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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 343 records · Page 19
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NASA NTRS1994

Consequences of magnetotail ion dynamics

The trajectories of a large ensemble of particles are calculated in a modified Tsyganenko magnetic field model with a uniform cross-tail electric field. The model magnetotail can be divided into several distinct dynamical regimes of ion motion. Near Earth, where the field lines are dipolar the adiabatic formalism is adequate. In the mid-tail and distant tail, guiding-center theory breaks down and must be replaced by a quasi-adiabatic formalism. There is an important transition region between the adiabatic and quasi-adiabatic regions where ion trajectories become more complicated and no simple analytical description holds. This wall region is characterized by rapid ion acceleration and a major loss of particles to the dusk flank. The moments of the ion distribution function are constructued from the ion trajectories, including density, temperature, and pressure in the x-z and x-y planes. In the noon-midnight meridian plane, parameters are relatively constant except near the Earth, while the x-y plots show strong gradients across the magnetotail. Magnetotail plasma convects earthward, drifts toward dusk, and is squeezed out of the tail in the near-Earth region. A thin current sheet forms in the quasi-adiabatic region, and the pressure tensor has significant off-diagonal terms at its edges. These terms are the result of quasi-adiabatic ion trajectories which lead to azimuthally asymmetric distribution functions capable of maintaining approximate stress balance across the current sheet. Simplified analytical descriptions provide further physical insight into ion dynamics that are observed.

Ashour-Abdalla, Maha↗
DOE OSTI2025

Pangenomes suggest ecological-evolutionary responses to experimental soil warming

ABSTRACT Below-ground carbon transformations that contribute to healthy soils represent a natural climate change mitigation, but newly acquired traits adaptive to climate stress may alter microbial feedback mechanisms. To better define microbial evolutionary responses to long-term climate warming, we study microorganisms from an ongoing in situ soil warming experiment where, for over three decades, temperate forest soils are continuously heated at 5°C above ambient. We hypothesize that across generations of chronic warming, genomic signatures within diverse bacterial lineages reflect adaptations related to growth and carbon utilization. From our bacterial culture collection isolated from experimental heated and control plots, we sequenced genomes representing dominant taxa sensitive to warming, including lineages of Actinobacteria, Alphaproteobacteria, and Betaproteobacteria. We investigated genomic attributes and functional gene content to identify signatures of adaptation. Comparative pangenomics revealed accessory gene clusters related to central metabolism, competition, and carbon substrate degradation, with few functional annotations explicitly associated with long-term warming. Trends in functional gene patterns suggest genomes from heated plots were relatively enriched in central carbohydrate and nitrogen metabolism pathways, while genomes from control plots were relatively enriched in amino acid and fatty acid metabolism pathways. We observed that genomes from heated plots had less codon bias, suggesting potential adaptive traits related to growth or growth efficiency. Codon usage bias varied for organisms with similar 16S rrn operon copy number, suggesting that these organisms experience different selective pressures on growth efficiency. Our work suggests the emergence of lineage-specific trends as well as common ecological-evolutionary microbial responses to climate change. IMPORTANCE Anthropogenic climate change threatens soil ecosystem health in part by altering below-ground carbon cycling carried out by microbes. Microbial evolutionary responses are often overshadowed by community-level ecological responses, but adaptive responses represent potential changes in traits and functional potential that may alter ecosystem function. We predict that microbes are adapting to climate change stressors like soil warming. To test this, we analyzed the genomes of bacteria from a soil warming experiment where soil plots have been experimentally heated 5°C above ambient for over 30 years. While genomic attributes were unchanged by long-term warming, we observed trends in functional gene content related to carbon and nitrogen usage and genomic indicators of growth efficiency. These responses may represent new parameters in how soil ecosystems feedback to the climate system.

Choudoir, Mallory J. (ORCID:0000000291175150)↗
NASA NTRS1927

Approximations for column effect in airplane wing spars

The significance attaching to "column effect" in airplane wing spars has been increasingly realized with the passage of time, but exact computations of the corrections to bending moment curves resulting from the existence of end loads are frequently omitted because of the additional labor involved in an analysis by rigorously correct methods. The present report represents an attempt to provide for approximate column effect corrections that can be graphically or otherwise expressed so as to be applied with a minimum of labor. Curves are plotted giving approximate values of the correction factors for single and two bay trusses of varying proportions and with various relationships between axial and lateral loads. It is further shown from an analysis of those curves that rough but useful approximations can be obtained from Perry's formula for corrected bending moment, with the assumed distance between points of inflection arbitrarily modified in accordance with rules given in the report. The discussion of general rules of variation of bending stress with axial load is accompanied by a study of the best distribution of the points of support along a spar for various conditions of loading.

Warner, Edward P↗
DOE OSTI2021

Operating Stresses and Their Effects on Degradation of LSM-Based SOFC Cathodes

The performance of solid oxides fuel cells (SOFCs) with four different Mn excess of lanthanum strontium manganite (LSM) -based cathodes were examined under different temperatures (1,000 °C, 900 °C), current densities (0, 380, and 760 mA cm -2 ), and cathode atmospheres (p O 2 )=0.1,0.15,0.21) for durations ranging from 58 to 1,008 h. Each yttria-stabilized zirconia (YSZ) electrolyte-supported “button” cell had a porous Ni/YSZ composite anode and a porous LSM/YSZ composite cathode. The cells’ output voltage versus time were recorded and electrochemical impedance spectroscopy (EIS) and linear sweep voltammetry (LSV) measurements were performed every 24 hours. The total area specific resistance (ASR) was calculated from these measurements. The values of ASR from both EIS and LSV were comparable between each other but lower than that from durability test. Distribution of relaxation times (DRT) analysis was performed to investigate the electrochemical processes and their corresponding relaxation frequencies as well as their attributions to the total ASR. The series resistance and parallel resistance that obtained from the equivalent circuit fit of the Nyquist plot were higher at low temperature and low p O 2 regardless of LSM compositions. The area of the peaks derived from DRT analysis increased with time during individual tests. The microstructures of the tested cells were examined using scanning electron microscopy and energy-dispersive x-ray spectroscopy (SEM/EDS). Manganese oxide particles were observed near the cathode-electrolyte interface after prolonged (1,008 h) testing in air of a cell with LSM of 11% manganese excess, and after a short test (58 h) under low oxygen (p O 2 = 0.10) in a cell with LSM of 5% manganese excess. However, the role of MnOx in cell degradation is still unknown.

08 HYDROGEN↗
DOE OSTI2018

Quantitative phosphoproteomics reveals GTBP-1 regulating C.elegans lifespan at different environmental temperatures

Highlights: • Comprehensive quantitative phosphoproteomics study of C.elegans during aging under different temperatures. • Phosphoproteomics analysis identified important proteins and signaling pathways. • The kinases CK2, MAPK and CAMK2 might play important roles in aging. • Functional experiments confirm that GTBP-1 could regulate C.elegans lifespan. • An important resource for future studies of protein phosphorylation in C.elegans. Temperature is one of the primary environmental factors that affect aging, in which protein phosphorylation is an important regulator. Currently, the understanding of phosphorylation events in regulatory networks during aging has remained rather limited. Herein, the phosphoproteomes of C.elegans of different age groups cultured at 20 °C (natural aging) and 25 °C (accelerated aging) were analyzed. Through using the iTRAQ-labeled phosphoproteomics method, 2375 phosphoproteins and 9063 phosphosites were identified. Volcano plots illustrated that 208 proteins during natural aging and 130 proteins during accelerated aging, were significantly changed. Gene ontology and pathway analysis revealed that these proteins were mainly involved in translation, development, metabolisms, and animal behavior processes. Moreover, our results uncovered those kinases CK2, MAPK and CAMK2 might play important roles in aging regulation. Functional experiments confirm that the candidated phosphoprotein GTBP-1 could regulate C.elegans lifespan at 20 °C or 25 °C and is more resistant to heat and oxidative stresses. In summary, our results provided an important resource for future studies of protein phosphorylation in worms. Data are available via ProteomeXchange with identifier PXD009661.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Effect of elevation, season and accelerated snowmelt on biogeochemical processes during isolated conifer needle litter decomposition

Increased drought and temperatures associated with climate change have implications for ecosystem stress with risk for enhanced carbon release in sensitive biomes. Litter decomposition is a key component of biogeochemical cycling in terrestrial ecosystems, but questions remain regarding the local response of decomposition processes to climate change. This is particularly complex in mountain ecosystems where the variable nature of the slope, aspect, soil type, and snowmelt dynamics play a role. Hence, the goal of this study was to determine the role of elevation, soil type, seasonal shifts in soil moisture, and snowmelt timing on litter decomposition processes. Experimental plots containing replicate deployments of harvested lodgepole and spruce needle litter alongside needle-free controls were established in open meadows at three elevations ranging from 2,800–3,500 m in Crested Butte, Colorado. Soil biogeochemistry variables including gas flux, porewater chemistry, and microbial ecology were monitored over three climatically variable years that shifted from high monsoon rains to drought. Results indicated that elevation and soil type influenced baseline soil biogeochemical indicators; however, needle mass loss and chemical composition were consistent across the 700 m elevation gradient. Rates of gas flux were analogously consistent across a 300 m elevation gradient. The additional variable of early snowmelt by 2–3 weeks had little impact on needle chemistry, microbial composition and gas flux; however, it did result in increased dissolved organic carbon in lodgepole porewater collections suggesting a potential for aqueous export. In contrast to elevation, needle presence and seasonal variability of soil moisture and temperature both played significant roles in soil carbon fluxes. Furthermore, during a pronounced period of lower moisture and higher temperatures, bacterial community diversity increased across elevation with new members supplanting more dominant taxa. Microbial ecological resilience was demonstrated with a return to pre-drought structure and abundance after snowmelt rewetting the following year. These results show similar decomposition processes across a 700 m elevation gradient and reveal the sensitivity but resilience of soil microbial ecology to low moisture conditions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Measurements of a single lateral jet injected into swirling crossflow

Experiments have been conducted to document the time-mean and turbulent flowfield of a deflected turbulent jet in a confined swirling crossflow. The jet-to-crossflow velocity ratio of 4 was investigated with swirler vane angles of 45 and 70 degrees. A six-orientation single hot-wire technique was used to measure the velocities and turbulence properties of the flow. In addition, a five-hole pitot probe technique was used to measure the time-mean velocities or verification purposes. The results are presented in the form of r-x plots to aid visualization of the fully three-dimensional flowfield. The swirl in the crossflow intensified the local velocity at the location of the injected jet, which effectively reduced the jet-to-crossflow velocity ratio. This caused the trajectory of the injected jet to follow the path of the local flow direction of the crossflow, and reduce its penetration into the crossflow. The time-mean velocity measurements using the hot-wire corresponded to pitot-probe data obtained in identical flow conditions. Turbulence stress data show the same trends as previous swirl flow data without lateral injection. The lateral jet was found to deflect the axis of the precessing vortex core.

Ong, L. H.↗
DOE OSTI2022

Auto-generating databases of Yield Strength and Grain Size using ChemDataExtractor

Abstract The emerging field of material-based data science requires information-rich databases to generate useful results which are currently sparse in the stress engineering domain. To this end, this study uses the’materials-aware’ text-mining toolkit, ChemDataExtractor, to auto-generate databases of yield-strength and grain-size values by extracting such information from the literature. The precision of the extracted data is 83.0% for yield strength and 78.8% for grain size. The automatically-extracted data were organised into four databases: a Yield Strength, Grain Size, Engineering-Ready Yield Strength and Combined database. For further validation of the databases, the Combined database was used to plot the Hall-Petch relationship for, the alloy, AZ31, and similar results to the literature were found, demonstrating how one can make use of these automatically-extracted datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bootstrapping a stress-tensor form factor through eight loops

We bootstrap the three-point form factor of the chiral stress-tensor multiplet in planar $\mathcal{N}$ = 4 supersymmetric Yang-Mills theory at six, seven, and eight loops, using boundary data from the form factor operator product expansion. This may represent the highest perturbative order to which multi-variate quantities in a unitary four-dimensional quantum field theory have been computed. In computing this form factor, we observe and employ new restrictions on pairs and triples of adjacent letters in the symbol. We provide details about the function space required to describe the form factor through eight loops. Plotting the results on various lines provides striking numerical evidence for a finite radius of convergence of perturbation theory. By the principle of maximal transcendentality, our results are expected to give the highest weight part of the gg → Hg and H → ggg amplitudes in the heavy-top limit of QCD through eight loops. These results were also recently used to discover a new antipodal duality between this form factor and a six-point amplitude in the same theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Functional but not taxonomic diversity increases productivity of Populus in the southeastern United States

Plant interactions like competition and facilitation impact ecosystem function and resilience. Improving our understanding of the relationships between these interactions and community productivity has important implications for managers of production systems in forestry and agriculture as well as conservation science. Populus spp. are an excellent model system for exploring how inter‐ and intraspecific interactions impact ecosystem functions, such as productivity, in forest plantations. In this study, we compared aboveground productivity of six Populus clones from three different taxa grown in monoclonal and mixed‐clonal plots. The different mixture treatments were intended to experimentally test aboveground biomass response to contrasting levels of taxonomic diversity and functional diversity based on nitrogen use characteristics of Populus clones. We hypothesize that functional diversity would be more important than taxonomic diversity in increasing aboveground productivity of mixed‐clonal plantings compared to monocultures. In addition, a subset of treatments was carried out on additional sites representing a productivity gradient in order to determine if the relationship between biodiversity and productivity in these systems diminished at more productive sites as suggested by the stress‐gradient hypothesis. We found that functionally diverse mixtures of clones had greater yield of aboveground biomass than the average of their constituent monocultures, while more taxonomically diverse mixes of clones did not differ from the average of their constituent monocultures. However, when reestablished on sites with extremely high or low productivity, the best performing clone mixture also did not differ from the average of its constituent monocultures. Our results suggest that intimate clone mixtures of Populus have the potential to significantly increase productivity, but results vary by mixture and by site. To capitalize on positive biodiversity effects on yield in production systems, targeted mixtures based on divergent functional traits linked to different use and acquisition strategies for site‐specific limiting resources are most likely to be successful.

BEF↗
NASA NTRS2001

Organization of P, S, and Fe Inclusions in a Freshwater Magnetococcus

Magnetotactic bacteria are a heterogeneous group of motile, mainly aquatic procaryotes that align and swim along geomagnetic field lines. They are of interest to astrobiologists because of the magnetite crystals found in the Mars meteorite ALH84001 which share many characteristics with the magnetite produced intracellularly by magnetotactic bacteria. These bacteria are diverse morphologically, physiologically and phylogenetically, sharing a few key characteristics: 1) the presence of intracellular membrane-bound magnetic crystals (magnetosomes), usually but not always arranged in chains; 2) motility by means of flagella; and 3) microaerophillic or anaerobic physiology. The bilophotrichous (having two flagella bundles) magnetotactic cocci (MC) are ubiquitous in aquatic habitats but have proven extremely difficult to cultivate. Because only several marine strains have been isolated and grown in axenic culture, little is known about the physiology and the biogeochemical roles of the MC. We studied the composition and distribution of intracellular structures in an uncultured MC, designated ARB-1. To do this, a combination of light microscopy, environmental scanning electron microscopy (ESEM), transmission electron microscopy (TEM) and energy dispersive X-ray spectroscopy (EDS) were used. Cells of ARB-1 were separated from sediments collected from Baldwin Lake (Los Angeles Arboretum, Arcadia, CA). They are large spherical to oblate spheroidal Gram-negative cells, ranging from 1 to 4 micrometers along the maximum dimension, which is perpendicular to the direction of swimming. Cells have two large phosphorus-containing inclusions that comprise a large percentage of the cell volume. Many smaller sulfur inclusions are located at the convex end of the cell. Most of the cellular Fe is present in the magnetosomes. These may be arranged as a clump at the concave end of the cell, near the two flagella bundles, or as chains, or as both a clump and chains. The magnetosomes were identified as magnetite (Fe3O4) by selected area electron diffraction (SAED) and high resolution TEM. We saw a trend between cell size and organization of the magnetosomes. Smaller, more spherical cells were more likely to have chains than were larger, more oblate cells. This may indicate different populations of cells, or it may be attributed to variations in cell growth cycle. The size distribution (length) of magnetosomes in chains was similar to that of magnetosomes in clusters, except that there was a larger size range for clustered magnetosomes. Magnetosomes from ARB-1 cells average 82 nm in length. If plotted on a graph of length as a function of aspect ratio, they fall within the single domain region of the plot. If compared with the size distributions of magnetite from ALH84001 and magnetosomes from the cultured magnetotactic vibrio MV-1, the magnetites produced by ARB-1 cells are, on average, larger and have a wider range of aspect ratio. ARB-1 cells have a specific organization of the P, S, and Fe inclusions. The P inclusions always occupy the majority of the cell volume and separate the S inclusions from the disorganized clumps of magnetosomes and the flagella bundles. The P inclusions may contain polyphosphate, which could play several roles in motility, adaptation to stress, growth and division, buoyancy, and energy. The S inclusions might be a way to store S, a potential energy source, when the cells move from sulfide to oxygen zones. The consistency of P, S, and Fe organization in ARB-1 cells suggests that these inclusions have some specific and interactive functions.

Cox, Lea↗
DOE OSTI2026

An uncertainty visualization framework for large-scale cardiovascular flow simulations: A case study on aortic stenosis

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework combines EasyVVUQ for parameter sampling with large-eddy simulation turbulence modeling in HemeLB, and executes ensembles on the Frontier exascale supercomputer. Spatially resolved metrics, including entropy and isosurface-crossing probability, are used to map uncertainty in pressure and wall shear stress fields directly onto vascular geometries. Two sources of model variability are examined: inlet peak velocity and the Smagorinsky constant. Inlet velocity variation produces high uncertainty downstream of the stenosis where turbulence develops, while upstream regions remain stable. Smagorinsky constant variation has little effect on the large-scale pressure field but increases WSS uncertainty in localized high-shear regions. In both cases, the stenotic throat manifests low entropy, indicative of robust identification of elevated WSS. By linking quantitative UQ measures to three-dimensional anatomy, the framework improves interpretability over conventional 1D UQ plots and supports clinically relevant decision-making, with broad applicability to vascular flow problems requiring both accuracy and spatial insight.

Hemodynamics↗
DOE OSTI2023

Final-stage densification kinetics of direct current–sinteredZrB2

Final-stage sintering was analyzed for nominally phase pure zirconium diboride synthesized by borothermal reduction of high-purity ZrO2. Analysis was conducted on ZrB2 ceramics with relative densities greater than 90% using the Nabarro–Herring stress–directed vacancy diffusion model. Temperatures of 1900°C or above and an applied uniaxial pressure of 50 MPa were required to fully densify ZrB2 ceramics by direct current sintering. Ram travel data were collected and used to determine the relative density of the specimens during sintering. Specimens sintered between 1900 and 2100°C achieved relative densities greater than 97%, whereas specimens sintered below 1900°C failed to reach the final stage of sintering. The average grain size ranged from 1.0 to 14.7 μm. The activation energy was calculated from the slope of an Arrhenius plot that used the Kalish equation. The activation energy was 162 ± 34 kJ/mol, which is consistent with the activation energy for dislocation movement in ZrB2. The diffusion coefficients for dislocation motion that controls densification were 5.1 × 10−6 cm2/s at 1900°C and 5.1 × 10−5 cm2/s at 2100°C, as calculated from activation energy and average grain sizes. This study provides evidence that the dominant mechanism for final-stage sintering of ZrB2 ceramics is dislocation motion.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Comparison of predicted and measured elastohydrodynamic film thickness in a 20-millimeter-bore ball bearing

Elastohydrodynamic film thicknesses were measured for a 20-mm bore ball bearing using the capacitance technique. The bearing was thrust loaded to 90, 445, and 778 N (20, 100, and 175 lb). The corresponding maximum contact stress on the inner race was 1.28, 2.09, and 2.45 GPa (185 000, 303,000, and 356, 000 psi). Test speeds ranged from 400 to 15,000 rpm. Measurements were taken with four different lubricants: (1) synthetic paraffinic; (2) synthetic paraffinic with additives; (3) synthetic type II aircraft oil; and (4) synthetic cycloaliphatic hydrocarbon traction fluid. The test bearing was mist lubricated. Test temperatures were 27, 65, and 121 C (80, 150, and 250 F). The measured results for the various test parameters were compared to theoretical predictions from computer programs. Also the data were plotted on dimensionless coordinates and compared to several classical isothermal theories.

Coy, J. J.↗
NASA NTRS1986

Analysis of a resistance-energy balance method for estimating daily evaporation from wheat plots using one-time-of-day infrared temperature observations

Accurate estimates of evaporation over field-scale or larger areas are needed in hydrologic studies, irrigation scheduling, and meteorology. Remotely sensed surface temperature might be used in a model to calculate evaporation. A resistance-energy balance model, which combines an energy balance equation, the Penman-Monteith (1981) evaporation equation, and van den Honert's (1948) equation for water extraction by plant roots, is analyzed for estimating daily evaporation from wheat using postnoon canopy temperature measurements. Additional data requirements are half-hourly averages of solar radiation, air and dew point temperatures, and wind speed, along with reasonable estimates of canopy emissivity, albedo, height, and leaf area index. Evaporation fluxes were measured in the field by precision weighing lysimeters for well-watered and water-stressed wheat. Errors in computed daily evaporation were generally less than 10 percent, while errors in cumulative evaporation for 10 clear sky days were less than 5 percent for both well-watered and water-stressed wheat. Some results from sensitivity analysis of the model are also given.

Choudhury, B. J.↗
DOE OSTI2025

Mortality correlates with tree functional traits across a wood density gradient in the Central Amazon

Introduction: Understanding the mechanisms of tree mortality in tropical ecosystems remains challenging, in part due to the high diversity of tree species and the inherently stochastic nature of mortality. Plant functional traits offer a mechanistic link between plant physiology and performance, yet their ability to predict growth and mortality remains poorly understood. Given recent increases in tree mortality rates in the Amazon forest following extreme drought and wind events, we tested if lower wood density and acquisitive plant functional traits were associated with increased growth and mortality for common co-occurring trees in the Central Amazon. Methods: Seventeen trees of different species with similar sizes but a range in wood density (WD) and wood traits were felled, then assessed for 27 different individual functional parameters, including whole tree architecture, stem xylem anatomical and hydraulic traits and leaf traits. Traits of the individual trees were related to stand-level growth and mortality rates collected periodically over 30 years from nearby permanent inventory plots. Results: Higher wood density was associated with smaller leaf size, lower foliar base cations, lower stem water content and sapwood fraction, in agreement with the fast-slow plant economics spectrum. Lower wood density was associated with more acquisitive characteristics with greater hydraulic capacity and foliar nutrient concentrations, correlating with greater growth and mortality rates. Discussion: Our results show that lower wood density is part of a coordinated suite of traits linked to high resource acquisition, fast growth, and increased mortality risk, providing a functional framework for predicting species performance and forest vulnerability under future climate stress.

demographics↗
DOE OSTI2020

The Consortium for Advanced Sorghum Phenomics (CASP). Final report

The goal of CASP was to accelerate breeding of biomass sorghum [Sorghum bicolor (L.) Moench] by identifying genotypes exhibiting high yield under well-watered, pre- or post-drought and/or salinity-stress conditions. We did this by combining high-throughput, non-invasive drone phenotyping with genomics and molecular profiling. Field-based phenotyping utilized a multi-modal sensor suite of LiDAR, multispectral cameras, and thermal cameras mounted on a commercial drone to detect traits required for yield prediction and selection of drought and saline tolerant lines of sorghum. Traits of interest included plant height (PH), leaf area index (LAI), wet biomass (BMW), and biomass at 65% moisture (BM65) and were measured from emergence to harvest on a weekly basis over three growing seasons. The final output were measurements of traits on a plot-by-plot basis, identified by the plot ID used by the Proprietary data processing software enabled raw field data to be turned into plant traits and delivered to the PNNL and JGI within the same workday.

09 BIOMASS FUELS↗
DOE OSTI2023

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation Inc. that is designed to operate on live cables up to 1000 volts. One of the main conclusions of a previous effort was that cable reflectometry plots can be difficult for humans to analyze due to baseline noise, low or noisy anomaly response peaks, or large responses from cable ends. Detection of cable anomalies for many of these frequencies and test conditions was challenging for manual analysis. This presented an ideal opportunity for ML analysis to distinguish undamaged cable indications from anomalous cable indications. This research discusses application of machine learning (ML) to reflectometry cable test methods. The goal was to assess feasibility to distinguish undamaged cable reflectometry responses from damaged or anomalous cable reflectometry responses. The assessment considered the 3 instruments, multiple frequency bandwidths from each instrument, multiple cable anomalies and test conditions, and both supervised and unsupervised ML approaches. Although approaches and analysis methods were not identical or directly comparable, both outputs were encouraging. The unsupervised prediction weighted accuracy was assessed by instrument and by frequency. It performed better at high frequencies with the highest prediction accuracy of 0.84 for the higher frequency FDR, 0.79 for the 48-MHz LiveWire SSTDR, and 0.77 for 300-MHz PNNL SSTDR. The initial weighted accuracy average across all frequencies for using supervised ML was 0.56 to 0.68. The supervised analysis was repeated with noisier training data removed resulting in weighted accuracies of 0.69 to 0.87. These weighted accuracies are not directly comparable due to differences in the supervised and unsupervised analysis details but do indicate an encouraging trend. Even with limited and unbalanced data, strong prediction accuracies seem encouraging for further work including more data under a wider range of conditions.

42 ENGINEERING↗