Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data Center”

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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Observation of Suppressed Charged-Particle Production in Ultrarelativistic Oxygen-Oxygen Collisions

A hot and dense state of nuclear matter, known as the quark-gluon plasma, is created in collisions of ultrarelativistic heavy nuclei. Highly energetic quarks and gluons, collectively referred to as partons, lose energy as they travel through this matter, leading to suppressed production of particles with large transverse momenta (𝑝 T ). Conversely, high-𝑝 T particle suppression has not been seen in proton-lead collisions, raising questions regarding the minimum system size required to observe parton energy loss. Oxygen-oxygen (OO) collisions examine a region of effective system size that lies between these two extreme cases. The CMS detector at the CERN LHC has been used to quantify charged-particle production in inclusive OO collisions for the first time via measurements of the nuclear modification factor (𝑅 AA ). The 𝑅 AA is derived by comparing particle production to expectations based on proton-proton (𝑝⁢𝑝) data and has a value of unity in the absence of nuclear effects. The data for OO and 𝑝⁢𝑝 collisions at a nucleon-nucleon center-of-mass energy $\sqrt{s_{NN}}$ = 5.36 TeV correspond to integrated luminosities of 6.1 nb −1 and 1.02 pb −1 , respectively. The 𝑅 AA is below unity with a minimum of 0.69 ± 0.04 around 𝑝 T = 6 GeV. The data exhibit better agreement with theoretical models incorporating parton energy loss as compared to baseline models without energy loss.

FOS: Physical sciences↗
DOE OSTI2022

Federal Automotive Statistical Tool: FY 2022 Data Call Status & Review Tools [Slides]

This presentation presents an overview of current federal vehicle fleet current data collection efforts covering required information submissions about the motor vehicles, fueling centers, and electric vehicle supply equipment (EVSE) inventory through the Federal Automotive Statistical Tool (FAST). The presentation also provides an overview of the capabilities within FAST to assist federal agency users with reviewing and improving the quality of their fleet data submissions. This presentation is intended for delivery via WebEx at the November 9, 2022 meeting of the DOE-sponsored INTERFUEL working group. FAST is a web-based information management tool developed by INL and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

NXREFINE

NXRefine implements a complete workflow for both data acquisition and reduction of single crystal diffuse x-ray scattering collected as a series of area detector frames during continuous sample rotation. The data are stored in HDF5 files, which conform to the NeXus data format standard. These files contain a comprehensive set of metadata, including the incident wavelength, powder calibration scans used to define detector distances, beam centers, and yaw, pitch, and roll corrections. Automated peak searches of the three-dimensional data arrays define a set of Bragg peaks that are used to define an orientation matrix, defined according to Busing and Levy, which is then used to transform the data from angular coordinates to reciprocal space coordinates using the CCTW program. Multiple rotations at different detector translations and offset rotation axes are combined to ensure that there are no gaps in the reconstructed data, and allow the construction of masks to eliminate detector artifacts due to Compton scattering within the sensor layers. Finally, the data can be transformed into 3D-ΔPDF maps using the punch-and-fill method after symmetrization.

OSBORN, RAYMOND↗
DOE OSTI2026

1990 CATS Household Travel Survey

The Chicago Area Transportation Study (CATS) 1990 Household Travel Survey was a self-administered mail-out mail-back survey. The purpose of the study was to update existing data on travel patterns and characteristics of Chicago residents. CATS surveyed the region on a county-by-county basis with the Chicago Central Business District in collaboration with the Urban Transportation Center of the University of Illinois. The study gathered demographic and travel behavior data from residents of northeastern Illinois who were 14 years old or older. 19,314 households participated in the survey. The study focused on non-work travel by motorized vehicle and by foot, and residents recorded their trips on a single travel day. Transportation-related variables include trip origin and destination, trip purpose, travel time, mode of travel used, vehicle occupancy, and walking distance (if that transit mode was involved).

1Hz data↗
DOE OSTI2024

Privacy Preserving Federated Learning for Advanced Scientific Ecosystems

We present a framework to provide privacy preserving (PP) federating learning (FL) across multiple computational and experimental facilities. This work joins the compute capabilities of National Energy Research Scientific Computing Center (NERSC) and Oak Ridge National Laboratory Research Cloud (ORC) with simulated experimental data, such as those produced at the SLAC National Accelerator Laboratory and Spallation Neutron Source (SNS). We describe the software infrastructure developed to provide privacy for computational and experimental networks. We developed algorithmic privacy across the federated system by embedding database security, computation, and communication into the federation architecture, utilizing scientific tools developed by the experimental community.

Archibald, Rick [ORNL] (ORCID:0000000245389780)↗
DOE OSTI2023

Machine Learning Enabled Sensor Fusion for In-Situ Defect Detection in Laser Powder Bed Fusion

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. The current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques such as X-Ray Computed Tomography (XCT), which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. RTX Technologies Research Center (RTRC) has licensed ORNL’s Peregrine software package – a printer- and camera-agnostic data analytics tool designed specifically for detecting process anomalies using in situ data collected during powder bed printing. The goal of this project was to feed temporally rich, multi-modal sensor data, including visible light, integrated near infrared (NIR), and spatially mapped co-axial melt pool thermal emission data into Peregrine to enable detection of subsurface flaws. XCT data was used as ground truth training data to allow Peregrine’s deep learning algorithms to recognize anomalies in these complex data streams in both test artifacts and industrially relevant geometries. Completion of this program has seen the successful implementation of multi-modal, multi-layer sensor data footprints for training of machine learning models in Peregrine. Flaws detected in XCT data have been successfully detected directly from this in situ data footprint, and initial analyses of the in situ probability-of-detection has been conducted, showing performance levels commensurate with traditional non-destructive evaluation (NDE) methods. The in situ monitoring methodology was then applied to an industrially relevant component that was using post-build NDE, highlighting the utility of the proposed method for hard-to-inspect AM components. As a direct result of this program, two journal manuscripts [1], [2] have been published in Additive Manufacturing, with additional manuscripts planned following program completion.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Determining the nature of magnetism in altermagnetic candidate RuO 2

The terminology “altermagnetism” has recently been adopted to describe collinear magnetic order with no net magnetization and nonrelativisitic, momentum-dependent spin splitting. The archetypal material used to theoretically explore altermagnetism is RuO 2 , but there has been significant debate as to whether RuO 2 possesses magnetic, let alone altermagnetic, order. To address questions surrounding the nature of magnetism in RuO 2 , we combine symmetry-sensitive torque magnetometry and magnetization measurements in single crystals up to 31 T. The data are inconsistent with collinear magnetic order possessing a Néel vector along the 𝑐 axis. Torque magnetometry further demonstrates an isotropic, field-independent magnetic susceptibility within the 𝑎⁢𝑏 plane, indicative of neither a Néel vector within the 𝑎⁢𝑏 plane nor a field-induced Néel vector reorientation. Magnetic quantum oscillations from both techniques reveal a nearly spherical Fermi surface pocket at the Brillouin zone center, in agreement with paramagnetic electronic structure calculations. Taken together, these data indicate that high-quality RuO 2 single crystals are itinerant paramagnets with no detectable long-range magnetic order and, by extension, no altermagnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

PV Variability at the DeSoto Next Generation Solar Energy Center (Cooperative Research and Development Final Report, CRADA Number CRD-11-425)

In order to support the continued integration of utility-scale solar photovoltaic sites into the Florida transmission system and to further enhance our understanding of the effects of cloud-induced output variability on the site and transmission operations, participant elects to enter a Cooperative Research and Development Agreement (CRADA) with the National Renewable Energy Lab (NREL). Under this agreement, NREL will work with participant to instrument their PV plant in DeSoto county FL and obtain solar radiation and power output data. The Florida Power & Light's (FPL) DeSoto Next Generation Energy Center is the largest installed PV plant in the country (25 MW). Our goal is that this site be instrumented and used for research into PV variability and forecasting.

14 SOLAR ENERGY↗
DOE OSTI2025

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Automated Vehicle Feasibility Study

This study collected automated vehicle (AV) performance data on public roadways in Athens, Ohio. The route for the study contained a combination of roads with different functional classifications, conditions, annual average daily traffic, and ownership responsibilities for maintenance and repair. Preparation for the public road deployment was done in a controlled environment at Transportation Research Center’s SMARTCenter, a dedicated AV test facility in East Liberty, Ohio. Researchers analyzed data and extracted insights relevant for both AV developers and infrastructure owners and operators. The study found that rural environments offer a unique set of roadway features such as hills and curves, which can challenge the driving behavior of an AV. Rural regions can also contain a large number of low-traffic gravel roads that lack pavement markings, which appear to be a crucial infrastructure element for operation of current generation AVs. Similarly, the presence of well-maintained lane lines along curves can influence the AV’s roadway departure tendencies. The study found that curvature-related behavior of an AV is also influenced by driving speed on the roadway segment. Such findings were consistent regardless of the time of day along the route or season of data collection. However, commentary about AV performance in active adverse weather cannot be made, as this is still an area of active research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2022 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office (BETO). It allows for the impact of research progress (both directly achieved in-house at the National Renewable Energy Laboratory [NREL] and furnished by partner organizations) to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked toward out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae SOT benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted primarily under NREL research and development projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model. Through partnerships under DISCOVR, collaborators at ASU furnished details on cultivation performance metrics including biomass productivity and harvest densities for recent growth trials done at the AzCATI site. The resulting biomass productivity was calculated at 18.5 g/m2/day (ash-free dry weight [AFDW], annual average) for seasonal cultivation of Picochlorum celeri, Tetraselmis striata LANL1001, and Monoraphidium minutum 26B-AM biomass strains at the ASU site. Picochlorum celeri achieved the best productivity from May to September, with Monoraphidium minutum 26B-AM being used in October, November, March, and April, and Tetraselmis striata employed during winter months (December through February). Beyond the standard SOT models, in Appendix C of this report we also present an industry case study evaluating several scenarios reflective of outdoor cultivation data furnished by an industry collaborator. This case study provides a supplementary datapoint on work being performed elsewhere achieving comparable cultivation productivity with more favorable compositional quality, producing biomass enriched in lipids as may be more optimal for conversion upgrading to fuels and products.

09 BIOMASS FUELS↗
DOE OSTI2025

The Atacama Cosmology Telescope: DR6 power spectra, likelihoods and ΛCDM parameters

We present power spectra of the cosmic microwave background (CMB) anisotropy in temperature and polarization, measured from the Data Release 6 maps made from Atacama Cosmology Telescope (ACT) data. These cover 19,000 deg 2 of sky in bands centered at 98, 150 and 220 GHz, with white noise levels three times lower than Planck in polarization. We find that the ACT angular power spectra estimated over 10,000 deg 2 , and measured to arcminute scales in TT, TE and EE, are well fit by the sum of CMB and foregrounds, where the CMB spectra are described by the ΛCDM model. Combining ACT with larger-scale Planck data, the joint P-ACT dataset provides tight limits on the ingredients, expansion rate, and initial conditions of the universe. We find similar constraining power, and consistent results, from either the Planck power spectra or from ACT combined with WMAP data, as well as from either temperature or polarization in the joint P-ACT dataset. When combined with CMB lensing from ACT and Planck, and baryon acoustic oscillation data from the Dark Energy Spectroscopic Instrument (DESI DR1), we measure a baryon density of Ω b h 2 = 0.0226 ± 0.0001, a cold dark matter density of Ω c h 2 = 0.118 ± 0.001, a Hubble constant of H 0 = 68.22 ± 0.36 km/s/Mpc, a spectral index of n s = 0.974 ± 0.003, and an amplitude of density fluctuations of σ 8 = 0.813 ± 0.005. Including the DESI DR2 data tightens the Hubble constant to H 0 = 68.43 ± 0.27 km/s/Mpc; ΛCDM parameters agree between the P-ACT and DESI DR2 data at the 1.6σ level. We find no evidence for excess lensing in the power spectrum, and no departure from spatial flatness. The contribution from Sunyaev-Zel'dovich (SZ) anisotropy is detected at high significance; we find evidence for a tilt with suppressed small-scale power compared to our baseline SZ template spectrum, consistent with hydrodynamical simulations with feedback.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2023 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office (BETO). It allows for the impact of research progress (both directly achieved in-house at the National Renewable Energy Laboratory [NREL] and furnished by partner organizations) to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked toward out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae SOT benchmarking efforts historically focused both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted primarily under NREL research and development projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model. Through partnerships under DISCOVR, collaborators at ASU furnished details on cultivation performance metrics including biomass productivity and harvest densities for recent growth trials done at the AzCATI site. The resulting biomass productivity was calculated at 16.7 g/m 2 /day (ash-free dry weight [AFDW], annual average) for seasonal cultivation of Picochlorum celeri TG2 and Monoraphidium minutum 26B-AM biomass strains at the ASU site. Picochlorum celeri achieved the best productivity from April to September, with Monoraphidium minutum 26B-AM being used between October and March. Tetraselmis striata LANL1001, usually part of the strain rotation in previous cultivation SOTs, was supplanted by Monoraphidium minutum 26B-AM in this year's outdoor cultivation trials. Finally, building from an industry case study presented in the 2022 SOT report, in the Appendix of this report we provide an update on further improved data furnished by an industry collaborator and resultant impacts on economics reflecting several seasonal scenarios. This case study provides a supplementary datapoint on work being performed elsewhere with a more dedicated focus on improved compositional quality, producing biomass enriched in lipids as may be more optimal for conversion upgrading to fuels and products.

09 BIOMASS FUELS↗
DOE OSTI2025

Accelerating discoveries at DIII-D with the Integrated Research Infrastructure

DIII-D research is being accelerated by leveraging high performance computing (HPC) and data resources available through the National Energy Research Scientific Computing Center (NERSC) Superfacility initiative. As part of this initiative, a high-resolution, fully automated, whole discharge kinetic equilibrium reconstruction workflow was developed that runs at the NERSC for most DIII-D shots in under 20 min. This has eliminated a long-standing research barrier and opened the door to more sophisticated analyses, including plasma transport and stability. These capabilities would benefit from being automated and executed within the larger Department of Energy Advanced Scientific Computing Research program’s Integrated Research Infrastructure (IRI) framework. The goal of IRI is to empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. For transport, we are looking at producing flux matched profiles and also using particle tracing to predict fast ion heat deposition from neutral beam injection before a shot takes place. Our starting point for evaluating plasma stability focuses on the pedestal limits that must be navigated to achieve better confinement. This information is meant to help operators run more effective experiments, so it needs to be available rapidly inside the DIII-D control room. So far this has been achieved by ensuring the data is available with existing tools, but as more novel results are produced new visualization tools must be developed. In addition, all of the high-quality data we have generated has been collected into databases that can unlock even deeper insights. This has already been leveraged for model and code validation studies as well as for developing AI/ML surrogates. The workflows developed for this project are intended to serve as prototypes that can be replicated on other experiments and can be run to provide timely and essential information for ITER, as well as next stage fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Reproductive intentions among HIV-negative gay and bisexual men initiating pre-exposure prophylaxis in the Sustainable Health Center Implementation pre-exposure prophylaxis pilot study, 2014–2016

Introduction We assessed reproductive intentions and associated characteristics among men enrolled in the Sustainable Health Center Implementation pre-exposure prophylaxis (PrEP) Pilot (SHIPP) Study. Methods We analyzed baseline data from 1275 men who self-identified as gay or bisexual and participated in the SHIPP study. SHIPP was a cohort study of PrEP implementation in five community health centers in Chicago, Jackson, Philadelphia, and Washington, D.C. conducted from 2014 to 2016. Participants completed audio computer-assisted self-interviews querying intentions to have a child in the future. We estimated the association between participants’ reproductive intentions and their characteristics using Poisson regression models. Results Approximately 47% of participants indicated their intentions to have a child. Black/non-Hispanic (aPR = 1.40; 95% CI: 1.10–1.78) and other/non-Hispanic participants (aPR = 1.40; 95% CI: 1.01–1.93) were more likely to report intentions to have a child than white/non-Hispanic participants. Participants were less likely to report intentions to have children as age increased (18–29 years, reference group; 30–39 years, aPR = 0.80, 95% CI: 0.64–0.99; 40–49 years, aPR = 0.49, 95% CI: 0.33–0.72; 50+ years, aPR = 0.07, 95% CI: 0.02–0.21). Conclusions Clinicians offering PrEP to black and other/non-Hispanic gay and bisexual men should assess their reproductive intentions as family-planning counseling may be an opportunity to introduce PrEP to HIV-negative gay and bisexual men.

Immunology↗
DOE OSTI2021

Data processing methods and data acquisition for samples larger than the field of view in parallel-beam tomography

Parallel-beam tomography systems at synchrotron facilities have limited field of view (FOV) determined by the available beam size and detector system coverage. Scanning the full size of samples bigger than the FOV requires various data acquisition schemes such as grid scan, 360-degree scan with offset center-of-rotation (COR), helical scan, or combinations of these schemes. Though straightforward to implement, these scanning techniques have not often been used due to the lack of software and methods to process such types of data in an easy and automated fashion. The ease of use and automation is critical at synchrotron facilities where using visual inspection in data processing steps such as image stitching, COR determination, or helical data conversion is impractical due to the large size of datasets. Here, we provide methods and their implementations in a Python package, named Algotom, for not only processing such data types but also with the highest quality possible. The efficiency and ease of use of these tools can help to extend applications of parallel-beam tomography systems.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Basin-wide gradients in dolomite d26Mg and 87Sr/86Sr identify the structural centre of the Williston Basin as a source of magnesium for dolomitization of the Middle Devonian Winnipegosis Formation

Dolomitized carbonates in the Williston Basin are common below the Middle Devonian Prairie Evaporite Formation, indicating a plausible role for brine-reflux as the source of Mg for dolomitization. However, the Lower Member Winnipegosis Formation, which directly underlies the evaporite sequence, exhibits dolomite 87Sr/86Sr ratios that are higher than expected for Middle Devonian seawater, instead suggesting that the dolomitizing fluids ascended from the deep basin where present-day formation waters are known to be more radiogenic. This interpretation is supported in this study by Mg isotope data showing a basin-scale gradient of increasing d26Mg values from the deep center (–2.03‰) to the edge (–1.34‰) of the Williston Basin along the lower Member Winnipegosis bed. Dolomite favors light isotopes of Mg when it forms, thus driving dolomitizing solutions, and the produced dolomite, towards heavier isotopic compositions in the direction of fluid flow. However, dolomite is also Mg-deficient when it forms, and its initial Mg isotope composition is susceptible to alteration by fluid-rock interactions occurring later in the depositional history of the deposit. We argue that the Mg isotope gradient in the Lower Member Winnipegosis was created by an ascending flow of isotopically light Mg-bearing fluid that differentially altered an earlier formed brine-reflux dolomite, with more alteration occurring deeper in the basin and less towards to edges. Alteration of pre-existing dolomite by an Mg isotope exchange mechanism requires large supplies of Mg. This fact, and the direction of fluid flow point to the underlying crystalline basement as an important Mg source for dolomitization in the Williston Basin. We speculate that ultramafic rocks supplied the Mg when they were hydrothermally altered during an anomalous heating event that affected the Williston Basin in the Late Devonian / Early Carboniferous. Seismic pumping drove these fluids upwards through fracture networks in the crust, and eventually into the deep center of the Williston Basin along vertically-oriented down-to-the-basement faults, pressuring deep aquifers like the Winnipegosis, which resulted in fluids migrating up the stratigraphic dip of the beds towards the edges of the basin. Plotting and contouring the dolomite d26Mg data on a map of the Williston Basin reveals the pathways taken by the migrating fluids. One prominent pathway extending outwards from the center of the basin towards the northeast bears a strong resemblance to petroleum migration fairways deduced for the underlying Late Ordovician Red River Formation. This study demonstrates that Mg isotopic mapping of large dolomite bodies is a useful tool for deciphering fluid flow histories in sedimentary basins and may assist in locating migrated petroleum and Mississippi Valley Type ore deposits.

Magnesium Isotopes, Strontium Isotopes, Dolomitiza↗
DOE OSTI2020

RedMaPPer: Evolution and Mass Dependence of the Conditional Luminosity Functions of Red Galaxies in Galaxy Clusters

In this work we characterize the luminosity distribution, halo-mass dependence, and redshift evolution of red galaxies in galaxy clusters using the SDSS Data Release 8 redMaPPer cluster sample. We propose a simple prescription for the relationship between the luminosity of both red central and red satellite galaxies and the mass of their host halos, and show that this model is well fit by the data. Using a larger galaxy cluster sample than previously employed in the literature, we find that the luminosities of red central galaxies scale as $\langle \mathrm{log}L\rangle \propto {A}_{L}\mathrm{log}({M}_{200b})$, with A L = 0.39 ± 0.04, and that the scatter of the red central galaxy luminosity at fixed M 200b (${\sigma }_{\mathrm{log}L| M}$) is ${0.23}_{-0.04}^{+0.05}$ dex, with the error bar including systematics due to mis-centering of the cluster finder, photometry, and photometric redshift estimation. Our data prefers a positive correlation between the luminosity of red central galaxies and the observed richness of clusters at a fixed halo mass, with an effective correlation coefficient ${d}_{\mathrm{eff}}={0.36}_{-0.16}^{+0.17}$. The characteristic luminosity of red satellites becomes dimmer from z = 0.3 to z = 0.1 by ~20% after accounting for passive evolution. We estimate the fraction of galaxy clusters where the brightest red galaxy is not the central to be P BNC ~ 20%. We discuss implications of these findings in the context of galaxy evolution and the galaxy–halo connection.

79 ASTRONOMY AND ASTROPHYSICS↗