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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Capture Cavities For The Cw Polarized Positron Source Ce + baf

The initial design of the capture cavities for the continuous wave (CW) polarized positron beams at Jefferson Lab (Ce + BAF) is presented. A chain of standing wave multi-cell copper cavities inside a solenoid tunnel are selected to improve the positron capture efficiency. The cavity design strategy is presented to accommodate constrains from the large phase distribution of the incident beams, RF power and RF heating. A matrix of design parameters’ range are given for future system optimization when the capture cavities are considered together with other sub-systems and beam dynamics. The contents will also be useful for other CW cavity design for beams with large phase space distribution.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Modified gravity constraints from the full shape modeling of clustering measurements from DESI 2024

We present cosmological constraints on deviations from general relativity (GR) from the first-year of clustering observations from the Dark Energy Spectroscopic Instrument (DESI) in combination with other available datasets including the CMB data from Planck with CMB-lensing from Planck and ACT, BBN constraints on the physical baryon density, the galaxy weak lensing and clustering from DESY3 and supernova data from DESY5. We first consider the μ(a,k)–Σ(a,k) modified gravity (MG) parameterization (as well as η(a,k)) in a ΛCDM and a w 0 w a CDM cosmological backgrounds. Using a functional form for time-only evolution gives μ 0 = 0.11 +0.44 -0.54 from DESI(FS+BAO)+BBN and a wide prior on n s . Using DESI(FS+BAO)+CMB+DESY3+DESY5-SN, we obtain μ 0 = 0.05 ± 0.22 and Σ 0 = 0.008 ± 0.045 and similarly μ 0 = 0.02 +0.19 -0.24 and η 0 = 0.09 +0.36 -0.60 , in an ΛCDM background. In w 0 w a CDM we obtain μ 0 = -0.24 +0.32 -0.28 and Σ 0 = 0.006 ± 0.043, consistent with GR, and we still find a preference of the data for a dynamical dark energy with w 0 > -1 and w a < 0. Using functional dependencies in both time and scale gives μ 0 and Σ 0 with a same level of precision as above but other scale MG parameters remain hard to constrain. We then move to binned parameterizations in a ΛCDM background starting with two bins in redshift and obtain, μ 1 = 1.02 ± 0.13, μ 2 = 1.04 ± 0.11, Σ 1 = 1.021 ± 0.029 and Σ 2 = 1.022 +0.027 -0.023 , all consistent with the unity value of GR in the binning formalism. We then extend the analysis to combine two bins in redshift and two in scale giving 8 MG parameters that we find all consistent with GR. We note that we find here that the tension reported in previous studies about Σ 0 being inconsistent with GR when using Planck PR3 data goes away when we use the recent LoLLiPoP+HiLLiPoP likelihoods. As noted in previous studies, this seems to indicate that the tension is indeed related to the CMB lensing anomaly in PR3 which is also resolved when using the recent likelihoods. We then constrain the class of Horndeski theory in the effective field theory of dark energy approach. We consider both EFT-basis and α-basis in the analysis. Assuming a power law parameterization for the EFT function Ω, which controls non-minimal coupling, we obtain Ω 0 = 0.012 +0.001 -0.012 and s 0 = 0.996 +0.54 -0.20 from the combination of DESI(FS+BAO)+DESY5SN+CMB in a ΛCDM background, which are consistent with GR. Similar results are obtained when using the α-basis and assuming no-braiding (α B = 0) giving c M < 1.14 at 95% CL in a ΛCDM background, also in agreement with GR. However, we see a mild yet consistent indication for c B > 0 when α B is allowed to vary which will require further study to determine whether this is due to systematics or new physics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

Crew Earth Observations: Twelve Years of Documenting Earth from the International Space Station

The Crew Earth Observations (CEO) payload was one of the initial experiments aboard the International Space Station, and has been continuously collecting data about the Earth since Expedition 1. The design of the experiment is simple: using state-of-the-art camera equipment, astronauts collect imagery of the Earth's surface over defined regions of scientific interest and also document dynamic events such as storms systems, floods, wild fires and volcanic eruptions. To date, CEO has provided roughly 600,000 images of Earth, capturing views of features and processes on land, the oceans, and the atmosphere. CEO data are less rigorously constrained than other remote sensing data, but the volume of data, and the unique attributes of the imagery provide a rich and understandable view of the Earth that is difficult to achieve from the classic remote sensing platforms. In addition, the length-of-record of the imagery dataset, especially when combined with astronaut photography from other NASA and Russian missions starting in the early 1960s, provides a valuable record of changes on the surface of the Earth over 50 years. This time period coincides with the rapid growth of human settlements and human infrastructure.

Evans, Cynthia A.↗
NASA NTRSDate not supplied

Temporal Changes in Astronauts’ Muscle and Cardiorespiratory Physiology Before, During, and After Spaceflight

Background: NASA’s planned space exploration missions will require astronauts to safely perform extravehicular activity (EVA) and to safely egress vehicles in a variety of landing scenarios. Prolonged exposure to spaceflight can diminish tolerance for physical activity, decrease cardiovascular and sensorimotor function, cause loss of bone mineral density, as well as reduced muscle mass and strength. Although exercise can mitigate these spaceflight-induced physiological decrements, little is known regarding the time-course of changes in muscle and aerobic performance during spaceflight. Furthermore, these exercise countermeasures are not fully protective. For example, maximal aerobic capacity (VO2pk), lower body muscle cross-sectional area, and strength decrease by about 10% to 15% after short- (≈14 days) and long-duration (≈6 months) missions on the International Space Station (ISS). Future space missions longer in duration and further from Earth will employ exploration vehicles that will have exercise hardware with less robust and more constrained exercise capabilities than of those available on the ISS. Thus, countermeasures will need to be optimized to protect crew health and performance on exploration-class missions lasting up to 3 years. This requires a more detailed understanding of the dynamic effects of spaceflight on human health and performance, the ability of exercise to protect against this deconditioning, and the interaction of exercise with interrelated factors like nutrition, sleep, and environmental conditions. Methods: We will use standardized research and medical testing protocols previously validated in 1g and microgravity to quantify the time course and the inter-individual variability of changes in physical performance, including cardiorespiratory fitness and muscle strength and endurance, before, during, and after spaceflight missions lasting 2 months, 6 months, and 1 year. Additionally, we will use an extrapolation model to predict changes associated with multi-year exploration missions. Additionally, we will monitor in-flight exercise, nutrition, and sleep using in-flight assessment tools. Significance: Our testing protocols will provide valuable information for determining time course of change and the interindividual variability of spaceflight-induced deconditioning of aerobic capacity and muscle strength and endurance over the course of spaceflight missions up to and beyond 1 year. This information will be vital to assess whether humans can be physically ready for deep space exploration, such as on a mission to Mars, using current technology, or if additional mitigation strategies are necessary.

N Strock↗
DOE OSTI2023

Constraining the Multiscale Structure of Geophysical Fields in Machine Learning: The Case of Precipitation

The use of deep-learning algorithms for estimating the value of geophysical variables from remotely sensed information is rapidly expanding. The typical objective function minimized in such algorithms is the mean square error (MSE), which is known to lead to smooth estimates with compressed dynamical range as compared to the true distribution of the variable of interest. Here, we introduce and evaluate alternative objective functions, focusing on the retrieval of precipitation rates from satellite passive microwave radiometric measurements using a deep convolutional neural network. For this testbed application, the results show that explicitly imposing the preservation of the statistical distribution and spatial wavelet power spectrum of the target variable allows to accurately reproduce extreme values and sharp gradients across multiple scales in this study.

58 GEOSCIENCES↗
DOE OSTI2020

Structural reversibility of Cu doped NU-1000 MOFs under hydrogenation conditions

The metal-organic framework (MOF), NU-1000, and its metalated counterparts have found proof-of-concept application in heterogeneous catalysis and hydrogen storage amongst others. A vapor-phase technique, akin to atomic layer deposition (ALD), is used to selectively deposit divalent Cu ions on oxo, hydroxo-bridged hexa-zirconium(IV) nodes capped with terminal –OH and -OH 2 ligands. Subsequent reaction with steam yields node-anchored, CuII-oxo,hydroxo clusters. We find that cluster installation via AIM (= ALD In MOFs) is accompanied by an expansion of MOF mesopore (channel) diameter . We investigated the behavior of the cluster-modified material, termed Cu-AIM-NU-1000, to heat treatment up to 325 °C, at atmospheric pressure with a low flow of H2 into the reaction cell. The response under these conditions revealed two important results: (1) Above 200 °C, the initially installed few-metal-ion clusters reduce to neutral Cu atoms. The neutral atoms migrate from the nodes and aggregate into Cu nanoparticles. While the size of particles formed in the MOF interior is constrained by the width of mesopores (ca. 3 nm), those formed on the exterior surface of the MOF can grow as large as ca. 8 nm. (2) Reduction and release of Cu atoms from the MOFs nodes is accompanied NU-1000 undergoes dynamic structural transformation as it reverts back to its original dimension following the release. These results show while the MOF framework itself remains intact at 325 °C in an H 2 atmosphere, the small, AIM-installed Cu II -oxo,hydroxo clusters are stable with respect to reduction and conversion to metallic nanoparticles only up to ~200 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Direct prediction of nonlinear tearing mode saturation using a variational principle

It is shown that the variational principle of multi-region relaxed magnetohydrodynamics (MRxMHD) can be used to predict the stability and nonlinear saturation of tearing modes in strong guide field configurations without resolving the dynamics and without explicit dependence on the plasma resistivity. While the magnetic helicity is not a good invariant for tearing modes, we show that the saturated tearing mode can be obtained as an MRxMHD state of a priori unknown helicity by appropriately constraining the current profile. The predicted saturated island width in a tearing-unstable force-free slab equilibrium is shown to reproduce the theoretical scaling at small values of Δ' and the scaling obtained from resistive magnetohydrodynamics simulations at large Δ'.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Approximating Trajectory Constraints With Machine Learning – Microgrid Islanding With Frequency Constraints

Here, we introduce deep earning aided constraint encoding to tackle the frequency-constraint microgrid scheduling problem. The nonlinear function between system operating condition and frequency nadir is approximated by using a neural network, which admits an exact mixed-integer formulation (MIP). This formulation is then integrated with the scheduling problem to encode the frequency constraint. With the stronger representation power of the neural network, the resulting commands can ensure adequate frequency response in a realistic setting in addition to islanding success. The proposed method is validated on a modified 33-node system. Successful islanding with a secure response is simulated under the scheduled commands using a detailed three-phase model in Simulink. The advantages of our model are particularly remarkable when the inertia emulation functions from wind turbine generators are considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Tropical High Cloud Feedback Relationships to Climate Sensitivity

Clouds constitute a large portion of uncertainty in predictions of equilibrium climate sensitivity (ECS). While low cloud feedbacks have been the focus of intermodel studies due to their high variability among global climate models, tropical high cloud feedbacks also exhibit considerable uncertainty. Here, we apply the cloud radiative kernel technique of Zelinka et al. to 22 models across the CMIP5 and CMIP6 ensembles to survey tropical high cloud feedbacks and analyze their relationship to ECS. We find that the net high cloud feedback and its altitude and optical depth feedback components are significantly positively correlated with ECS in the tropical mean. On the other hand, the tropical mean high cloud amount feedback is not correlated with ECS. These relationships are most pronounced outside of areas of strong climatological ascent, suggesting the importance of thin cirrus feedbacks. Finally, we explore connections between high cloud feedbacks, climate sensitivity, and mean state high cloud properties. In general, high ECS models are cloudier in the upper troposphere but have a thinner high cloud population. Furthermore, we find that having more thin cirrus in the mean state relates to more positive high cloud altitude and optical depth feedbacks, and it either amplifies or dampens the high cloud amount feedback depending on the large-scale dynamical regime (amplifying in descent and dampening in ascent). In summary, our analysis highlights the importance of tropical high cloud feedbacks for driving intermodel spread in ECS and suggests that mean state high cloud characteristics might provide a unique opportunity for observationally constraining high cloud feedbacks.

atmosphere↗
DOE OSTI2020

California-Kepler Survey. IX. Revisiting the Minimum-mass Extrasolar Nebula with Precise Stellar Parameters

We investigate a possible correlation between the solid surface density Σ of the minimum-mass extrasolar nebula (MMEN) and the host star mass M {sub ⋆} and metallicity [Fe/H]. Leveraging on the precise host star properties from the California-Kepler Survey (CKS), we found that Σ=50{sub −20}{sup +33} g cm{sup −2} (a/1 au){sup −1.75±0.07} (M {sub ⋆}/M {sub ⊙}){sup 1.04±0.22} 10{sup 0.22±0.05[Fe/H]} for Kepler-like systems (1–4R {sub ⊕}; a < 1 au). The strong M {sub ⋆} dependence is reminiscent of previous dust continuum results that the solid disk mass scales with M {sub ⋆}. The weaker [Fe/H] dependence shows that sub-Neptune planets, unlike giant planets, form readily in lower metallicity environment. The innermost region (a < 0.1 au) of an MMEN maintains a smooth profile despite a steep decline of planet occurrence rate: a result that favors the truncation of disks by corotating magnetospheres with a range of rotation periods, rather than the sublimation of dust. The Σ of Kepler multitransiting systems shows a much stronger correlation with M {sub ⋆} and [Fe/H] than singles. This suggests that the dynamically hot evolution that produced single systems also partially removed the memory of formation in disks. Radial-velocity planets yielded a MMEN very similar to CKS planets; transit-timing-variation planets’ postulated convergent migration history is supported by their poorly constrained MMEN. We found that lower mass stars have a higher efficiency of forming/retaining planets: for Sun-like stars, about 20% of the solid mass within ∼1 au are converted/preserved as sub-Neptunes, compared to 70% for late-K to early-M stars. This may be due to the lower binary fraction, lower giant-planet occurrence, or the longer disk lifetime of lower mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Regulation of Solar Wind Electron Temperature Anisotropy by Collisions and Instabilities

Abstract Typical solar wind electrons are modeled as being composed of a dense but less energetic thermal “core” population plus a tenuous but energetic “halo” population with varying degrees of temperature anisotropies for both species. In this paper, we seek a fundamental explanation of how these solar wind core and halo electron temperature anisotropies are regulated by combined effects of collisions and instability excitations. The observed solar wind core/halo electron data in ( β ∥ , T ⊥ / T ∥ ) phase space show that their respective occurrence distributions are confined within an area enclosed by outer boundaries. Here, T ⊥ / T ∥ is the ratio of perpendicular and parallel temperatures and β ∥ is the ratio of parallel thermal energy to background magnetic field energy. While it is known that the boundary on the high- β ∥ side is constrained by the temperature anisotropy-driven plasma instability threshold conditions, the low- β ∥ boundary remains largely unexplained. The present paper provides a baseline explanation for the low- β ∥ boundary based upon the collisional relaxation process. By combining the instability and collisional dynamics it is shown that the observed distribution of the solar wind electrons in the ( β ∥ , T ⊥ / T ∥ ) phase space is adequately explained, both for the “core” and “halo” components.

Yoon, Peter H. (ORCID:0000000181343790)↗
NASA NTRS1990

The white dwarf luminosity function - A possible probe of the galactic halo

The dynamically inferred dark halo mass density, amounting to above 0.01 solar masses/cu pc at the sun's Galactocentric radius, can be composed of faint white dwarfs provided that the halo formed in a sufficiently early burst of star formation. The model is constrained by the observed disk white dwarf luminosity function which falls off below log (L/solar L) = -4.4, due to the onset of star formation in the disk. By using a narrow range for the initial mass function and an exponentially decaying halo star formation rate with an e-folding time equal to the free-fall time, all the halo dark matter is allowed to be in cool white dwarfs which lie beyond the falloff in the disk luminosity function. Although it is unlikely that all the dark matter is in these dim white dwarfs, a definite signature in the low-luminosity end of the white dwarf luminosity function is predicted even if they comprise only 1 percent of the dark matter. Current CCD surveys should answer the question of the existence of this population within the next few years.

Tamanaha, Christopher M.↗
NASA NTRS1994

Incremental triangulation by way of edge swapping and local optimization

This document is intended to serve as an installation, usage, and basic theory guide for the two dimensional triangulation software 'HARLEY' written for the Silicon Graphics IRIS workstation. This code consists of an incremental triangulation algorithm based on point insertion and local edge swapping. Using this basic strategy, several types of triangulations can be produced depending on user selected options. For example, local edge swapping criteria can be chosen which minimizes the maximum interior angle (a MinMax triangulation) or which maximizes the minimum interior angle (a MaxMin or Delaunay triangulation). It should be noted that the MinMax triangulation is generally only locally optical (not globally optimal) in this measure. The MaxMin triangulation, however, is both locally and globally optical. In addition, Steiner triangulations can be constructed by inserting new sites at triangle circumcenters followed by edge swapping based on the MaxMin criteria. Incremental insertion of sites also provides flexibility in choosing cell refinement criteria. A dynamic heap structure has been implemented in the code so that once a refinement measure is specified (i.e., maximum aspect ratio or some measure of a solution gradient for the solution adaptive grid generation) the cell with the largest value of this measure is continually removed from the top of the heap and refined. The heap refinement strategy allows the user to specify either the number of cells desired or refine the mesh until all cell refinement measures satisfy a user specified tolerance level. Since the dynamic heap structure is constantly updated, the algorithm always refines the particular cell in the mesh with the largest refinement criteria value. The code allows the user to: triangulate a cloud of prespecified points (sites), triangulate a set of prespecified interior points constrained by prespecified boundary curve(s), Steiner triangulate the interior/exterior of prespecified boundary curve(s), refine existing triangulations based on solution error measures, and partition meshes based on the Cuthill-McKee, spectral, and coordinate bisection strategies.

Wiltberger, N. Lyn↗
NASA NTRS2019

Precision Monitoring of Cool Evolved Stars: Constraining Effects of Convection and Pulsation

Mass loss from cool evolved stars is an important ingredient of the cosmic matter cycle, enriching the Universe with newly formed elements and dust. However, physical processes that are not considered in current models represent uncertainties in our general understanding of mass loss. Time-series of interferometric data provide the strongest tests of dynamical processes in the atmospheres of these stars. Here, we present a pilot study of such measurements obtained with the GRAVITY instrument on the Very Large Telescope Interferometer.

Andrea Chiavassa↗
NASA NTRS2023

A Framework for Estimating Global River Discharge From the Surface Water and Ocean Topography Satellite Mission

The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1 year after launch) will provide discharge for all river that reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge time series. We expect that discharge uncertainty will be less than 30% for two-thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage-constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge time series will be dominated by random error and are expected to be estimated within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.

Michael Durand↗
DOE OSTI2023

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2021

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. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.

Alexey N Shiklomanov↗
NASA NTRS1989

Neural learning of constrained nonlinear transformations

Two issues that are fundamental to developing autonomous intelligent robots, namely, rudimentary learning capability and dexterous manipulation, are examined. A powerful neural learning formalism is introduced for addressing a large class of nonlinear mapping problems, including redundant manipulator inverse kinematics, commonly encountered during the design of real-time adaptive control mechanisms. Artificial neural networks with terminal attractor dynamics are used. The rapid network convergence resulting from the infinite local stability of these attractors allows the development of fast neural learning algorithms. Approaches to manipulator inverse kinematics are reviewed, the neurodynamics model is discussed, and the neural learning algorithm is presented.

Barhen, Jacob↗