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DOE OSTI2023

Constraining AGN Torus Sizes with Optical and Mid-infrared Ensemble Structure Functions

We propose a new method to constrain the size of the dusty torus in broad-line active galactic nuclei (AGNs) using optical and mid-infrared (MIR) ensemble structure functions (SFs). Because of the geometric dilution of the torus, the MIR response to optical continuum variations has suppressed variability with respect to the optical that depends on the geometry (e.g., size, orientation, opening angle) of the torus. More extended tori have steeper MIR SFs with respect to the optical SFs. We demonstrate the feasibility of this SF approach using simulated AGN light curves and a geometric torus model. While it is difficult to use SFs to constrain the orientation and opening angle due to the insensitivity of the SF on these parameters, the size of the torus can be well determined. Applying this method to the ensemble SFs measured for 587 SDSS quasars, we measure a torus R–L relation of $\mathrm{log}\,{R}_{\mathrm{eff}}(\mathrm{pc})={0.51}_{-0.04}^{+0.04}\times \mathrm{log}({{L}}_{\mathrm{bol}}/{10}^{46}\,\mathrm{erg}\ {{\rm{s}}}^{-1})-{0.38}_{-0.01}^{+0.01}$ in the WISE W1 band and sizes ~1.4 times larger in the W2 band, which are in good agreement with dust reverberation mapping measurements. Compared with the reverberation mapping technique, the SF method is much less demanding in data quality and can be applied to any optical+MIR light curves for which a lag measurement may not be possible, as long as the variability process and torus structure are stationary. While this SF method does not extract all information contained in the light curves (i.e., the transfer function), it provides an intuitive interpretation for the observed trends of AGN MIR SFs compared with optical SFs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The Progenitors of Superluminous Type Ia Supernovae

Abstract Recent observations of type Ia supernovae (SNe Ia) have discovered a subclass of “super-Chandrasekhar” SNe Ia (SC SNe Ia) whose high luminosities and low ejecta velocities suggest that they originate from the explosions of white dwarfs (WDs) with masses that exceed the Chandrasekhar mass limit. Different models have been proposed to explain the progenitors of these explosions, including a “magnetized WD” model and a “WD merger” model. To test the robustness of these models, we conduct a 1D numerical parameter survey of WD explosions using these models as initial conditions. We follow the explosions using the hydrodynamics code Castro and then use the radiation transport code SuperNu to create light curves and spectra for the models. We find that while both classes of models fall within the range of SC SNe Ia observations on the light-curve width–luminosity relation, only the WD merger models reproduce the observed low ejecta velocities. The light curves of our merger models are more similar photometrically to observations than our magnetized models. Given this, we discuss possible explanations for the brightest SC SNe Ia observations that cannot be reproduced with our WD merger models. This study provides the basis for future SC SNe Ia observations and higher-dimensional numerical models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties

Quasars are bright and unobscured active galactic nuclei (AGN) thought to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The temporal variability of a quasar’s brightness contains valuable information about its physical properties. The UV/optical variability is thought to be a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). Upcoming wide-field telescopes such as the Rubin Observatory Legacy Survey of Space and Time (LSST) are expected to observe tens of millions of AGN in multiple filters over a ten year period, so there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are machine learning models well suited for modeling quasar variability, as they can explicitly capture the underlying stochastic dynamics. In this work, we adapt latent SDEs to jointly reconstruct multivariate quasar light curves and infer their physical properties such as the black hole mass, inclination angle, and temperature slope. Our model is trained on realistic simulations of LSST ten year quasar light curves, and we demonstrate its ability to reconstruct quasar light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multioutput Gaussian process regression baseline. Our method has the potential to provide a deeper understanding of the physical properties of quasars and is applicable to a wide range of other multivariate time series with missing data and irregular sampling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Dramatic Rebrightening of the Type-changing Stripped-envelope Supernova SN 2023aew

Abstract Multipeaked supernovae with precursors, dramatic light-curve rebrightenings, and spectral transformation are rare, but are being discovered in increasing numbers by modern night-sky transient surveys like the Zwicky Transient Facility. Here, we present the observations and analysis of SN 2023aew, which showed a dramatic increase in brightness following an initial luminous (−17.4 mag) and long (∼100 days) unusual first peak (possibly precursor). SN 2023aew was classified as a Type IIb supernova during the first peak but changed its type to resemble a stripped-envelope supernova (SESN) after the marked rebrightening. We present comparisons of SN 2023aew’s spectral evolution with SESN subtypes and argue that it is similar to SNe Ibc during its main peak. P-Cygni Balmer lines are present during the first peak, but vanish during the second peak’s photospheric phase, before H α resurfaces again during the nebular phase. The nebular lines ([O i ], [Ca ii ], Mg i ], H α ) exhibit a double-peaked structure that hints toward a clumpy or nonspherical ejecta. We analyze the second peak in the light curve of SN 2023aew and find it to be broader than that of normal SESNe as well as requiring a very high 56 Ni mass to power the peak luminosity. We discuss the possible origins of SN 2023aew including an eruption scenario where a part of the envelope is ejected during the first peak and also powers the second peak of the light curve through interaction of the SN with the circumstellar medium.

Sharma, Yashvi (ORCID:0000000345311745)↗
DOE OSTI2025

On Finding Black Holes in Photometric Microlensing Surveys

There are expected to be millions of isolated black holes in the galaxy resulting from the deaths of massive stars. Measuring the abundance and properties of this remnant population would shed light on the end stages of stellar evolution and the evolution paths of black hole systems. Detecting isolated black holes is currently only possible via gravitational microlensing, which has so far yielded one definitive detection. The difficulty in finding microlensing black holes lies in having to choose a small subset of events, based on characteristics of their light curves, to allocate expensive and scarce follow-up resources to confirm the identity of the lens. Current methods either rely on simple cuts in parameter space without using the full distribution information or are only effective on small subsets of events. In this paper, we present a new lens classification method. The classifier takes in posterior constraints on light-curve parameters and combines them with a Galactic simulation to estimate the lens class probability. This method is flexible and can be used with any set of microlensing light-curve parameters, making it applicable to large samples of events. We make this classification framework available via the popclass Python package. We apply the classifier to ~10,000 microlensing events from the Optical Gravitational Lensing Experiment survey and find 23 high-probability black hole candidates. Our classifier also suggests that the only known isolated black hole is an observational outlier, according to current Galactic models, and the allocation of astrometric follow-up on this event was a high-risk strategy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Union through UNITY: Cosmology with 2000 SNe Using a Unified Bayesian Framework

Type Ia supernovae (SNe Ia) were instrumental in establishing the acceleration of the Universe’s expansion. By virtue of their combination of distance reach, precision, and prevalence, they continue to provide key cosmological constraints, complementing other cosmological probes. Individual SN surveys cover only over about a factor of 2 in redshift, so compilations of multiple SN data sets are strongly beneficial. We assemble an up-to-date “Union” compilation of 2087 cosmologically useful SNe Ia from 24 data sets (“Union3”). We take care to put all SNe on the same distance scale and update the light-curve fitting with SALT3 to use the full rest-frame optical. Over the next few years, the number of cosmologically useful SNe Ia will increase by more than a factor of 10, and keeping systematic uncertainties subdominant will be more challenging than ever. We discuss the importance of treating outliers, selection effects, light-curve shape/color populations/standardization relations, unexplained dispersion, and heterogeneous observations simultaneously. We present an updated Bayesian framework, called UNITY1.5 (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to model selection effects, standardization, and systematic uncertainties compared to earlier analyses. As an analysis byproduct, we also recover the posterior of the SN-only peculiar-velocity field, although we do not interpret it in this work. We compute updated cosmological constraints with Union3 and UNITY1.5, finding weak 1.7σ–2.6σ tension with flat cold dark matter and possible evidence for thawing dark energy (w0 > − 1, wa < 0). We release our SN distances, light-curve fits, and UNITY1.5 framework to the community.

Rubin, David↗
DOE OSTI2025

Analysis of Two Models for the Angular Structure of the Outflows Producing the Swift/XRT “Larger-angle Emission” of Gamma-Ray Bursts

The quasi-instantaneous emission from a relativistic surface endowed with a Lorentz factor that decreases away from the outflow symmetry axis can naturally explain the three phases observed by Swift X-Ray Telescope (XRT) in gamma-ray bursts (GRBs) and their afterglows (GRB tail, afterglow plateau, and postplateau) based only on the angular change of the relativistic Doppler boost across the outflow surface. We develop further the analytical formalism of the “larger-angle emission” model for the case of “n-exponential” outflows (where the Lorentz factor Γ dependence of the angular location θ is Γ ~ exp{-(θ/θ c ) n }), and compare its ability to account for the X-ray emission of XRT afterglows relative to that of “power-law” outflows (Γ ∼ θ −g ). Power-law outflows yield longer afterglow plateaus, followed by slower postplateau flux decays than n-exponential outflows, features which may be used in identifying which type of angular structure is at work in a given afterglow. Identifying the Γ(θ) angular structure that accommodates XRT light curves is slightly complicated by the fact that the afterglow X-ray light curve is also determined by how two characteristics of the comoving-frame emission spectrum (peak energy $E'_p$ and peak intensity $i'_p$) change with the angular location or, equivalently, with the Lorentz factor. Here, we assume power-law Γ dependences of those spectral characteristics and find that, unlike power-law outflows, n-exponential outflows cannot account for plateaus with a temporal dynamical range larger than 100 (2 dex in logarithmic space). To capture all the information contained in XRT afterglow measurements (0.3–10 keV unabsorbed flux and effective spectral slope), we calculate 0.3 and 10 keV light curves using a broken-power-law emission spectrum of peak energy and low- and high-energy slopes that are derived from the effective slope measured by XRT. This economical peak energy determination is found to be consistent with the results of more expensive spectral fits. The angular distributions of the Lorentz factor, comoving frame peak energy, and peak intensity (Γ(θ), $E'_p$(θ), $i'_p$(θ)) constrain the (yet-to-be determined) convolution of various features of the production of relativistic jets by solar-mass black holes and of their propagation through the progenitor/circumburst medium, while the $E'_p$(Γ) and $i'_p$(Γ) dependences may constrain the GRB dissipation mechanism and the GRB emission process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Inferring Type II-P Supernova Progenitor Masses from Plateau Luminosities

Abstract Connecting observations of core-collapse supernova explosions to the properties of their massive star progenitors is a long-sought, and challenging, goal of supernova science. Recently, Barker et al. presented bolometric light curves for a landscape of progenitors from spherically symmetric neutrino-driven core-collapse supernova (CCSN) simulations using an effective model. They find a tight relationship between the plateau luminosity of the Type II-P CCSN light curve and the terminal iron-core mass of the progenitor. Remarkably, this allows us to constrain progenitor properties with photometry alone. We analyze a large observational sample of Type II-P CCSN light curves and estimate a distribution of iron-core masses using the relationship of Barker et al. The inferred distribution matches extremely well with the distribution of iron-core masses from stellar evolutionary models and namely, contains high-mass iron cores that suggest contributions from very massive progenitors in the observational data. We use this distribution of iron-core masses to infer minimum and maximum masses of progenitors in the observational data. Using Bayesian inference methods to locate optimal initial mass function parameters, we find M min = 9.8 − 0.27 + 0.37 and M max = 24.0 − 1.9 + 3.9 solar masses for the observational data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Synchronous Rotation in the (136199) Eris–Dysnomia System

We combine photometry of Eris from a 6 month campaign on the Palomar 60 inch telescope in 2015, a 1 month Hubble Space Telescope WFC3 campaign in 2018, and Dark Energy Survey data spanning 2013–2018 to determine a light curve of definitive period 15.771 ± 0.008 days (1σ formal uncertainties), with nearly sinusoidal shape and peak-to-peak flux variation of 3%. This is consistent at part-per-thousand precision with the P = 15.785 90 ± 0.00005 day sidereal period of Dysnomia's orbit around Eris, strengthening the recent detection of synchronous rotation of Eris by Szakáts et al. with independent data. Photometry from Gaia are consistent with the same light curve. We detect a slope of 0.05 ± 0.01 mag per degree of Eris's brightness with respect to illumination phase averaged across g, V, and r bands, intermediate between Pluto's and Charon's values. Variations of 0.3 mag are detected in Dysnomia's brightness, plausibly consistent with a double-peaked light curve at the synchronous period. The synchronous rotation of Eris is consistent with simple tidal models initiated with a giant-impact origin of the binary, but is difficult to reconcile with gravitational capture of Dysnomia by Eris. The high albedo contrast between Eris and Dysnomia remains unexplained in the giant-impact scenario.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Inferred inflow forecast horizons guiding reservoir release decisions across the United States

Abstract. Medium- to long-range forecasts often guide reservoir release decisions to support water management objectives, including mitigating flood and drought risks. While there is a burgeoning field of science targeted at improving forecast products and associated decision support models, data describing how and when forecasts are applied in practice remain undeveloped. This lack of knowledge may prevent hydrological modelers from developing accurate reservoir release schemes for large-scale, distributed hydrology models that are increasingly used to assess the vulnerabilities of large regions to hydrological stress. We address this issue by estimating seasonally varying, regulated inflow forecast horizons used in the operations of more than 300 dams throughout the conterminous United States (CONUS). For each dam, we take actual forward observed inflows (perfect foresight) as a proxy for forecasted flows available to the operator and then identify for each week of the year the forward horizon that best explains the release decisions taken. Resulting “horizon curves” specify for each dam the inferred inflow forecast horizon as a function of the week of the water year. These curves are analyzed for strength of evidence for contribution of medium- to long-range forecasts in decision making. We use random forest classification to estimate that approximately 80 % of large dams and reservoirs in the US (1553±50 out of 1927 dams with at least 10 Mm3 storage capacity) adopt medium- to long-range inflow forecasts to inform release decisions during at least part of the water year. Long-range forecast horizons (more than 6 weeks ahead) are detected in the operations of reservoirs located in high-elevation regions of the western US, where snowpack information likely guides the release. A simulation exercise conducted on four key western US reservoirs indicates that forecast-informed models of reservoir operations may outperform models that neglect the horizon curve – including during flood and drought conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrated GW Farm ABM

This Data Repository includes data used for the integrated groundwater- farm ABM model, raw model output from scenario ensemble, and processed outputs that isolate the groundwater storage depletion outcomes for the 35,000 farm cells. Model Inputs: Farm ABM Inputs: This folder contains the input data used by the integrated groundwater - farm ABM modelling script (Python file) used for the high performance computing (HPC) experiments. The sub-folder "data inputs" contains all of the farm attribute data, while the three files in the folder have the hydrogeological data lookup table (NLDAS Cost Curve Attributes.csv), a lookup table (Theis well function table.csv) for the groundwater cost curve function, and the farm indexes and corresponding NLDAS ids for all of the cells run in this experiment (nldas farms subset final.csv). NLDAS Cost curve hydrogeological data: Hydrogeological data aggregated to 1/8 degree resolution and aligned with the NLDAS grid. Parameters include: water depth below ground surface [meters], subsurface porosity [unitless], aquifer depth from ground surface to aquifer bottom [meters], annual average recharge (USGS: mm, Doll: meters), and three different hydraulic conductivity (K) values (meters/day). The three K values represent the mean value from Gleeson et al. (2018), one standard deviation above the mean from Gleeson et al. (2018), and the de Graaf et al. 2020 modifications to certain lithologies. Additional information about these datasets and their processing are documented in the supplement to Yoon et al. 2025 (in review). Output: Raw outputs: This folder contains a .zip file that has model outputs for the entire scenario ensemble. There is one csv for each farm id, using the format "farm farmid cases.csv". The relationship between the farm id and NLDAS id is defined by the "nldas farms subset final.csv" located in the Farm ABM Inputs folder. Each csv has 625 rows, corresponding to 625 combinations of different scenario parameter values. Each row (scenario) represents the outcome of a 100 year simulation. Columns define scenario settings and summary statistics for each scenario. The first four columns define the scenario settings: "hydro ratio," "econ ratio," "K scenario," and "gamma scenario." The hydro and econ ratios are values passed to the modeling script that influence multipliers for other model parameters, as documented in the supplement to Yoon et al. 2025 (in review). The gamma multiplier is a coefficient multiplier applied to the baseline gamma values (values below 1 represent lower unobserved costs compared to baseline, values above 1 represent higher costs). The K scenario names represent K values of: "low": 0.5 m/d, "int 1": 2.5 m/d, "int 2": 10 m/d, "high": 50 m/d, and "gleeson": mean Gleeson K value. "Perc vol depleted" is the fraction of groundwater depleted at the end of the 100 simulation. Processed Output: Derived depletion outcomes from raw outputs: All of the individual csv files from the Raw outputs were aggregated into a single file that has the scenario settings and fraction depletion "Perc vol depleted" for every farm cell, for every scenario. The other two files define relationships between the farm id, NLDAS id, and local and major aquifer units, used for aquifer-level depletion analysis.

Agent based modeling↗
DOE OSTI2020

High voltage, cross-field, gas switch and method of operation

A high voltage gas switch includes a gas-tight housing containing an ionizable gas at a preselected gas pressure. The gas switch includes a gas-tight housing containing an ionizable gas at a gas pressure selected based upon a Paschen curve for the ionizable gas, where the Paschen curve plots breakdown voltages of the ionizable gas as a function of gas pressure multiplied by grid-to-anode distance, and where values of gas pressure multiplied by grid-to-anode distance increase over at least a portion of the Paschen curve in conjunction with increasing breakdown voltages. The gas switch also includes an anode disposed within the gas-tight housing, a cathode disposed within the gas-tight housing, and a control grid positioned between the anode and the cathode, where the control grid is spaced apart from the anode by a grid-to-anode distance selected based upon a desired operating voltage.

42 ENGINEERING↗
DOE OSTI2020

Radial Wall Jet Flow Over Sigmoidal Surfaces

Radial wall jet flows across flat smooth surfaces have been studied for decades. These studies show that the radial velocity of these jets decays inversely with distance from the nozzle with modest contribution from friction (Poreh, et al., 1967; Rajaratnam, 1976). However, the extent to which flat surface results apply to curved surfaces remains unclear. In this article we explore the influence of settled particle bed slope on these velocity profiles. We model the step change in thickness as a sigmoidal curve of variable steepness and use conservation of momentum to evaluate the velocity profile. We show that the velocity profile attenuates because of curvature. Next, we evaluate the influence of surface curvature on radial wall jet flow. Jet flows over particle beds often introduce curvature in the particle bed profile but the influence of the developed curvature on the velocity profile has not been explored. Here we develop a solution for steady fixed beds based on conservation of momentum. We find that surface curvature has a significant influence on the velocity decay coefficients and celerity of radial wall jets, provided there is velocity slip in the vicinity of the particle bed interface, which is strictly true for particle surfaces. Conservation of momentum predicts conditions where the forward momentum of the flow is directed completely upward. The solution identifies two new dimensionless groups that determine whether a curved surface is sufficient to block radial flow and force flow vertically.

Surface curvature, jet flow, multiphase flow↗
DOE OSTI2021

Cumulative short-lived photofission product yields for nuclear forensic application

Experiments have long been carried out with linear accelerator (linac) produced bremsstrahlung X-rays to study high-energy photon-induced fission, known as “photofission”. One benefit of photofission, when compared with neutron-induced fission, is the ability to investigate fundamental physics of fission at excitation energies lower than what is possible with neutrons [1]. Absorption of an incident neutron results in a compound nucleus with an excitation energy at least equal to the neutron binding energy; thus, the lowest energy region of the fission barrier cannot be studied. Fission product yield distributions are dependent on the incident particle energy and the target nucleus mass. They are generally represented by a double-humped curve, with low and high mass “peaks” and an intermediate mass “valley”. As incident particle energy increases, the excitation energy of the nucleus increases, thereby increasing the overall yield of isotopes in the valley with respect to the two maxima or peaks of the fission product curve [3]. Photofission is most probable for incident photons around 14 MeV due to the giant dipole resonance. Induced photofission around this energy results in a fission product yield distribution that resembles 14 MeV DT neutron fission more than thermal or fast (500 keV) neutron fission. In post-detonation nuclear forensics, the peak-to-valley ratio of the fission product yield curve could be used for characterizing device type by providing an indication of the neutron energy spectrum that had induced fission (e.g., 500 keV vs. 14 MeV). The goal of this work is to improve nuclear data for isotopes of interest in nuclear forensics and special nuclear material (SNM) detection, specifically the fission product yield data via photofission experiments for the isotopes of 238U and 232Th. Photofission has been proposed as a less costly and more flexible production method for the valley isotopes that are representative of DT neutron fission product yield distributions, which would benefit nuclear forensics exercises in testing for analysis techniques. Natural uranium and thorium targets were irradiated with bremsstrahlung photons (nominal endpoint energies of 8, 14, and 20 MeV), generated via impingement of high-energy electrons on a tungsten electron-to-photon radiator. Gamma-ray spectroscopy was used to observe and identify the decay of the resulting fission products. The photofission yields of 102 fission products were measured for the set of the 238U and 232Th targets at the three bremsstrahlung X-ray endpoint energies 8, 14, and 20 MeV. These fragments included masses ranging from A=84 to A=144, with half-lives as short as 1.07 seconds.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Dynamic clay microstructures emerge via ion complexation waves

Clays control carbon, water and nutrient transport in the lithosphere, promote cloud formation5 and lubricate fault slip through interactions among hydrated mineral interfaces. Clay mineral properties are difficult to model because their structures are disordered, curved and dynamic. Consequently, interactions at the clay mineral-aqueous interface have been approximated using electric double layer models based on single crystals of mica and atomistic simulations. We discover that waves of complexation dipoles at dynamically curving interfaces create an emergent long-range force that drives exfoliation and restacking over time- and length-scales that are not captured in existing models. Curvature delocalizes electrostatic interactions in ways that fundamentally differ from planar surfaces, altering the ratio of ions bound to the convex and concave sides of a layer. Multiple-scattering reconstruction of low-dose energy-filtered cryo electron tomography enabled direct imaging of ion complexes and electrolyte distributions at hydrated and curved mineral interfaces with {\aa}ngstrom resolution over micron length scales. Layers exfoliate and restack abruptly and repeatedly over timescales that depend strongly on the counterion identity, demonstrating that the strong coupling between elastic, electrostatic and hydration forces in clays promote collective reorganization previously thought to be a feature only of active matter.

Whittaker, Michael L↗
DOE OSTI2021

Case Study: Hybrid Carbon Conversion Using Low-Carbon Energy Sources in Coal-Producing States

The demand for more carbon efficient power sources and a decrease in natural gas prices has decreased the desire for coal power. This decrease in demand has led to massive job losses in coal mining regions over the past decade. The purpose of this project is to develop a hybrid energy system utilizing both a coal power plant and advanced reactor, which is competitive with natural gas by improving on profitability and decreasing carbon emissions. This report details the problem with a summary of the impact on the coal industry and the availability of renewable energy sources in the Appalachian region. Because of the geography of the region, variable renewable energy sources are not available without significant size and siting restrictions. However, biomass in the form of wood waste is abundant and can be used as a carbon neutral energy source. Combining biomass and coal processing, in addition to thermal power plants, can increase system profits and efficiency by providing peaking power and conversion opportunities for secondary markets. The electric load is based on publicly available demand data from Appalachian Power, which services the western Virginia and southern West Virginia in the Appalachian region. The demand information is combined by service, normalized, and scaled to an average demand of 1000 kW, which will be the basis for sizing the hybrid energy system. A traditional screening curve analysis for a coal plant and advanced reactor shows that the least cost design varies significantly based on the assumed discount rate and capital recovery period. An optimization program to size the design in TEAL based on the load curve gives 10 optimal designs, all with a negative resulting net present value (NPV) and a coal plant capacity of less than 15%. Including profits from selling captured carbon at a flat rate results in a positive NPV; however, the coal capacity factor only increases to about 40%. There are limitations with this optimization as well since the price of CO2 is likely to decrease as more is sold to the conversion market. The suggested design will combine coal power, an advanced reactor, and coal and biomass coprocessing to produce a variety of products that can be sold to the conversion market while increasing system efficiency. The analysis of conversion pathways for coal and biomass reveals that multiple options will need to be included in the analysis to produce the optimal system design. Three systems will be optimized and compared to determine the best design based on the figures of merit of total NPV and cost of carbon avoided. The first system will include a coal power plant and an advanced reactor that will sell electricity to the grid to meet demand and sell captured carbon to the conversion market. The second system adds a high-temperature steam electrolysis plant, which will utilize electricity during times of low demand to produce hydrogen and sell it to the conversion market. The third system adds biomass and coal processing with options for hydrocarbon oils, syngas to be produced for the conversion market, and electricity generation to power components within the system or provide peaking power. This analysis will be based on a new approach that combines traditional screening curve methods with a dispatch algorithm that optimizes the system based on the opportunity cost of different production options. The resulting optimization algorithm should provide results with less processing time than HERON’s decision tree method. The results from this analysis will determine an optimal design and reinforce the benefits of coal power when used in a hybrid energy system. The initial results show that the addition of a secondary market for carbon sales could result in a positive NPV and increases the capacity factor of the coal plant as compared to a design with only sales to the electricity market. The addition of more markets and additional coal consumption from biomass coprocessing could increase NPV further, replace carbon in other markets through the sale of biomass-derived hydrocarbons, and demonstrate the value of coal power technology.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Post-Irradiation Fracture Toughness Characterization of Generation II FeCrAl Alloys

FeCrAl alloys are promising candidate materials for the accident tolerant fuel (ATF) cladding application due to their exceptional resistance to oxidation in elevated temperature steam environments. Currently, limited fracture toughness data are available for the FeCrAl alloys, including the FeCrAl alloys newly developed at Oak Ridge National Laboratory (ORNL) under the U.S. Department of Energy’s Advanced Fuels Campaign (AFC) program. In this study, two Generation II candidate FeCrAl alloys, i.e., C06M (81.8Fe-10Cr-6Al-0.03Y-2Mo-0.2Si) and C36M (78.8Fe-13Cr-6Al-0.03Y-2Mo-0.2Si), were irradiated in the High Flux Isotope Reactor (HFIR) at ORNL to assess the fracture characteristics of these alloys after neutron irradiation. A total of six rabbit capsules were irradiated in HFIR at target temperatures of 200°C, 330°C, and 500°C up to target damage doses of 8 displacements per atom (dpa) and 16 dpa. Post-irradiation fracture toughness testing was performed following the Master Curve method in the ASTM E1921 standard. The main findings of this study are:1) Both the C06M and C36M alloys exhibited a similar response to irradiation concerning irradiation hardening and embrittlement.2) The irradiation temperature played different roles in terms of irradiation hardening and embrittlement for both C06M and C36M: after irradiation between 166°C and 204°C, both materials exhibited significant irradiation hardening and embrittlement; after irradiation between 315°C and 343°C, both materials showed small irradiation hardening without irradiation embrittlement. After irradiation between 501°C and 507°C, however, the irradiation softening without irradiation embrittlement was observed in both materials.3) Comparing the microhardness and Master Curve reference temperature T0q before and after neutron irradiation, we did not observe a linear correlation between the two parameters for both C06M and C36M steels. This should be mainly due to a flat response of the Master Curve reference temperature T0q to the irradiations at 166–204°C and 315–343°C ranges4) C06M showed a lower T0q, meaning better toughness, than C36M at the unirradiated condition, and such trend was kept even after neutron irradiation except for the 166–204°C irradiation after which both materials had similar T0q.5) In terms of hardening and embrittlement, the irradiation effect on both C06M and C36M appeared to saturate after an irradiation dose of 7 dpa.

Chen, Xiang↗
DOE OSTI2023

EVs@Scale Next-Gen Profiles - EV Profile Capture 2023

As part of the U.S. DOE EVs@Scale consortium Next-Gen Profiles (NGP) project, the profile capture of production electric vehicles undergoing high power charging (HPC) is conducted over a wide range of conditions to explore variance and performance. Charge session parameters are collected from both the electric vehicle (EV) and electric vehicle supply equipment (EVSE) at a rate of 10Hz and entered into a time-series database for analysis. These charge profiles are captured under nominal and off-nominal conditions, exploring the impact of battery state of charge (SOC), battery temperature, vehicle condition, smart charge management (SCM), and EVSE limitations. Nominal conditions are defined to be ideal conditions that should transfer the maximum allowable energy in the minimum possible amount of time. Nominal condition profiles are compared across EVs to characterize state-of-the-art EV charging performance against one another. Off-nominal condition profiles are compared against its nominal condition profile counterpart to highlight the variance across less desirable starting conditions within a single EV. Under nominal conditions, most EVs can achieve the original equipment manufacturer (OEM) rated peak-power and charge times. Peak power across EVs has variance due to the vehicle design, battery topology, charging strategy, etc. These 10-100% nominal preconditioned charge profiles across 13 EVs (11 light-duty (LD), 2 heavy-duty (HD)) were used for analysis in power curve analysis, power distribution, SOC and range comparison, thermal impacts of current draw, battery pack size and energy charged, and ramp rates. Power curve analysis show the uniqueness in power vs time curves across all EVs, breaking down the features of a typical profile and where variation is typically seen. Power distribution results showed that over 50% of charge time is spent below 50kW and only 12.1% is spent above 200kW. SOC and range performance yielded different top performing EVs when exploring goals of performance from SOC and range gained after 10-min (EV2) and 20-min (EV8), and time-to-achieve 80% SOC (EV8) and 200 miles of range (EV1). Current draw from 400-volt EVs had a higher thermal impact to cable/connector temperatures when compared to 800-volt EVs, due to a higher current requirement to achieve similar power levels. There was high variance in C rating, a useful metric when comparing the relationship between peak/average charge session power and relative battery pack size, across EVs under test. Ramp rates during initial power transfer were examined, fastest and slowest speeds ranging from 192.5kW/second to 2.6kW/second respectively. A similar analysis of ramp rates was also conducted for OCPP curtailment testing, where EVs underwent a 2-minute 65A curtailment request before returning to full-power charge. Under off-nominal conditions, most EVs experienced variation from the nominal condition profiles. EVs that underwent the full set of NGP defined testing conditions were compared, analysis of which was categorized by 800-volt and 400-volt EVs. It should be noted that the 800-volt EVs had significantly higher peak power ratings than the 400-volt EVs, and thus were more prone to variance. Initial state of charge, battery temperature, and vehicle condition had a considerable impact on peak power levels and charge time for the 800-volt vehicles under test. EVSE limited tests lowered achievable power down to 200kW, greatly impacted 800-volt charging power, and had little to no effect on 400-volt charging power. Adapter testing was performed on a single 400-volt EV, where power and current limitations were found but overall charge time was not significantly impacted. Adapter and boost converter testing was performed on a single 800-volt EV, where both charge power and charge time were greatly impacted. Charge profiles are unique, and comparing such requires analysis that examines starting conditions, vehicle and battery topologies,

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