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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Advancing Open Science in Atmospheric Research: Integrating Data Usability and Machine Learning

In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences." "In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences.

Jennifer Wei↗
DOE OSTI2021

Machine-learning based prediction of injection rate and solenoid voltage characteristics in GDI injectors

We report that current state-of-the-art gasoline direct-injection (GDI) engines use multiple injections as one of the key technologies to improve exhaust emissions and fuel efficiency. For this technology to be successful, secured adequate control of fuel quantity for each injection is mandatory. However, nonlinearity and variations in the injection quantity can deteriorate the accuracy of fuel control, especially with small fuel injections. Therefore, it is necessary to understand the complex injection behavior and to develop a predictive model to be utilized in the development process. This study presents a methodology for rate of injection (ROI) and solenoid voltage modeling using artificial neural networks (ANNs) constructed from a set of Zeuch-style hydraulic experimental measurements conducted over a wide range of conditions. A quantitative comparison between the ANN model and the experimental data shows that the model is capable of predicting not only general features of the ROI trend, but also transient and non-linear behaviors at particular conditions. In addition, the end of injection (EOI) could be detected precisely with a virtually generated solenoid voltage signal and the signal processing method, which applies to an actual engine control unit. A correlation between the detected EOI timings calculated from the modeled signal and the measurement results showed a high coefficient of determination.

42 ENGINEERING↗
DOE OSTI2026

Effects of slope steepness and cross-slope wind speed on fire spreading behavior for various vegetation

Wildland fire behavior is significantly influenced by environmental factors such as slope steepness, wind speed, and fuel type. Understanding these interactions is critical for improving predictive models and fire management. This study explores how slope steepness and cross-slope wind speed influence fire spread dynamics in various fuel bed types. Simulations are conducted using a physics-based wildland fire model, HIGRAD/FIRETEC, across six slope angles (0–50 %), four cross-slope wind speeds (4–10 m s –1 ), and three fuel bed types (grass, shrubland, and forest). Representative cases are additionally compared with FARSITE fireline evolution. Fire behavior is categorized into distinct propagation types based on spread characteristics and analyzed. The fire propagation angle, which indicates deviation from the wind direction, generally increases with steeper slopes and decreases with stronger cross-slope winds. Secondary upslope propagation is observed in shrubland under moderate slopes, while secondary downwind propagation occurs in all fuel beds at higher wind speeds. These findings highlight fire spread characteristics that differ from predictions by traditional models like Rothermel’s. By capturing complex propagation patterns and dynamics, this study demonstrates the value of a physics-based, atmosphere-fire coupled model for accurate wildland fire prediction. Incorporating secondary propagations and the influence of fuel bed complexities into predictive models can improve the accuracy of fire spread forecasts, enabling more effective fire management and risk mitigation efforts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Degradation of small mare surface features

Ring-moat structures are interpreted as remnants of flow topography associated with mare emplacement. Measurements of narrow moats characterizing these small mare features reveal a contradiction between their inferred preservation and the degree of surface degradation predicted by theoretical erosional models. Moat widths smaller than 50 m are recorded in areas where erosional models predict that walls of craters three to four times as large should be degraded to slopes of 1 deg. Crater statistics in such regions provide estimates of equilibrium conditions for impact crater formation that are consistent with the degree of preservation of the narrow moats. Although relative ages determined by observation of crater wall slopes near 20 deg, may be appropriate, it is concluded that current erosional models are not valid down to impact-degraded slopes of 1 deg. Relative age estimates based on the inferred degraded state of highly subdued craters are believed to be invalid, particularly for late Eratosthenian-age and Copernican-age mare units. In regions displaying ring-moat structures, highly subdued craters larger than the average moat widths are intepreted as either endogenic features associated with the emplacement of mare flow units or degraded secondary craters, which are typically subdued at the outset.

Schultz, P. H.↗
DOE OSTI2024

Testing of a 40-kWth Counterflow Particle-Supercritical Carbon Dioxide Narrow-Channel, Fluidized Bed Heat Exchanger

Particle-based primary heat exchangers (HXs) must deliver sCO2 fluid temperatures above 700°C to couple particle-based concentrating solar receivers and thermal energy storage (TES) sub-systems with efficient sCO2 power cycles. Particle-sCO2 HX designs have struggled to meet DOE cost targets (≤ $150/kWth) due to the amount of expensive nickel alloys necessary for manufacturing full-scale, particle-sCO2 HXs. Our team has demonstrated that mild bubbling fluidization of falling particles in a counterflow narrow-channel fluidized bed can reduce required HX surface area and thus, costs by increasing particle-wall heat transfer coefficients hT,w > 800 W m-2 K-1. This paper reports on the fabrication and testing of a stainless steel, particle-sCO2 HX with 12 fluidized-bed channels approximately 10.5 mm deep spaced between diffusion-bonded, micro-channel sCO2 plates. The HX with a core length of ≈0.56 m is fed with CARBOBEAD HSP particles through a short, fluidized freeboard zone just above the core. Testing to date in the National Solar Thermal Test Facility (NSTTF) at Sandia National Laboratories has shown that parallel bed fluidization maintains uniform particle inventory across the instrumented channels. Heat transfer thermal duty between the particle and sCO2 flows exceeds 30 kWth with sCO2 inlet temperatures of 200ºC and particle inlet temperatures up to 440ºC and mass flow rates of 0.2 kg s-1 fluidized by counterflowing gas flow rates of 0.005 kg s-1. Tests at higher particle and sCO2 inlet temperatures (600ºC and 400ºC respectively) are targeted to achieve > 40 kWth with model-predicted overall heat transfer coefficients U > 400 W m-2 K-1.

14 SOLAR ENERGY↗
NASA NTRS2001

Optimal firing rate estimation

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

NASA Discipline Neuroscience↗
NASA NTRS1990

Prediction of functional aerobic capacity without exercise testing

The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate VO2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml.kg-1.min-1) and R = 0.78 (SE = 5.6 ml.kg-1.min-1). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from VO2peak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5-9.7 ml.kg-1.min-1. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6-5.4 ml.kg-1.min-1 with these subjects.(ABSTRACT TRUNCATED AT 250 WORDS).

Oxygen Consumption↗
DOE OSTI2021

Quantifying Properties for a Mechanistic, Predictive Understanding of Aqueous Impact on Aging of Medium and Low Voltage AC and DC Cabling in Nuclear Power Plants

To address the gap in knowledge in understanding degradation in relevant service conditions, this project aimed to develop a mechanistic, predictive model of medium and low voltage cable failure based on the primary environmental degradation parameters of aqueous immersion time, temperature, and the oxidation extent. To do so, we took a two-fold approach toward evaluating degradation as related to the aqueous condition. First, we evaluated the chemical, mechanical, and electrical properties of polymers that comprise the cabling insulation under varied aqueous conditions at different temperatures. Secondly, we evaluated the performance of insulation materials under similar accelerated aging conditions in addition to the dielectric breakdown of the cabling under submersion conditions. Thermal oxidation and immersion of LDPE thin films were done using a Parr vessel and the extent of oxidation was monitored using the carbonyl index from ATR-FTIR spectrum, a ratio quantifying the carbonyl functionality produced on the LDPE film surface. Increasing the temperature, oxidation time, and oxygen pressure increased the water-vapor permeability and the carbonyl content. Thermogravimetric analysis of the films confirmed that there is indeed an initial weight loss of the smaller molecular weight molecules and volatiles. At higher temperatures, there is a secondary mass loss. Up to 70°C, the mass loss curves were similar until 80°C, when the aged films decreased at a much greater rate with respect to increasing temperature. This was seen in the 10, 50, 90% weight loss temperatures. The mechanical properties of sheet PP and HDPE as well as injection molded LDPE, HDPE, HDPP dog bones were plotted with respect to the time spent in the Parr vessel during thermal oxidation. For the sheet PP and HDPE, the UTS and the modulus of elasticity decreased while the elongation increased. The injection-molded LDPE, HDPE, and HDPP dog bones experienced a similar trend where the changes in the properties were within experimental uncertainty. This analysis of LDPE in dry and immersive oxygen-rich environments is an important baseline for future experiments looking at other degradation mechanisms. A predictive aging model for low-density polyethylene insulative cable housings was developed. This model revealed a combination of physical and chemical processes which lead to an increase in permeability and a decrease in strength of the insulator. In creating this predictive model, a gap of knowledge in the literature was revealed in two areas: understanding how the crystallinity of a polymer changes with time and visualizing the predicted pores formed through the insulator which leads to failure. Developing and using an adapted ATR-FTIR method, crystallinity was monitored and compared to bulk crystallinity found via DSC. Inhomogeneity in crystallinity changes were observed but the FTIR method but was found to be less reliable. Pore visualization was found utilizing electrical impedance spectroscopy saturated aged polyethylene films with synthesized citrate-capped gold nanoparticles, and chloroauric acid precursor. results indicate a decreasing impedance of the polyethylene films caused by the transport of ions through the film. SEM imaging was then performed for elemental analysis of the films and counter electrodes for the presence of ions. Chloride and gold ions were detected; however, no nanoparticles were found. This gives an estimated pore size of at least 0.3 nm through the aged film. Cyclic submergence of polyethylene and polypropylene in aqueous solutions of copper sulfate and Harrison’s solution were examined. It was discovered that aging in these mixed conditions and at 90°C did cause a small, yet significant increase to tensile strength for both unaged polyethylene and polypropylene. The PE and PP in cycled and submerged conditions did not have tensile strengths significantly different from dry-aged after 16 weeks. For both solutions, it was determined that capacitance increases with both water tree depth and cable temperature and is relatively independent of changing water tree AR. As for resistance, there is no apparent change between depth percentages of 10 and 80 for both solutions. This is because the water tree has not yet entered the conductor and thus there is no shorting current flowing through the tree yet. Between 80 and 100% water tree depth, it is observed that for both solutions there is a rapid decrease in resistance because the tree is now impacting the conductor shield and allowing shorting current to flow through it. The relationship between resistance and temperature was found to be inversed. As temperature increases, resistance decreases for both water tree solutions with distilled water having the most apparent difference across the range of temperatures simulated. With regards to water tree AR, resistance was found to be relatively independent at depth percentages of 10, 50, and 70, but there was some relationship at 100% depth for both solutions. At this depth, as water tree AR increased, resistance was found to also increase. Through the examination of voltage and electric field distribution plots, it was confirmed for EPR cables that increasing water tree depth leads to increasing distortion. The increase in shorting current at 100% depth for aqueous copper sulfate compared to distilled water was also visualized. Lastly, the relationship between shorting current and temperature for narrow water trees was visualized and validated using the distribution plots. This study has led to a better understanding of the effect of cable temperature, water tree solution, and geometry of the tree region on cable degradation. Furthermore, this study has documented simulation results of water tree degradation in EPR MV cables, which had been previously lacking in information. Future work in this area will add frequency into the mix and examine what effect it has on the rate of cable degradation as a result of water treeing. To compliment the work being carried by UMD on different polymer chemistries, harvested medium voltage (MV) cables were selected for accelerated aging study at ORNL. These medium voltage cables are representative of the vintages and materials that are currently in use at existing nuclear power plants (NPPs). These cables were immersed in water at 90°C and energized for a period of two years at elevated voltage. Partial discharge was measured during this period of time to track potential degradation. Unfortunately, due to the absence of failure, the extent of integration between the UMD techniques and the harvested MV insulation was limited. However, based on the findings and from the UMD research in the previous sections on polyethylene and polypropylene, follow-on characterization for harvested MV cable insulation should focus on sample preparation to take advantage of the UMD techniques to better understand mechanistic degradation in MV cable insulations. This would include: 1.) Utilization of solutions and impedance measurement insulation to track permeability in harvested and accelerated aging insulation samples, 2.) Adaptation of gold nanoparticle synthesis for electrical impedance spectroscopy with supporting SEM characterization to study pore formation in harvested and accelerated aged insulation samples, & 3.) ATR-FTIR crystallinity with multiple temperature dependent harvested MV cable insulation under different air and submerged accelerated aging. In addition, low voltage dielectric spectroscopy and high voltage dissipation factor, tan δ, could be implemented as a condition monitoring tool for harvested MV cable insulation in submerged environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Moisture ingress in commercial steel drums: Water content determination, diffusion modelling and predicted permeation rates

Commercial steel drums underpin the global economy, playing a pivotal role in the storage and transportation of critical materials. Transported and stored materials, such as food, chemical and nuclear waste, can be sensitive to ambient conditions, particularly moisture that can enhance negative effects such as corrosion and material degradation. Although international standards and regulations are in place for the qualification of steel drums, there are no current testing requirements, established limits or boundaries for the permeation of moisture into the drums during transportation or storage. This work aims to provide insights into the moisture ingress over time into properly sealed steel drums and provides estimated moisture ingress rates over time through extrapolation. Water vapour transmission rate (WVTR) measurements through the gasket material at 10–40°C were 0.11–2.1 g/m 2 /day resulting in a permeation activation energy of 30.2 kJ/mol. Water sorption measurements and Karl Fischer titration (KFT) on ethylene propylene diene monomer (EPDM) gasket material revealed a decrease in equilibrium moisture saturation with increasing temperature. KFT measurements also revealed the presence of moisture within the adhesive and drum wall after exposure to ambient conditions. KFT and Fourier transform infrared spectroscopy (FTIR) show that moisture will desorb from the EPDM and drum wall after exposure to desiccating conditions, although a minimal amount of moisture will remain present. When sealed to the manufacturer's recommendations, the steel drums are effective in minimizing moisture ingress. In conclusion, in sealed empty drums, moisture ingress rates for 19-L drums were 0.4–1.5 mg/day at 25°C 15% relative humidity (RH) and increased to 7.1–8.8 mg/day at 40°C 90% RH, and moisture ingress rates for 210-L drums were 2.5 and 3.5 mg/day at field deployment conditions of 15.5°C 51.5% RH and 23°C 40% RH, respectively.

42 ENGINEERING↗
DOE OSTI2022

Can a shock-induced phonon up-pumping model relate to impact sensitivity of molecular crystals, polymorphs and cocrystals?

Impact sensitivity engineering of high-energy molecular crystals requires accurate predictive models. For this purpose, the promising multi-phonon based approach is selected, assessing a bit more its strengths and weaknesses. Presently used with high-quality phonon calculations of 22 molecular crystals, using a physics-based criterion to determine the phonon bath extent, the resulting intrinsic shock sensitivity index (SSI) is compared to the most common marker of impact sensitivity, h 50 , as determined from drop-weight impact tests. Selecting a data subset from experiments performed under very similar conditions (2.5 kg hammer with grit and 30–40 mg samples), the model can predict h 50 values for mono-molecular crystals with very good accuracy, including the ability to discriminate the polymorphs of HMX and CL20. This very good agreement validates an initial indirect up-pumping mechanism occurring under these conditions, where the doorway modes also interact with the phonon bath. However, the phonon bath criterion for mono-molecular crystals does not transfer well to cocrystals. Owing to the vibrational coupling of the co-molecules, it seems a broader phonon bath should be considered. Additionally recalling experimental uncertainty and various experimental factors affecting h 50 values for a given compounds, we recommend that the density of the sample, granularity and morphology be systematically considered and reported along with measurements, which will in turn allow for more systematic data and predictive capabilities for sensitivity models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Beam dynamics corrections in the measurement of the anomalous precession frequency at the Muon $g-2$ experiment at Fermilab

The Muon $g-2$ experiment at Fermilab (E989) aims to measure the anomalous magnetic moment of the muon with an accuracy of 140 ppb (parts per billions). This accuracy, obtained by adding in quadrature a statistical and a systematic contribution of comparable value (100 ppb), will allow to reduce the experimental uncertainty (from the previous E821 experiment at BNL \cite{bnl}) of a factor of 4, and represents one of the most precise tests of the Standard Model (SM) theory of elementary particles. The first result on the Run-1 dataset \cite{prl} was released on April 7, 2021, showing a very good agreement with the previous result from BNL experiment, with a slightly better uncertainty. The corresponding experimental average increases the significance of the discrepancy between the measured and Standard Model prediction of 4.2$\sigma$ \cite{white_paper}.\\ \noindent The measured quantity is the muon magnetic anomaly a$_\mu$=$\frac{g_\mu-2}{2}$ where g$_\mu$ is the gyromagnetic factor of the muon. Dirac's equation predicts g$_\mu$ = 2, while radiative corrections, dominated by the QED contribution due to an exchange of a virtual photon, causes a per-mille correction on this quantity. By including all the SM contributions, a$_\mu$ is known at 370 ppb. The E989 experiment measures $a_\mu$ injecting positive muons with momentum of 3.1 GeV/$c$ polarized longitudinally in bunches (called $fills$) with an average rate of 12 Hz, in a storage ring of 14 meters diameter. Due to the parity violation in the weak muon decay, high energy positrons produced are emitted preferably in the muon's spin direction. By counting the number of positrons with energy greater then 1.7 GeV in function of the time, the frequency precession of the muon spin is measured, that together with the measurement of the magnetic field, allows to extract $a_\mu$. The positrons are detected with 24 electromagnetic calorimeters, that measure the energy and the arrival time of the positrons, each made of 54 crystals of lead fluoride (PbF$_2$) read by silicon photomultipliers (SiPM). Together with calorimeters, two tracking detectors are used to make non-destructive measurements of the muon beam characteristic by reconstructing the muon decay position extrapolating backward the decay positrons. The knowledge of the beam motion inside the ring plays a fundamental role in the analysis of $a_{\mu}$, where the measured anomalous precession frequency $\omega_a$ must be corrected for four main beam dynamics effects. A first correction is associated with the presence of an electric field responsible of the vertical focusing on the storage ring, where vertical direction is orthogonal to the orbit and horizontal direction is along the storage ring radius. Due to the oscillations in the vertical direction, the so called vertical betatron oscillations, a second correction is necessary to account for an average angle associated with the muon motion off the ideal orbit. A third correction is caused by lost muons in the ring which have a different spin phase at the injection respect to the decay ones. Finally, due to the correlation between the vertical and horizontal beam motion of the muons and the acceptance of the calorimeter, a correction (called ``phase-acceptance") arises. In Run1, due to the presence of two damaged resistors in one electrostatic quadrupole, this correction had a prominent role. The replacement of the damaged resistors before Run2 decreased this effect by one order of magnitude, and a further reduction in Run-3 was provided by an improved orbit.\\ \noindent The work of this Thesis focuses on the beam dynamics corrections on $\omega_a$. Due to the prominent role in Run-1 a special attention has been put to the phase-acceptance correction\footnote{The effect of this correction on the E821 BNL measurement of the $g-2$ has been evaluated to be within the quoted systematic error.}. Chapter \ref{ch:anomalous_magnetic_moment} introduces the anomalous magnetic moment of the muon. Chapter \ref{ch:early_experiment} describes the history of the Muon $g-2$ experiments. Chapter \ref{ch:theory} discusses the Standard Model prediction and possible new physics scenario. Chapter \ref{ch:muon_g2_experiment} describes the E989 experiment, whose experimental technique and the apparatus are discussed focusing on the improvements needed to reach the final goal on $a_\mu$ measurement. The original work of the Thesis is discussed in the last 5 chapters. Chapter \ref{ch:experiment_technique} presents the analysis technique to extract $\omega_a$, Chapter \ref{ch:beam_dynamics} describes the beam dynamics in the E989 experiment, Chapter \ref{ch:beam_dynamics_correction} discusses the beam dynamics correction to $\omega_a$, and Chapter \ref{sec:pa_corr} focuses on the phase acceptance correction. Finally Chapter \ref{ch:run23_analysis_improvements} contains the Run-2/3 improvements which are expected to allow for an increased precision ons the beam dynamics co...

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

A Reference Ocean Surface Emission and Backscatter Model from Microwaves to Infrared

Satellite observations are vital for the initialization of Numerical Weather Prediction models, and very important for climate monitoring and prediction, as well as other applications such as hydrology and flood awareness prediction. Knowledge of radiative contributions from the Earth's surface is needed to sound the lower troposphere from space. The lack of a reference quality ocean emission and backscatter model is a major gap in our ability to provide absolute calibration of the satellite based observing system. Uncertainty in emissivity models is not well characterized and different models are used for different spectral bands, for active and passive instruments. An International Space Science Institute (ISSI) team was put together [4] to address these issues. The objectives of the team are to provide a reference model as a community software (i.e., documented and freely available code), that is maintained and supported, has traceable uncertainty estimations, and that enables new science from microwaves to infrared with bidirectional reflectance distribution function (BRDF) capability. We will present the model and its various components, discussing the choices between various parameterizations, building on the LOCEAN model of [2]. The model predictions will be evaluated at various frequencies, including comparisons to radiometric observations by SMAP, AMSR2 and GMI (e.g., [5]). We will discuss early model evaluation in the infrared and for active microwave sensors. Areas of ongoing research include improving the foam parametrization (coverage and emissivity) to provide consistent performances across frequencies, building on [1], and the azimuthal dependence of the active and passive signals. The model will be used to generate training data for fast models e.g., Fastem, [3], that are used in operational data assimilation and climate re-analysis.

Emmanuel Dinnat↗
DOE OSTI2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Correlations between azimuthal anisotropy Fourier harmonics in PbPb collisions at sNN =2.76 TeV in the HYDJET++ model and in the multiphase transport model

Correlations between azimuthal anisotropy Fourier harmonics vn (n=2,3,4) are studied using the events from PbPb collisions at sNN=2.76 TeV generated by the HYDJET++ and multiphase transport (AMPT) models, and compared to the corresponding experimental results obtained by the ATLAS Collaboration. The Fourier harmonics vn are measured over a wide centrality range using the two-particle azimuthal correlation method. The slopes of the v2-v3 correlation from both models are in a good agreement with the ATLAS data. The HYDJET++ model predicts a stronger slope for the v2-v4 and v3-v4 correlations than the ones experimentally measured, while the results from the AMPT model are in a rather good agreement with the experimental results. In contrast to the HYDJET++ predictions, the AMPT model predicts a boomeranglike shape in the structure of the correlations as found in the experimental data. © 2020 American Physical Society.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Combination of searches for heavy spin-1 resonances using 139 fb -1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb -1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, $t\overline{t}$, and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Measurement of Higgs boson decay into $b$-quarks in associated production with a top-quark pair in $pp$ collisions at $ \sqrt{s} $ = 13 TeV with the ATLAS detector

The associated production of a Higgs boson and a top-quark pair is measured in events characterized by the presence of one or two electrons or muons. The Higgs boson decay into a b-quark pair is used. The analyzed data, corresponding to an integrated luminosity of 139 fb –1 , were collected in proton-proton collisions at the Large Hadron Collider between 2015 and 2018 at a centre-of-mass energy of √s = 13 TeV. The measured signal strength, defined as the ratio of the measured signal yield to that predicted by the Standard Model, is $0.35$ $^{+0.36}_{–0.34}$. This result is compatible with the Standard Model prediction and corresponds to an observed (expected) significance of 1.0 (2.7) standard deviations. The signal strength is also measured differentially in bins of the Higgs boson transverse momentum in the simplified template cross-section framework, including a bin for specially selected boosted Higgs bosons with transverse momentum above 300 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗