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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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DOE OSTI2021

Development and Implementation of Digital Image Correlation for Out-of-Cell Burst Testing

This report details the progress made towards utilizing in-situ methods to observe and quantify unirradiated Zircaloy-4 (Zr4) fuel cladding deformation during out-of-cell design basis accident conditions, specifically during loss-of-coolant accident (LOCA) burst testing in the Severe Accident Test Station at Oak Ridge National Laboratory. Digital image correlation (DIC) was implemented to calculate cladding strain during burst and infrared (IR) thermography was used to attempt a correlation of strain with temperature and to investigate thermal gradients. For both techniques, early experimentation revealed experimental modifications were necessary for implementation. For DIC, this manifested as shortened cladding lengths which could be centered in front of the viewing chamber bored through the IR furnace side, and for IR thermography this meant conducting burst tests in air without a reaction tube and the incorporation of a SiC shell to eliminate direct IR reflections from the tungsten lamps. In the following, the technical issues and subsequent origin of these modifications are discussed, laying the framework for a proof-of-concept DIC/IR characterization of a burst test in the final section.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Report Summarizing Progress in Digital Image Correlation Analysis of Burst Phenomenon

This report is an update on the progress made towards utilizing in-situ methods to observe and quantify Zry-4 deformation behavior during burst testing. A heavily modified burst test was developed that allows both digital image correlation and infrared thermography to be utilized during testing to quantify strain and axial thermal gradient data during burst. A variety of tests ranging from 6.2-15.9 MPa internal pressure and utilizing both constant and transient pressure conditions were conducted and presently reported on. The test modifications, which are detailed extensively in a previous report, are effectively found to have no discernible impact on burst temperatures when compared to historical Zircaloy burst data. To support future modeling studies, the IR thermography data was used to approximate the thermal gradient down the axial length at burst for all the claddings. Then, DIC is first correlated to thermocouple temperature for a 10.3 MPa Transient pressure test, and then DIC correlated to IR thermal gradient data down the axial length of a 8.2 MPa Transient pressure test at several points.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Genomes to Structure and Function Workshop Report 2022

The goal of the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Program is to achieve a predictive understanding of complex biological, earth, and environmental systems with the aim of advancing the nation’s energy and infrastructure security. (https://www.energy.gov/science/ ber/biological-and-environmental-research). To pursue this goal, collaborations among experts in diverse research areas that lead to multidisciplinary projects are indispensable. The roles of DOE’s User Facilities, which offer unique and powerful resources for such research projects, are evolving, and expectations for the facilities are increasing. To respond to Users’ needs, the Joint Genome Institute (JGI) and Environmental Molecular Sciences Laboratory (EMSL) initiated the Facilities Integrating Collaborations for User Science (FICUS) program in 2014. This collaboration has grown into a popular and successful program, advancing more than 100 multidisciplinary projects to date. Similarly, the new interFacility collaborations among the JGI, EMSL, and User resources for BER structural biology and imaging at the Basic Energy Science (BES) Program’s synchrotron and neutron facilities are becoming essential for cutting-edge transdisciplinary science. To further explore the need for the BER research community to combine genomic, functional, and structural approaches to advance their research, an organizing committee was formed to develop and jointly host a 3-part workshop. The committee’s members represented seven DOE National Laboratory User Facilities (Appendix 1 lists the members). The “Genomes to Structure and Function” virtual workshop (see Appendices 2–5) was composed of three sessions. The first session, titled “Molecular Structures” (October 27– 28, 2021), highlighted diverse integrative experimental and computational approaches correlating structural data with sequencing and functional information, as well as predicting protein structures to model complex biological systems. The second session, “Intracellular Organization, and Material Synthesis and Decomposition” (December 15–16, 2021), covered imaging methods for observing, quantifying, and manipulating biosystems. The third session, “Imaging the Rhizosphere and Cellular Organization” (January 26–27, 2022) emphasized advanced and non-invasive imaging techniques applied to plant root-microbe-soil interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Reducing the Risk of Airborne Contamination through Intelligent Container Surveillance

DOE Manual 441.1-1 provides a set of performance criteria that nuclear material storage containers must achieve to provide protection to the worker, public, and environment. At Los Alamos National Laboratory, the SAVY-4000 is the container of choice for nuclear material storage, meeting all Manual requirements. At the outset, polymer components of the SAVY 4000 were considered to be life-limiting components due to their performance degradation resulting from radiation exposure. However, recent annual surveillance results revealed another life-limiting phenomenon for the container: a deterioration of the package integrity through corrosion of the stainless steel components, primarily the body. Container surveillance remains the choice method of observing, measuring, and tracking container health in service.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Hydrodynamic Coupling to a Homogenized Radiation Transport Method based on Young Measures

Resolving radiation transport fields subject to opacity profiles with strong, oscillatory line structure while potentially falling under intermediate optical depth conditions presents a numerical challenge in radiation transport modeling. The Young measure-based homogenization technique formulated by Haut et al. (2017) was investigated as a candidate method for resolving radiation fields under such conditions more accurately. The method was compared against frequently-utilized mean opacity methods as the Rosseland and Planck formulations. In this work, all methods were tested through radiation slab calculations separately comprised of aluminum, copper, and krypton, each for different thermodynamic conditions. Following these offline radiation slab calculations, demonstrations shifted towards the SCEPTRE radiation transport code and, subsequently, the multiphysics ALEGRA code for approximately-coupled radiation-material simulations. Throughout all the simulations shown in this study, for a fixed computational cost, the homogenized method was observed to be more accurate than any of the solutions determined through traditional mean opacity approaches.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗
DOE OSTI2020

The Hubble Space Telescope's Near-UV and Optical Transmission Spectrum of Earth as an Exoplanet

We observed the 2019 January total lunar eclipse with the Hubble Space Telescope’s STIS spectrograph to obtain the first near-UV (1700–3200 Å) observation of Earth as a transiting exoplanet. The observatories and instruments that will be able to perform transmission spectroscopy of exo-Earths are beginning to be planned, and characterizing the transmission spectrum of Earth is vital to ensuring that key spectral features (e.g., ozone, or O{sub 3}) are appropriately captured in mission concept studies. O{sub 3} is photochemically produced from O{sub 2}, a product of the dominant metabolism on Earth today, and it will be sought in future observations as critical evidence for life on exoplanets. Ground-based observations of lunar eclipses have provided the Earth’s transmission spectrum at optical and near-IR wavelengths, but the strongest O{sub 3} signatures are in the near-UV. We describe the observations and methods used to extract a transmission spectrum from Hubble lunar eclipse spectra, and identify spectral features of O{sub 3} and Rayleigh scattering in the 3000–5500 Å region in Earth’s transmission spectrum by comparing to Earth models that include refraction effects in the terrestrial atmosphere during a lunar eclipse. Our near-UV spectra are featureless, a consequence of missing the narrow time span during the eclipse when near-UV sunlight is not completely attenuated through Earth’s atmosphere due to extremely strong O{sub 3} absorption and when sunlight is transmitted to the lunar surface at altitudes where it passes through the O{sub 3} layer rather than above it.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Self-supervised Representation Learning for Astronomical Images

Sky surveys are the largest data generators in astronomy, making automated tools for extracting meaningful scientific information an absolute necessity. We show that, without the need for labels, self-supervised learning recovers representations of sky survey images that are semantically useful for a variety of scientific tasks. These representations can be directly used as features, or fine-tuned, to outperform supervised methods trained only on labeled data. We apply a contrastive learning framework on multiband galaxy photometry from the Sloan Digital Sky Survey (SDSS), to learn image representations. We then use them for galaxy morphology classification and fine-tune them for photometric redshift estimation, using labels from the Galaxy Zoo 2 data set and SDSS spectroscopy. In both downstream tasks, using the same learned representations, we outperform the supervised state-of-the-art results, and we show that our approach can achieve the accuracy of supervised models while using 2-4 times fewer labels for training. The codes, trained models, and data can be found at https://portal.nersc.gov/project/dasrepo/self-supervised-learning-sdss.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Using an Absolute Cavity Pyrgeometer to Calibrate Pyrgeometers Outdoors with Respect to the International System of Units

Accurate measurement of the atmospheric longwave irradiance is important for renewable energy and atmospheric science applications. Pyrgeometers are deployed outdoors all over the world to measure the atmospheric longwave irradiance and presently are calibrated with traceability to the interim standards for atmospheric longwave radiation measurement, the standards are based on four pyrgeometers and their average irradiance is the World InfraRed Standard Group (WISG) which is developed and maintained by The Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC). Since 2013 the InfraRed Integrating Sphere (IRIS) developed by PMOD/WRC and the Absolute Cavity Pyrgeometer (ACP) developed by the National Renewable Energy Laboratory (NREL) have been compared outdoors six times at different locations and the difference between the measured atmospheric longwave irradiance by ACP and IRIS was less than 2 W/m2 with traceability to the International System of Units (SI). During the six comparisons the irradiance measured by the interim WISG was 5 W/m2 lower than the irradiance measured by the average irradiance measured by the ACP and IRIS [1]. Based on this discrepancy, the World Meteorological Organization's Commission for Instruments and Methods of Observation (CIMO) recommended that the interim WISG should be adjusted to be traceable to SI units [2]. In anticipation of CIMO's expert team agreement on establishing the world reference using the average irradiance measured by ACP and IRIS in this article we describe a procedure to calibrate pyrgeometers with traceability to SI. One Absolute Cavity Pyrgeometer (ACP95F3) was used to calibrate four pyrgeometers traceable to SI units. Three Eppley PIRs and one Kipp&Zonen CG4 were originally calibrated with traceability to the interim WISG. Using the described procedure below, the responsivity of each pyrgeometer was then adjusted to match the irradiance measured by ACP. Outdoor data was collected during one clear sky nights monitored by the output thermopile voltage of ACP95F3. The irradiance measured by the PIRs was calculated using NREL equation and the CG4 using NREL equation and PMOD/WRC equation. Using the NREL equation, the calculated uncertainty (U_95) of the PIRs varied from 2.43 W/m2 to 2.67 W/m2, and for the CG4 using the NREL equation U_95 equals 1.97 W/m2, and using the PMOD equation U_95 equals 2.88 W/m2 with respect to SI.

International System of Units↗
DOE OSTI2023

Patterns and rates of soil movement and shallow failures across several small watersheds on the Seward Peninsula, Alaska

Abstract. Thawing permafrost can alter topography, ecosystems, and sediment and carbon fluxes, but predicting landscape evolution of permafrost-influenced watersheds in response to warming and/or hydrological changes remains an unsolved challenge. Sediment flux and slope instability in sloping saturated soils have been commonly predicted from topographic metrics (e.g., slope, drainage area). In addition to topographic factors, cohesion imparted by soil and vegetation and melting ground ice may also control spatial trends in slope stability, but the distribution of ground ice is poorly constrained and hard to predict. To address whether slope stability and surface displacements follow topographic-based predictions, we document recent drivers of permafrost sediment flux present on a landscape in western Alaska that include creep, solifluction, gullying, and catastrophic hillslope failures ranging in size from a few meters to tens of meters, and we find evidence of rapid and substantial landscape change on an annual timescale. We quantify the timing and rate of surface movements using a multi-pronged, multi-scalar dataset including aerial surveys, interannual GPS surveys, synthetic aperture radar interferometry (InSAR), and climate data. Despite clear visual evidence of downslope soil transport of solifluction lobes, we find that the interannual downslope surface displacement of these features does not outpace downslope displacement of soil in locations where lobes are absent (downslope movement means: 7 cm yr−1 for lobes over 2 years vs. 10 cm yr−1 in landscape positions without lobes over 1 year). Annual displacements do not appear related to slope, drainage area, or modeled total solar radiation but are likely related to soil thickness, and volumetric sediment fluxes are high compared to temperate landscapes of comparable bedrock lithology. Time series of InSAR displacements show accelerated movement in late summer, associated with intense rainfall and/or deep thaw. While mapped slope failures do cluster at slope–area thresholds, a simple slope stability model driven with hydraulic conductivities representative of throughflow in mineral and organic soil drastically overpredicts the occurrence of slope failures. This mismatch implies permafrost hillslopes have unaccounted-for cohesion and/or throughflow pathways, perhaps modulated by vegetation, which stabilize slopes against high rainfall. Our results highlight the breadth and complexity of soil transport processes in Arctic landscapes and demonstrate the utility of using a range of synergistic data collection methods to observe multiple scales of landscape change, which can aid in predicting periglacial landscape evolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Vertical column dual-comb spectroscopy to a TBS

Open-path dual-frequency-comb spectroscopy (DCS) is a broadband, high spectral resolution, and high precision method for measuring gas concentrations over kilometer-scale paths. It has been used for detection and quantification of emissions of pollutants, hazardous gasses, and greenhouse gasses (GHGs). DCS has been shown to measure trace-gas mixing ratios with 0.14%-0.4% agreement between instruments. To achieve high signal-to-noise ratios (SNRs) with DCS, comb light is targeted onto a retroreflector at the end of the measurement path, which returns the signal to a detector co-located with the launch signal. Installing the retroreflector on a mobile platform such as a balloon or unmanned aerial vehicle (UAV) extends the capabilities of DCS by enabling variable path lengths, greater mobility, and access to higher altitudes. Mobile-target DCS has many uses in plume and leak detection, emissions modeling, and planetary boundary layer (PBL) studies. It is a promising method for observing vertical distributions of GHGs and mixing processes in the PBL, which are difficult to measure but important for pollution and climate monitoring as well as for understanding transport of gasses through the atmosphere. Tethered balloons are an intriguing platform because they enable longer flight durations and higher altitudes than easily obtainable with a UAV and thus allow for column measurements up to and above the PBL. New measurements completed in October/November 2024 reach the highest altitudes above ground level yet achieved by mobile-target DCS. For these measurements, the retroreflector was mounted on a 7 m diameter tethered helium balloon. An actively tracking gimbal on the ground holds the DCS launch telescope and keeps the 5 cm beam pointed onto the retroreflector while the balloon is lifted, lowered, and moved by wind and turbulence.

atmosphere↗
DOE OSTI2023

Using an Absolute Cavity Pyrgeometer to Calibrate Pyrgeometers Outdoors with Respect to the International System of Units

Accurate measurement of the atmospheric longwave irradiance is important for renewable energy and atmospheric science applications. Pyrgeometers are deployed outdoors all over the world to measure the atmospheric longwave irradiance and presently are calibrated with traceability to the interim standards for atmospheric longwave radiation measurement, the standards are based on four pyrgeometers and their average irradiance is the World InfraRed Standard Group (WISG) which is developed and maintained by The Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC). Since 2013 the InfraRed Integrating Sphere (IRIS) developed by PMOD/WRC and the Absolute Cavity Pyrgeometer (ACP) developed by the National Renewable Energy Laboratory (NREL) have been compared outdoors six times at different locations and the difference between the measured atmospheric longwave irradiance by ACP and IRIS was less than 2 w/m2 with traceability to the International System of Units (SI). During the six comparisons the irradiance measured by the interim WISG was 5 w/m2 lower than the irradiance measured by the average irradiance measured by the ACP and IRIS [1]. Based on this discrepancy, the World Meteorological Organization's Commission for Instruments and Methods of Observation (CIMO) recommended that the interim WISG should be adjusted to be traceable to SI units [2]. In anticipation of CIMO's expert team agreement on establishing the world reference using the average irradiance measured by ACP and IRIS in this article we describe a procedure to calibrate pyrgeometers with traceability to SI. One Absolute Cavity Pyrgeometer (ACP95F3) was used to calibrate four pyrgeometers traceable to SI units. Three Eppley PIRs and one Kipp&Zonen CG4 were originally calibrated with traceability to the interim WISG. Using the described procedure below, the responsivity of each pyrgeometer was then adjusted to match the irradiance measured by ACP. Outdoor data was collected during one clear sky night monitored by the output thermopile voltage of ACP95F3. The irradiance measured by the PIRs and CG4 was calculated using NREL equation. The calculated uncertainty (U95) of the PIRs varied from 2.43 w/m2 to 2.67 w/m2 , and for the CG4 equals 1.97 w/m2 with respect to SI.

absolute cavity pyrgeometer↗
DOE OSTI2021

Sequential Bayesian inference of transition rates in the hidden Markov model for multi-state system degradation

The more easily available system performance data and advances in data analytics have provided us with opportunities to optimize maintenance programs for engineered systems, for example nuclear power plants. One key task in maintenance optimization is to obtain an accurate model for system degradation. Here, in this research, we propose a Bayesian method to address this problem. Noting that systems usually exhibit multiple states and that the actual state of a system usually is not directly observable, in the method we first model the system degradation process and the observation process based on a hidden Markov model. Then we develop a sequential Bayesian inference algorithm based on importance sampling and the forward algorithm to infer the posterior distributions of the transition rates in the hidden Markov model based on available observations. The proposed Bayesian method allows us to take advantage of evidence from multiple sources, and also allows us to perform Bayesian inference sequentially, without the need to use the entire history of observations every time new observations are collected. We demonstrate the proposed method using both synthetic data for a nuclear power plant feedwater pump and realistic data for a nuclear power plant chemistry analytical device.

42 ENGINEERING↗
DOE OSTI2022

The Davis–Chandrasekhar–Fermi method revisited

ABSTRACT Despite the rich observational results on interstellar magnetic fields in star-forming regions, it is still unclear how dynamically significant the magnetic fields are at varying physical scales, because direct measurement of the field strength is observationally difficult. The Davis–Chandrasekhar–Fermi (DCF) method has been the most commonly used method to estimate the magnetic field strength from polarization data. It is based on the assumption that gas turbulent motion is the driving source of field distortion via linear Alfvén waves. In this work, using MHD simulations of star-forming clouds, we test the validity of the assumption underlying the DCF method by examining its accuracy in the real 3D space. Our results suggest that the DCF relation between turbulent kinetic energy and magnetic energy fluctuation should be treated as a statistical result instead of a local property. We then develop and investigate several modifications to the original DCF method using synthetic observations, and propose new recipes to improve the accuracy of DCF-derived magnetic field strength. We further note that the biggest uncertainty in the DCF analysis may come from the linewidth measurement instead of the polarization observation, especially since the line-of-sight gas velocity can be used to estimate the gas volume density, another critical parameter in the DCF method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Robust Matrix Completion State Estimation in Distribution Systems

Due to the insufficient measurements in the distribution system state estimation (DSSE), full observability and redundant measurements are difficult to achieve without using the pseudo measurements. The matrix completion state estimation (MCSE) combines the matrix completion and power system model to estimate voltage by exploring the low-rank characteristics of the matrix. This paper proposes a robust matrix completion state estimation (RMCSE) to estimate the voltage in a distribution system under a low-observability condition. Tradition state estimation weighted least squares (WLS) method requires full observability to calculate the states and needs redundant measurements to proceed a bad data detection. The proposed method improves the robustness of the MCSE to bad data by minimizing the rank of the matrix and measurements residual with different weights. It can estimate the system state in a low-observability system and has robust estimates without the bad data detection process in the face of multiple bad data. The method is numerically evaluated on the IEEE 33-node radial distribution system. The estimation performance and robustness of RMCSE are compared with the WLS with the largest normalized residual bad data identification (WLS-LNR), and the MCSE.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

In-situ and in-operando analysis of voltage losses using sense wires for proton exchange membrane water electrolyzers

Proton exchange membrane water electrolyzer development requires understanding processes at the materials and interface levels to reach the required performance and lifetime targets for increasing market penetration. To achieve the required progress, it is critical to develop advanced in-situ diagnostics that allow observation of the changes that come with the reduction of catalyst loading combined with long-term intermittent operation. This work presents an internal voltage sensing method that enables observing internal voltage drops in an operating electrolyzer cell. It allows the total cell resistance to be separated into anode, CCM, and cathode resistance. The method is demonstrated by operating cells with different anode porous transport layers (PTLs). The changing properties of the PTLs result in significant variations of the resistances. Enhancing the PTL properties with a protective coating reduces the anode resistance significantly. In addition to these observations, the method enables a real-time monitoring of resistance related values that impact performance in water electrolyzers. Long-term experiments with the method allow us to gain insights into processes that occur during operation such as conditioning or degradation. The internal voltage sensing method presented in this study is a novel technique for diagnosing, analyzing, and optimizing water electrolyzers and other energy conversion devices.

42 ENGINEERING↗
DOE OSTI2022

The future of Earth system prediction: Advances in model-data fusion

Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation), and some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations. We highlight how future developments can enable advanced heterogeneous observation networks and models to improve predictions of the Earth system (including atmosphere, land surface, oceans, cryosphere, and chemistry) across scales from weather to climate. As the community pushes to develop the next generation of models and data systems, there is a need to take a more holistic, integrated, and coordinated approach to models, observations, and their uncertainties to maximize the benefit for Earth system prediction and impacts on society.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

An iterative method to deblend AGN-Host contributions for Integral Field spectroscopic observations

ABSTRACT We present a new iterative deblending method to separate the host galaxy (HG) and their Active Galactic Nuclei (AGNs) emission with the use of Integral Field spectroscopic (IFS) data. The method decomposes the resolved HG emission from the unresolved AGN emission by modelling the two-dimensional surface brightness (SB) profile of the point-spread function (PSF) and the two-dimensional SB HG continuum simultaneously per each monochromatic slide. Our method does not require any prior information about the observed SB profile or a detailed fitting of the PSF, making it ideal for the automatic analysis of large galaxy samples. In this work, we test the quality of our method, its advantages, and its disadvantages. We test our method by using a set of IFS mock data cubes to quantify the reliability of our deblending process and further compare our method with the qdblend3d analysis tool. Furthermore, we applied our method to three data cubes selected from the MaNGA survey according to the dominance of either its HG or its AGN. We show that our deblending method is capable of disengaging the bright, non-resolved AGN emission from the HG continuum and its narrow emission lines. However, the decoupling depends on how well the IFS spatially resolves the PSF, and on the relative flux intensity of the HG-AGN. Therefore, the method is ideal for disentangling the bright-flux contribution from AGN-dominated spectra.

Ibarra-Medel, H. (ORCID:0000000297906313)↗