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At least 991 records · Page 55

Quantification of Sub-Pixel Dynamics in High-Speed Neutron Imaging

The high penetration depth of neutrons through many metals and other common materials makes neutron imaging an attractive method for non-destructively probing the internal structure and dynamics of objects or systems that may not be accessible by conventional means, such as X-ray or optical imaging. While neutron imaging has been demonstrated to achieve a spatial resolution below 10 μm and temporal resolution below 10 μs, the relatively low flux of neutron sources and the limitations of existing neutron detectors have, until now, dictated that these cannot be achieved simultaneously, which substantially restricts the applicability of neutron imaging to many fields of research that could otherwise benefit from its unique capabilities. In this work, we present an attenuation modeling approach to the quantification of sub-pixel dynamics in cyclic ensemble neutron image sequences of an automotive gasoline direct injector at a 5 μs time scale with a spatial noise floor in the order of 5 μm.

47 OTHER INSTRUMENTATION↗

Studies of Disks Around the Sun and Other Stars

This is a NASA Origins of Solar Systems research program, and this NASA Headquarters grant has now been transferred to a new grant at NASA GSFC (NAG5-4082). Thus the need for this 'Final Report' on a project that is not, in fact, complete. We are conducting research designed to enhance our understanding of the evolution and detectability of comet clouds and disks. This area holds promise for also improving our understanding of outer solar system formation, the bombardment history of the planets, the transport of volatiles and organics from the outer solar system to the inner planets, and to the ultimate fate of comet clouds around the Sun and other stars. According to "standard" theory, both the Kuiper Belt and the Oort Cloud are (at least in part) natural products of the planetary accumulation stage of solar system formation. One expects such assemblages to be a common attribute of other solar systems. Our program consists of modeling collisions in the Kuiper Belt and the dust disks around other stars. The modeling effort focuses on moving from our simple, first-generation, Kuiper Belt collision rate model, to a time-dependent, second-generation model that incorporates physical collisions, velocity evolution, dynamical erosion, and various dust transport mechanisms. This second generation model is to be used to study the evolution of surface mass density and the object-size spectrum in the disk.

Stern, S. Alan↗

A Historic View of Solar Coronal Mass Ejections (CMEs)

We present a historic overview of CME observations, ending with concepts for future measurement capabilities. One of the first detections of what we now call a CME was provided by instrumentation on OSO-7 and reported by Tousey (1973); but the phrase "corona) mass ejection" was coined after the Skylab/ATM coronagraph detected dozens of the transients over its nine month observing run (e.g., Munro et al., 1979). Pre-discovery identification of likely CMEs were then reported in historic eclipse photographs and drawings (e.g., Eddy, 1974; Cliver, 1989). Multi-year observations followed with groundbased MLSO MK3/4 coronagraph (1980-present), and spacebased missions: Solwind (1979-1985), SMM (1980-1989), SOHO LASCO/EIT (1996-present), SMEI (2003-present), and STEREO SECCHI (2006-present). The Spartan 201 coronagraph flew in space multiple times. The influential Gosling (1993) "solar flare myth" manuscript identified CMEs as the cause of the most severe geomagnetic storms, thus cementing their importance in Sun-Earth connection studies. A new window into CMEs was opened with the launch of SOHO in 1995 when the UVCS spectrometer began returning plasma diagnostics of a significant number of events (e.g., Ciaravella et al., 2006). What about the future for CME research? Statistical properties of the UVCS CME observations are forthcoming; the STEREO mission should continue to return views of CMEs from unique vantage points; and the recent launch of SDO should provide new insights into the small spatial scale dynamics of activity associated with CMEs. Several new observing techniques have been demonstrated at total eclipses, and inclusion on spacebased platforms in the future could also prove valuable for understanding CMEs. A common element of several recent proposals is to image the white-light corona with extremely high spatial resolution. The momentary glimpses of the corona during total solar eclipses have shown fine structure that is not captured by global models, and dynamics of these structured elements may be important to resolve the question of CME initiation.

SaintCyr, Orville C.↗

Neural Image Compression: Generalization, Robustness, and Spectral Biases

Recent advances in neural image compression (NIC) have resulted in models which are starting to outperform traditional codecs. While this has led to growing excitement about using these methods in real-world applications, the successful adoption of any machine learning system (including NIC) in the wild requires it to generalize (and be robust) to unseen distribution shifts at deployment time. Unfortunately, current research lacks comprehensive datasets and informative tools to evaluate and understand compression performance in real-world settings. To bridge this crucial gap, first, this paper presents a comprehensive benchmark suite to evaluate the out-of-distribution (OOD) performance of image compression methods. Specifically, we design CLIC-C and Kodak-C by introducing 15 common corruptions to popular CLIC and Kodak benchmarks. Next, we propose spectrally inspired introspection tools to gain a deeper understanding of errors introduced by image compression methods as well as their OOD performance. To this end, we carry out a detailed performance comparison of the classical codec with various variants of NIC (e.g., original, variable rate, pruned), revealing intriguing findings that challenge our current understanding of the strengths and limitations of NIC. Finally, we corroborate our empirical findings with theoretical analysis, providing an in-depth view of the OOD performance of NIC. Our benchmarks, spectral introspection tools, and findings provide a crucial bridge to the real-world adoption of NIC. We hope that our work will propel future efforts in designing more robust and generalizable NIC methods.

neural networks, Variational Autoencoder, robustne↗

Modeling and Simulation of Austenitic Welds and Coarse-grained Specimens: Part II

The Pacific Northwest National Laboratory (PNNL) is conducting confirmatory research for the U.S. Nuclear Regulatory Commission (NRC) to evaluate commercially available nondestructive examination (NDE) modeling and simulation software used in the nuclear industry. Simulation results from ultrasonic testing (UT) models can inform the design and qualification of inspection techniques and help interpret inspection results. CIVA is a modeling and simulation package developed by the French Alternative Energies and Atomic Energy Commission (CEA). CIVA was selected for this study because it is readily available and has been used for NDE in the US commercial nuclear power industry. This report is focused on completing the efforts initiated in the previous PNNL report to evaluate UT modeling and simulation performance, reliability, and accuracy in relation to common inservice inspection (ISI) scenarios in nuclear power plants (NPP). This work will be used to provide guidance when establishing methods to perform and evaluate simulations for more standardized model implementation, simulation analysis, and interpretation of results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Offshore reanalysis wind speed assessment across the wind turbine rotor layer off the United States Pacific coast

Abstract. The California Pacific coast is characterized by considerable wind resource and areas of dense population, propelling interest in offshore wind energy as the United States moves toward a sustainable and decarbonized energy future. Reanalysis models continue to serve the wind energy community in a multitude of ways, and the need for validation in locations where observations have been historically limited, such as offshore environments, is strong. The U.S. Department of Energy (DOE) owns two lidar buoys that collect wind speed observations across the wind turbine rotor layer along with meteorological and oceanographic data near the surface to characterize the wind resource. Lidar buoy data collected from recent deployments off the northern California coast near Humboldt County and the central California coast near Morro Bay allow for validation of commonly used reanalysis products. In this article, wind speeds from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), the Climate Forecast System version 2 (CFSv2), the North American Regional Reanalysis (NARR), the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), and the analysis system of the Rapid Refresh (RAP) are validated at heights within the wind turbine rotor layer ranging from 50 to 100 m. The validation results offer guidance on the performance and uncertainty associated with utilizing reanalyses for offshore wind resource characterization, providing the offshore wind energy community with information on the conditions that lead to reanalysis error. At both California coast locations, the reanalyses tend to underestimate the observed rotor-level wind resource. Occasions of large reanalysis error occur in conjunction with stable atmospheric conditions, wind speeds associated with peak turbine power production (> 10 m s−1), and mischaracterization of the diurnal wind speed cycle in summer months.

17 WIND ENERGY↗

Persistent neural activity in head direction cells

Many neurons throughout the rat limbic system discharge in relation to the animal's directional heading with respect to its environment. These so-called head direction (HD) cells exhibit characteristics of persistent neural activity. This article summarizes where HD cells are found, their major properties, and some of the important experiments that have been conducted to elucidate how this signal is generated. The number of HD and angular head velocity cells was estimated for several brain areas involved in the generation of the HD signal, including the postsubiculum, anterior dorsal thalamus, lateral mammillary nuclei and dorsal tegmental nucleus. The HD cell signal has many features in common with what is known about how neural integration is accomplished in the oculomotor system. The nature of the HD cell signal makes it an attractive candidate for using neural network models to elucidate the signal's underlying mechanisms. The conditions that any network model must satisfy in order to accurately represent how the nervous system generates this signal are highlighted and areas where key information is missing are discussed.

Non-NASA Center↗

Topic Modeling of NASA Space System Problem Reports: Research in Practice

Problem reports at NASA are similar to bug reports: they capture defects found during test, post-launch operational anomalies, and document the investigation and corrective action of the issue. These artifacts are a rich source of lessons learned for NASA, but are expensive to analyze since problem reports are comprised primarily of natural language text. We apply topic modeling to a corpus of NASA problem reports to extract trends in testing and operational failures. We collected 16,669 problem reports from six NASA space flight missions and applied Latent Dirichlet Allocation topic modeling to the document corpus. We analyze the most popular topics within and across missions, and how popular topics changed over the lifetime of a mission. We find that hardware material and flight software issues are common during the integration and testing phase, while ground station software and equipment issues are more common during the operations phase. We identify a number of challenges in topic modeling for trend analysis: 1) that the process of selecting the topic modeling parameters lacks definitive guidance, 2) defining semantically-meaningful topic labels requires nontrivial effort and domain expertise, 3) topic models derived from the combined corpus of the six missions were biased toward the larger missions, and 4) topics must be semantically distinct as well as cohesive to be useful. Nonetheless,topic modeling can identify problem themes within missions and across mission lifetimes, providing useful feedback to engineers and project managers.

Data Mining↗

Exploring biofiber properties and their influence on biocomposite tensile properties

Biofibers serve as effective reinforcements for neat polylactic acid (PLA) in biocomposites, offering an attractive opportunity to decarbonize the manufacturing sector of the United States by displacing fossil-based reinforcement fibers such as carbon fibers. Also, biofiber production can stimulate economic growth in rural economies, fueling sustainable development. PLA resins are commonly compounded with biofibers to create biocomposites suitable for additive manufacturing. PLA-biofiber composites often exhibit better overall material properties than neat (pure) PLA, but the associations between biofiber properties and the material properties of their biocomposites remain largely unexplored. Hence, this research delves into a comprehensive exploration of diverse biofibers, scrutinizing their physical and chemical attributes, including size, shape, ash content and biochemical composition. The study meticulously analyzes the flow properties of each biofiber and elucidates the ultimate tensile strengths and Young's modulus of corresponding biocomposite samples. Noteworthy correlations between biofiber and biocomposite tensile properties are uncovered, shedding light on critical interrelationships. The study introduces an approach employing regression models to predict the ultimate tensile strength and Young's modulus of biocomposites. These models, validated with a cross-validation technique, exhibit remarkable predictive accuracy, particularly in estimating ultimate tensile strength. © 2024 Oak Ridge National Laboratory managed by UT-Battelle, LLC and The Author(s). Polymer International published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

36 MATERIALS SCIENCE↗

Nanoscale Spatial Distribution of Supported Nanoparticles Controls Activity and Stability in Powder Catalysts for CO Oxidation and Photocatalytic H 2 Evolution

Here we discuss, supported metal nanoparticles are essential components of high-performing catalysts, and their structures are intensely researched. In comparison, nanoparticle spatial distribution in powder catalysts is conventionally not quantified, and the influence of this collective property on catalyst performance remains poorly investigated. Here, we demonstrate a general colloidal self-assembly method to control uniformity of nanoparticle spatial distribution on common industrial powder supports. We quantify distributions on the nanoscale using image statistics and show that the type of nanospatial distribution determines not only the stability, but also the activity of heterogeneous catalysts. Widely investigated systems (Au–TiO 2 for CO oxidation thermocatalysis and Pd–TiO 2 for H 2 evolution photocatalysis) were used to showcase the universal importance of nanoparticle spatial organization. Spatially and temporally resolved microkinetic modeling revealed that nonuniformly distributed Au nanoparticles suffer from local depletion of surface oxygen, and therefore lower CO oxidation activity, as compared to uniformly distributed nanoparticles. Nanoparticle spatial distribution also determines the stability of Pd–TiO 2 photocatalysts, because nonuniformly distributed nanoparticles sinter while uniformly distributed nanoparticles do not. This work introduces new tools to evaluate and understand catalyst collective (ensemble) properties in powder catalysts, which thereby pave the way to more active and stable heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Inferring the Contribution of Microbial Taxa and Organic Matter Molecular Formulas to Ecological Assembly

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTI feat ), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTI feat , we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTI feat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTI feat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTI feat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.

59 BASIC BIOLOGICAL SCIENCES↗

The state of the art for neutron irradiation experiments from the perspective of the High Flux Isotope Reactor (HFIR)

Irradiation experiment campaigns are critical to advancing nuclear energy technologies by providing data on material performance under relevant radiation conditions. Successful irradiation experiments require integrated design efforts that balance technical goals with facility constraints. Here, this paper presents an expert-informed overview of irradiation experiment design at the High Flux Isotope Reactor. It addresses the nuclear materials research and irradiation experiment communities to guide them toward developing technically sound, facility-compatible campaigns. The High Flux Isotope Reactor is a multipurpose reactor supporting isotope production, neutron scattering, and materials testing. Its high, steady-state neutron flux is ideal for irradiation experiments, but successful execution demands coordinated thermal, structural, and reactor physics analyses. The paper outlines the complete development workflow from concept definition and design optimization to safety qualification and post-irradiation examination. Standardized capsule platforms are also discussed in terms of flexibility, specimen capacity, and thermal performance. Common failure modes such as unanticipated geometric variations, can impact temperature-dose profiles and compromise data reliability. Therefore, detailed thermal modeling and accurate as-built characterization are essential for meaningful post-irradiation data interpretation. Key recommendations include early engagement all stakeholders, clearly defined design expectations, and alignment of specimen geometries with post-irradiation examination capabilities. This approach reduces design iterations, enhances data quality, and supports more efficient use of irradiation resources. Strategic and well-planned irradiation testing not only improves individual campaign success but also accelerates the deployment of advanced nuclear technologies. By closing critical data gaps and reducing development risks, the nuclear materials community can more effectively contribute to the future of clean, resilient energy systems.

Experiments↗

Predictive Models and Novel Accelerated Tests for the Reliability of Cell Metallization in Photovoltaic Modules (Final Report)

Studies of metallization corrosion m photovoltaics have mainly been limited to comparisons of modules placed in accelerated chambers to fielded modules [1]. Damp Heat accelerated tests and phenomenological equations [2] are used to assess metallization corrosion without understanding the effect of UV light and temperature and humidity cycles on encapsulant adhesion degradation. The roles of encapsulant in-and out-diffusions of moisture and encapsulant impurities are important. Furthermore, few photovoltaic metallization corrosion studies included the role of bias and leakage currents, which are crucial in the electrochemical reaction of metallization. Leakage currents can highly accelerate the corrosion mechanism and are important to include in the studies of corrosion. In our research plan, we will address the following gaps in the PV community's understanding of metallization corrosion: (1) metallization corrosion with bias, humidity, and impurities in the encapsulant or metallization; (2) humidity diffusion through fresh and degraded encapsulants; and (3) comparison of model predictions with outdoor field modules and SunPower's extensive data for its back-contact and front-contact fleets [2] along with NREL's store of >20 year old modules. Our goal is to build models and accelerated tests to predict long term degradation of metallization corrosion of photovoltaic modules in the field. Our studies will include metals used in c-Si solar cells (Cu, Ag, and Al) and commonly used encapsulants (EV A (ethylene vinyl acetate), TPO (thermoplastic olefin), and silicone).

14 SOLAR ENERGY↗

Mechanistic studies of polymeric samples exposed aboard STS 8

The early Shuttle flights and the attendant opportunity to deploy material samples to the near-Earth space environment, along well-defined trajectories and accompanied by detailed characterization of these samples prior to and following the flight exposure, have brought to light several novel phenomena associated with interaction of these materials with the space environment. JPL, in coordination with other NASA Centers, has carried out a research program to study the degradation and oxidation processes caused by interaction of these materials with atomic oxygen at an energy of 5 eV. In addition, energetic atomic oxygen is believed to be responsible for the shuttle glow first observed during the flight of STS-3. The shuttle glow phenomenon has been extensively studied and modeled because of its long-range potential impact on optical communication schemes and its more immediate impact on the Space Telescope. This report summarizes the results of certian material degradation and erosion experiments carried out aboard STS-8 between August 30, 1983 and September 5, 1983. Based on these data, a generic degradation model has been developed for common structural polymers.

Liang, Ranty H.↗

Probabilistic Study Conducted on Sensor-Based Engine Life Calculation

Turbine engine life management is a very complicated process to ensure the safe operation of an engine subjected to complex usage. The challenge of life management is to find a reasonable compromise between the safe operation and the maximum usage of critical parts to reduce maintenance costs. The commonly used "cycle count" approach does not take the engine operation conditions into account, and it oversimplifies the calculation of the life usage. Because of the shortcomings, many engine components are regularly pulled for maintenance before their usable life is over. And, if an engine has been running regularly under more severe conditions, components might not be taken out of service before they exceed their designed risk of failure. The NASA Glenn Research Center and its industrial and academic partners have been using measurable parameters to improve engine life estimation. This study was based on the Monte Carlo simulation of 5000 typical flights under various operating conditions. First a closed-loop engine model was developed to simulate the engine operation across the mission profile and a thermomechanical fatigue (TMF) damage model was used to calculate the actual damage during takeoff, where the maximum TMF accumulates. Next, a Weibull distribution was used to estimate the implied probability of failure for a given accumulated cycle count. Monte Carlo simulations were then employed to find the profiles of the TMF damage under different operating assumptions including parameter uncertainties. Finally, probabilities of failure for different operating conditions were analyzed to demonstrate the importance of a sensor-based damage calculation in order to better manage the risk of failure and on-wing life.

Guo, Ten-Huei↗

A NASA Applied Spaceflight Environments Office Concept

The National Aeronautics and Space Administration (NASA) is launching a bold and ambitious new space initiative. A significant part of this new initiative includes exploration of new worlds, the development of more innovative technologies, and expansion our presence in the solar system. A common theme to this initiative is the exploration of space beyond Low Earth Orbit (LEO). As currently organized, NASA does not have an Agency-level office that provides coordination of space environment research and development. This has contributed to the formation of a gap between spaceflight environments knowledge and the application of this knowledge for multi-program use and for use outside NASA. This paper outlines a concept to establish a NASA-level Applied Spaceflight Environments (ASE) office that will provide coordination and funding for sustained multi-program support in three technical areas that have demonstrated these needs through customer requests. These technical areas are natural environments characterization and modeling, materials and systems analysis and test, and operational space environments modeling. Additionally the ASE office will serve as an entry point of contact for external users who wish to take advantage of data and assets associated with space environments, including space weather. This paper will establish the need for the ASE, discuss a concept for organizational structure and outline the scope in the three technical areas.

Spann, James F.↗

Assessment of Satellite Ocean Colour Radiometry and Derived Geophysical Products

Standardization of methods to assess and assign quality metrics to satellite ocean color radiometry and derived geophysical products has become paramount with the inclusion of the marine reflectance and chlorophyll-a concentration (Chla) as essential climate variables (ECV; [1]) and the recognition that optical remote sensing of the oceans can only contribute to climate research if and when a continuous succession of satellite missions can be shown to collectively provide a consistent, long-term record with known uncertainties. In 20 years, the community has made significant advancements toward that objective, but providing a complete uncertainty budget for all products and for all conditions remains a daunting task. In the retrieval of marine water-leaving radiance from observed top-of-atmosphere radiance, the sources of uncertainties include those associated with propagation of sensor noise and radiometric calibration and characterization errors, as well as a multitude of uncertainties associated with the modeling and removal of effects from the atmosphere and sea surface. This chapter describes some common approaches used to assess quality and consistency of ocean color satellite products and reviews the current status of uncertainty quantification in the field. Its focus is on the primary ocean color product, the spectrum of marine reflectance Rrs, but uncertainties in some derived products such as the Chla or inherent optical properties (IOPs) will also be considered.

Ocean↗