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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Estimated vapor pressure for WTP process streams

Design assumptions during the vacuum refill phase of the Pulsed Jet Mixers (PJMs) in the Hanford Waste Treatment and Immobilization Plant (WTP) equate the vapor pressure of all process streams to that of water when calculating the temperature at which the vacuum refill is reduced or eliminated. WTP design authority asked the authors to assess this assumption by performing calculations on proposed feed slurries to calculate the vapor pressure as a function of temperature. The vapor pressure was estimated for each WTP waste group. The vapor pressure suppression caused by dissolved solids is much greater than the increase caused by organic components such that the vapor pressure for all of the waste group compositions is less than that of pure water. The vapor pressure for each group at 145°F ranges from 81% to 98% of the vapor pressure of water. If desired, the PJM could be operated at higher temperatures for waste groups with high dissolved solids that suppress vapor pressure. The SO4 group with the highest vapor pressure suppression could be operated up to 153°F before reaching the same vapor pressure of water at 145°F. However, most groups would reach equivalent vapor pressure at 147 to 148°F. If any of these waste streams are diluted, the vapor pressure can exceed the vapor pressure of water at mass dilution ratios greater than 10, but the overall effect is less than 0.5%.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Exploring the Use of DSCOVR/EPIC Satellite Observations to Monitor Vegetation Phenology

Vegetation phenology plays a pivotal role in regulating several ecological processes and has profound impacts on global carbon exchange. Large-scale vegetation phenology monitoring mostly relies on Low-Earth-Orbit satellite observations with low temporal resolutions, leaving gaps in data that are important for monitoring seasonal vegetation phenology. High temporal resolution satellite observations have the potential to fill this gap by frequently collecting observations on a global scale, making it easier to study change over time. This study explored the potential of using the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, which captures images of the entire sunlit face of the Earth at a temporal resolution of once every 1–2 h, to observe vegetation phenology cycles in North America. We assessed the strengths and shortcomings of EPIC-based phenology information in comparison with the Moderate-resolution Imaging Spectroradiometer (MODIS), Enhanced Thematic Mapper (ETM+) onboard Landsat 7, and PhenoCam ground-based observations across six different plant functional types. Our results indicated that EPIC could capture and characterize seasonal changes of vegetation across different plant functional types and is particularly consistent in the estimated growing season length. Our results also provided new insights into the complementary features and benefits of the four datasets, which is valuable for improving our understanding of the complex response of vegetation to global climate variability and other disturbances and the impact of phenology changes on ecosystem productivity and global carbon exchange.

Weber, Maridee A.↗
DOE OSTI2014

A study of self organized criticality in ion temperature gradient mode driven gyrokinetic turbulence

An investigation on the characteristics of self organized criticality (Soc) in ITG mode driven turbulence is made, with the use of various statistical tools (histograms, power spectra, Hurst exponents estimated with the rescaled range analysis, and the structure function method). For this purpose, local non-linear gyrokinetic simulations of the cyclone base case scenario are performed with the GENE software package. Although most authors concentrate on global simulations, which seem to be a better choice for such an investigation, we use local simulations in an attempt to study the locally underlying mechanisms of Soc. We also study the structural properties of radially extended structures, with several tools (fractal dimension estimate, cluster analysis, and two dimensional autocorrelation function), in order to explore whether they can be characterized as avalanches. We find that, for large enough driving temperature gradients, the local simulations exhibit most of the features of Soc, with the exception of the probability distribution of observables, which show a tail, yet they are not of power-law form. The radial structures have the same radial extent at all temperature gradients examined; radial motion (transport) though appears only at large temperature gradients, in which case the radial structures can be interpreted as avalanches.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Cyber-Physical Attacks With Control Objectives

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based on a remotely controlled helicopter under attack.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

NS5A inhibitors unmask differences in functional replicase complex half-life between different hepatitis C virus strains

We synthesized the Hepatitis C virus (HCV) RNA by the replicase complex (RC), a macromolecular assembly composed of viral non-structural proteins and cellular co-factors. Inhibitors of the HCV NS5A protein block formation of new RCs but do not affect RNA synthesis by preformed RCs. Without new RC formation, existing RCs turn over and are eventually lost from the cell. We aimed to use NS5A inhibitors to estimate the half-life of the functional RC of HCV. We compared different cell culture-infectious strains of HCV that may be grouped based on their sensitivity to lipid peroxidation: robustly replicating, lipid peroxidation resistant (LPO R ) viruses (e.g. JFH-1 or H77D) and more slowly replicating, lipid peroxidation sensitive (LPO S ) viruses (e.g. H77S.3 and N.2). Furthermore, in luciferase assays, LPO S HCV strains declined under NS5A inhibitor therapy with much slower kinetics compared to LPO R HCV strains. This difference in rate of decline was not observed for inhibitors of the NS5B RNAdependent RNA polymerase suggesting that the difference was not simply a consequence of differences in RNA stability. In further analyses, we compared two isoclonal HCV variants: the LPO S H77S.3 and the LPO R H77D that differ only by 12 amino acids. Differences in rate of decline between H77S.3 and H77D following NS5A inhibitor addition were not due to amino acid sequences in NS5A but rather due to a combination of amino acid differences in the non-structural proteins that make up the HCV RC. The mathematical modeling of intracellular HCV RNA dynamics suggested that differences in RC stability (half-lives of 3.5 and 9.9 hours, for H77D and H77S.3, respectively) are responsible for the different kinetics of antiviral suppression between LPO S and LPO R viruses. In nascent RNA capture assays, the rate of RNA synthesis decline following NS5A inhibitor addition was significantly faster for H77D compared to H77S.3 indicating different half-lives of functional RCs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Designing a Stochastic Adaptive Impulsive Observer for Stochastic Linear and Nonlinear Impulsive Systems

State observation (estimation) is a very important issue in system analysis and control. This paper develops a new observer called Stochastic Adaptive Impulsive Observer (SAIO) for the state estimation of impulsive systems. The proposed observer is applicable to linear and nonlinear stochastic impulsive systems. In addition, the effect of parametric uncertainty is considered and unknown parameters of the system are estimated by suitable adaptation laws. Impulsive system theory, particularly stochastic Lyapunov-like function, is used to analyze the stability and convergence of the state estimations. The main advantages of the proposed observer are: 1) it gives continuous estimation from discrete time measurements of the system output, and 2) it is useful for state estimation when continuous measurements are impossible or expensive. Simulation results show the effectiveness of the proposed observer and we believe that it has many applications in control and estimation theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The XFaster Power Spectrum and Likelihood Estimator for the Analysis of Cosmic Microwave Background Maps

We present the XFaster analysis package, XFaster is a fast, iterative angular power spectrum estimator based on a diagonal approximation to the quadratic Fisher matrix estimator. XFaster uses Monte Carlo simulations to compute noise biases and filter transfer functions and is thus a hybrid of both Monte Carlo and quadratic estimator methods. In contrast to conventional pseudo-C ℓ based methods, the algorithm described here requires a minimal number of simulations, and does not require them to be precisely representative of the data to estimate accurate covariance matrices for the bandpowers. The formalism works with polarization-sensitive observations and also data sets with identical, partially overlapping, or independent survey regions. The method was first implemented for the analysis of BOOMERanG data (Netterfield et al. 2002; Jones et al. 2006), and also used as part of the Planck analysis (Rocha et al. 2011). Here, we describe the full, publicly available analysis package, written in Python, as developed for the analysis of data from the 2015 flight of the SPIDER instrument (SPIDER Collaboration 2021). The package includes extensions for self-consistently estimating null spectra and for estimating fits for Galactic foreground contributions. We show results from the extensive validation of XFaster using simulations, and its application to the SPIDER data set.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A Medium-/Low-Voltage Joint State Estimator Through Linear Uncertainty Propagation

Traditionally, distribution system state estimations (DSSE) are challenged by the lack of measurements at both primary and secondary sides of the system. The widely available cable television (CATV) voltage sensors installed in low-voltage (LV) networks bring opportunities to achieve higher quality DSSE covering a broader area of the distribution network. This study proposes a medium-/low-voltage (MV/LV) joint distribution system state estimation approach using the untapped CATV measurements. It aims at addressing the need for system situational awareness at the grid edge while improving the estimation accuracy at both the primary and secondary sides compared to its disjointed counterpart. Linearized measurement functions and boundary condition uncertainty propagation rules are derived to ensure the computational efficiency and accuracy of the joint state estimator. Numerical experiments are conducted on an IEEE test feeder to demonstrate the efficacy of the proposed method and the value of CATV measurements.

joint state estimation↗
DOE OSTI2017

Solar Thermoelectricity via Advanced Latent Heat Storage: A Cost-Effective Small-Scale CSP Application

We are developing a novel concentrating solar electricity-generating technology that is both modular and dispatchable. Solar ThermoElectricity via Advanced Latent heat Storage (STEALS) uses concentrated solar flux to generate high-temperature thermal energy, which directly converts to electricity via thermoelectric generators (TEGs), stored within a phase-change material (PCM) for electricity generation at a later time, or both allowing for simultaneous charging of the PCM and electricity generation. STEALS has inherent features that drive its cost-competitive scale to be much smaller than current commercial concentrating solar power (CSP) plants. Most obvious is modularity of the solid-state TEG, which favors smaller scales in the kilowatt range as compared to CSP steam turbines, which are minimally 50 MWe for commercial power plants. Here, we present techno-economic and market analyses that show STEALS can be a cost-effective electricity-generating technology with particular appeal to small-scale microgrid applications. We evaluated levelized cost of energy (LCOE) for STEALS and for a comparable photovoltaic (PV) system with battery storage. For STEALS, we estimated capital costs and the LCOE as functions of the type of PCM including the use of recycled aluminum alloys, and evaluated the cost tradeoffs between plasma spray coatings and solution-based boron coatings that are applied to the wetted surfaces of the PCM subsystem. We developed a probabilistic cost model that accounts for uncertainties in the cost and performance inputs to the LCOE estimation. Our probabilistic model estimated LCOE for a 100-kWe STEALS system that had 5 hours of thermal storage and 8-10 hours of total daily power generation. For these cases, the solar multiple for the heliostat field varied between 1.12 and 1.5. We identified microgrids as a likely market for the STEALS system. We characterized microgrid markets in terms of nominal power, dispatchability, geographic location, and customer type, and specified additional features for STEALS that are needed to meet the needs of this growing power market.

14 SOLAR ENERGY↗
DOE OSTI2019

Statistically Rigorous Uncertainty Quantification for Physical Parameter Model Calibration with Functional Output

In experiments conducted on the Z-machine at Sandia National Laboratories, dynamic material properties cannot be analyzed using traditional analytic methods, necessitating solving an inverse problem. Bayesian model calibration is a statistical framework for solving an inverse problem to estimate parameters input into a computational model in the presence of multiple uncertainties. Disentangling input parameter uncertainty and model misspecification is often poorly identified problem. When using computational models for physical parameter estimation, the issue of parameter identifiability must be carefully considered to obtain accurate and precise estimates of physical parameters. Additionally, in dynamic material properties applications, the experimental output is a function, velocity over time. While we can sample an arbitrarily large number of points from the measured velocity, these curves only contain a finite amount of information about the calibration parameters. In this report, we propose modifications to the Bayesian model calibration framework to simplify and improve the estimation of physical parameters with functional outputs. Specifically, we propose scaling the likelihood function by an effective sample size rather than modeling the discrepancy function; and modularizing input nuisance parameters with weakly identified parameters. We evaluate the performance of these proposed methods using a statistical simulation study and then apply these methods to estimate parameters of the tantalum equation of state. We conclude that these proposed methods can provide simple, fast, and statistically valid alternatives to the full Bayesian model calibration procedure; and that these methods can be used to estimate parameters of the equation of state for tantalum.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Twist-2 pseudoscalar and vector meson distribution amplitudes in light-front quark model with exponential-type confining potential

We study the twist-2 distribution amplitudes (DAs) and the decay constants of pseudoscalar light ( π , K ) and heavy ( D , D s , B , B s ) mesons as well as the longitudinally and transversely polarized vector light ( ρ , K * ) and heavy ( D * , D s * , B * , B s * ) mesons in the light-front quark model with the Coulomb plus exponential-type confining potential V exp = a + b e α r in addition to the hyperfine interaction. We first compute the mass spectra of ground state pseudoscalar and vector light and heavy mesons and fix the model parameters necessary for the analysis, applying the variational principle with the trial wave function up to the first three lowest order harmonic oscillator (HO) wave functions $Φ(x,k_{\bot}) = Σ^{3}_{n=1} c_nΦ_{nS}$. We then obtain the numerical results for the corresponding decay constants of light and heavy mesons. We estimate the DAs, analyze their variation as a function of momentum fraction and compute the first six ξ -moments of the B and D mesons as well. We compare our results with the available experimental data as well as with the other theoretical model predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

The dark matter haloes of HI selected galaxies

We present the neutral hydrogen mass (M HI) function (HIMF) and velocity width (w 50 ) function (HIWF) based on a sample of 7857 galaxies from the 40 per cent data release of the ALFALFA survey (α.40). The low mass (velocity width) end of the HIMF (HIWF) is dominated by the blue population of galaxies whereas the red population dominates the HIMF (HIWF) at the high mass (velocity width) end. We use a deconvolution method to estimate the HI rotational velocity (V rot ) functions (HIVF) from the HIWF for the total, red, and blue samples. The HIWF and HIVF for the red and blue samples are well separated at the knee of the function compared to their HIMFs. We then use recent stacking results from the ALFALFA survey to constrain the halo mass (M h ) function of HI-selected galaxies. This allows us to obtain various scaling relations between M HI –w 50 –V rot –M h , which we present. The M HI –M h relation has a steep slope ~2.10 at small masses and flattens to ~0.34 at masses larger than a transition halo mass, $\log _{10}(M_{\rm{ht}}h_{70}^2/M_{\odot })=10.62$. Our scaling relation is robust and consistent with a volume-limited sample of α.40. The M HI –M h relation is qualitatively similar to the M star –M h relation but the transition halo mass is smaller by ~1.4 dex compared to that of the M star –M h relation. Our results suggest that baryonic processes like heating and feedback in larger mass haloes suppress HI gas on a shorter time-scale compared to star formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Quantum Monte Carlo calculation of the binding energy of the beryllium dimer

The accurate calculation of the binding energy of the beryllium dimer is a challenging theoretical problem. In this study, the binding energy of Be{sub 2} is calculated using the diffusion Monte Carlo (DMC) method, using single Slater determinant and multiconfigurational trial functions. DMC calculations using single-determinant trial wave functions of orbitals obtained from density functional theory calculations overestimate the binding energy, while DMC calculations using Hartree-Fock or CAS(4,8), complete active space trial functions significantly underestimate the binding energy. In order to obtain an accurate value of the binding energy of Be{sub 2} from DMC calculations, it is necessary to employ trial functions that include excitations outside the valence space. Our best estimate DMC result for the binding energy of Be{sub 2}, obtained by using configuration interaction trial functions and extrapolating in the threshold for the configurations retained in the trial function, is 908 cm{sup −1}, only slightly below the 935 cm{sup −1} value derived from experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Keeping it real: revisiting a real-space approach to running ensembles of cosmological N-body simulations

In setting up initial conditions for ensembles of cosmological N-body simulations there are, fundamentally, two choices: either maximizing the correspondence of the initial density field to the assumed fourier-space clustering or, instead, matching to real-space statistics and allowing the DC mode (i.e. overdensity) to vary from box to box as it would in the real universe. As a stringent test of both approaches, I perform ensembles of simulations using power law and a ''powerlaw times a bump'' model inspired by baryon acoustic oscillations (BAO), exploiting the self-similarity of these initial conditions to quantify the accuracy of the matter-matter two-point correlation results. The real-space method, which was originally proposed by Pen 1997 [1] and implemented by Sirko 2005 [2], performed well in producing the expected self-similar behavior and corroborated the non-linear evolution of the BAO feature observed in conventional simulations, even in the strongly-clustered regime (σ{sub 8}∼>1). In revisiting the real-space method championed by [2], it was also noticed that this earlier study overlooked an important integral constraint correction to the correlation function in results from the conventional approach that can be important in ΛCDM simulations with L{sub box}∼<1 h{sup −1}Gpc and on scales r∼>L{sub box}/10. Rectifying this issue shows that the fourier space and real space methods are about equally accurate and efficient for modeling the evolution and growth of the correlation function, contrary to previous claims. An appendix provides a useful independent-of-epoch analytic formula for estimating the importance of the integral constraint bias on correlation function measurements in ΛCDM simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A roadmap for the functional annotation of protein families: a community perspective

Over the last 25 years, biology has entered the genomic era and is becoming a science of ‘big data’. Most interpretations of genomic analyses rely on accurate functional annotations of the proteins encoded by more than 500 000 genomes sequenced to date. By different estimates, only half the predicted sequenced proteins carry an accurate functional annotation, and this percentage varies drastically between different organismal lineages. Such a large gap in knowledge hampers all aspects of biological enterprise and, thereby, is standing in the way of genomic biology reaching its full potential. A brainstorming meeting to address this issue funded by the National Science Foundation was held during 3–4 February 2022. Bringing together data scientists, biocurators, computational biologists and experimentalists within the same venue allowed for a comprehensive assessment of the current state of functional annotations of protein families. Further, major issues that were obstructing the field were identified and discussed, which ultimately allowed for the proposal of solutions on how to move forward.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Low cadmium exposure in males and lactating females–estimation of biomarkers

Background: Urine cadmium (Cd) and renal function biomarkers, mostly analysed in urine spot samples, are well established biomarkers of occupational exposure. Their use and associations at low environmental level are common, but have recently been questioned, particularly in terms of physiological variability and normalisation bias in the case of urine spot samples. Aim: To determine the appropriateness of spot urine and/or blood Cd exposure biomarkers and their relationships with renal function biomarkers at low levels of exposure. To this end, we used data from Slovenian human biomonitoring program involving 1081 Slovenians (548 males, mean age 31 years; 533 lactating females, mean age 29 years; 2007–2015) who have not been exposed to Cd occupationally. Results: Geometric means (GMs) of Cd in blood and spot urine samples were 0.27 ng/mL (0.28 for males and 0.33 for females) and 0.19 ng/mL (0.21 for males and 0.17 for females), respectively. Differing results were obtained when contrasting normalisation by urine creatinine with specific gravity. GMs of urine albumin (Alb), alpha-1-microglobulin (A1M), N-acetyl-beta-glucosaminidase (NAG), and immunoglobulin G (IgG) were far below their upper reference limits. Statistical analysis of unnormalised or normalised urine data often yielded inconsistent and conflicting results (or trends), so association analyses with unnormalised data were taken as more valid. Relatively weak positive associations were observed between urine Cd (ng/mL) and blood Cd (β=0.11, p=0.002 for males and β=0.33, p<0.001 for females) and for females between urine NAG and blood Cd (β=0.14, p=0.04). No associations were found between other renal function biomarkers and blood Cd. Associations between Cd and renal function biomarkers in urine were stronger (p<0.05, β=0.11–0.63). Mostly, all of the associations stayed significant but weakened after normalisation for diuresis. In the case of A1M, its associations with Cd were influenced by current smoking and blood Pb in males and by pre-pregnancy smoking and blood Se in females (β up to 0.34, p<0.001). Statistical analysis of unnormalised or normalised urine data often yielded inconsistent and conflicting results (or trends), so association analyses data with unnormalised were taken as more valid. Conclusions: The observed uncertainties introduced by urine normalisation, particularly by creatinine, confirm blood Cd as a superior low-Cd exposure biomarker versus urine Cd in cases when 24 h urine is unattainable. Evidence that A1M can be positively related to Cd, smoking (current or pre-pregnancy), Pb, and Se status, points to the versatile biological functions of A1M. - Highlights: • Creatinine normalisation of spot urine data is inappropriate at low Cd exposure. • Blood Cd as low-Cd exposure biomarker is superior over spot urine Cd. • Cd in urine, but not in blood, was significantly associated with A1M. • A1M – Cd relations were influenced by smoking, Se and less so by Pb.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Single-pixel interior filling function approach for detecting and correcting errors in particle tracking

We present a general method for detecting and correcting biases in the outputs of particle-tracking experiments. Our approach is based on the histogram of estimated positions within pixels, which we term the single-pixel interior filling function (SPIFF). We use the deviation of the SPIFF from a uniform distribution to test the veracity of tracking analyses from different algorithms. Unbiased SPIFFs correspond to uniform pixel filling, whereas biased ones exhibit pixel locking, in which the estimated particle positions concentrate toward the centers of pixels. Although pixel locking is a well-known phenomenon, we go beyond existing methods to show how the SPIFF can be used to correct errors. Here, the key is that the SPIFF aggregates statistical information from many single-particle images and localizations that are gathered over time or across an ensemble, and this information augments the single-particle data. We explicitly consider two cases that give rise to significant errors in estimated particle locations: undersampling the point spread function due to small emitter size and intensity overlap of proximal objects. In these situations, we show how errors in positions can be corrected essentially completely with little added computational cost. Additional situations and applications to experimental data are explored in SI Appendix. In the presence of experimental-like shot noise, the precision of the SPIFF-based correction achieves (and can even exceed) the unbiased Cramér–Rao lower bound. We expect the SPIFF approach to be useful in a wide range of localization applications, including single-molecule imaging and particle tracking, in fields ranging from biology to materials science to astronomy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

BEER ANALYSIS OF KEPLER AND CoRoT LIGHT CURVES. II. EVIDENCE FOR SUPERROTATION IN THE PHASE CURVES OF THREE KEPLER HOT JUPITERS

We analyzed the Kepler light curves of four transiting hot Jupiter systems—KOI-13, HAT-P-7, TrES-2, and Kepler-76, which show BEaming, Ellipsoidal, and Reflection (BEER) phase modulations. The mass of the four planets can be estimated from either the beaming or the ellipsoidal amplitude, given the mass and radius of their parent stars. For KOI-13, HAT-P-7, and Kepler-76 we find that the beaming-based planetary mass estimate is larger than the mass estimated from the ellipsoidal amplitude, consistent with previous studies. This apparent discrepancy may be explained by equatorial superrotation of the planet atmosphere, which induces an angle shift of the planet reflection/emission phase modulation, as was suggested for Kepler-76 in the first paper of this series. We propose a modified BEER model that supports superrotation, assuming either a Lambertian or geometric reflection/emission phase function, and provides a photometry-consistent estimate of the planetary mass. Our analysis shows that for Kepler-76 and HAT-P-7, the Lambertian superrotation BEER model is highly preferable over an unshifted null model, while for KOI-13 it is preferable only at a 1.4σ level. For TrES-2 we do not find such preference. For all four systems the Lambertian superrotation model mass estimates are in excellent agreement with the planetary masses derived from, or constrained by, radial velocity measurements. This makes the Lambertian superrotation BEER model a viable tool for estimating the masses of hot Jupiters from photometry alone. We conclude that hot Jupiter superrotation may be a common phenomenon that can be detected in the visual light curves of Kepler.

79 ASTRONOMY AND ASTROPHYSICS↗