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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Informed total-error-minimizing priors: Interpretable cosmological parameter constraints despite complex nuisance effects

While Bayesian inference techniques are standard in cosmological analyses, it is common to interpret resulting parameter constraints with a frequentist intuition. This intuition can fail, for example, when marginalizing high-dimensional parameter spaces onto subsets of parameters, because of what has come to be known as projection effects or prior volume effects. We present the method of informed total-error-minimizing (ITEM) priors to address this problem. An ITEM prior is a prior distribution on a set of nuisance parameters, such as those describing astrophysical or calibration systematics, intended to enforce the validity of a frequentist interpretation of the posterior constraints derived for a set of target parameters (e.g., cosmological parameters). Our method works as follows. For a set of plausible nuisance realizations, we generate target parameter posteriors using several different candidate priors for the nuisance parameters. We reject candidate priors that do not accomplish the minimum requirements of bias (of point estimates) and coverage (of confidence regions among a set of noisy realizations of the data) for the target parameters on one or more of the plausible nuisance realizations. Of the priors that survive this cut, we select the ITEM prior as the one that minimizes the total error of the marginalized posteriors of the target parameters. As a proof of concept, we applied our method to the density split statistics measured in Dark Energy Survey Year 1 data. We demonstrate that the ITEM priors substantially reduce prior volume effects that otherwise arise and that they allow for sharpened yet robust constraints on the parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Long-run Marginal Emission Rates for Electricity - Workbooks for 2021 Cambium Data

These workbooks contain modeled estimates of long-run marginal emission rates (LRMER) for the contiguous United States. The LRMER is an estimate of the rate of emissions that would be either induced or avoided by a long-term (i.e., more than several years) change in electrical demand. It incorporates both the projected changes to the electric grid, as well as the potential for an incremental change in electrical demand to influence the structural evolution of the grid (i.e., the building and retiring of capital assets, such as generators and transmission lines). It is therefore distinct from the more-commonly-known short-run marginal, which treats grid assets as fixed. The Levelized LRMER worksheet within each workbook is set up to produce a levelized long-run marginal emission rate based on user-provided inputs. These levelized LRMER values are intended for analysts to use when estimating the emissions induced (or avoided) by a long-term change in end-use electricity demand. There are two workbooks that supply the data at two different geographic resolutions: states and GEA regions (20 regions that are similar to, but not exactly the same as, the US EPA's eGRID regions). For more data underlying these emissions factors, see the Cambium 2021 project at https://cambium.nrel.gov/. For more details on the inputs into the scenarios available in the workbooks, see the Standard Scenarios 2021 Report (https://www.nrel.gov/docs/fy22osti/80641.pdf). This data was produced as part of the Cambium project. For more details about the methodology, see the Cambium Documentation: Version 2021 (https://www.nrel.gov/docs/fy22osti/81611.pdf). This data is planned to be updated annually. Information on the latest versions can be found at https://www.nrel.gov/analysis/cambium.html.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Evidence of galaxy assembly bias in SDSS DR7 galaxy samples from count statistics

We present observational constraints on the galaxy–halo connection, focusing particularly on galaxy assembly bias from a novel combination of counts-in-cylinders statistics, P(N CIC ), with the standard measurements of the projected two-point correlation function w p (r p ), and number density n gal of galaxies. We measure n gal , w p (r p ), and P(N CIC ) for volume-limited, luminosity-threshold samples of galaxies selected from SDSS DR7, and use them to constrain halo occupation distribution (HOD) models, including a model in which galaxy occupation depends upon a secondary halo property, namely halo concentration. We detect significant positive central assembly bias for the M r < -20.0 and M r <-19.5 samples. Central galaxies preferentially reside within haloes of high concentration at fixed mass. Positive central assembly bias is also favoured in the M r < -20.5 and M r < -19.0 samples. We find no evidence of central assembly bias in the M r < -21.0 sample. We observe only a marginal preference for negative satellite assembly bias in the M r < -20.0 and M r < -19.0 samples, and non-zero satellite assembly bias is not indicated in other samples. Our findings underscore the necessity of accounting for galaxy assembly bias when interpreting galaxy survey data, and demonstrate the potential of count statistics in extracting information from the spatial distribution of galaxies, which could be applied to both galaxy–halo connection studies and cosmological analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A Review of Value of Solar Studies In Theory and In Practice

This brief summarizes a collection of state- and utility-commissioned value-of-solar (VoS) studies and related literature, with a focus on who commissioned the study, which value and cost categories were discussed and/or quantified, and the methods used. Our objective is to compile information on prior VoS studies to inform state regulators and other stakeholders that may pursue related studies or integrate findings into rate design. The brief is organized into three parts: 1) an introduction to distributed solar photovoltaic (DPV) compensation; 2) a review of theoretical research on VoS; and 3) a review of VoS studies. The vast majority of VoS studies have served an informational role of quantifying the net benefits of PV. Three studies were commissioned in states or utility service territories that subsequently implemented VoS tariffs in California, New York, and Austin, Texas. When applied as a tariff, VoS aims to compensate PV output as efficiently as possible by doing so at rates that reflect the marginal benefits and costs of PV through value and cost categories that may vary temporally and/or geographically. This could lead to higher compensation in locations and times where more PV output is more valuable and consequently drive adoption in those locations to provide more societal benefits. Value and cost factors can be broadly grouped into five categories: generation, transmission, distribution, other utility, and other social categories. Those conducting VoS studies must weigh various tradeoffs when deciding which categories to include and quantify. Tradeoffs include prioritizing values based on their magnitude of value or cost impact, as well as taking into account the feasibility of data collection and accurate quantification. Values of higher magnitude and estimation feasibility are quantified in the majority of studies, including the earliest of studies conducted in the 2000s and 2010s. Additionally, some values of higher magnitude but low feasibility in the earliest of studies have become quantifiable in recent years. There are some values with low average system-wide levels but very high magnitude in specific locations or hours. The value magnitude in some cases can be tied to DPV penetration with low value in areas with little congestion and/or low penetration and vice versa. In these cases, values that are easier to quantify are often incorporated, while those that are more difficult are often addressed via a placeholder value. The placeholder value is paired with a discussion around data needs and methods to improve future estimates, as well as a conversation about when these value categories may increase in magnitude and necessitate more rigorous quantification. This brief summarizes findings from two meta-analyses of VoS studies that took place between 2005 and 2018, as well as findings from four additional studies published from 2018 to 2023. Table ES-1 summarizes the various value and cost categories included in each respective study and whether they were quantified, discussed, or omitted. Values such as avoided energy, capacity, transmission capacity, line losses, and avoided environmental costs are quantified in every study. Some categories were deemed harder to quantify and less impactful at the time of the study, so they were discussed but not quantified (e.g., ancillary services). Other categories, including many at the distribution level, were very locationally and/or temporally specific and dependent on high DPV penetration. These were sometimes quantified and at other times discussed. Notably, when it came to utility costs, integration costs were discussed in all cases, though they were deemed to have a small impact. Other utility costs were omitted for the most part; however, the utility-commissioned study (by NorthWestern Energy in Montana) included both lost utility revenue and programmatic/administrative cost categories. While there are some similarities across studies, each had fairly unique methods that are detailed in the body of this brief.

14 SOLAR ENERGY↗
DOE OSTI2021

Smart Meters Enabling Voltage Monitoring and Control Functionalities: The Last-Mile Voltage Stability Issue

It is a demanding yet challenging task to design the next generation of smart meters. This work investigates the new voltage monitoring and control function for the next-generation smart meters, and identifies its added values for power system voltage stability issues. In terms of voltage monitoring, the risk benefit analysis for adding voltage magnitudes to smart meter measurements is presented, and the risk mitigation strategies along with the co-simulation validation via GridLAB-D and NS-3 are proposed, all providing insight into the new function evaluation. In terms of voltage control, a new voltage stability control scheme is developed, which uses voltage measurements from smart meters and utilizes the observability and controllability of distributed energy resources and controllable loads. Different from traditional voltage control schemes focusing on voltage regulation and power quality monitoring from the utility perspective, the proposed control scheme can achieve the maximum real power transfer margin at the end user side, enabling the voltage stability issues being solved at the grid edge, i.e. the last-mile segment. It is the first work that considers voltage monitoring and control collectively for smart meter investment. It can help power engineering community supplement smart meter applications and shape the next-generation smart meters.

42 ENGINEERING↗
DOE OSTI2024

DEM simulation of the compression of crushable sand: does the initial particle shape matter?

Advances in DEM modeling, combined with high-resolution X-ray tomography, opened the way for computer models based on virtual replicas of the particles which preserve nearly all facets of their geometry. This leads to simulation advantages, but also high computational costs. Here we tackle a question stemming from this trend: how accurate should particle models be to ensure accuracy? We address this question for the case of the compression of crushable sand. LS-DEM was used to generate three models of Ottawa sand (exact replicas, ellipsoids, and spheres) from digital images of its grains. Compression-induced crushing was simulated for all sets by tracking evolving size and shape distribution. The results confirm that exact replicas provide the closest match of the measurements. However, intermediate degrees of rendering (e.g. ellipsoids preserving volume and aspect ratio of the real grains) led to satisfactory results only marginally different from those of exact replicas. In conclusion, these findings provide an example of the protocols that may be followed to identify the optimal degree of particle approximation which should be regarded as mandatory to achieve a conscious, sustainable use of computational resources.

58 GEOSCIENCES↗
DOE OSTI2021

Geometric Tail Approximation for Reliability and Survivability

A common problem in developing high-reliability systems is estimating the reliability for a population of components that cannot be 100% tested. The radiation survivability of a population of components is often estimated by testing a very small sample to some multiple of the required specification level, known as an overtest. Given a successful test with a sufficient overtest margin, the population of components is assumed to have the required survivability or radiation reliability. However, no mathematical justification for such claims has been crafted without making aggressive assumptions regarding the statistics of the unknown distribution. Here we illustrate a new approach that leverages geometric bounding arguments founded on relatively modest distribution assumptions to produce conservative estimates of component reliability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Progressing Analysis of Variable Electric Rates (PAVER) Study

The Progressing Analysis of Variable Electric Rates (PAVER) study analyzed the impact of a range of time-varying electric rates on the performance of a regional electric grid and the resulting costs for participating and non-participating customers. This analysis leveraged and extended the work of PNNL’s Distribution System Operator with Transactive (DSO+T) study. Five different rate designs were included: a flat volumetric energy charge, a typical Time of Use (TOU) rate, a dynamic energy (DE) rate (based on wholesale locational marginal prices), a dynamic energy and capacity (DE+C) rate, and, finally, a Block and Swing (B&S) rate that billed customers based on their average load profile at constant pricing, but used the DE+C dynamic price for load deviations from their average profile. These rates were analyzed in a large-scale co-simulation of an entire regional grid with a customer population representative of the current state. A large fraction (80%) of residential and commercial customers were assumed to participate in these time-varying rates with automatically controlled HVAC, water heaters, electric vehicles, and batteries. This study assumed no industrial sector participation. The DE and DE+C rates saw system peak loads reduced by 6-7%, while the large participation in the TOU rate case saw a significant rebound effect and a resulting peak load increase of >5%. The impacts to the annual and peak system demand impacted system wholesale prices and the overall grid operating costs. This cost structure determined the revenue needed to be collected from customers by each rate design. Participating customers on the DE and DE+C rates (located in one of the modeled DSOs) saw reductions in average annual electricity bills of 11-17% with average increases in monthly bill variation of no more than 13%. At such high participation levels, TOU customers saw 10% higher average annual bills (due to system-wide rebound effects) and average increased monthly bill variation of 16%. Residential owners of large flexible loads (such as electric vehicles) saw larger bill savings (17-20%) when on a fully dynamic rate. The presence of on-site generation (such as rooftop solar) did not appear to appreciably change customer outcomes. Customers on the Block and Swing rate did see 6% lower monthly bill variation (as intended) than the flat rate case, but at the expense of appreciable bill savings, which were only 3%, comparable to the savings seen by non-participants. Given this finding we recommend that additional research be conducted into how best various bill protection mechanisms can balance minimizing customer bill variation with providing financial incentives commensurate with the flexibility customers provide. We also recommend that customer outcomes be explored across a range of regions using current actual customer and system cost data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Flattening the Radial Temperature Profile across the Transformational Challenge Reactor Core

The Transformational Challenge Reactor (TCR) program is demonstrating an agile development approach to advanced nuclear reactor design, which has traditionally utilized a linear design process. In leveraging artificial intelligence, additive manufacturing, advanced materials, and cutting-edge modeling and simulation, the TCR program aims to minimize the high cost and lengthy deployment timelines now standard in the nuclear industry. Within a relatively short period of time, a robust and mature advanced gas-cooled reactor was iteratively designed under the TCR program, using these cutting-edge technologies. The TCR is a 3 MWt gas-cooled microreactor fueled with uranium nitride (UN) tristructural isotropic (TRISO) fuel particles. Though manufactured via traditional means, these UN TRISO particles are loaded into additively manufactured silicon carbide (SiC) cans [4]. Once loaded with TRISO particles, the SiC cans are densified using a chemical vapor infiltration process. The additively manufactured SiC enables significantly more freedom in the design of the fuel form than could ever be achieved using traditionally manufactured SiC. The helium coolant, pressurized to 5 MPa, enters the core at 300°C and nominally exits it at 500°C. Typically, the most thermally limiting components in any reactor design are the fuel assemblies in the core center. To provide a wide thermal margin in these central fuel assemblies, the flow may be biased toward the center of the core to more effectively cool these fuel assemblies with more power deposition and flatten the core’s radial temperature distribution. An analytical fluid model of the TCR core was developed to explore methods for biasing the flow away from the cooler outer fuel assemblies and towards the hotter inner ones. Higher-fidelity models developed in STAR-CCM+ 2020.3.1, a computational fluid dynamics code, were then utilized to verify the analytical model’s findings.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Tax Credits for Clean Electricity: The Distributional Impacts of Supply-Push Policies in the Power Sector

We evaluate distributional and efficiency consequences of the bulk power clean electricity tax credits authorized by the 2022 Inflation Reduction Act. To do so, we link detailed electricity capacity expansion, computable general equilibrium, microsimulation, and air pollution models to estimate economic welfare and health incidence across demographic groups. We evaluate trade-offs between policy efficiency and income progressivity by comparing the tax credits to cap-and-trade policies. The tax credits encourage increased clean electricity investment, resulting in a reallocation of capital from elsewhere in the economy, higher prices for capital and other goods, lower power prices, and lower emissions. The tax credits yield progressive outcomes for economic welfare at the expense of efficiency while all modeled policies demonstrate progressivity in health impacts. The health benefits, absent climate benefits, exceed total policy costs and provide greater benefits for low-income and historically marginalized households given coincidence of household locations and emissions exposure intensity.

distributional impacts↗
DOE OSTI2022

Status of the PIP-II Cryoplant

The Proton Improvement Plan-II (PIP-II) is an essential upgrade to the Fermilab accelerator complex featuring a new 800-MeV Superconducting Radio-Frequency (SRF) linear accelerator (Linac). The Linac contains 23 SRF cryomodules with the SRF cavities operating at 2 K, a high temperature thermal shield at 40 K and low temperature intercepts at 4.5 K. The PIP-II cryoplant will provide the necessary cooling for the cryomodules and the cryogenic distribution system interconnecting cryoplant and cryomodules. This paper describes the evolution of the PIP-II cryoplant conceptual design and specifications, including the expected heat loads, required cooling features and the integrated design. The cryoplant capacity margin analysis and fast cool-down mode will also be discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Heterotrimeric G‐protein, Gi1, is involved in the regulation of proliferation, neuronal migration, and dendrite morphology during cortical development in vivo

Abstract Heterotrimeric G‐proteins are composed of α, β, and γ subunits, and function as signal transducers. Critical roles of the α‐subunits of Gi/o family heterotrimeric G‐proteins, Gαi2, and Gαo1, have so far been reported in brain development and neurodevelopmental disorders. In this study, we tried to clarify the role of Gαi1, α‐subunit of another Gi/o family member Gi1, during corticogenesis, based on the recent identification of its gene abnormalities in neurodevelopmental disorders. In western blot analyses, Gαi1 was found to be expressed in mouse brain in a developmental stage‐dependent manner. Morphological analyses revealed that Gαi1 was broadly distributed in cerebral cortex with relatively high expression in the ventricular zone (VZ) at embryonic day (E) 14. Meanwhile, Gαi1 was enriched in membrane area of yet unidentified early mitotic cells in the VZ and the marginal zone at E14. Acute knockdown of Gαi1 with in utero electroporation in cerebral cortex caused cell cycle elongation of the neural progenitor cells and promoted their cell cycle exit. Gαi1‐deficient cortical neurons also exhibited delayed radial migration during corticogenesis, with abnormally elongated leading processes and hampered nucleokinesis. In addition, silencing of Gαi1 prevented basal dendrite development. The migration and dendritic phenotypes were at least partially rescued by an RNAi‐resistant version of Gαi1. Collectively, these results strongly suggest a crucial role of Gi1 in cortical development, and disturbance of its function may cause deficits in synaptic network formation, leading to neurodevelopmental disorders. image

Hamada, Nanako↗
DOE OSTI2020

VADER: A Tool for Criticality Safety Validation

The purpose of criticality safety is to prevent any inadvertent criticality from occurring during the handling or storage of fissile material. Calculations are frequently used to demonstrate that a sufficient subcritical margin exists. Validation is a key aspect of the evaluation process, establishing the suitability, accuracy, and associated uncertainty of the computational method and data to be used for the intended application. The validation process is performed by comparing the results of critical experiments with the calculated results from models of the experiments using the computational method to be validated. Laboratory critical experiments are controlled systems that achieve a k eff of approximately 1 in order to investigate the parameters at which such a critical condition is achieved. The validation parameters that are traditionally applied to safety analysis calculations are the bias and the bias uncertainty . The bias is the deviation of the average k eff of the validation suite from unity. The bias uncertainty accounts for the statistical uncertainty in the bias based on the standard deviation, sample size, and distribution of k eff values of the validation suite. The values of bias and bias uncertainty ensure that the systems predicted to be subcritical by the computational method will indeed be subcritical. The bias and bias uncertainty are often combined to determine an upper subcritical limit (USL) or computational margin that can then be applied to safety analysis calculations. Many methods have been developed by different organizations to calculate the bias and bias uncertainty for various types of criticality analyses. Each of these methods typically requires that the validity of various underpinning statistical assumptions be confirmed to demonstrate that the method is appropriate for the analysis of a given validation suite. An example of the validation decision making flow is shown in Fig.1. As shown in Fig. 1, the analyst performing the validation fits a trend line to the data and performs a test to determine if the trend was a statistically better representation of the data than if it were treated as an uncorrelated sample. If the trend line is a better representation of the data, then the analyst uses any one of a number of trending techniques to determine the bias and bias uncertainty. If a trend is not an appropriate representation of the data, then the analyst proceeds to perform a normality assessment for the data. If the normal assumption can be shown to be acceptable, then the analyst calculates the bias and bias uncertainty with the parametric technique. If the assumption of normality cannot be justified, then the nonparametric technique is used. Once the decision flow has been followed and the appropriate technique has been selected, the bias and bias uncertainty is typically combined with an administrative margin to determine a USL below which calculated values of k eff for safety analysis models can be considered subcritical. The calculations used in each decision are often performed with spreadsheets or with small programs available at various sites performing criticality analyses. Expertise in understanding and interpreting the results must be maintained to perform these calculations. This can often be an error-prone process. Oak Ridge National Laboratory (ORNL) is currently developing the Validation and Data Evaluation Resource (VADER) to simplify and automate the criticality safety validation process and to provide a software quality assurance pedigree to the calculational methods used. This paper discusses the use of the Fulcrum user interface with VADER, the anticipated initial capabilities of VADER to perform validation analyses, and the output from the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Analyzing Impact of Distributed PV Generation on Integrated Transmission & Distribution System Voltage Stability—A Graph Trace Analysis Based Approach

The use of a Graph Trace Analysis (GTA)-based power flow for analyzing the voltage stability of integrated Transmission and Distribution (T&D) networks is discussed in the context of distributed Photovoltaic (PV) generation. The voltage stability of lines and the load carrying capability of buses is analyzed at various PV penetration levels. It is shown that as the PV generation levels increase, an increase in the steady state voltage stability of the system is observed. Moreover, within certain regions of stability margin changes, changes in voltage stability margins of transmission lines are shown to be linearly related to changes in the loading of the lines. Two case studies are presented, where one case study involves a model with eight voltage levels and 784,000 nodes. In one case study, a voltage-stability heat map is used to demonstrate the identification of weak lines and buses.

14 SOLAR ENERGY↗
DOE OSTI2025

A scoping study of far-SOL main-wall protection limiters for steady-state operation of compact pilot plant tokamaks

We present a novel method for handling steady-state heat fluxes incident on the main wall of pilot plant-scale magnetic fusion devices, based on the utilization of protection limiters in the far scrape-off layer (SOL). This method helps avoid large plasma-wall gaps, without excessively compromising blanket performance. We present an optimization algorithm for determining the appropriate size and scale of these protection limiters given (1) probability distributions of SOL plasma parameters and (2) assumed risk tolerance. As part of this optimization, we have developed an analytic description of parallel heat fluxes across limiter shadows, and an objective cost function (the ‘Far-SOL Marginal Cost’) to quantify the impact that different main-wall thermal management design choices have on reactor capital cost. Applying the model to a midscale fusion pilot plant concept shows that making use of far-SOL protection limiters can reduce capital costs on the order of $500 M, relative to naively increasing the plasma-wall gap. Our analysis demonstrates that the far-SOL power decay length is the highest-leverage plasma assumption for thermal loading of the first wall, and the primary cost driver for main wall thermal management. The relative cost efficiency of protection limiters increases as assumptions on the far-SOL heat flux become more pessimistic. The concepts described in this paper motivate the further development of far-SOL protection limiters as part of larger efforts to design economical core-edge-wall compatible solutions for a fusion pilot plant.

Design under uncertainty↗
DOE OSTI2023

Sensitivity Analysis of Effectiveness of FLEX Strategies Using a CDF-Based Importance Measure Under Accident Conditions

One of the lessons learned from the Fukushima Daiichi nuclear power plant (NPP) accident is strengthening the station blackout (SBO) mitigation capabilities by enhancing defense in depth for all existing and new NPPs. One of the possible remedies is diverse and flexible coping strategies (FLEX). The objective of this study is to address the benefits of FLEX in various accident scenarios in terms of both risk and cost. FLEX was originally devised against SBO accidents. In this research, we investigate the fundamental plant responses against accidents considering two fundamentally different cases: accidents that lead to high pressure on the primary side and accidents that lead to low pressure on the primary side. Several uncertainties are associated with the characteristics of the FLEX portable equipment. Specifically, the time for FLEX deployment may depend on several factors such as type of accident, point of injection, availability of safety systems, battery backup timings, and human actions. This study utilizes a dynamic risk assessment framework to analyze accident scenarios and suggests a novel importance measure, which is a cumulative distribution function– based importance metric that characterizes the influence of input distribution on complete output distribution. The importance of the existing and newly developed FLEX strategy based on risk significance is illustrated with examples. The suggested measure provides clear insight into how FLEX affects risk of the whole system and additional risk margins thanks to new safety systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Critical magnetic Reynolds number of the turbulent dynamo in collisionless plasmas

The intracluster medium of galaxy clusters is an extremely hot and diffuse, nearly collisionless plasma, which hosts dynamically important magnetic fields of ~μG strength. Seed magnetic fields of much weaker strength of astrophysical or primordial origin can be present in the intracluster medium. In collisional plasmas, which can be approximated in the magnetohydrodynamical (MHD) limit, the turbulent dynamo mechanism can amplify weak seed fields to strong dynamical levels efficiently by converting turbulent kinetic energy into magnetic energy. However, the viability of this mechanism in weakly collisional or completely collisionless plasma is much less understood. In this study, we explore the properties of the collisionless turbulent dynamo using three-dimensional hybrid-kinetic particle-in-cell simulations. We explore the properties of the collisionless turbulent dynamo in the kinematic regime for different values of the magnetic Reynolds number, Rm, initial magnetic-to-kinetic energy ratio, (E mag /E kin ) i , and initial Larmor ratio, (r Larmor /L box ) i , i.e. the ratio of the Larmor radius to the size of the turbulent system. We find that in the ‘un-magnetized’ regime, (r Larmor /L box ) i > 1, the critical magnetic Reynolds number for the dynamo action Rm crit ≈ 107 ± 3. In the ‘magnetized’ regime, (r Larmor /L box ) i ≲ 1, we find a marginally higher Rm crit = 124 ± 8. We find that the growth rate of the magnetic energy does not depend on the strength of the seed magnetic field when the initial magnetization is fixed. We also study the distribution and evolution of the pressure anisotropy in the collisionless plasma and compare our results with the MHD turbulent dynamo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Examining the self-interaction of dark matter through central cluster galaxy offsets

ABSTRACT While collisionless cold dark matter models have been largely successful in explaining a wide range of observational data, some tensions still exist, and it remains possible that dark matter possesses a non-negligible level of self-interactions. In this paper, we investigate a possible observable consequence of self-interacting dark matter: offsets between the central galaxy and the centre of mass of its parent halo. We examine 23 relaxed galaxy clusters in a redshift range of 0.1–0.3 drawn from clusters in the Dark Energy Survey and the Sloan Digital Sky Survey which have archival Chandra X-ray data of sufficient depth for centre and relaxation determination. We find that most clusters in our sample show non-zero offsets between the X-ray centre, taken to be the centroid within the cluster core, and the central galaxy position. All of the measured offsets are larger, typically by an order of magnitude, than the uncertainty in the X-ray position due to Poisson noise. In all but six clusters, the measured offsets are also larger than the estimated, combined astrometric uncertainties in the X-ray and optical positions. A more conservative cut on concentration to select relaxed clusters marginally reduces but does not eliminate the observed offset. With our more conservative sample, we find an estimated median X-ray to central galaxy offset of $\mu = 6.0 ^{+ 1.4}_{- 1.5}$ kpc. Comparing to recent simulations, this distribution of offsets is consistent with some level of dark matter self-interaction, though further simulation work is needed to place constraints.

79 ASTRONOMY AND ASTROPHYSICS↗