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DOE OSTI2023

Rotation curves and dynamical masses of MaNGA barred galaxies

In this paper we analyse a sample of 46 barred galaxies of MaNGA. Our goal is to investigate the stellar kinematics of these galaxies and obtain their rotation curves. Additionally, we aim to derive the total stellar and dynamical masses, as well as the maximum rotation velocity, in order to examine their distributions and scaling relations. Using the Pipe3D dataproducts publicly available we obtained the rotation curves, which were fitted considering two components of an axisymmetric Miyamoto–Nagai gravitational potential. We found a wide range of the maximum rotation velocities (117–340 ${\rm km\, s^{-1}}$), with a mean value of 200 ${\rm km\, s^{-1}}$. In addition we found that the total stellar and dynamical masses are in the range of log(M star /M ⊙ ) = 10.1−11.5, with a mean value of log(M star /M ⊙ ) = 10.8, and log(M dyn /M ⊙ ) = 10.4−12.0, with a mean value of log(M dyn /M ⊙ ) = 11.1, respectively. We found a strong correlation between dynamical mass and maximum velocity, between maximum velocity and magnitude, and between stellar mass and maximum velocity. According to these results, barred galaxies exhibit similar behaviour to that of normal spiral galaxies with respect to these relations, as well as in terms of the distribution of their dynamical mass and maximum rotation velocity. However, we found that the distribution of stellar masses of barred galaxies is statistically different from other samples including non-barred galaxies. Finally, analysing the galaxies that show nuclear activity, we find no difference with the rotation curves of normal galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The dark matter profile of the Milky Way inferred from its circular velocity curve

ABSTRACT In this paper, we construct the circular velocity curve of the Milky Way out to ∼30 kpc, providing an updated model of the dark matter density profile. We derive precise parallaxes for 120 309 stars with a data-driven model, using APOGEE DR17 spectra combined with GaiaDR3, 2MASS, and WISE photometry. At outer galactic radii up to 30 kpc, we find a significantly faster decline in the circular velocity curve compared to the inner parts. This decline is better fit with a cored Einasto profile with a slope parameter $0.91^{+0.04}_{-0.05}$ than a generalized Navarro–Frenk–White (NFW) profile. The virial mass of the best-fitting dark matter halo profile is only $1.81^{+0.06}_{-0.05}\times 10^{11}$ M⊙, significantly lower than what a generalized NFW profile delivers. We present a study of the potential systematics, affecting mainly large radii. Such a low mass for the Galaxy is driven by the functional forms tested, given that it probes beyond our measurements. It is found to be in tension with mass measurements from globular clusters, dwarf satellites, and streams. Our best-fitting profile also lowers the expected dark matter annihilation signal flux from the galactic centre by more than an order of magnitude, compared to an NFW profile-fit. In future work, we will explore profiles with more flexible functional forms to more fully leverage the circular velocity curve and observationally constrain the properties of the Milky Way’s dark matter halo.

Ou, Xiaowei (ORCID:0000000246699967)↗

DOE OSTI2024

Training custom light curve models of SN Ia subpopulations selected according to host galaxy properties

ABSTRACT Type Ia supernova (SN Ia) cosmology analyses include a luminosity step function in their distance standardization process to account for an observed yet unexplained difference in the post-standardization luminosities of SNe Ia originating from different host galaxy populations [e.g. high-mass ($M \gtrsim 10^{10} \, {\rm M}_{\odot }$) versus low-mass galaxies]. We present a novel method for including host-mass correlations in the SALT3 (Spectral Adaptive Light curve Template 3) light curve model used for standardizing SN Ia distances. We split the SALT3 training sample according to host-mass, training independent models for the low- and high-host-mass samples. Our models indicate that there are different average Si ii spectral feature strengths between the two populations, and that the average spectral energy distribution of SNe from low-mass galaxies is bluer than the high-mass counterpart. We then use our trained models to perform an SN cosmology analysis on the 3-yr spectroscopically confirmed Dark Energy Survey SN sample, treating SNe from low- and high-mass host galaxies as separate populations throughout. We find that our mass-split models reduce the Hubble residual scatter in the sample, albeit at a low statistical significance. We do find a reduction in the mass-correlated luminosity step but conclude that this arises from the model-dependent re-definition of the fiducial SN absolute magnitude rather than the models themselves. Our results stress the importance of adopting a standard definition of the SN parameters (x0, x1, c) in order to extract the most value out of the light curve modelling tools that are currently available and to correctly interpret results that are fit with different models.

Taylor, G. (ORCID:0000000157563259)↗

DOE OSTI2025

Probing Curved Spacetime with a Distributed Atomic Processor Clock

Quantum dynamics on curved spacetime has never been directly probed beyond the Newtonian limit. Although we can describe such dynamics theoretically, experiments would provide empirical evidence that quantum theory holds even in this extreme limit. The practical challenge is the minute spacetime curvature difference over the length scale of the typical extent of quantum effects. Here, we propose a quantum network of alkaline earth (like) atomic processors for constructing a distributed quantum state that is sensitive to the differential proper time between its constituent atomic processor nodes, implementing a quantum observable that is affected by post-Newtonian curved spacetime. Conceptually, we propose to delocalize one clock between three locations by encoding the presence or absence of a clock into the state of the local atoms. By separating three atomic nodes over approximately kilometer-scale elevation differences and distributing one clock between them via a 𝑊 state, we demonstrate that the curvature of spacetime is manifest in the interference of the three different proper times that give rise to three distinct beat notes in our nonlocal observable. We further demonstrate that 𝑁-atom entanglement within each node enhances the interrogation bandwidth by a factor of 𝑁. We discuss how our proposed system can probe new facets of fundamental physics, such as the linearity, unitarity, and probabilistic nature of quantum theory on curved spacetime. Our protocol combines several recent advances with neutral atom and trapped ions to realize a novel quantum probe of gravity uniquely enabled by quantum networks.

Covey, Jacob P. [Univ. of Illinois at Urbana-Champ↗

DOE OSTI2025

Efficient analysis of small-angle scattering curves for large biomolecular assemblies using Monte Carlo methods

Structure elucidation from small-angle scattering curves of large biomolecular assemblies is notoriously challenging. This is because the simulation of high-resolution features in the structure of large macromolecular assemblies, such as de novo protein assemblies, is computationally demanding when it needs to cover a broad range of length scales. Conventional methods, such as the numerical approximation to the Debye equation or the use of spherical harmonics, do not scale well as the size of the assembly increases, which limits their application to small structures (e.g. individual proteins). This work explores the effectiveness of a Monte Carlo method to simulate and fit scattering curves for large biomolecular assemblies spanning over ranges covering atomic and molecular detail (e.g. spacing and orientation of proteins in an assembly) as well as large-scale (hundreds of nanometres) features. Owing to its speed and scalability, it can be combined with a fitting algorithm to extract structural features from experimental small-angle scattering curves in biomolecular assemblies that are otherwise intractable for interpretation. This work first demonstrates the effectiveness of the tool using experimental small-angle X-ray scattering (SAXS) data from tile-like proteins that assemble into 1D tube-like macromolecular structures. Here, the diameter distribution of tubes is extracted from SAXS fits, and this is quantitatively compared with distributions from electron microscopy. SAXS data are also obtained from 2D sheet-like protein assemblies, and the proposed method is used to quantify structural features such as the separation distance between protein building blocks and the flexing of the sheet. An open-source implementation of the methodology is provided for use in a broad range of biological systems involving multi-scale scattering analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

An Open Source Perovskite Solar Cell Curve Tracer

When developing systems for perovskite solar cells (PSCs), it is important to have a testing platform that closely resembles your deployed systems. While developing a 1 U CubeSat, the Big Red Sat-1 at the University of Nebraska-Lincoln, we found a lack of passive curve tracing instrumentation, which we needed for our mission. To that end, we developed a benchtop passive curve tracer that leverages the Ossila Solar Simulator as an AM1.5 light source. This device utilizes a ladder of switched resistors and a precision voltage and current measurement to achieve the curve tracing. It also integrates a common-anode multiplexer to switch through multipixel PSCs. Finally, the solar cell holder is separate from the main measurement system, so various substrates sizes and pixel counts can be supported. This system is tested using various PSCs. It has been open sourced to enable reuse in future systems that may benefit from the lower power consumption and flight heritage.

14 SOLAR ENERGY↗

DOE OSTI2024

Robust VAR Capability Curve of DER with Uncertain Renewable Generation

Active distribution system with high penetration of inverter based distributed energy resources(DER), can be utilized for var-related ancillary services at the transmission side interface. In order to utilize the DER flexibility, transmission system operator must be presented the aggregated DER flexibility of distribution system. However, the uncertainty in renewable generation, questions the credibility of aggregated capability curve in practice. In this paper, we incorporate the uncertainty into aggregation process to develop capability curve while preserving the real physics (unbalance and lossy nature) of distribution system. The Resulting capability curve with the associated probability can be harnessed by the TSO for decision making for both planning and operation.

Kar, Aditya Shankar↗

DOE OSTI2024

A Bayesian Multi-fidelity Neural Network to Predict Nonlinear Frequency Backbone Curves

The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. Here, this paper presents a multi-fidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics Research Challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model's uncertainty. Once trained, the multi-fidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.

42 ENGINEERING↗

DOE OSTI2022

Specimen Size and Geometry Effects on the Master Curve Fracture Toughness Measurements of EUROFER97 and F82H Steels

EUROFER97 and F82H are two leading reduced-activation ferritic-martensitic (RAFM) steels for fusion blanket applications. Exposure to the harsh environment of fusion reactors can result in severe degradation of materials fracture toughness (FT). Thus, the post-irradiation evaluation of FT is critical to understanding the material behavior. Due to the space constraint of irradiation facilities, the development of small specimen test techniques (SSTT) is necessary to evaluate the performance of irradiated materials. In this study, we evaluated the specimen size and geometry effects on the ductile-to-brittle transition FT of EUROFER97 batch-3 and F82H-BA12 steels. The specimen thicknesses ranged from 1.65 to 12.7 mm and the geometries included 1.65 mm bend bar, 4 mm mini-compact tension (miniCT), and 0.5T compact tension (CT) specimens. Fracture toughness testing and evaluations were performed using the Master Curve method in the ASTM E1921-19 standard. After size correction to 1T size using the Master Curve method, no specimen size effect was observed between the 4 mm miniCT and 0.5T CT specimens for the Master Curve reference temperature T0Q, while the bend bars yielded a higher T0Q. A strong effect of fatigue precrack front straightness on T0Q for 0.5T CT specimens was observed. The minimum number of specimens needed for each specimen geometry has been determined.

Chen, Xiang↗

DOE OSTI2021

Changes in Climate and Its Effect on Timing of Snowmelt and Intensity-Duration-Frequency Curves

Snow is a critical water resource for much of the U.S. and failure to account for changes in climate could deleteriously impact military assets. In this study, we produced historical and future snow trends through modeling at three military sites (in Washington, Colorado, and North Dakota) and the Western U.S. For selected rivers, we performed seasonal trend analysis of discharge extremes. We calculated flood frequency curves and estimated the probability of occurrence of future annual maximum daily rainfall depths. Additionally, we generated intensity-duration-frequency curves (IDF) to find rainfall intensities at several return levels. Generally, our results showed a decreasing trend in historical and future snow duration, rain-on-snow events, and snowmelt runoff. This decreasing trend in snowpack could reduce water resources. A statistically significant increase in maximum streamflow for most rivers at the Washington and North Dakota sites occurred for several months of the year. In Colorado, only a few months indicated such an increase. Future IDF curves for Colorado and North Dakota indicated a slight increase in rainfall intensity whereas the Washington site had about a twofold increase. This increase in rainfall intensity could result in major flood events, demonstrating the importance of accounting for climate changes in infrastructure planning.

58 GEOSCIENCES↗

DOE OSTI2022

Literature Review on Next Generation Solvent Isopar ® L Vapor Pressure Curve and the Partitioning of its Modifier and Extractant

The Next Generation Solvent (NGS) is set to replace the Original Caustic Side Solvent Extractant (CSSX) at the Salt Waste Processing Facility (SWPF). The Savannah River National Laboratory (SRNL) was requested by Savannah River Mission Completion (SRMC), formerly Savannah River Remediation (SRR), to perform a literature review on the following topics to address flammability concerns with the current solvent: Isopar ® L vapor pressure curve for NGS, partitioning ratio for the extractant MaxCalix and the modifier Cs-7SB, and high cesium concentration impacts on NGS radiolysis and potential solvent degradation rates in high cesium concentrations. The following conclusions and recommendations are made based on previous experimental work and literature: (1) Current SWPF flammable gas generation calculations use an Isopar ® L vapor pressure curve based on experimental testing with the Original CSSX solvent. No such testing to date has been performed with NGS. It is suggested that the decrease in Cs-7SB concentration for NGS compared to the Original CSSX solvent would lead to a slightly higher vapor pressure at all temperatures in SWPF vessels. A bounding NGS vapor pressure curve has been provided; it is recommended to see if these values would challenge current flammability controls and to perform testing if needed.(2) The partitioning ratio for Cs-7SB is known in the Original CSSX solvent with dilute nitric acid and caustic solutions. No tests could be found for the partitioning of Cs-7SB to dilute boric acid solutions; however, a similar partitioning ratio is expected. Due to the lipophilic alkyl chains on MaxCalix, it is expected to be even less soluble than BOBCalixC6 in the aqueous phase and should not be considered a significant contributor to the f organic term. Additionally, the reaction rate of N,N’,N’’-Tris(3,7-dimethyloctyl)guanidine (TiDG) or its degradation products with a hydrogen radical should be estimated/determined if they are found to be significant contributors to the f organic term. (3) NGS is expected to see much higher Cs concentrations at SWPF in comparison to its use at the Modular CSSX Unit (MCU). These higher Cs concentrations could influence radiolytic degradation rates of the solvent. NGS appears to be fairly stable to radiolytic degradation based on previous testing and its use at MCU. However, there has not been radiolytic flammable gas generation testing with NGS to date. There is a risk that the continued use of G-values obtained for flammable gases produced from the irradiation of the Original CSSX solvent is not bounding for NGS, but this is considered a very low risk due to the similarities in the composition of the solvents, as well as the conservatisms in the experimental design of the Original CSSX testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Timing based clustering in the Northern Finland Birth Cohorts 1966 and 1986 suggests two new patterns for childhood BMI curve [Poster]

Childhood body mass index (BMI) is a widely used measure of adiposity in children (<18 years of age). Children grow with individual tempo and individuals of the same age, or of the same BMI, might be in different phases in their individual growth curves. Variability between different childhood BMI curves can be separated in two components: phase variability (x-axis; time) and amplitude variability (y-axis; BMI). Phase variability can be thought of arising from differences in maturational age between individuals. This is related to the timing of peaks and valleys in a child’s BMI curve.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Preserving Superconvergence of Spectral Elements for Curved Domains [Slides]

Finite Element Methods (FEM) and Spectral Element Methods (SEM) are crucial for solving partial differential equations (PDEs) on complex geometries. SEM offers superior accuracy due to potential superconvergence for simple domains. Challenges persist for domains with curved boundaries, restricting SEM’s advantages in real-world applications. A proposed solution is the introduction of a novel strategy to enhance accuracy and maintain superconvergence of SEM in curved domains. The strategy includes a mesh-generation procedure with geometrically refined elements near curved boundaries and a post-processing phase using the Adaptive Extended Stencil Finite Element Method (AES-FEM). The method, named AES-FEM post-processed Spectral Element Method (ApSEM), aligns the accuracy of non-tensor-product elements with superconvergent spectral elements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Integral Field Probe for Mapping of Curved Magnets

The Single Stretched Wire (SSW) method allows highly precise integral field measurements by recording voltage across a tensioned wire mounted to 2-axis linear stages at either end of the magnet aperture. However, traditional SSW probes are not well suited for curved accelerator magnets, which are essential for steering charged particles along arced trajectories in storage rings or beamlines. The tension required to eliminate sag demands a purely straight path, making them incompatible with non-linear magnet geometries. To address this limitation for curved magnets, a modified approach was developed using a segmented, 3D-printed support structure that incorporates a pre-shaped anti-sag curve. Under its own weight and that of the wire bundle, the structure deforms to lie flat while conforming to the curvature of the magnet in the horizontal plane. The optimal geometry of the probe was derived using an iterative process combining FEA simulations in Ansys Mechanical with testing of various carbon fiber-reinforced filaments. The printed and assembled probe was successfully used to measure the SDD-059 magnet at Fermilab, yielding promising results.

Jakopin, Alexander [Northern Illinois U.]↗

DOE OSTI2021

Core-Collapse Supernovae: From Neutrino-Driven 1D Explosions to Light Curves and Spectra.

We present broadband light curves and spectra for a suite of core-collapse supernova models computed self-consistently in spherical symmetry within the PUSH framework. We use the open source LANL code SuperNU to compute light curves and spectra. This data release covers only the electromagnetic counterparts of the models, not the models themselves, which were produced at North Carolina State University and used with permission. We follow spectra from the photospheric to the nebular phase. The data is released as machine-readable ASCII tables, with luminous flux tabulated by wavelength (or band for the broadband light curves) vs. time.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Wind Turbine Sound Setbacks and Supply Curves: Ordinances and Extrapolated Trends, 110 Hub Height, 130 Rotor Diameter

This dataset provides a comprehensive set of wind turbine sound setbacks from every residential structure in the contiguous United States (CONUS). A sound setback is defined as the minimum required distance between a residential structure and a hypothetical turbine installation site to ensure that modeled sound levels received at the residence do not exceed local sound ordinances, which are commonly expressed in A-weighted decibels (dBA). Therefore, sound setbacks are a local spatial assessment combining multiple factors, including the sound pressure curve as a function of the observer location (distance and direction) relative to the turbine, local sound regulations, and the geographical distribution of residential structures. The dataset is organized into multiple scenario-based products, detailed as follows: 1. Existing and extrapolated sound setbacks. An existing scenario characterizes sound setbacks only in states or counties that have implemented sound regulations as of 2022. The extrapolated scenarios extend a constant sound threshold to counties that lack explicit sound regulations, with thresholds ranging from 35 to 60 dBA, in 5-dBA increments reflecting the variation observed in current sound ordinances. 2. Sound setbacks in directional and worst scenarios. The directional scenario accounts for the distance and orientation of residential structures relative to a hypothetical turbine location, utilizing the turbine's sound emissions in that specific direction. In contrast, the worst scenario takes loudest sound level at each distance step from the turbine, irrespective of directional considerations, which aligns with current industry practice. 3. Supply curves for Open and Reference Access scenarios. This dataset includes supply curves generated by the reV model, which integrates each of the above sound setbacks into both Open and Reference siting scenarios. In addition, two Open and Reference baselines scenarios were included which do not consider sound setbacks for comparative analysis. All sound setback data are stored in TIF files, with partial maps of the data provided in PNG format. The values in the sound setback raster range from 0 to 1, representing the fraction of developable land within a 90 meter by 90 meter pixel due to sound ordinances. A value of 0 indicates areas where wind energy development is prohibited, while a value of 1 signifies areas fully permissible. The wind turbine parameters used in the sound modeling are based on the land-based turbine from International Energy Agency (IEA), featuring a rated electrical power of 3.4 MW, a rotor diameter of 130 meters, and a hub height of 110 meters. The atmospheric conditions, including wind speed/direction, turbulence, air temperature, relative humidity, and air pressure, that drive the sound generation are obtained from the WIND Toolkit dataset.

Array↗

DOE OSTI2022

Physics-Based Method for Generating Fully Synthetic IV Curve Training Datasets for Machine Learning Classification of PV Failures

Classification machine learning models require high-quality labeled datasets for training. Among the most useful datasets for photovoltaic array fault detection and diagnosis are module or string current-voltage (IV) curves. Unfortunately, such datasets are rarely collected due to the cost of high fidelity monitoring, and the data that is available is generally not ideal, often consisting of unbalanced classes, noisy data due to environmental conditions, and few samples. In this paper, we propose an alternate approach that utilizes physics-based simulations of string-level IV curves as a fully synthetic training corpus that is independent of the test dataset. In our example, the training corpus consists of baseline (no fault), partial soiling, and cell crack system modes. The training corpus is used to train a 1D convolutional neural network (CNN) for failure classification. The approach is validated by comparing the model’s ability to classify failures detected on a real, measured IV curve testing corpus obtained from laboratory and field experiments. Results obtained using a fully synthetic training dataset achieve identical accuracy to those obtained with use of a measured training dataset. When evaluating the measured data’s test split, a 100% accuracy was found both when using simulations or measured data as the training corpus. When evaluating all of the measured data, a 96% accuracy was found when using a fully synthetic training dataset. The use of physics-based modeling results as a training corpus for failure detection and classification has many advantages for implementation as each PV system is configured differently, and it would be nearly impossible to train using labeled measured data.

Hopwood, Michael W. (ORCID:0000000161901767)↗

DOE OSTI2020

The TESS Phase Curve of KELT-1b Suggests a High Dayside Albedo

We measured the optical phase curve of the transiting brown dwarf KELT-1b (TOI 1476) using data from the TESS spacecraft. We found that KELT-1b shows significant phase variation in the TESS bandpass, with a relatively large phase amplitude of 234{sub −44}{sup +43} ppm and a secondary eclipse depth of 371{sub −49}{sup +47} ppm. We also measured a marginal eastward offset in the dayside hot spot of 18.°3 ± 7.°4 relative to the substellar point. We detected a strong phase-curve signal attributed to ellipsoidal distortion of the host star with an amplitude of 399 ± 19 ppm. Our results are roughly consistent with the Spitzer phase curves of KELT-1b, but the TESS eclipse depth is deeper than expected. Our cloud-free 1D models of KELT-1b’s dayside emission are unable to fit the full combined eclipse spectrum. Instead, the large TESS eclipse depth suggests that KELT-1b may have a significant dayside geometric albedo of A {sub g} ∼ 0.5 in the TESS bandpass, which would agree with the tentative trend between equilibrium temperature and geometric albedo recently suggested by Wong et al. We posit that if KELT-1b has a high dayside albedo, it is likely due to silicate clouds that form on KELT-1b’s nightside and are subsequently transported onto the western side of KELT-1b’s dayside hemisphere before breaking up.

79 ASTRONOMY AND ASTROPHYSICS↗