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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Molecular Evolution of the H5 and H7 Highly Pathogenic Avian Influenza Virus Haemagglutinin Cleavage Site Motif

ABSTRACT Avian influenza viruses are ubiquitous in the Anatinae subfamily of aquatic birds and occasionally spill over to poultry. Infection with low pathogenicity avian influenza viruses generally leads to subclinical or mild clinical disease. In contrast, highly pathogenic avian influenza viruses emerge from low pathogenic forms and can cause severe disease associated with extraordinarily high mortality rates. Here, we describe the natural history of avian influenza virus, with a focus on H5Nx and H7Nx subtypes, and the emergence of highly pathogenic forms; we review the biology of AIV; we examine cleavage of haemagglutinin by host cell enzymes with a particular emphasis on the biochemical properties of the proprotein convertases, and trypsin and trypsin‐like proteases; we describe mechanisms implicated in the functional evolution of the haemagglutinin cleavage site motif that leads to emergence of HPAIVs; and finally, we discuss the diversity of H5 and H7 haemagglutinin cleavage site sequence motifs. It is crucial to understand the molecular attributes that drive the emergence and evolution of HPAIVs with pandemic potential to inform risk assessments and mitigate the threat of HPAIVs to poultry and human populations.

Luczo, Jasmina M. [Australian Animal Health Labora↗

Discovery of a Ferromagnetic Nickel Chalcogenide Nanocluster Ni 3 S 3 H(PEt 3 ) 5

Atomically precise ligated nanoclusters (NC) are promising cluster-based materials with novel molecular architectures and tunable magnetic properties. Herein, the synthesis and characterization of a nickel sulfide NC Ni 3 S 3 H(PEt 3 ) 5 (PEt 3 = triethylphosphine) with distinct magnetic properties are reported. Magnetization measurements reveal its magnetic moment of 1.5 µ B in the solid phase, consistent with the existence of one unpaired electron predicted by density functional theory (DFT) calculations. Additionally, experimental measurements indicate the presence of ferromagnetic ordering within each Ni 3 S 3 H(PEt 3 ) 5 NC and strong coercivity at temperatures below 20 K. Ion mobility-mass spectrometry is employed in conjunction with DFT calculations and collision cross-section simulations to investigate the structure of the isolated Ni 3 S 3 H(PEt 3 ) 5 . Theoretical studies show that [Ni 3 S 3 H(PEt 3 ) 5 ] + has a planar Ni 3 S 3 core where three Ni atoms are arranged in a triangle with three bridging S atoms residing in the same plane. This structure is preserved in both solution and solid phases, which is confirmed by spectroscopic studies of Ni 3 S 3 H(PEt 3 ) 5 . Additionally, DFT calculations indicate that all spins at the Ni sites are aligned parallel, confirming the presence of ferromagnetic coupling. Overall, this study provides key insights into the structure and magnetic properties of Ni 3 S 3 H(PEt 3 ) 5 , which will facilitate the design of new NC-based magnetic materials.

Nickel sulfide nanocluster↗

Automated Programmable Logic Controller Memory Forensics Using RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and Internet-based technologies has enhanced industrial control system operations but have inadvertently increased their vulnerabilities to cyber attacks. When an industrial control system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies. Memory forensics is critical in the incident analysis process to ascertain what occurred. Approaches for analyzing the persistent memory in industrial control devices are limited and almost nonexistent for volatile memory. This chapter proposes an automated methodology for programmable logic controller memory dump analysis using computer vision and deep learning techniques. The methodology converts the sequences of bytes in a programmable logic controller memory dump to red-green-blue pixels and employs a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. The trained model is employed to automatically segment new memory images and identify forensic artifacts. Evaluation of the methodology on a Schneider Electric Modicon M221 programmable logic controller under code injection and code modification attacks demonstrates its ability to detect attack artifacts in memory dumps.

Asmar Awad, Rima [ORNL] (ORCID:0000000233407742)↗

Estimating evapotranspiration from deciduous broadleaf forests by considering the effect of foliar litter

Forest litter cover significantly alters the ground surface resistance, which influences the water and energy transfer processes between the land surface and atmosphere. Penman-Monteith (PM) model is widely used to estimate land surface evapotranspiration (ET). However, it was shown to overestimate ET during the period when foliar litter covers the ground surface. Therefore, incorporating the effect of foliar litter on ground surface resistance can potentially improve ET estimates. Here, in this study, we proposed a foliar litter surface resistance model to describe the effect of litter cover on water vapor transport, then incorporated the litter surface resistance into the PM model (noted as PM-EL model). The performance of the PM-EL model was evaluated using observations from 18 deciduous broadleaf forest (DBF) flux sites across global FLUXNET2015 datasets. Results showed that: (1) both the PM model and the PM-EL model are most sensitive to ground surface resistance among resistance parameters; (2) the proposed litter resistance model is capable of describing the seasonal dynamic of litter in DBF ; (3) the PM-EL model, has been shown to improve ET estimates with the coefficient of determination increased by 8.5 %, the mean absolute error and relative root mean square error decreased by 22.1 % and 20.9 %, respectively. The study contributes to our understanding of the effect of litter cover on ET estimation and provides insights into forest ecohydrology and land surface mass and energy transfer processes.

Deciduous Broadleaf Forest↗

Multiscale Effects Masked the Impact of the COVID-19 Pandemic on Electricity Demand in the United States

Shelter-in-place orders and business closures related to COVID-19 changed the hourly profile of electricity demand and created an unprecedented source of uncertainty for the grid. The potential for continued shifts in electricity profiles has implications for electricity sector investment and operating decisions that maintain reserve margins and provide grid reliability. This study reveals that understanding this uncertainty requires an understanding of the underlying drivers at the customer-class scale. This paper utilizes three datasets to compare the impacts of COVID-19 on electricity consumption across a range of spatiotemporal and customer scales. At the utility/customer-class scale, COVID-19-induced shutdowns in the spring of 2020 shifted weekday residential load profiles to resemble weekend profiles from previous years. Total commercial loads declined, but the commercial diurnal load profile was unchanged. With only total loads available at the balancing authority scale, the apparent impact of COVID-19 was smaller during the summer due in part to phased re-opening and spatial variability in re-opening, but there were still clear variations once total loads were broken down zonally. Monthly data at the state scale showed an increase in state-level residential electricity sales, a decrease in commercial sales, and a small net decrease in total sales in most states from April-August 2020. Analyses that focus on total load or a single scale may miss important changes that become apparent when the load is broken down regionally or by customer class.

COVID-19, electricity demand, multiscale, Commonwe↗

Residual resistance ratio measurement system for Nb 3 Sn wires extracted from Rutherford cables

Residual resistance ratio (RRR) of superconducting strands is an important parameter for magnet electrical stability. RRR serves as a measure of the low-temperature electrical conductivity of the copper within a conductor that has a copper stabilization matrix. For Nb 3 Sn, due to the need of a reaction heat treatment, the technical requirements for high quality measurements of strands extracted from Rutherford cables are particularly demanding. Quality of wire, cabling deformation, heat treatment temperature, heat treatment atmosphere, sample handling, and measurement methods can all affect the RRR. Therefore, as an integral part of the electrical quality control (QC) of Nb 3 Sn Rutherford cables manufactured at the Lawrence Berkeley National Laboratory, it was prudent that we established a RRR measurement system that can isolate the assessment of cable-fabrication-related impacts from sample preparation and measurement factors. Here we describe a bespoke cryocooler-based measurement system, capable of measuring RRR of over 80 samples in a single cooldown. The samples are mounted on custom-designed printed circuit boards that accommodate the shape of strands extracted from a Rutherford cable without added deformation, which we will show is critical in ensuring that the measurements accurately represent the RRR values of the conductor within the cable. Using this sample mounting solution, we routinely measure the overall RRR of the strand as well as individual intra-strand sections corresponding to both cable edges and cable broad faces with high reproducibility. Such measurements provide valuable information on the variation of RRR along the length of the strands as well as across strand productions and cable runs over time.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhanced boron doping for diamond growth in cylindrical CVD reactors using a Faraday cage

We report on the use of 3D-printed titanium Faraday cages in a cylindrical resonant cavity CVD reactor for the growth of heavily boron-doped single-crystalline superconducting diamond. We show that the cage enhances boron doping uniformity and provides control of the doping efficiency and growth rate by varying the distance between the plasma and the diamond surface. Using finite element modelling, we demonstrate that the Faraday cage focuses the electric field at the top of the cage whilst also suppressing the electric field inside the cage, thereby pinning the plasma at a fixed height above the sample. This eliminates plasma “hot spots” at the edges of the sample and creates a more uniform plasma electron and hydrogen radical distribution over the sample, resulting in a more uniform boron incorporation.

Boron doped diamond↗

Effects of dissolved cations, dissolved organic carbon, and exposure concentrations on per- and polyfluoroalkyl substances bioaccumulation in freshwater algae

Per- and polyfluoroalkyl substances (PFAS) have attracted global attention because of their persistence, toxicity, bioaccumulation potential, and associated adverse effects. As important primary producers, freshwater algae constitute the base of the food web in freshwater aquatic ecosystems. However, the effects of key environmental factors on PFAS uptake and bioaccumulation in freshwater algae have not been thoroughly studied. In this study, three bioaccumulation experiments were conducted to evaluate the influence of dissolved cations, dissolved organic carbon, and exposure concentrations on PFAS bioaccumulation in algae. Among the 14 studied PFAS, seven long-chain PFAS tended to bioaccumulate in algae. Elevated divalent cations (Ca 2+ and Mg 2+ ) and dissolved organic carbon did not significantly change the algal bioconcentration factors (BCFs) of PFAS, suggesting complexity of the interactions among PFAS, environmental factors, and biotic activities. Additionally, increasing exposure concentrations (0.5, 1, 5, and 10 μg/L of each PFAS) increased PFAS concentrations in algae but decreased the BCF values. This indicated that attention should be paid to the application of BCFs in future studies, including ecological risk assessment. Moreover, fluorotelomer sulfonic acids (FTSs) were incompletely recovered, suggesting that biotransformation occurred. Further studies should be conducted to evaluate whether algae play a role in FTSs biotransformation and to determine the mechanisms. In conclusion, studying the impacts of key environmental factors on PFAS bioaccumulation in algae is crucial for understanding the bioaccumulation processes that occur at the lowest trophic level and that eventually affect the dynamics of entire aquatic ecosystems.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Development of a River Dynamical Core for E3SM to simulate compound flooding on Exascale-class heterogeneous supercomputers

Flooding events pose significant risk to human life, property, and infrastructure. Physically-consistent quantification of altered flood risks in global models requires hyper-resolution (~1 km) or fine flood simulations using two-dimensional (2D) physics schemes, both of which are unavailable in the current generation Earth System Models. Here, in this work, we have developed the River Dynamical Core (RDycore), which is an open-source, 2D shallow water equation (SWE) library for the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM). RDycore uses PETSc and libCEED libraries that allows it to run efficiently on CPUs and GPUs, as well as select a time-integration algorithm at runtime without requiring any code modifications. RDycore achieves spatial error convergence rates for problems with analytical and manufactured solutions similar to those reported previously in the literature, or consistent with the implemented first-order spatial discretization scheme. RDycore's accuracy in predicting flooding for a well-studied dam break problem is comparable to existing SWE models. For a problem with 471 million grid cells, RDycore achieves a speedup of 6.6x and 7.6x on GPUs compared to CPUs when using 320 compute nodes on DOE's Perlmutter and Frontier supercomputers, respectively. The one-way coupling of the RDycore library within E3SM is demonstrated by performing multiple 5-day flooding simulations during Hurricane Harvey driven by five precipitation datasets. The E3SM--RDycore simulations at 30 m spatial resolution accurately simulate maximum water height during the hurricane when benchmarked against a previously published study and achieve a speedup of 15x (Perlmutter) and 21x (Frontier) on GPUs relative to CPUs. The work presented here is the foundational step in providing hardware and algorithmic portability framework for simulating kilometer-scale river dynamics within E3SM.

Flood Simulation↗

Enhancing operational safety: The NSTX-U Shorted Turn Protection (STP) system

The NSTX-U Shorted Turn Protection (STP) system is a vital safety feature designed to protect the tokamak’s coils during operations. It employs a Kalman filter-based algorithm to monitor coil currents and detect faults in real-time. If an anomaly is detected, the system swiftly terminates the tokamak pulse to prevent damage. Developed with Matlab and Simulink, the STP system has been validated through real-time simulations, ensuring its effectiveness for the upcoming upgrades of the NSTX-U facility. In conclusion, this article presents the theory for implementation of the STP algorithm and the results from simulation and real-time implementation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Shadow masks predictions in SPARC tokamak plasma-facing components using HEAT code and machine learning methods

Here, this work uses machine learning (ML) to complement HEAT (Heat flux Engineering Analysis Toolkit) by developing 3-D footprint surrogate models for fast and accurate heat load calculations in the divertor of the SPARC tokamak. The focus is on shadowed regions, or magnetic shadows, caused by the 3-D geometry of plasma-facing components (PFCs). ML classifiers are employed to create a surrogate model for HEAT generated shadow masks, predicting these shadow masks and divertor heat flux profiles based on a diverse range of equilibria and only the plasma current, safety factor(q95) at the edge, and magnetic flux angles as input parameters. The ultimate goal is to integrate the model for real-time control and future operational decisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Evolution of storage monitoring – update in response to commercial and regulatory drivers

Carbon Capture and Storage (CCS) is in transition from first-of-a kind projects and research-orientated pilots to commercially-motivated applications. Monitoring results from many newly developed and planned large scale commercial projects are limited; however, it is worthwhile to assess their evolution and consider new strategies as part of an effort to assess and document best practices. Commercial monitoring is targeted to activities that comply with regulatory drivers and de-risk investments. Commercial monitoring also supports accounting that storage has occurred and is tied to project financing. It deals with long time frames and large volumes injected into multiple wells and multiple projects in favorable areas. We see developing trends toward reproducible workflows that systematically reduce risks and clarify expectations for oversight and long-term surveillance. Monitoring techniques showing increasing trends include injection zone pressure as a history-matching and compliance tool. To reduce cost and environmental impact of time-lapse seismic data collection, deploying new approaches and tools, such as use of fibre and installed sources are increasingly applied. Concern over the risk of induced seismicity by regulatory bodies and the general public has increased, which has also resulted in increased monitoring. Some techniques used in the early research phases have been sidelined or used only in restricted applications. For example, geochemical analyses in the injection zone as well as the environment are now being deployed less than it was in research-oriented programs, except in the US where it is required by the permitting process. Expectations of frequent area-wide near surface monitoring have also decreased.

25 ENERGY STORAGE↗

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗

Beam focusing and consequences for Doppler backscattering measurements

The phenomenon of focusing of microwave beams in a plasma near a turning-point caustic is discussed by exploiting the analytical solution to the Gaussian beam-tracing equations in the two-dimensional (2-D) linear-layer problem. The location of maximum beam focusing and the beam width at that location are studied in terms of the beam initial conditions. This focusing must be taken into account to interpret Doppler backscattering (DBS) measurements. We find that the filter function that characterises the scattering intensity contribution along the beam path through the plasma is inversely proportional to the beam width, predicting enhanced scattering from the beam focusing region. We show that the DBS signal enhancement for decreasing incident angles between the beam path and the density gradient is due to beam focusing and not due to forward scattering, as was originally proposed by (Gusakov et al., (Plasma Phys. Contr. Fusion, vol. 56, 2014, p. 0250092014, 2017); Plasma Phys. Rep. vol. 43(6), 2017, pp. 605–613). The analytic beam model is used to predict the measurement of the k y density-fluctuation wavenumber power spectrum via DBS, showing that, in an NSTX-inspired example, the spectral exponent of the turbulent, intermediate-to-high k y density-fluctuation spectrum might be quantitatively measurable via DBS, but not the spectral peak corresponding to the driving scale of the turbulent cascade.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The high-field tokamak physics basis for the ARC fusion power plant

This editorial summarizes the physics basis underlying the ARC high-field tokamak fusion power plant, including recent advances in tokamak plasma understanding, the role of the SPARC device, and key remaining physics questions. It describes how these results guide the ARC Version 3A design and outlines opportunities for the broader fusion community to contribute to the development of first-generation fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Glacial‐Interglacial and Millennial‐Scale Changes in Nitrous Oxide Emissions Pathways and Source Regions

During the transition from the Last Glacial Maximum (LGM) to the Holocene, the atmospheric N 2 O mole fraction increased by 80 nmol mol −1 . Using ice core measurements of N 2 O isotopomer ratios, we show that this increase was driven by increases in both nitrification and denitrification, with the relative partitioning between both production pathways depending on the assumed isotopic end-member source signatures. Similarly, we also attribute a 35 nmol mol −1 N 2 O mole fraction increase during the Heinrich Stadial 4/Dansgaard Oeschger 8 (HS4/DO8) millennial-scale event to increases in both N 2 O production pathways. In contrast, the 25 nmol mol −1 N 2 O mole fraction decrease during the Younger Dryas was driven almost exclusively by a decrease in nitrification. The deglacial and HS4/DO8 increases in N 2 O production occurred in both marine and terrestrial environments, with the terrestrial source responding faster to warming by about two centuries. Constraints on changes in nitrification and denitrification emissions are robust and consistent with previous studies showing the sensitivity of N 2 O emissions to abrupt Northern Hemisphere warming. This study demonstrates for the first time the importance of both denitrification and nitrification pathways in driving source changes. Absolute emissions are more uncertain due to uncertainty about source isotopomer signatures. For instance, the contribution of denitrification to emissions at the LGM shifts from (65 ± 10) % to (91 ± 6) % when factoring in isotope enrichment due to partial reduction of N 2 O to N 2 during denitrification. Reducing uncertainty in source signatures will increase the power of ice core N 2 O isotope records in deducing environmental change.

54 ENVIRONMENTAL SCIENCES↗

Dissolved Organic Carbon in Coastal Waters: Global Patterns, Stocks and Environmental Physical Controls

Abstract Dissolved organic carbon (DOC) in coastal waters is integral to biogeochemical cycling, but global and regional drivers of DOC are still uncertain. In this study we explored spatial and temporal differences in DOC concentrations and stocks across the global coastal ocean, and how these relate to temperature and salinity. We estimated a global median coastal DOC stock of 3.15 Pg C (interquartile range (IQR) = 0.85 Pg C), with median DOC concentrations being 2.2 times higher than in open ocean surface waters. Globally and seasonally, salinity was the main driver of DOC with concentrations correlated negatively with salinity, without a clear relationship to temperature. DOC concentrations and stocks varied with region and season and this pattern is likely driven by riverine inputs of DOC and nutrients that stimulate coastal phytoplankton production. Temporally, high DOC concentrations occurred mainly in months with high freshwater input, with some exceptions such as in Eastern Boundary Current margins where peaks are related to primary production stimulated by nutrients upwelled from the adjacent ocean. No spatial trend between DOC and temperature was apparent, but many regions (19 out of 25) had aligned peaks of seasonal temperature and DOC, related to increased phytoplankton production and vertical stratification at high temperatures. Links of coastal DOC with salinity and temperature highlight the potential for anthropogenic impacts to alter coastal DOC concentration and composition, and thereby ecosystem status.

Lønborg, Christian [Section for Marine Diversity a↗