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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Toward Accurate Modeling of Galaxy Clustering on Small Scales: Constraining the Galaxy-halo Connection with Optimal Statistics

Applying halo models to analyze the small-scale clustering of galaxies is a proven method for characterizing the connection between galaxies and their host halos. Such works are often plagued by systematic errors or limited to clustering statistics that can be predicted analytically. In this work, we employ a numerical mock-based modeling procedure to examine the clustering of Sloan Digital Sky Survey DR7 galaxies. We apply a standard halo occupation distribution (HOD) model to dark matter only simulations with a ΛCDM cosmology. To constrain the theoreStical models, we utilize a combination of galaxy number density and selected scales of the projected correlation function, redshift-space correlation function, group multiplicity function, average group velocity dispersion, mark correlation function, and counts-in-cells statistics. We design an algorithm to choose an optimal combination of measurements that yields tight and accurate constraints on our model parameters. Compared to previous work using fewer clustering statistics, we find a significant improvement in the constraints on all parameters of our halo model for two different luminosity-threshold galaxy samples. Most interestingly, we obtain unprecedented high-precision constraints on the scatter in the relationship between galaxy luminosity and halo mass. However, our best-fit model results in significant tension (>4σ) for both samples, indicating the need to add second-order features to the standard HOD model. To guarantee the robustness of these results, we perform an extensive analysis of the systematic and statistical errors in our modeling procedure, including a first of its kind study of the sensitivity of our constraints to changes in the halo mass function due to baryonic physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Strong Dark Matter Self-interactions Diversify Halo Populations within and surrounding the Milky Way

Abstract We perform a high-resolution cosmological zoom-in simulation of a Milky Way (MW)–like system, which includes a realistic Large Magellanic Cloud analog, using a large differential elastic dark matter self-interaction cross section that reaches ≈100 cm 2 g −1 at relative velocities of ≈10 km s −1 , motivated by the diverse and orbitally dependent central densities of dwarf galaxies within and surrounding the MW. We explore the effects of dark matter self-interactions on satellite, splashback, and isolated halos through their abundance, central densities, maximum circular velocities, orbital parameters, and correlations between these variables. We use an effective constant cross section model to analytically predict the stages of our simulated halos’ gravothermal evolution, demonstrating that deviations from the collisionless R max – V max relation can be used to select deeply core-collapsed halos, where V max is a halo’s maximum circular velocity, and R max is the radius at which it occurs. We predict that a sizable fraction (≈20%) of subhalos with masses down to ≈10 8 M ⊙ is deeply core collapsed in our SIDM model. Core-collapsed systems form ≈10% of the isolated halo population down to the same mass; these isolated, core-collapsed halos would host faint dwarf field galaxies with extremely steep central density profiles. Finally, most halos with masses above ≈10 9 M ⊙ are core-forming in our simulation. Our study thus demonstrates how self-interactions diversify halo populations in an environmentally dependent fashion within and surrounding MW-mass hosts, providing a compelling avenue to address the diverse dark matter distributions of observed dwarf galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Magnetically self-regulated formation of early protoplanetary disks

The formation of protoplanetary disks during the collapse of molecular dense cores is significantly influenced by angular momentum transport, notably by the magnetic torque. In turn, the evolution of the magnetic field is determined by dynamical processes and non-ideal MHD effects such as ambipolar diffusion. Considering simple relations between various timescales characteristic of the magnetized collapse, we derive an expression for the early disk radius, r≃18 au (η{sub AD}/0.1s){sup 2/9}(B{sub z}/0.1G){sup −4/9}(M/0.1M{sub ⊙}){sup 1/3}, where M is the total disk plus protostar mass, η{sub AD} is the ambipolar diffusion coefficient, and B {sub z} is the magnetic field in the inner part of the core. This is significantly smaller than the disks that would form if angular momentum was conserved. The analytical predictions are confronted against a large sample of 3D, non-ideal MHD collapse calculations covering variations of a factor 100 in core mass, a factor 10 in the level of turbulence, a factor 5 in rotation, and magnetic mass-to-flux over critical mass-to-flux ratios 2 and 5. The disk radius estimates are found to agree with the numerical simulations within less than a factor 2. A striking prediction of our analysis is the weak dependence of circumstellar disk radii upon the various relevant quantities, suggesting weak variations among class-0 disk sizes. In some cases, we note the onset of large spiral arms beyond this radius.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Magnetic Pumping as a Source of Particle Heating and Power-Law Distributions in the Solar Wind

Based on the rate of expansion of the solar wind, the plasma should cool rapidly as a function of distance to the Sun. Observations show this is not the case. In this work, a magnetic pumping model is developed as a possible explanation for the heating and the generation of power-law distribution functions observed in the solar wind plasma. Most previous studies in this area focus on the role that the dissipation of turbulent energy on microscopic kinetic scales plays in the overall heating of the plasma. However, with magnetic pumping, particles are energized by the largest-scale turbulent fluctuations, thus bypassing the energy cascade. In contrast to other models, we include the pressure anisotropy term, providing a channel for the large-scale fluctuations to heat the plasma directly. A complete set of coupled differential equations describing the evolution, and energization, of the distribution function are derived, as well as an approximate closed-form solution. Numerical simulations using the VPIC kinetic code are applied to verify the model's analytical predictions. The results of the model for realistic solar wind scenario are computed, where thermal streaming of particles are important for generating a phase shift between the magnetic perturbations and the pressure anisotropy. In turn, averaged over a pump cycle, the phase shift permits mechanical work to be converted directly to heat in the plasma. Here, the results of this scenario show that magnetic pumping may account for a significant portion of the solar wind energization.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Turbulence and Particle Acceleration in a Relativistic Plasma

Abstract In a collisionless plasma, the energy distribution function of plasma particles can be strongly affected by turbulence. In particular, it can develop a nonthermal power-law tail at high energies. We argue that turbulence with initially relativistically strong magnetic perturbations (magnetization parameter σ ≫ 1) quickly evolves into a state with ultrarelativistic plasma temperature but mildly relativistic turbulent fluctuations. We present a phenomenological and numerical study suggesting that in this case, the exponent α in the power-law particle-energy distribution function, f ( γ ) d γ ∝ γ − α d γ , depends on magnetic compressibility of turbulence. Our analytic prediction for the scaling exponent α is in good agreement with the numerical results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Magnetic Field Amplification by a Plasma Cavitation Instability in Relativistic Shock Precursors

Abstract Plasma streaming instabilities play an important role in magnetic field amplification and particle acceleration in relativistic shocks and their environments. However, in the far shock precursor region where accelerated particles constitute a highly relativistic and dilute beam, streaming instabilities typically become inefficient and operate at very small scales when compared to the gyroradii of the beam particles. We report on a plasma cavitation instability that is driven by dilute relativistic beams and can increase both the magnetic field strength and coherence scale by orders of magnitude to reach near-equipartition values with the beam energy density. This instability grows after the development of the Weibel instability and is associated with the asymmetric response of background leptons and ions to the beam current. The resulting net inductive electric field drives a strong energy asymmetry between positively and negatively charged beam species. Large-scale particle-in-cell simulations are used to verify analytical predictions for the growth and saturation level of the instability and indicate that it is robust over a wide range of conditions, including those associated with pair-loaded plasmas. These results can have important implications for the magnetization and structure of shocks in gamma-ray bursts, and more generally for magnetic field amplification and asymmetric scattering of relativistic charged particles in plasma astrophysical environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

Electron Recombination in a Dense Hydrogen Plasma

A high pressure hydrogen gas filled RF cavity was subjected to an intense proton beam to study the evolution of the beam induced plasma inside the cavity. Varying beam intensities, gas pressures and electric fields were tested. Beam induced ionized electrons load the cavity, thereby decreasing the accelerating gradient. The extent and duration of this degradation has been measured. A model of the recombination between ionized electrons and ions is presented, with the intent of producing a baseline for the physics inside such a cavity used in a muon accelerator. Analysis of the data taken during the summer of 2011 shows that self recombination takes place in pure hydrogen gas. The decay of the number of electrons in the cavity once the beam is turned off indicates self recombination rather than attachment to electronegative dopants or impurities. The cross section of electron recombination grows for larger clusters of hydrogen and so at the equilibrium of electron production and recombination in the cavity, processes involving H{sub 5}{sup +} or larger clusters must be taking place. The measured recombination rates during this time match or exceed the analytic predicted values. The accelerating gradient in the cavity recovers fully in time for the next beam pulse of a muon collider. Exactly what the recombination rate is and how much the gradient degrades during the 60 ns muon collider beam pulse will be extrapolated from data taken during the spring of 2012.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

Tiny Bubbles in my BEC

Ultracold atomic gases provide a unique way for exploring many-body quantum phenomena that are inaccessible to conventional low-temperature experiments. Nearly two decades ago the Bose-Einstein condensate (BEC) - an ultracold gas of bosons in which almost all bosons occupy the same single-particle state - became experimentally feasible. Because a BEC exhibits superfluid properties, it can provide insights into the behavior of low-temperature helium liquids. We describe the case of a single distinguishable atom (an impurity) embedded in a BEC and strongly coupled to the BEC bosons. Depending on the strength of impurity-boson and boson-boson interactions, the impurity self-localizes into two fundamentally distinct regimes. The impurity atom can behave as a tightly localized 'polaron,' akin to an electron in a dielectric crystal, or as a 'bubble,' an analog to an electron bubble in superfluid helium. We obtain the ground state wavefunctions of the impurity and BEC by numerically solving the two coupled Gross-Pitaevskii equations that characterize the system. We employ the methods of imaginary time propagation and conjugate gradient descent. By appropriately varying the impurity-boson and boson-boson interaction strengths, we focus on the polaron to bubble crossover. Our results confirm analytical predictions for the polaron limit and uncover properties of the bubble regime. With these results we characterize the polaron to bubble crossover. We also summarize our findings in a phase diagram of the BEC-impurity system, which can be used as a guide in future experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2013

A Study of Turbulence-Driven Inward Momentum Flux & Construction of a Difference Scheme for Fokker-Planck-Landau Operator

Momentum transport driven by microinstability is studied via analytic theories, gyrokinetic simulations, and experimental data analysis. A scenario for rotation profile evolution is constructed based on experimental observation that parallel flow initiates at edge region and penetrates into core region of tokamak [1]. In particular, turbulent diffusion and inward convective pinch are studied according to this scenario. For study of convective momentum pinch, toroidal ion temperature gradient mode near marginal stability is examined in kinetic limit. It is found from quasilinear estimation that the inward turbulent equipartition momentum pinch remains as the most robust part of pinch. In addition, it is found that ion temperature gradient driven momentum pinch is inward for typical parameters, while ion density gradient driven momentum pinch is outward. It is shown by theoretical formulas and experimental data analysis that momentum pinch velocity is sensitive to the electron to ion temperature ratio. For study of diffusive momentum transport, parallel shear flow instability is studied in fluid limit. Diffusion coefficient using mixing length estimate from nonlocal theory reveals that it has a strong dependence on the parallel flow shear and is mainly carried by fluctuations in short wavelength regime. Gyrokinetic simulation of collisionless parallel shear flow instability shows that the analytic prediction of diffusion coefficient is comparable to numerical values in the linear phase of the simulations. In the nonlinear phase, fluctuation energy gets transferred to the long wavelength regime. A two-dimensional, uniform velocity-grid based solver for the nonlinear Fokker-Planck-Landau (FPL) collision operator has been developed in the limit of strong magnetic field. The conservative and entropy increasing semidiscretized numerical scheme for the isotropic FPL equation by C. Buet et al. (2002) has been extended to 2D velocity space. A Picard fixed point method is used for semi-implicit time advance. One time evaluation of interpolation coefficients for probability distribution function is introduced so that numerical equilibrium is achieved with Maxwellian. However, positivity property is sacrificed at the saving of computational costs. In addition, a highly practical method is suggested to apply the velocity-grid based collision solver to particle-in-cell code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

ATF Transient Prescription Tests in TREAT

EXECUTIVE SUMMARY The Transient Reactor Test facility (TREAT) was constructed in the late 1950’s and provided thousands of transient irradiations before being placed in standby mode in 1994. In 2017, it resumed operation in order to reclaim its crucial role in nuclear-heated safety research. TREAT is a transient reactor where inherently-safe core physics, a nimble transient rod drive system, and a philosophy of continual facility improvement work together to enable flexible power maneuvers for fuel safety research. While the facility’s flexible design and multi-mission nature saw historic experiments for numerous transient types, TREAT was not specifically adapted to optimize or demonstrate its full performance capability for Light Water Reactor (LWR) postulated accidents including Hot Zero Power Reactivity Initiated Accidents (HZP-RIA) and Loss of Coolant Accidents (LOCA). The physics of HZP-RIA drive very brief pulses with fairly large energy excursions. TREAT is currently capable of approaching HZP-RIA pulse widths through transients initiated on a large step insertion of reactivity and terminated shortly thereafter by rapid re-insertion of the transient rods (“clipping”). LOCAs are postulated to occur quite differently, starting from normal power operations followed by a long period of lower power decay heat. TREAT is able to simulate LOCA events with an initial flattop transient for tens of seconds, followed by a sizeable power reduction, to a longer segment where specimen fission heating represents internal decay heat generation. Two reactor physics testing campaigns were undertaken to address the HZP-RIA type transients, neither of which had been performed in any great measure historically to address data gaps in the timing, repeatability of clipping and effect of dynamic transient rod motions on core-to-specimen fission power coupling. The first campaign, referred to as the Accident Tolerant Fuel (ATF) transient prescription tests, employed dosimeters in the core to characterize the effect of rod motions on specimen power coupling for clipped, unclipped, and low-level steady state operations each with approximately the same moderate core energy release. This campaign was accompanied by efforts to measure dosimetry and compare results to analytic predictions. The other HZP-RIA campaign, referred to as Narrow Pulse Width (NPW) transient prescriptions, employed higher step insertions with increased core energy release to demonstrate TREAT’s capability in achieving the narrowest-possible pulse width. Additionally, a series of LOCA transient prescriptions were also performed to demonstrate how well TREAT could perform long-duration shaped transients. Both NPW and LOCA transient prescriptions did not include dosimeters but used existing plant power instrumentation to produce transient power data. All three transient prescription campaigns were successfully carried out in TREAT. The ATF-3 transient prescriptions showed that TREAT can perform clipped transients with remarkable repeatability. Measurement and modeling both showed that the power coupling in small, fissile dosimeters does not change by more than 8% between clipped, unclipped, and steady state runs while uncertainty sources in both the modeling and measurement methods were identified and found to be on the order of 20% in total. Overall, the ATF-3 transient prescription tests were successful in determining repeatability and consistency of dosimeter power coupling, developing processes for modeling and measuring this crucial parameter, and demonstrating the need for continued efforts in transient prescription work at TREAT in support of future experiment design and post test data interpretation. The NPW and LOCA transient prescriptions were also successfully performed to exhibit TREAT’s capability for these important LWR accident categories. The NPW transients showed pulse widths of ~90 ms, which were the narrowest ever achieved in TREAT to date and relevant for the upper end range of HZP-RIA simulation. This effort provided crucial data for calibrating kinetic models to be used in enhanced pulse-narrowing strategies in upcoming irradiations. Similarly, The LOCA transient prescriptions showed that TREAT can simulate the needed nuclear heating and event time scales for LOCA fuel safety research and provided essential data for future experiment design.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 3

This project is a collaborative research effort between PKMJ Technical Services LLC, Idaho National Laboratory, and Public Service Enterprise Group (PSEG) Nuclear, LLC. The collaboration, led by PKMJ Technical Services LLC, is part of the industry Funding Opportunity Announcement (FOA) award under Advanced Nuclear Technology Development FOA #DE-FOA-0001817. The pilot demonstration focuses on the Circulating Water System (CWS), an important non-safety-related system that impacts the power generation capability of the plant site. Achieving riskinformed condition-based Predictive Maintenance (PdM) on the CWS will result in significant economic benefits, and the developed methodologies can also be applied to other plant systems. This approach supports an industry goal of ensuring that nuclear power generation remains a viable, economically competitive option in the energy market. Operation and Maintenance (O&M) costs include labor-intensive Preventive Maintenance (PM) programs that involve manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies as well as time-based replacement of assets, irrespective of condition. This project offers an alternative by focusing on riskinformed condition-based maintenance to reduce O&M costs while still maintaining plant health and safety. This report summarizes the progress made toward achieving a risk-informed condition-based maintenance approach. The research and development (R&D) activities presented in this report are associated with development of a nuclear digital platform application, integration of fault signature models, and automated work management processes. The fault signatures and Machine Learning (ML) models are key components in predictive analytics and are heavily leveraged to improve the insights received by existing plant process data sources. Availability of the analysis results within a centralized digital platform enhances efficiency by enabling automation of activities otherwise performed manually. Personnel are presented with enhanced information that can be used to evaluate plant status and risks. Utilizing the enhancements to data analytics supports automated responses, (i.e. issuance of work orders) to address developing equipment faults and thus preventing forced, unplanned shutdowns of components or systems. The R&D activities described within this report lay the foundation for developing and demonstrating a digital automated platform to centralize the implementation of condition monitoring and response to equipment faults. The digital automated platform is cloud-based and designed to enable improved efficiency of plant processes. The digital platform includes content related to maintenance optimization, fault signature analysis, and plant records, which can all be used to support efficiencies when located within a centralized digital platform. These efficiencies could be further enhanced when deployed through industry-wide deployment of the technology to improve insights and processes based upon economies of scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Seismic and LOCA safety testing and analysis program for Westinghouse PWR fuel under end of life conditions

The NRC issued Information Notice - IN 2012-09 in June 2012 which challenges approved assumptions based on the beginning of life (BOL) conditions in seismic and LOCA analysis. Westinghouse manufactures a variety of PWR fuel designs, including 14*14, 15*15, 16*16 and 17*17 array, also different fuel lengths from 12 feet to 14 feet. The fuels are supplied to the cores designed by Westinghouse and Combustion Engineering, and other cores around world. To address IN 2012-09 efficiently and economically, Westinghouse and PWR Owner Groups launched a testing and analysis program funded by PWROG. The program planed testing and analysis matrices based on types of fuel designs. The testing plan includes grid crush tests, fuel assembly mechanical tests and flowing water damping tests. Applying modelling technique, the program will reduce the number of test and cost. The ultimate goal of the program is to generate fuel assembly EOL models for all fuel designs manufactured by Westinghouse and to be ready for any plant specific seismic and LOCA analysis to address NRC IN for EOL effect. The phase I of PWROG for EOL conditions has been completed and several conclusions are obtained. First, the gapped grids reduce grid dynamic stiffness, local impact stiffness and crush strength. Also, due to gapped grids, both the fuel assembly natural frequency and stiffness are reduced. Secondly, applying higher fuel assembly damping due to the flowing water effect can significantly reduce fuel assembly impact forces. However, during a seismic event the reactor coolant pumps may trip resulting in a coast-down. As such, reduced flow rates that occur during the pump coast-down must be considered. Thirdly, the analytical model representation of a reactor core adequately characterizes the core response under seismic and LOCA excitations. Static and dynamic structural test results of a fuel assembly compared with analytical predictions indicate that the fuel assembly lateral and axial structural behavior can be fully determined with finite element models. Fourthly, analyses for EOL fuel assemblies under seismic and LOCA loads demonstrate EOL effect and flowing water damping effect. With flowing water damping benefit, significant margin can be recovered for fuel assemblies with EOL conditions and under seismic loads.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Sockeye Heat Pipe Analysis Code Verification and Validation

Some of the most promising microreactor designs currently under development utilize heat pipe technology to transfer heat from the reactor core to the secondary side heat exchanger, due to the technology’s compactness, efficiency, passivity, and reliability. Sockeye is an engineering-scale heat pipe tool developed under the Nuclear Energy Advanced Modeling and Simulation Program to be used for the design and safety analysis of microreactors. Sockeye’s core capability lies in a 1D, two-phase, compressible flow model, used to simulate the working fluid inside the heat pipe. Sockeye is built on the Multiphysics Object-Oriented Simulation Environment framework, which allows for seamless multiphysics coupling with other Nuclear Energy Advanced Modeling and Simulation tools and can thus be used in a full-scale simulation of a microreactor assembly, which can include hundreds of heat pipes. This paper presents some initial verification and validation assessments performed for Sockeye. We demonstrate good agreement between Sockeye’s numerical results and steady-state analytic solutions for velocity and pressure drop, with differences attributable to the underlying assumptions made by the analytic solutions. We also show that Sockeye reproduces analytic predictions of key operational limits, such as the capillary limit and the sonic limit. Finally, we compare Sockeye results to experimental data for the SAFE-30 heat pipe module test.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Dynamically suppressing cavity dephasing induced by frequency fluctuations of a coupled nonlinear mode

High-coherence superconducting cavities offer a promising platform for quantum information, with long coherence times and negligible intrinsic dephasing. However, cavity control generally relies on nonlinear Josephson elements whose frequency fluctuations are inherited by the cavity as dephasing, potentially limiting control fidelities and eroding the noise bias used in error-correction protocols. Here, we introduce Stark-Assisted Flux-noise Evasion (SAFE), a hardware-efficient protocol that protects the cavity from inherited dephasing using only a weak off-resonant microwave drive applied to the nonlinear element. As a concrete setup, we analyze a 3D superconducting cavity dispersively coupled to a flux-tunable transmon (FTT) subject to $1/f$ flux noise. Analytical predictions are confirmed by Monte Carlo simulations with realistic parameters, which show that SAFE can extend the cavity dephasing time by more than an order of magnitude while keeping residual drive-induced decoherence subdominant.

Lu, Yunwei [Northwestern U.] (ORCID:00000003401756↗
DOE OSTI2014

Predicting Student Success using Analytics in Course Learning Management Systems

Educational data analytics is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the student and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present the efforts carried out at Oak Ridge National Laboratory (ORNL) toward conducting predictive analytics to academic data collected from 2009 through 2013 and available in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total GPA at the same term they enrolled in the course. Then, Logistic Regression and Neural Network predictive models are used to identify students as early as possible that are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy.

Educational data mining↗
DOE OSTI2021

Data analytics approach to predict high-temperature cyclic oxidation kinetics of NiCr-based Alloys

Abstract Although of practical importance, there is no established modeling framework to accurately predict high-temperature cyclic oxidation kinetics of multi-component alloys due to the inherent complexity. We present a data analytics approach to predict the oxidation rate constant of NiCr-based alloys as a function of composition and temperature with a highly consistent and well-curated experimental dataset. Two characteristic oxidation models, i.e., a simple parabolic law and a statistical cyclic oxidation model, have been chosen to numerically represent the high-temperature oxidation kinetics of commercial and model NiCr-based alloys. We have successfully trained machine learning (ML) models using highly ranked key input features identified by correlation analysis to accurately predict experimental parabolic rate constants ( k p ). This study demonstrates the potential of ML approaches to predict oxidation kinetics of alloys over wide composition and temperature ranges. This approach can also serve as a basis for introducing more physically meaningful ML input features to predict the comprehensive cyclic oxidation behavior of multi-component high-temperature alloys with proper constraints based on the known underlying mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Predicting diagnostic error in radiology via eye-tracking and image analytics: Preliminary investigation in mammography

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels.Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated.Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features.Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

An analytical model to predict curvature effects of the carbon nanotube on the overall behavior of nanocomposites

In this study, analytical expressions are introduced to provide a better understanding of carbon nanotubes (CNTs) curvature on the overall behavior of nanocomposites. The curviness of CNT is modeled as the wave geometries, and the transformed physical characteristics are applied to micromechanical framework. Since five independent elastic constants of CNTs are essential to derive the waviness effect, atomistic molecular statics simulations with varying nanotube radii are conducted. Influences of CNT curviness on the effective stiffness of the nanocomposites are analyzed, noting that the curvature effect is significantly influential on the effective stiffness of the nanocomposites, and it may improve or reduce the reinforcing effect depending on the orientation of CNTs. In addition, the predictions are compared with experimental data of the CNT-reinforced nanocomposites to assess the reliability of the proposed method. The developed constitutive model is expected to be used to determine the volume concentration of the reinforcing CNTs and mechanical responses of CNT-reinforced composites under various CNT curvature, radius, and orientation conditions.

42 ENGINEERING↗