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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,027 records · Page 57
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Using Mineralogy to Interpret Martian Geologic History

The surface mineralogy of Mars is key to interpreting the planet’s geologic history and constraining when and where Mars may have been habitable to microbial life. Orbital mineralogical data from infrared spectrometers collected over the last two decades have demonstrated that Mars is more than a basaltic planet. Thermal infrared (TIR) emission spectrometers have identified regional variations in igneous minerals, iron oxides, and chloride salts, showing evidence for magmatic evolution and aqueous alteration. Orbital visible/shortwave infrared reflectance spectra provide detailed information about the aqueous history of Mars through the identification of clay minerals, sulfates, carbonates, zeolites, and amorphous materials in ancient ~3-4-billion-year-old terrains. Mineralogical data from rovers allow us to better characterize mineral formation mechanisms by identifying mineral assemblages and placing them in geologic context using outcrop- to grain-scale images. TIR and Mössbauer data from the Mars Exploration Rovers helped identify an ancient dune-interdune playa environment with multiple episodes of groundwater at Meridiani Planum and volcanism-induced hydrothermalism at Gusev crater. The CheMin X-ray diffractometer on the Mars Science Laboratory Curiosity rover in Gale crater is the first fully quantitative mineralogical instrument sent to another planetary surface. CheMin data allow the quantification of minerals and X-ray amorphous materials with a mineral detection limit of <1 wt.% and provide crystal chemistry of major phases from refined unit-cell parameters. CheMin has revealed local mineralogical changes in ancient sedimentary rocks not seen from orbit and helped identify habitable environments. Throughout the 600+ m of vertical stratigraphy studied so far, changes in clay mineralogy, Fe-oxides/oxyhydroxides, sulfates, and carbonates demonstrate a long history of surface and groundwater at Gale crater with variable salinity, pH, Eh, and temperature. Recent CheMin data document a decrease in clay minerals and an increase in sulfate minerals in younger strata that corresponds with a change from fluvio-lacustrine to eolian depositional environments, potentially documenting a change to a drier climate across the planet.

E. B. Rampe↗
DOE OSTI2019

The pros and cons of beyond standard model interpretations of ANITA events

The Antarctic Impulsive Transient Antenna (ANITA) experiment has observed two air shower events with energy ~500 PeV emerging from the Earth with exit angles ~30⁰ above the horizon. As was immediately noted by the ANITA Collaboration, these events (in principle) could originate in the atmospheric decay of an upgoing τ-lepton produced through a charged current interaction of a ντ inside the Earth. However, the relatively steep arrival angles of these perplexing events create tension with the standard model (SM) neutrino-nucleon interaction cross section. Deepening the conundrum, the IceCube neutrino telescope and the Pierre Auger Observatory with substantially larger exposures to cosmic ντ's in this energy range have not observed any events. This lack of observation implies that the messenger particle (MP) giving rise to ANITA events must produce an air shower event rate at least a factor of 40 larger than that produced by a flux of τ-neutrinos to avoid conflicts with the upper limits reported by the IceCube and the Pierre Auger collaborations. In addition, the sensitivity of ANITA to MP-induced events must be comparable to or larger than those of IceCube and Auger to avoid conflict with the non-observation of any signal at these facilities. Beyond SM interpretations of ANITA events can be classified according to whether the MPs: (i) live inside the Earth, (ii) originate in neutrino-nucleon collisions inside the Earth, (iii) come from cosmological distances. In this communication we investigate the positive and negative facets of these three classes of models.

None, None↗
DOE OSTI2021

Challenges of Interpreting and Applying New IPC-J-STD-001 Cleanliness Standards in High-Reliability Applications

The electronics industry has rapidly and widely embraced the replacement of ROSE testing with an SIR-focused approach to testing for certification of a qualified manufacturing plan. These new cleanliness documentation standards, housed in IPC J-STD-001 Rev. H, have just begun to impact electronics manufacturers as design and production teams work through how to meet them. This research focuses on the particular challenges of applying these new standards in high-reliability product applications, through the lens of interpreting SIR test results and what they mean for process capability, repeatability and diagnosing a need for process changes. The experiments examined a variety of factors that influence SIR results and suggest areas where SIR test plans can be greatly improved.

Capen, William↗
DOE OSTI2023

Interpretable Joint Event-Particle Reconstruction for Neutrino Physics at NOvA with Sparse CNNs and Transformers

The complex events observed at the NOvA long-baseline neutrino oscillation experiment contain vital information for understanding the most elusive particles in the standard model. The NOvA detectors observe interactions of neutrinos from the NuMI beam at Fermilab. Associating the particles produced in these interaction events to their source particles, a process known as reconstruction, is critical for accurately measuring key parameters of the standard model. Events may contain several particles, each producing sparse high-dimensional spatial observations, and current methods are limited to evaluating individual particles. To accurately label these numerous, high-dimensional observations, we present a novel neural network architecture that combines the spatial learning enabled by convolutions with the contextual learning enabled by attention. This joint approach, TransformerCVN, simultaneously classifies each event and reconstructs every individual particle's identity. TransformerCVN classifies events with 90% accuracy and improves the reconstruction of individual particles by 6% over baseline methods which lack the integrated architecture of TransformerCVN. In addition, this architecture enables us to perform several interpretability studies which provide insights into the network's predictions and show that TransformerCVN discovers several fundamental principles that stem from the standard model.

Shmakov, Alexander↗
DOE OSTI2023

Learning to Branch with Interpretable Machine Learning Models

Machine learning is being increasingly used in improving decisions made within branch-and-bound algorithms for solving mixed-integer programs (MIPs). Branching is a key component in branch-and-bound algorithms, this work presents IDAES-core project update on building simple and interpretable machine learning models for branching and improving decision-making tools applied for the optimization of advanced energy systems.

Bayramoglu, Selin↗
DOE OSTI2019

Performance and Compliance Monitoring - Different Objectives and Different Interpretation - 19109

Environmental surveillance and monitoring are a critical part of an overall strategy for protection of the public and environment. For site closure and disposal activities, monitoring and surveillance can be expected to continue many years into the future. In the case of environmental monitoring, two general types are commonly discussed: compliance and performance (or functional) monitoring. The objective of compliance monitoring is relatively clear. Compliance monitoring is conducted to demonstrate compliance with specific regulatory limits (e.g., maximum contaminant levels in groundwater). In this case, if your measurement is above these values, it is a regulatory concern. Monitoring can be especially challenging for engineered solutions involving robust barriers expected to last for decades or potentially hundreds or thousands of years. Although some gradual releases are expected to occur as barriers lose effectiveness, observable changes in groundwater are likely to be very small and may be delayed for very long times. For robust engineered systems, compliance in the near future is not expected to be a significant concern. The question becomes, what type of monitoring can be used to identify the potential for a compliance problem in the future? This has led to increasing use of performance monitoring as an early warning system. Rather than comparing against environmental standards, performance monitoring is compared against assumptions and results from a performance assessment. Performance monitoring is used to observe other potential indicators of changes in system behavior (vadose zone concentrations, changes in chemistry near the waste, changes in engineered features). Translating a change in a local measurement to a potential change in the concentration in an aquifer that would lead to a potential compliance concern in the future is a significant challenge for performance monitoring. Such monitoring needs to be more carefully interpreted and communicated than compliance monitoring. Considerations for implementation of performance monitoring are the focus of this paper. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Form factors for semileptonic B-decays with HISQ light quarks and clover b-quarks in Fermilab interpretation

We compute the vector, scalar, and tensor form factors for the $B\to \pi$, $B\to K$, and $B_s\to K$ amplitudes, which are needed to describe semileptonic $B$-meson decay rates for both the charged and neutral current cases. We use the highly improved staggered quark (HISQ) action for the sea and light valence quarks. The bottom quark is described by the clover action in the Fermilab interpretation. Simulations are carried out on $N_f = 2+1+1$ MILC HISQ ensembles at approximate lattice spacings from $0.15$ fm down to $0.057$ fm. We present blinded preliminary results for the form factors.

Jeong, Hwancheol↗
DOE OSTI2024

Interpreting Transformers for Jet Tagging

Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments like ATLAS and CMS at the CERN LHC. Particle Transformer (ParT), a state-of-the-art model, leverages particle-level attention to improve jet-tagging tasks, which are critical for identifying particles resulting from proton collisions. This study focuses on interpreting ParT by analyzing attention heat maps and particle-pair correlations on the $\eta$-$\phi$ plane, revealing a binary attention pattern where each particle attends to at most one other particle. At the same time, we observe that ParT shows varying focus on important particles and subjets depending on decay, indicating that the model learns traditional jet substructure observables. These insights enhance our understanding of the model's internal workings and learning process, offering potential avenues for improving the efficiency of transformer architectures in future high-energy physics applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

$B\rightarrow D^{(*)}$ decays from $N_f=2+1+1$ highly improved staggered quarks and clover $b$-quark in the Fermilab interpretation

We present an update on the analysis of semileptonic $B\rightarrow D^{(*)}$ decays at non-zero recoil. Our computation employs $2 + 1 + 1$ FNAL-MILC ensembles with highly improved staggered quark (HISQ) action for sea and light valence quarks, while the bottom quark is treated using the clover action in the Fermilab interpretation. Simulations are performed across several lattice spacings, ranging approximately from $\sim 0.15$ fm to $\sim 0.06$ fm, and for various quark masses. We will present an overview of the analysis and show some preliminary results for the form factors.

DeTar, Carleton [Utah U.] (ORCID:0000000202166771)↗
DOE OSTI2022

Quantitative interpretation of time-lapse seismic data at Farnsworth field unit: Rock physics modeling, and calibration of simulated time-lapse velocity responses

Here, this study investigates the contribution of fluid saturation variation to the time-lapse velocity response by performing fluid substitution modeling. The methodology is exemplified by the time-lapse seismic monitoring of carbon dioxide at Farnsworth field unit (FWU). In order to evaluate the fluid distribution in a matured oil reservoir, the Southwest Regional Partnership (SWP) acquired multiple vertical seismic profile (VSP) surveys at different times during the CO 2 –water alternatinggas (WAG) injection period. In this work, we present a thorough methodology for computing the elastic response of the saturated rock for different fluid saturations using a site-specific petro-elastic model (PEM). The output from the PEM was combined with results from a fluid compositional model to compute the seismic velocities at times corresponding to each VSP survey. To produce a calibrated simulated response, the measured time-lapse seismic velocities were integrated into the numerical simulation model. The mismatches between the predicted and measured time-lapse velocities were minimized through an iterative calibration process using a trained artificial neural network proxy (ANN) coupled with a particle swarm optimizer (PSO). Our study indicates that the hybrid optimization workflow can effectively perform the history matching. With an accurate prediction of the hydrodynamic properties, the migration of CO 2 within the subsurface was modeled by predicting the spatial velocity distribution for a radius of 305 m around the injection well. The technology demonstrated and the expertise gained from this study can guide similar CO 2 -WAG projects.

58 GEOSCIENCES↗