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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

In Situ Monitoring of Groundwater Contamination for Sustainable Remediation Using the Kalman Filter - 18423

Groundwater monitoring is critical for nuclear-related facilities as well as radioactively contaminated sites. Recent advances in sensing, data analytics and simulation capabilities provide substantial opportunities to improve and change current monitoring procedures. In particular, we need a paradigm shift from contaminant-only or compliance-only monitoring programs to comprehensive monitoring, i.e., including other ancillary environmental variables for a holistic understanding of the groundwater systems and plume behaviors. Such new approaches are needed for the effective implementation of sustainable remediation (enhanced and natural attenuation), and they have great potential for cost reduction in site monitoring. This paper reviews recent developments for improving long-term monitoring, with focus on the effective use of in situ sensors, data analytics and simulation capabilities. In particular, we highlight a recent application of the Kalman filter algorithm to estimate contaminant concentrations continuously in real time, based on in-situ measured water quality parameters (e.g. electrical conductance and pH) and sparse groundwater sampling. The results show that we can reduce the groundwater sampling frequency significantly, while capturing the dynamics of short- and long-term contaminant concentration changes. Such advanced and integrated monitoring systems will be beneficial for local residents (e.g., to ensure the safety by detecting adverse events early, enabling a swift response) as well as for site operators (e.g., to gain/improve public acceptance, to be better prepared for litigations and false claims, and to reduce overall monitoring cost). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Plasma transport in an Eulerian AMR code

A plasma transport model has been implemented in an Eulerian AMR radiation-hydrodynamics code, xRage, which includes plasma viscosity in the momentum tensor, viscous dissipation in the energy equations, and binary species mixing with consistent species mass and energy fluxes driven by concentration gradients, ion and electron baro-diffusion terms and temperature gradient forces. The physics basis, computational issues, numeric options, and results from several test problems are discussed. The transport coefficients are found to be relatively insensitive to the kinetic correction factors when the concentrations are expressed with the molar fractions and the ion mass differences are large. The contributions to flow dynamics from plasma viscosity and mass diffusion were found to increase significantly as scale lengths decrease in an inertial confinement fusion relevant Kelvin-Helmholtz instability mix layer. The mixing scale lengths in the test case are on the order of 100 μm and smaller for viscous effects to appear and 10 μm or less for significant ion species diffusion, evident over durations on the order of nanoseconds. The temperature gradient driven mass flux is seen to deplete a high Z tracer ion at the ion shock front. The plasma transport model provides the generation of the atomic mix per unit of interfacial area between two species with no free parameters. The evolution of the total atomic mix then depends also on an accurate resolution or estimate of the interfacial area between the species mixing by plasma transport. High resolution simulations or a more Lagrangian-like treatment of species interfaces may be required to distinguish plasma transport and numerical diffusion in an Eulerian computation of complex and dynamically evolving mix regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles

Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.

Oke, Doris↗
DOE OSTI2018

Design of a Robust Digital Control System for the Rectification Column Used in the Production of Divinyl

A complex optimization criterion that takes into account the integral quadratic error and the stability margin of a robust digital control system for the rectification column used for the butylene-divinyl fraction is proposed. The influence of the weight coefficient, taking into account the ratio of the performance and stability indicators, on the dynamic characteristics of the system is investigated. High system performance and system stability indices over a sufficiently broad range of variation of the parameters of the rectification column are achieved through the use of the proposed optimization criterion and a stability estimation algorithm in the synthesis of a robust digital control system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Testing Dynamic Earthquake Rupture Models Generated With Stochastic Stress Drop

In this study we investigate the performance of rupture dynamics modeling using heterogenous stress for a M6.5 crustal earthquake on a strike slip vertical fault. In our simulations we used heterogenous stress drop models with correlated stochastic perturbations following the work of Pitarka et al. (2009). The stress model with multiscale variability is designed to accommodate high-stress drop asperity areas and small-scale spatial stress variations. The stress drop and size of asperities are estimated following the IM2011 (Irikura and Miyake, 2011) recipe. In our spontaneous rupture modeling we use a linear slip weakening friction law, with depth depend strength excess, dynamic stress drop and slip weakening distance Dc. Our strategy in preparing the model parameters with vertical and lateral variability is in agreement with observations of earthquake rupture that have confirmed the existence of a shallow weak rupture zone consisting of ductile crustal material, located in the upper 4 km of the crust, and brittle seismogenic zone, underlying the weak zone. The primary objective of our study is to develop a procedure for preparing dynamic rupture models with multiscale variability, and validate spontaneous rupture modeling of strike-slip faults by comparing the resulting rupture kinematics and near-fault ground motion with empirical models for this type of rupture.

58 GEOSCIENCES↗
DOE OSTI2018

Collaborative Research: The Role of Grain Boundary Structure and Chemistry in Materials Failure

Throughout the one year duration of this award significant progress was made in understanding the effect of grain boundaries in polycrystalline materials. The starting point of this work is that each grain boundary can be characterized by an interface energy and respective interface parameter, which depend on the boundary chemical composition and structure. As this is a new point of view for treating grain boundaries, an interdisciplinary approach was followed to prove the existence of such interface terms. Throughout the project, hence, theory, experiments and simulations were used. Molecular dynamics and dislocation density-function dynamics were performed to understand dislocation-grain boundary interactions in pure Al crystalline materials, as potentials for Al are well established. The formation of dislocation pile-ups was observed and the strain profiles were in agreement with interfacial gradient plasticity, which is the theoretical framework that allows the introduction of mechanically induced interface energies. After verifying numerically the existence of mechanically induced interface energies, nanoindentation experiments were performed near grain boundaries of Fe-Si crystals that contained three grain boundaries. By indenting in close proximity to the boundary these experiments allowed for measuring the critical stress at which deformation was transmitted across the boundary to the adjacent grains, either through dislocation transmission or absorption and subsequent emission. This critical stress, also termed grain boundary yield stress, was in accordance with the value predicted by interfacial gradient plasticity, further verifying that mechanically induced interface energies can help define the material response. In the Fe-Si crystals the Si content was kept constant at 3wt%, but three specimen were considered each of which was characterized by a different misorientation at the grain boundary. By relating the experiments with the analytical gradient plasticity expressions it was possible to obtain first estimates for the interface parameter as ~200N/m. This value was not proportional to the misorientation angle, but depended also on the grain boundary plane. The continuation of this project is performing more detailed experiments on additional Fe-Si and Fe-C systems (both nanoindentation and in-situ transmission electron microscopy) to further understand the physical origin of such interface parameters. Furthermore, molecular dynamics nanoindentation simulations are also performed on similar systems to better understand the dislocation grain boundary interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities

Abstract As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Quantum parameter estimation in the Unruh–DeWitt detector model

Relativistic effects on the precision of quantum metrology for particle detectors, such as two-level atoms are studied. The quantum Fisher information is used to estimate the phase sensitivity of atoms in non-inertial motions or in gravitational fields. The Unruh–DeWitt model is applicable to the investigation of the dynamics of a uniformly accelerated atom weakly coupled to a massless scalar vacuum field. When a measuring device is in the same relativistic motion as the atom, the dynamical behavior of quantum Fisher information as a function of Rindler proper time is obtained. It is found out that monotonic decrease in phase sensitivity is characteristic of dynamics of relativistic quantum estimation. The origin of the decay of quantum Fisher information is the thermal bath that the accelerated detector finds itself in due to the Unruh effect. To improve relativistic quantum metrology, we reasonably take into account two reflecting plane boundaries perpendicular to each other. The presence of the reflecting boundary can shield the detector from the thermal bath in some sense.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Frequent Subgraph Discovery in Large Attributed Streaming Graphs

The problem of finding frequent subgraphs in large dynamic graphs has so far only consid- ered a dynamic graph as being represented by a series of static snapshots taken at various points in time. This representation of a dynamic graph does not lend itself well to real time processing of real world graphs like social networks or internet traffic which consist of a stream of nodes and edges. In this paper we propose an algorithm that discovers the frequent subgraphs present in a graph represented by a stream of labeled nodes and edges. Our algorithm is efficient and consists of tunable parameters that can be tuned by the user to get interesting patterns from various kinds of graph data. In our model updates to the graph arrive in the form of batches which contain new nodes and edges. Our algorithm con- tinuously reports the frequent subgraphs that are estimated to be found in the entire graph as each batch arrives. We evaluate our system using 5 large dynamic graph datasets: the Hetrec 2011 challenge data, Twitter, DBLP and two synthetic. We evaluate our approach against two popular large graph miners, i.e., SUBDUE and GERM. Our experimental re- sults show that we can find the same frequent subgraphs as a non-incremental approach applied to snapshot graphs, and in less time.

Dynamic graph, Frequent subgraph mining, pattern d↗
DOE OSTI2018

Dynamic Model of Basic Oxygen Steelmaking Process Based on Multi-zone Reaction Kinetics: Model Derivation and Validation

A multi-zone kinetic model coupled with a dynamic slag generation model was developed for the simulation of hot metal and slag composition during the basic oxygen furnace (BOF) operation. The three reaction zones (i) jet impact zone, (ii) slag–bulk metal zone, (iii) slag–metal–gas emulsion zone were considered for the calculation of overall refining kinetics. In the rate equations, the transient rate parameters were mathematically described as a function of process variables. A micro and macroscopic rate calculation methodology (micro-kinetics and macro-kinetics) were developed to estimate the total refining contributed by the recirculating metal droplets through the slag–metal emulsion zone. The micro-kinetics involves developing the rate equation for individual droplets in the emulsion. The mathematical models for the size distribution of initial droplets, kinetics of simultaneous refining of elements, the residence time in the emulsion, and dynamic interfacial area change were established in the micro-kinetic model. In the macro-kinetics calculation, a droplet generation model was employed and the total amount of refining by emulsion was calculated by summing the refining from the entire population of returning droplets. A dynamic Fe{sub t}O generation model based on oxygen mass balance was developed and coupled with the multi-zone kinetic model. The effect of post-combustion on the evolution of slag and metal composition was investigated. The model was applied to a 200-ton top blowing converter and the simulated value of metal and slag was found to be in good agreement with the measured data. The post-combustion ratio was found to be an important factor in controlling Fe{sub t}O content in the slag and the kinetics of Mn and P in a BOF process.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Modeling the relative dynamics of DNA-coated colloids

Here, we construct a theoretical model for the dynamics of a microscale colloidal particle, modeled as an interval, moving horizontally on a DNA-coated surface, modelled as a line coated with springs that can stick to the interval. Averaging over the fast DNA dynamics leads to an evolution equation for the particle in isolation, which contains both friction and diffusion. The DNA-induced friction coefficient depends on the physical properties of the DNA, and substituting parameter values typical of a 1 μm colloid coated densely with weakly interacting DNA gives a coefficient about 100 times larger than the corresponding coefficient of hydrodynamic friction. We use a mean-field extension of the model to higher dimensions to estimate the friction tensor for a disc rotating and translating horizontally along a line. When the DNA strands are very stiff and short, the friction coefficient for the disc rolling approaches zero while the friction for the disc sliding remains large. Together, these results could have significant implications for the dynamics of DNA-coated colloids or other ligand-receptor systems, implying that DNA-induced friction between colloids can be stronger than hydrodynamic friction and should be incorporated into simulations, and that it depends nontrivially on the type of relative motion, possibly causing the particles to assemble into out-of-equilibrium metastable states governed by the pathways with the least friction.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Information content of spatially distributed ground-based measurements for hydrologic-parameter calibration in mixed rain-snow mountain headwaters

Parameters in hydrologic models used in mixed rain-snow regions are often uncertain to calibrate and overfitted on streamflow. To contribute addressing these challenges, we used an algorithm that assesses modeling performances through time (Dynamic Identifiability Analysis) to quantify the information content of spatially distributed ground-based measurements for identifying optimal parameter values in the Precipitation Runoff Modeling System (PRMS) model. Including spatially distributed ground-based measurements in Identifiability Analysis allowed us to unambiguously estimate more parameter values than only using streamflow (seven parameters instead of two out of a pool of thirty-three). Peaks in information gain were obtained when using dew-point temperature to identify precipitation phase-partitioning parameters. Multi-attribute identifiability analysis also yielded optimal parameter values that were temporally less variable than those estimated using streamflow alone. Overall, identifying parameter values using ground-based measurements improved the simulation of key drivers of the surface-water budget, such as air temperature and precipitation-phase partitioning. However, parameters simulating surface-to-subsurface mass fluxes like snow accumulation and melt or evapotranspiration were poorly identified by any attribute and so emerged as key sources of predictive uncertainty for this distributed-parameter hydrologic model. In conclusion, this work demonstrates the value of expanded ground-based measurements for identifying parameters in distributed-parameter hydrologic models and so diagnosing their conceptual uncertainty across the water budget.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Astrometric microlensing probes of the isolated neutron star population with Roman

Notoriously hard to detect and study, isolated neutron stars (NSs) might provide valuable answers to fundamental questions about stellar evolution and explosion physics. With the upcoming Roman Space Telescope, scheduled for launch in 2026, a new and powerful channel for their detection will become available: astrometric microlensing. We set out to create a realistic sample of simulated gravitational microlensing events as observed by Roman with the Galactic Bulge Time Domain Survey. We focus in particular on the population of NS lenses, which has until now been largely understudied. We used dedicated Galactic models tailored for application to microlensing by compact objects. In addition to populations of stars, white dwarfs, and black holes, we simulated four different NS populations with Maxwellian natal kick distributions: v = (150, 250, 350, 450) km/s. For each simulation, we applied projected Roman precision, cadence, and detectability criteria. We found that the parameter space log10 t E –log 10 θ E , which will be accessible to Roman observations, is efficient for the classification of stellar remnants. We found a feature in this space that is characteristic of NSs; using this feature, optimal samples of NS candidates can be constructed from Roman -like datasets. We describe the dependence of the observable parameter distributions on the assumed mean kick velocities. As the effects of natal kicks are very complex and mutually counteracting, we suggest that more detailed studies focused on the dynamics of NSs are needed in anticipation of Roman and future surveys. We estimate that Roman will observe approximately 11 000 microlensing events, including ~100 with NS lenses, whose photometric and astrometric signals are detectable; the event yield decreases by 38% when gap-filling low-cadence observations are not included. We make all simulated microlensing event datasets publicly available in preparation for Roman data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SU-E-J-61: Electrodynamics and Nano-Scale Fluid Dynamics in Protein Localization of Nuclear Pore Complexes

Purpose: To develop a simulation to catalyze a reevaluation of common assumptions about 3 dimensional diffusive processes and help cell biologists gain a more nuanced, intuitive understanding of the true physical hurdles of protein signaling cascades. Furthermore, to discuss the possibility of intracellular electrodynamics as a critical, unrecognized component of cellular biology and protein dynamics that is necessary for optimal information flow from the cell membrane to the nucleus. Methods: The Unity 3D gaming physics engine was used to build an accurate virtual scale model of the cytoplasm within a few hundred nanometers of the nuclear membrane. A cloud of simulated pERK proteins is controlled by the physics simulation, where diffusion is based on experimentally measured values and the electrodynamics are based on theoretical nano-fluid dynamics. The trajectories of pERK within the cytoplasm and through the 1250 nuclear pores on the nuclear surface is recorded and analyzed. Results: The simulation quickly demonstrates that pERKs moving solely by diffusion will rarely locate and come within capture distance of a nuclear pore. The addition of intracellular electrodynamics between charges on the nuclear pore complexes and on pERKs increases the number of successful translocations by allowing the electro-physical attractive effects to draw in pERKs from the cytoplasm. The effects of changes in intracellular shielding ion concentrations allowed for estimation of the “capture radius” under varying conditions. Conclusion: The simulation allows a shift in perspective that is paramount in attempting to communicate the scale and dynamics of intracellular protein cascade mechanics. This work has allowed researchers to more fully understand the parameters involved in intracellular electrodynamics, such as shielding anion concentration and protein charge. As these effects are still far below the spatial resolution of currently available measurement technology this simulation is invaluable to researchers to visualize and study current hypotheses concerning protein dynamics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Adaptive fuzzy dynamic surface control for the chaotic permanent magnet synchronous motor using Nussbaum gain

This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaos of PMSM and show the effectiveness and robustness of the proposed method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Readout models for BaFBr 0.85 I 0.15 :Eu image plates

The linearity of the photostimulated luminescence process makes repeated image-plate scanning a viable technique to extract more dynamic range. In order to obtain a response estimate, two semi-empirical models for the readout fading of an image plate are introduced; they relate the depth distribution of activated photostimulated luminescence centers within an image plate to the recorded signal. Model parameters are estimated from image-plate scan series with BAS-MS image plates and the Typhoon FLA 7000 scanner for the hard x-ray image-plate diagnostic over a collection of experiments providing x-ray energy spectra whose approximate shape is a double exponential.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

PROPERTIES OF THE MOLECULAR CORES OF LOW LUMINOSITY OBJECTS

We present a survey toward 16 low luminosity objects (LLOs with an internal luminosity, L{sub int}, lower than 0.2 L{sub ⊙}) with N{sub 2}H{sup +} (1–0), N{sub 2}H{sup +} (3–2), N{sub 2}D{sup +} (3–2), HCO{sup +} (3–2), and HCN (3–2) using the Arizona Radio Observatory Kitt Peak 12 m Telescope and Submillimeter Telescope. Our goal is to probe the nature of these faint protostars which are believed to be either very low mass or extremely young protostars. We find that the N{sub 2}D{sup +}/N{sub 2}H{sup +} column density ratios of LLOs are similar to those of typical starless cores and Class 0 objects. The N{sub 2}D{sup +}/N{sub 2}H{sup +} column density ratios are relatively high (>0.05) for LLOs with kinetic temperatures less than 10 K in our sample. The distribution of N{sub 2}H{sup +} (1–0) line widths spreads between that of starless cores and young Class 0 objects. If we use the line width as a dynamic evolutionary indicator, LLOs are likely young Class 0 protostellar sources. We further use the optically thick tracers, HCO{sup +} (3–2) and HCN (3–2), to probe the infall signatures of our targets. We derive the asymmetry parameters from both lines and estimate the infall velocities by fitting the HCO{sup +} (3–2) spectra with two-layer models. As a result, we identify eight infall candidates based on the infall velocities and seven candidates have infall signatures supported by asymmetry parameters from at least one of HCO{sup +} (3–2) and HCN (3–2)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Combined $\mathrm{APOGEE}$-$\mathrm{GALAH}$ stellar catalogues using the Cannon

APOGEE and GALAH are two high resolution multi-object spectroscopic surveys that provide fundamental stellar parameters and multiple elemental abundance estimates for about half a million stars in the Milky Way. Both surveys observe in different wavelength regimes and use different data reduction pipelines leading to significant offsets and trends in stellar parameters and abundances for the common stars observed in both surveys. Such systematic differences/offsets in stellar parameters and abundances make it difficult to effectively utilize them to investigate Galactic abundance trends in spite of the unique advantage provided by their complementary sky coverage and different Milky Way components they observe. Hence, we use the Cannon data-driven method selecting a training set of 4418 common stars observed by both surveys. This enables the construction of two catalogues, one with the APOGEE-scaled and the other with the GALAH-scaled stellar parameters. Using repeat observations in APOGEE and GALAH, we find high precision in metallicity (~0.02–0.4 dex) and alpha abundances (~0.02–0.03 dex) for spectra with good signal-to-noise ratio (SNR >; 80 for APOGEE and SNR > 40 for GALAH). We use open and globular clusters to validate our parameter estimates and find small scatter in metallicity (0.06 dex) and alpha abundances (0.03 dex) in APOGEE-scaled case. The final catalogues have been cross-matched with the Gaia EDR3 catalogue to enable their use to carry out detailed chemo-dynamic studies of the Milky Way from perspectives of APOGEE and GALAH.

79 ASTRONOMY AND ASTROPHYSICS↗