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DOE OSTI2022

Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters

The temporal analysis of products (TAP) reactor, a transient kinetic tool, provides users with information as the catalyst state evolves. However, the state of the art for TAP uncertainty quantification only considers the experimental noise present in the outlet flow signal. Additional sources of uncertainty, including, but not limited to, initial surface coverages, the catalyst zone location, the inert void fraction, and the gas pulse intensity and pulse delay, are not included. For this reason, a framework for quantifying all uncertainty sources present in TAP experiments is presented and applied to a carbon monoxide oxidation case study. Herein, two methods for quantifying these sources of uncertainty are introduced. The first utilizes initial state sensitivities to approximate the parameter variances, as well as to provide insights into the structural certainty of the model. The second generates parameter confidence distributions through an ensemble-based sampling algorithm. This initial state covariance matrix can ultimately be merged with the experimental noise covariance matrix, providing a unified description of the parameter uncertainties for a single TAP experiment.

36 MATERIALS SCIENCE↗

NASA NTRS2016

GOCI Yonsei Aerosol Retrieval (YAER) Algorithm and Validation During the DRAGON-NE Asia 2012 Campaign

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGONNE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 x AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

Choi, Myungje↗

NASA NTRS2019

Thermal Property Estimation of Fibrous Insulation: Heat Transfer Modeling and the Continuous Genetic Algorithm

Thermal properties of high-temperature fibrous insulation materials were estimated from transient thermal tests using an inverse heat transfer technique. Transient temperature data from an experimental set up was collected and a simple, one-dimensional numerical model was constructed to replicate the temperatures within the test assembly. The Continuous Genetic Algorithm optimization technique in conjunction with a numerical thermal model and transient test data was used to estimate coefficients of a functional representation of the thermal property. The thermal properties, i.e., thermal conductivity and specific heat, of an alumina insulation felt were estimated over the temperature range of 300 K to 1700 K at various constant static pressures in nitrogen gas and compared with published data. The resulting thermal property estimates were within 10% of published values over the entire temperature range at various pressures. The methodology, application, and results are presented.

Frye, Elora↗

DOE OSTI2021

Search for low-energy neutrinos from astrophysical sources with Borexino

We report on searches for neutrinos and antineutrinos from astrophysical sources performed with the Borexino detector at the Laboratori Nazionali del Gran Sasso in Italy. Electron antineutrinos ( $\bar{ν}_e$ ) are detected in an organic liquid scintillator through the inverse β -decay reaction. In the present work we set model-independent upper limits in the energy range 1.8-16.8 MeV on neutrino fluxes from unknown sources that improve our previous results, on average, by a factor 2.5. Using the same data set, we first obtain experimental constraints on the diffuse supernova $\bar{ν}_e$ fluxes in the previously unexplored region below 8 MeV. A search for $\bar{ν}_e$ in the solar neutrino flux is also presented: the presence of $\bar{ν}_e$ would be a manifestation of a non-zero anomalous magnetic moment of the neutrino, making possible its conversion to antineutrinos in the strong magnetic field of the Sun. We obtain a limit for a solar $\bar{ν}_e$ flux of 384 cm -2 s -1 (90% C.L.), assuming an undistorted solar 8 B neutrinos energy spectrum, that corresponds to a transition probability pνe→$\bar{ν}_e$< 7.2 ×10-5 (90% C.L.) for E $\bar{ν}_e$ > 1.8 MeV.At lower energies, by investigating the spectral shape of elastic scattering events, we obtain a new limit on solar 7 Be- ν e conversion into $\bar{ν}_e$ of pνe→$\bar{ν}_e$< 0.14 (90% C.L.) at 0.862 MeV. Last, we investigate solar flares as possible neutrino sources and obtain the strongest up-to-date limits on the fluence of neutrinos of all flavor neutrino below 3–7 MeV. Assuming the neutrino flux to be proportional to the flare’s intensity, we exclude an intense solar flare as the cause of the observed excess of events in run 117 of the Cl-Ar Homestake experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1982

A numerical simulation of an atmospheric vortex street

A simplified mesoscale mixed-layer model is utilized to study the flow past an ocean island during a case of cold air outbreak over the Kuroshio Current. Using data taken during AMTEX '75, the governing equations are integrated in time to simulate the development of a Karman vortex street downstream of the island of Cheju-do. The surface layer, inversion layer, and overlying stable layer are all parametrized in the model. Very weak sinusoidal waviness but no vortex street was found in the case of the island. For a mixed layer barely deep enough to allow no part of the mountain on the island to protrude, there was more pronounced waviness but still no vortices. This result may not hold for boundary layers with poor vertical mixing. A numerical simulation of the vortex street yielded good results in comparison. The speed ratio, spacing ratio, and Strouhal number agreed rather closely with observations.

Ruscher, P. H.↗

NASA NTRS1986

Modelling short channel mosfets for use in VLSI

In an investigation of metal oxide semiconductor field effect transistor (MOFSET) devices, a one-dimensional mathematical model of device dynamics was prepared, from which an accurate and computationally efficient drain current expression could be derived for subsequent parameter extraction. While a critical review revealed weaknesses in existing 1-D models (Pao-Sah, Pierret-Shields, Brews, and Van de Wiele), this new model in contrast was found to allow all the charge distributions to be continuous, to retain the inversion layer structure, and to include the contribution of current from the pinched-off part of the device. The model allows the source and drain to operate in different regimes. Numerical algorithms used for the evaluation of surface potentials in the various models are presented.

Klafter, Alex↗

NASA NTRS2015

Stratospheric Temperatures and Water Loss From Moist Greenhouse Atmospheres of Earth-Like Planets

A radiative-convective climate model is used to calculate stratospheric temperatures and water vapor concentrations for ozone-free atmospheres warmer than that of modern Earth. Cold, dry stratospheres are predicted at low surface temperatures, in agreement with recent 3D calculations. However, at surface temperatures above 350 K, the stratosphere warms and water vapor becomes a major upper atmospheric constituent, allowing water to be lost by photodissociation and hydrogen escape. Hence, a moist greenhouse explanation for loss of water from Venus, or some exoplanet receiving a comparable amount of stellar radiation, remains a viable hypothesis. Temperatures in the upper parts of such atmospheres are well below those estimated for a gray atmosphere, and this factor should be taken into account when performing inverse climate calculations to determine habitable zone boundaries using 1D models.

Astrobiology↗

DOE OSTI2023

Microsecond Isomer at the N = 20 Island of Shape Inversion Observed at FRIB

Excited-state spectroscopy from the first experiment at the Facility for Rare Isotope Beams (FRIB) is reported. A 24(2)-μs isomer was observed with the FRIB Decay Station initiator (FDSi) through a cascade of 224- and 401-keV γ rays in coincidence with 32 Na nuclei. This is the only known microsecond isomer (1 μs ≤T 1/2 <1 ms) in the region. This nucleus is at the heart of the N=20 island of shape inversion and is at the crossroads of the spherical shell-model, deformed shell-model, and ab initio theories. It can be represented as the coupling of a proton hole and neutron particle to 32 Mg, 32 Mg+π -1 +ν +1 . This odd-odd coupling and isomer formation provides a sensitive measure of the underlying shape degrees of freedom of 32 Mg, where the onset of spherical-to-deformed shape inversion begins with a low-lying deformed 2 + state at 885 keV and a low-lying shape-coexisting 0$^+_2$ state at 1058 keV. Here, we suggest two possible explanations for the 625-keV isomer in 32 Na: a 6 - spherical shape isomer that decays by E2 or a 0 + deformed spin isomer that decays by M2. The present results and calculations are most consistent with the latter, indicating that the low-lying states are dominated by deformation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion

Combinatorial fusion analysis (CFA) is an approach for combining multiple scoring systems using the rank-score characteristic function and cognitive diversity measure. One example is to combine diverse machine learning models to achieve better prediction quality. In this work, we apply CFA to the synthesis of metal halide perovskites containing organic ammonium cations via inverse temperature crystallization. Using a data set generated by high-throughput experimentation, four individual models (support vector machines, random forests, weighted logistic classifier, and gradient boosted trees) were developed. We characterize each of these scoring systems and explore 66 possible combinations of the models. When measured by the precision on predicting crystal formation, the majority of the combination models improves the individual model results. The best combination models outperform the best individual models by 3.9 percentage points in precision. In addition to improving prediction quality, we demonstrate how the fusion models can be used to identify mislabeled input data and address issues of data quality. In particular, we identify example cases where all single models and all fusion models do not give the correct prediction. Experimental replication of these syntheses reveals that these compositions are sensitive to modest temperature variations across the different locations of the heating element that can hinder or enhance the crystallization process. In summary, we demonstrate that model fusion using CFA can not only identify a previously unconsidered influence on reaction outcome but also be used as a form of quality control for high-throughput experimentation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Code for Calculating Regional Seismic Travel Time

The RSTT software computes predictions of the travel time of seismic energy traveling from a source to a receiver through 2.5D models of the seismic velocity distribution within the Earth. The two primary applications for the RSTT library are tomographic inversion studies and seismic event location calculations. In tomographic inversions studies, a seismologist begins with number of source-receiver travel time observations and an initial starting model of the velocity distribution within the Earth. A forward travel time calculator, such as the RSTT library, is used to compute predictions of each observed travel time and all of the residuals (observed minus predicted travel time) are calculated. The Earth model is then modified in some systematic way with the goal of minimizing the residuals. The Earth model obtained in this way is assumed to be a better model than the starting model if it has lower residuals. The other major application for the RSTT library is seismic event location. Given an Earth model, an initial estimate of the location of a seismic event, and some number of observations of seismic travel time thought to have originated from that event, location codes systematically modify the estimate of the location of the event with the goal of minimizing the difference between the observed and predicted travel times. The second application, seismic event location, is routinely implemented by the military as part of its effort to monitor the Earth for nuclear tests conducted by foreign countries.

BALLARD, SANFORD↗

DOE OSTI2020

Regional Seismic Travel Time v.3.2.0

BALLARD, SANFORD↗

NASA NTRS1979

Studies of oceanic tectonics based on GEOS-3 satellite altimetry

Using statistical analysis, geoidal admittance (the relationship between the ocean geoid and seafloor topography) obtained from GEOS-3 altimetry was compared to various model admittances. Analysis of several altimetry tracks in the Pacific Ocean demonstrated a low coherence between altimetry and seafloor topography except where the track crosses active or recent tectonic features. However, global statistical studies using the much larger data base of all available gravimetry showed a positive correlation of oceanic gravity with topography. The oceanic lithosphere was modeled by simultaneously inverting surface wave dispersion, topography, and gravity data. Efforts to incorporate geoid data into the inversion showed that the base of the subchannel can be better resolved with geoid rather than gravity data. Thermomechanical models of seafloor spreading taking into account differing plate velocities, heat source distributions, and rock rheologies were discussed.

Poehls, K. A.↗

DOE OSTI2021

Long-lived biνo at the LHC

We examine the detection prospects for a long-lived bi ν o, a pseudo-Dirac bino which is responsible for neutrino masses, at the LHC and at dedicated long-lived particle detectors. The bi ν o arises in U(1) R -symmetric supersymmetric models where the neutrino masses are generated through higher dimensional operators in an inverse seesaw mechanism. At the LHC the bi ν o is produced through squark decays and it subsequently decays to quarks, charged leptons and missing energy via its mixing with the Standard Model neutrinos. We consider long-lived bi ν os which escape the ATLAS or CMS detectors as missing energy and decay to charged leptons inside the proposed long-lived particle detectors FASER, CODEX-b, and MATHUSLA. We find the currently allowed region in the squark-bi ν o mass parameter space by recasting most recent LHC searches for jets+. We also determine the reach of MATHUSLA, CODEX-b and FASER. We find that a large region of parameter space involving squark masses, bi ν o mass and the messenger scale can be probed with MATHUSLA, ranging from bi ν o masses of 10 GeV-2 TeV and messenger scales 10 2 - 11 TeV for a range of squark masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Quantifying uncertainty in analysis of shockless dynamic compression experiments on platinum. II. Bayesian model calibration

Dynamic shockless compression experiments provide the ability to explore material behavior at extreme pressures but relatively low temperatures. Typically, the data from these types of experiments are interpreted through an analytic method called Lagrangian analysis. Here, in this work, alternative analysis methods are explored using modern statistical methods. Specifically, Bayesian model calibration is applied to a new set of platinum data shocklessly compressed to 570 GPa. Several platinum equation-of-state models are evaluated, including traditional parametric forms as well as a novel non-parametric model concept. The results are compared to those in Paper I obtained by inverse Lagrangian analysis. The comparisons suggest that Bayesian calibration is not only a viable framework for precise quantification of the compression path, but also reveals insights pertaining to trade-offs surrounding model form selection, sensitivities of the relevant experimental uncertainties, and assumptions and limitations within Lagrangian analysis. The non-parametric model method, in particular, is found to give precise unbiased results and is expected to be useful over a wide range of applications. The calibration results in estimates of the platinum principal isentrope over the full range of experimental pressures to a standard error of 1.6%, which extends the results from Paper I while maintaining the high precision required for the platinum pressure standard.

Brown, Justin Lee↗

DOE OSTI2021

Very-high-energy Emission from Pulsars

Abstract Air-Cherenkov telescopes have detected pulsations at energies above 50 GeV from a growing number of Fermi pulsars. These include the Crab, Vela, PSR B1706−44, and Geminga, with the first two having pulsed detections above 1 TeV. In some cases, there appears to be very-high-energy (VHE) emission that is an extension of the Fermi spectra to high energies, while in other cases, additional higher-energy spectral components that require a separate emission mechanism may be present. We present results of broadband spectral modeling using global magnetospheric fields and multiple emission mechanisms that include synchro-curvature (SC) and inverse Compton scattered (ICS) radiation from accelerated particles (primaries) and synchrotron self-Compton (SSC) emission from lower-energy pairs. Our models predict three distinct VHE components: SC from primaries whose high-energy tail can extend to 100 GeV, SSC from pairs that can extend to several TeV, and ICS from primary particles accelerated in the current sheet that scatter pair synchrotron radiation, which appears beyond 10 TeV. Our models suggest that H.E.S.S.-II and MAGIC have detected the high-energy tail of the primary SC component that produces the Fermi spectrum in Vela, Geminga, and PSR B1706−44. We argue that the ICS component peaking above 10 TeV from Vela has been seen by H.E.S.S. Detection of this emission component from the Crab and other pulsars is possible with the High Altitude Water Cherenkov Observatory and Cherenkov Telescope Array, and will directly measure the maximum particle energy in pulsars.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2021

Very-high-energy Emission from Pulsars

Air-Cherenkov telescopes have detected pulsations at energies above 50 GeV from a growing number of Fermi pulsars. These include the Crab, Vela, PSR B1706−44, and Geminga, with the first two having pulsed detections above 1 TeV. In some cases, there appears to be very-high-energy (VHE) emission that is an extension of the Fermi spectra to high energies, while in other cases, additional higher-energy spectral components that require a separate emission mechanism may be present. We present results of broadband spectral modeling using global magnetospheric fields and multiple emission mechanisms that include synchro-curvature (SC) and inverse Compton scattered (ICS) radiation from accelerated particles (primaries) and synchrotron self-Compton (SSC) emission from lower-energy pairs. Our models predict three distinct VHE components: SC from primaries whose high-energy tail can extend to 100 GeV, SSC from pairs that can extend to several TeV, and ICS from primary particles accelerated in the current sheet that scatter pair synchrotron radiation, which appears beyond 10 TeV. Our models suggest that H.E.S.S.-II and MAGIC have detected the high-energy tail of the primary SC component that produces the Fermi spectrum in Vela, Geminga, and PSR B1706−44. We argue that the ICS component peaking above 10 TeV from Vela has been seen by H.E.S.S. Detection of this emission component from the Crab and other pulsars is possible with the High Altitude Water Cherenkov Observatory and Cherenkov Telescope Array, and will directly measure the maximum particle energy in pulsars.

Alice K. Harding↗

DOE OSTI2026

Inverse design of hypoeutectoid pearlite steel microstructures using a deep learning and genetic algorithm optimization framework

Goal-oriented microstructure design in metallic materials is a challenging task due to complex structure-property relationships. Traditional experimental and computational approaches are time-intensive and economically inefficient, limiting their applicability for large-scale design space exploration. Here, in this work, we propose an end-to-end framework that integrates deep learning models with genetic optimization to design microstructures with targeted mechanical properties. Deep learning models enable accurate forward design, while their integration with genetic optimization enables efficient inverse design within a few hours, compared to days or weeks using conventional finite element simulations. The framework combines experimental characterization and finite element modeling to analyze the influence of microstructural features on the mechanical behavior of hypoeutectoid steels. Data from both experiments and simulations are used to train the deep learning models. To demonstrate its effectiveness, we apply the framework to 0.63% carbon steel with proeutectoid ferrite and pearlite phases, commonly used in industrial applications. In this study, 2D microstructures were used for modeling, selected primarily for computational efficiency and to establish proof of concept. The framework successfully optimizes microstructures for targeted yield strength, ultimate strength, and stress concentration factors while significantly reducing computational time. Beyond hypoeutectoid steels, this scalable framework can be extended to other material systems and integrated with additive manufacturing, offering an efficient approach for accelerating microstructure design for specific engineering applications.

ConvLSTM↗

DOE OSTI2023

Enabling Hyper-Differential Sensitivity Analysis for Ill-Posed Inverse Problems

Inverse problems constrained by partial differential equations (PDEs) play a critical role in model development and calibration. In many applications, there are multiple uncertain parameters in a model that must be estimated. However, high dimensionality of the parameters and computational complexity of the PDE solves make such problems challenging. A common approach is to reduce the dimension by fixing some parameters (which we will call auxiliary parameters) to a best estimate and use techniques from PDE-constrained optimization to estimate the other parameters. In this article, hyper-differential sensitivity analysis (HDSA) is used to assess the sensitivity of the solution of the PDE-constrained optimization problem to changes in the auxiliary parameters. Foundational assumptions for HDSA require satisfaction of the optimality conditions which are not always practically feasible as a result of ill-posedness in the inverse problem. Here we introduce novel theoretical and computational approaches to justify and enable HDSA for ill-posed inverse problems by projecting the sensitivities on likelihood informed subspaces and defining a posteriori updates. Our proposed framework is demonstrated on a nonlinear multiphysics inverse problem motivated by estimation of spatially heterogeneous material properties in the presence of spatially distributed parametric modeling uncertainties.

97 MATHEMATICS AND COMPUTING↗