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DOE OSTI2025

Snowmass 2021 cross frontier report: Dark matter complementarity

The fundamental nature of Dark Matter is a central theme of the Snowmass 2021 process, extending across all frontiers. In the last decade, advances in detector technology, analysis techniques and theoretical modeling have enabled a new generation of experiments and searches while broadening the types of candidates we can pursue. Over the next decade, there is great potential for discoveries that would transform our understanding of dark matter. In the following, we outline a road map for discovery developed in collaboration among the frontiers. A strong portfolio of experiments that delves deep, searches wide, and harnesses the complementarity between techniques is key to tackling this complicated problem, requiring expertise, results, and planning from all Frontiers of the Snowmass 2021 process.

Boveia, Antonio [The Ohio State Univ., Columbus, O↗
NASA NTRS2002

Shear Instabilities as a Probe of Jupiter's Atmosphere

Linear wave patterns in Jupiter clouds with wavelengths strongly clustered around 300 km are commonly observed in the planet's equatorial atmosphere. We propose that the preferred wavelength is related to the thickness of an unstable shear layer within the clouds. We numerically analyze the linear stability of wavelike disturbances that have nonzero horizontal phase speeds in Jupiter's atmosphere and find that. if the static stability in the strongly clustered around 300 km are commonly observed in the planet's equatorial atmosphere. We propose that the preferred wavelength is related to the thickness of an unstable shear layer within the clouds. We numerically analyze the linear stability of wavelike disturbances that have nonzero horizontal phase speeds in Jupiter's atmosphere and find that. if the static stability in the shear layer is very low (but still nonnegative), a deep vertical shear layer like the one measured by the Galileo probe can generate the instabilities. The fastest growing waves grow exponentially within an hour, and their wavelengths match the observations. Close to zero values of static stability that permit the growth of instabilities are within the range of values measured by the Galileo probe in a hot spot. Our model probes Jupiter's equatorial atmosphere below the cloud deck and suggests that thick regions of wind shear and low static stability exist outside hot spots.

Bosak, Tanja↗
NASA NTRS2002

Hot HB Stars in Globular Clusters - Physical Parameters and Consequences for Theory. VI. The Second Parameter Pair M3 and M13

We present the results of spectroscopic analyses of hot horizontal branch (HB) stars in M13 and M3, which form a famous second parameter pair. From the spectra we derived - for the first time in M13 - atmospheric parameters (effective temperature and surface gravity) as well as abundances of helium, magnesium, and iron. Consistent with analyses of hot HB stars in other globular clusters we find evidence for helium depletion and iron enrichment in stars hotter than about 12,000 K in both M3 and M13. Accounting for the iron enrichment substantially improves the agreement with canonical evolutionary models, although the derived gravities and masses are still somewhat too low. This remaining discrepancy may be an indication that scaled-solar metal-rich model atmospheres do not adequately represent the highly non-solar abundance ratios found in blue HB stars with radiative levitation. We discuss the effects of an enhancement in the envelope helium abundance on the atmospheric parameters of the blue HB stars, as might be caused by deep mixing on the red giant branch or primordial pollution from an earlier generation of intermediate mass asymptotic giant branch stars.

Moehler, S.↗
NASA NTRS2003

Hot HB Stars in Globular Clusters: Physical Parameters and Consequences for Theory: The Second Parameter Pair M 3 and M 13 - VI

We present the results of spectroscopic analyses of hot horizontal branch (HB) stars in M 13 and M 3, which form a famous "second parameter" pair. F rom the spectra and Stromgren photometry we derived - for the first time in M 13 - atmospheric parameters (effective temperature and surface gravity). For stars with Stromgren temperatures between 10,000 and 12,000 K we found excellent agreement between the atmospheric parameters derived from Stromgren photometry and those derived from Balmer line profile fits. However, for cooler stars there is a disagreement in the parameters derived by the two methods, for which we have no satisfactory explanation. Stars hotter than 12,000 K show evidence for helium depletion and iron enrichment, both in M 3 and M 13. Accounting for the iron enrichment substantially improves the agreement with canonical evolutionary models, although the derived gravities and masses are still somewhat too low. This remaining discrepancy may be an indication that scaled-solar metal-rich model atmospheres do not adequately represent the highly non-solar abundance ratios found in blue HB stars affected by diffusion. We discuss the effects of an enhancement in the envelope helium abundance on the atmospheric parameters of the blue HB stars, as might be caused by deep mixing on the red giant branch or primordial pollution from an earlier generation of intermediate mass asymptotic giant branch stars. Key words. Stars: atmospheres - Stars: evolution - Stars: horizontal branch - Globular clusters: individual: M 3 - Globular clusters: individual: M 13

Moehler, S.↗
NASA NTRS2022

Evolution of Biological Satellites: From Low Earth Orbit to NASA’s BioSentinel Deep Space Mission

NASA has set its sights on human exploration in deep space with the Artemis missions, with an ambitious plan to put astronauts back on the Moon and to eventually land human missions on Mars. Such missions will require significant countermeasures, likely both technological and biomedical, to protect biology from chronic radiation exposure. Small satellites like CubeSats can inform these countermeasures by querying relevant space environments with model organisms over relevant durations. NASA has launched five biological CubeSats into low Earth orbit (LEO) from GeneSat in 2006 to EcAMSat in 2017. Each one of these missions increased our understanding of the effects of spaceflight, while refining technologies and imparting valuable lessons to the next generation of CubeSats. The Artemis I rocket will carry ten CubeSats, each of them with its own objective. One in particular, BioSentinel, will conduct the first study of the biological response to interplanetary space radiation beyond LEO since Apollo 17. Once it reaches its heliocentric orbit – after a short lunar fly-by – BioSentinel will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast cells will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical density. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles.

Sergio R Santa Maria↗
DOE OSTI2024

FY24 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and data analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and crack formation in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), or,in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or more of: height, color, and 16-bit grayscale values as functions of position in a plane projection) to detect signs of surface corrosion and cracking after being trained on similar data, with the features to be detected. Although the initial scope included screening for broader indicators of corrosion, e.g., pitting, identification of potential cracks was prioritized for the past several years at the request of program leadership. Labeled training data is essential to developing the ML algorithm, and enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the large volume of data required to train ML algorithms and the relative rarity of cracks in the ICCWR data set. The updated program will read binary data from either LCM, WAMS or SEM files, interrogate data attributes, facilitate user labeling of data for training ML algorithms, execute ML algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. In FY24, hourglass neural networks (HNNs) that were initiated in FY22 were further developed and tested using available LCM data, and their performance was tested against that of the alternative U-Net Neural Network algorithm structure. HNNs along with previously developed Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) comprise a suite of ML tools for identification of cracks in the ICCWR

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1991

The formation of antipodal-impact terrains on Mars

The regions antipodal to Mars' three largest impact basins, Hellas, Isidis, and Argyre, were assessed for evidence of impact induced seismically disrupted terrains. Photogeology and preliminary computer modeling using the Simplified Arbitrary Lagrangian-Eulerian computer program suggest such terrain could have been formed by the Hellas and Isidis impacts. Previously, the only assessment of potential surface disruptions on Mars antipodal to large impacts was by Peterson (1978). Herein, the results give credence to Peterson's assertions. For Hellas, the computer model clearly suggests that antipodal pressures were probably strong enough to have fractured the crust and disrupted the surface, and may account for aspects of volcanism at Alba Patera. It is suggested that the Hellas impact produced sufficient focused energy at its antipode to produce deep fracture in the Martian crust centered below the current caldera for Alba Petera. With the generation and evolution of magma in the Tharsis area, the fracture system provided a ready conduit for early stage eruptions of Martians lavas derived from deep in the crust and/or upper mantle, perhaps of komatiitic composition.

Williams, D. A.↗
NASA NTRS2019

NASA’s Galactic Cosmic Ray Simulator at Brookhaven National Laboratory: Enabling Human Exploration Missions to the Moon and Mars

With exciting new Agency plans for a sustainable return to the moon, astronauts will once again leave earth’s protective magnetosphere only to endure higher levels of radiation from galactic cosmic rays (GCR) and the possibility of a large solar particle event (SPE). Gateway, lunar landers, and surface habitats will be designed to protect crew against SPE’s with vehicle optimization, storm shelter concepts, and/or active dosimetry; however, the ever-penetrating GCR will continue to pose the most significant health risks especially as lunar missions increase in duration and as NASA sets its aspirations on Mars. The primary risks of concern include epithelial carcinogenesis and leukemia, central nervous system effects resulting in potential in-mission cognitive or behavioral impairment and/or late neurological disorders, degenerative tissue effects including cataracts, circulatory and heart disease, as well as, potential immune system decrements impacting multiple aspects of crew health. Characterization and mitigation of these risks requires a significant reduction in the large biological uncertainties of chronic (low-dose rate) heavy ion exposures and the validation of countermeasures in a relevant space environment. NASA has developed the “GCR Simulator” at Brookhaven National Laboratory to generate a spectrum of ion beams that approximates the primary and secondary GCR field experienced at human organ locations within a deep-space vehicle. The majority of the dose is delivered from protons (~65-75%) and alpha particles (~10-20%) with heavier ions (Z≤3) contributing the remainder. The “GCR Simulator” exposes state-of-the art cellular and animal model systems to 33 sequential beams including 4 proton energies plus degrader, 4 helium energies plus degrader, and the five heavy ions of C, O, Si, Ti, and Fe. A polyethylene degrader is used with the 100 MeV/n H and He beams to provide a nearly continuous distribution of low energy particles. A 500 mGy exposure, delivering doses from each of the 33 beams, requires 75-90 minutes. To more closely simulate the low dose rates found in space, sequential field exposures can be divided into daily fractions over 2-4 weeks, with individual fractions as low as 0.1-0.2 mGy. In the large beam configuration (60 x 60 cm(exp 2)), 54 special housing cages can accommodate 2-3 mice each for a 70-75 min duration or ~15 individually housed rats. Emerging research results from our 2018 runs utilizing mixed heavy ion fields and protracted space exposures are forthcoming and deepen our understanding of the numerous health risks faced by our astronauts. This paper discusses NASA’s innovative technology solution for a ground-based GCR simulator at the NASA Space Radiation Laboratory to enable future exploration missions.

Lisa C Simonsen↗
NASA NTRSDate not supplied

NASA Space Radiation Laboratory Galactic Cosmic Ray Simulator

With exciting new Agency plans for a sustainable return to the moon, astronauts will once again leave earth’s protective magnetosphere only to endure higher levels of radiation from galactic cosmic rays (GCR) and the possibility of a large solar particle event (SPE). Gateway, lunar landers, and surface habitats will be designed to protect crew against SPEs with vehicle optimization, storm shelter concepts, and/or active dosimetry; however, the ever-penetrating GCR will continue to pose the most significant health risks especially as lunar missions increase in duration and as NASA sets its aspirations on Mars. The primary risks of concern include carcinogenesis, central nervous system effects resulting in potential in-mission cognitive or behavioral impairment and/or late neurological disorders, degenerative tissue effects including cataracts, circulatory and heart disease, as well as, potential immune system decrements impacting multiple aspects of crew health. Characterization and mitigation of these risks requires a significant reduction in the large biological uncertainties of chronic (low-dose rate) heavy ion exposures and the validation of countermeasures in a relevant space environment. NASA has developed the “GCR Simulator” at Brookhaven National Laboratory to generate a spectrum of ion beams that approximates the primary and secondary GCR field experienced at human organ locations within a deep-space vehicle. The majority of the dose is delivered from protons (~65-75%) and helium ions (~10-20%) with heavier ions (Z>3) contributing the remainder. The “GCR Simulator” exposes state-of-the art cellular and animal model systems to 33 sequential beams including 4 proton energies plus degrader, 4 helium energies plus degrader, and the five heavy ions of C, O, Si, Ti, and Fe. A polyethylene degrader is used with the 100 MeV/n H and He beams to provide a nearly continuous distribution of low energy particles. A 500 mGy exposure, delivering doses from each of the 33 beams, requires 75-90 minutes. To more closely simulate the low dose rates found in space, sequential field exposures can be divided into daily fractions over 2-6 weeks, with individual beam fractions as low as 0.1-0.2 mGy. In the large beam configuration (60 x 60 cm2), 54 special housing cages can accommodate 2-3 mice each for a 70-75 min duration or ~15 individually housed rats. Emerging research results from our 2018 runs utilizing mixed heavy ion fields and protracted space exposures are forthcoming and will deepen our understanding of the numerous health risks faced by astronauts. This talk discusses NASA’s innovative technology solution for a ground-based GCR simulator at the NASA Space Radiation Laboratory to enable future exploration missions.

galactic cosmic ray simulator↗
NASA NTRS1997

MEASUREMENT OF THE NOISE IMPROVEMENT OF A 34-METER CASSEGRAIN ANTENNA RETROFITTED WITH A LOW-BACKSCATTERING STRUT

Large axially-symmetric ground-based dual-reflector antennas are used in a variety of applications simultaneously requiring very high gain and very low noise (e.g., satellite communications, radio astronomy, deep-space communications, and radar). In these systems, reducing the noise by 10 % is equivalent to increasing the antenna gain by roughly 0.5 dB. Since the early days of radio-astronomy this fact has continuously driven efforts to reduce the noise of front-end low-noise amplifiers--a major noise contributor. As the performance of the front-end amplifiers improved, the relative importance of the noise generated by the surrounding warm ground increased, causing the antenna noise to become a major factor in the overall system sensitivity. Since large ground-based reflectors have been around for several decades, the various electrical and mechanical parameters affecting their performance have received considerable attention and are generally well understood. However, the impact of the subreflector supporting struts on the antenna noise performance remains a source of uncertainty. The reason for this stems from the usually large electrical dimensions involved, which precludes the accurate modeling of the various strut-scattering mechanisms. For the particular antennas used on NASA's Deep Space Network, which have been designed to minimize all noise sources, several studies have typically reported measured noise temperatures between 2 and 3 K (at approx. 8.45 GHz, antenna pointing at zenith), attributed to the struts and other unknown effects (see for example [1] and [2]). With this in mind, an effort has recently been conducted to determine optimal strut shapes to reduce the associated noise contribution [3].

Prata, A., Jr.↗
DOE OSTI2025

An efficient surrogate model of secondary electron formation and evolution

This work extends the adjoint-deep learning framework for runaway electron (RE) evolution, developed by McDevitt et al. [Phys. Plasmas 32, 042503 (2025)], to account for large-angle collisions. By incorporating large-angle collisions, the framework allows the avalanche of REs to be captured, an essential component of RE dynamics. This extension is accomplished by using a Rosenbluth–Putvinski approximation to estimate the distribution of secondary electrons generated by large-angle collisions. By evolving both the primary and multiple generations of secondary electrons, the present formulation can capture both the detailed temporal evolution of a RE population beginning from an arbitrary initial momentum space distribution, along with providing approximations to the saturated growth and decay rates of the RE population. Predictions of the adjoint-deep learning framework are verified against a traditional RE solver, with good agreement present across a broad range of parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2010

Design and Preliminary Thermal Performance of the Mars Science Laboratory Rover Heat Exchangers

The challenging range of proposed landing sites for the Mars Science Laboratory Rover requires a rover thermal management system that is capable of keeping temperatures controlled across a wide variety of environmental conditions. On the Martian surface where temperatures can be as cold as -123 degrees Centigrade and as warm as 38 degrees Centigrade, the Rover relies upon a Mechanically Pumped Fluid Loop (MPFL) and external radiators to maintain the temperature of sensitive electronics and science instruments within a -40 degrees Centigrade to 50 degrees Centigrade range. The MPFL also manages significant waste heat generated from the Rover power source, known as the Multi Mission Radioisotope Thermoelectric Generator (MMRTG). The MMRTG produces 110 Watts of electrical power while generating waste heat equivalent to approximately 2000 Watts. Two similar Heat Exchanger (HX) assemblies were designed to both acquire the heat from the MMRTG and radiate waste heat from the onboard electronics to the surrounding Martian environment. Heat acquisition is accomplished on the interior surface of each HX while heat rejection is accomplished on the exterior surface of each HX. Since these two surfaces need to be at very different temperatures in order for the MPFL to perform efficiently, they need to be thermally isolated from one another. The HXs were therefore designed for high in-plane thermal conductivity and extremely low through-thickness thermal conductivity by using aerogel as an insulator inside composite honeycomb sandwich panels. A complex assembly of hand welded and uniquely bent aluminum tubes are bonded onto the HX panels and were specifically designed to be easily mated and demated to the rest of the Rover Heat Recovery and Rejection System (RHRS) in order to ease the integration effort. During the cruise phase to Mars, the HX assemblies serve the additional function of transferring heat from the Rover MPFL to the separate Cruise Stage MPFL so that heat generated deep inside the Rover can be dissipated via the Cruise Stage radiators. Significant fabrication challenges had to be overcome in order to make the HX design a reality. The cruise phase thermal performance of the Rover HXs was verified in the cruise phase system level thermal vacuum test that was performed at JPL in January of 2009. The Rover HXs were modeled in I-DEAS TMG and predictions are compared to actual data from the test.

Heat Rejection System↗
NASA NTRS2015

A WRF-Chem Analysis of Flash Rates, Lightning-NOx Production and Subsequent Trace Gas Chemistry of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). This is a continuation of previous work, which compared lightning observations (Oklahoma Lightning Mapping Array and National Lightning Detection Network) with flashes generated by various flash rate parameterization schemes (FRPSs) from the literature in a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the 29-30 May 2012 Oklahoma thunderstorm. Based on the Oklahoma radar observations and Lightning Mapping Array data, new FRPSs are being generated and incorporated into the model. The focus of this analysis is on estimating the amount of lightning-generated nitrogen oxides (LNOx) produced per flash in this storm through a series of model simulations using different production per flash assumptions and comparisons with DC3 aircraft anvil observations. The result of this analysis will be compared with previously studied mid-latitude storms. Additional model simulations are conducted to investigate the upper troposphere transport, distribution, and chemistry of the LNOx plume during the 24 hours following the convective event to investigate ozone production. These model-simulated mixing ratios are compared against the aircraft observations made on 30 May over the southern Appalachians.

Cummings, Kristin A.↗
DOE OSTI2026

Hadron-Argon Cross-Section Measurements at Protodune

The Deep Underground Neutrino Experiment (DUNE) is a next-generation experiment designed to measure neutrino oscillations with unprecedented precision, specifically seeking to identify CP violation in the lepton sector. DUNE utilizes the Liquid Argon Time Projection Chamber (LArTPC) as its core detecting technology, offering high-resolution imaging to reconstruct neutrino interactions on argon. A primary challenge in this reconstruction is the modeling of hadronic final-state interactions (FSI), where hadrons produced at the initial interaction vertex undergo further scattering before escaping the nucleus. In this thesis, I utilize the ProtoDUNE-SP detector and its 1~GeV/$c$ hadron beam at the CERN Neutrino Platform to present the first measurements of total inelastic $\pi^+$-argon and proton-argon cross sections in an energy regime critical to DUNE. I detail the development and validation of the ``slicing method'', which utilizes a kiloton-scale LArTPC to extract hadron-argon cross sections. These measurements provide an indispensable benchmark for informing DUNE's FSI modeling, and our results show no significant tension with current model predictions. Additionally, I study the impact of FSI modeling on DUNE’s sensitivity to oscillation parameters. This study demonstrates that variations in FSI models may be degenerate with oscillation features, highlighting the necessity of using direct experimental data to refine interaction models. Finally, I provide an outlook on related studies that will further contribute to this effort, supporting the ambitious physics goals of upcoming neutrino oscillation programs including DUNE.

Yin-Rui, Liu [U. Chicago (main)]↗
DOE OSTI2025

Reduced-order modeling for efficient cross section library development in high-temperature gas reactor pebble-bed depletion analysis

Accurate modeling of running-in and equilibrium conditions in pebble-bed reactors (PBRs) requires precise microscopic multigroup neutron cross sections. In Griffin, deterministic neutronics calculations rely on multivariate interpolation over large cross section libraries, resulting in significant memory usage and performance bottlenecks. This work, together with a companion paper on Griffin integration, explores reduced-order models (ROMs) to replace interpolation with lightweight surrogates. Several ROM techniques are benchmarked, with deep neural networks (DNNs) demonstrating superior memory efficiency, scalability, and predictive accuracy. A total of 295 DNNs were trained to build a comprehensive isotope library, integrated into Griffin through a custom LibTorch interface for depletion analysis. Initial results demonstrate that DNN-based ROMs drastically reduce memory demands while preserving accuracy, enabling finer tabulations and additional state variables without overhead. In conclusion, the framework also supports online cross section generation and real-time DNN updates through transfer learning, improving fidelity by capturing self-shielding and evolving nuclide compositions during burnup.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2022

Unique Observational Constraints on the Seasonal and Longitudinal Variability of the Earth’s Planetary Albedo and Cloud Distribution Inferred From EPIC Measurements

Thorough comparison to observations is key to developing a credible climate model forecasting capability. Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation provide a unique observational perspective that permits a more reliable model/data comparison than is possible with the otherwise available satellite data. The uniqueness is in the DSCOVR satellite’s viewing geometry, which enables continuous viewing of the Earth’s sunlit hemisphere from its Lissajous orbit around the Lagrangian L1 point. The key instrument is the Earth Polychromatic Imaging Camera (EPIC), which views the Earth’s sunlit hemisphere with 1024-by-1024-pixel imagery in 10 narrow spectral bands from 317 to 780 nm, acquiring up to 22 high spatial resolution images per day. The additional feature is that the frequency of EPIC image acquisition is nearly identical to that of the climate GCM data generation scheme where climate data for the entire globe are ‘instantaneously’ calculated at 1-h radiation time-step intervals. Implementation of the SHS (Sunlit Hemisphere Sampling) EPIC-view geometry for the in-line GCM output data sampling establishes a precise self-consistency in the space-time data sampling between EPIC observational and GCM output data generation and sampling. The remaining problem is that the GCM generated data are radiative fluxes, while the EPIC measurements are backscatter-dependent radiances. Radiance to flux conversion is a complex problem with no simple way to convert GCM radiative fluxes into spectral radiances. The more expedient approach is to convert the EPIC spectral radiances into broadband radiances by MODIS/CERES-based regression relationships and then into solar radiative fluxes using the CERES angular distribution models. Averaging over the sunlit hemisphere suppresses the meteorological weather noise, but preserves the intra-seasonal larger scale variability. Longitudinal slicing by the Earth’s rotation permits a self-consistent model/data comparison of the longitudinal model/data differences in the variability of the reflected solar radiation. Ancillary EPIC Composite data provide additional cloud property information for climate model diagnostics. Comparison of EPIC-derived seasonal and longitudinal variability of the Earth’s planetary albedo with the GISS ModelE2 results shows systematic overestimate of cloud reflectivity over the Pacific Ocean with corresponding underestimates over continental land areas.

DSCOVR↗
DOE OSTI2024

Machine Learning‐Assisted Microearthquake Location Workflow for Monitoring the Newberry Enhanced Geothermal System

Abstract Enhanced geothermal systems (EGS) offer a sustainable energy source but face challenges in accurately locating microearthquakes induced during reservoir stimulation. Locating these microearthquakes provides reliable feedback on the stimulation progress. Current deep learning methods for locating earthquakes require extensive data sets for training, which is problematic as detected microearthquakes are often limited. To address the scarcity of training data, we propose a practical workflow using probabilistic multilayer perceptron (PMLP) which predicts microearthquake locations from cross‐correlation time lags in waveforms. Utilizing a 3D velocity model of Newberry site derived from ambient noise interferometry, we generate numerous synthetic microearthquakes and 3D acoustic waveforms for PMLP training. Accurate synthetic tests prompt us to apply the trained network to the 2012 and 2014 stimulation field waveforms. To enhance the accuracy of source localization, we carefully handpick the P‐arrival times. Predictions on the 2012 stimulation data set show major microseismic activity at depths of 0.5–1.2 km, correlating with a known casing leakage scenario. In the 2014 data set, the majority of predictions concentrate at 2.0–2.9 km depths, consistent with results obtained from conventional physics‐based inversion, and align with the presence of natural fractures from 2.0 to 2.7 km. We validate our findings by comparing the synthetic and field picks, demonstrating a satisfactory match for the first arrivals. By combining the benefits of quick inference speeds and accurate location predictions, we demonstrate the feasibility of using realistic synthetic data set to locate microseismicity for EGS monitoring.

15 GEOTHERMAL ENERGY↗
NASA NTRS2010

Robust Optimization Design Algorithm for High-Frequency TWTs

Traveling-wave tubes (TWTs), such as the Ka-band (26-GHz) model recently developed for the Lunar Reconnaissance Orbiter, are essential as communication amplifiers in spacecraft for virtually all near- and deep-space missions. This innovation is a computational design algorithm that, for the first time, optimizes the efficiency and output power of a TWT while taking into account the effects of dimensional tolerance variations. Because they are primary power consumers and power generation is very expensive in space, much effort has been exerted over the last 30 years to increase the power efficiency of TWTs. However, at frequencies higher than about 60 GHz, efficiencies of TWTs are still quite low. A major reason is that at higher frequencies, dimensional tolerance variations from conventional micromachining techniques become relatively large with respect to the circuit dimensions. When this is the case, conventional design- optimization procedures, which ignore dimensional variations, provide inaccurate designs for which the actual amplifier performance substantially under-performs that of the design. Thus, this new, robust TWT optimization design algorithm was created to take account of and ameliorate the deleterious effects of dimensional variations and to increase efficiency, power, and yield of high-frequency TWTs. This design algorithm can help extend the use of TWTs into the terahertz frequency regime of 300-3000 GHz. Currently, these frequencies are under-utilized because of the lack of efficient amplifiers, thus this regime is known as the "terahertz gap." The development of an efficient terahertz TWT amplifier could enable breakthrough applications in space science molecular spectroscopy, remote sensing, nondestructive testing, high-resolution "through-the-wall" imaging, biomedical imaging, and detection of explosives and toxic biochemical agents.

Wilson, Jeffrey D.↗