Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “DISTRIBUTION”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

NH 4 OH Looping with Membrane CO 2 Absorber and Distributed Stripper for Enhanced Algae Growth

The University of Kentucky Center for Applied Energy (UK CAER) has devised a unique, integrated CO2 capture and utilization technology. CO2 from coal-fired power generation flue gas is first captured at half the operating cost of a typical aqueous CO2 capture system (CCS), distributed in an aqueous stream and then fixed by algae in bioreactors where the algae production is increased by 50% over that with a typical intermittent nutrient feeding system. Lower CCS operating cost is achieved by eliminating the flue gas pretreatment step for cooling and SO2 removal, eliminating steam extraction from the power generation steam cycle for solvent regeneration, and eliminating CO2 compression. Higher algae production is achieved by continuous, just-in-time nutrient feed to the bioreactors directly from a distributed solvent regenerator, which maintains the bioreactor pH for optimum growth. The process starts with a uniquely configured membrane absorber, where the flue gas is indirectly contacted with an ammonium hydroxide (NH4OH) solvent. Dissolved NH3 is attractive for both CO2 capture and as an algae nutrient. For CO2 capture it is inexpensive, has a low regeneration energy, is thermally- and oxidatively-stable and has a viscosity near that of water, which makes is easy to transport. Numerous studies have shown that the scrubbing capacity of NH3 is approximately 0.9-1.2 kg of CO2/kg of NH3, with a CO2 removal efficiency of ~99% and half the solvent regeneration energy than that of 30 wt% MEA[1, 2, 3]. NH3 is attractive as an algae nutrient due to its low cost. The rich NH4OH solvent is pumped to a set of distributed regenerators which are co-located with the algae bioreactors. Solvent pumping, transport and distribution reduces the balance of plant (BOP) cost compared to a typical aqueous CCS related to the flue gas duct and boost fan required to transport the flue gas. The energy required for the distributed solvent regeneration is supplied by solar-thermal panels eliminating the need for steam extraction from the power generation steam cycle. After solvent regeneration, the product stream contains both the CO2 captured from the flue gas and volatized NH3 from the solvent. This product stream is fed directly to the bioreactors, eliminating the need for compression of the CO2 stream. The relative amounts of CO2 and NH3 in the product stream are adjusted and controlled by a controlling the regeneration conditions (pressure and temperature). The continuous feed of the right ratio of nutrients overcomes the typical inhibition of algae growth resulting from frequent pH swings in the bioreactor due to unbalanced (intermittent) feeding systems for CO2 and N. Also, because the regenerators will operate at pressure and be located in close proximity to the bioreactors, there is no worry about pressure drop when sparging the gas into the algae. Sparging produces small bubbles which is beneficial for mass transfer efficiency. One known challenge when using an NH4OH solvent is high NH3 emission. Hydrophobic membranes are used for CO2 capture using an aqueous NH3 solution[4, 5] without the direct contact between flue gas and aqueous solution. Additionally, UK CAER CO2 capture and utilization process manages NH3 slip in three extra measures. First, NH3 slip is minimized by working with minimal species partial pressure, which is proportional to the concentration in the liquid. Hence, lowering the capture solvent concentration will lower the NH3 partial pressure. Second, UK CAER’s previous work has demonstrated that the addition of Zn2+ into NH3 solutions to chelate the NH3 can reduce NH3 volatility. Third, the configuration of the membrane CO2 absorber utilizes condensed water from the flue gas to continually wash the gas-side of the membrane to reduce fouling and recapture NH3 slip. Additional details about the UK CAER unique, integrated CO2 capture and utilization technology will be presented along with technology development plans. Diao, N., Q. Li, and Z. Fang. 2004. Heat transfer in ground heat exchangers with groundwater advection. International Journal of Thermal Sciences. 43: 1203-1211, He, Q., M. Chen, L. Meng, K. Liu, and W. Pan. 2004. Study on Carbon Dioxide Removal from Flue Gas by Absorption of Aqueous Ammonia. Western Kentucky University. Yeh, A.C., and H. Bai. 1999. Comparison of ammonia and monoethanolamine solvents to reduce CO2 greenhouse gas emissions. The Science of the Total Environment. 228: 121-133, Villeneuve, K., D. Roizard, J.C. Remigy, M. Iacono, and S. Rode. 2018. CO2 capture by aqueous ammonia with hollow fiber membrane contactors: Gas phase reactions and performance stability. Separation and Purification Technology, 199: 189-197, Toro Molina, C., and C. Bouallou. 2016. Carbon dioxide absorption by ammonia intensified with membrane contactors. Clean Techn Environ Policy 18, 2133–2146 (2016)

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Incorporating new evaluation on angular distributions and energy spectra of neutron-induced charged particle reactions into the next ENDF library release (Technical Progress Report)

This project aims to provide the improved Evaluated Nuclear Data File (ENDF) using the newly measured data as well as the latest nuclear reaction model for calculating angular distributions and energy spectra on neutron-induced charged particle reactions through the collaboration of Korea Atomic Energy Research Institute (KAERI) and Los Alamos National Laboratory (LANL). The LANL group will provide the experimental data for angular distributions and spectra of (n,p) and (n,α) on several structural materials such as Fe, Ni and Zn isotopes using the Low Energy Neutron-induced Charged-particle (Z) Chamber (LENZ) instrument at Los Alamos Neutron Science Center (LANSCE). The KAERI group will provide the improved evaluated nuclear library which is based on the LANL experimental data, and further will predict angular distributions and spectra of (n,p) and (n,α) reactions on unmeasured nuclides, such as Cr, Mn, Co, Cu and so on. For the first year of this project, we planned to analyze (n,p) and (n,α) reactions for 54,56 Fe and perform new measurements on those reactions for 58,60 Ni isotopes with the LENZ instrument at LANSCE. For improving our evaluation quality, we have studied reaction models to reproduce LANL’s experimental angular distributions and energy spectra using the full Hauser-Feshbach model code, CoH3 with no approximations used. As the first year’s deliverables, we provided the experimental (n,p) and (n,α) reaction cross sections for 54,56 Fe and incorporate new evaluation on angular distributions and energy spectra of neutron-induced charged particle reactions into the current ENDF/B-VIII.0.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A Closed-Loop Distribution System Restoration Tool for Natural Disaster Recovery. Final CRADA report

We propose to continue the development of the restoration algorithms and the tool’s user interface, both of which have been developed under the GMLC-0131 project. This project aims to develop a distribution restoration decision support tool that will assist utilities in performing distribution restoration after extreme weather events in an optimal and efficient manner. The tool will integrate the weather information/forecasts and system fragility assessment together with the field measurement data to improve the situational awareness and estimate the system damage status. Advanced optimization models will be leveraged to dispatch repair crews and associated resources. New resources (e.g., automatic switches and distributed generators (DGs)) enabled by distribution automation and smart grid development will be utilized to reconfigure distribution grids and pick up loads promptly to reduce the outage sizes and durations. The closed-loop feature of the tool will make the tool adaptive to the evolving weather events and varying restoration capabilities. In this CRADA, we will collaborate with S&C Electric Company (S&C) to refine ANL-1060 (07/17/2019) the restoration algorithms that can be potentially applicable for any utility systems and vendor products, including: 1) Customizable information from both utility users and vendor users; 2) User interface design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

STOCHASTIC OPTIMAL POWER FLOW FOR REAL-TIME MANAGEMENT OF DISTRIBUTED RENEWABLE GENERATION AND DEMAND RESPONSE (Final Report)

To meet the grand challenge of a sustainable energy future, there has been a surge of interest in renewable energy. Today, the uncertainty associated with renewable resources is handled by using operating reserves. The high penetration of renewable resources, however, introduces difficult-to-control dynamics and challenges for power system operation. Decision support tools are necessary at the bulk system operational level to recognize and efficiently utilize renewable resources and distributed demand response products in concert with traditional grid resources. It is envisaged that responsive load can potentially have very significant cost advantages over either spinning or non-spinning ramping reserve. Critical decisions are made during hour(s)-ahead and real-time power system operation regarding the commitment and dispatch of generators to ensure power delivery is both reliable and economic. These decisions are typically made by a security constrained optimal flow, which determines future generator commitments, dispatches, and ensures adequate reserves are available in the event of a contingency (unexpected outage) or if future system conditions deviate from forecasts. However, security has been always based on a pre-specified subset of contingency constraints whose enforcement does not guarantee security under all possible future possibilities while also giving little or no weight to the likelihood of each contingent event or the severity of its consequences. Existing tools, which are based exclusively on deterministic optimization models, do not yield optimal operational decisions to address these new challenges, in terms of both reliability and cost-effectiveness. This project has focused on developing a stochastic optimal power flow (SOPF) framework, which integrates renewable resource uncertainty, load uncertainty, distributed storage (DS), demand response (DR) products, in a holistic manner to address the uncertainty associated with ever-increasing renewable resources, along with the inclusion of distributed demand response products in future power systems. A proof-of-concept problem was created using the Pennsylvania-Jersey-Maryland (PJM) power system network. Synthetic wind generation was added to the system to simulate 50% wind penetration. A 1-hour test of SOPF operation indicated more than 6% operational cost savings. The project continued by adding the Midwestern Independent System Operator (MISO) as a partner, with focus shifting from SOPF to Stochastic Look-Ahead Unit Commitment (SLAC). Unlike PJM, MISO is faced with significant renewable energy resources within its footprint and is challenged with substantial uncertainty in its operations. The SLAC distinguishes itself from existing tools that operators use. At best, today’s tools solve two to three cases independently, where one or two system parameters, such as forecasted load level (e.g., a low, base, and high forecast), are varied and the resulting scenarios are analyzed independently. The stochastic-based optimization of SLAC leverages statistical information from an ensemble of potential operational scenarios and their respective likelihood. The SLAC output can be translated into valuable information to the operator such as suggested commitments, optimal scheduling and dispatch of resources, reserve requirements at both locational and zonal resolutions, ramping availability and requirements, availability of demand response including operational guidance concerning the near-term and real-time coordination between distributed energy resources, and utilization of distributed storage resources. The developed SOPF/SLAC tool, a stand-alone tool compatible with existing EMSs, will provide system operators with unprecedented visibility, flexibility and predictability to these resources and operational guidance concerning the real-time coordination between DERs and DR/DS products. The game changing and practical impact of this disruptive technology will be dramatic and will usher in a new era in the electric power industry, wherein green energy concepts are fully embraced, and electric power costs are lowered throughout the nation.

42 ENGINEERING↗
DOE OSTI2023

Scanning Mobility Particle Sizer (SMPS)-Aerodynamic Particle Sizer (APS) Merged Size Distribution (mergedsmpsaps) Value-Added Product Report

Aerosol particles influence the Earth’s radiation balance directly by absorbing and scattering light and indirectly by influencing cloud formation, properties, and lifetimes. Measurements of aerosol particle optical properties, mass loading, size distributions, microphysical properties, cloud formation properties, and chemical composition are important for understanding the aerosol life cycle and for validating earth system models that predict these quantities. The Atmospheric Radiation Measurement (ARM) user facility’s Aerosol Observing System (AOS) is a highly instrumented platform designed to house instruments that measure many of these aerosol properties in situ. Currently, ARM operates at least four different instruments that measure a portion of the ambient aerosol size distribution. Most users are interested in the entire size distribution or a portion of the size distribution that extends across the measurement range of multiple instruments. However, merging these distributions is not trivial as the instruments employ different measurement principals and, in most cases, report data as a function of different representations of the aerosol diameter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Effect of the Velocity Distribution on Kilonova Emission

The electromagnetic emission from the nonrelativistic ejecta launched in neutron star mergers (either dynamically or through a disk wind) has the potential to probe both the total mass and composition of this ejecta. These observations are crucial in understanding the role of these mergers in the production of r-process elements in the Universe. However, many properties of the ejecta can alter the light curves and we must both identify which properties play a role in shaping this emission and understand the effects these properties have on the emission before we can use observations to place strong constraints on the amount of r-process elements produced in the merger. This paper focuses on understanding the effect of the velocity distribution (amount of mass moving at different velocities) for lanthanide-rich ejecta on the light curves and spectra. The simulations use distributions guided by recent calculations of disk outflows and compare the velocity-distribution effects to those of ejecta mass, velocity, and composition. Our comparisons show that uncertainties in the velocity distribution can lead to a factor of 2–4 uncertainties in the inferred ejecta mass based on peak infrared luminosities. We also show that early-time UV or optical observations may be able to constrain the velocity distribution, reducing the uncertainty in the ejecta mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Managed Tokens Service for Securely Keeping and Distributing Grid Tokens

Fermilab is transitioning authentication and authorization for grid operations to using bearer tokens based on the WLCG Common JWT (JSON Web Token) Profile. One of the functionalities that Fermilab experimenters rely on is the ability to automate batch job submission, which in turn depends on the ability to securely refresh and distribute the necessary credentials to experiment job submit points. Thus, with the transition to using tokens for grid operations, we needed to create a service that would obtain, refresh, and distribute tokens for experimenters’ use. This service would avoid the need for experimenters to be experts in obtaining their own tokens and would better protect the most sensitive long-lived credentials. Further, the service needed to be widely scalable, as we are currently keeping credentials active for approximately 15 experiments, each with 1-3 different credentials, and distributing those credentials to 2-20 submit points per experiment, with those numbers steadily increasing. To address these issues, we created and deployed a Managed Tokens service. The service is written in Go, taking advantage of that language’s native concurrency primitives to easily be able to scale operations as we onboard experiments. The service uses as its first credentials a set of kerberos keytabs, stored on the same secure machine that the Managed Tokens service runs on. These kerberos credentials allow the service to use htgettoken via condor_vault_storer to store vault tokens in the HTCondor credential managers (credds) that run on the batch system scheduler machines (HTCondor schedds); as well as downloading a local, shorter-lived copy of the vault token. The kerberos credentials are then also used to distribute copies of the locally-stored vault tokens to experiment submit points. When experimenters schedule jobs to be submitted, these distributed vault tokens are used to access a Hashicorp Vault instance (run separately from the Managed Tokens service), and previously-stored refresh tokens there are used to obtain the bearer token that is submitted with the job. We will discuss here the design of the Managed Tokens service, including elaborating on certain choices we made with regards to concurrent operations, configuration, monitoring, and deployment.

Bhat, Shreyas↗
DOE OSTI2026

Experimental Report: Multi-Instrument Comparison of AAF Size Distribution Instruments

Aerosols are particles suspended in the atmosphere, ranging in size from nanometers to micrometers. Their size distribution affects key atmospheric processes, including nucleation, coagulation, scavenging, activation, and radiative properties (Seinfeld and Pandis 2016). Aerosol size distribution is a critical parameter in atmospheric science, influencing processes such as cloud formation and radiative forcing. Accurate representation of aerosol size distributions is essential for understanding their impact on climate, air quality, and human health. However, aerosol size and composition vary significantly across time and space due to meteorological conditions and natural or anthropogenic sources. (Wu and Boor 2021). Various instruments are used to measure aerosol size distributions, each with distinct principles, advantages, and limitations. This report begins with an in-depth overview of aerosol size-distribution comparison studies, focusing on the passive cavity aerosol spectrometer probe (PCASP), portable optical particle spectrometer (POPS), ultra-high-sensitivity aerosol spectrometer (UHSAS), aerodynamic particle sizer (APS), and scanning mobility particle sizer (SMPS). All of these instruments are used by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), which commissioned this comparison and report. The report evaluates the strengths and weaknesses of these instruments, highlights their applications, and discusses efforts to merge data from multiple instruments for comprehensive analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Least-cost Optimal Distribution Grid Expansion (LODGE): Utility Pilots

The Least-cost Optimal Distribution Grid Expansion (LODGE) model provides the optimal portfolio of distribution system upgrades—e.g., voltage regulators, feeder reconductoring, transformer upgrades and non-wires alternatives (NWA), such as strategic siting of storage and distributed generation—to interconnect distributed energy resources (DERs) and enable load growth. It can be used to assess grid infrastructure costs and explore policy and regulatory solutions for distribution planning and DER valuation.In 2025, Berkeley Lab conducted three pilot analyses to validate LODGE results with empirical utility data before the model’s first release in 2026. The pilots, done with utilities in Washington, Colorado, and New Mexico, provide examples that illustrate how the model works, what it can do, and the value of the analysis.

Heleno, Miguel↗
DOE OSTI2022

Mapping the Spatial Distribution of Fibrillar Polymorphs in Human Brain Tissue

Alzheimer’s disease (AD) is a neurodegenerative disorder defined by the progressive formation and spread of fibrillar aggregates of Aβ peptide and tau protein. Polymorphic forms of these aggregates may contribute to disease in varying ways since different neuropathologies appear to be associated with different sets of fibrillar structures and follow distinct pathological trajectories that elicit characteristic clinical phenotypes. The molecular mechanisms underlying the spread of these aggregates in disease may include nucleation, replication, and migration all of which could vary with polymorphic form, stage of disease, and region of brain. Given the linkage between mechanisms of progression and distribution of polymorphs, mapping the distribution of fibrillar structures in situ has the potential to discriminate between mechanisms of progression. However, the means of carrying out this mapping are limited. Optical microscopy lacks the resolution to discriminate between polymorphs in situ, and higher resolution tools such as ssNMR and cryoEM require the isolation of fibrils from tissue, destroying relevant spatial information. Here, we demonstrate the use of scanning x-ray microdiffraction (XMD) to map the locations of fibrillar polymorphs of Aβ peptides and tau protein in histological thin sections of human brain tissue. Coordinated examination of serial sections by immunohistochemistry was used to aid in the interpretation of scattering patterns and to put the observations in a broader anatomical context. Scattering from lesions in tissue shown to be rich in Aβ fibrils by immunohistochemistry exhibited scattering patterns with a prototypical 4.7 Å cross-β peak, and overall intensity distribution that compared well with that predicted from high resolution structures. Scattering from lesions in tissue with extensive tau pathology also exhibited a 4.7 Å cross-β peak but with intensity distributions that were distinct from those seen in Aβ-rich regions. In summary, these observations demonstrate that XMD is a rich source of information on the distribution of fibrillar polymorphs in diseased human brain tissue. When used in coordination with neuropathological examination it has the potential to provide novel insights into the molecular mechanisms underlying disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Classification of Intensity Distributions of Transmission Eigenchannels of Disordered Nanophotonic Structures Using Machine Learning

Light-matter interaction optimization in complex nanophotonic structures is a critical step towards the tailored performance of photonic devices. The increasing complexity of such systems requires new optimization strategies beyond intuitive methods. For example, in disordered photonic structures, the spatial distribution of energy densities has large random fluctuations due to the interference of multiply scattered electromagnetic waves, even though the statistically averaged spatial profiles of the transmission eigenchannels are universal. Classification of these eigenchannels for a single configuration based on visualization of intensity distributions is difficult. However, successful classification could provide vital information about disordered nanophotonic structures. Emerging methods in machine learning have enabled new investigations into optimized photonic structures. In this work, we combine intensity distributions of the transmission eigenchannels and the transmitted speckle-like intensity patterns to classify the eigenchannels of a single configuration of disordered photonic structures using machine learning techniques. Specifically, we leverage supervised learning methods, such as decision trees and fully connected neural networks, to achieve classification of these transmission eigenchannels based on their intensity distributions with an accuracy greater than 99%, even with a dataset including photonic devices of various disorder strengths. Simultaneous classification of the transmission eigenchannels and the relative disorder strength of the nanophotonic structure is also possible. Our results open new directions for machine learning assisted speckle-based metrology and demonstrate a novel approach to classifying nanophotonic structures based on their electromagnetic field distributions. These insights can be of paramount importance for optimizing light-matter interactions at the nanoscale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Risk Assessment Framework for Cyber-Physical Security in Distribution Grids with Grid-Edge DERs

Integration of inverter-based distributed energy resources (DERs) is reshaping the landscape of distribution grids to fulfill the socioeconomic, environmental, and sustainability goals. Addressing the technological challenges of DER grid integration requires an adaptive communication layer for efficient DER management and control. This transition has given rise to a cyberphysical system (CPS) architecture within the distribution system, causing new vulnerabilities for cyberphysical attacks. To better address potential threats, this paper presents a comprehensive risk assessment framework for cyberphysical security in distribution grids with grid-edge DERs. The framework incorporates a detailed CPS model accounting for dynamic DER characteristics within the distribution grid. It identifies vulnerabilities in DER communication systems, models attack scenarios, and addresses communication latency crucial for inverter control timescales. Subsequently, the quantification of attack impacts employs an attack probability model including both the vulnerability and criticality of cyber components. The proposed risk assessment framework was validated through testing on the modified IEEE 13-node and 123-node test feeders.

cyberattack↗
DOE OSTI2021

A Novel Feature of Valence Quark Distributions in Hadrons

Examining the evolution of the maximum of valence quark distribution, qV, weighted by Bjorken x, h(x,t)≡xqV(x,t), it is observed that h(x,t) at the peak becomes a one-parameter function; h(xp,t)=Φ(xp(t)), where xp is the position of the peak, t=logQ2, and Q2 is the resolution scale. This observation is used to derive a new model-independent relation which connects the partial derivative of the valence parton distribution functions (PDFs) in xp to the quantum chromodynamics (QCD) evolution equation through the xp derivative of the logarithm of the function Φ(xp(t)). A numerical analysis of this relation using empirical PDFs results in an observation of the exponential form of the Φ(xp(t))=h(xp,t)=CeDxp(t) for leading to next-to-next leading order approximations of PDFs for the range of Q2, covering four orders in magnitude. The exponent, D, of the observed “height-position” correlation function converges with the increase in the order of approximation. This result holds for all the PDF sets considered. A similar relation is observed also for the pion valence quark distribution, indicating that the obtained relation may be universal for any non-singlet partonic distribution. The observed “height-position” correlation is used also to indicate that no finite number of exchanges can describe the analytic behavior of the valence quark distribution at the position of the peak at fixed Q2.

Leon, Christopher↗
DOE OSTI2023

A Wide View of the Galactic Globular Cluster NGC 2808: Red Giant and Horizontal Branch Star Spatial Distributions

Wide-field and deep DECam multiband photometry, combined with HST data for the core of the Galactic globular cluster NGC 2808, allowed us to study the distribution of various stellar subpopulations and stars in different evolutionary phases out to the cluster tidal radius. We used the C ugi = (u - g) - (g - i) index to identify three chemically distinct subpopulations along the red giant branch and compared their spatial distributions. The most light-element-enriched subpopulation (P3) is more centrally concentrated; however, it shows a more extended distribution in the external regions of the cluster compared to the primordial (P1) and intermediate (P2) composition populations. Furthermore, the P3 subpopulation centroid is off-center relative to those of the P1 and P2 groups. We also analyzed the spatial distribution of horizontal branch stars and found that the relative fraction of red horizontal branch stars increases for radial distances larger than ≈1$^{'}_{.}$5, while that of the blue and hotter stars decreases. These new observations, combined with literature spectroscopic measurements, suggest that the red horizontal branch stars are the progeny of all the stellar subpopulations in NGC 2808, i.e., primordial and light-element enhanced, while the blue stars are possibly the result of a combination of the "hot-flasher" and the "helium-enhanced" scenarios. A similar distribution of different red giant branch subpopulations and horizontal branch stars was also found for the most massive Galactic globular cluster, ω Cen, based on combined DECam and HST data, which suggests that the two may share a similar origin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The Effect of the Velocity Distribution on Kilonova Emission

Abstract The electromagnetic emission from the nonrelativistic ejecta launched in neutron star mergers (either dynamically or through a disk wind) has the potential to probe both the total mass and composition of this ejecta. These observations are crucial in understanding the role of these mergers in the production of r -process elements in the Universe. However, many properties of the ejecta can alter the light curves and we must both identify which properties play a role in shaping this emission and understand the effects these properties have on the emission before we can use observations to place strong constraints on the amount of r -process elements produced in the merger. This paper focuses on understanding the effect of the velocity distribution (amount of mass moving at different velocities) for lanthanide-rich ejecta on the light curves and spectra. The simulations use distributions guided by recent calculations of disk outflows and compare the velocity-distribution effects to those of ejecta mass, velocity, and composition. Our comparisons show that uncertainties in the velocity distribution can lead to a factor of 2–4 uncertainties in the inferred ejecta mass based on peak infrared luminosities. We also show that early-time UV or optical observations may be able to constrain the velocity distribution, reducing the uncertainty in the ejecta mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The DREAMS Project: Disentangling the Impact of Halo-to-Halo Variance and Baryonic Feedback on Milky Way Dark Matter Speed Distributions

Dark matter direct detection experiments require information about the local dark matter speed distribution to produce constraints on dark matter candidates, or infer their properties in the event of a discovery. In this paper, we analyze how the uncertainty in the dark matter speed distribution near the Sun is affected by baryonic feedback, halo-to-halo variance, and halo mass. To do so, we harness the statistical power of the new DREAMS cold dark matter simulation suite, which is comprised of 1024 zoom-in Milky Way–mass halos with varied initial conditions as well as cosmological and astrophysical parameters. Applying a normalizing flows emulator to these simulations, we find that the uncertainty in the local dark matter speed distribution is dominated by halo-to-halo variance and, to a lesser extent, uncertainty in host halo mass. Uncertainties in supernova and black hole feedback (from the IllustrisTNG model in this case) are negligible in comparison. Using the DREAMS suite, we present a state-of-the-art prediction for the dark matter speed distribution in the Milky Way. Although the standard halo model is contained within the uncertainty of this prediction, individual galaxies may have distributions that differ from it. Lastly, we apply our DREAMS results to the XENON1T experiment and demonstrate that the astrophysical uncertainties are comparable to the experimental ones, solidifying previous results in the literature obtained with a smaller sample of simulated Milky Way–mass halos.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Algorithm to extract direction in 2D discrete distributions and a continuous Frobenius norm

In this study, we present a novel algorithm for determining directionality in 2D distributions of discrete data. We compare a reference dataset with a known direction to a measured dataset with an unknown direction by the Frobenius norm of the difference (FND) to find the unknown direction. To generalize this concept, we develop a continuous Frobenius norm of the difference (CFND) as a continuous analog of the FND and derive its analytical expression. By relating fitted and normalized 2D Gaussian distributions, we show that the CFND approximates the FND, and we validate this relationship with computer simulations. We find that a first-order approximation of the CFND between two similar Gaussian distributions takes the form of an absolute sine function, offering a simple analytical form with potential for specialized applications in segmented inverse beta decay (IBD) neutrino detectors, astronomy, machine learning, and more. Although this method may easily extend to 3D scalar fields, our focus here is on 2D real-valued fields as it directly applies to directionality. Our methodology consists of modeling a 2D Gaussian distribution, binning the data into a histogram, and encoding it as a square matrix. Rotating this matrix around its geometric center and comparing it to a measured dataset using the FND gives us rotational data that we fit with an absolute sine function. The location of the minimum of this fit is the angle closest to the true angle of the direction in the measured dataset. We present the derivation and discuss initial applications of the CFND in our novel algorithm, demonstrating its success in approximating directionality in 2D distributions.

Data Analysis, Statistics and Probability (physics↗
DOE OSTI2021

Efficacy of a portable, moderate-resolution, fast-scanning differential mobility analyzer for ambient aerosol size distribution measurements

Abstract. Ambient aerosol size distributions obtained with a compact scanning mobility analyzer, the “Spider” differential mobility analyzer (DMA), are compared to those obtained with a conventional mobility analyzer, with specific attention to the effect of mobility resolution on the measured size distribution parameters. The Spider is a 12 cm diameter radial differential mobility analyzer that spans the 10–500 nm size range with 30 s mobility scans. It achieves its compact size by operating at a nominal mobility resolution R=3 (sheath flow = 0.9 L min−1; aerosol flow = 0.3 L min−1) in place of the higher ratio of sheath flow to aerosol flow commonly used. The question addressed here is whether the lower resolution is sufficient to capture key characteristics of ambient aerosol size distributions. The Spider, operated at R=3 with 30 s up- and downscans, was co-located with a TSI 3081 long-column mobility analyzer, operated at R=10 with a 360 s sampling duty cycle. Ambient aerosol data were collected over 26 consecutive days of continuous operation, in Pasadena, CA. Over the 17–500 nm size range, the two instruments exhibit excellent correlation in the total particle number concentrations and geometric mean diameters, with regression slopes of 1.13 and 1.00, respectively. Our results suggest that particle sizing at a lower resolution than typically employed may be sufficient to obtain key properties of ambient size distributions, at least for these two moments of the size distribution. Moreover, it enables better counting statistics, as the wider transfer function for a given aerosol flow rate results in a higher counting rate.

54 ENVIRONMENTAL SCIENCES↗