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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 1,423 records · Page 79

A search for dark matter produced in association with a dark Higgs boson decaying into a Higgs boson pair in 3b or 4b final states using pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

A search is performed for dark matter particles produced in association with a resonant pair of Higgs bosons using 140 fb −1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. This signature is expected in some extensions of the Standard Model predicting the production of dark matter particles, and is interpreted in terms of a dark Higgs model containing a Z′ mediator in which the dark Higgs boson s decays into a pair of Higgs bosons. The dark Higgs boson is reconstructed through final states with at least three b-tagged jets, produced by the pair of Higgs boson decays, in events with significant missing transverse momentum consistent with the presence of dark matter. The observed data are found to be in good agreement with Standard Model predictions, constraining scenarios with dark Higgs boson masses within the range of 250 to 400 GeV and Z′ mediators up to 2.3 TeV.

Dark Energy and Dark Matter↗

Testing and Expertise for Marine Energy (TEAMER) Program Support - Numerical Modeling Assistance for iProTech's "PIP" WEC Device: Cooperative Research and Development Final Report, CRADA Number CRD-20-17303

Develop a time-domain, 3 degree of freedom numerical model of IProTech's PIP device, including power take-off (PTO), that can be used to develop control algorithms and establish a baseline technology performance level (TPL). This is important to IProTech because having a good numerical model allows IProTech to optimize design and control algorithms on an ongoing basis. A baseline TPL enables the PIP technology to be benchmarked against other wave energy converter (WEC) concepts, providing (i) justification (or not) for investment in wave tank model testing, (ii) identifying optimum design parameters and control algorithms for the test model, (iii) specifying test conditions and (iv) interpreting wave tank test results. An accredited WEC-Sim model of the PIP device is an essential tool for further development of the technology. 1) The development of numerical models of the PIP concept will enable iProTech to evaluate the potential performance of this concept, and to investigate how sensitive the device is to different variables within the system (e.g. hydraulic components, geometry dimensions, etc.) 2) The numerical models were developed with WEC-Sim and PTO-Sim -- the de-facto industry standard WEC numerical modeling tools. A detailed model of the system's hydraulic circuit was developed with PTO-Sim. However, WEC-Sim is based on linear hydrodynamics and has several limitations; validation against high fidelity models/physical scale models would help to build confidence in the results.

16 TIDAL AND WAVE POWER↗

Relaxation processes in a low-order three-dimensional magnetohydrodynamics model

The time asymptotic behavior of a Galerkin model of 3D magnetohydrodynamics (MHD) has been interpreted using the selective decay and dynamic alignment relaxation theories. A large number of simulations has been performed that scan a parameter space defined by the rugged ideal invariants, including energy, cross helicity, and magnetic helicity. It is concluded that time asymptotic state can be interpreted as a relaxation to minimum energy. A simple decay model, based on absolute equilibrium theory, is found to predict a mapping of initial onto time asymptotic states, and to accurately describe the long time behavior of the runs when magnetic helicity is present. Attention is also given to two processes, operating on time scales shorter than selective decay and dynamic alignment, in which the ratio of kinetic to magnetic energy relaxes to values 0(1). The faster of the two processes takes states initially dominant in magnetic energy to a state of near-equipartition between kinetic and magnetic energy through power law growth of kinetic energy. The other process takes states initially dominant in kinetic energy to the near-equipartitioned state through exponential growth of magnetic energy.

Stribling, Troy↗

Models for various aspects of dwarf novae and nova-like stars

The first attempts to explain the nature of dwarf novae were based on the assumption of single-star phenomena, in which emission lines were assumed to be caused by circumstellar gas shells. The outburst behavior was tentatively ascribed to the kind of (also not understood) mechanism leading to nova outbursts. The realization that some, and possibly all, dwarf novae and nova-like stars (and novae) are binaries eventually led to models which bore more and more similarities to the modern interpretation on the basis of the Roche model. Not all cataclysmic variables are known binaries. In fact, with respect to the entire number of known objects, the proven binaries are still the minority, but all the brightest variables are in fact known to binaries. Not a single system is known which exhibits the usual characteristics of a cataclysmic variable and at the same time can be declared with certainty to be a single star. Two systems are known, the dwarf nova EY Cyg and the recurrent nova V1017 Sgr, in which, in spite of intensive search, no radial velocity variations have been found; but they still exhibit composite spectra consisting of a bright continuum, an emission spectrum, and a cool absorption spectrum. If the Roche model is correct, it is to be expected that a small percentage of objects is viewed pole-on, so orbital motions do not make themselves felt as Doppler shifts of spectral lines. So even these two systems support the hypothesis that all cataclysmic variables (with the possible exception of symbiotic stars) are binaries. In cataclysmic variables, it seems that the brightness changes observed in dwarf novae and nova-like stars in the optical and the UV are due directly to changes in the accretion disks. The study and understanding of accretion disks in these systems can bear potentially valuable consequences for many other fields in astronomy. The observed spectra of dwarf novae and nova-like stars comprise a fairly large range: pure emission spectra, pure absorption spectra, a mixture of both, asymmetric line profiles, very different slopes of the continuous flux distribution -- and one single system may exhibit all of these features at different times. Agreement and disagreement between computed and observed spectra should show whether or not the Roche model is applicable and where it probably will have to be modified and improved. Except for their outburst behavior and its immediate consequences, novae, dwarf novae, and nova-like stars cannot be physically distinguished from each other.

Ladous, Constanze↗

Global Ocean Evaporation: How Well Can We Estimate Interannual to Decadal Variability?

Evaporation from the world's oceans constitutes the largest component of the global water balance. It is important not only as the ultimate source of moisture that is tied to the radiative processes determining Earth's energy balance but also to freshwater availability over land, governing habitability of the planet. Here we focus on variability of ocean evaporation on scales from interannual to decadal by appealing to three sources of data: the new MERRA-2 (Modern-Era Retrospective analysis for Research and Applications -2); climate models run with historical sea-surface temperatures, ice and atmospheric constituents (so-called AMIP experiments); and state-of-the-art satellite retrievals from the Seaflux and HOAPS (Hamburg Ocean-Atmosphere Parameters and Fluxes from Satellite) projects. Each of these sources has distinct advantages as well as drawbacks. MERRA-2, like other reanalyses, synthesizes evaporation estimates consistent with observationally constrained physical and dynamical models-but data stream discontinuities are a major problem for interpreting multi-decadal records. The climate models used in data assimilation can also be run with lesser constraints such as with SSTs and sea-ice (i.e. AMIPs) or with additional, minimal observations of surface pressure and marine observations that have longer and less fragmentary observational records. We use the new ERA-20C reanalysis produced by ECMWF embodying the latter methodology. Still, the model physics biases in climate models and the lack of a predicted surface energy balance are of concern. Satellite retrievals and comparisons to ship-based measurements offer the most observationally-based estimates, but sensor inter-calibration, algorithm retrieval assumptions, and short records are dominant issues. Our strategy depends on maximizing the advantages of these combined records. The primary diagnostic tool used here is an analysis of bulk aerodynamic computations produced by these sources and uses a first-order Taylor series analysis of wind speed, SST, near-surface stability and relative humidity variations around climatology to gauge the importance of these components. We find that the MERRA-2 evaporation record is strongly influenced by the availability of wind speed and humidity from passive microwave imagers beginning in the late 1980s as well as by the SST record. The trend over the period 1980 to present is nearly 10%. AMIP or the ERA-20C trends are much smaller. We find that ENSO-related signals involving both wind speed and thermodynamic variability remain the primary signal in the latter and are confirmed by satellite retrievals. We present uncertainty estimates based on the various data sources and discuss the implications for GEWEX water and energy budget science challenges.

Robertson, Franklin R.↗

Search for dark matter produced in association with a single top quark and an energetic W boson in $\sqrt{s}=$ 13 TeV $pp$ collisions with the ATLAS detector

This paper presents a search for dark matter, $χ$, using events with a single top quark and an energetic W boson. The analysis is based on proton–proton collision data collected with the ATLAS experiment at $\sqrt{s}=$ 13 TeV during LHC Run 2 (2015–2018), corresponding to an integrated luminosity of 139 fb -1 . The search considers final states with zero or one charged lepton (electron or muon), at least one $b$-jet and large missing transverse momentum. In addition, a result from a previous search considering two-charged-lepton final states is included in the interpretation of the results. The data are found to be in good agreement with the Standard Model predictions and the results are interpreted in terms of 95% confidence-level exclusion limits in the context of a class of dark matter models involving an extended two Higgs-doublet sector together with a pseudoscalar mediator particle. The search is particularly sensitive to on-shell pro duction of the charged Higgs boson state, $H$ ± , arising from the two-Higgs-doublet mixing, and its semi-invisible decays via the mediator particle, $a$: $H$ ± → $W$ ± $a$(→ $χ$ $χ$). Signal models with $H$ ± masses up to 1.5 TeV and a masses up to 350 GeV are excluded assuming a tan $β$ value of 1. For masses of a of 150 (250) GeV, tan $β$ values up to 2 are excluded for $H$ ± masses between 200 (400) GeV and 1.5 TeV. Signals with tan $β$ values between 20 and 30 are excluded for $H$ ± masses between 500 and 800 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A model of the physical properties of comet Encke

The available observational data on periodic comet Encke were collected and interpreted in order to construct a model of the comet. The model is intended for use in the design of scientific experiments and spacecraft systems to be used on future missions to Encke. Numerical values and ranges of uncertainty are given for all of the important structural, compositional, and photometric parameters with references to the original research from which these were calculated or estimated.

Taylor, F. W.↗

Modeling the effect of habitat availability and quality on endangered winter-run Chinook salmon ( Oncorhynchus tshawytscha ) production in the Sacramento Valley

Reconciliation between water uses and sustaining aquatic species populations requires an effort to identify and quantify essential habitat characteristics for ecosystem health and valuation methods to predict ecosystem response to restoration actions. This process is particularly challenging for anadromous fish species such as California's Sacramento River winter-run Chinook salmon, due to their limited geographic range and diverse life history habitat requirements. Tools, such as life-cycle models, are needed to manage population dynamics and quantify the composite effects of processes across space and time. Nevertheless, complex institutions can hinder result interpretation and communication, and limit model use in decision-making. This paper focuses on the federally endangered and endemic Sacramento River winter-run Chinook (Oncorhynchus tshawytscha) by developing a Winter-Run Habitat-based Population Model (WRHAP). Additionally, WRHAP is a conceptual, freshwater rearing stage model that includes alternative rearing habitats reported in the literature (e.g., floodplains, off-channel and tributaries), defines rules of habitat use based on instream conditions, and incorporates a juvenile growth module that combines bioenergetics modeling with empirical growth rates. Model outputs reasonably follow observed out-migration patterns and provide a realistic smolt size distribution arriving at the San Francisco Bay. This effort demonstrates the importance of currently “non-critical” habitats (as defined by the Endangered Species Act) for juvenile development, with floodplain habitat contributing to a quarter of out-migrating biomass (despite < 18% availability and <10% of total rearing days), and off-channel growth being one of the most sensitive parameters (explaining ~13% of average juvenile weight variance). The model shows the utility of a simple population model to explore relationships between habitat quality/quantity and juvenile development, and to assist water/environmental management and decision-making processes focused on species recovery.

54 ENVIRONMENTAL SCIENCES↗

Chemical and Hydrodynamical Models of Cometary Comae

Multi-fluid modelling of the outflowing gases which sublimate from cometary nuclei as they approach the Sun is necessary for understanding the important physical and chemical processes occurring in this complex plasma. Coma chemistry models can be employed to interpret observational data and to ultimately determine chemical composition and structure of the nuclear ices and dust. We describe a combined chemical and hydrodynamical model [1] in which differential equations for the chemical abundances and the energy balance are solved as a function of distance from the cometary nucleus. The presence of negative ions (anions) in cometary comae is known from Giotto mass spectrometry of 1P/Halley. The anions O(-), OH(-), C(-), CH(-) and CN(-) have been detected, as well as unidentified anions with masses 22-65 and 85-110 amu [2]. Organic molecular anions such as C4H(-) and C6H(-) are known to have a significant impact on the charge balance of interstellar clouds and circumstellar envelopes and have been shown to act as catalysts for the gas-phase synthesis of larger hydrocarbon molecules in the ISM, but their importance in cometary comae has not yet been fully explored. We present details of new models for the chemistry of cometary comae that include atomic and molecular anions and calculate the impact of these anions on the coma physics and chemistry af the coma.

Charnley, Steven↗

Analysis of radar images by means of digital terrain models

It is pointed out that the importance of digital terrain models in the processing, analysis, and interpretation of remote sensing data is increasing. In investigations related to the study of radar images, digital terrain models can have a particular significance, because radar reflection is a function of the terrain characteristics. A procedure for the analysis and interpretation of radar images is discussed. The procedure is based on a utilization of computer simulation which makes it possible to produce simulated radar images on the basis of a digital terrain model. The simulated radar images are used for the geometric and radiometric rectification of real radar images. A description of the employed procedures is provided, and the obtained results are discussed, taking into account a test area in Northern California.

Domik, G.↗

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗

Model atmospheres for K and M giants

To aid in the interpretations of observations of K and M giant stars, model atmospheres have been calculated, covering the range in effective temperature between 3000 and 4000 K and in surface gravity-log g between 0.0 and 2.0. These models are computed under the usual assumptions of hydrostatic equilibrium, constancy of total (radiative plus convective) flux, and LTE in plane-parallel, horizontally homogeneous geometry. A significant development in these models is the incorporation of an opacity-sampled treatment of absorption by water vapor, which becomes dominant at lower temperatures. The thermal structure and scaling properties of the models are discussed, as are the effects of certain composition changes expected in the course of stellar evolution.

Brown, Jeffery A.↗

Interpretable ensemble learning unveils main aerosol optical properties in predicting cloud condensation nuclei number concentration

Variations in cloud condensation nuclei number concentration (N CCN ) significantly influence cloud microphysics, yet direct N CCN measurements remain challenging. Here, we present an N CCN ensemble learning (NEL) model utilizing ensemble learning and interpretability analysis on aerosol optical parameters. Validated at two land sites, two ocean sites and one polar site within the Atmospheric Radiation Measurement program, the mean absolute percentage error range of the NEL model across different environments is from 12% to 36%, demonstrating high accuracy. Key findings reveal that aerosol optical parameters can serve as predictors for N CCN . Aerosol scattering and backscattering coefficients, absorption coefficient, backscatter fraction (BSF), and Ångström exponent (AE) are positively correlated with N CCN , while single scattering albedo shows negative correlations. N CCN prediction at land sites is highly sensitive to BSF, largely driven by the backscattering coefficient, as fine particles dominate in these sites. At ocean sites, N CCN prediction is more sensitive to AE, primarily influenced by the scattering coefficient, due to the higher proportion of larger particles. At the polar site, N CCN prediction shows sensitivity to both BSF and AE, mainly driven by the scattering coefficient, as polar sites are cleaner and contain larger particles. These differences reflect the variation in particle size and number concentration across different environments.

Atmospheric science↗

Comparative analysis of magnetic resonance in the polaron pair recombination and the triplet exciton-polaron quenching models

We present a comparative theoretical study of magnetic resonance within the polaron pair recombination (PPR) and the triplet exciton-polaron quenching (TPQ) models. Both models have been invoked to interpret the photoluminescence detected magnetic resonance (PLDMR) results in π-conjugated materials and devices. We show that resonance line shapes calculated within the two models differ dramatically in several regards. First, in the PPR model, the line shape exhibits unusual behavior upon increasing the microwave power: it evolves from fully positive at weak power to fully negative at strong power. In contrast, in the TPQ model, the PLDMR is completely positive, showing a monotonic saturation. Second, the two models predict different dependencies of the resonance signal on the photoexcitation power, P L . At low P L , the resonance amplitude Δ I/I is ∝ P L within the PPR model, while it is ∝ P 2 L crossing over to P 3 L within the TPQ model. On the physical level, the differences stem from different underlying spin dynamics. Most prominently, a negative resonance within the PPR model has its origin in the microwave-induced spin-Dicke effect, leading to the resonant quenching of photoluminescence. The spin-Dicke effect results from the spin-selective recombination, leading to a highly correlated precession of the on-resonance pair partners under the strong microwave power. This effect is not relevant for TPQ mechanism, where the strong zero-field splitting renders the majority of triplets off resonance. On the technical level, the analytical evaluation of the line shapes for the two models is enabled by the fact that these shapes can be expressed via the eigenvalues of a complex Hamiltonian. This bypasses the necessity of solving the much larger complex linear system of the stochastic Liouville equations. Lastly, our findings pave the way towards a reliable discrimination between the two mechanisms via cw PLDMR.

36 MATERIALS SCIENCE↗

Structure of high-lying excited states in 47 Ca with ℓ ≥ 3 populated in fast-beam 𝛾-ray-tagged one-neutron pickup reactions

Located just one neutron removed from doubly magic, stable 48 Ca, the adjacent isotope 47 Ca has been studied extensively with neutron-removing transfer reactions and interpreted within a shell-model picture. Neutron-adding transfer reactions onto the stable 46 Ca, however, have not been performed in nearly 60 years and never with the aid of high-resolution 𝛾-ray spectroscopy. Here, we report on the 12 C⁡( 46 , Ca 47 Ca+𝛾)⁢𝑋 one-neutron pickup reaction from 12 C onto 46 Ca at more than 50 MeV/nucleon, a regime of orbital angular momentum mismatch that selectively populates 47 Ca final states based on ℓ ≥ 3 neutron configurations. Newly observed excited states and 𝛾-ray transitions are discussed in comparison to 𝑓⁡𝑝 shell-model calculations in a variety of configuration spaces. Furthermore, it is shown that the nature of the observed spectrum of final states can be well interpreted, albeit with a significant fragmentation of the 𝜈⁢0⁢𝑓 5/2 strength observed in the measurement that is not borne out in the structure calculations.

39 ≤ A ≤ 58↗

elm-diagnostics

elm-diagnostics is a Python package for computing diagnostic analyses and visualizations for the E3SM Land Model (ELM) component and is meant to support new feature development in ELM. The tool reads model history files and performs quantitative analyses including budget-closure checking, variable transformations, temporal aggregations, and statistical summaries to support model evaluation, validation, and scientific interpretation. The framework is designed for extensibility, with modular architecture enabling straightforward addition of new diagnostic methods, derived variables, analysis types, visualization approaches, and model-specific adaptations

Hoffman, Matt [Los Alamos National Laboratory]↗

Transition Documentation on a Three-Element High-Lift Configuration at High Reynolds Numbers: Analysis

A 2-D high-lift system experiment was conducted in August of 1996 in the Low Turbulence Pressure Tunnel at NASA Langley Research Center, Hampton, VA. The purpose of the experiment was to obtain transition measurements on a three element high-lift system for CFD code validation studies. A transition database has been created using the data from this experiment. The present report contains the analysis of the surface hot film data in terms of the transition locations on the three elements. It also includes relevant information regarding the pressure loads and distributions and the wakes behind the model to aid in the interpretation of the transition data. For some of the configurations the current pressure data has been compared with previous wind tunnel entries of the same model. The methodology used to determine the regions of transitional flow is outlined and each configuration tested has been analyzed. A discussion of interference effects, repeatability, and three-dimensional effects on the data is included.

Bertelrud, Arild↗

Quantifying Climate and Catchment Control on Hydrological Drought in the Continental United States

The evolution of hydrological drought events is a result of complex (nonlinear) interactions between climate and catchment processes. To investigate such nonlinear relationship, we integrated a machine learning modeling framework based on the random forest (RF) algorithms with an interpretation framework to quantify the role of climate and catchment controls on hydrological drought. More particularly, our framework interprets a built RF machine-learning model to identify dominant variables and visualize their functional dependence and interaction effects on hydrological drought characteristics utilizing concepts of minimal depth, interactive depth, and partial dependence. We test our proposed modeling framework based on a set of 652 continental United States catchments with minimal human interference for a period of 1979–2010. Application of this framework indicated presence of three distinct drought regimes, which includes, Regime 1: droughts with longer duration, less frequent and lesser intensity; Regime 2: droughts with moderate duration, moderate frequency, and moderate intensity; and Regime 3: droughts with shorter duration, more frequent, and more intense. RF algorithm was able to accurately model the drought characteristics (intensity, duration, and number of events) for all the three drought regimes as a function of selected variables. It was observed that the type of dominant variables as well as their nonlinear functional relationship with hydrological droughts characteristics can vary between three selected regimes. Finally, our interpretation framework indicated that catchment characteristics have a significant role in controlling the hydrologic drought for catchments (regime 1), whereas both climate and catchment characteristics control hydrological drought in regimes 2 and 3.

54 ENVIRONMENTAL SCIENCES↗