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DOE OSTI2022

Influence of Aerosol Embedded in Shallow Cumulus Cloud Fields on the Surface Solar Irradiance

Ubiquitous shallow cumulus clouds are associated with complex variability in surface solar irradiance (SSI). Aerosol embedded in the cloud field typically has a much smaller overall radiative effect, but can significantly perturb the shape of the SSI probability density function (PDF). These perturbations have important implications for several applications that utilize SSI, but are poorly quantified and are the subject of this study. Multiple cases of shallow cumulus cloud fields with embedded aerosol are simulated at the Southern Great Plains Atmospheric Observatory using large eddy simulation (LES). The LES-derived cloud and aerosol fields are then ingested into Monte Carlo three-dimensional (3D) radiative transfer to simulate SSI. We find a variety of perturbations to the SSI PDF that depend on aerosol presence and optical properties. The processes leading to these perturbations include extinction of the direct beam that often increases from the clear-sky region toward cloud edge due to aerosol hygroscopic growth, and scattering of radiation by aerosol into cloud shadows. The ability to predict the SSI PDF in the presence of aerosol is assessed by adding three representative aerosol optical properties into an existing machine learning framework. We show that machine learning accurately predicts the SSI PDF across a wide range of conditions with negligible computational expense. Importance metrics reveal the relatively high influence of aerosol optical properties in making the predictions. These new findings highlight the important role that aerosol plays in SSI variability for highly 3D cloud-aerosol environments and provides a computationally efficient route forward for its simulation.

3D radiative transfer↗

NASA NTRS1974

Impact-induced fractionation in the lunar highlands

A synthesis of the relevant data concerning lunar highland polymict breccias from the fields of petrography, chemistry, photogeology, and impact studies compels the prediction that the breccias should have homogeneous matrices from rock to rock within regions of the highlands of limited size where impact mixing has been efficient and extensive. But the matrices of returned breccias, even from one landing site, display a wide range in composition. This incompatibility between prediction and observation is a paradox that may be resolved by a process that acts after impact mixing to cause a differentiation of the breccia compositions. Partial melting of the local surficial material, and separation of melt and residue in ejecta and/or fall-back blankets, is compatible with the reviewed data and may resolve the paradox.

Warner, J. L.↗

NASA NTRS1984

The identification of hydrogen in Grw +70 deg 8247

The ultraviolet spectrum of the magnetic degenerate Grw -70 deg 8247 contains a relatively sharp, but resolved absorption feature near 1345 A. This is interpreted as the sigma(-), 1s0 to 2p-1 component of hydrogen Ly-alpha in a very strong magnetic field, near 350 megagauss. A cyclotron absorption may also exist near 2300 A, corresponding to such a field. Review of theoretical predictions of these hydrogen levels shows that a relatively sharp feature near 1335 A would be produced in fields within the range from 280 to 800 megagauss. The predicted wavelength has considerable uncertainty, perhaps + or - 10 A. Diffuse features in the red region of Palomar CCD spectra may arise from two sigma(-) and a pi component, based on even less certain computations for H-alpha. The large field is consistent with polarization data. The original bands discovered by Minkowski are not yet identifiable. But this important, magnetic star contains hydrogen even on the basis of Ly-alpha alone.

Greenstein, J. L.↗

NASA NTRS1990

Theoretical hypervelocity ballistic limit for single or double plates using nonlinear modal analysis

The original research on the use on nonlinear vibration technique to solve for the hypervelocity ballistic limit for double plates is examined. Such structure is commonly found in typical Space Station design where the incoming space or man-made debris would be fragmented upon hitting the outer plate (shield) and the subsequent impact on the main wall would result in a much reduced damge of the space station or spacecraft. The existing few theoretical impact equations do not agree well with each other. The existing computer code bumper used at NASA-Johnson Space Center appears to predict an unconservative ballistic limit when compared with experimental data where the velocity ranges from 3 km/s to 8 km/s. Such unconservative prediction is unacceptable from a practical safe design point of view. The bumper code is based on Wilkinson's (1968) paper and his equations have not been improved nor modified even though they are viewed with suspicion due to lack of agreement with experiments. To make matters worse, there is not another theory which is better than Wilkinson's equation and the designers are forced to use purely empirical Nysmith (1969) or semiempirical equations developed by Cour-Palais in 1969. The Cour-Palais equations were later modified empirically in 1989. The purpose of the present investigation is to examine the many assumptions of the Wilkinson equation. An attempt is made to present design charts based on the modified-Wilkinson equation so that the designer can get a feel of the ranges of the parameters which are of interest and discard a huge range of parameters, thus, significantly reducing the number of test shots required. The analysis is based on a solution of the governing nonlinear differential equations for a plate, assuming axisymmetric behavior using polar coordinates.

Hui, David↗

DOE OSTI2023

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗

NASA NTRS2001

Rotor Broadband Noise Prediction with Comparison to Model Data

This paper reports an analysis and prediction development of rotor broadband noise. The two primary components of this noise are Blade-Wake Interaction (BWI) noise, due to the blades' interaction with the turbulent wakes of the preceding blades, and "Self" noise, due to the development and shedding of turbulence within the blades' boundary layers. Emphasized in this report is the new code development for Self noise. The analysis and validation employs data from the HART program, a model BO-105 rotor wind tunnel test conducted in the German-Dutch Wind Tunnel (DNW). The BWI noise predictions are based on measured pressure response coherence functions using cross-spectral methods. The Self noise predictions are based on previously reported semiempirical modeling of Self noise obtained from isolated airfoil sections and the use of CAMRAD.Modl to define rotor performance and local blade segment flow conditions. Both BWI and Self noise from individual blade segments are Doppler shifted and summed at the observer positions. Prediction comparisons with measurements show good agreement for a range of rotor operating conditions from climb to steep descent. The broadband noise predictions, along with those of harmonic and impulsive Blade-Vortex Interaction (BVI) noise predictions, demonstrate a significant advance in predictive capability for main rotor noise.

Brooks, Thomas F.↗

NASA NTRS2003

Laser Ranging Simulation Program

Laser Ranging Simulation Program (LRSP) is a computer program that predicts selected aspects of the performances of a laser altimeter or other laser ranging or remote-sensing systems and is especially applicable to a laser-based system used to map terrain from a distance of several kilometers. Designed to run in a more recent version (5 or higher) of the MATLAB programming language, LRSP exploits the numerical and graphical capabilities of MATLAB. LRSP generates a graphical user interface that includes a pop-up menu that prompts the user for the input of data that determine the performance of a laser ranging system. Examples of input data include duration and energy of the laser pulse, the laser wavelength, the width of the laser beam, and several parameters that characterize the transmitting and receiving optics, the receiving electronic circuitry, and the optical properties of the atmosphere and the terrain. When the input data have been entered, LRSP computes the signal-to-noise ratio as a function of range, signal and noise currents, and ranging and pointing errors.

Piazolla, Sabino↗

DOE OSTI2021

The Atacama Cosmology Telescope: A Search for Planet 9

We use Atacama Cosmology Telescope (ACT) observations at 98 GHz (2015–2019), 150 GHz (2013–2019), and 229 GHz (2017–2019) to perform a blind shift-and-stack search for Planet 9. The search explores distances from 300 au to 2000 au and velocities up to 6farcm3 per year, depending on the distance (r). For a 5 Earth-mass Planet 9 the detection limit varies from 325 au to 625 au, depending on the sky location. For a 10 Earth-mass planet the corresponding range is 425 au to 775 au. The predicted aphelion and most likely location of the planet corresponds to the shallower end of these ranges. The search covers the whole 18,000 square degrees of the ACT survey. No significant detections are found, which is used to place limits on the millimeter-wave flux density of Planet 9 over much of its orbit. Overall we eliminate roughly 17% and 9% of the parameter space for a 5 and 10 Earth-mass Planet 9, respectively. These bounds approach those of a recent INPOP19a ephemeris-based analysis, but do not exceed it. We also provide a list of the 10 strongest candidates from the search for possible follow-up. More generally, we exclude (at 95% confidence) the presence of an unknown solar system object within our survey area brighter than 4–12 mJy (depending on position) at 150 GHz with current distance 300 au < r < 600 au and heliocentric angular velocityy <?CDATA $1\buildrel{\,\prime}\over{.} 5\,{\mathrm{yr}}^{-1}\lt v\cdot \tfrac{500\,\mathrm{au}}{r}\lt 2\buildrel{\prime\prime}\over{.} 3\,{\mathrm{yr}}^{-1}$?> 1 .' 5 yr – 1 < v · 500 au r < 2 ." 3 yr – 1 , corresponding to low-to-moderate eccentricities. These limits worsen gradually beyond 600 au, reaching 5–15 mJy by 1500 au.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2021

The Atacama Cosmology Telescope: A search for Planet 9

We use Atacama Cosmology Telescope (ACT) observations at 98 GHz (2015–2019), 150 GHz (2013–2019), and 229 GHz (2017–2019) to perform a blind shift-and-stack search for Planet 9. The search explores distances from 300 au to 2000 au and velocities up to 6\farcm3 per year, depending on the distance (r). For a 5 Earth-mass Planet 9 the detection limit varies from 325 au to 625 au, depending on the sky location. For a 10 Earth-mass planet the corresponding range is 425 au to 775 au. The predicted aphelion and most likely location of the planet corresponds to the shallower end of these ranges. The search covers the whole 18,000 square degrees of the ACT survey. No significant detections are found, which is used to place limits on the millimeter-wave flux density of Planet 9 over much of its orbit. Overall we eliminate roughly 17% and 9% of the parameter space for a 5 and 10 Earth-mass Planet 9, respectively. These bounds approach those of a recent INPOP19a ephemeris-based analysis, but do not exceed it. We also provide a list of the 10 strongest candidates from the search for possible follow-up. More generally, we exclude (at 95% confidence) the presence of an unknown solar system object within our survey area brighter than 4–12 mJy (depending on position) at 150 GHz with current distance 300 au < r < 600 au and heliocentric angular velocity 1\farcm5 per yr < v x (500au/r) < 2\farcs3 per yr, corresponding to low-to-moderate eccentricities. These limits worsen gradually beyond 600 au, reaching 5–15 mJy by 1500 au.

Sigurd Naess↗

NASA NTRS1988

Characterization of a centrifugal pump in He II

As part of an effort to determine the feasibility of helium transfer in space, a centrifugal pump was tested in He II at a variety of flow rates, pump speeds, and fluid temperatures. The pump, which has a straight bladed impeller 6.86 cm in diameter, generated a maximum pressure rise of 15 kPa and a maximum flow rate of 22 g/s for the conditions of the test. Pump performance seems to be independent of fluid temperature and is in good agreement with the values predicted by the manufacturer. Over the range of flow coefficients, the measured maximum efficiency is around 50 percent. Cavitation is observed in the pump and is thought to be highly dependent on the local heating of the helium in the pump. Preliminary measurements of the noise spectra of the pump suggest a possible mechanism to predict the onset of cavitation.

Weisend, J. G., II↗

DOE OSTI2021

A novel approach to partitioning evapotranspiration into evaporation and transpiration in flooded ecosystems

Reliable partitioning of micrometeorologically measured evapotranspiration (ET) into evaporation (E) and transpiration (T) would greatly enhance our understanding of the water cycle and its response to climate change related shifts in local-to-regional climate conditions and rising global levels of vapor pressure deficit (VPD). While some methods on ET partitioning have been developed, their underlying assumptions make them difficult to apply more generally, especially in sites with large contributions of E. Here, we report a novel ET partitioning method using artificial neural networks (ANNs) in combination with a range of environmental input variables to predict daytime E from nighttime ET measurements. The study uses eddy covariance data from four restored wetlands in the Sacramento-San Joaquin Delta, California, USA, as well as leaf-level T data for validation. The four wetlands vary in their vegetation make-up and structure, representing a range of ET conditions. The ANNs were built with increasing complexity by adding the input variable that resulted in the next highest average value of model testing R 2 across all sites. The order of variable inclusion (and importance) was: VPD > gap-filled sensible heat flux (H_gf) > air temperature (T air ) > friction velocity (u * ) > other variables. The model using VPD, H_gf, T air , and u * showed the best performance during validation with independent data and had a mean testing R 2 value of 0.853 (averaged across all sites, range from 0.728 to 0.910). In comparison to other methods, our ANN method generated T/ET partitioning results which were more consistent with CO 2 exchange data especially for more heterogeneous sites with large E contributions. Further, our method improves the understanding of T/ET partitioning. While it may be particularly suited to flooded ecosystems, it can also improve T/ET partitioning in other systems, increasing our knowledge of the global water cycle and ecosystem functioning.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2015

Pressure Loss Predictions of the Reactor Simulator Subsystem at NASA GRC

Testing of the Fission Power System (FPS) Technology Demonstration Unit (TDU) is being conducted at NASA GRC. The TDU consists of three subsystems: the Reactor Simulator (RxSim), the Stirling Power Conversion Unit (PCU), and the Heat Exchanger Manifold (HXM). An Annular Linear Induction Pump (ALIP) is used to drive the working fluid. A preliminary version of the TDU system (which excludes the PCU for now), is referred to as the RxSim subsystem and was used to conduct flow tests in Vacuum Facility 6 (VF 6). In parallel, a computational model of the RxSim subsystem was created based on the CAD model and was used to predict loop pressure losses over a range of mass flows. This was done to assess the ability of the pump to meet the design intent mass flow demand. Measured data indicates that the pump can produce 2.333 kg/sec of flow, which is enough to supply the RxSim subsystem with a nominal flow of 1.75 kg/sec. Computational predictions indicated that the pump could provide 2.157 kg/sec (using the Spalart-Allmaras turbulence model), and 2.223 kg/sec (using the k- turbulence model). The computational error of the predictions for the available mass flow is -0.176 kg/sec (with the S-A turbulence model) and -0.110 kg/sec (with the k-epsilon turbulence model) when compared to measured data.

Turbulence Models↗

NASA NTRS2016

Pressure Loss Predictions of the Reactor Simulator Subsystem at NASA Glenn Research Center

Testing of the Fission Power System (FPS) Technology Demonstration Unit (TDU) is being conducted at NASA Glenn Research Center. The TDU consists of three subsystems: the reactor simulator (RxSim), the Stirling Power Conversion Unit (PCU), and the heat exchanger manifold (HXM). An annular linear induction pump (ALIP) is used to drive the working fluid. A preliminary version of the TDU system (which excludes the PCU for now) is referred to as the "RxSim subsystem" and was used to conduct flow tests in Vacuum Facility 6 (VF 6). In parallel, a computational model of the RxSim subsystem was created based on the computer-aided-design (CAD) model and was used to predict loop pressure losses over a range of mass flows. This was done to assess the ability of the pump to meet the design intent mass flow demand. Measured data indicates that the pump can produce 2.333 kg/sec of flow, which is enough to supply the RxSim subsystem with a nominal flow of 1.75 kg/sec. Computational predictions indicated that the pump could provide 2.157 kg/sec (using the Spalart-Allmaras (S‒A) turbulence model) and 2.223 kg/sec (using the k- turbulence model). The computational error of the predictions for the available mass flow is ‒0.176 kg/sec (with the S-A turbulence model) and -0.110 kg/sec (with the k- turbulence model) when compared to measured data.

Mass Flow↗

DOE OSTI2020

Extended Search for the Invisible Axion with the Axion Dark Matter Experiment

This paper reports on a cavity haloscope search for dark matter axions in the galactic halo in the mass range 2.81–3.31 µeV . This search excludes the full range of axion-photon coupling values predicted in benchmark models of the invisible axion that solve the strong CP problem of quantum chromodynamics. Unprecedented sensitivity in this higher mass range is achieved by deploying an ultra low-noise Josephson parametric amplifier as the first-stage signal amplifier.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1979

An analytical study of electric vehicle handling dynamics

Hypothetical electric vehicle configurations were studied by applying available analytical methods. Elementary linearized models were used in addition to a highly sophisticated vehicle dynamics computer simulation technique. Physical properties of specific EV's were defined for various battery and powertrain packaging approaches applied to a range of weight distribution and inertial properties which characterize a generic class of EV's. Computer simulations of structured maneuvers were performed for predicting handling qualities in the normal driving range and during various extreme conditions related to accident avoidance. Results indicate that an EV with forward weight bias will possess handling qualities superior to a comparable EV that is rear-heavy or equally balanced. The importance of properly matching tires, suspension systems, and brake system front/rear torque proportioning to a given EV configuration during the design stage is demonstrated.

Greene, J. E.↗

DOE OSTI2022

Intense infrared lasers for strong-field science

The advent of chirped-pulse amplification in the 1980s and femtosecond Ti:sapphire lasers in the 1990s enabled transformative advances in intense laser–matter interaction physics. Whereas most of experiments have been conducted in the limited near-infrared range of 0.8–1 μm, theories predict that many physical phenomena such as high harmonic generation in gases favor long laser wavelengths in terms of extending the high-energy cutoff. Significant progress has been made in developing few-cycle, carrier-envelope phase-stabilized, high-peak-power lasers in the 1.6–2 μm range that has laid the foundation for attosecond X ray sources in the water window. Even longer wavelength lasers are becoming available that are suitable to study light filamentation, high harmonic generation, and laser–plasma interaction in the relativistic regime. Long-wavelength lasers are suitable for sub-bandgap strong-field excitation of a wide range of solid materials, including semiconductors. In the strong-field limit, bulk crystals also produce high-order harmonics. In this review, we first introduce several important wavelength scaling laws in strong-field physics, then describe recent breakthroughs in short- (1.4–3 μm), mid- (3–8 μm), and long-wave (8–15 μm) infrared laser technology, and finally provide examples of strong-field applications of these novel lasers. Furthermore, some of the broadband ultrafast infrared lasers will have profound effects on medicine, environmental protection, and national defense, because their wavelengths cover the water absorption band, the molecular fingerprint region, as well as the atmospheric infrared transparent window.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Machine Learning-Based Process Control for Injection Molding of Recycled Polypropylene

The increased interest in artificial intelligence in manufacturing has driven the adoption of machine learning to optimize processes and improve efficiency. A key challenge in injection molding is the variability of recycled materials, which affects part quality and processing stability. This study presents a novel closed-loop process control approach for injection molding, leveraging machine learning to adaptively predict processing inputs and quality outcomes. The methodology was tested on five blends of recycled polypropylene (rPP), using artificial neural networks (ANNs), linear regression, and polynomial regression to model the relationships between material properties and process parameters. The dataset was split 80/20 into training and testing sets. The ANN model was implemented using TensorFlow and Keras, with six hidden layers of 32 neurons per layer, ReLU activation, and an Adam optimizer. Empirical tuning and early stopping were used to optimize performance and prevent overfitting. Predictions were evaluated based on mean absolute error (MAE), mean squared error (MSE), and percentage error. The results showed that yield stress, ultimate elongation, and part weight were accurately predicted within a 5% error for linear and polynomial regression models and within a 10% error for the ANN. However, modulus predictions were less reliable, with errors of ~11% for ANN and linear regression and ~40% for polynomial regression, reflecting the inherent variability of this property in rPP blends. Predictions of processing inputs had errors ranging from 3% to 25%, depending on the model and response variable. No single modeling approach was consistently superior across all responses, highlighting the complexity of the relationship between material properties, process parameters, and quality metrics. Overall, the work demonstrates that closed-loop process control, powered by machine learning, can effectively predict key quality parameters in injection molding of recycled materials. The proposed approach can improve process stability and material utilization, facilitating increased adoption of sustainable materials.

Krantz, Joshua↗

NASA NTRS1987

3-D axial blade row flow field inviscid finite volume prediction and verification

A modification of the unsteady finite volume three-dimensional Euler scheme of Denton (1982) is developed to provide more accurate steady state solutions at enhanced convergence rates, and it is assessed for application to detailed axial blade row flow predictions by correlating predictions with data for a wide range of flow fields. Radial and pitchwise smoothing are minimized by the elimination of under-relaxing while time marching, by the addition of an internal transient averaging scheme, and by the use of the maximum stable local time step for each grid element. Results show that the flow field is accurately predicted in regions of primarily axial pressure gradients, though the predictions do not correlate well with the data in regions of strong nonaxial pressure gradients. Though the scheme is second order accurate in the axial direction, it is first order accurate in the other dimensions, smearing the flow field details.

Zacharias, Robert M.↗