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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Probabilistic Modeling of Commercial Building Occupancy Patterns Using Location-Based Map Data: Preprint

Considering occupancy patterns is crucial to simulate buildings' energy use. Current energy models use inputs that simplify the actual diversity in occupancy into static occupancy patterns and are not able to represent the numerous variations in occupancy patterns between buildings and across different locations. Recently, inferring occupancy schedules from metered electricity consumption data was used to model occupancy in commercial buildings. However, the translation from metered data to occupancy schedules requires many assumptions that might not capture the reality, and the process is hindered by the availability of data from advanced metering infrastructure. With the development of information technologies, occupancy modeling should not be limited to traditional approaches. The prevalence of social networks and location services with real-time user feedback provides publicly accessible data via Maps Application Programming Interfaces (APIs) such as Google Maps, SafeGraph, Mapbox, Foursquare, etc. This paper presents an automated framework for modeling parametric occupancy patterns using such APIs to calibrate commercial district buildings' energy models. This process includes three main steps: data extraction and processing, parametric schedules generation, and schedules integration. We demonstrated this framework in districts where we used maps API to generate more accurate behavioral patterns for operations and electric vehicle charging events. We used these patterns to determine differences in energy use across key sociodemographic and spatial parameters. The presented method has the potential for worldwide applications. Users can utilize this framework to extract data for selected locations of interest to create more realistic behavioral patterns for commercial facilities across different districts.

building energy modeling↗
DOE OSTI2021

Classification and computation of extreme events in turbulent combustion

In the design of practical combustion systems, ensuring safety and reliability is an important requirement. For instance, reliably avoiding lean blowout, flame flashback or inlet unstart is critical for ensuring safe operation. Currently, the science of predicting such events is based on prior experience, limited modeling or diagnostic tools and purely statistical approaches. Even though computational and experimental tools for studying combustion devices have vastly advanced in the last three decades, the analysis of such failure events has not been pursued widely. While the use of data for model development and calibration is being widely accepted, the extension to failure events introduces numerous challenges. In particular, the focus here is on so-called data-poor problems, where the cost of generating data is extremely high and is not easily amenable to existing computational and experimental approaches. Data-poor problems are particularly relevant when related to extreme events (also called anomalous events) that can lead to catastrophic failure of the system. It is argued that transient events that describe such failure can have different causal mechanisms. To develop the scientific inference process, a classification of such problems is used to determine specific modeling paths as well as computational tools needed. Research opportunities in the emerging field of extreme event prediction are highlighted in order to identify critical and immediate needs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

Low-Earth Orbit Trajectory Optimization in the Presence of Atmospheric Uncertainty

The previous 20 to 25 years have seen a tremendous increase in space exploration, and with that an increase in the level of logistics planning needed to ensure mission success. For spacecraft that are designed to be periodically re-supplied, a key logistics consumable is propellant, as it constitutes the greatest up-mass on re-supply vehicles. A trajectory design strategy is therefore desired that minimizes propellant usage in order to ease the demand for propellant re-supply missions. This thesis develops such a strategy in three stages, and uses the International Space Station (ISS) as its testbed, as no other LEO spacecraft is more challenging from a space logistics standpoint. First, the ISS trajectory planning problem is formulated as a constrained burn optimization problem assuming a deterministic atmosphere. The cost function is total ∆v, with constraints imposed on longitude of ascending viii node (LAN) and semi-major axis (SMA) altitude. Analytic derivatives are constructed for both the cost and constraints, which are necessary given the 6-week to 2-year time frames being considered. A gradient-based optimizer is then utilized to find locally-optimal solutions to real-world ISS trajectory planning problems. Second, atmospheric uncertainty is addressed by constructing a probabilistic model of space weather data using Gaussian Processes (GPs). Bayesian inference is performed using the GP model to generate mean and covariance estimates for space weather predictions, whose pedigree is assessed against test data. The predictions are then mapped into atmospheric density via the analytic Jacchia-Roberts density model, and the effect of space weather uncertainty on orbital lifetime is examined. Third, an ISS burn execution uncertainty model is developed. This model, along with the space weather uncertainty model, are deployed in a linear covariance analysis to ascertain their combined effect on LAN and SMA altitude dispersions. The deterministic constraints from the original problem are re-formulated as stochastic constraints, where now the constraint uncertainty interval is required to fall within specified bounds. An updated optimization framework is constructed using the original ∆v cost function along with the stochastic constraints to solve the trajectory optimization problem under atmospheric uncertainty. Finally, the complete architecture is summarized for deployment in an operational setting.

Trajectory Optimization↗
DOE OSTI2026

In-Situ TEM Molten Salt Corrosion

Molten salt reactors (MSRs) offer a compelling pathway for next-generation nuclear energy, with advantages in thermal efficiency, inherent safety, and flexible fuel management. Yet, halide-based molten salts introduce significant materials challenges, particularly alloy corrosion. Alloy performance in these environments ultimately depends on understanding how corrosion initiates and progresses at the nanoscale, however most existing models rely on post-exposure characterization, leaving degradation mechanisms largely inferred rather than directly observed. NiCr alloys have garnered interest in MSRs applications as the Ni-based matrix provides strength and creep resistance, while Cr content offers oxidation resistance in air. However, NiCr corrosion resistance in chloride salts has proven poor due to preferential chromium dissolution, the formation of Cr-depleted pathways, and grain-boundary attack. This work aims to directly visualize corrosion of Ni-20Cr exposed to LiCl-KCl using in-situ Transmission Electron Microscopy (TEM) to capture real-time microstructural evolution during corrosion. Experiments will be performed at ~800 °C under controlled pressure conditions while utilizing Energy-Dispersive X-ray Spectroscopy (EDS) to analyze elemental redistribution. Observation of chromium depletion fronts, associated surface restructuring, and localized chloride enrichment are expected. Ultimately, this study is expected to provide a link between microscale processes and the macroscopic degradation behaviors relevant to MSR operation in advanced reactor environments. Simultaneously, this approach enables future in-situ investigations regarding alloy composition, salt chemistry, and their influence on corrosion pathways and long-term stability.?

36 - MATERIALS SCIENCE↗
NASA NTRS1999

10 000-hr Cyclic Oxidation Behavior of 68 High-Temperature Co-, Fe-, and Ni- Base Alloys Evaluated at 982 deg. C (1800 deg. F)

Power systems with operating temperatures in the range of 815 to 982 C (1500 to 1800 F) frequently require alloys that can operate for long times at these temperatures. A critical requirement is that these alloys have adequate oxidation resistance. The alloys used in these power systems require thousands of hours of operating life with intermittent shutdown to room temperature. Intermittent power plant shutdowns, however, offer the possibility that the protective scale will tend to spall (i.e., crack and flake off) upon cooling, increasing the rate of oxidative attack in subsequent heating cycles. Thus, it is critical that candidate alloys be evaluated for cyclic oxidation behavior. It was determined that exposing test alloys to ten 1000-hr cycles in static air at 982 10 000-hr Cyclic Oxidation Behavior of 68 High-Temperature Co-, Fe-, and Ni-Base Alloys Evaluated at 982 C (1800 F) could give a reasonable simulation of long-time power plant operation. Iron- (Fe-), nickel- (Ni-), and cobalt- (Co-) based high-temperature alloys with sufficient chromium (Cr) and/or aluminum (Al) content can exhibit excellent oxidation resistance. The protective oxides formed by these classes of alloys are typically Cr2O3 and/or Al2O3, and are usually influenced by their Cr, or Cr and Al, content. Sixty-eight Co-, Fe-, and Ni-base high-temperature alloys, typical of those used at this temperature or higher, were used in this study. At the NASA Lewis Research Center, the alloys were tested and compared on the basis of their weight change as a function of time, x-ray diffraction of the protective scale composition, and the physical appearance of the exposed samples. Although final appearance and x-ray diffraction of the final scale products were two factors used to evaluate the oxidation resistance of each alloy, the main criterion was the oxidation kinetics inferred from the specific weight change versus time data. These data indicated a range of oxidation behavior including parabolic (typical of isothermal oxidation), paralinear, linear, and mixed-linear kinetics.

Barrett, Charles A.↗
DOE OSTI2024

Revealing Decision Conservativeness Through Inverse Distributionally Robust Optimization

This paper introduces Inverse Distributionally Robust Optimization (I-DRO) as a method to infer the conservativeness level of a decision-maker, represented by the size of a Wasserstein metric-based ambiguity set, from the optimal decisions made using Forward Distributionally Robust Optimization (F-DRO). By leveraging the Karush-Kuhn-Tucker (KKT) conditions of the convex F-DRO model, we formulate I-DRO as a bi-linear program, which can be solved using off-the-shelf optimization solvers. Additionally, this formulation exhibits several advantageous properties. We demonstrate that I-DRO not only guarantees the existence and uniqueness of an optimal solution but also establishes the necessary and sufficient conditions for this optimal solution to accurately match the actual conservativeness level in F-DRO. Furthermore, we identify three extreme scenarios that may impact I-DRO effectiveness. Our case study applies F-DRO for power system scheduling under uncertainty and employs I-DRO to recover the conservativeness level of system operators. Numerical experiments based on an IEEE 5-bus system and a realistic NYISO 11-zone system demonstrate I-DRO performance in both normal and extreme scenarios. An extended version of this paper with additional analyses is available at li2024revealing.

distributionally robust optimization↗
NASA NTRS1995

Fuzzy inference enhanced information recovery from digital PIV using cross-correlation combined with particle tracking

Particle Image Velocimetry provides a means of measuring the instantaneous 2-component velocity field across a planar region of a seeded flowfield. In this work only two camera, single exposure images are considered where both cameras have the same view of the illumination plane. Two competing techniques which yield unambiguous velocity vector direction information have been widely used for reducing the single exposure, multiple image data: cross-correlation and particle tracking. Correlation techniques yield averaged velocity estimates over subregions of the flow, whereas particle tracking techniques give individual particle velocity estimates. The correlation technique requires identification of the correlation peak on the correlation plane corresponding to the average displacement of particles across the subregion. Noise on the images and particle dropout contribute to spurious peaks on the correlation plane, leading to misidentification of the true correlation peak. The subsequent velocity vector maps contain spurious vectors where the displacement peaks have been improperly identified. Typically these spurious vectors are replaced by a weighted average of the neighboring vectors, thereby decreasing the independence of the measurements. In this work fuzzy logic techniques are used to determine the true correlation displacement peak even when it is not the maximum peak on the correlation plane, hence maximizing the information recovery from the correlation operation, maintaining the number of independent measurements and minimizing the number of spurious velocity vectors. Correlation peaks are correctly identified in both high and low seed density cases. The correlation velocity vector map can then be used as a guide for the particle tracking operation. Again fuzzy logic techniques are used, this time to identify the correct particle image pairings between exposures to determine particle displacements, and thus velocity. The advantage of this technique is the improved spatial resolution which is available from the particle tracking operation. Particle tracking alone may not be possible in the high seed density images typically required for achieving good results from the correlation technique. This two staged approach offers a velocimetric technique capable of measuring particle velocities with high spatial resolution over a broad range of seeding densities.

Wernet, Mark P.↗
NASA NTRS1995

Making intelligent systems team players. A guide to developing intelligent monitoring systems

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Land, Sherry A.↗
DOE OSTI2024

Homomorphic Encryption for Electrical Metering Aggregation: Protecting the Privacy of Building Tenants

Electrical meters are devices that measure consumer electricity usage. The data collected by these meters is necessary for utility billing and electrical grid management but can also be used to assess the environmental impact of buildings. Prior research has found that unprotected metering data could potentially be used to infer some information about the behaviors of building tenants by detecting changes in electricity usage. For example, a period of low electricity usage could suggest that the tenants are not in the building. As smart metering becomes more common, there is a growing need for data privacy protections for metering data that do not negatively impact the quality and availability of data used for energy management and billing applications. To identify potential solutions, we developed a Python-based data aggregation platform to analyze the potential efficacy of privacy-enhancing technologies for energy metering applications. This platform aggregates groups of metering sites into virtual buildings, which could potentially detach changes in electrical activity from individual tenants, making it more difficult to track the activity of a specific tenant. To further protect data during analysis, this project utilizes homomorphic encryption as part of its initial approach. Homomorphic encryption offers a means of protecting energy consumption data while permitting mathematical operations to be performed without the need to know the data contents. This allows for data to be processed into usable statistics without revealing energy consumption information. A series of homomorphic encryption libraries were evaluated to determine their applicability and limitations in the context of metering data. The use of these techniques may help to reassure consumers and encourage further adoption of smart grid infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2010

Kepler Planet Detection Mission: Introduction and First Results

The Kepler Mission is designed to determine the frequency of Earth-size and rocky planets in and near the habitable zone (HZ) of solar-like stars. The HZ is defined to be the region of space where a rocky planet could maintain liquid water on its surface. Kepler is the 10th competitively-selected Discovery Mission and was launched on March 6, 2009. Since completing its commissioning, Kepler has observed over 156,000 stars simultaneously and near continuously to search for planets that periodically pass in front of their host star (transit). The photometric precision is approximately 23 ppm for 50% of the 12th magnitude dwarf stars for an integration period of 6.5 hours. During the first 3 months of operation the photometer detected transit-like signatures from more than 200 stars. Careful examination shows that many of these events are false-positives such as small stars orbiting large stars or blends of target stars with eclipsing binary stars. Ground-based follow-up observations confirm the discovery of five new exoplanets with sizes between 0.37 andl.6 Jupiter radii (R(sub J)) and orbital periods ranging from 3.2 to 4.9 days. Ground-based observations with the Keck 1, Hobby-Ebberly, Hale, WIYN, MMT, Tillinghast, Shane, and Nordic Optical Telescopes are used to vet the planetary candidates and measure the masses of the putative planets. Observations of occultations and phase variations of hot, short-period planets such as HT-P-7b provide a probe of atmospheric properties. Asteroseismic analysis already shows the presence of p-mode oscillations in several stars. Such observations will be used to measure the mean stellar density and infer the stellar size and age. For stars too dim to permit asteroseismology, observations of the centroid motion of target stars will be used to measure the parallax and be combined with photometric measurements to estimate stellar sizes. Four open clusters are being observed to determine stellar rotation rates as a function of age and spectral type. Many different types of stellar variability are observed with unprecedented precision and over a wide range of time scales. Solar-like photometric variability of thousands of field stars is being studied to determine how photometric variability and the stellar rotation rates change with stellar age and metallicity. A wide variety of other astrophysical phenomena have also been observed. The data are being analyzed at the Ames Research Center and archived at the MAST at STScI. The Kepler Mission also supports a vigorous Guest Observer Program.

Borucki, William↗
NASA NTRS1999

The Earth System Science Pathfinder VOLCAM Volcanic Hazard Mission

The VOLCAM mission is planned for research on volcanic eruptions and as a demonstration of a satellite system for measuring the location and density of volcanic eruption clouds for use in mitigating hazards to aircraft by the operational air traffic control systems. A requirement for 15 minute time resolution is met by flight as payloads of opportunity on geostationary satellites. Volcanic sulfur dioxide and ash are detected using techniques that have been developed from polar orbiting TOMS (UV) and AVHRR (IR) data. Seven band UV and three band IR filter wheel cameras are designed for continuous observation of the full disk of the earth with moderate (10 - 20 km) ground resolution. This resolution can be achieved with small, low cost instruments but is adequate for discrimination of ash and sulfur dioxide in the volcanic clouds from meteorological clouds and ozone. The false alarm rate is small through use of sulfur dioxide as a unique tracer of volcanic clouds. The UV band wavelengths are optimized to detect very small sulfur dioxide amounts that are present in pre-eruptive outgassing of volcanoes. The system is also capable of tracking dust and smoke clouds, and will be used to infer winds at tropopause level from the correlation of total ozone with potential vorticity.

Krueger, Arlin J.↗
NASA NTRS2010

Modeling of LEO Orbital Debris Populations in Centimeter and Millimeter Size Regimes

The building of the NASA Orbital Debris Engineering Model, whether ORDEM2000 or its recently updated version ORDEM2010, uses as its foundation a number of model debris populations, each truncated at a minimum object-size ranging from 10 micron to 1 m. This paper discusses the development of the ORDEM2010 model debris populations in LEO (low Earth orbit), focusing on centimeter (smaller than 10 cm) and millimeter size regimes. Primary data sets used in the statistical derivation of the cm- and mm-size model populations are from the Haystack radar operated in a staring mode. Unlike cataloged objects of sizes greater than approximately 10 cm, ground-based radars monitor smaller-size debris only in a statistical manner instead of tracking every piece. The mono-static Haystack radar can detect debris as small as approximately 5 mm at moderate LEO altitudes. Estimation of millimeter debris populations (for objects smaller than approximately 6 mm) rests largely on Goldstone radar measurements. The bi-static Goldstone radar can detect 2- to 3-mm objects. The modeling of the cm- and mm-debris populations follows the general approach to developing other ORDEM2010-required model populations for various components and types of debris. It relies on appropriate reference populations to provide necessary prior information on the orbital structures and other important characteristics of the debris objects. NASA's LEO-to-GEO Environment Debris (LEGEND) model is capable of furnishing such reference populations in the desired size range. A Bayesian statistical inference process, commonly adopted in ORDEM2010 model-population derivations, changes a priori distribution into a posteriori distribution and thus refines the reference populations in terms of data. This paper describes key elements and major steps in the statistical derivations of the cm- and mm-size debris populations and presents results. Due to lack of data for near 1-mm sizes, the model populations of 1- to 3.16-mm objects are an empirical extension from larger debris. The extension takes into account the results of micro-debris (from 10 micron to 1 mm) population modeling that is based on shuttle impact data, in the hope of making a smooth transition between micron and millimeter size regimes. This paper also includes a brief discussion on issues and potential future work concerning the analysis and interpretation of Goldstone radar data.

Xu, Y.-L.↗
NASA NTRS2016

Megafans of the Northern Kalahari Basin

We identify eleven megafans (partial cones of fluvial sediment, >80 km radius) in the northern Kalahari Basin, using several criteria based on VIS and IR remotely sensed data and SRTM-based surface morphology reconstructions. Two other features meet fewer criteria of the form which we class as possible megafans. The northern Kalahari megafans are located in a 1700 km arc around the southern and eastern flanks of the Angola's Bié Plateau, from northern Namibia through northwest Botswana to western Zambia. Three lie in the Owambo subbasin centered on the Etosha Pan, three in the relatively small Okavango rift depression, and five in the Upper Zambezi basin. The population includes the well-known Okavango megafan (150 km), Namibia's Cubango megafan, the largest megafan in the region (350 km long), and the largest nested group (the five major contiguous megafans on the west slopes of the upper Zambezi Valley). We use new, SRTM-based topographic roughness data to discriminate various depositional surfaces within the flat N. Kalahari landscapes. We introduce the concepts of divide megafans, derived megafans, and fan-margin rivers. Conclusions. (i) Eleven megafan cones total an area of ~190,000 sq km. (ii) Different controls on megafan size operate in the three component basins: in the Okavango rift structural controls become the prime constraint on megafan length by controlling basin dimensions. Megafans in the other les constricted basins appear to conform to classic relationships fan area, slope, and feeder-basin area. (iii) Active fans occupy the Okavango rift depression with one in the Owambo basin. The rest of the population are relict but recently active fans (surfaces are relict with respect to activity by the feeder river). (iv) Avulsive behavior of the formative river-axiomatic for the evolution of megafans-has resulted in repeated rearrangements of regional drainage, with likely effects in the study area well back into the Neogene. Divide megafans comprise the majority of the identified features, some of which have delivered water and sediment alternately to neighboring basins in the course of normal avulsion activity, likely resulting in significant changes in the hydrologies of two of the study-area subbasins. (v) Paleoclimatic inferences extracted from fluvial and lacustrine sediments therefore need to take account of avulsion-driven drainage configurations, especially where these are autogenically controlled.

Wilkinson, M. J.↗
DOE OSTI2023

On the impact of tidal generation and energy storage integration in PV-rich electric distribution systems

Deep decarbonization of power system operations requires the maximal utilization of available renewable resources. At distribution-level operations, however, grid operators can face numerous challenges in integrating renewables at scale owing to the inherent intermittence of renewable energy resources. These include phenomena such as voltage fluctuations, which are typically mitigated through control actuators such as on-load tap changers (OLTC) as well as energy storage devices, such as battery energy storage systems (BESS). On the one hand, high intermittence of the available renewable portfolio may require increasingly aggressive control of actuators, thereby accelerating the probability of equipment failure. On the other hand, integrating BESS operations and having a diverse renewable generation portfolio can typically help stagger power/energy flow to mitigate the aforementioned adverse impacts. In this paper, we employ a Bayesian framework for equipment lifetime estimation to understand the impact of including tidal energy resources and BESS in distribution system operations for feeders having substantial distribution photovoltaic generation. Our results indicate that while tidal energy alone may slightly decrease equipment reliability, the adverse impact on reliability is significantly magnified by a generation portfolio consisting of tidal generation and photovoltaic generation. Here, we also study the tidal and photovoltaic hosting capacity problem with and without energy storage systems using equipment reliability as an added constraint. We conclude that energy storage increases the reliability-constrained hosting capacity of the distribution system.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Spaceborne Lidar Retrievals of PM2.5 for Air Quality Studies and Applications

Fine particulate matter (PM2.5) substantially contributes to air pollution and negatively affects human health. While many studies have investigated the use of passive column-integrated aerosol optical depth to infer surface PM2.5, the use of lidar observations for air quality characterization is not nearly as extensive. Lidar measurements are critical, however, due to the vertical aerosol information they provide, including near the surface. In this presentation, we first provide an overview of various lidar-based approaches for estimating PM2.5 concentrations and then discuss how lidar measurements can assist other air quality applications. For example, estimates of PM2.5 have been obtained in a physics-based approach through CALIOP near-surface aerosol extinction retrievals, assumptions on the mass extinction efficiency, and incorporating other parameters (an aerosol hygroscopic growth factor and PM2.5/PM10 ratio). Application of this algorithm over the contiguous United States (CONUS) from 2006 to 2018 yielded larger PM2.5 values over the eastern and western CONUS (~10-15 μg/m³) and lower PM2.5 levels in the central CONUS (~5 μg/m³). These spatial patterns were similar to those from gridded PM2.5 concentrations obtained through in situ measurements at ground stations operated by the US Environmental Protection Agency. In another approach, the Cloud Aerosol Transport System (CATS) lidar was used with the Goddard Earth Observing System (GEOS) model in a 1D ensemble-based variational technique to obtain PM2.5 over the US and Europe, and the spatial patterns of the CATS/GEOS based PM2.5 concentrations generally captured those from surface stations (with corresponding hourly EPA PM2.5 vs CATS PM2.5 statistics of R=0.4 and bias=1.5 μg/m³). In our recent work, as part of the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group, we have applied both the CALIOP and CATS/GEOS based approaches over the highly polluted country of India during the post-monsoon season (September-October 2016). We derived elevated levels of two-month mean PM2.5 (~100 μg/m³) in northern India, especially near New Delhi. These high PM2.5 concentrations in the Indo-Gangetic plain are driven in large part from the seasonal burning of crop residue and meteorological conditions typical at this time of the year, such as low wind speeds and a shallow boundary layer. While the satellite-derived PM2.5 moderately replicates (R = ~0.7-0.9) the spatial variability in the two-month mean of surface in situ PM2.5 from monitoring sites operated by the Central and State Pollution Control Boards, we show results from specific scenes for which there are large deviations between the satellite-derived PM2.5 and in situ measurements. Other current work on this topic focuses on developing PM2.5 estimates using airborne high spectral resolution lidar measurements through machine learning regression algorithms and involves several parameters (e.g., aerosol extinction, color ratio, lidar ratio). Application of this method over major metropolitan areas in the US and Asia have resulted in high correlations (R = 0.93) with surface measurements. This airborne lidar approach can be adapted to spaceborne lidar measurements, and all three of these approaches can be applied to ESA’s EarthCARE Atmospheric Lidar instrument, setting the stage for the future Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System (CALIGOLA) mission. Ultimately, beyond estimates of PM2.5, the aerosol vertical distribution from lidars can benefit studies involving passive sensor approaches for PM2.5 proxies (including from geostationary satellites), wildfire smoke plume injection heights, volcanic emissions (e.g., ash height retrievals), and aerosol/air quality model assimilation, evaluation, and forecasts.

Travis D Toth↗
DOE OSTI2023

Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Tristructural isotropic (TRISO) particle fuel is one of the most promising fuel concepts enabling high temperature and high burnup reactor operation. One dominant source of radioactivity released from the TRISO particles is silver (Ag), which is subject to a high release fraction and long decay life compared to other fission products. Previous modeling efforts using the fuel performance code BISON indicated nonnegligible uncertainties in modeling the diffusion process of fission products in TRISO compared to the Advanced Gas Reactor experiments. The overall uncertainties observed when modeling the fission product diffusion can result from uncertainties in model parameters, noisy experimental measurements, and deficiencies in the developed models. The three types of underlying uncertainties have not yet been properly quantified in open literature. Here, this paper presents the Bayesian uncertainty quantification (UQ) using massively parallelizable Markov chain Monte Carlo samplers. The uncertainties due to model parameters, model inadequacy, and experimental measurement noise are quantified, with the σ term used to represent the sum of the model inadequacy and measurement noise uncertainties. It is worth noting that this is the first time the σ term is inferred for nuclear fuel experiments, as compared to using prescribed values for uncertainty quantification in previous work. The parallelizable Markov chain Monte Carlo samplers efficiently infer the model parameters and the σ term, giving insight into physical parameters like diffusion coefficients and the combined model discrepancy and measurement noise. A subsequent forward uncertainty quantification (UQ) is also performed based on the calibration results to generate more accurate predictions of the Ag release. The model inadequacy plus experimental noise is the most dominant source of uncertainty compared to the parametric uncertainty. All the UQ analyses presented in this work are based on the second series of the irradiation experiments in the Advanced Gas Reactor program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Survey of tungsten gross erosion from main plasma facing components in WEST during a L-mode high fluence campaign

An initial high fluence campaign was performed in WEST, in 2023, on the newly installed actively cooled tungsten divertor composed of ITER-grade monoblocks. The campaign consisted in the repetition of a 60 s long Deuterium L-mode pulse in attached divertor conditions, cumulating over 10000s of plasma exposure. A maximum deuterium fluence of approximately 5⋅1⁢026 m−2 was reached in the outer strike point region, representative of a few high performance ITER pulses. Gross tungsten erosion inferred from visible spectroscopy shows that the most eroded plasma facing component is the inner divertor target with rates ten times larger than on the outer divertor target. The outer midplane tungsten bumpers, located a few centimeters from the plasma, show gross erosion rates two times lower than at the outer divertor. We conclude that the outer midplane bumpers have a negligible contribution to the long range tungsten migration and deposition onto the lower divertor. The cumulated gross erosion rate on the inner divertor translates in an effective gross erosion thickness of about 20μ⁢m, while it is about 2μ⁢m for the outer divertor. Strikingly, these orderings coincide with the thickness of deposits found locally on the divertor: the exposed surfaces of high field side monoblocks are covered with several tens of μ⁢m tungsten deposits, while on the lower field side, few μ⁢m thin tungsten deposits are only found on the magnetically shadowed parts of monoblocks. The strong impact of those deposits on WEST operation, namely perturbation of surface temperature measurement with infra-red thermography, and the emission of flakes causing radiative perturbation of the confined plasma, calls for anticipating similar issues in ITER. In particular, the start of research operation shall consider the definition of a divertor erosion budget in order to anticipate the formation of deleterious deposits.

Fedorczak, N.↗
NASA NTRS2000

Investigation of the Transport of Solar Ions Through the Earth's Magnetosphere

The objective of this study has been to infer, by statistical means, the most probable mode of entry of solar wind plasma into Earth's magnetotail, using a particular set of archived data from the Lockheed Plasma Composition Experiment on the International Sun-Earth Explorer One (ISEE-1) satellite, jointly sponsored by the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) in the 1970's and 80's. Despite their considerable age, the Lockheed ISEE-1 data are still, at the time of this report, the only substantial ion composition data in the sub-keV to keV energy range available from the magnetotail beyond 9 R(sub E), because of various technical problems with ion mass spectrometers on later missions, and are therefore a unique source of information about the mixing of solar and terrestrial origin plasmas in the tail, within the ISEE-1 apogee of almost 23 R(sub E). The entire set of archived data used in this study, covering the 4.5 years of operation of the instrument and comprising not only tail measurements but also data from the inner magnetosphere as well as data from outside the magnetopause, is now available to the public via the WorldWideWeb at the address: http://cis.spasci.com/ISEE_ions The fundamental assumption of this and other studies of magnetosphere ion composition is that He++ and O+ ions are virtually certain "tags" of solar and terrestrial origins, respectively. This is an assumption with strong theoretical basis and it is corroborated by observational evidence, including the often substantial differences between the velocity distribution functions of those two species. The H+ ions can have a dual origin, in principle, but the close resemblance in the ISEE-1 data between the dynamics of H+ and He++ ions indicates a predominantly solar origin of the H+ ions in the tail, at least. By the same token, the usually minor He+ ions are probably almost entirely of terrestrial origin, because of their similarity to the O+ ions.

Lennartsson, O. W.↗