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At least 217 records · Page 12

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗

Nevada National Security Site Demonstration Reactor Siting and Capability Study

The study’s purpose is to identify suitable testbeds within the NNSS for the demonstration of advanced and emerging reactor technologies. These testbeds are envisioned to be existing structures, facilities, or sites that may be suitable for advanced reactor demonstrations, advanced reactor fuel fabrication, or other experimental support for advanced reactor demonstrations. This study examines siting alternatives at NNSS with the objective of identifying locations for near term ARD projects. Included in the outcomes is an evaluation of the quantitative and qualitative factors that must be addressed for each site if selected to host an ARD sponsored demonstration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Metrology of a Focusing Capillary Using Optical Ptychography

The focusing property of an ellipsoidal monocapillary has been characterized using the ptychography method with a 405 nm laser beam. The recovered wavefront gives a 12.5×10.4μm 2 focus. The reconstructed phase profile of the focused beam can be used to estimate the height error of the capillary surface. The obtained height error shows a Gaussian distribution with a standard deviation of 1.3 μm. This approach can be used as a quantitative tool for evaluating the inner functional surfaces of reflective optics, complementary to conventional metrology methods.

36 MATERIALS SCIENCE↗

Color as a tool for quantitative analysis of heterogeneous polymer degradation

Polymers are widely used industry, but degrade due to environmental conditions, such as elevated temperature or radiation. The degradation of polymers is dominated oxidation in oxygenated environments. Such oxidation is commonly referred to as thermal-oxidation or photo-oxidation and in many situations is heterogeneous through thickness of the polymer. While heterogeneous oxidation of polymers is a common phenomenon, the effect on the lifetime of polymers is not well understood as methods to evaluate such oxidation are time consuming and challenging to implement. Here we show a novel method for quantitative evaluation of heterogeneous oxidation in polymers using a fast and accurate color approach. The proposed color approach was observed to improve the efficiency of obtaining heterogenous oxidation profiles in half the time of common approaches, such as indention or Fourier transform infrared spectroscopy. Furthermore, the method was found to produce trends similar to that observed using common approaches and the applicability of the method was verified by mapping oxygen concentration through thickness using energy dispersive X-ray spectroscopy. Lastly, the utility of the proposed method was demonstrated through the generation of an oxidation design space, which is envisioned to assist with designing experiments towards estimation of polymer lifetime. Finally, we anticipate this work to be a starting point for further evaluation of heterogeneous oxidation in polymers using optical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Benchmark Analysis

Tremendous progress has been achieved in the development of land models and their inclusion in Earth system models (ESMs). However, we still have very limited knowledge on the performance skills of these land models. This chapter introduces benchmark analysis, which is a procedure to measure performance of models against a set of defined standards. The benchmark analysis includes: (1) defining targeted aspects of model performance to be evaluated; (2) testing model performance in comparison with a set of benchmarks; (3) measuring model performance skill through quantitative metrics; and (4) evaluating model performance and offering suggestions for future model improvement.

Luo, Yiqi↗

Omics-Lethal Human Viruses, MERS-CoV Experiment MCL003

The purpose of this experiment was to evaluate the human host response to wild-type icMERS-CoV virus infection and mockulum. Sample data was obtained from human lung adenocarcinoma cells (Calu-3) for proteome, metabolome, and lipidome expression analysis. Resulting quantitative data profiles were evaluated for extreme outlier behavior using MPLEX protocol. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, and lipidomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

A Multi-Criteria Impact Evaluation Methodology Applied to FLEX Strategies in Nuclear Power Plants

As responses to Fukushima Dai-ichi nuclear accident, several advanced, near-term technologies have been or are being introduced to enhance safety of operating nuclear power plants (NPPs) as well as improving their sustainability. Examples include Accident-Tolerant Fuel designs, Diverse and Flexible Coping Strategies (FLEX), and passive cooling system designs. The combinations of these technologies, coupled with enhancements to plant components and systems and improved fuel cycle efficiency, constitute a concept of Enhanced Resilient Plant Systems, which is proposed and being explored by Idaho National Laboratory (INL) under the Risk-Informed Systems Analysis Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program. To decide if introducing a technology is necessary or worthy, the impacts of this technology on NPPs should be evaluated, preferably in a quantitative manner, and provided to decision makers. This paper summarizes an on-going work conducted by the authors on developing a multi-criteria impact evaluation methodology. This methodology is expected to be applicable to evaluate a variety of technologies, while FLEX strategy is adopted as a case study for this paper.

99 GENERAL AND MISCELLANEOUS↗

Extraction and selective promotion of zero-group velocity and cutoff frequency resonances in bi-dimensional waveguides using the electromechanical impedance method

This study showcases the electromechanical impedance (EMI) technique for extracting and promoting zero-group velocity (ZGV) and cutoff frequency resonances in a waveguide structure. Here, we identify the mechanisms of multiple resonances in the EMI spectra via a wave propagation perspective. Both simulation and experiments reveal the fact that sharp resonances in the conductance spectra are associated with either ZGV or cutoff frequency points. Consequently, we design four test configurations to enhance local resonances by aligning induced motions with considered mode shapes. Reasonable agreement between simulation and experiment results is observed. We evaluate the performance of considered configurations in terms of mode enhancement, and configurations that can selectively promote certain mode families are summarized. This study also shines the light on the EMI technique for quantitative non-destructive evaluation (NDE) by potentially supporting the inverse characterization of mechanical properties of host structures.

42 ENGINEERING↗

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

59 BASIC BIOLOGICAL SCIENCES↗

Corroborative Evaluation of the Real-World Energy Saving Potentials of InfoRich Eco-Autonomous Driving (iREAD) System

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing. These four approaches, spanning simulation and testing aspects, evaluate real-world fuel economy benefits with different ranges and resolutions. The large-scale simulations leverage an extensive real-world driving database to assess overall eco-driving benefits across a range of road network and driving scenarios. The real-world driving data are further leveraged to generate representative driving routes for deeper evaluation. Based on the representative routes, in-depth simulation relying on high-fidelity models investigates how different traffic scenarios can impact the eco-driving performance. The vehicle-in-the-loop setup reinforces the in-depth simulations by conducting tests with an actual vehicle operated on a chassis dynamometer; the measured energy savings were indeed found to agree with the in-depth simulation savings estimates. Finally, limited but representative road testing with the fully integrated vehicle will be conducted to demonstrate the eco-driving capability and conclude the overall evaluation regimen.

ARPA-E↗

A subdermal tagging technique for juvenile sturgeon using a new self-powered acoustic tag

Abstract Background A new technology for a self-powered acoustic tag (SPT) was developed for active tracking of juvenile fish, intended to avoid the typical battery life constraints associated with active telemetry technology. We performed a laboratory study to evaluate a subdermal tagging technique for the SPT and effects of the tag on survival, tag retention, and growth in juvenile white sturgeon ( Acipenser transmontanus ). Results Survival was associated with tag retention. White sturgeon implanted with the SPT ( n = 30) had 93% survival and tag retention by day 28, 67% by day 101, and 38% by day 595 post-tagging. Sturgeon implanted with a passive integrated transponder (PIT) tag only (control group) had 96% survival and tag retention by day 28, and through day 101 post-tagging. Fish in the PIT group were repurposed after day 101, so no comparisons with this group were made at day 595 post-tagging. Specific growth rate (SGR) for fork length was a median of 0.25% day −1 by day 28 for the SPT group, which was significantly lower than the PIT group (median: 0.42% day −1 ; n = 27). The SPT and PIT groups had similar SGR fork length by day 101 post-tagging (0.22 and 0.25% day −1 , respectively). SGR weight was also lower for the SPT group compared to the PIT group on day 28 (1.39 and 2.11% day −1 , respectively), but the difference again dissipated by day 101 (0.79 and 0.88% day −1 , respectively). Conclusion The tagging technique and placement of the SPT allowed the tag to remain upright along the flank of the sturgeon to ensure maximum battery output of the SPT; however, retention rates of the SPT were not ideal. We provided suggestions to improve the tagging technique. Suggestions included tagging fish that are > 400 mm FL, moving the incision location to extend the cavity and create a pocket for the placement of the SPT, and performing a quantitative wound-healing evaluation. Future studies are therefore recommended to evaluate these suggestions.

59 BASIC BIOLOGICAL SCIENCES↗

Acoustic Exposure to Turbine Operation Quantifies Risk to Bats at Commercial Wind Energy Facilities

ABSTRACT Turbine‐related bat mortality at commercial wind energy facilities may threaten populations of migratory tree‐roosting bat species in North America. Industry stakeholders and regulatory agencies alike are investigating strategies to reduce risk of population‐level consequences as the wind energy industry grows. Bats collide with turbines only when turbine rotors are spinning and curtailing turbine operation at low wind speeds can effectively reduce bat fatality rates. Nonetheless, few quantitative data exist to determine appropriate threshold wind speeds below which turbine operations should be curtailed. Carcass monitoring is labor‐intensive and does not provide information on factors linked to bat fatality rates on any scale finer than nightly. We tested whether acoustic bat data recorded at turbine nacelles could provide a more precise and sensitive measure of fatality risk to bats by analyzing acoustics, weather, turbine operation, and carcass data collected at 2 commercial wind energy facilities in West Virginia over 7 years. Each wind facility implemented several distinct curtailment treatments during our study, allowing us to compare fatality rates and acoustic bat activity across multiple operational strategies. We found that bat passes exposed to turbine operation explained close to 80% of the variation in carcass‐based estimates of bat fatality rates and accounted for significant variation in raw carcass counts per turbine and probability of finding bat carcasses during individual turbine searches. Conversely, bat activity occurring when turbines were not operating had little or no relationship to fatality rates. We also found that patterns in bat activity exposure could be predicted accurately among turbines and years. Our results demonstrate that measuring exposure of acoustic bat activity provides a quantitative basis for designing, evaluating, and adaptively managing curtailment strategies. This is an important advance towards using curtailment to reduce bat fatality rates strategically while allowing for increased generation of renewable energy. © 2021 The Authors. Wildlife Society Bulletin published by Wiley Periodicals LLC on behalf of The Wildlife Society.

17 WIND ENERGY↗

Association of small vessel disease with tau pathology

Emerging evidence suggests that small vessel disease (SVD) is a risk factor for clinical dementia and may contribute to AD neuropathological changes. Watershed brain regions are located at the most distal areas between arterial territories, making them vulnerable to SVD-related changes. We examined the association of pathologic markers of SVD, specifically arteriolosclerosis in watershed brain regions, with AD pathologic changes. Participants (N= 982; mean age-at-death = 90; 69% women) were enrolled as part of one of two cohort studies of aging and dementia. At autopsy, neuropathological evaluation included semi-quantitative grading of arteriolosclerosis pathology from 2 cortical watershed regions: the anterior watershed (AWS) and posterior watershed (PWS), densities for cortical β-amyloid and tau-tangle pathology, and other common age-related pathologies. Linear regression models examined the association of watershed arteriolosclerosis pathology with β-amyloid and tau-tangle burden. In follow-up analyses, available ex-vivo MRI and proteomics data in a subset of decedents were leveraged to examine the association of whole brain measure of WMH, as a presumed MRI marker of SVD, with β-amyloid and tau-tangle burden, as well as to examine the association of watershed arteriolosclerosis with proteomic tau. Watershed arteriolosclerosis was common, with 45% of older persons having moderate-to-severe arteriolosclerosis pathology in the AWS region, and 35% in the PWS. In fully adjusted models that controlled for demographics and common age-related pathologies, an increase in severity of PWS arteriolosclerosis was associated with a higher burden of tau-tangle burden, specifically neocortical tau burden, but not with β-amyloid. AWS arteriolosclerosis was not associated with β-amyloid or tau pathology. Ex-vivo WMH was associated with greater tau-tangle pathology burden but not β-amyloid. Furthermore, PWS arteriolosclerosis was associated with higher abundance of tau phosphopeptides, that promote formation of tau aggregates. These data provide compelling evidence that SVD, specifically posterior watershed arteriolosclerosis pathology, is linked with tau pathological changes in the aging brain.

60 APPLIED LIFE SCIENCES↗

Systematic analysis of melt pool dynamics in laser processing of mixed powder feedstocks

Functionally graded materials (FGMs) fabricated via additive manufacturing of blended powders offer the potential to spatially tailor properties for new technologies, such as fusion first-wall systems, turbine blades, and spacecraft. However, processing these materials is difficult due to the multiplicity of processing parameters to optimize, all of which must be changed as substrate material, powder feedstock compositions, and melt pool dynamics evolve. Here, this work systematically evaluates the qualitative and quantitative effects of these variables on the melt pool size, shape, composition, and particle distribution in an exemplar Ti-Ta system, and connects the experimental results to Marangoni flow behavior and phenomena observed in other systems. Increasing laser power linearly increases melt pool size and layer thickness, driving engineering considerations such as part/geometrical tolerances. Decreasing laser velocity changes the melt pool shape from lenticular to convex and reduces chemical homogeneity due to extreme thermal and compositional gradients between the melt pool center and boundaries. Thermophysical property differences between the powder feedstock and substrate material, as well as the directionality of the gradient, affect dilution and melt pool dynamics, which in turn affect the melt pool boundary characteristics, shape, and uniformity. Mixed powder feedstocks of intermediate compositions do not behave according to linear interpolations between single-material endpoints, instead building taller and wider melt pools. As such, it is recommended to quantify process maps for at least one intermediate composition in the FGM or multi-material system of interest to ensure optimized processing parameters, predictable melt pool sizes and shapes, and compositional and spatial precision.

Dissimilar↗

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗

High-throughput calculations of charged point defect properties with semi-local density functional theory—performance benchmarks for materials screening applications

Abstract Calculations of point defect energetics with Density Functional Theory (DFT) can provide valuable insight into several optoelectronic, thermodynamic, and kinetic properties. These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches. For applications of DFT-based high-throughput computation for data-driven materials discovery, point defect properties are of interest, yet are currently excluded from available materials databases. This work presents a benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We consider three different a-posteriori correction sets implemented in an automated workflow, and evaluate the qualitative and quantitative differences among four different categories of defect information: thermodynamic transition levels, formation energies, Fermi levels, and dopability limits. We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy.

36 MATERIALS SCIENCE↗

Three-dimensional imaging of mitochondrial cristae complexity using cryo-soft X-ray tomography

Mitochondria are dynamic organelles that change morphology to adapt to cellular energetic demands under both physiological and stress conditions. Cardiomyopathies and neuronal disorders are associated with structure-related dysfunction in mitochondria, but three-dimensional characterizations of the organelles are still lacking. In this study, we combined high-resolution imaging and 3D electron density information provided by cryo-soft X-ray tomography to characterize mitochondria cristae morphology isolated from murine. Using the linear attenuation coefficient, the mitochondria were identified (0.247 ± 0.04 µm -1 ) presenting average dimensions of 0.90 ± 0.20 µm in length and 0.63 ± 0.12 µm in width. The internal mitochondria structure was successfully identified by reaching up the limit of spatial resolution of 35 nm. The internal mitochondrial membranes invagination (cristae) complexity was calculated by the mitochondrial complexity index (MCI) providing quantitative and morphological information of mitochondria larger than 0.90 mm in length. The segmentation to visualize the cristae invaginations into the mitochondrial matrix was possible in mitochondria with MCI ≥ 7. Altogether, we demonstrated that the MCI is a valuable quantitative morphological parameter to evaluate cristae modelling and can be applied to compare healthy and disease state associated to mitochondria morphology.

3-D reconstruction↗

Dangling bonds, the charge neutrality level, and band alignment in semiconductors

We present a systematic study of the electronic properties of dangling bonds (DBs) in a variety of semiconductors and examine the relationship between DBs and the charge neutrality level (CNL) in the context of band alignments of semiconductors. We use first-principles calculations based on density functional theory to assess the energetics of DBs in a set of diamond-structure group-IV and III–V or II–VI zinc-blende-structure semiconductors, considering both cation and anion-derived states. We examine the charge-state transition levels of DBs to assess whether they can serve as a CNL to align band structures, by comparing with offsets calculated from interface calculations. Our results show that this approach for evaluating the CNL yields quantitative results for band offsets and provides useful insights. We discuss the relation with alternative approaches for determination of CNLs based on branch-point energies or transition levels of interstitial hydrogen.

36 MATERIALS SCIENCE↗