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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

High-Resolution Characterization of Comingled Contaminants in the Deep Vadose Zone, Hanford Site, Washington - 17387

The contaminated deep vadose zone in the Central Plateau of the Hanford Site in Washington state presents a unique challenge to remediation. The Comprehensive Environmental Response, Compensation, and Liability Act, commonly known as the CERCLA project responsible for addressing these deep contaminants is designated as the 200-Deep Vadose Zone Operable Unit (DV-1 project). The vadose zone is 55-82 meters (180-270 feet) thick and is contaminated with both radiological and chemical contaminants from multiple historical waste streams. The mobile contaminants from this waste are still present in the deep vadose zone and pose a potential threat to the groundwater. Characterizing the nature and extent of the comingled mobile contaminants is an important step before assessing possible remedial alternatives. One factor controlling the migration and distribution of subsurface contaminants is the lithologic heterogeneity of the vadose zone sediments. A sampling plan for the DV-1 project includes continuous sediment core collection and analysis to identify key lithologic factors (i.e., small-scale bedding and structural features) that act as barriers, preferential pathways or conduits for mobile contaminants migrating through the vadose zone. Over six hundred meters (2,000 feet) of intact sediment core from 26 boreholes were collected in 1.5 meters (5 feet) long, 10 centimeter (4-inch) diameter segments. These intact sediment samples provide significant improvement in the level of detail and understanding of mechanisms and features controlling contaminant distribution that is not possible with traditional homogenized drill cuttings or conventional split-spoon samples. Detailed geological descriptions and photographs of the intact core are correlated to high-resolution geophysical logs which aid in the development of a comprehensive contaminant distribution profile of the borehole. These lithologic interpretations are used to define specific depth intervals for sampling based on changes in moisture, lithology, and elevated gamma radiation. The selected samples are analyzed for contaminants of concern, geochemical parameters, and hydraulic properties. Significant lithologic features observed in the intact cores include sharp contact boundaries to graded bedding, iron-oxide and carbonate cementation, silty laminations, clastic dike intrusions, and soft sediment deformation. Preliminary geologic logs integrated with the sample analysis indicate features that correlate to the variable distribution of contaminants both laterally and vertically. Integration of measured hydraulic parameters to lithologic units in individual borehole profiles provide key inputs for more precise geo-framework and vadose zone flux models supporting the DV-1 project. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2015

Potential Mission Scenarios Post Asteroid Crewed Mission

A deep-space mission has been proposed to identify and redirect an asteroid to a distant retrograde orbit around the moon, and explore it by sending a crew using the Space Launch System and the Orion spacecraft. The Asteroid Redirect Crewed Mission (ARCM), which represents the third segment of the Asteroid Redirect Mission (ARM), could be performed on EM-3 or EM-4 depending on asteroid return date. Recent NASA studies have raised questions on how we could progress from current Human Space Flight (HSF) efforts to longer term human exploration of Mars. This paper will describe the benefits of execution of the ARM as the initial stepping stone towards Mars exploration, and how the capabilities required to send humans to Mars could be built upon those developed for the asteroid mission. A series of potential interim missions aimed at developing such capabilities will be described, and the feasibility of such mission manifest will be discussed. Options for the asteroid crewed mission will also be addressed, including crew size and mission duration.

Lopez, Pedro, Jr.↗
DOE OSTI2015

Spectroscopic evidence for negative electronic compressibility in a quasi-three-dimensional spin–orbit correlated metal

Negative compressibility is a sign of thermodynamic instability of open1,2,3 or non-equilibrium4,5 systems. In quantum materials consisting of multiple mutually coupled subsystems, the compressibility of one subsystem can be negative if it is countered by positive compressibility of the others. Manifestations of this effect have so far been limited to low-dimensional dilute electron systems6,7,8,9,10,11. Here, we present evidence from angle-resolved photoemission spectroscopy (ARPES) for negative electronic compressibility (NEC) in the quasi-three-dimensional (3D) spin–orbit correlated metal (Sr1-xLax)3Ir2O7. Increased electron filling accompanies an anomalous decrease of the chemical potential, as indicated by the overall movement of the deep valence bands. Such anomaly, suggestive of NEC, is shown to be primarily driven by the lowering in energy of the conduction band as the correlated bandgap reduces. Our finding points to a distinct pathway towards an uncharted territory of NEC featuring bulk correlated metals with unique potential for applications in low-power nanoelectronics and novel metamaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Potential Risks of Freshwater Aquifer Contamination with Geosequestration

Substantial leakage of CO 2 from deep geological strata to shallow potable aquifers is likely to be rare, but chemical detection of potential leakage nonetheless remains an integral component of any safe carbon capture and storage system. CO 2 that infiltrates an unconfined freshwater aquifer will have an immediate impact on water chemistry by lowering pH in most cases and by altering the concentration of total dissolved solids. Chemical signatures in affected waters provide an important opportunity for early detection of leaks. In the presence of CO 2 , trace elements such as Mn, Fe, and Ca can increase by an order of magnitude or more above control concentrations within 100 days. Therefore, these and other elements should be monitored along with pH as geochemical markers of potential CO 2 leaks. Dissolved inorganic carbon and alkalinity can also be rapidly responsive to CO 2 and are stable indicators of a leak. Importantly, such changes may be detectable long before direct changes in CO 2 are observed. The experimental results also suggest that the relative severity of the impact of leaks on overlying drinking-water aquifers should be considered in the selection of CO 2 sequestration sites. One primary selection criteria should be metal and metalloid availability, such as uranium and arsenic abundance, to carefully monitor chemical species that could trigger changes above maximum contaminant levels (MCLs). Overall, the risks of leakage from underground CO 2 storage are real but appear to be manageable if systems are closely monitored.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Operations of a Radioisotope-based Propulsion System Enabling CubeSat Exploration of the Outer Planets

Exploration to the outer planets is an ongoing endeavor but in the current economical environment, cost reduction is the forefront of all concern. The success of small satellites such as CubeSats launched to Near-Earth Orbit has lead to examine their potential use to achieve cheaper science for deep space applications. However, to achieve lower cost missions; hardware, launch and operations costs must be minimized. Additionally, as we push towards smaller exploration beds with relative limited power sources, allowing for adequate communication back to Earth is imperative. Researchers at the Center for Space Nuclear Research are developing the potential of utilizing an advanced, radioisotope-based system. This system will be capable of providing both the propulsion power needed to reach the destination and the additional requirements needed to maintain communication while at location. Presented here are a basic trajectory analysis, communication link budget and concept of operations of a dual-mode (thermal and electric) radioisotope-based propulsion system, for a proposed mission to Enceladus (Saturnian icy moon) using a 6U CubeSat payload. The radioisotope system being proposed will be the integration of three sub-systems working together to achieve the overall mission. At the core of the system, stored thermal energy from radioisotope decay is transferred to a passing propellant to achieve high thrust – useful for quick orbital maneuvering. An auxiliary closed-loop Brayton cycle can be operated in parallel to the thrusting mode to provide short bursts of high power for high data-rate communications back to Earth. Additionally, a thermal photovoltaic (TPV) energy conversion system will use radiation heat losses from the core. This in turn can provide the electrical energy needed to utilize the efficiency of ion propulsion to achieve quick interplanetary transit times. The intelligent operation to handle all functions of this system under optimized conditions adds to the complexity of the mission architecture.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Vadose zone monitoring at the radioactive waste management sites at the Nevada national security site - 15294

Two lysimeter facilities continuously monitor the vadose zone at the radioactive waste disposal sites at the Nevada National Security Site. The time-series data collected at these facilities support the performance assessments of the radioactive waste disposal sites, the closure cover designs, and the long-term monitoring decisions for these sites. The Weighing Lysimeter Facility at the Area 5 Radioactive Waste Management Site (RWMS) consists of a bare-soil weighing lysimeter and a vegetated weighing lysimeter. The upper surfaces of both weighing lysimeters are exposed to precipitation. The Drainage Lysimeter Facility at the Area 3 RWMS includes bare-soil lysimeters that receive precipitation or precipitation supplemented with irrigation equal to double precipitation and vegetated lysimeters that have the same upper boundary conditions as the bare-soil lysimeters. Lysimeter sensors are connected to data-loggers that are accessed remotely for data acquisition. Lysimeter water balance measurements show the arid climate and native vegetation at the NNSS provide a natural sustainable system to effectively prevent transport of contaminants from the RWMSs through the vadose zone to groundwater. Transport by infiltration and percolation of present day precipitation at the RWMSs is prevented. The native desert vegetation is adapted to extract moisture from very dry soils and maintains negative matric potentials at the base of the root zone effectively buffering the deep vadose zone from episodic precipitation events at the surface. The very negative matric potential at the base of the root zone effectively intercepts all infiltration from precipitation and draws moisture upward from the vadose zone below the root zone. This system is sustainable because it does not rely on engineered features and mimics the stable landscapes and no groundwater recharge of the current condition surrounding the RWMSs. The system depends on establishing native vegetation in the covers above the waste cells and a stable climate. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Impacts of Aerosol and Environmental Conditions on Maritime and Continental Deep Convective Systems Using a Bin Microphysical Model

A series of model simulations were conducted to investigate the effects of cloud condensation nuclei (CCN) loading and convective available potential energy (CAPE) on tropical maritime and midlatitude continental deep convection. Dynamical downscaling from global aerosol reanalysis was used to represent aerosol fields for the two convective regimes. We describe a control run and multiple sensitivity experiments using a limited-area model, employing spectral-bin cloud microphysics. The CCN loading is perturbed between the target maritime and continental conditions, roughly 40–2,000 cm -3 at 850 hPa and 1% supersaturation. Surface precipitation rates monotonically increase with increasing CCN loading for both the maritime and continental situations, while these monotonic increases are disrupted in the simulations with reduced CAPE. The increase in precipitation is in the form of convective precipitation, at the expense of stratiform precipitation. CCN increases promote increases in supercooled cloud water, in agreement with previous modeling studies. However, in the simulations investigated herein, the changes in supercooled water have different impacts on the cloud microphysics in the maritime and continental simulations. Increased supercooled water contents lead to more hail and less graupel in the continental simulation. For the maritime simulation, enhanced supercooled cloud water contents promote an increase in graupel since little or no hail is produced. This distinction is due to the difference in relative magnitudes and peak altitudes of supercooled water and snow amounts, which is further attributable to moisture and dynamical differences in the two cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Influence of Agricultural Managed Aquifer Recharge (AgMAR) and Stratigraphic Heterogeneities on Nitrate Reduction in the Deep Subsurface

Agricultural managed aquifer recharge (AgMAR) is a strategy whereby surface water is used to intentionally flood croplands to recharge underlying aquifers. However, nitrate (NO 3 - ) contamination in agriculturally intensive regions poses a threat to groundwater resources under AgMAR. We use a reactive transport model to understand the effects of AgMAR management strategies (i.e., by varying the frequency, duration between flooding events, and amount of water) on NO 3 - leaching to groundwater under different stratigraphic configurations and antecedent moisture conditions. We examine the potential of denitrification and nitrogen retention in deep vadose zone sediments (~15 m) using variable AgMAR application rates on two-dimensional representations of differently textured soils, soils with discontinuous bands/channels, and with preferential flow paths characteristic of agricultural fields. Simulations indicate finer textured sediments, alone or embedded within/adjacent to high flow regions, are important reducing zones providing conditions needed for denitrification. Simulation results suggest that applying water all-at-once rather than in increments transports higher concentrations of NO 3 - deeper into the profile, which may exacerbate groundwater quality. This transport into deeper depths can be aggravated by wetter antecedent soil moisture conditions. However, applying water all-at-once also increases denitrification within the vadose zone by promoting anoxic conditions. We conclude that AgMAR can be designed to enhance denitrification in the subsurface and reduce NO 3 - leaching to groundwater, while specifically accounting for lithologic heterogeneity, antecedent soil moisture conditions, and depth to the water table. Our findings are potentially relevant to other systems that experience flooding inundation such as floodplains and dedicated recharge basins.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Inter-Calibration and Concatenation of Climate Quality Infrared Cloudy Radiances from Multiple Instruments

A change in climate is not likely captured from any single instrument, since no single instrument can span decades of time. Therefore, to detect signals of global climate change, observations from many instruments on different platforms have to be concatenated. This requires careful and detailed consideration of instrumental differences such as footprint size, diurnal cycle of observations, and relative biases in the spectral brightness temperatures. Furthermore, a common basic assumption is that the data quality is independent of the observed scene and therefore can be determined using clear scene data. However, as will be demonstrated, this is not necessarily a valid assumption as the globe is mostly cloudy. In this study we highlight challenges in inter-calibration and concatenation of infrared radiances from multiple instruments by focusing on the analysis of deep convective or anvil clouds. TRMM/VIRS is potentially useful instrument to make correction for observational differences in the local time and foot print sizes, and thus could be applied retroactively to vintage instruments such as AIRS, IASI, IRIS, AVHRR, and HIRS. As the first step, in this study, we investigate and discuss to what extent AIRS and VIRS agree in capturing deep cloudy radiances at the same local time. The analysis also includes comparisons with one year observations from CrIS. It was found that the instruments show calibration differences of about 1K under deep cloudy scenes that can vary as a function of land type and local time of observation. The sensitivity of footprint size, view angle, and spectral band-pass differences cannot fully explain the observed differences. The observed discrepancies can be considered as a measure of the magnitude of issues which will arise in the comparison of legacy data with current data.

cloudy radiance↗
DOE OSTI2023

SMEFT probes in future precision DIS experiments

We analyze the potential of future high-energy deep-inelastic scattering (DIS) experiments to probe new physics within the framework of the Standard Model effective field theory (SMEFT). We perform a detailed study of SMEFT probes at a future Large Hadron-electron Collider (LHeC) and a Future Circular lepton-hadron Collider (FCC-eh) machine, and extend previous simulations of the potential of an electron-ion collider (EIC) to include 𝑍-boson vertex corrections. Precision 𝑍-pole constraints on vertex corrections suffer from numerous degeneracies in the Wilson-coefficient parameter space. We find that both the LHeC and the FCC-eh can help remove these degeneracies present in the existing global fits of precision 𝑍-pole observables and LHC data. The FCC-eh and LHeC will in many cases improve upon the existing precision electroweak bounds on the SMEFT parameter space. This highlights the important role of precision DIS measurements for new physics studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A deep learning-based battery sizing optimization tool for hybridizing generation plants

Hybrid generation and energy storage systems offer the ability to increase flexibility of the combined asset. This flexibility can be used to increase provision of services already provided by the generation asset, such as timing sale of electricity to the energy market during high price periods, and also enable provision of additional services, such as ancillary services or contribute to resource adequacy. From a generation asset owner perspective, the decision to hybridize includes selecting an energy storage system that, among other factors, maximizes financial performance of the energy storage investment. Yet, existing tools to optimize energy storage sizing are either too rudimentary (i.e., based on “rules of thumb”) or too complex to implement (i.e., require specialized engineering and software knowledge and a high-performance computer to run). This work presents a novel deep learning-based battery sizing optimization tool that is designed to help generation asset owners easily assess preliminary sizing considerations for potential battery investments to hybridize their generation facility. The tool uses deep learning to predict revenue over a broad search space of potential battery sizes, estimates capital and operating costs (including accounting for battery degradation), and computes financial performance of each potential battery system investment, recommending a system with maximum financial performance. The tool is tested and validated for hydropower assets. Finally, this tool will help a greater cross-section of industry consider investments in battery systems, increasing their revenue and helping them compete in rapidly evolving electrify markets.

13 HYDRO ENERGY↗
NASA NTRS1989

Jupiter's Great Red Spot as a shallow water system

Voyager cloud-top velocity data for Jupiter's Great Red Spot (GRS) is used to derive the bottom topography up to a constant that depends on the unknown radius of deformation. The bottom topography is inferred from the Bernoulli streamfunction, kinetic energy per unit mass, and absolute vorticity values derived from the velocity data. The results are used to calculate potential vorticity versus latitude far from the vortex. It is found that the deep atmosphere is in differential motion and that the far-field potential vorticity gradient changes sign at several latitudes. Numerical experiments are conducted to study the time-dependent behavior of the shallow water analog of Jupiter's analog.

Dowling, Timothy E.↗
DOE OSTI2020

A Roadmap for Reaching the Potential of Brain-Derived Computing

Neuromorphic computing is a critical future technology for the computing industry, but it has yet to achieve its promise and has struggled to establish a cohesive research community. A large part of the challenge is that full realization of the potential of brain inspiration requires advances in both device hardware, computing architectures, and algorithms. This simultaneous development across technology scales is unprecedented in the computing field. This article presents a strategy, framed by market and policy pressures, for moving past these current technological and cultural hurdles to realize its full impact across technology. Achieving the full potential of brain-derived algorithms as well as post-complementary metal-oxide-semiconductor (CMOS) scaling neuromorphic hardware requires appropriately balancing the near-term opportunities of deep learning applications with the long-term potential of less understood opportunities in neural computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗
DOE OSTI2021

Deeply Rooted: Evaluating Plant Rooting Depth as a Means for Enhanced Soil Carbon Sequestration (Full Technical Report)

Soils store three times as much carbon (C) as the atmosphere, but are not at capacity, and enhanced soil C storage is considered an essential strategy to mitigate rising atmospheric CO 2 levels. Agricultural soils have experienced substantial C loss in the past century due to poor agricultural practices and erosion. A shift towards deep-rooting crops and low-impact soil management could potentially increase long-term sequestration of C fixed by plants and stored in their root tissues, particularly for crops that have naturally deep root systems (>1 meter). A substantial amount of the CO 2 taken up by plants is allocated to their root systems, and because C deposited in deep soil layers has a longer residence time (up to millennia, in contrast to C deposited in topsoils), C increases at depth may have better long-term C sequestration potential than topsoils. However, the accrual, turnover, and stabilization of C in subsoils is a critical knowledge gap. We investigated a deeply rooted plant, switchgrass (Panicum virgatum), as a means of increasing carbon stocks in marginal and agricultural soils. We hypothesized that deep (>30 cm) SOC stocks would be greater under bioenergy crops relative to stocks under shallow-rooted conventional crop cover. To test this hypothesis, we compared soil depth profiles beneath deeply rooted switchgrass (cultivated for 4-30 years) and paired shallowrooted annual controls. We studied 12 field sites, 3 that were collected in 2018 before the start of the project as part a Department of Energy (DOE) Sustainable Biofuels study, and 9 that we collected in 2019 on a national field sampling campaign across the eastern US. In our publication from the 2018 study, which was written in collaboration with the LLNL Soil Microbiome Scientific Focus Area (SFA), we found that C stocks increased under switchgrass, but that the increases were dependent on soil texture. In the 2019 study, we found that carbon accrual tended to occur most consistently in low C soil in the southern US, which could indicate that perennial grasses may be a viable strategy to increase SOC in marginals soils in this region. We have published two studies from the 2019 sampling campaign thus far, we measured microbial growth parameters that will aid in modeling subsoil carbon cycling, and we found that switchgrass appears to move water upward in the soil profile and could promote drought tolerance, which a phenomenon commonly performed by trees known as ‘hydraulic redistribution;’ our study is the first to show this can occur in deep-rooted grasses. Finally, we published a modeling paper in collaboration with the LLNL Soil Microbiome SFA, where we found that poorly crystalline minerals are abundant and strongly correlated with organic C in geographically limited zones with enhanced weathering rates. Our results will inform technological development in the agricultural carbon sequestration sector as well as future negative emissions policies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS2008

Qualification of Commercial XIPS(R) Ion Thrusters for NASA Deep Space Missions

Electric propulsion systems based on commercial ion and Hall thrusters have the potential for significantly reducing the cost and schedule-risk of Ion Propulsion Systems (IPS) for deep space missions. The large fleet of geosynchronous communication satellites that use solar electric propulsion (SEP), which will approach 40 satellites by year-end, demonstrates the significant level of technical maturity and spaceflight heritage achieved by the commercial IPS systems. A program to delta-qualify XIPS(R) ion thrusters for deep space missions is underway at JPL. This program includes modeling of the thruster grid and cathode life, environmental testing of a 25-centimeter electromagnetic (EM) thruster over DAWN-like vibe and temperature profiles, and wear testing of the thruster cathodes to demonstrate the life and benchmark the model results. This paper will present the delta-qualification status of the XIPS thruster and discuss the life and reliability with respect to known failure mechanisms.

electric propulsion↗
DOE OSTI2017

Deep learning in color: towards automated quark/gluon jet discrimination

Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. Here, to establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate quark and gluon jets better than observables designed by physicists. Our approach builds upon the paradigm that a jet can be treated as an image, with intensity given by the local calorimeter deposits. We supplement this construction by adding color to the images, with red, green and blue intensities given by the transverse momentum in charged particles, transverse momentum in neutral particles, and pixel-level charged particle counts. Overall, the deep networks match or outperform traditional jet variables. We also find that, while various simulations produce different quark and gluon jets, the neural networks are surprisingly insensitive to these differences, similar to traditional observables. This suggests that the networks can extract robust physical information from imperfect simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Improving the Transportability of a Deep Learning Denoising Model Using Transfer Learning Techniques

The adoption of machine learning techniques in the seismology community has led to great performance improvements in several areas, including signal processing. Specifically, the development of deep learning–based seismic waveform denoising models has the potential to yield improvements in signal detection capabilities for networks operating in particularly noisy environments. Recent advancements in the design of these deep learning denoising models have included the incorporation of continuous and discrete wavelet transform functions into the network architecture to improve the learning capabilities and efficiency of said models. These wavelet transform–based seismic denoising models have shown improved denoising capabilities in regions where there is good agreement between the data features present in the training and evaluation datasets. However, questions remain about the overall transportability of these models to other monitoring regions. Here, in this study, we will determine the baseline transportability of a newly developed multilevel wavelet‐transform convolutional neural network (MWCNN) seismic denoising model. We accomplish this by taking a version of the MWCNN denoising model trained on data collected from the Utah region and evaluating its denoising performance on datasets collected from the neighboring Nevada region, which differ with regard to monitoring sensor types and event histories. We find that there is a notable variability in denoising performance related to the degree of similarity between the initial and new target datasets. The most notable difference in denoising performance is the ability of the denoising model to preserve accurate amplitude information associated with the signal energy present in the waveform data. Finally, we evaluate the ability of transfer learning techniques to improve the transportability of the MWCNN denoising model. We find that although there is still a performance gap present in the denoising results of the MWCNN model, transfer learning did yield improved results.

Quinones, Louis [Sandia National Laboratories (SNL↗