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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 OSTI2016

The Mu2e crystal calorimeter and improvements in the $\mu^-\mbox{N} \to e^-\mbox{N}$ search sensitivity

The Mu2e experiment will search for Charged Lepton Flavor Violation (CLFV) looking at the conversion of a muon into an electron in the field of an aluminum nucleus. About $7\cdot 10^{17}$ muons, provided by a dedicated muon beam line in construction at the Fermi National Accelarator Laboratory (Fermilab), will be stopped in 3 years in the Aluminum target. The corresponding single event sensitivity will be $2.5\cdot 10^{-17}$. The Standard Model of particle physics, even extendend to include the finite neutrino masses, predicts the ratio R μe between muon conversions and muon nuclear captures to be $\sim 10^{- 52}$. Several extensions of the Standard Model predict R μe to be in the range of $10^{-14} - 10^{-18}$. % The current best experimental limit, set by the SINDRUM II experiment is $7 \cdot 10^{-13}$ @ $90\%$ CL. The Mu2e experiment plans to improve this experimental limit by four order of magnitude to test many of the possible extensions of the Standard Model. To reach this ambitious goal, the Mu2e experiment is expected to use an intense pulsed muon beam, and rely on a detector system composed of a straw tube tracker and a calorimeter made of pure CsI crystals. The calorimeter plays a central role in the Mu2e measurement, providing particle identification capabilities that are necessary for rejecting two of the most dangerous background sources that can mimic the μ⁻N → e⁻N conversion electron: cosmic muons and $\bar{p}$ induced background. The calorimeter information allows also to improve the tracking performance. Thanks to a calorimeter-seeded track finder algorithm, it is possible to increase the track reconstruction efficiency, and make it more robust with respect to the occupancy level. Expected performances of the calorimeter have been studied in a beam test at the Beam Test Facility in Frascati (Rome, Italy). A reduced scale calorimeter prototype has been exposed to an electron beam, with energy varying from 80 to 140 MeV, for measuring the timing resolution and validate the Monte Carlo prediction. A timing resolution $\sigma_{\rm t}<200$ ps @ 100 MeV has been obtained. Combination of the background rejection performance, and the improvements in the track reconstruction, have then been used in the calculation of the expected Mu2e sensitivity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Transition Metal Polypyridine Complexes: Studies of Mediation in Dye-Sensitized Solar Cells and Charge Separation

The Elliott group has long been supported by DOE for studies of cobalt(II/III) trisbypiridine (DTB) mediator complexes in dye sensitized solar cells. Previous work demonstrated that Co(II/III) chemistry is sensitive to the environment, showing unprecedented electrode-surface and electrolyte dependant voltammetry. In electrolytes that have large lipophilic cations, voltammetry of the [Co(DTB) 3 ] 2+/3+ couple is nearly Nernstian in appearance on nominally oxide-free metal surfaces. In contrast, on semiconductor electrodes in electrolytes with small, hard cations such as Li + , the electron transfer rates are so slow that it is difficult to measure any Faradaic current even at overpotentials of ±1 V. These studies are of direct relevance to the operation of cobalt-based mediators in solar cells. The research has also shown that these mediators are compatible with copper phenantroline based dyes, in contrast to I - due to the insolubility of CuI.

14 SOLAR ENERGY↗
DOE OSTI2023

Time-Sensitive Quantum Key Distribution (TSQKD)

This is the final report for the Time-Sensitive Quantum Key Distribution (TSQKD) project and summarizes the demonstration and longer-term field testing at an electric utility, EPB of Chattanooga, in Chattanooga, TN. The demonstration was held virtually (due to the COVID pandemic) and successfully executed the tests outlined in a prior report, “Task 10: Develop a QKD Time-Sensitive Networking Test Suite” submitted 9/30/2020. The portable test equipment explained in Task 10 and earlier task reports was tested at GE Research remotely connected with Qubitekk’s QKD equipment in San Diego, CA. Then the equipment was shipped to Qubitekk for physical integration with Qubitekk’s Quantum DataLoc™ Key Server 1570nm (http://qubitekk.com/products/qkd-for-industrial-control-systems-ics/). The portable test equipment was shipped from Qubitekk to EPB for demonstration and extended field testing. A summary of the demonstration and test results are described in this report. The demo and extended field test results are enabled by the NETCONF/YANG IEEE P1913 data management model developed as part of this project (Task 5). The NETCONF/YANG IEEE P1913 data management model demonstrated significant practical utility in providing a common means of monitoring and configuring the QKD system. All data in this report comes from the IEEE P1913 data management model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

BSM Sensitivity Analysis and Meta-Modeling Next Steps [Slides]

We performed a global sensitivity analysis of the Bioenergy Scenario Model (BSM), using Elementary Effects analysis to identify potentially influential factors, with a focus on sustainable aviation fuel (SAF) production. The process was iterative and informed key model changes and updates over the course of the study in addition to identifying the key model inputs that affect the cumulative production of SAF from the present through 2050. More work will be performed to gain deeper insight into the sensitivity of individual pathways as part of our larger efforts to develop a reduced-form version of the BSM.

09 BIOMASS FUELS↗
DOE OSTI2026

VIC-Global Parameter Dataset Sensitivity with the Variable Infiltration Capacity Model: Evaluating the importance of dynamic land surface parameters when using the VIC-Global parameter dataset

Accurate prediction of runoff is essential to water resources management, flood risk assessment, and ecosystem protection. However, many hydrological models still have relatively substantial limitations when representing the influence of land use and land cover (LULC) on runoff generation and routing. Changes in LULC, such as deforestation, urban expansion, agricultural intensification, and wetland loss, have been shown to alter the water balance at the land surface through fundamental hydrologic processes (e.g., interception, infiltration, evapotranspiration, and soil storage). However, it remains an open question what the exact magnitude and timing of these impacts are for the spatial and temporal scales commonly used in engineering applications. In this analysis we focus on one aspect of recent LULC change for assessing human impacts, which is urbanization. Specifically we seek to determine the impacts of urbanization on the magnitude and timing of surface runoff and baseflow in HUC-12 basins in Clark County, Nevada which has experienced rapid urbanization. We use the Variable Infiltration Capacity (VIC) hydrology model with a widely used off-the-shelf dataset of land surface parameters, VIC-Global, both of which have been commonly used in the past for water and energy balance modeling for large scale hydrologic studies. We examine two scenarios where the first scenario removes all urbanized land cover and parameterizes those areas of the basins as barren or open shrubland. The second scenario tests the opposite case where all areas of the basins are classified as urban regardless of their present classification. The results from the VIC model show there is a low sensitivity for daily surface runoff between scenarios. The daily baseflow values indicate similar low sensitivity to the classification change during specific periods, but then have substantial differences during other period when large precipitation events are occurring. This is likely due to the assumed parameter values for the urban land cover classification made by the VIC-Global dataset. Using a static land cover parameterization is reasonable for large domain hydrology models that are being used for near-term planning horizons (<30 years). However, longer planning horizons where feedbacks between the atmosphere and land surface are important, especially in transient climate situations, considerations for how to update land surface parameters should be incorporated.

42 ENGINEERING↗
DOE OSTI2026

A tale of two extremes: Temperature sensitivity of carbon loss from cool and hot soils

Soils represent the largest terrestrial carbon (C) pool, and the flux of carbon dioxide (CO 2 ) from soils to the atmosphere is ~ 6-10 times more than anthropogenic emissions. Understanding responses of soil CO 2 emissions to warming is crucial for evaluating feedback to ongoing environmental changes. The relationship between microbial respiration and temperature is typically modeled using a Q 10 function. Generally, observations of the apparent Q 10 of soil respiration are higher for cold vs. warm ecosystems, reflecting expected biophysical controls of Arrhenius kinetics. However, results from two field warming experiments in the tropics contradict this expectation, both observing extraordinarily high soil respiration responses to in situ warming. Our overall objective for the proposed work is to reduce uncertainty in temperature sensitivity of soil C loss by systematically synthesizing underlying mechanisms related to soil C turnover and stabilization. We are evaluating the temperature sensitivity of soil respiration in ecosystems across temperature extremes (e.g., arctic/boreal and tropical systems) by integrating data collected from field warming experiments with machine learning and biogeochemical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Challenges and Lessons Learned in Applying Sensitivity Analysis to Building Stock Energy Models

Uncertainty Analysis (UA) and Sensitivity Analysis (SA) offer essential tools to determine the limits of inference of a model and explore the factors which have the most effect on the model outputs. However, despite a well established body of work applying UA and SA to models of individual buildings, a review of the literature relating to energy models for larger groups of buildings undertaken by Fennell et al. (2019) highlighted very limited application at larger scales. This contribution describes the efforts undertaken by a group of research teams in the context of IEA-EBC Annex 70 working with a diverse set of Building Stock Models (BSMs) to apply global sensitivity analysis methods and compare their results. Since BSMs are a class of model defined by their output and coverage rather than their structure and inputs, they represent a diverse set of modelling approaches. Key challenges for the application of SA are identified and explored, including the influence of model form, input data types and model outputs. This study combines results from 7 different modelling teams, each using different models across a range of urban areas to explore these challenges and begin the process of developing standardised workflows for SA of BSMs.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2023

Fuel performance uncertainty quantification and sensitivity analysis in the presence of epistemic and aleatoric sources of uncertainties

Fuel performance modeling and simulation includes many uncertain parameters from models to boundary conditions, manufacturing parameters and material properties. These parameters exhibit large uncertainties and can have an epistemic or aleatoric nature, something that renders fuel performance code-to-code and code-to-measurements comparisons for complex phenomena such as the pellet cladding mechanical interaction (PCMI) very challenging. Additionally, PCMI and other complex phenomena found in fuel performance modeling and simulation induce strong discontinuities and non-linearities that can render difficult to extract meaningful conclusions form uncertainty quantification (UQ) and sensitivity analysis (SA) studies. In this work, we develop and apply a consistent treatment of epistemic and aleatoric uncertainties for both UQ and SA in fuel performance calculations and use historical benchmark-quality measurement data to demonstrate it. More specifically, the developed methodology is applied to the OECD/NEA Multi-physics Pellet Cladding Mechanical Interaction Validation benchmark. A cold ramp test leading to PCMI is modeled. Two measured quantities of interest are considered: the cladding axial elongation during the irradiations and the cladding outer diameter after the cold ramp. The fuel performance code used to perform the simulation is FAST. The developed methodology involves various steps including a Morris screening to decrease the number of uncertain inputs, a nested loop approach for propagating the epistemic and aleatoric sources of uncertainties, and a global SA using Sobol indices. The obtained results indicate that the fuel and cladding thermal conductivities as well as the cladding outer diameter uncertainties are the three inputs having the largest impact on the measured quantities. More importantly, it was found that the epistemic uncertainties can have a significant impact on the measured quantities and can affect the outcome of the global sensitivity analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Uncertainty quantification and sensitivity analysis of a nuclear thermal propulsion reactor startup sequence

The research presented in this article describes progress in applying stochastic methods, uncertainty quantification, parametric studies, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated via the radiation transport code Griffin to simulate neutronics. Our goal is to develop a reduced-order (surrogate) model that can be rapidly sampled with perturbations to multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums (CDs), which is itself controlled by a hybrid proportional-integral-derivative (PID) controller actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time [Λ] and effective delayed neutron fraction [ β eff ] from a transient Griffin simulation executed via Griffin’s improved quasi-static solver to provide the kinetic parameters) as inputs to functions that control the CD rotation angle. By investigating numerous stochastic approaches, we developed a dual-purpose surrogate model of the NTP system, using polynomial regression in the Multiphysics Object-Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM). The trained model can be rapidly sampled while simultaneously perturbing various input parameters, such as coefficients on the PID control or temperature (directly affecting the neutron cross section). The surrogate model delivers accurate (within 5%) results at speeds orders of magnitude faster (minutes, not days of computational time) than the base model. Once the surrogate model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs as well as the effects of these inputs on the model output. For example, coefficients used in the PID control system may vary due to some type of physical interference, or uncertainty may exist in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters, and operational boundaries can be determined. The goal of this work is to support development of an advanced control system for operating CDs in a functioning NTP system. This work is a scoping study of the MOOSE STM.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

Uncertainty Quantification and Sensitivity Analysis of Nuclear Construction Cost Reduction Pathways

High construction costs have plagued recent nuclear projects and they hamper the widespread deployment of nuclear technology. The Nuclear Cost Reduction Tool is a plant economic framework that quantifies the impact that various plant design and construction attributes have on construction costs and cost overruns and shows the positive effects of learning over a series of deployments. However, a downside of the current model is that all model outputs and capabilities are deterministic. To provide a more comprehensive view, this study evaluated the impact of model parameter uncertainty through a sensitivity analysis applied to 18 model parameters. This approach quantified the impact of model uncertainty on the output variables of Net Overnight Capital Cost (Net OCC), Construction Duration (CD), and Levelized Cost of Electricity (LCOE). Monte Carlo analysis revealed uncertainty distributions for these variables, showing that absolute uncertainty decreases over a series of deployments. A local sensitivity analysis showed that even small parameter perturbations (5%) can have a significant impact on project execution, highlighting areas that could reduce costs by billions across an order book of plants. The results of this study have improved the understanding of the model and identified the most impactful model parameters and construction attributes.

Levelized Cost of Electricity↗
DOE OSTI2019

Simultaneous Thermal Stability and Ultrahigh Sensitivity of Heterojunction SERS Substrates

This paper reports the design of Ag-Al 2 O 3 -Ag heterojunctions based on Ag nanorods (AgNRs) and their applications as thermally stable and ultrasensitive substrates of surface-enhanced Raman scattering (SERS). Specifically, an ultrathin Al 2 O 3 capping layer of 10 nm on top of AgNRs serves to slow down the surface diffusion of Ag at high temperatures. Then, an additional Ag layer on top of the capping layer creates AgNRs-Al 2 O 3 -Ag heterojunctions, which lead to giant enhancement of electromagnetic fields within the Al 2 O 3 gap regions that could boost the SERS enhancement. As a result of this design, the SERS substrates are thermally stable up to 200 °C, which has been increased by more than 100 °C compared with bare AgNRs, and their sensitivity is about 400% that of pure AgNRs. This easy yet effective capping approach offers a pathway to fabricate ultrasensitive, thermally stable and easily prepared SERS sensors, and to extend SERS applications for high-temperature detections, such as monitoring in situ the molecule reorientation process upon annealing. Such simultaneous achievement of thermal stability and SERS sensitivity represents a great advance in the design of SERS sensors and will inspire the fabrication of novel hetero-nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Acoustic Tomography of the Atmosphere: A Large-Eddy Simulation Sensitivity Study

Accurate measurement of atmospheric turbulent fluctuations is critical for understanding environmental dynamics and improving models in applications such as wind energy. Advanced remote sensing technologies are essential for capturing instantaneous velocity and temperature fluctuations. Acoustic tomography (AT) offers a promising approach that utilizes sound travel times between an array of transducers to reconstruct turbulence fields. This study presents a systematic evaluation of the time-dependent stochastic inversion (TDSI) algorithm for AT using synthetic travel-time measurements derived from large-eddy simulation (LES) fields under both neutral and convective atmospheric boundary-layer conditions. Unlike prior work that relied on field observations or idealized fields, the LES framework provides a ground-truth atmospheric state, enabling quantitative assessment of TDSI retrieval reliability, sensitivity to travel-time measurement noise, and dependence on covariance model parameters and temporal data integration. A detailed sensitivity analysis was conducted to determine the best-fit model parameters, identify the tolerance thresholds for parameter mismatch, and establish a maximum spatial resolution. The TDSI algorithm successfully reconstructed large-scale velocity and temperature fluctuations with root mean square errors ( RMSE s) below 0.35 m/s and 0.12 K, respectively. Spectral analysis established a maximum spatial resolution of approximately 1.4 m, and reconstructions remained robust for travel-time measurement uncertainties up to 0.002 s. These findings provide critical insights into the operational limits of TDSI and inform future applications of AT for atmospheric turbulence characterization and system design.

17 WIND ENERGY↗
DOE OSTI2016

A high-sensitivity tunable two-beam fiber-coupled high-density magnetometer with laser heating

Atomic magnetometers (AM) are finding many applications in biomagnetism, national security, industry, and science. Fiber-coupled (FC) designs promise to make them compact and flexible for operation. Most FC designs are based on a single-beam configuration or electrical heating. Here, we demonstrate a two-beam FC AM with laser heating that has 5 fT/Hz 1/2 sensitivity at low frequency (50 Hz), which is higher than that of other fiber-coupled magnetometers and can be improved to the sub-femtotesla level. Here, this magnetometer is widely tunable from DC to very high frequencies (as high as 100 MHz; the only issue might be the application of a suitable uniform and stable bias field) with a sensitivity under 10 fT/Hz 1/2 and can be used for magneto-encephalography (MEG), magneto-cardiography (MCG), underground communication, ultra-low MRI/NMR, NQR detection, and other applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Phage K gp102 Drives Temperature-Sensitive Antibacterial Activity on USA300 MRSA

There is widespread interest in using obligately lytic bacteriophages (“phages”) to treat human bacterial infections. Among Staphylococcus aureus infections, the USA300 lineage is a frequent cause of invasive disease. We observed that phage K, a model S. aureus myophage, exhibits temperature-sensitive growth on USA300 strains, with the wild-type phage providing poorer growth suppression in broth and forming smaller and fainter plaques at 37 °C vs. 30 °C. We isolated 65 mutants of phage K that had improved plaquing characteristics at 37 °C when compared to the parental phage. In all 65 mutants, this phenotype was attributable to loss-of-function (LoF) mutations in gp102, which encodes a protein of unknown function that has homologs only among the Herelleviridae (SPO1-like myophages infecting gram-positive bacteria). Additional experiments with representative mutants consistently showed that the temperature-sensitive plaque phenotype was specific to USA300 MRSA strains and that Gp102 disruption was correlated with improved suppression of bacterial growth in broth and improved antibacterial activity in a mouse model of upper respiratory tract infection. The same genotype and in vitro phenotypes could be replicated in close relatives of phage K. Gp102 disruption did not have a detectable effect on adsorption but did delay cell culture lysis relative to wild-type under permissive infection conditions, suggesting that gp102 conservation might be maintained by selective pressure for more rapid replication. Expression of gp102 on a plasmid was toxic to both an MSSA and a USA300 MRSA strain. Molecular modeling predicts a protein with two helix-turn-helix domains that displays some similarity to DNA-binding proteins such as transcription factors. While its function remains unclear, gp102 is a conserved gene that is important to the infection process of Kayvirus phages, and it appears that the manner in which USA300 strains defend against them at 37 °C can be overcome by gp102 LoF mutations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.

58 GEOSCIENCES↗
DOE OSTI2016

Data assimilation in a solar dynamo model using Ensemble Kalman Filters: sensitivity and robustness in reconstruction of meridional flow speed

We implement an Ensemble Kalman Filter procedure using the Data Assimilation Research Testbed for assimilating “synthetic” meridional flow-speed data in a Babcock–Leighton-type flux-transport solar dynamo model. By performing several “observing system simulation experiments,” we reconstruct time variation in meridional flow speed and analyze sensitivity and robustness of reconstruction. Using 192 ensemble members including 10 observations, each with 4% error, we find that flow speed is reconstructed best if observations of near-surface poloidal fields from low latitudes and tachocline toroidal fields from midlatitudes are assimilated. If observations include a mixture of poloidal and toroidal fields from different latitude locations, reconstruction is reasonably good for ⩽40% error in low-latitude data, even if observational error in polar region data becomes 200%, but deteriorates when observational error increases in low- and midlatitude data. Solar polar region observations are known to contain larger errors than those in low latitudes; our forward operator (a flux-transport dynamo model here) can sustain larger errors in polar region data, but is more sensitive to errors in low-latitude data. An optimal reconstruction is obtained if an assimilation interval of 15 days is used; 10- and 20-day assimilation intervals also give reasonably good results. Assimilation intervals <5 days do not produce faithful reconstructions of flow speed, because the system requires a minimum time to develop dynamics to respond to flow variations. Reconstruction also deteriorates if an assimilation interval >45 days is used, because the system’s inherent memory interferes with its short-term dynamics during a substantially long run without updating.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

SPITZER SECONDARY ECLIPSE DEPTHS WITH MULTIPLE INTRAPIXEL SENSITIVITY CORRECTION METHODS OBSERVATIONS OF WASP-13b, WASP-15b, WASP-16b, WASP-62b, AND HAT-P-22b

We measure the 4.5 μ m thermal emission of five transiting hot Jupiters, WASP-13b, WASP-15b, WASP-16b, WASP-62b, and HAT-P-22b using channel 2 of the Infrared Array Camera (IRAC) on the Spitzer Space Telescope . Significant intrapixel sensitivity variations in Spitzer IRAC data require careful correction in order to achieve precision on the order of several hundred parts per million (ppm) for the measurement of exoplanet secondary eclipses. We determine eclipse depths by first correcting the raw data using three independent data reduction methods. The Pixel Gain Map (PMAP), Nearest Neighbors (NNBR), and Pixel Level Decorrelation (PLD) each correct for the intrapixel sensitivity effect in Spitzer photometric time-series observations. The results from each methodology are compared against each other to establish if they reach a statistically equivalent result in every case and to evaluate their ability to minimize uncertainty in the measurement. We find that all three methods produce reliable results. For every planet examined here NNBR and PLD produce results that are in statistical agreement. However, the PMAP method appears to produce results in slight disagreement in cases where the stellar centroid is not kept consistently on the most well characterized area of the detector. We evaluate the ability of each method to reduce the scatter in the residuals as well as in the correlated noise in the corrected data. The NNBR and PLD methods consistently minimize both white and red noise levels and should be considered reliable and consistent. The planets in this study span equilibrium temperatures from 1100 to 2000 K and have brightness temperatures that require either high albedo or efficient recirculation. However, it is possible that other processes such as clouds or disequilibrium chemistry may also be responsible for producing these brightness temperatures.

79 ASTRONOMY AND ASTROPHYSICS↗