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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

TIC 168789840: A Sextuply Eclipsing Sextuple Star System

We report the discovery of a sextuply eclipsing sextuple star system from TESS data, TIC 168789840, also known as TYC 7037-89-1, the first known sextuple system consisting of three eclipsing binaries. The target was observed in Sectors 4 and 5 during Cycle 1, with lightcurves extracted from TESS Full Frame Image data. It was also previously observed by the WASP survey and ASAS-SN. The system consists of three gravitationally bound eclipsing binaries in a hierarchical structure of an inner quadruple system with an outer binary subsystem. Follow-up observations from several different observatories were conducted as a means of determining additional parameters. The system was resolved by speckle interferometry with a 0.″42 separation between the inner quadruple and outer binary, inferring an estimated outer period of ∼2 kyr. It was determined that the fainter of the two resolved components is an 8.217 day eclipsing binary, which orbits the inner quadruple that contains two eclipsing binaries with periods of 1.570 days and 1.306 days. Markov Chain Monte Carlo (MCMC) analysis of the stellar parameters has shown that the three binaries of TIC 168789840 are “triplets,” as each binary is quite similar to the others in terms of mass, radius, and T {sub eff}. As a consequence of its rare composition, structure, and orientation, this object can provide important new insight into the formation, dynamics, and evolution of multiple star systems. Future observations could reveal if the intermediate and outer orbital planes are all aligned with the planes of the three inner eclipsing binaries.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Eco-PiNN: A Physics-informed Neural Network for Eco-toll Estimation

The eco-toll estimation problem quantifies the expected environmental cost (e.g., energy consumption, exhaust emissions) for a vehicle to travel along a path. This problem is important for societal applications such as eco-routing, which aims to find paths with the lowest exhaust emissions or energy need. The challenges of this problem are threefold: (1) the dependence of a vehicle's eco-toll on its physical parameters; (2) the lack of access to data with eco-toll information; and (3) the influence of contextual information (i.e. the connections of adjacent segments in the path) on the eco-toll of road segments. Prior work on eco-toll estimation has mostly relied on pure data-driven approaches and has high estimation errors given the limited training data. To address these limitations, we propose a novel Eco-toll estimation Physics-informed Neural Network framework (Eco-PiNN) using three novel ideas, namely, (1) a physics-informed decoder that integrates the physical laws governing vehicle dynamics into the network, (2) an attention-based contextual information encoder, and (3) a physics-informed regularization to reduce overfitting. Experiments on real-world heavy-duty truck data show that the proposed method can greatly improve the accuracy of eco-toll estimation compared with state-of-the-art methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Spatially resolved assessment of hepatic function using 99mTc-IDA SPECT

Purpose: 99mTc-iminodiacetic acid (IDA) hepatobiliary imaging is usually quantified for hepatic function on the entire liver or regions of interest (ROIs) in the liver. The authors presented a method to estimate the hepatic extraction fraction (HEF) voxel-by-voxel from single-photon emission computed tomography (SPECT)/CT with a 99mTc-labeled IDA agent of mebrofenin and evaluated the spatially resolved HEF measurements with an independent physiological measurement.Methods: Fourteen patients with intrahepatic cancers were treated with radiation therapy (RT) and imaged by 99mTc-mebrofenin SPECT before and 1 month after RT. The dynamic SPECT volumes were with a resolution of 3.9 × 3.9 × 2.5 mm{sup 3}. Throughout the whole liver with approximate 50 000 voxels, voxelwise HEF quantifications were estimated and compared between using arterial input function (AIF) from the heart and using vascular input function (VIF) from the spleen. The correlation between mean of the HEFs over the nontumor liver tissue and the overall liver function measured by Indocyanine green clearance half-time (T1/2) was assessed. Variation of the voxelwise estimation was evaluated in ROIs drawn in relatively homogeneous regions of the livers. The authors also examined effects of the time range parameter on the voxelwise HEF quantification.Results: Mean of the HEFs over the liver estimated using AIF significantly correlated with the physiological measurement T1/2 (r= 0.52, p= 0.0004), and the correlation was greatly improved by using VIF (r= 0.79, p < 0.0001). The parameter of time range for the retention phase did not lead to a significant difference in the means of the HEFs in the ROIs. Using VIF and a retention phase time range of 7–30 min, the relative variation of the voxelwise HEF in the ROIs was 10%± 6% of respective mean HEF.Conclusions: The voxelwise HEF derived from 99mTc-IDA SPECT by the deconvolution analysis is feasible to assess the spatial distribution of hepatic function in the liver.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Model-Based Localizatiion in a Shallow Ocean Environment: A Sequential Bayesian/Optimization Approach

The shallow ocean is a dynamically changing medium leading to nonstationary statistical behavior when subjected to temperature, wind, surface variations, bottom interactions, noise and extraneous disturbances as well as other conditions that render it a uniquely challenging environment — especially from a signal processing perspective. Processors must account for and adapt to such instantaneous changes in order to be effective. Thus, a processor is required to “adapt” to these environmental variations while simultaneously providing meaningful estimates that are necessary for such applications as detection, localization, inversion and enhancement. In this paper, we develop a parametrically adaptive, sequential Bayesian processor capable of jointly estimating both modal functions and environmental parameters to provide enhanced estimates for a focused optimizer capable locating a target in the noisy shallow ocean environment.

42 ENGINEERING↗
DOE OSTI2022

MEGASIM: Lifetimes and Resonances of Earth Trojan Asteroids—The Death of Primordial ETAs?

Abstract We present an analysis of lifetimes and resonances of Earth Trojan Asteroids (ETAs) in the MEGASIM data set. Trojan asteroids co-orbit the Sun with a planet, but remain bound to the Lagrange points, L4 (60° leading the planet) or L5 (60° trailing). In the circular three-body approximation, the stability of a Trojan asteroid depends on the ratio of the host planet mass and the central mass. For the inner planets, the range of stability becomes increasingly small, so perturbations from the planets have made primordial Trojans rare. To date, there have been just two ETAs (2010 TK 7 and 2020 XL 5 ), several Mars Trojans, and a Venus Trojan discovered. The estimated lifetimes of the known inner system Trojans are shorter than a million years, suggesting they are interlopers rather than members of a stable and long-lasting population. With the largest ETA n -body simulation to date, we are able to track their survival across a wide initialized parameter space. We find that the remaining fraction of ETAs over time is well fit with a stretched exponential function that, when extrapolated beyond our simulation run time, predicts zero ETAs by 2.33 Gyr. We also show correlations between ETA ejections and the periods of the Milankovitch cycles. Though Earth’s orbital dynamics dominate the instabilities of ETAs, we provide evidence that ETA ejections are linked to resonances found in the variation of the orbital elements of many if not all of the planets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

POPULATION PARAMETERS OF INTERMEDIATE-AGE STAR CLUSTERS IN THE LARGE MAGELLANIC CLOUD. III. DYNAMICAL EVIDENCE FOR A RANGE OF AGES BEING RESPONSIBLE FOR EXTENDED MAIN-SEQUENCE TURNOFFS

We present a new analysis of 11 intermediate-age (1-2 Gyr) star clusters in the Large Magellanic Cloud based on Hubble Space Telescope imaging data. Seven of the clusters feature main-sequence turnoff (MSTO) regions that are wider than can be accounted for by a simple stellar population, whereas their red giant branches (RGBs) indicate a single value of [Fe/H]. The star clusters cover a range in present-day mass from about 1 x 10{sup 4} M{sub sun} to 2 x 10{sup 5} M{sub sun}. We compare radial distributions of stars in the upper and lower parts of the MSTO region, and calculate cluster masses and escape velocities from the present time back to a cluster age of 10 Myr. Our main result is that for all clusters in our sample with estimated escape velocities v{sub esc} {approx}> 15 km s{sup -1} at an age of 10 Myr, the stars in the brightest half of the MSTO region are significantly more centrally concentrated than the stars in the faintest half and more massive RGB and asymptotic giant branch stars. This is not the case for clusters with v{sub esc} {approx}< 10 km s{sup -1} at an age of 10 Myr. We argue that the wide MSTO region of such clusters is caused mainly by a {approx}200-500 Myr range in the ages of cluster stars due to extended star formation within the cluster from material shed by first-generation stars featuring slow stellar winds. Dilution of this enriched material by accretion of ambient interstellar matter is deemed plausible if the spread of [Fe/H] in this ambient gas was very small when the second-generation stars were formed in the cluster.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Tumor Tracking Method Based on a Deformable 4D CT Breathing Motion Model Driven by an External Surface Surrogate

Purpose: To develop a tumor tracking method based on a surrogate-driven motion model, which provides noninvasive dynamic localization of extracranial targets for the compensation of respiration-induced intrafraction motion in high-precision radiation therapy. Methods and Materials: The proposed approach is based on a patient-specific breathing motion model, derived a priori from 4-dimensional planning computed tomography (CT) images. Model parameters (respiratory baseline, amplitude, and phase) are retrieved and updated at each treatment fraction according to in-room radiography acquisition and optical surface imaging. The baseline parameter is adapted to the interfraction variations obtained from the daily cone beam (CB) CT scan. The respiratory amplitude and phase are extracted from an external breathing surrogate, estimated from the displacement of the patient thoracoabdominal surface, acquired with a noninvasive surface imaging device. The developed method was tested on a database of 7 lung cancer patients, including the synchronized information on internal and external respiratory motion during a CBCT scan. Results: About 30 seconds of simultaneous acquisition of CBCT and optical surface images were analyzed for each patient. The tumor trajectories identified in CBCT projections were used as reference and compared with the target trajectories estimated from surface displacement with the a priori motion model. The resulting absolute differences between the reference and estimated tumor motion along the 2 image dimensions ranged between 0.7 and 2.4 mm; the measured phase shifts did not exceed 7% of the breathing cycle length. Conclusions: We investigated a tumor tracking method that integrates breathing motion information provided by the 4-dimensional planning CT with surface imaging at the time of treatment, representing an alternative approach to point-based external–internal correlation models. Although an in-room radiograph-based assessment of the reliability of the motion model is envisaged, the developed technique does not involve the estimation and continuous update of correlation parameters, thus requiring a less intense use of invasive imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

A nonlinear lag correction algorithm for a-Si flat-panel x-ray detectors

Purpose: Detector lag, or residual signal, in a-Si flat-panel (FP) detectors can cause significant shading artifacts in cone-beam computed tomography reconstructions. To date, most correction models have assumed a linear, time-invariant (LTI) model and correct lag by deconvolution with an impulse response function (IRF). However, the lag correction is sensitive to both the exposure intensity and the technique used for determining the IRF. Even when the LTI correction that produces the minimum error is found, residual artifact remains. A new non-LTI method was developed to take into account the IRF measurement technique and exposure dependencies. Methods: First, a multiexponential (N = 4) LTI model was implemented for lag correction. Next, a non-LTI lag correction, known as the nonlinear consistent stored charge (NLCSC) method, was developed based on the LTI multiexponential method. It differs from other nonlinear lag correction algorithms in that it maintains a consistent estimate of the amount of charge stored in the FP and it does not require intimate knowledge of the semiconductor parameters specific to the FP. For the NLCSC method, all coefficients of the IRF are functions of exposure intensity. Another nonlinear lag correction method that only used an intensity weighting of the IRF was also compared. The correction algorithms were applied to step-response projection data and CT acquisitions of a large pelvic phantom and an acrylic head phantom. The authors collected rising and falling edge step-response data on a Varian 4030CB a-Si FP detector operating in dynamic gain mode at 15 fps at nine incident exposures (2.0%-92% of the detector saturation exposure). For projection data, 1st and 50th frame lag were measured before and after correction. For the CT reconstructions, five pairs of ROIs were defined and the maximum and mean signal differences within a pair were calculated for the different exposures and step-response edge techniques. Results: The LTI corrections left residual 1st and 50th frame lag up to 1.4% and 0.48%, while the NLCSC lag correction reduced 1st and 50th frame residual lags to less than 0.29% and 0.0052%. For CT reconstructions, the NLCSC lag correction gave an average error of 11 HU for the pelvic phantom and 3 HU for the head phantom, compared to 14-19 HU and 2-11 HU for the LTI corrections and 15 HU and 9 HU for the intensity weighted non-LTI algorithm. The maximum ROI error was always smallest for the NLCSC correction. The NLCSC correction was also superior to the intensity weighting algorithm. Conclusions: The NLCSC lag algorithm corrected for the exposure dependence of lag, provided superior image improvement for the pelvic phantom reconstruction, and gave similar results to the best case LTI results for the head phantom. The blurred ring artifact that is left over in the LTI corrections was better removed by the NLCSC correction in all cases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Field Sensitivity Analysis of Turbulence Model Parameters for Flow Over a Wing

Reynolds-averaged-Navier-Stokes (RANS) turbulence models are a critical tool in computational-fluid-dynamics simulations of aerodynamic systems, but simulation results can be highly sensitive to RANS-model parameter choices. Sensitivity analysis can be used to quantify these impacts, and the objective of this study is to demonstrate field sensitivity analysis with respect to ten parameters in the 2003 Menter shear-stress-transport (SST) turbulence model. Here, the analysis is demonstrated for an application relevant to wind energy, namely, flow over a NACA 0015 wing at 12 degree angle of attack and a Reynolds number of 1.5 x 10 6 . We quantify sensitivity using Sobol indices and the mean-squared gradient, which are estimated using polynomial chaos and active subspace models, respectively. Our results indicate that there are substantial spatial variations in parameter sensitivities, with different sets of most-sensitive parameters near the wing, as well as in the downstream wake, consistent with the physical interpretations of the turbulence model inputs. We show that, for this particular turbulence model and flow, simultaneous dimension reduction is possible across all quantities of interest, enabling efficient exploration of model outcomes. Ultimately, this analysis provides new insights into turbulence model parameter sensitivities in incompressible flows, and also demonstrates the implementation of field sensitivity analysis for applications relevant to aerodynamics simulations.

17 WIND ENERGY↗
DOE OSTI2020

Sound Speed as a Candidate for Internal Temperature Monitoring During Solid Phase Processing of Materials

Internal temperature is an important parameter for understanding the solid phase processing (SPP) of materials and improving feedback control of these processes. Friction stir processes, shear assisted processing and extrusion (ShAPE ™ ), and ultrahigh velocity (UHV) cold spray are examples of such processes. Simple thermal models based on temperatures measured at the boundary of the deforming body cannot capture the dynamic nature of temperature generation within the deforming solid. One possibly way of understanding internal temperature is by measuring sound speed, which varies as a function of temperature for materials and directing ultrasonic wave propagation through selected material volumes of interest. In this project, longitudinal wave speed is estimated for aluminum 6061. Piezoelectric materials bonded to a specimen provided data from which longitudinal wave speed was estimated. A discussion evaluated the linear relationship of wave speed versus temperature and postulated how wave speed measurements could be used to estimate the internal temperature of selected material volumes for feedback during SPP of materials. Instrumentation, data and analysis, and a discussion are reviewed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks

Advances in computational science offer a principled pipeline for predictive modeling of cardiovascular flows and aspire to provide a valuable tool for monitoring, diagnostics and surgical planning. Such models can be nowadays deployed on large patient-specific topologies of systemic arterial networks and return detailed predictions on flow patterns, wall shear stresses, and pulse wave propagation. However, their success heavily relies on tedious pre-processing and calibration procedures that typically induce a significant computational cost, thus hampering their clinical applicability. Here, we put forth a machine learning framework that enables the seamless synthesis of non-invasive in-vivo measurement techniques and computational flow dynamics models derived from first physical principles. We illustrate this new paradigm by showing how one-dimensional models of pulsatile flow can be used to constrain the output of deep neural networks such that their predictions satisfy the conservation of mass and momentum principles. Once trained on noisy and scattered clinical data of flow and wall displacement, these networks can return physically consistent predictions for velocity, pressure and wall displacement pulse wave propagation, all without the need to employ conventional simulators. A simple post-processing of these outputs can also provide a relatively cheap and effective way for estimating Windkessel model parameters that are required for the calibration of traditional computational models. Finally, the effectiveness of the proposed techniques is demonstrated through a series of prototype benchmarks, as well as a realistic clinical case involving in-vivo measurements near the aorta/carotid bifurcation of a healthy human subject.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

Polyhydroxyalkanoates (PHAs) represent an emerging class of biosynthetic and biodegradable polyesters that exhibit considerable potential to replace petroleum-based plastics towards a sustainable future. Despite the promise, general structure–property mappings within this class of polymers remain largely unexplored. An efficient exploration of this vast chemical space calls for the development and validation of predictive methods for accurate estimation of a diverse range of properties for PHA-based polymers. Towards this aim, we present and validate in this work the results of our molecular dynamics (MD) simulation based approach aimed at predicting glass transition temperatures (T g ) of PHA-based polymers. Since generally available and widely used polymer forcefields exhibit a relatively poor performance for T g predictions, we have developed a new forcefield by modifying the polymer consistent force field (PCFF) via refining a selected set of torsion potentials of the polymer backbone using accurate density functional theory (DFT) computations. After carefully assessing the dependence of critical simulation parameters, such as, polymer chain length, number of polymer chains, supercell size, and thermal quenching rate used in the simulation, the applicability and transferability of the modified PCFF (mPCFF) is demonstrated by directly comparing the computed T g predictions of various polymers with different chemistries, polymer side chain lengths and functional groups forming the polymer side chains against the respective experimentally measured values. Furthermore, the transport properties such as self-diffusion coefficient and viscosity are computationally determined and their well-known correlation with the target properties is demonstrated. Lastly, we have employed the developed approach to predict T g values for a number of yet-to-be-synthesized PHA-based polymers with a diverse set of functional groups in the polymer side chains. The results are further rationalized by correlating the predicted T g values with the inter-chain H-bond formation tendencies of the different side chain functional groups. This work represents an important first step towards computationally guided design of PHA-based functional polymers and opens up new directions for a systematic investigation of composition- and configuration-dependent structure–property relationships in more complex binary and ternary copolymer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Data-Driven Model for Photovoltaic Generation: Comparison with Physical Models Using a Microgrid in Puerto Rico

Photovoltaic (PV) generation is a critical component of microgrids, but its accurate modeling is challenging due to the complex and dynamic interactions between solar irradiance, temperature, and PV system installation. This paper develops a multilayer perceptron (MLP) model that inputs solar irradiance and temperature to estimate the PV generation, and it compares the proposed data-driven model’s performance to two well-known physical models: the single-diode model and the inverter model. The results demonstrate that all the models can reach high levels of accuracy. However, the MLP model outperforms the physical models on average by 4.5 to 6.6 percent in R squared scores and 220 to 290 Watts in RMSE scores, and it does not require physical system parameters. Moreover, the data-driven model can overcome the limitations of the lack of real-time PV generation data.

R pesante colón, Marcos↗
DOE OSTI2018

Development and evaluation of a variably saturated flow model in the global E3SM Land Model (ELM) version 1.0

Abstract. Improving global-scale model representations of near-surface soil moisture and groundwater hydrology is important for accurately simulating terrestrial processes and predicting climate change effects on water resources. Most existing land surface models, including the default E3SM Land Model (ELMv0), which we modify here, routinely employ different formulations for water transport in the vadose and phreatic zones. Clark et al. (2015) identified a variably saturated Richards equation flow model as an important capability for improving simulation of coupled soil moisture and shallow groundwater dynamics. In this work, we developed the Variably Saturated Flow Model (VSFM) in ELMv1 to unify the treatment of soil hydrologic processes in the unsaturated and saturated zones. VSFM was tested on three benchmark problems and results were evaluated against observations and an existing benchmark model (PFLOTRAN). The ELMv1-VSFM's subsurface drainage parameter, fd, was calibrated to match an observationally constrained and spatially explicit global water table depth (WTD) product. Optimal spatially explicit fd values were obtained for 79 % of global 1.9∘ × 2.5∘ grid cells, while the remaining 21 % of global grid cells had predicted WTD deeper than the observationally constrained estimate. Comparison with predictions using the default fd value demonstrated that calibration significantly improved predictions, primarily by allowing much deeper WTDs. Model evaluation using the International Land Model Benchmarking package (ILAMB) showed that improvements in WTD predictions did not degrade model skill for any other metrics. We evaluated the computational performance of the VSFM model and found that the model is about 30 % more expensive than the default ELMv0 with an optimal processor layout. The modular software design of VSFM not only provides flexibility to configure the model for a range of problem setups but also allows for building the model independently of the ELM code, thus enabling straightforward testing of the model's physics against other models.

58 GEOSCIENCES↗
DOE OSTI2011

Real-Time Dynamic Brake Assessment Proof of Concept Final Report

This proof-of-concept research was performed to explore the feasibility of using real-world braking data from commercial motor vehicles to make a diagnosis of brake condition similar to that of the performance-based brake tester (PBBT). This was done by determining the relationship between pressure and brake force (P-BF), compensating for the gross vehicle weight (GVW). The nature of this P-BF relationship (e.g., low braking force for a given brake application pressure) may indicate brake system problems. In order to determine the relationship between brake force and brake application pressure, a few key parameters of duty cycle information were collected. Because braking events are often brief, spanning only a few seconds, a sample rate of 10 Hz was needed. The algorithm under development required brake application pressure and speed (from which deceleration was calculated). Accurate weight estimation was also needed to properly derive the braking force from the deceleration. In order to ensure that braking force was the predominant factor in deceleration for the segments of data used in analysis, the data was screened for grade as well. Also, the analysis needed to be based on pressures above the crack pressure. The crack pressure is the pressure below which the individual brakes are not applied due the nature of the mechanical system. This value, which may vary somewhat from one wheel end to another, is approximately 10 psi. Therefore, only pressures 15 psi and above were used in the analysis. The Department of Energy s Medium Truck Duty Cycle research has indicated that under the real-world circumstances of the test vehicle brake pressures of up to approximately 30 psi can be expected. Several different types of data were collected during the testing task of this project. Constant-pressure stopping tests were conducted at several combinations of brake application pressure (15, 20, 25, and 30 psi), load conditions (moderately and fully laden), and speeds (20 and 30 mph). Data was collected at 10 Hz. Standard and stepped-pressure performance-based brake tests with brake pressure transducers were performed for each loading condition. The stepped-pressure test included the constant-pressure intervals of brake application at 15, 20, 25, and 30 psi. The PBBT data files included 10 Hz streaming data collected during the testing of each axle. Two weeks of real-world duty cycle (driving and braking) data was also collected at 10 Hz. Initial analysis of the data revealed that the data collected in the field (i.e., day-to-day operations) provided the same information as that obtained from the controlled tests. Analysis of the data collected revealed a strong linear relationship between brake application pressure and deceleration for given GVWs. As anticipated, initial speed was not found to be a significant factor in the deceleration-pressure relationship, unlike GVW. The positive results obtained from this proof of concept test point to the need for further research to expand this concept. A second phase should include testing over a wider range of speeds and include medium brake application pressures in addition to the low pressures tested in this research. Testing on multiple vehicles would also be of value. This future phase should involve testing to determine how degradation of braking performance affects the pressure-deceleration relationship.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Ab-initio study of thermal expansion in pure graphene

Graphene is a zero band gap semiconductor with exceptionally high thermal conductivity. The electronic properties having been studied, therole of phonon in contributing to thermal expansion, thermal conductivity and other thermodynamic properties, is required to be investigated. This paper focuses more on thermal expansion. Some others results like phonon dispersion, Grüneisenparameters and bulk modulus,which are essential to estimation of thermal expansion, are also presented. The dynamical matrix was calculated using VASP code using both DFT and DFPT and the phonon frequencies were calculated using phonopy code under harmonic approximation. The linear thermal expansion coefficient of graphene is found to be strongly dependent on temperature but remains negative upto 470 K and positive thereafter, with a room temperature value of −1.44×10{sup −6}. The negative expansion coefficient is very interesting and is found to be in conformity with experimental as well as with recent theoretical estimates. There is only qualitative agreement of our results with experimental data and motivates further investigation, primarily on the high negative values of Grüneisen parameters.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Characterization of partially observed epidemics through Bayesian inference: application to COVID-19

We demonstrate a Bayesian method for the "real-time'" characterization and forecasting of partially observed COVID-19 epidemic. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients.The method is designed to help guide medical resource allocation in the early epoch of the outbreak. The estimation problem is posed as one of Bayesian inference and solved using a Markov chain Monte Carlo technique. The data used in this study was sourced before the arrival of the second wave of infection in July 2020. The proposed modeling approach, when applied at the country level, generally provides accurate forecasts at the regional, state and country level. The epidemiological model detected the flattening of the curve in California, after public health measures were instituted.The method also detected different disease dynamics when applied to specific region of New Mexico

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

THE KOZAI–LIDOV MECHANISM IN HYDRODYNAMICAL DISKS. III. EFFECTS OF DISK MASS AND SELF-GRAVITY

Previously we showed that a substantially misaligned viscous accretion disk with pressure that orbits around one component of a binary system can undergo global damped Kozai–Lidov (KL) oscillations. These oscillations produce periodic exchanges of the disk eccentricity with inclination. The disk KL mechanism is quite robust and operates over a wide range of binary and disk parameters. However, the effects of self-gravity, which are expected to suppress the KL oscillations for sufficiently massive disks, were ignored. Here, we analyze the effects of disk self-gravity by means of hydrodynamic simulations and compare the results with the expectations of analytic theory. The disk mass required for suppression in the simulations is a few percent of the mass of the central star and this roughly agrees with an analytical estimate. The conditions for suppression of the KL oscillations in the simulations are close to requiring that the disk be gravitationally unstable. We discuss some implications of our results for the dynamics of protoplanetary disks and the related planet formation.

79 ASTRONOMY AND ASTROPHYSICS↗