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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 649 records · Page 36
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NASA NTRS2002

The Retrospective Iterated Analysis Scheme for Nonlinear Chaotic Dynamics

Atmospheric data assimilation is the name scientists give to the techniques of blending atmospheric observations with atmospheric model results to obtain an accurate idea of what the atmosphere looks like at any given time. Because two pieces of information are used, observations and model results, the outcomes of data assimilation procedure should be better than what one would get by using one of these two pieces of information alone. There is a number of different mathematical techniques that fall under the data assimilation jargon. In theory most these techniques accomplish about the same thing. In practice, however, slight differences in the approaches amount to faster algorithms in some cases, more economical algorithms in other cases, and even give better overall results in yet some other cases because of practical uncertainties not accounted for by theory. Therefore, the key is to find the most adequate data assimilation procedure for the problem in hand. In our Data Assimilation group we have been doing extensive research to try and find just such data assimilation procedure. One promising possibility is what we call retrospective iterated analysis (RIA) scheme. This procedure has recently been implemented and studied in the context of a very large data assimilation system built to help predict and study weather and climate. Although the results from that study suggest that the RIA scheme produces quite reasonable results, a complete evaluation of the scheme is very difficult due to the complexity of that problem. The present work steps back a little bit and studies the behavior of the RIA scheme in the context of a small problem. The problem is small enough to allow full assessment of the quality of the RIA scheme, but it still has some of the complexity found in nature, namely, its chaotic-type behavior. We find that the RIA performs very well for this small but still complex problem which is a result that seconds the results of our early studies.

Todling, Ricardo↗
NASA NTRSDate not supplied

Structural Dynamics Observations in Space Launch System Green Run Hot Fire Testing

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. The Green Run Hot Fire (GRHF) of the SLS Core Stage provided a flight-like ground test environment for verification of integrated vehicle TVC performance. A TVC model coupled to a vehicle structural dynamic model has been developed previously and incrementally validated in subsystem tests and simulations. Still, some aspects of TVC performance in GRHF were not anticipated. The ensuing investigation demonstrated the need for well-instrumented test environments, various levels of modeling fidelity, test-representative structural models, and caution in reuse of legacy components. This paper is the sixth installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. It introduces the salient structural dynamic phenomena uncovered in ambient and hot fire testing. During the Green Run test campaign, a comparison of ambient and hot fire step responses showed a significant change in apparent damping due to the presence of friction, challenging long standing assumptions that friction could be neglected. Additionally, the characteristic response of the engine and thrust structure during GRHF proved to be more complex than anticipated, as evidenced by the available actuator, thrust structure, and engine measurements. While the string-potentiometer based test instrumentation was intended to allow for reconstruction of the engine angles along the two control axes, the geometric placement, location uncertainty, and responses in overlapping frequency spectra revealed additional phenomena requiring further analysis and post-processing. The observations from both modal and frequency response testing during the Green Run ambient and hot fire configurations led to Engine and Core Stage FEM (finite element model) updates. When evidence of unexpected engine motion was found in engine section accelerometer data, the authors pursued additional structural analysis leading to FEM updates associated with the TVC gimbal and thrust structure. Through collaboration between structures, TVC, and flight control disciplines, the test-informed models and root-cause analysis led to confident flight rationale for the first flight of the SLS launch vehicle.

Richard K. Moore↗
NASA NTRSDate not supplied

Structural Dynamics Observations in Space Launch System Green Run Hot Fire Testing

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. The Green Run Hot Fire (GRHF) of the SLS Core Stage provided a flight-like ground test environment for verification of integrated vehicle TVC performance. A TVC model coupled to a vehicle structural dynamic model has been developed previously and incrementally validated in subsystem tests and simulations. Still, some aspects of TVC performance in GRHF were not anticipated. The ensuing investigation demonstrated the need for well-instrumented test environments, various levels of modeling fidelity, test-representative structural models, and caution in reuse of legacy components. This paper is the sixth installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. It introduces the salient structural dynamic phenomena uncovered in ambient and hot fire testing. During the Green Run test campaign, a comparison of ambient and hot fire step responses showed a significant change in apparent damping due to the presence of friction, challenging long standing assumptions that friction could be neglected. Additionally, the characteristic response of the engine and thrust structure during GRHF proved to be more complex than anticipated, as evidenced by the available actuator, thrust structure, and engine measurements. While the string-potentiometer based test instrumentation was intended to allow for reconstruction of the engine angles along the two control axes, the geometric placement, location uncertainty, and responses in overlapping frequency spectra revealed additional phenomena requiring further analysis and post-processing. The observations from both modal and frequency response testing during the Green Run ambient and hot fire configurations led to Engine and Core Stage FEM (finite element model) updates. When evidence of unexpected engine motion was found in engine section accelerometer data, the authors pursued additional structural analysis leading to FEM updates associated with the TVC gimbal and thrust structure. Through collaboration between structures, TVC, and flight control disciplines, the test-informed models and root-cause analysis led to confident flight rationale for the first flight of the SLS launch vehicle.

Richard Moore↗
NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST to reduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗
DOE OSTI2024

A Diffusion‐Based Uncertainty Quantification Method to Advance E3SM Land Model Calibration

Abstract Calibrating land surface models and accurately quantifying their uncertainty are crucial for improving the reliability of simulations of complex environmental processes. This, in turn, advances our predictive understanding of ecosystems and supports climate‐resilient decision‐making. Traditional calibration methods, however, face challenges of high computational costs and difficulties in accurately quantifying parameter uncertainties. To address these issues, we develop a diffusion‐based uncertainty quantification (DBUQ) method. Unlike conventional generative diffusion methods, which are computationally expensive and memory‐intensive, DBUQ innovates by formulating a parameterized generative model and approximates this model through supervised learning, which enables quick generation of parameter posterior samples to quantify its uncertainty. DBUQ is effective, efficient, and general‐purpose, making it suitable for site‐specific ecosystem model calibration and broadly applicable for parameter uncertainty quantification across various earth system models. In this study, we applied DBUQ to calibrate the Energy Exascale Earth System Model land model at the Missouri Ozark AmeriFlux forest site. Results indicated that DBUQ produced accurate parameter posterior distributions similar to those from Markov Chain Monte Carlo sampling but with 30 times less computing time. This significant improvement in efficiency suggests that DBUQ can enable rapid, site‐level model calibration at a global scale, enhancing our predictive understanding of climate impacts on terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Neutral hydrogen and optical properties of three amorphous galaxies

We present new interferometric H I and optical observations of three amorphous galaxies, systems with a smooth, high surface brightness but an asymmetrical distribution of light. All three galaxies are forming stars and have LMC-like emission-line ratios, low dust content, and high H I velocity dispersions. NGC 1140 has a boxy inner morphology with a hook off one corner. At low light levels unusual extensions of starlight are seen curving to the northwest and southeast. The galaxy contains a very luminous central star-forming region and a small chain of H II regions that coincide with the hook. The central H II region has broad H(alpha) velocity profiles full width at half maximum (FWHM) less than or equal to 140 km/s, and it is a radio continuum source. There is a rotating H I gas disk, 40 kpc in radius, at a position angle 51 deg from the optical major axis. The central gas ridge follows the chain of H II regions, and the H I peak is on the hook. The outer gas on the southeast side curves away from the H I major axis. The central gas density is high, and the surface density declines very slowly with radius. The rotation velocity yields a mass of 1 x 10(exp 11) solar mass at 3.3 Holmberg radii (R(sub H)). NGC 1800 has a hook that coincides with a large H II region, and an r(exp 1/4) luminosity distribution. There are numerous H II regions along the major axis and extraordinary filaments of ionized gas. Emanating from the major axis on either side of the galaxy are H(alpha) fingers approximately 750 pc long. About 2.3 kpc to the north is a web of filaments approximately 3 kpc in extent. H(alpha) profiles of H II regions and filaments are narrow. The H I gas disk has a position angle that is approximately 13 deg different from that of the optical axis. There are two peaks near the center, one of which is near the largest H II region. Beyond the Holmberg radius to the west is a 6 x 10(exp 6) solar mass H I cloud. Its velocity indicates a mass of approximately 6 x 10(exp 9) solar mass for NGC 1800 at 1.5 R(sub H). At approximately R(sub 25) to the east there is a large H I shell. Also at approximately R(sub 25) on both sides the velocity gradient switches by 90 deg, and in the interior the rotation is about the major axis. The central gas density is low and falls off slowly. In the inner regions NGC 4670 resembles an S0/a galaxy seen rather edge-on. It contains a central supergiant H II region with very high velocity widths (FWHM less than or equal to 180 km/s) and complex velocity structures. It is a radio continuum source as well. The H I gas is a single spherical cloud or a disk at low inclination centered on the galaxy with a slight elongation along the optical major axis and rotation about the minor axis. The central gas density is high, and there is a high degree of concentration. The rotation speed indicates a total mass of 5 x 10(exp 10) solar mass at 1.1 R(sub H). We compare these characteristics with properties of gas in the presence of stellar bar potentials, gas warps, and interacting and merging galaxy models. Although there are inconsistencies and uncertainties, we conclude that NGC 1140 is a spiral of low surface brightness that has undergone a merger, while NGC 1800 and NGC 4670 are, respectively, probably an Im system and a spiral that had an encounter of the Noguchi (1988a) kind.

Hunter, Deidre A.↗
DOE OSTI2021

Transient absorption spectroscopy to explore cellular pathways to photobiomodulation

Photobiomodulation (PBM) describes the use of low irradiance light in the red to near-infrared wavelength range to stimulate biological effects in tissue, and many biological and spectroscopic techniques are used to study PBM. However, these techniques focus on the products or downstream effects rather than the electronic transitions that initiate the PBM processes. This study presents a novel approach to studying low irradiance light exposures on individual proteins and/or protein complexes by combining a continuous wave (CW) laser diode with femtosecond transient absorption spectroscopy (TAS), coined here as CW-TAS, and tests the system on reduced cytochrome c (Cyt c) for proof of principle. TAS was conducted using a 532-nm excitation pump beam and a 350-600 nm supercontinuum probe. In this work, CW laser diodes with wavelengths of 450 nm, 635 nm, and 808 nm were interchangeably fiber coupled into the HELIOS Fire. Samples of Cyt c were tested by TAS using a pump power of 15 µW, both with and without CW exposure. CW exposures were carried out with irradiances of 1.60 and 3.20 mW/cm 2 , except for 808 nm, which was only tested at 1.60 mW/cm 2 . Both kinetic and global analyses were performed on the TAS data and the time constants for sets with and without CW exposures were compared. The TAS data for Cyt c with the full dosage of CW exposures did not alter the TAS data distinguishably from the control data. No new electronic transient signals were observed beyond the background when testing Cyt c with the CW exposures. Kinetic analysis confirmed that existing transients did not deviate beyond uncertainty. Global time constants for Cyt c were calculated to be 0.25 ± 0.03 ps and 5.1 ± 0.3 ps for the control study, and the time constants for the CW exposed Cyt c were not significantly different. This study concludes that CW irradiation, at doses delivered, does not alter the transient absorption data of Cyt c. The CW-TAS method provides a new tool for studying PBM effects in other proteins and protein complexes, such as Complex IV, in future studies.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2024

Mineral Dust Optical Properties for Remote Sensing and Global Modeling: A Review

Dust plays a key role in many Earth system processes and is ubiquitous in the Martian atmosphere. Various intensive field campaigns, laboratory analyses, space-based remote sensing missions, and global modeling efforts aim to characterize dust optical properties. This is a bountiful time for dust scientists, and yet the interpretation of retrievals and comparison to models remains complicated by various conflicting assumptions that are part of each algorithm. For example, the conversion of satellite radiance measurements into products like aerosol optical depth for model evaluation depends upon aerosol properties like particle size and shape that are often prescribed and not part of the retrieval. Conversely, the model calculation of aerosol optical depth often uses different assumptions. The goal of this review is to first document algorithmic assumptions by various satellite retrieval products and models, and identify where there is consistency and where there are differences. In general, the differences documented in this paper reflect uncertainties resulting from incomplete observational characterization of dust aerosols and limitations in our understanding. Second, we note what observations might reduce uncertainties in our knowledge and bring greater consistency to retrievals and models, allowing for a more rigorous and harmonious comparison. The lack of comprehensive and realistic shape models for dust is an outstanding issue, such that closure between forward modeling from particle refractive index, shape, and size and observed optical properties cannot be achieved. Limitations in the computational methods that must be applied to model scattering from complex shapes also makes accurate optical modeling for dust challenging. Field observations indicate the persistence of coarse and giant dust particles at higher altitudes and farther downwind from their source than previously expected. Remote sensing retrieval algorithms based on observations at visible wavelengths have limited sensitivity to these particles and generally do not consider them, although a recent product based on longwave radiances is encouraging. Current measurements of the refractive index of bulk dust and fundamental dust minerology components such as hematite vary widely, inhibiting attempts to represent the variability in dust optical properties and forcing, as expected from different major dust source regions on Earth that have varying mineralogical composition. Some remote sensing retrieval algorithms allow for limited refractive index variability in their inversion solutions through mixing with other fine mode aerosol models, or optimizing the single scattering albedo, but Earth system models surveyed for this paper assume a globally uniform, size-invariant refractive index. Although no Martian dust samples have yet been returned to Earth, remote sensing observations indicate that Martian dust is globally homogenous in composition, and a single spectral refractive index assumption has been widely adopted to represent Martian dust. The lack of comprehensive, statistically representative measurements of dust particle microphysical properties (size distribution, morphology, complex index of refraction spectra, internal structure heterogeneity), and the resulting optical properties, limits our ability to verify the fidelity of these assumptions. A chain of measurements is needed, ranging from characterizing individual dust mineralogy components (e.g., pure hematite and goethite) to in situ sampling of complex atmospheric aerosol mixtures. Such results could be applied to both remote sensing retrievals that characterize the optical properties of the total aerosol burden in the atmosphere from total radiance measurements, and to global models that represent the total aerosol burden in the atmosphere by building it up from the balance of individual aerosol sources and sinks.

Aeolian dust↗
DOE OSTI2021

Development of a Framework for Data Integration, Assimilation, and Learning for Geological Carbon Sequestration (DIAL-GCS) (Final Report)

This project aimed to develop and demonstrate a Data Integration, Assimilation, and Learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS is an intelligence monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in machine learning technologies, complex event processing (CEP), and reduced-order modeling. The safe and efficient operation of GCS repositories requires integrated monitoring to track the injected CO¬2 as it moves within a storage reservoir. GCS projects are data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. The success of GCS thus depends in a large part on our ability to access, assimilate, and analyze heterogeneous data and information sources in a timely manner. This project included a number of meaningful and necessary tasks to transform the human domain knowledge into machine-interpretable rules for automating knowledge extraction and discovery in GCS. The specific technical objectives of the proposed DIAL-GCS project were to develop an ontology-driven GCS data management module for storing, querying, and exchanging GCS data (both historic and live sensor data) from multiple sources and in heterogeneous formats. Incorporate a CEP engine for detecting abnormal situations by seamlessly combining expert knowledge, rule-based reasoning, and machine learning. Enable uncertainty quantification and predictive analytics using a combination of coupled-process modeling, AI/ML methods, and reduced-order modeling, and integrate and demonstrate the system’s capabilities with both real and simulated data. As far as we know, this is one of the first projects aimed to develop intelligent monitoring systems (IMS) targeting the GCS. Under this project, the team had developed a large number of web applications and scientific algorithms that contribute the main theme of intelligent monitoring. The team has published more than a dozen peer reviewed papers and disseminated the research results at multiple technical meetings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2021-2022

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC, also referred to as the Garfield Fire Site), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from August 2021 to July 2022. Ten Wingscape Timelapse Pro cameras, and twenty seven Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory's Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. Additional information available in *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Diagnosing Challenges and Setting Priorities for Sustainable Water Resource Management Under Climate Change

Managing transboundary river basins requires balancing tradeoffs of sustainable water use and coping with climate uncertainty. We demonstrate an integrated approach to exploring these issues through the lens of a social-ecological system, combining remote and in-situ earth observations, hydrologic and climate models, and social surveys. Specifically, we examine how climate change and dam development could impact the Se Kong, Se San and Sre Pok rivers in the Mekong region. We find that climate change will lead to increased precipitation, necessitating a shift in dam operations, from maintaining low flows to reducing flood hazards. We also find that existing water governance systems in Laos, Vietnam, and Cambodia are ill-prepared to address the problem. We conclude that the solution space for addressing these complex issues will be highly constrained unless major deficiencies in transboundary water governance, strategic planning, financial capacity, information sharing, and law enforcement are remedied in the next decades.

Ibrahim Nourein Mohammed↗
DOE OSTI2026

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.

17 WIND ENERGY↗
NASA NTRS2015

Why Is Improvement of Earth System Models so Elusive? Challenges and Strategies from Dust Aerosol Modeling

Past decades have seen an accelerating increase in computing efficiency, while climate models are representing a rapidly widening set of physical processes. Yet simulations of some fundamental aspects of climate like precipitation or aerosol forcing remain highly uncertain and resistant to progress. Dust aerosol modeling of soil particles lofted by wind erosion has seen a similar conflict between increasing model sophistication and remaining uncertainty. Dust aerosols perturb the energy and water cycles by scattering radiation and acting as ice nuclei, while mediating atmospheric chemistry and marine photosynthesis (and thus the carbon cycle). These effects take place across scales from the dimensions of an ice crystal to the planetary-scale circulation that disperses dust far downwind of its parent soil. Representing this range leads to several modeling challenges. Should we limit complexity in our model, which consumes computer resources and inhibits interpretation? How do we decide if a process involving dust is worthy of inclusion within our model? Can we identify a minimal representation of a complex process that is efficient yet retains the physics relevant to climate? Answering these questions about the appropriate degree of representation is guided by model evaluation, which presents several more challenges. How do we proceed if the available observations do not directly constrain our process of interest? (This could result from competing processes that influence the observed variable and obscure the signature of our process of interest.) Examples will be presented from dust modeling, with lessons that might be more broadly applicable. The end result will either be clinical depression or there assuring promise of continued gainful employment as the community confronts these challenges.

Climate models↗
DOE OSTI2022

Probability of committed warming exceeding 1.5 ∘ C and 2.0 ∘ C Paris targets

Abstract The feasibility of achieving the Paris 1.5 ∘ C target continues to be a complex and hotly debated question. To help resolve this question we calculate probability distributions of the committed warming that would ensue if all anthropogenic emissions were stopped immediately, or at successive future times. We use a simple Earth system model together with a Bayesian approach that incorporates multiple lines of evidence and accounts for known model biases. This analysis reveals a wide range of possible outcomes, including no further warming, but also a 15% chance of overshooting the 1.5 ∘ C target, and 1%–2% chance for 2 ∘ C, even if all emissions had stopped in 2020. If emissions merely stabilize in 2020 and stop in 2040, these probabilities increase to 90% and 17%. The uncertainty arises mainly from that of present forcing by aerosols. Rather than there being a fixed date by which emissions must stop, the probability of reaching either target—which is already below 100%—gradually diminishes with delays in eliminating emissions, by 3%–4% per year for 1.5 ∘ C.

Sherwood, Steven C. (ORCID:0000000174208216)↗
NASA NTRS1974

Research on infrared astrophysics and X ray and XUV astronomy

The infrared research was divided into two related subjects, observations at wavelengths less than 34 microns and millimeter wavelength observations. A new complex of infrared sources in the Orion Nebula observed along with a broad range of galactic and extragalactic objects. The Comet Kohoutek was measured in the 1-20 micron wavelength region and its thermal properties agreed closely with those of Comet Ikeya-Seki. Combined infrared and photoelectric studies of the Makarian galaxies showed them to have a composite spectrum with a large emission feature in the far infrared. The development of one millimeter photometry and composited bolometers is described. A technique of reconstructing two dimensional surface brightness distributions with appropriate errors from individual strip scans was developed. Model parameters were determined by fitting data in non-linear systems. Results show spectral parameter uncertainties are underestimated or incorrectly evaluated in most studies.

Source record↗
NASA NTRS2012

Blade Displacement Measurement Technique Applied to a Full-Scale Rotor Test

Blade displacement measurements using multi-camera photogrammetry were acquired during the full-scale wind tunnel test of the UH-60A Airloads rotor, conducted in the National Full-Scale Aerodynamics Complex 40- by 80-Foot Wind Tunnel. The objectives were to measure the blade displacement and deformation of the four rotor blades as they rotated through the entire rotor azimuth. These measurements are expected to provide a unique dataset to aid in the development and validation of rotorcraft prediction techniques. They are used to resolve the blade shape and position, including pitch, flap, lag and elastic deformation. Photogrammetric data encompass advance ratios from 0.15 to slowed rotor simulations of 1.0, thrust coefficient to rotor solidity ratios from 0.01 to 0.13, and rotor shaft angles from -10.0 to 8.0 degrees. An overview of the blade displacement measurement methodology and system development, descriptions of image processing, uncertainty considerations, preliminary results covering static and moderate advance ratio test conditions and future considerations are presented. Comparisons of experimental and computational results for a moderate advance ratio forward flight condition show good trend agreements, but also indicate significant mean discrepancies in lag and elastic twist. Blade displacement pitch measurements agree well with both the wind tunnel commanded and measured values.

Abrego, Anita I.↗
DOE OSTI2021

New Capability at ORNL: High Precision Uranium Titration

Destructive analytical measurements establish a nuclear facility’s nuclear material inventory and inventory differences for Nuclear Material Accountancy and Control. A nuclear laboratory’s ability to perform accurate high-precision analytical measurements is key for tracking large inventories within a facility’s material balance areas and during production to track material movement through dynamic processes. For uranium, these measurements are made by using several established high-precision measurement protocols. These include isotope dilution mass spectrometry, gravimetry, and potentiometric titrations. Whatever measurement technique a nuclear lab chooses to use, reference materials (RMs) with certified attributes and accompanying uncertainties are used to calibrate measurement systems, and are the cornerstone for accurate results. In addition to calibration, RMs provide for metrological traceability, are used for method development and validation, and thus provide critical evaluations of the appropriateness and performance of analytical processes used. Evaluations may include validation that a method is fit-for-purpose, quantification of systematic and random biases, and the evaluation of long-term and short-term performance metrics. High-precision measurement techniques require that measured attributes be certified to a high degree of precision in the RMs used—ultimately, to a higher degree than that of the measurement technique itself. The US authority on the production of special nuclear material Certified Reference Materials is the NBL Program Office (NBLPO), formally known as New Brunswick Laboratory (NBL). The NBLPO is responsible for the sales and distribution of existing NBL certified reference materials (CRMs) and for the production of the next generation of nuclear RMs. To accomplish its mission, NBLPO is establishing key base capabilities within the DOE laboratory complex that formerly existed at the NBL laboratory. The Nuclear Analytical Chemistry (NAC) section within the Chemical Sciences Division (CSD) at Oak Ridge National Laboratory (ORNL) is currently working with NBLPO to set up laboratory and measurement capabilities to provide measurements and capabilities for production and/or recertification of existing and future CRMs for uranium assay. The NBL-developed high-precision titration (HPT) method is a critically-evaluated, extremely precise and accurate primary method utilized for the determination of uranium content in a variety of uranium materials. The HPT method, combined with detailed balance weighing protocols, provides for an analytical methodology that is unsurpassed in precision and one in which all sources of error have been evaluated, a requirement of CRM certification. HPT capability within the United States was lost with the closure of the labs at NBL. The NAC has been collaborating with NBLPO to stand up and demonstrate the capability to perform uranium assay via HPT at ORNL. HPT can produce results with an expanded uncertainty of approximately 0.01% for pure uranium compounds, with typical precisions of <0.006%. The major tasks required to stand up the method at ORNL were the refurbishment of a dedicated lab and equipment setup, procedure development, analyst training, establishing method-specific quality assurance, and qualification of an analyst to perform the method. This report summarizes these tasks, outlines the documents drafted, and gives the outcome of the qualification titrations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Quantitative 14 N NMR with Monte Carlo Uncertainty Analysis of Nitrate/Nitrite in Alkaline Nuclear Waste

While monitoring of nitrate and nitrite concentrations is important for managing corrosion in nuclear waste systems, existing analytical methods are hindered by turbidity, spectral interference, and delays from sample handling. Here, we demonstrate quantitative 14 N nuclear magnetic resonance (qNMR) spectroscopy as a direct, matrix-tolerant approach for nitrate and nitrite detection at natural abundance. Monte Carlo resampling was integrated into the workflow to quantify random error, establish precision–time tradeoffs, and separate noise-limited uncertainty from systematic bias arising from shimming, transmitter offset, or excitation pulse conditions. Quantification of nitrate and nitrite were validated in controlled alkaline matrix challenges and in 18-component Hanford-type simulants. These results establish 14 N qNMR as a practical, uncertainty-bounded tool for monitoring redox-active nitrogen species in chemically complex environments and provide a generalizable framework for quantitative analysis of quadrupolar nuclei.

Graham, Trent R. [Pacific Northwest National Labor↗