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At least 91 records · Page 5

Advancing Multi-Hazard Risk and Safety Considerations for Aging Nuclear Facilities (Revision 1)

This project will demonstrate a multi-hazard time-dependent probabilistic risk assessment (PRA) approach for nuclear facilities considering aging-related deterioration of structures. A generic pressurized water reactor (PWR) reactor subjected to seismic mainshock-aftershock sequences considering the aging of the containment structure will be used as a case study to demonstrate the multi-hazard PRA approach. Using advanced modeling and simulation, seismic mainshock-aftershock fragility functions will be simulated for the containment structure considering aging effects. A multi-hazard PRA model for a generic PWR reactor will be built to quantify the multi-hazard core damage frequency (CDF) and large early release frequency (LERF) with explicit time-dependent modeling of event sequences. To date, the cascading impacts of multi-hazards are not adequately accounted for in the PRA models for nuclear facilities. In addition, for both initial and periodic evaluation of facilities to withstand natural phenomena hazards (NPH), deterioration of the SSCs due to aging and other effects is not adequately considered. By advancing multi-hazard considerations accounting for aging effects, this project will contribute to improved understanding of the safety of aging nuclear facilities. Project outcomes such as the multi-hazard CDF and LERF will also allow facility owners to optimize upgrade and retrofit protocols. This project is divided into two components: (1) advanced modeling and simulations; and (2) multi-hazard PRA. For the first component, Idaho National Laboratory’s (INL) Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) and BlackBear codes will be used to simulate the seismic response and damage of a containment structure under cascading mainshock-aftershock sequences with aging effects. Uncertainties related to the seismic inputs, material parameters, and environmental factors such as temperature and humidity will be identified and propagated to the fragility functions. These fragility functions, which consider aging effects, will be time dependent. The second component will take the fragility information from the first component to build a multi-hazard time-dependent PRA model starting from a generic PWR model to evaluate the multi-hazard CDF and LERF and characterize the associated consequences. For this component, OpenPRA Web Application and SAPHIRE code will be used. Events such as the Fukushima Daiichi accident have highlighted the importance of considering the cascading impacts of multi-hazards for PRA. Moreover, many of the reactors in the current nuclear fleet in the United States (US) are already operating well beyond their initially planned design life, and applications for further extensions to operating licenses are being considered. Therefore, considering multi-hazard effects and aging deterioration in the NPH risk assessment process will contribute to the safety of both existing and future nuclear facilities. Outcomes of this project will thus directly benefit the standards DOE-STD-1020-16 and DOE-HDBK-1224-18.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Elucidating and Mitigating High-Voltage Degradation Cascades in Cobalt-Free LiNiO 2 Lithium-Ion Battery Cathodes

LiNiO 2 (LNO) is a promising cathode material for next-generation Li-ion batteries due to its exceptionally high capacity and cobalt-free composition that enables more sustainable and ethical large-scale manufacturing. However, its poor cycle life at high operating voltages over 4.1 V impedes its practical use, thus motivating efforts to elucidate and mitigate LiNiO 2 degradation mechanisms at high states of charge. Here, a multiscale exploration of high-voltage degradation cascades associated with oxygen stacking chemistry in cobalt-free LiNiO 2 , is presented. In this work, lattice oxygen loss is found to play a critical role in the local O3–O1 stacking transition at high states of charge, which subsequently leads to Ni-ion migration and irreversible stacking faults during cycling. This undesirable atomic-scale structural evolution accelerates microscale electrochemical creep, cracking, and even bending of layers, ultimately resulting in macroscopic mechanical degradation of LNO particles. By employing a graphene-based hermetic surface coating, oxygen loss is attenuated in LNO at high states of charge, which suppresses the initiation of the degradation cascade and thus substantially improves the high-voltage capacity retention of LNO. Overall, this study provides mechanistic insight into the high-voltage degradation of LNO, which will inform ongoing efforts to employ cobalt-free cathodes in Li-ion battery technology.

25 ENERGY STORAGE↗

Pervasive alterations to snow-dominated ecosystem functions under climate change

Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. So our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.

54 ENVIRONMENTAL SCIENCES↗

Morphological Processing of Ultraviolet Emissions of Electrical Corona Discharge for Analysis and Diagnostic Use

Electron cascades from electrical discharge produce secondary emissions from atmospheric plasma in the ultraviolet band. For a single point of discharge, these emissions exhibit a stereotypical discharge morphology, with latent information about the discharge location. Morphological processing can uncover the location and therefore can have diagnostic utility.

Schubert, Matthew R.↗

The helical decomposition and the instability assumption

Direct numerical simulations show that the triadic transfer function T(k,p,q) peaks sharply when q (or p) is much smaller than k. The triadic transfer function T(k,p,q) gives the rate of energy input into wave number k from all interactions with modes of wave number p and q, where k, p, q form a triangle. This observation was thought to suggest that energy is cascaded downscale through non-local interactions with local transfer and that there was a strong connection between large and small scales. Both suggestions were in contradiction with the classical Kolmogorov picture of the energy cascade. The helical decomposition was found useful in distinguishing between kinematically independent interactions. That analysis has gone beyond the question of non-local interaction with local transfer. In particular, an assumption about the statistical direction of triadic energy transfer in any kinematically independent interaction was introduced (the instability assumption). That assumption is not necessary for the conclusions about non-local interactions with local transfer recalled above. In the case of turbulence under rapid rotation, the instability assumption leads to the prediction that energy is transferred in spectral space from the poles of the rotation axis toward the equator. The instability assumption is thought to be of general validity for any type of triad interactions (e.g. internal waves). The helical decomposition and the instability assumption offer detailed information about the homogeneous statistical dynamics of the Navier-Stokes equations. The objective was to explore the validity of the instability assumption and to study the contributions of the various types of helical interactions to the energy cascade and the subgrid-scale eddy-viscosity. This was done in the context of spectral closures of the Direct Interaction or Quasi-Normal type.

Waleffe, Fabian A.↗

Performance of an optical relay satellite using Reed-Solomon coding over a cascaded optical PPM and BPSK channel

The nature of the optical/microwave interface aboard the relay satellite is considered. To allow for the maximum system flexibility, without overburdening either the optical or RF channel, demodulating the optical on board the relay satellite but leaving the optical channel decoding to be performed at the ground station is examined. The occurrence of erasures in the optical channel is treated. A hard decision on the erasure (i.e., the relay selecting a symbol at random in case of erasure occurrence) seriously degrades the performance of the overall system. Coding the erasure occurrences at the relay and transmitting this information via an extra bit to the ground station where it can be used by the decoder is suggested. Many examples with varying bit/photon energy efficiency and for the noisy and noiseless optical channel are considered. It is shown that coding the erasure occurrences dramatically improves the performance of the cascaded channel relative to the case of hard decision on the erasure by the relay.

Divsalar, D.↗

Diffractive optical computing in free space

Abstract Structured optical materials create new computing paradigms using photons, with transformative impact on various fields, including machine learning, computer vision, imaging, telecommunications, and sensing. This Perspective sheds light on the potential of free-space optical systems based on engineered surfaces for advancing optical computing. Manipulating light in unprecedented ways, emerging structured surfaces enable all-optical implementation of various mathematical functions and machine learning tasks. Diffractive networks, in particular, bring deep-learning principles into the design and operation of free-space optical systems to create new functionalities. Metasurfaces consisting of deeply subwavelength units are achieving exotic optical responses that provide independent control over different properties of light and can bring major advances in computational throughput and data-transfer bandwidth of free-space optical processors. Unlike integrated photonics-based optoelectronic systems that demand preprocessed inputs, free-space optical processors have direct access to all the optical degrees of freedom that carry information about an input scene/object without needing digital recovery or preprocessing of information. To realize the full potential of free-space optical computing architectures, diffractive surfaces and metasurfaces need to advance symbiotically and co-evolve in their designs, 3D fabrication/integration, cascadability, and computing accuracy to serve the needs of next-generation machine vision, computational imaging, mathematical computing, and telecommunication technologies.

36 MATERIALS SCIENCE↗

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology↗

A resilient network recovery framework against cascading failures with deep graph learning

Because of the increasing importance and dependencies of infrastructure networks and the potential for massive cascading failures in real-world network systems, maintenance optimization to effectively reduce system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. In this work, a new recovery framework was developed to rapidly identify important system components for maintenance to improve network resilience against cascading failures. Here this work provides distinct advantages to determine an optimal maintenance priority by combining real-time network structure importance with other maintenance prioritization based on customer preference. This approach adopts structural graph embedding and deep reinforcement learning to extract real-time network topology information (such as minimum vertex cover) to update the maintenance priority during the recovery process. Based on the case studies on synthetic networks and a US airport network, the proposed recovery framework with real-time network topology awareness shows better performance than other maintenance prioritization strategies regarding resilience enhancement. This work improves the understanding of how the changing network structure influences maintenance effects. It also provides insights of the practical usefulness of advanced deep learning on helping optimal maintenance prioritization to effectively reduce the intensity and extent of cascading failures.

42 ENGINEERING↗

Measuring forest landscape patterns in the Cascade Range of Oregon, USA

This paper describes the use of a set of spatial statistics to quantify the landscape pattern caused by the patchwork of clearcuts made over a 15-year period in the western Cascades of Oregon. Fifteen areas were selected at random to represent a diversity of landscape fragmentation patterns. Managed forest stands (patches) were digitized and analyzed to produce both tabular and mapped information describing patch size, shape, abundance and spacing, and matrix characteristics of a given area. In addition, a GIS fragmentation index was developed which was found to be sensitive to patch abundance and to the spatial distribution of patches. Use of the GIS-derived index provides an automated method of determining the level of forest fragmentation and can be used to facilitate spatial analysis of the landscape for later coordination with field and remotely sensed data. A comparison of the spatial statistics calculated for the two years indicates an increase in forest fragmentation as characterized by an increase in mean patch abundance and a decrease in interpatch distance, amount of interior natural forest habitat, and the GIS fragmentation index. Such statistics capable of quantifying patch shape and spatial distribution may prove important in the evaluation of the changing character of interior and edge habitats for wildlife.

Ripple, William J.↗

Molecular dynamics investigation of radiation damage in semiconductors

Results of a molecular dynamics investigation of the effects of radiation damage on the crystallographic structure of semiconductors are reported. Particular cosiderastion is given to the formation of point defects and small defect complexes in silicon at the end of a radiation-damage cascade. The calculations described make use of the equivalent crystal theory of Smith and Banerjea (1988). Results on the existence of an atomic displacement threshold, the defect formation energy, and some crystallographic information on the defects observed are reported.

Good, Brian S.↗

Design of Timer Circuit for Dynamic Data System

The Branch That I work in is in the Aero Electronic Test Branch, which is part of the Research and Testing Division. The Aero Electronic Test Branch deals with electronic control and instrumentation systems. This branch supports the research and test study of wind tunnels such as the l0x10,9x15, and 8x6. Wind tunnels are used in research to test certain parts of a jet, plane, shuttle or any other flying object in certain test conditions. My assignment is to design a programmable trigger circuit on a 19 standard rack mount that will allow the circuit to latch and hold for a predefined amount of time entered by the user when receiving a signal. It should then re-arm itself within 0.25 seconds after the time is finished. The time should be able to be seen on a display showing the time entered. The time range has to be from 0-600 seconds in 0.01 second increments (600.00). From the information given, counters will be needed to design and build this circuit. A counter, in it s simplest form, is a group of flip flops that can temporarily store bits of information put into the circuit. They can be constructed in many different ways, such as in 4 flip flops (4-bit counter) or 8 flip flops and even higher. Counters are usually cascaded with other counters to reach higher bits, such as 16 or 24 bit counters. The application in which I will use the counters will be to count down from any programmable number that I input either by a keyboard or a thumbwheel. Also, I will use counters that will be used specifically as a frequency divider to divide the pulses that enter the circuit through an input signal from a crystal clock. The pulses will need to be divided so that it will function as a 100Hz clock putting out 100 pulses per second. A switch will be used to load my inputs in and more than likely a button also so that I can stop and hold the count at any point of time. I will use 5 BCD up/down programmable counters, and a certain amount (depending on what kind of "divide by N" counter I use) of frequency dividing counters for the assignment. After the design is carefully made, a task order will be written and then given to the manufacturer to create a rack mount circuit board that will match my specifications given. The applications in which this design will be used for is in the use of the six-component balance signal conditioner for measurement and electronic system control. It can be used as a timer system for the balance signal conditioner in which it does numerous tests for the Wind tunnel research, in which a preset time can be set for how long it performs its tests. Specifically, my design should be applied to the balance signal conditioner used for the 8x6 wind tunnel research. Hopefully this design should aid in more efficient research for the 8x6 wind tunnel.

Young, Nathaniel, III↗

Installation for the study of the angular distribution of cosmic muons with super-high energies at large zenith angles

An installation consisting of an ionization calorimeter and a counter hodoscope can be used to record cascade showers caused by the electromagnetic interactions of muons with superhigh energies in the cosmic ray horizontal flux. The direction of the muons is determined by a hodoscope consisting of 2196 counters. The information obtained makes it possible to restore the angular and energy distribution of the cosmic muons, which, in turn, makes it possible to determine the mechanism of their generation. The accuracy with which the angle of the passing particle is determined is discussed in detail in addition to the causes which can introduce distortions, such as shower accompaniment of neutrons, escape of shower electrons from the calorimeter, random coincidences, etc.

Borog, V. V.↗

Standoff Infrared Measurements of Chemical Plume Dynamics in Complex Terrain Using a Combination of Active Swept-ECQCL Laser Spectroscopy with Passive Hyperspectral Imaging

Chemical plume detection and modeling in complex terrain present numerous challenges. We present experimental results from outdoor releases of two chemical tracers (sulfur hexafluoride and Freon-152a) from different locations in mountainous terrain. Chemical plumes were detected using two standoff instruments collocated at a distance of 1.5 km from the plume releases. A passive long-wave infrared hyperspectral imaging system was used to show time- and space-resolved plume transport in regions near the source. An active infrared swept-wavelength external cavity quantum cascade laser system was used in a standoff configuration to measure quantitative chemical column densities with high time resolution and high sensitivity along a single measurement path. Both instruments provided chemical-specific detection of the plumes and provided complementary information over different temporal and spatial scales. The results show highly variable plume propagation dynamics near the release points, strongly dependent on the local topography and winds. Effects of plume stagnation, plume splitting, and plume mixing were all observed and are explained based on local topographic and wind conditions. Measured plume column densities at distances ~100 m from the release point show temporal fluctuations over ~1 s time scales and spatial variations over ~1 m length scales. The results highlight the need for high-speed and spatially resolved measurement techniques to provide validation data at the relevant spatial and temporal scales required for high-fidelity terrain-aware microscale plume propagation models.

47 OTHER INSTRUMENTATION↗

Secretory stimuli distinctly regulate insulin secretory granule maturation through structural remodeling

Insulin secretory granule (ISG) maturation is a crucial aspect of insulin secretion and glucose homeostasis. The regulation of this maturation remains poorly understood, especially how secretory stimuli affect ISG maturity and subcellular localization. In this study, we used soft X-ray tomography (SXT) to quantitatively map ISG morphology, density, and location in single INS-1E and mouse pancreatic β cells under the effect of various secretory stimuli. We found that the activation of glucokinase (GK), gastric inhibitory polypeptide receptor (GIPR), glucagon-like peptide-1 receptor (GLP-1R), and G protein-coupled receptor 40 (GPR40) promotes ISG maturation. Each stimulus induces unique structural remodeling in ISGs, by altering size and density, depending on the specific signaling cascades activated. These distinct ISG subpopulations mobilize and redistribute in the cell, altering the overall cellular structural organization. Our results provide insight into how current diabetes and obesity therapies impact ISG maturation and may inform the development of future treatments that target maturation specifically.

insulin granule maturation↗

Search for heavy dark matter from dwarf spheroidal galaxies: leveraging cascades and subhalo models

Abstract TheFermiLarge Area Telescope (Fermi-LAT) has been widely used to search for Weakly Interacting Massive Particle (WIMP) dark matter signals due to its unparalleled sensitivity in the GeV energy band. The leading constraints for WIMP byFermi-LAT are obtained from the analyses of dwarf spheroidal galaxies within the Local Group, which are compelling targets for dark matter searches due to their relatively low astrophysical backgrounds and high dark matter content. In the meantime, the search for heavy dark matter with masses above TeV remains a compelling and relatively unexplored frontier. In this study, we utilize 14-yearFermi-LAT data to search for dark matter annihilation and decay signals in 8 classical dwarf spheroidal galaxies within the Local Group. We consider secondary emission caused by electromagnetic cascades of prompt gamma rays and electrons/positrons from dark matter, which enables us to extend the search withFermi-LAT to heavier dark matter cases. We also update the dark matter subhalo model with informative priors respecting the fact that they reside in subhalos of our Milky Way halo aiming to enhance the robustness of our results. We place constraints on dark matter annihilation cross section and decay lifetime for dark matter masses ranging from 10 3 GeV to 10 11 GeV, where our limits are more stringent than those obtained by many other high-energy gamma-ray instruments.

Astronomy & Astrophysics↗

Cascade Error Projection with Low Bit Weight Quantization for High Order Correlation Data

In this paper, we reinvestigate the solution for chaotic time series prediction problem using neural network approach. The nature of this problem is such that the data sequences are never repeated, but they are rather in chaotic region. However, these data sequences are correlated between past, present, and future data in high order. We use Cascade Error Projection (CEP) learning algorithm to capture the high order correlation between past and present data to predict a future data using limited weight quantization constraints. This will help to predict a future information that will provide us better estimation in time for intelligent control system. In our earlier work, it has been shown that CEP can sufficiently learn 5-8 bit parity problem with 4- or more bits, and color segmentation problem with 7- or more bits of weight quantization. In this paper, we demonstrate that chaotic time series can be learned and generalized well with as low as 4-bit weight quantization using round-off and truncation techniques. The results show that generalization feature will suffer less as more bit weight quantization is available and error surfaces with the round-off technique are more symmetric around zero than error surfaces with the truncation technique. This study suggests that CEP is an implementable learning technique for hardware consideration.

Duong, Tuan A.↗

Superlattices and NiPi structures in new forms of cascade solar cells

The activity in the field of photovoltaic semiconductor superstructures is described. Progress was accomplished in the two principal directions previously defined in our initial proposal, i.e.: (1) Theoretical investigation of the optical properties of superlattices; and (2) New solar cell concepts and device modeling. Although important information concerning the optical constants of superlattices and multiple quantum well structures was obtained from our computer model, most of the theoretical efforts have progressively shifted from the former to the latter aspect of the project because of the discovery of a new kind of photovoltaic device which may exhibit improved performances with respect to conventional solar cells.

Leburton, J. P.↗