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At least 271 records · Page 15

Optical array for high-quality imaging in harsh environments

Methods and apparatus are disclosed for producing high quality images in uncontrolled or impaired environments. In some examples of the disclosed technology, groups of cameras for high dynamic range (HDR), polarization diversity, and optional other diversity modes are arranged to concurrently image a common scene. For example, in a vehicle checkpoint application, HDR provides discernment of dark objects inside a vehicle, while polarization diversity aids in rejecting glare. Spectral diversity, infrared imaging, and active illumination can be applied for better imaging through a windshield. Preprocessed single-camera images are registered and fused. Faces or other features of interest can be detected in the fused image and identified in a library. Impairments can include weather, insufficient or interfering lighting, shadows, reflections, window glass, occlusions, or moving objects.

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Premelting, Melting, and Degradation Properties of Molten Alkali Nitrates: LiNO{sub 3}, NaNO{sub 3}, KNO{sub 3}, and Binary NaNO{sub 3}-KNO{sub 3}

A simultaneous thermal analyzer (STA) was used to observe the transition and degradation events of LiNO{sub 3}, NaNO{sub 3}, KNO{sub 3}, and binary NaNO{sub 3}-KNO{sub 3} salts for potential use as phase change materials (PCMs) and heat transfer fluid (HTF). Samples were heated from 50 °C to 800 °C at 10 °C/min scanning rate in three atmospheres (argon, air, and oxygen) using an STA to observe decomposition behavior. Thermal stability increased for all salts at high partial pressure of O{sub 2} (P{sub O{sub 2}}= 1.0) compared to inert argon (P{sub O{sub 2}}= 0). O{sub 2}, N{sub 2}, NO, N{sub 2}O, and NO{sub 2} were main evolved gases during nitrate decomposition. NO and O{sub 2} started to evolve at approximately the same temperature after melting, indicating that primary and secondary decomposition reactions were concurrent and overlapping. The solid-solid transition, liquidus and solidus temperatures, heat of transition, heat of melting, and heat of solidification were obtained at various heating-cooling rates (1, 2, 4, 5, 6, 8, 10, and 15 °C/min) using an STA. At all heating-cooling rates, a small gap exists between liquidus and solidus temperatures for all samples due to the salts exhibiting supercooling phenomena. This study showed that the degradation point depends on the blanket atmosphere top of the molten salts and that heating rates have a minor effect on transition events (peaks height, peaks width, and transition enthalpies).

36 MATERIALS SCIENCE↗

CONCURRENT, CONDENSED STEIN VARIATIONAL GRADIENT DESCENT FOR UNCERTAINTY QUANTIFICATION OF NEURAL NETWORKS

In this work, we propose a Stein variational gradient descent (SVGD) method to concurrently sparsify, train, and provide uncertainty quantification (UQ) of a complexly parameterized model, such as a neural network (NN). It employs a graph reconciliation and condensation process to reduce complexity and increase similarity in the Stein ensemble of parameterizations. Therefore, the proposed concurrent, condensed SVGD (ccSVGD) method can provide UQ on parameters, not just outputs. Furthermore, the parameter reduction speeds up the convergence of the Stein gradient descent as it reduces the combinatorial complexity by aligning and differentiating the sensitivity to parameters. These properties are demonstrated with an illustrative example and an application to a mechanical response representation problem in solid mechanics.

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An in-situ neutron diffraction study of a multi-phase transformation and twinning-induced plasticity steel during cyclic loading

In-situ neutron diffraction during cyclic tension-compression loading (∼+3.5% to −2.8%) of a 17Mn-3Al-2Si-1Ni-0.06C steel that exhibits concurrent transformation and twinning -induced plasticity effects indicated a significant contribution of intragranular back stresses to the observed Bauschinger effect. Rietveld analysis revealed a higher rate of martensitic transformation during tension compared to compression. Throughout cycling, α′-martensite exhibited the highest phase strains such that it bears an increasing portion of the macroscopic load as its weight fraction evolves. On the other hand, the ε-martensite strain remained compressive as it accommodated most of the internal strains caused by the shape misfit associated with the γ→ε and/or ε→α′ transformations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Synthesis of Correct Digital Controller Models from Specifications by Model Transformation (21-0320)

The design of high consequence controllers (in weapons systems, autonomy, etc.) that do what they are supposed to do is a significant challenge. Testing simply does not come close to meeting the requirements for assurance. Today circuit designers at Sandia (and elsewhere) typically capture the core behavior of their components using state models in tools such as STATEFLOW. They then check that their models meet certain requirements (e.g. “The system bus must not deadlock” or “both traffic lights at an intersection must not be green at the same time”) using tools called model checkers. If the model checker returns “yes” then the property is guaranteed to be satisfied by the model. However, there are several drawbacks to this industry practice: (1) there is a lot of detail to get right, this is particularly challenging when there are multiple components requiring complex coordination (2) any errors returned by the model checker have to be traced back through the design and fixed, necessitating rework, (3) there are severe scalability problems with this approach, particularly when dealing with concurrency. All this places high demands on the designers who now face not only an accelerated schedule but also controllers of increasing complexity. This report describes a new and fundamentally different approach to the construction of safety-critical digital controllers. Instead of directly constructing a complete model and then trying to verify it, the designer can start with an initial abstract (think “sketch”) model plus the requirements, from which a correct concrete model is automatically synthesized. There is no need for post-hoc verification of required functional properties. Having tool to carry this out will significantly impact the nation’s ability to ensure the safety of high-consequence digital systems. The approach has been implemented in a prototype tool, along with a suite of examples, including ones that reflect actual problems faced by designers. Our approach operates on a variant of Statecharts developed at Sandia called Qspecs. Statecharts are a widely used formalism for developing concurrent reactive systems, supporting scalability through allowing state models containing composite states, which are the serial or parallel composition of substates which can themselves contain statecharts. Statecharts enable an incremental style of development, in which states are progressively refined to incorporate greater detail in an incremental model of software development. Our approach formulates a set of constraints from the structure of the models and the requirements and propagates these constraints to a fixpoint. The solution to the constraints is an inductive invariant along with guards on the transitions. We also show how our approach extends to implementation refinement, decomposition, composition, and elaboration. We currently handle safety requirements written in LTL (Linear Temporal Logic)

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Concurrent Uranium Overmass and Hydraulic Fluid Leak

In the Spring of 2017, the Y-12 National Security Complex had a NCS operational event involving hydraulic fluid leaking into a glovebox containing fissile material. The hydraulic fluid intermixed with fissile material in the glovebox but remained in a safe slab-like configuration. Unknown at the time, a large enough mass of uranium to support a moderated nuclear criticality accident resided below the glovebox floor in an unfavorable volume sand separator system. Thanks to the operator following procedures and shutting down the hydraulic pump supplying the jolter, a potential accident was adverted. As a result of the event, significant physical modifications were made to the process to enhance safety. Additionally, changes were made in how the materials in the glovebox are processed in order to prevent liquid intrusion and significant uranium accumulation in the sand separator system.

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Parametric Model of Debris Penetration Through Sump Strainers with Concurrent Filtration and Shedding

Two primary debris fates are of key interest to the risk-informed resolution analysis: (1) accumulation on the primary sump strainers with corresponding head loss, and (2) partial penetration of debris through the strainers with subsequent accumulation on fuel channel screens in the lower plenum. Accumulation on the core can impede flow, potentially causing local excessive heating and potentially limiting mixing to the point that boron precipitation can occur. Two opportunities exist for diverting debris away from the core: (1) a fraction of the ECCS recirculation flow feeds containment spray systems directly from the common header, (2) a fraction of debris-laden flow can bypass the core and proceed directly to the break without accumulating debris on the fuel assembly screen. Both of these pathways extend the time necessary to build debris levels of concern on either the strainers or the fuel assemblies.

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AI-enhanced Codesign for Next-Generation Neuromorphic Circuits and Systems

This report details work that was completed to address the Fiscal Year 2022 Advanced Science and Technology (AS&T) Laboratory Directed Research and Development (LDRD) call for “AI-enhanced Co-Design of Next Generation Microelectronics.” This project required concurrent contributions from the fields of 1) materials science, 2) devices and circuits, 3) physics of computing, and 4) algorithms and system architectures. During this project, we developed AI-enhanced circuit design methods that relied on reinforcement learning and evolutionary algorithms. The AI-enhanced design methods were tested on neuromorphic circuit design problems that have real-world applications related to Sandia’s mission needs. The developed methods enable the design of circuits, including circuits that are built from emerging devices, and they were also extended to enable novel device discovery. We expect that these AI-enhanced design methods will accelerate progress towards developing next-generation, high-performance neuromorphic computing systems.

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A Greenhouse-Gas Information System: Monitoring and Validating Emissions Reporting and Mitigation

Current GHG-mitigating regimes, whether internationally agreed or self-imposed, rely on the aggregation of self-reported data, with limited checks for consistency and accuracy, for monitoring. As nations commit to more stringent GHG emissions-mitigation actions and as economic rewards or penalties are attached to emission levels, self-reported data will require independent confirmation that they are accurate and reliable, if they are to provide the basis for critical choices and actions that may be required. Supporting emissions-mitigation efforts and agreements, as well as monitoring energy- and fossil-fuel intensive national and global activities would be best achieved by a process of: (1) monitoring of emissions and emission-mitigation actions, based, in part, on, (2) (self-) reporting of pertinent bottom-up inventory data, (3) verification that reported data derive from and are consistent with agreed-upon processes and procedures, and (4) validation that reported emissions and emissions-mitigation action data are correct, based on independent measurements (top-down) derived from a suite of sensors in space, air, land, and, possibly, sea, used to deduce and attribute anthropogenic emissions. These data would be assessed and used to deduce and attribute measured GHG concentrations to anthropogenic emissions, attributed geographically and, to the extent possible, by economic sector. The validation element is needed to provide independent assurance that emissions are in accord with reported values, and should be considered as an important addition to the accepted MRV process, leading to a MRV&V process. This study and report focus on attributes of a greenhouse-gas information system (GHGIS) needed to support MRV&V needs. These needs set the function of such a system apart from scientific/research monitoring of GHGs and carbon-cycle systems, and include (not exclusively): the need for a GHGIS that is operational, as required for decision-support; the need for a system that meets specifications derived from imposed requirements; the need for rigorous calibration, verification, and validation (CV&V) standards, processes, and records for all measurement and modeling/data-inversion data; the need to develop and adopt an uncertainty-quantification (UQ) regimen for all measurement and modeling data; and the requirement that GHGIS products can be subjected to third-party questioning and scientific scrutiny. This report examines and assesses presently available capabilities that could contribute to a future GHGIS. These capabilities include sensors and measurement technologies; data analysis and data uncertainty quantification (UQ) practices and methods; and model-based data-inversion practices, methods, and their associated UQ. The report further examines the need for traceable calibration, verification, and validation processes and attached metadata; differences between present science-/research-oriented needs and those that would be required for an operational GHGIS; the development, operation, and maintenance of a GHGIS missions-operations center (GMOC); and the complex systems engineering and integration that would be required to develop, operate, and evolve a future GHGIS. Present monitoring systems would be heavily relied on in any GHGIS implementation at the outset and would likely continue to provide valuable future contributions to GHGIS. However, present monitoring systems were developed to serve science/research purposes. This study concludes that no component or capability presently available is at the level of technological maturity and readiness required for implementation in an operational GHGIS today. However, purpose-designed and -built components could be developed and implemented in support of a future GHGIS. The study concludes that it is possible to develop and provide a capability-driven prototype GHGIS, as part of a Phase-1 effort, within three years from project-funding start, that would make use of and integrate existing sensing and system capabilities. As part of a Phase-2 effort, a requirements-driven, operational GHGIS could be developed, within ten years from project funding start. That schedule is driven by the development and long lead-times for some system components. The two efforts would be focused on different deliverables but could commence concurrently, to save time, if that was deemed desirable. We note that, developing and supporting an operational GHGIS will require a new approach and management, sustained funding and other support, as well as technical advances and development of purpose-built components that meet the requisite specifications. A functioning GHGIS will provide the basis for reasoned choices on how best to respond to rising GHG levels, especially when proposed U.S. actions are compared with or conditioned on the actions of other nations.

54 ENVIRONMENTAL SCIENCES↗

A Cast of Thousands: How the IDEAS Productivity Project Has Advanced Software Productivity and Sustainability

Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. Department of Energy’s Exascale Computing Project have been tackling new frontiers in modeling, simulation, and analysis by exploiting unprecedented exascale computing capabilities—building an advanced software ecosystem that supports next-generation applications and addresses disruptive changes in computer architectures. However, concerns are growing about the productivity of the developers of scientific software. Members of the Interoperable Design of Extreme-scale Application Software project serve as catalysts to address these challenges through fostering software communities, incubating and curating methodologies and resources, and disseminating knowledge to advance developer productivity and software sustainability. This article discusses how these synergistic activities are advancing scientific discovery—mitigating technical risks by building a firmer foundation for reproducible, sustainable science at all scales of computing, from laptops to clusters to exascale and beyond.

97 MATHEMATICS AND COMPUTING↗

The Use Of Computational Human Performance Modeling As Task Analysis Tool

During a review of the Advanced Test Reactor safety basis at the Idaho National Laboratory, human factors engineers identified ergonomic and human reliability risks involving the inadvertent exposure of a fuel element to the air during manual fuel movement and inspection in the canal. There were clear indications that these risks increased the probability of human error and possible severe physical outcomes to the operator. In response to this concern, a detailed study was conducted to determine the probability of the inadvertent exposure of a fuel element. Due to practical and safety constraints, the task network analysis technique was employed to study the work procedures at the canal. Discrete-event simulation software was used to model the entire procedure as well as the salient physical attributes of the task environment, such as distances walked, the effect of dropped tools, the effect of hazardous body postures, and physical exertion due to strenuous tool handling. The model also allowed analysis of the effect of cognitive processes such as visual perception demands, auditory information and verbal communication. The model made it possible to obtain reliable predictions of operator performance and workload estimates. It was also found that operator workload as well as the probability of human error in the fuel inspection and transfer task were influenced by the concurrent nature of certain phases of the task and the associated demand on cognitive and physical resources. More importantly, it was possible to determine with reasonable accuracy the stages as well as physical locations in the fuel handling task where operators would be most at risk of losing their balance and falling into the canal. The model also provided sufficient information for a human reliability analysis that indicated that the postulated fuel exposure accident was less than credible.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data Efficiency Assessment of Generative Adversarial Networks for Critical Heat Flux Synthetic Data Generation

This study investigates the application of generative artificial intelligence techniques, particularly conditional generative adversarial networks (cGAN), in real-world engineering contexts, with a specific focus on synthetic data generation for critical heat flux (CHF). Utilizing a dataset comprising more than 20,000 real experimental CHF measurements, we conduct a series of experiments to examine cGAN’s behavior. These experiments encompass varying sizes of the training dataset, training cGAN on data from diverse experimental sources to generate new data on unseen experimental setups, and assessing the impact of excluding various input features on cGAN’s data generation accuracy. Our findings underscore the pronounced data dependency of cGAN for reliable performance, with decreased efficacy observed with smaller training dataset sizes. Notably, cGAN exhibits varying performance when trained on data from different experiments, with superior predictive capabilities observed for certain experiment sources compared to others. For instance, when cGAN was trained on data from Smolin et al.’s experiments or Zenkevich et al., it exhibited relatively good performance in generating the data from Becker et al., Kirillov et al., and Alekseev et al. experiments. In contrast, when trained with Alekseev et al.’s data and tasked with generating other experimental setups, cGAN showed notably poor performance. In both scenarios, cGAN’s performance was inferior compared to training on samples from all experiments concurrently. A feature importance analysis highlights the significant influence of parameters such as mass flux and heated length on accurate CHF generation, while other parameters like diameter and pressure have less impact. Inlet temperature is identified as a moderating factor by cGAN.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Passive techniques for long-term reactor cooling

In a pressurized water reactor (PWR), emergency core cooling (ECC) responds to depressurization due to a vessel penetration break at the top of the pressure vessel by draining water from a body of water through an injection line into the pressure vessel. A barrier operates concurrently with the ECC to suppress flow of liquid water from the pressure vessel out the vessel penetration break. The barrier may comprise one or more of: (1) an injection line extension passing through the central riser to drain water into the central riser; (2) openings in a lower portion of a central riser to shunt some upward flow from the central riser into a lower portion of the downcomer annulus; and (3) a surge line providing fluid communication between a pressurizer volume at the top of the pressure vessel and the remainder of the pressure vessel which directs water outboard toward the downcomer annulus.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mixed Arlequin method for multiscale poromechanics problems: Mixed Arlequin method for multiscale poromechanics problems

An Arlequin poromechanics model is introduced to simulate the hydro-mechanical coupling effects of fluid-infiltrated porous media across different spatial scales within a concurrent computational framework. A two-field poromechanics problem is first recast as the twofold saddle point of an incremental energy functional. We then introduce Lagrange multipliers and compatibility energy functionals to enforce the weak compatibility of hydro-mechanical responses in the overlapped domain. Here, to examine the numerical stability of this hydro-mechanical Arlequin model, we derive a necessary condition for stability, the twofold inf–sup condition for multi-field problems, and establish a modified inf–sup test formulated in the product space of the solution field. We verify the implementation of the Arlequin poromechanics model through benchmark problems covering the entire range of drainage conditions. Finally, through these numerical examples, we demonstrate the performance, robustness, and numerical stability of the Arlequin poromechanics model.

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Scheduling of Collaborative Sequential Compressed Sensing Over Wide Spectrum Band

The cognitive radio (CR) technology holds promise to significantly increase spectrum availability and wireless network capacity. With more spectrum bands opened up for CR use, it is critical yet challenging to perform efficient wideband sensing. In this work, we propose an integrated sequential wideband sensing scheduling framework that concurrently exploits sequential detection and compressed sensing (CS) techniques for more accurate and lower-cost spectrum sensing. First, to ensure more timely detection without incurring high overhead involved in periodic recovery of CS signals, we propose smart scheduling of a CS-based sequential wideband detection scheme to effectively detect the PU activities in the wideband of interest. Second, to further help users under severe channel conditions identify the occupied sub-channels, we develop two collaborative strategies, namely, joint reconstruction of the signals among neighboring users and wideband sensing-map fusion. Third, to achieve robust wideband sensing, we propose the use of anomaly detection in our framework. Lastly, extensive simulations demonstrate that our approach outperforms peer schemes significantly in terms of sensing delay, accuracy and overhead.

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Evaluation of Additively Manufactured Monolithic SiC and SiC-Matrix Ceramic Matrix Composites for Concentrating Solar Receiver Applications - Fabrication and Testing of Receiver Design Feature Specimens in a Simulating Lab Test via Laser Heating

Increasing operating temperatures of solar receivers is paramount to the efficiency of concentrated solar thermal (CST) and solar power (CSP) systems. Owing to its high temperature stability combined with excellent thermal and optical properties, SiC has been the material of choice for application in high-temperature solar receivers. We report the results of our study of the effective heat transfer characteristics of several candidate SiC structure motifs, or feature geometries, which are fabricated via additive manufacturing. The SiC structure motifs studied include different permutations of three-dimensional periodic lattices and defined shapes. A solar-thermal simulating laboratory test setup is constructed using a 4kW CO2 laser system with beam shaping optics to apply concurrent radiative heating power on one face of 2”-diameter cylindrical feature specimens, representing the structure motifs of interest for receiver element design, while flowing through the sample as heat transfer fluid. Using the test setup, simulative test conditions representative of a concentrated solar flux of up to ~2000 suns could be achieved in the lab tests under varying air flow through the test structure. A simple 1D numerical analysis scheme is developed to extract an effective or compound heat transfer coefficient representative of the test structure under steady-state heat flow conditions. The test results and their use to guide the selection and optimization of SiC material and structure motifs for the receiver element design fabrication are discussed.

14 SOLAR ENERGY↗

Segregation-affected yielding and stability in nanotwinned silver by microalloying

Small-scale mechanics of solute atom segregation and incipient plasticity in nanotwinned Ag containing trace concentrations of Cu were studied by using large-scale hybrid Monte-Carlo and molecular-dynamic simulations. It is found that solute Cu atoms are segregated concurrently to grain boundaries and intrinsic twin-boundary kink-step defects during thermal annealing. Low Cu dopant contents below 1 at. % are predicted to substantially increase twin stability in nanotwinned Ag, accompanied with a pronounced rise in yield strength at 300 K. Incipient plasticity is associated with kink-step migration, grain-boundary sliding, and dislocation nucleation from grain boundaries and twin-boundary defects, which are affected by doping. Cu-dependent yield strengthening in doped nanotwinned Ag is shown to correlate with the critical stress required to initiate crystal slip emitted from grain boundaries and twin-boundary defects. Finally, these findings provide fundamental insight into the roles of twin-boundary imperfections on plastic yielding, and offer new clues to further extend the extraordinary stability and strength of nanotwinned metals by microalloying.

36 MATERIALS SCIENCE↗

Highly efficient removal and sequestration of Cr(VI) in confined MoS 2 interlayer Nanochannels: Performance and mechanism

Environmental contamination by Cr(VI) is of particular concern because of its severe toxicity and high mobility. In this study, we employed two-dimensional MoS 2 nanosheets in the removal of Cr(VI), with an emphasis on revealing the removal mechanisms, and how the compositional and structural uniqueness of 2D MoS 2 nanomaterials intrinsically impact the Cr removal efficiency. Through batch experiments with dispersed nanosheets, we found that MoS 2 nanosheets exhibited a high Cr(VI) removal capacity at ~1100 mg/g via a phase-dependent mechanism. Particularly, the 1T polymorph in the MoS 2 nanosheets removed Cr(VI) through a redox-reaction mechanism, which was different from the adsorptive removal of Cr(VI) by MoS 2 reported previously, highlighting the compositional effects on the removal mechanism and performance. More importantly, the reduced product Cr(III) was concurrently removed via precipitation and adsorption onto the MoS 2 nanosheets, which could avoid the additional pH-elevation step that is typically needed in the conventional treatment. The unique 2D flake-like structure of MoS 2 nanosheets enabled the formation of aligned and ion-accessible nanochannels, where Cr(VI) species were accommodated, reduced and sequestered. The irreversible shrinking of the nanochannels under drying modified the interior of the layer-stacked structure into confined compartments preventing the release and re-oxidation of the immobilized Cr(III). In conclusion, the compiled results highlight the effects of MoS 2 composition and structure on the Cr removal efficiency and mechanism, which has substantial implications on future studies tailoring these unique features of 2D nanomaterials for various remediation scenarios.

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