or permittivity) of the material, while the dispersion is equal to the imaginary component of the dielectric constant divided by the real component. Measurements were performed at two temperatures to determine whether these dielectric properties might be used to monitor moderate temperature changes within these materials using an external fringing field capacitor. It was found that the real dielectric constant of the high explosives generally changed by only about 1% on heating from 24 to 65°C, and that the externally measured capacitance is therefore not a reliable parameter for monitoring temperature changes in these explosives. Temperature- based changes in the dispersion were often 20% or greater, and for several materials (e.g., Composition B, Detasheet) the temperature and dispersion showed good correlation as the temperature of the explosive was cycled up and down. It is thus possible that for some high explosives the externally measured dispersion is a useful parameter for monitoring temperature changes. However, other factors may limit the usefulness of this technique, including the need to have the plates of a fringing field capacitor in direct contact with the high explosive to obtain measurements, and the limited penetration depth of the fringing field into the explosive material.
In a recent paper, the authors proposed a general methodology for probabilistic learning on manifolds. The method was used to generate numerical samples that are statistically consistent with an existing dataset construed as a realization from a non-Gaussian random vector. The manifold structure is learned using diffusion manifolds and the statistical sample generation is accomplished using a projected Itô stochastic differential equation. This probabilistic learning approach has been extended to polynomial chaos representation of databases on manifolds and to probabilistic nonconvex constrained optimization with a fixed budget of function evaluations. The methodology introduces an isotropic-diffusion kernel with hyperparameter ε. Currently, ε is more or less arbitrarily chosen. In this paper, we propose a selection criterion for identifying an optimal value of ε, based on a maximum entropy argument. The result is a comprehensive, closed, probabilistic model for characterizing data sets with hidden constraints. This entropy argument ensures that out of all possible models, this is the one that is the most uncertain beyond any specified constraints, which is selected. Applications are presented for several databases.
Over the past few years, interest has rocketed in the use of wide bandgap devices for energy-efficiency applications such as the electric grid, vehicle electrification, and more-electric aircraft. Deployed in these situations, devices must have a high reliability. In fact, this attribute is so crucial that it is a primary gatingfactor, determining the rate at which these wide bandgap devices are being inserted into these system applications.
We study a setting where a group of agents, each receiving partially informative private observations, seek to collaboratively learn the true state (among a set of hypotheses) that explains their joint observation profiles over time. To solve this problem, we propose a distributed learning rule that differs fundamentally from existing approaches, in the sense that it does not employ any form of 'belief-averaging'. Specifically, every agent maintains a local belief on each hypothesis that is updated in a Bayesian manner without any network influence, and an actual belief that is updated (up to normalization) as the minimum of its own local belief and the actual beliefs of its neighbors. Under minimal requirements on the signal structures of the agents and the underlying communication graph, we establish consistency of the proposed belief update rule, i.e., we show that the actual beliefs of the agents asymptotically concentrate on the true state almost surely. As one of the key benefits of our approach, we show that our learning rule can be extended to scenarios that capture misbehavior on the part of certain agents in the network, modeled via the Byzantine adversary model. In particular, we prove that each non-adversarial agent can asymptotically learn the true state of the world almost surely, under appropriate conditions on the observation model and the network topology.
Hansen, Nils H.; Wang, Zhandong; Herbinet, Olivier; Battin-Leclerc, Frederique
The aim of this paper is to review recent progress in detection and quantification of hydroperoxides, and to understand their reaction kinetics in combustion environments. Hydroperoxides, characterized by an –OOH group, are ubiquitous in the atmospheric oxidation of volatile organic compounds (∼300 K), and in the liquid and gas phase oxidation of fuel components at elevated temperatures (∼400–1000 K). They are responsible for two-stage fuel ignition in internal combustion engines and they play an important role in the formation and evolution of secondary organic aerosols in the atmosphere. The introduction outlines the importance of hydroperoxide chemistry in combustion reaction processes. In addition to this main topic, the role of hydroperoxides in atmospheric and liquid phase oxidation chemistry is also introduced, for a more general perspective. The second part of this paper briefly reviews the mechanistic insights of hydroperoxide chemistry in combustion systems, including experimental detection of these reactive species before 2010. Since that time significant progress has been made by advanced diagnostic techniques like tunable synchrotron vacuum ultraviolet photoionization mass spectrometry and infrared cavity ring-down spectroscopy. The third chapter of this work summarizes progress in gas phase oxidation experiments to measure hydrogen peroxide, alkyl hydroperoxides, olefinic hydroperoxides, ketohydroperoxides, and more complex hydroperoxides that include as many as five oxygen atoms. The fourth section details recent advances in understanding the combustion chemistry of hydroperoxides, involving the formation of carboxylic acids and diones, as well as the development of oxidation models that include a third O2 addition reaction mechanism. Finally, challenges are discussed, and perspectives are offered regarding the future of accurately measuring molecule-specific hydroperoxide concentrations and understanding their respective reaction kinetics.
Mitra, Aritra; Richards, John R.; Bagchi, Saurabh; Sundaram, Shreyas
We study the problem of collaboratively estimating the state of a discrete-time LTI process by a network of sensor nodes interacting over a time-varying directed communication graph. Existing approaches to this problem either (i) make restrictive assumptions on the dynamical model, or (ii) make restrictive assumptions on the sequence of communication graphs, or (iii) require multiple consensus iterations between consecutive time-steps of the dynamics, or (iv) require higher-dimensional observers. In this paper, we develop a distributed observer that operates on a single time-scale, is of the same dimension as that of the state, and works under mild assumptions of joint observability of the sensing model, and joint strong-connectivity of the sequence of communication graphs. Our approach is based on the notion of a novel 'freshness-index' that keeps track of the age-of-information being diffused across the network. In particular, such indices enable nodes to reject stale information regarding the state of the system, and in turn, help achieve stability of the estimation error dynamics. Based on the proposed approach, the estimate of each node can be made to converge to the true state exponentially fast, at any desired convergence rate. In fact, we argue that finite-time convergence can also be achieved through a suitable selection of the observer gains. Our proof of convergence is self-contained, and employs simple arguments from linear system theory and graph theory.
The third Sandia Fracture Challenge highlighted the geometric and material uncertainties introduced by modern additive manufacturing techniques. Tasked with the challenge of predicting failure of a complex additively-manufactured geometry made of 316L stainless steel, we combined a rigorous material calibration scheme with a number of statistical assessments of problem uncertainties. Specifically, we used optimization techniques to calibrate a rate-dependent and anisotropic Hill plasticity model to represent material deformation coupled with a damage model driven by void growth and nucleation. Through targeted simulation studies we assessed the influence of internal voids and surface flaws on the specimens of interest in the challenge which guided our material modeling choices. Employing the Kolmogorov–Smirnov test statistic, we developed a representative suite of simulations to account for the geometric variability of test specimens and the variability introduced by material parameter uncertainty. This approach allowed the team to successfully predict the failure mode of the experimental test population as well as the global response with a high degree of accuracy.
Accurate distribution secondary low-voltage circuit models are needed to enhance overall distribution system operations and planning, including effective monitoring and coordination of distributed energy resources located in the secondary circuits. We present a full-scale demonstration across three real feeders of a computationally efficient approach for estimating the secondary circuit topologies and parameters using historical voltage and power measurements provided by smart meters. The method is validated against several secondary configurations, and compares favorably to satellite imagery and the utility secondary model. Feeder-wide results show how much parameters can vary from simple assumptions. Model sensitivities are tested, demonstrating only modest amounts of data and resolutions of data measurements are needed for accurate parameter and topology results.
A new potential-based TDIE formulation for dielectric regions is proposed that directly uses magnetic current densities as unknowns. This new formulation avoids the use of inconvenient integral operators that complicate the discretization, while also providing simpler computation of far-field results due to direct access to the magnetic current density. Appropriate marching-on-in-time discretization schemes are discussed so that stable results can be achieved at middle frequencies. Overall, this results in the improved performance of these new equations compared to previous formulations. The accuracy and stability of this new formulation is demonstrated through numerical results.
The discontinuous Petrov-Galerkin (DPG) methodology of Demkowicz and Gopalakrishnan guarantees the optimality of the finite element solution in a user-controllable energy norm, and provides several features supporting adaptive schemes. The approach provides stability automatically; there is no need for carefully derived numerical fluxes (as in DG schemes) or for mesh-dependent stabilization terms (as in stabilized methods). In this paper, we focus on features of Camellia that facilitate implementation of new DPG formulations; chief among these is a rich set of features in support of symbolic manipulation, which allow, e.g., bilinear formulations in the code to appear much as they would on paper. Many of these features are general in the sense that they can also be used in the implementation of other finite element formulations. In fact, because DPG's requirements are essentially a superset of those of other finite element methods, Camellia provides built-in support for most common methods. We believe, however, that the combination of an essentially "hands-free" finite element methodology as found in DPG with the rapid development features of Camellia are particularly winsome, so we focus on use cases in this class. In addition to the symbolic manipulation features mentioned above, Camellia offers support for one-irregular adaptive meshes in 1D, 2D, 3D, and space-time. It provides a geometric multigrid preconditioner particularly suited for DPG problems, and supports distributed parallel execution using MPI. For its load balancing and distributed data structures, Camellia relies on packages from the Trilinos project, which simplifies interfacing with other computational science packages. Camellia also allows loading of standard mesh formats through an interface with the MOAB package. Camellia includes support for static condensation to eliminate element-interior degrees of freedom locally, usually resulting in substantial reduction of the cost of the global problem. We include a discussion of the variational formulations built into Camellia, with references to those formulations in the literature, as well as an MPI performance study.
We describe an approach to predict failure in a complex, additively-manufactured stainless steel part as defined by the third Sandia Fracture Challenge. A viscoplastic internal state variable constitutive model was calibrated to fit experimental tension curves in order to capture plasticity, necking, and damage evolution leading to failure. Defects such as gas porosity and lack of fusion voids were represented by overlaying a synthetic porosity distribution onto the finite element mesh and computing the elementwise ratio between pore volume and element volume to initialize the damage internal state variables. These void volume fraction values were then used in a damage formulation accounting for growth of these existing voids, while new voids were allowed to nucleate based on a nucleation rule. Blind predictions of failure are compared to experimental results. The comparisons indicate that crack initiation and propagation were correctly predicted, and that an initial porosity field superimposed as higher initial damage may provide a path forward for capturing material strength uncertainty. The latter conclusion was supported by predicted crack face tortuosity beyond the usual mesh sensitivity and variability in predicted strain to failure; however, it bears further inquiry and a more conclusive result is pending compressive testing of challenge-built coupons to de-convolute materials behavior from the geometric influence of significant porosity.
Genedy, Moneeb; Matteo, Edward N.; Stenko, Michael; Stormont, John C.; Taha, Mahmoud R.
Microscale defects (microannuli) at the steel-cement and rock-cement interfaces are a major cause of failure in the integrity of wellbore systems. Microscale defects/microcracks as small as 30 μm are sufficient to create a significant leakage pathway for fluids. In this paper, the authors propose the use of nanomodified methyl methacrylate (NM-MMA) polymer as a seal material for 30-μm microcracks. Four materials were evaluated for their ability to serve as an effective seal material to seal 30-μm microcracks: microfine cement, epoxy, methyl methacrylate (MMA), and NM-MMA incorporating 0.5% by weight aluminum nanoparticles (ANPs). The seal materials' bond strengths with shale were investigated using push-out tests. In addition, the ability to flow fluid through the microcracks was investigated using sagittal microscopic images. Viscosity, surface tension, and contact angle measurements explain the superior ability of MMA seal materials to flow into very thin microcracks compared with other materials. Post-test analysis shows MMA repair materials are capable of completely filling the microcracks. In addition, incorporating ANPs in MMA resulted in significant improvement in seal material ductility. Dynamic mechanical analysis (DMA) showed that incorporating ANPs in MMA reduced the creep compliance and improved creep recovery of NM-MMA. X-ray diffraction (XRD) analysis shows that incorporating ANPs in MMA resin increases the degree of polymer crystallization, resulting in significant improvement in seal material ductility.
Koski, Jason K.; Krook, Nadia M.; Ford, Jamie; Yahata, Yoshikazu; Ohno, Kohji; Murray, Christopher B.; Frischknecht, Amalie F.; Composto, Russell J.; Riggleman, Robert A.
There are limited theoretically predicted phase diagrams for polymer nanocomposites (PNCs) because conventional modeling techniques are largely unable to predict the macroscale phase behavior of PNCs. Here, we show that recent field-based methods, including PNC field theory (PNC-FT) and theoretically informed Langevin dynamics, can be used to calculate phase diagrams for polymer-grafted nanoparticles (gNPs) incorporated into a polymer matrix. We calculate binodals for the transition from the miscible, dispersed phase to the macrophase separated state as functions of important experimental parameters, including the ratio of the matrix chain degree of polymerization (P) to the grafted chain degree of polymerization (N), the enthalpic repulsion between the matrix and grafted chains, the grafting density (σ), the size of the NPs, and the NP volume fraction. We demonstrate that thermal and polymer conformational fluctuations enhance the degree of phase separation in gNP-PNCs, a result of depletion interaction effects. We support this conclusion by experimentally investigating the phase separation of poly(methyl methacrylate)-grafted silica NPs in a polystyrene matrix as a function of P/N. The simulations only agree with experiments when fluctuations are included because fluctuations are needed to properly capture the depletion interactions between the gNPs. We clarify the role of conformational entropy in driving depletion interactions in PNCs and suggest that inconsistencies in the literature may be due to polymer chain length effects since conformational entropy increases with increasing chain length.
The third Sandia Fracture Challenge (SFC3) was a benchmark problem for comparing experimental and simulated ductile deformation and failure in an additively manufactured (AM) 316L stainless steel structure. One surprising observation from the SFC3 was the Challenge-geometry specimens had low variability in global load versus displacement behavior, attributed to the large stress-concentrating geometric features dominating the global behavior, rather than the AM voids that tend to significantly influence geometries with uniform cross-sections. This current study reinvestigates the damage and failure evolution of the Challenge-geometry specimens, utilizing interrupted tensile testing with micro-computed tomography (micro-CT) scans to monitor AM void and crack growth from a virgin state through complete failure. This study did not find a correlation between global load versus displacement behavior and AM void attributes, such as void volume, location, quantity, and relative size, which incidentally corroborates the observation from the SFC3. However, this study does show that the voids affect the local behavior of damage and failure. Surface defects (i.e. large voids located on the surface, far exceeding the nominal surface roughness) that were near the primary stress concentration affected the location of crack initiation in some cases, but they did not noticeably affect the global response. The fracture surfaces were a combination of classic ductile dimples and crack deviation from a more direct path favoring intersection with AM voids. Even though the AM voids promoted crack deviation, pre-test micro-CT scan statistics of the voids did not allow for conclusive predictions of preferred crack paths. This study is a first step towards investigating the importance of voids on the ductile failure of AM structures with stress concentrations.
An outline of a Bayesian source location framework for using seismic and acoustic observations is developed and tested on synthetic and real data. Seismic and acoustic phenomena are both commonly used in detection and location of a variety of natural or man-made events, such as volcanic eruptions, quarry blasts, and military exercises. Typically, seismic and acoustic observations have been utilized independently of each other. Here, we outline a Bayesian formulation for combining the two observations in a single estimate of the location and origin time. Using realistic estimates of uncertainty, we subsequently explore how combining the different observation types can benefit event location at local to near-regional distances. We apply the method to synthetic data and to real observations from a mining blast in Bingham Mine in Utah. Our findings suggest that, for relatively sparse or azimuthally limited observations, the relative strengths of the two different phenomenologies enable more precise joint-event localization than either seismic or infrasonic measurements alone.
The mounting reliance on computational simulations to predict all aspects of the lifecycle of a mechanical system, from fabrication to failure, has prompted the mechanics community to selfassess its abilities to perform those predictions. Benchmark problems in mechanics that compare simulations that use different computational approaches with experiments have sprung up lately, including the NIST AM-Bench looking at additively manufactured (AM) materials (https://www.nist.gov/ambench),the Contact-Mechanics Challenge (Miiser, 2017) considering adhesion between two nominally flat surfaces, Numisheet providing semiannual benchmarking activities in sheet metal forming (http://numisheet2018.org),and the Sandia Fracture Challenge (SFC) (Boyce, 2014 and Boyce, 2016) investigating ductile failure. The previous SFCs have shown that progress has been made in computations of ductile failure, but improvements still can be made, hence the third Sandia Fracture Challenge (SFC3), the subject of this Special Volume. The most recent installment of SFC is building on previous successes and tackling the difficult problem of fracture in an AM 316L stainless steel structure.
Proceedings - International Conference on Distributed Computing Systems
Logan, Jeremy; Mehta, Kshitij; Heber, Gerd; Klasky, Scott; Kurc, Tahsin; Podhorszki, Norbert; Widener, Patrick W.; Wolf, Matthew
Scientific data collections grow ever larger, both in terms of the size of individual data items and of the number and complexity of items. To use and manage them, it is important to directly address issues of robust and actionable provenance. We identify three key drivers as our focus: managing the size and complexity of metadata, lack of a priori information to match usage intents between publishers and consumers of data, and support for campaigns over collections of data driven by multi-disciplinary, collaborating teams. We introduce the Hoarde abstraction as an attempt to formalize a way of looking at collections of data to make them more tractable for later use. Hoarde leverages middleware and systems infrastructures for scientific and technical data management. Through the lens of a select group of challenging data usage scenarios, we discuss some of the aspects of implementation, usage, and forward portability of this new view on data management.
Sinuous antennas are capable of producing ultrawideband (UWB) radiation with polarization diversity. This capability makes the sinuous antenna an attractive candidate for UWB polarimetric radar applications. Additionally, the ability of the sinuous antenna to be implemented as a planar structure makes it a good fit for close-in sensing applications such as ground penetrating radar. However, recent literature has shown the sinuous antenna to suffer from resonances, which degrade performance. Such resonances produce late time ringing, which is particularly troubling for pulsed close-in sensing applications. The resonances occur in two forms: log-periodic resonances on the arms, and a resonance due to the sharp ends left by the outer truncation. A detailed investigation as to the correlation between the log-periodic resonances and the sinuous antenna design parameters indicates the resonances may be mitigated by selecting appropriate design parameters. In addition, a novel truncation method is proposed to remove the sharp end resonance. Both simulation and measured results are provided to support the developed sinuous antenna design guidance.
Many applications have growing demands for memory, particularly in the HPC space, making the memory system a potential bottleneck of next-generation computing systems. Sharing the memory system across processor sockets and nodes becomes a compelling argument given that memory technology is scaling at a slower rate than processor technology. Moreover, as many applications rely on shared data, e.g., graph applications and database workloads, having a large number of nodes accessing shared memory allows for efficient use of resources and avoids duplicating huge files, which can be infeasible for large graphs or scientific data. As new memory technologies come on the market, the flexibility of upgrading memory and system updates become major a concern, disaggregated memory systems where memory is shared across different computing nodes, e.g., System-on-Chip (SoC), is expected to become the most common design/architecture on memory-centric systems, e.g., The Machine project from HP Labs. However, due to the nature of such systems, different users and applications compete for the available memory bandwidth, which can lead to severe contention due to memory traffic from different SoCs. In this paper, we discuss the contention problem in disaggregated memory systems and suggest mechanisms to ensure memory fairness and enforce QoS. Our simulation results show that employing our proposed QoS techniques can speed up memory response time by up to 55%.
The present study introduces the coupled multiphysics model as part of the structural health monitoring (SHM) system. In particular, the Ultrasonic Guided Waves (UGWs) propagation is tracked in order to identify the damage to the structure. For this purpose, a multiphysics mathematical model is proposed. The model constitutes a monolithically coupled system of acoustic and elastic wave equations (WpFSI problem) where the wave signal displacement measurements are analyzed as the UGWs propagates in the solid, fluid and their interface. The ultimate goal of this paper is to explore and develop the efficient numerical solution of the WpFSI problem using the finite element method. A detailed description of the modeling framework and conditions that facilitate the coupling is provided. To couple the displacement-based acoustic wave equations for the isothermal fluid with elastic wave equations for the Saint Venant-Kirchhoff material model, the present study uses a monolithic solution algorithm. In particular, at each time step, wave equations are transformed to a fixed reference configuration via the arbitrary Lagrangian-Eulerian (ALE) mapping and automatically adopt the boundary conditions from the previous time step. The implementation is accomplished via the finite element library deal.II (Goll et al., 2017) based software toolbox DOPELIB (Bangerth et al., 2007) which provides modularized higher level algorithms. Beyond SHM systems, the model is relevant for problems from biomechanics and biomedicine, vibromechanics, poroelasticity as well as subsurface and porous media flow. The model developed here serves as a first step towards the on-line SHM system modeling, where structural dynamics are accounted for.
In this paper, we present alternate integer programming formulations for the multi-dimensional assignment problem, which is typically employed for multi-sensor fusion, multi-target tracking (MTT) or data association in general. The first formulation is the Axial Multidimensional Assignment Problem with Decomposable Costs (MDADC). The decomposable costs comes from the fact that there are only pairwise costs between stages or scans of a target tracking problem or corpuses of a data association context. The difficulty with this formulation is the large number of transitivity or triangularity constraints that ensure if entity A is associated to entity B and entity B is associated with entity C, then it must also be that entity A is associated to entity C. The second formulation uses both pairs and triplets of observations, which offer more accurate representation for kinematic tracking of targets. This formulation avoids the large number of transitivity constraints but significantly increases the number of variables due to triples. Solution to large-scale problems has alluded researchers and practitioners alike. We present solution methods based on Lagrangian Relaxation and massively parallel algorithms that are implemented on Graphics Processing Units (GPUs). We test the problem formulations and solution algorithms on MTT problems. The triples formulation tends to be more accurate for tracking measures and the MDADC solver can solve much larger problems in reasonable computational time.
The high performance computing industry is undergoing a period of substantial change. Not least because of fabrication and lithographic challenges in the manufacturing of next-generation processors. As such challenges mount, the industry is looking to generate higher performance from additional functionality in the micro-architecture space as well as a greater emphasis on efficiency in the design of networkon-chip resources and memory subsystems. Such variation in design opens opportunities for new entrants in the data center and server markets where varying compute-to-memory ratios can present end users with more efficient node designs for particular workloads. In this paper we compare the recently released Marvell ThunderX2 Arm processor - arguably the first high-performance computing capable Arm design available in the marketplace. We perform a set of micro-benchmarking and mini-application evaluation on the ThunderX2 comparing it with Intel's Haswell and Skylake Xeon server parts commonly used in contemporary HPC designs. Our findings show that no one processor performs the best across all benchmarks, but that the ThunderX2 excels in areas demanding high memory bandwidth due to the provisioning of more memory channels in its design. We conclude that the ThunderX2 is a serious contender in the HPC server segment and has the potential to offer supercomputing sites with a viable high-performance alternative to existing designs from established industry players.
A new potential-based TDIE formulation for dielectric regions is proposed that directly uses magnetic current densities as unknowns. This new formulation avoids the use of inconvenient integral operators that complicate the discretization, while also providing simpler computation of far-field results due to direct access to the magnetic current density. Appropriate marching-on-in-time discretization schemes are discussed so that stable results can be achieved at middle frequencies. Overall, this results in the improved performance of these new equations compared to previous formulations. The accuracy and stability of this new formulation is demonstrated through numerical results.
The ability to rapidly drill through diverse, layered materials can greatly enhance future mine-rescue operations, energy exploration, and underground operations. Pneumatic-percussive drilling holds great promise in this area due to its ability to penetrate very hard materials and potential for portability. Currently such systems require expert operators who require extensive training. We envision future applications where first responders who lack such training can still respond rapidly and safely perform operations. Automated techniques can reduce the dependence on expert operators while increasing efficiency and safety. However, current progress in this area is restricted by the difficulty controlling such systems and the complexity of modeling percussive rock-bit interactions. In this work we develop and experimentally validate a novel intelligent percussive drilling architecture that is tailored to autonomously operate in diverse, layered materials. Our approach combines low-level feedback control, machine learning-based material classification, and on-line optimization. Our experimental results demonstrate the effectiveness of this approach and illustrate the performance benefits over conventional methods.
Electromagnetic shields are usually employed to protect cables and other devices; however, these are generally not perfect, and may permit external magnetic and electric fields to penetrate into the interior regions of the cable, inducing unwanted current and voltages. The aim of this paper is to verify a circuit model tool with our previously proposed analytical model [1] for evaluating currents and voltages induced in the inner conductor of braided-shield cables. This circuit model will enable coupling between electromagnetic and circuit simulations.
This study examines the single-event upset and single-event latch-up susceptibility of the Xilinx 16nm FinFET Zynq UltraScale+ RFSoC FPGA in proton irradiation. Results for SEU in configuration memory, BlockRAM memory, and device SEL are given.
This study examines the single-event upset and single-event latch-up susceptibility of the Xilinx 16nm FinFET Zynq UltraScale+ RFSoC FPGA in proton irradiation. Results for SEU in configuration memory, BlockRAM memory, and device SEL are given.
As quantum theory matures, quantum applications that significantly depend on electromagnetic effects are becoming increasingly of interest to engineers. We discuss a number of diverse computations that are needed in the engineering design of various devices leveraging these quantum effects. In each case, the broadband knowledge of the classical dyadic Green's function of the problem being analyzed plays an important role. As a result, many of these applications require the extremely broadband solution of classical electromagnetic scattering problems in complex geometries to evaluate components of the dyadic Green's functions. This suggests that classical time domain computational electromagnetics methods will play an important role in the future of quantum applications.
Ryder, Kaitlyn L.; Ryder, Landen D.; Sternberg, Andrew L.; Kozub, John A.; Zhang, Enxia; Khachatrian, Ani; Buchner, Steven P.; Mcmorrow, Dale P.; Hales, Joel M.; Zhao, Yuanfu; Wang, Liang; Wang, Chuanmin; Weller, Robert A.; Schrimpf, Ronald D.; Weiss, Sharon M.; Reed, Robert A.; Black, Dolores; King, Michael P.
The insect brain is a great model system for low power electronics: Insects carry out multisensory integration and are able to change the way the process information, learn, and adapt to changes in their environment with a very limited power budget. This context-dependent processing allows them to implement multiple functionalities within the same network, as well as to minimize power consumption by having context-dependent gains in their first layers of input processing. The combination of low power consumption, adaptability and online learning, and robustness makes them particularly appealing for a number of space applications, from rovers and probes to satellites, all having to deal with the progressive degradation of their capabilities in remote environments. In this work, we explore architectures inspired in the insect brain capable of context-dependent processing and learning. Starting from algorithms, we have explored three different implementations: A spiking implementation in a neuromorphic chip, a custom implementation in an FPGA, and finally hybrid analog/digital implementations based on cross-bar arrays. For the latter, we found that the development of novel resistive materials is crucial in order to enhance the energy efficiency of analog devices while maintaining an adequate footprint. Metal-oxide nanocomposite materials, fabricated using ALD with processes compatible with semiconductor processing, are promising candidates to fill in that role.
Energy storage systems are flexible and controllable resources that can provide a number of services for the electric power grid. Many technologies are available, and corresponding models vary greatly in level of detail and tractability. In this work, we propose an adaptive optimal control and estimation approach for real-time dispatch of energy storage systems that neither requires accurate state-of-energy measurements nor knowledge of an accurate state-of-energy model. Specifically, we formulate an online optimization problem that simultaneously solves moving horizon estimation and model predictive control problems, which results in estimates of the state-of-energy, estimates of the charging and discharging efficiencies, and future dispatch signals. We present a numerical example in which the plant is a nonlinear, time-varying Lithium-ion battery model and show that our approach effectively estimates the state-of-energy and dispatches the system without accurate knowledge of the dynamics and in the presence of significant measurement noise.
Krishnamoorthy, Siddharth; Cutts, James A.; Komjathy, Attila; Pauken, Michael T.; Bowman, Daniel B.; Martire, Leo; Garcia, Raphael; Mimoun, David; Jackson, Jennifer M.