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Results for “Change detection”

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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Detecting tropospheric composition and climate responses to US air pollution controls in the context of internally-arising variability

Since the 1970s, air pollutant emissions controls in the United States (US) have lowered concentrations of ozone (O 3 ) and aerosols, which have opposing radiative effects on surface temperature. Using a pair of initial-condition ensembles generated by a fully-coupled chemistry-climate model, we simulate the “world avoided” by US air pollution controls. In this counterfactual world, we find tropospheric column O 3 increases, robust to natural internal variability, extending across the Northern Hemisphere. Robust aerosol increases, dominated by sulfate, remain localized near the US. Wintertime Northwest Atlantic cloud droplet number concentration is particularly sensitive to US aerosol. While an ensemble mean US surface cooling signal (−0.4 °C) implies that aerosol-driven cooling prevails over any O 3 -induced warming, we find that large regional internal variability will confound its detection in any single transient realization. Larger signal-to-noise ratios for composition versus climate variables underscore the greater detectability of emissions-driven changes in tropospheric composition compared to their associated climate impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Optical pulse-induced ultrafast antiferrodistortive transition in SrTiO 3

The ultrafast dynamics of the antiferrodistortive phase transition in perovskite SrTiO 3 is monitored via time-domain Brillouin scattering. Using femtosecond optical pulses, we initiate a thermally driven tetragonal-to-cubic structural transformation and detect the crystal phase through changes in the frequency of Brillouin oscillations (BO) induced by propagating acoustic phonons. Coupling the measured BO frequency with a spatiotemporal heat diffusion model, we demonstrate that, for a sample kept in the tetragonal phase, deposition of sufficient thermal energy induces a rapid transformation of the heat-affected region to the cubic phase. The initial phase change is followed by a slower reverse cubic-to-tetragonal phase transformation occurring on a timescale of hundreds of picoseconds. Here, we attribute this ultrafast phase transformation in the perovskite to a structural resemblance between atomic displacements of the R-point soft optic mode of the cubic phase and the tetragonal phase, both characterized by anti-phase rotation of oxygen octahedra. The structural relaxation time exhibits a strong temperature dependence consistent with the prediction of the equation of motion describing collective oxygen octahedra rotation based on the energy landscape of the phenomenological Landau theory of phase transitions. Evidence of such a fast structural transition in perovskites can open up new avenues in information processing and energy storage sectors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects

Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. In this study, we developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Dynamics of stellar disc tilting from satellite mergers

The Milky Way’s stellar disc can tilt in response to torques that result from infalling satellite galaxies and their associated tidal debris. In this work, we explore the dynamics of disc tilting by running N-body simulations of mergers in an isolated, isotropic Milky Way-like host galaxy, varying over satellite virial mass, initial position, and orbit. We develop and validate a first-principles understanding of the dynamics that govern how the host galaxy’s stellar disc responds to the satellite’s dark matter (DM) debris. We find that the degree of disc tilting can be large for cosmologically motivated merger histories. In particular, our results suggest that the Galactic disc may still be tilting in response to Gaia-Sausage-Enceladus, one of the most significant recent mergers in the Milky Way’s history. In conclusion, these findings have implications for terrestrial direct detection experiments as disc tilting changes the relative location of the Sun with respect to DM substructure left behind by a merging galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Robust neural network-enhanced estimation of local primordial non-Gaussianity

When applied to the nonlinear matter distribution of the universe, neural networks have been shown to be very statistically sensitive probes of cosmological parameters, such as the linear perturbation amplitude σ 8 . However, when used as a “black box,” neural networks are not robust to baryonic uncertainty. We propose a robust architecture for constraining primordial non-Gaussianity f NL , by training a neural network to locally estimate σ 8 , and correlating these local estimates with the large-scale density field. We apply our method to N-body simulations, and show that σ⁡(f NL ) is 3.5 times better than the constraint obtained from a standard halo-based approach. Finally, we show that our method has the same robustness property as large-scale halo bias: baryonic physics can change the normalization of the estimated f NL , but cannot change whether f NL is detected.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Electric Field Imaging Using Polarized Neutrons

In this paper, we experimentally demonstrate that electrically neutral particles, neutrons, can be used to directly visualize the electrostatic field inside a target volume that can be physically isolated or occupied. Electric field images are obtained using a spin-polarized neutron beam with a recently developed polarimetry method for polychromatic beams that permits detection of a small angular change in spin orientation. This work may enable a new diagnostic technique sensitive to the structure of electric potential, electric polarization, charge distribution, and dielectric constant by imaging spatially dependent electric fields in objects that cannot be accessed by other probes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Multifractal Characterization of Distribution Synchrophasors for Cybersecurity Defense of Smart Grids

“Source ID Mix” spoofing emerged as a new type of cyber-attack on Distribution Synchrophasors (DS) where adversaries have the capability to swap the source information of DS without changing the measurement values. Accurate detection of such a highly-deceptive attack is a challenging task especially when the spoofing attack happens on short fragments of DS recorded within a relatively small geographical scale. Herein this letter proposes an effective approach to detect this cyber-attack by realizing the multifractal characteristics of DS measurements. First, the multifractal cross-correlation of DS measured at multiple intra-state locations is revealed. Then the derived correlation is integrated with weighted two-dimensional multifractal surface interpolation to reconstruct quasi high-resolution signals. Finally, informative location-specific signatures are extracted from the high-resolution DS and they are integrated with advanced machine learning techniques for source authentication. Experiments using the real-life DS are performed to verify the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Electropotential Verification for Nuclear Safeguards

The international safeguards regime desires methods to efficiently verify that facilities are only performing declared activities. Electropotential verification (EPV) is a newly proposed technique that was tested for its feasibility to perform facility design information verification (DIV). EPV works by passing a constant, low voltage current through a conductive system (facility infrastructure of nuclear fuel assembly) and measuring the resulting voltage at various places throughout the infrastructure in order to establish a baseline. Changes made to the system affect these voltage readings, which will deviate from the baseline and indicate that a change to the system was made. For large scale infrastructure such as a nuclear facility DIV, it appears feasible that changes in configuration of the system’s grounding can be detected in real-time, and the location of the change can be inferred from the measured intensity of the change in voltage.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Electropotential Verification for Nuclear Safeguards

The international safeguards regime desires methods to efficiently verify that facilities are only performing declared activities. Electropotential verification (EPV) is a newly proposed technique that was tested for its feasibility to perform facility design information verification (DIV) and verification of spent nuclear fuel while in a cooling pool. EPV works by passing a constant, low voltage current through a conductive system (facility infrastructure of nuclear fuel assembly) and measuring the resulting voltage at various places throughout the infrastructure in order to establish a baseline. Changes made to the system affect these voltage readings, which will deviate from the baseline and indicate that a change to the system was made. For facility DIV, it appears feasible that changes in configuration of the system’s grounding can be detected in real-time, and the location of the change can be inferred from the measured intensity of the change in voltage. Determination of whether or not spent fuel was present in a fuel rod, as well as the presence/absence of a fuel rod from an assembly using EPV, proved unsuccessful with the sensitivity of instrumentation used in this study.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Numerical Simulation of Infrasound Resonance in Underground Tunnel Structures

Remote observation of infrasound resonant signals emanating from underground tunnel structures could potentially allow the remote quantification of the geometry of the underground structures in which the signals were generated. However, the sensitivity of these observations to tunnel geometry and changes in that geometry are unknown. In this report we outline a numerical simulation study with the following three objectives: 1. Can we model infrasound resonance using numerical simulations? 2. What is the sensitivity of the modeled observations to changes in tunnel geometry or boundary conditions? And 3. Can we accurately model resonant observations of explosions occurring in Redmond Salt Mine in Central Utah. In this report we outline affirmative answers to the first two objectives, but we were unable to accurately model the Redmond Explosions due to numerical instability in the model of the complex structure of the mine. Recommendations for future work emphasize the need to acquire additional datasets and to explore a more data-based approach in which changes in data signatures are detected as a first step towards developing a method which inverts resonant infrasound signals for tunnel geometry.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Benchmark Tracking System for Performance Monitoring

Benchmarking is essential for high-performance software development, particularly for monitoring performance across code iterations. This project focused on enhancing the benchmarking process for Lamellar, an asynchronous runtime for High-Performance Computing (HPC) systems developed at Pacific Northwest National Laboratory. Prior to this work, benchmark results were difficult to track and compare across code versions, presenting significant challenges in identifying performance regressions and long-term trends. The primary objective was to establish a systematic, reproducible approach for measuring performance and detecting regressions following code commits. Our methodology involved three key components: standardizing benchmark outputs, implementing data versioning, and developing analysis tools. We standardized the benchmark output format to JSON Line records containing specific fields (execution time, hardware specifications, and environmental variables). To address data management challenges, we evaluated several options and eventually chose a git repository dedicated to benchmark data. We developed a suite of Python tools that processed benchmark results, enriched them with metadata, and facilitated search in the repository. The resulting system enables more efficient filtering and comparison of performance metrics across commit histories, hardware configurations, and benchmark variants through a unified query interface. Our implementation reduces computational overhead by first checking for existing results through configuration matching before initiating new benchmark runs, thereby conserving resources. The system has been validated by Lamellar developers. It organizes results by benchmark type and build configurations for efficient retrieval. Future developments include a planned Large Language Model interface for predicting benchmark performance, incorporating the criterion package for statistical analysis, which will enable automated detection of statistically significant performance changes, and integration with continuous integration pipelines. Despite these enhancements being reserved for future work, this project has successfully provided the Lamellar development team with a framework for maintaining consistent performance standards and identifying optimization opportunities across workloads and hardware environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Investigating Nanoscale Electron Transfer Processes at the Cell-Mineral Interface in Cobalt-Doped Ferrihydrite Using Geobacter sulfurreducens: A Multi-Technique Approach

Cobalt is an essential element for life and plays a crucial role in supporting the drive to clean energy, due to its importance in rechargeable batteries. Co is often associated with Fe in the environment, but the fate of Co in Fe-rich biogeochemically-active environments is poorly understood. To address this, synchrotron-based scanning X-ray microscopy (SXM) was used investigate the behaviour of cobalt at the nanoscale in Co-Fe(III)-oxyhydroxides undergoing microbial reduction. SXM can assess spatial changes in metal speciation and organic compounds helping to elucidate the electron transfer processes occurring at the cell-mineral interface and inform on the fate of cobalt in redox horizons. G. sulfurreducens was used to reduce synthetic Co-ferrihydrite as an analogue of natural cobalt-iron-oxides. Magnetite [Fe(II)/Fe(III) 3 O 4 ] production was confirmed by powder X-ray diffraction (XRD), SXM and X-ray magnetic circular dichroism (XMCD) data, where best fits of the latter suggested Co-bearing magnetite. Macro-scale XAS techniques suggested Co(III) reduction occurred and complementary SXM at the nanoscale, coupled with imaging, found localised biogenic Co(III) reduction at the cell-mineral interface via direct contact with outer membrane cytochromes. No discernible localised changes in Fe speciation were detected in the reordered cobalt-iron-oxides that were formed and at the end point of the experiment only 11% Co and 1.5% Fe had been solubilised. The solid phase retention, alongside the highly localised and preferential cobalt bioreduction observed at the nanoscale is consistent with retention of Co in redox zones. This work improves our fundamental molecular-scale understanding of the fate of Co in complex environmental systems and supports the development of biogenic Co-doped magnetite for industrial applications from drug delivery systems to magnetic recording media.

58 GEOSCIENCES↗
DOE OSTI2024

A multi-omic survey of black cottonwood tissues highlights coordinated transcriptomic and metabolomic mechanisms for plant adaptation to phosphorus deficiency

Phosphorus (P) deficiency in plants creates a variety of metabolic perturbations that decrease photosynthesis and growth. Phosphorus deficiency is especially challenging for the production of bioenergy feedstock plantation species, such as poplars (Populus spp.), where fertilization may not be practically or economically feasible. While the phenotypic effects of P deficiency are well known, the molecular mechanisms underlying whole-plant and tissue-specific responses to P deficiency, and in particular the responses of commercially valuable hardwoods, are less studied. We used a multi-tissue and multi-omics approach using transcriptomic, proteomic, and metabolomic analyses of the leaves and roots of black cottonwood (Populus trichocarpa) seedlings grown under P-deficient (5 µM P) and replete (100 µM P) conditions to assess this knowledge gap and to identify potential gene targets for selection for P efficiency. In comparison to seedlings grown at 100 µM P, P-deficient seedlings exhibited reduced dry biomass, altered chlorophyll fluorescence, and reduced tissue P concentrations. In line with these observations, growth, C metabolism, and photosynthesis pathways were downregulated in the transcriptome of the P-deficient plants. Additionally, we found evidence of strong lipid remodeling in the leaves. Metabolomic data showed that the roots of P-deficient plants had a greater relative abundance of phosphate ion, which may reflect extensive degradation of P-rich metabolites in plants exposed to long-term P-deficiency. With the notable exception of the KEGG pathway for Starch and Sucrose Metabolism (map00500), the responses of the transcriptome and the metabolome to P deficiency were consistent with one another. No significant changes in the proteome were detected in response to P deficiency. Collectively, our multi-omic and multi-tissue approach enabled the identification of important metabolic and regulatory pathways regulated across tissues at the molecular level that will be important avenues to further evaluate for P efficiency. These included stress-mediating systems associated with reactive oxygen species maintenance, lipid remodeling within tissues, and systems involved in P scavenging from the rhizosphere.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry

Since their advent over 2 decades ago, autonomous Argo floats have revolutionized the field of oceanography, and, more recently, the addition of biogeochemical and biological sensors to these floats has greatly improved our understanding of carbon, nutrient, and oxygen cycling in the ocean. While Argo floats offer unprecedented horizontal, vertical, and temporal coverage of the global ocean, uncertainties remain about whether Argo sampling frequency and density capture the true spatiotemporal variability in physical, biogeochemical, and biological properties. As the true distributions of, e.g., temperature or oxygen are unknown, these uncertainties remain difficult to address with Argo floats alone. Numerical models with synthetic observing systems offer one potential avenue to address these uncertainties. Here, we implement synthetic biogeochemical Argo floats into the Energy Exascale Earth System Model version 2 (E3SMv2), which build on the Lagrangian In Situ Global High-Performance Particle Tracking (LIGHT) module in E3SMv2 (E3SMv2-LIGHT-bgcArgo-1.0). Since the synthetic floats sample the model fields at model run time, the end user defines the sampling protocol ahead of any model simulation, including the number and distribution of synthetic floats to be deployed, their sampling frequency, and the prognostic or diagnostic model fields to be sampled. Using a 6-year proof-of-concept simulation, we illustrate the utility of the synthetic floats in different case studies. In particular, we quantify the impact of (i) sampling density on the float-derived detection of deep-ocean change in temperature or oxygen and on float-derived estimates of phytoplankton phenology, (ii) sampling frequency and sea-ice cover on float trajectory lengths and hence float-derived estimates of current velocities, and (iii) short-term variability in ecosystem stressors on estimates of their seasonal variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tackling the Giants: Applying Smart Labs Principles to Constant Air Volume Lab Buildings

Laboratories typically consume 3 to 10 times more energy than similarly sized commercial buildings, and as much as 50% of that energy is wasted by inefficient and poorly operating fume hoods and ventilation systems. One challenge faced by older laboratory buildings is the heating, ventilation, and air-conditioning systems serving many of these buildings. The older systems are usually constant air volume (CAV) systems that maintain constant ventilation rates that cause excess airflow and inefficient energy use. Variable air volume systems can be more efficient systems with sensors to detect the need for a change in volumetric flow rate; however; renovation of ventilation systems can create disruption to ongoing research and operations along with considerable up-front costs. When a Smart Labs program is implemented, an organization has a systems-based management approach that yields a high-performing laboratory building. As decarbonization continues as a priority for sites, buildings with CAV systems are difficult to address. This work centers around practical guidance for improving lab buildings with CAV. In conjunction with industry input on top technology solutions and best practices, recommendations will include performing a laboratory ventilation risk assessment in conjunction with robust retro-commissioning work, which is a crucial step in the Smart Lab process. By applying Smart Labs principles, the aging laboratory building stock of 153,343 (Lawrence Berkeley National Laboratory [LBNL] 2017), comprising roughly 500,000 lab spaces in the United States, can be brought to safe and high-performance operations.

building↗
DOE OSTI2026

Horizontal transfer of chromosomal DNA mediated by an integrative and conjugative element generates frequent localized recombination in Novosphingobium aromaticivorans

Horizontal gene transfer is an important evolutionary process by which DNA is exchanged between cells that are physically co-located but not direct evolutionary descendants. Horizontal transfer of highly divergent DNA is relatively easy to detect and can produce major phenotypic changes, exemplified by the acquisition of antibiotic resistance determinants. However, transfer of high-identity DNA, for example, between strains of the same species, is likely to be more frequent, harder to detect, and highly impactful in aggregate. In this work, we demonstrate that soil isolates of the alphaproteobacterium Novosphingobium aromaticivorans can exchange chromosomal DNA, leading to multiple unselected recombination events spanning approximately 10% of the chromosome. Chromosomal recombination was directional and more efficient near an integrative and conjugative element (ICE), and required a relaxase found in the ICE. Recombination could not be observed in strains from closely related Novosphingobium species. In combination, these results suggest that ICE-mediated recombination can efficiently recombine DNA within N. aromaticivorans, increasing the adaptive potential of the species while also enforcing species boundaries through preferential intraspecific recombination.

Allemann, Marco [ORNL]↗
DOE OSTI2022

Characterization of inexpensive metal oxide sensor performance for trace methane detection

Abstract. Methane, a major contributor to climate change, is emitted by a variety of natural and anthropogenic sources. Commercially available lab-grade instruments for sensing trace methane are expensive, and previous efforts to develop inexpensive, field-deployable trace methane sensors have had mixed results. Industrial and commercial metal oxide (MOx) methane sensors, which are intended for leak detection and safety monitoring, can potentially be repurposed and adapted for low-concentration sensing. As an initial step towards developing a low-cost sensing system, we characterize the performance of five off-the-shelf MOx sensors for 2–10 ppm methane detection in a laboratory setting (Figaro Engineering TGS2600, TGS2602, TGS2611-C00, TGS2611-E00, and Henan Hanwei Electronics MQ4). We identify TGS2611-C00, TGS2611-E00, and MQ4 as promising for trace methane sensing but show that variations in ambient humidity and temperature pose a challenge for the sensors in this application.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Invisible ship tracks show large cloud sensitivity to aerosol

Cloud reflectivity is sensitive to atmospheric aerosol concentrations because aerosols provide the condensation nuclei on which water condenses. Increased aerosol concentrations due to human activity affect droplet number concentration, liquid water and cloud fraction, but these changes are subject to large uncertainties. Ship tracks, long lines of polluted clouds that are visible in satellite images, are one of the main tools for quantifying aerosol–cloud interactions. However, only a small fraction of the clouds polluted by shipping show ship tracks. Here we show that even when no ship tracks are visible in satellite images, aerosol emissions change cloud properties substantially. We develop a new method to quantify the effect of shipping on all clouds, showing a cloud droplet number increase and a more positive liquid water response when there are no visible tracks. We directly detect shipping-induced cloud property changes in the trade cumulus regions of the Atlantic, which are known to display almost no visible tracks. Our results indicate that previous studies of ship tracks were suffering from selection biases by focusing only on visible tracks from satellite imagery. The strong liquid water path response we find translates to a larger aerosol cooling effect on the climate, potentially masking a higher climate sensitivity than observed temperature trends would otherwise suggest.

54 ENVIRONMENTAL SCIENCES↗