Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “peak estimation”

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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. In this work, by defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

DEMONSTRATION OF A DATA-DRIVEN PHYSICS-BASED APPROACH FOR COMPUTATIONALLY EFFICIENT CFD PREDICTION OF TWO-PHASE BUBBLY FLOW

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale physics-guided data-driven approach, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. By defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

42 ENGINEERING↗
DOE OSTI2025

Achieving a large transverse emittance ratio in the Relativistic Heavy Ion Collider: Beam experiments, analytical estimates, and implications for the Electron-Ion Collider

The Electron-Ion Collider (EIC), to be built at Brookhaven National Laboratory, will collide a polarized high-energy electron beam with polarized proton and light ion beams in the center-of-mass energy range of 20–140 GeV, achieving a maximum peak luminosity of up to 1 × 10 34 cm − 2 s − 1 for the proton and electron collisions. To achieve such a high luminosity, the EIC will employ small, flat beams at the interaction point, which requires a transverse emittance ratio of about 11:1. Since 2017, we have carried out a series of beam experiments to test the feasibility of achieving such a large emittance ratio in the Relativistic Heavy Ion Collider (RHIC). Thanks to the existing stochastic cooling and decoupling feedback system in RHIC, we successfully demonstrated a large transverse emittance ratio of 11:1 with gold ion beams in 2023. In this article, we will present more details and data analysis for these experiments, along with analytical estimates and numerical multiparticle simulations, and provide an outlook for future EIC coupling compensation. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Machine-learning-based estimates of global natural vegetated wetland methane emissions (2000–2025)

Wetlands are the largest natural source of atmospheric methane (CH 4 ), yet comprehensive global budgets are typically delayed by years, preventing a timely understanding of CH 4 sources, sinks, and trends. To reduce this delay, we present a model emulator-driven framework and accompanying workflow that enable timely, continuous emission updates using a machine-learning emulator to reconstruct spatially explicit monthly emission fields at 1° × 1° resolution. We apply this framework to a global dataset of natural vegetated wetland CH 4 emissions to extend the most recent Global Methane Budget (GMB; Saunois et al., 2025) record that covers the 2000–2020 emissions through 2025. In the test data (∼ 30 % of the total dataset), the emulator achieved a global R 2 of 0.65 ± 0.003 (mean ± 95 % CI, hereafter) and an RMSE of 5.49 ± 0.12×10 -3 Tg CH 4 yr −1 . The emulator is trained on 35 GMB model estimates, including 22 process-based models and 13 atmospheric inversions, paired with 10 ensemble realizations of 11 gridded climate predictor variables from atmospheric reanalyses. Our results show that the global mean predicted wetland CH 4 emissions for 2021–2025 (157.8 ± 2.4 Tg CH 4 yr −1 ) are not significantly higher (∼ 0.05 Tg CH 4 yr −1 ) than the 2000–2020 baseline. However, this stability masks a significant hemispheric redistribution of emissions. We detect an increase in Northern Hemisphere (NH) emissions in 2021–2025, with mid- and high-latitudes increasing by 0.76 ± 0.07 and 0.35 ± 0.03 Tg CH 4 yr −1 , respectively, while the tropics and Southern Hemisphere (SH) extratropics show offsetting negative trends (−0.95 ± 0.19 and -0.11 ± 0.02 Tg CH 4 yr −1 , respectively). The predicted emissions are able to capture the low emissions in 2023 in South America linked to El Niño-related drought, as reported by recent studies (Ciais et al., 2026; Quinn et al., 2025). Furthermore, we identify a distinct seasonal amplification of global emission trends that peaks in late boreal summer. This new modeled dataset and operational framework bridge the gap between the latest updated budgets and low-latency monitoring, providing a scalable capacity to frequently update global emission estimates and critical early warnings of regional wetland feedback loops. The data are publicly available at https://doi.org/10.5281/zenodo.18870108 (Li et al., 2026).

Li, Mengze [National University of Singapore (Sing↗
DOE OSTI2021

Modeling Within-Host Dynamics of SARS-CoV-2 Infection: A Case Study in Ferrets

The pre-clinical development of antiviral agents involves experimental trials in animals and ferrets as an animal model for the study of SARS-CoV-2. Here, we used mathematical models and experimental data to characterize the within-host infection dynamics of SARS-CoV-2 in ferrets. We also performed a global sensitivity analysis of model parameters impacting the characteristics of the viral infection. We provide estimates of the viral dynamic parameters in ferrets, such as the infection rate, the virus production rate, the infectious virus proportion, the infected cell death rate, the virus clearance rate, as well as other related characteristics, including the basic reproduction number, pre-peak infectious viral growth rate, post-peak infectious viral decay rate, pre-peak infectious viral doubling time, post-peak infectious virus half-life, and the target cell loss in the respiratory tract. These parameters and indices are not significantly different between animals infected with viral strains isolated from the environment and isolated from human hosts, indicating a potential for transmission from fomites. While the infection period in ferrets is relatively short, the similarity observed between our results and previous results in humans supports that ferrets can be an appropriate animal model for SARS-CoV-2 dynamics-related studies, and our estimates provide helpful information for such studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Geothermal Deep Direct Use for Turbine Inlet Cooling in East Texas

The National Renewable Energy Laboratory (NREL), the Southern Methodist University Geothermal Laboratory (SMU), Eastman Chemical (Longview, TX), and TAS (Houston, TX) evaluated the feasibility of using geothermal heat to improve the performance of a natural-gas power plant in East Texas. The area of interest is the Eastman Chemical plant in Longview, Texas, which is on the northwestern margin of a geologic region known as the Sabine Uplift. The feasibility study focused on determining the potential for accessing a subsurface hot-water geothermal resource within a 10-km radius of the site to provide thermal energy for absorption chillers. Wells within a 20-km radius are included for broader geological comparison to determine the heat flow, temperature-at-depth, field porosity and permeability. The lithologies of most interest are the Lower Cretaceous Trinity Group and Upper Jurassic Cotton Valley Group. The deeper Cotton Valley formations are hotter (averaging 117 to 130°C), yet permeability and porosity are low. The shallower Trinity Group contains more variability in permeability and porosity and lower temperatures averaging about 98 to 117°C. The shallower formations are considered despite the lower temperature because of increased ability to produce larger volumes of water and extract enough heat before reinjection. The complete SMU analysis is available in the National Geothermal Data System (NGDS). Tapping such deep geothermal sources for direct heating (as opposed to power generation) is known as geothermal deep direct use (DDU). Geothermal DDU has potential across a wide swath of the United States but is underutilized due to challenging project economics associated with developing a deep geothermal resource for what are typically small-scale, variable-demand projects. This project examines the feasibility of geothermal energy integration in a natural-gas combined cycle power station in East Texas. The DDU resource is tapped to drive absorption chillers (24/7) for production of chilled water at 5-10°C (41-50°F). This chilled water is stored until needed, which allows for continuous operation with a relatively small-capacity geothermal/absorption chiller system. When conditions are favorable, the chilled water is dispatched to cool the air entering the compressor stage of a gas combustion turbine. This process, known as turbine inlet cooling (TIC), boosts power production during periods of high temperature and high-power demand. Such systems can enhance grid reliability and reduce the cost for peak-demand power. A simulation model of the power plant was developed in IPSEpro software and validated against operational data from the plant. This model allowed the team to estimate the additional power that could be produced by applying TIC under different operating and ambient conditions. Absorption chiller performance was estimated from vendor sources to determine the production rate of chilled water from the geothermal resource. Geothermal drilling and development costs were estimated using NREL's GEOPHIRES 2.0. The expected lower drilling costs in this region led to an estimated cost of geothermal heat of about $4/MMBtu (1.4 cents/kWh t ). The estimated cost for the absorption chillers and TIC hardware were obtained from literature sources and project partners. Hourly data were obtained for weather, natural gas and electricity prices, and plant operating state for 2017, which served as a representative year. NREL estimated the capital cost, operating cost, and additional electricity production and revenue for different combinations of geothermal capacity, chiller capacity, and water storage-tank size. The analysis drove toward smaller geothermal and chiller systems to reduce equipment cost. A relatively low-cost water storage tank accumulated the near-continuous chilled water output for later use when TIC was most valued.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Toward Improved Regional Hydrological Model Performance Using State-Of-The-Science Data-Informed Soil Parameters

Accurate soil moisture and streamflow data are an aspirational need of many hydrologically relevant fields. Model simulated soil moisture and streamflow hold promise but models require validation prior to application. Calibration methods are commonly used to improve model fidelity but misrepresentation of the true dynamics remains a challenge. In this study, we leverage soil parameter estimates from the Soil Survey Geographic (SSURGO) database and the probability mapping of SSURGO (POLARIS) to improve the representation of hydrologic processes in the Weather Research and Forecasting Hydrological modeling system (WRF-Hydro) over a central California domain. Our results show WRF-Hydro soil moisture exhibits increased correlation coefficients ( r ), reduced biases, and increased Kling-Gupta Efficiencies (KGEs) across seven in situ soil moisture observing stations after updating the model's soil parameters according to POLARIS. Compared to four well-established soil moisture data sets including Soil Moisture Active Passive data and three Phase 2 North American Land Data Assimilation System land surface models, our POLARIS-adjusted WRF-Hydro simulations produce the highest mean KGE (0.69) across the seven stations. More importantly, WRF-Hydro streamflow fidelity also increases, especially in the case where the model domain is set up with SSURGO-informed total soil thickness. The magnitude and timing of peak flow events are better captured, r increases across nine United States Geological Survey stream gages, and the mean KGE across seven of the nine gages increases from 0.12 to 0.66. Our pre-calibration parameter estimate approach, which is transferable to other spatially distributed hydrological models, can substantially improve a model's performance, helping reduce calibration efforts and computational costs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Adaptive Extremum Seeking Control Based LCL Filter Resonant Frequency Online Estimation

The LCL filter has been widely used in the grid-tied inverter systems. However, the resonance of the LCL filter can reduce the system stability margin and the control performance. Moreover, the grid impedance variations can lead to the drift of the resonant frequency, which can further worsen the system robustness. Thus, it is important to know the actual resonant frequency of the LCL filter. In this letter, an adaptive extremum seeking control (AESC) based estimation scheme is proposed to estimate the resonant frequency of the LCL filter online. Further by injecting a high-frequency (HF) signal into the inverter output voltage, the AESC scheme can identify the extremum of the LCL filter amplitude response, i.e., resonant peak. The amplitude of injection signal is adaptive based on the inverter HF response, which can address the tradeoff between the dynamic response and inverter output current quality. Most importantly, compare to other method, the proposed scheme has very low computational complexity, which minimizes the burden to the normal inverter controller operation. Stability analysis is given in this letter, and experimental studies are conducted to validate the effectiveness of the proposed scheme.

42 ENGINEERING↗
DOE OSTI2025

Resolving the Valence of Iron Oxides by Resonant Photoemission Spectroscopy

Precisely determining the oxidation states of metal cations within variable-valence transition metal oxides remains a significant challenge, yet it is crucial for understanding and predicting the properties of these technologically important materials. Iron oxides, in particular, exhibit a remarkable diversity of electronic structures due to the variable valence states of iron (Fe 2+ and Fe 3+ ). A quantitative analysis using conventional X-ray photoelectron spectroscopy (XPS) is challenging because of the strong overlap of the Fe 2p XPS peaks from different oxidation states. Here, in this study, we show how this problem can be resolved using Resonant Photoemission Spectroscopy (ResPES), which unambiguously distinguishes Fe oxidation states and spectroscopically estimates the composition ratio of Fe cation valence states in the complex Fe oxides. We demonstrate this in the model case of a FeO 2 monolayer film on Pt(111), showing that the FeO 2 film consists of an equal mixture of Fe 2+ and Fe 3+ cations, yielding an average valence of +2.5, contrary to the +3 valence proposed based on density functional theory (DFT).

Chen, Hao [Lawrence Berkeley National Laboratory (↗
DOE OSTI2026

Sequential Fracture Activation and Stress Evolution During EGS Stimulation at Utah FORGE Revealed by Waveform Cross‐Correlation

Mapping fracture networks in Enhanced Geothermal Systems (EGS) is essential for optimizing reservoir performance, yet complex fracture evolution during stimulation remains difficult to resolve. This study examines the evolution of microseismicity and fracture networks during stage 3 of the 2022 EGS stimulation at the Utah Frontier Observatory for Research in Geothermal Energy site. We map the fracture network represented by 20 clusters of seismic events identified by waveform similarities with cross-correlation. We characterize their geometric properties such as strike, dip, length, and width, and analyze the time evolution of activated fractures. The results reveal a systematic fracture evolution: early activation of pre-existing natural fractures, complex network development during peak injection, and continued activation of less favorably oriented fractures post-injection. Magnitude calibration using the Principal Component Analysis of cross-correlated waveforms improves relative amplitude measurements, refining estimations of the Gutenberg-Richter b-values with spatial variations in b-values suggesting stress re-distribution across the stimulated area. Analysis of the stress state of selected fractures further shows that fractures requiring higher excess pore pressure primarily activate at the end of injection and post-injection, highlighting stress transfer due to pore pressure as a dominant triggering mechanism. These findings provide insights into fracture propagation, stress evolution, and seismic hazard assessment in EGS reservoirs.

Asirifi, Richard [Texas A & M Univ., College Stati↗
DOE OSTI2024

Applicability of alkali beam emission spectroscopy on NSTX-U

Understanding fast pedestal dynamics and turbulent transport in the edge and scrape-off layer (SOL) plasma of spherical tokamaks is crucial for the design and operation of future fusion reactors. The alkali beam emission spectroscopy diagnostic technique offers a means to measure the absolute electron density radial profile and fluctuation amplitude in these regions. Here, in this study, we demonstrate that injecting a sodium neutral beam radially into the plasma and analyzing the light emission from its 3p–3s atomic transition using near-orthogonal viewing angles allows for accurate measurement of the electron density profile and fluctuations in the National Spherical Torus Experiment (NSTX) Upgrade spherical tokamak. Our findings indicate a peak signal-to-noise ratio of 118 in the pedestal and 12 in the SOL under typical NSTX plasma conditions. The spatial resolution for the electron density profile is estimated to be between 2 and 8 mm, while for fluctuation measurements, it ranges from 12 to 15 mm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Implications of Non-Bingham Rheology

One of the key challenges now facing the US Department of Energy (DOE) is the fate of radioactive waste remaining from World War II and the Cold War which is stored underground in tanks some 75 feet in diameter and over 30 feet tall. Over time, the waste has segmented into multiple layers with sludges and slurries at the bottom with salt crust layers often at the top and liquid in between. DOE’s current official baseline plans call for remaining sludges and slurries to be removed from the tanks and converted into a more stable glass waste form. Minimizing worker exposure to radiation drives DOE to use slurry processing techniques to suspend, mobilize, transport, mix, and process the waste. Therefore, a clear and quantitative understanding of Hanford waste rheology is essential for the success of the DOE mission. Historically much of the waste has been characterized using Eugene Bingham’s model more than a century old that provides a straight line fit to higher shear rate data with the intercept suggesting a yield stress and the slope providing the consistency. Yet, Bingham fits overestimate the shear stress at a given shear rate for low to intermediate shear rates, exactly the range of shear rates typically encountered in pipe flow, where shear rates peak along the pipe wall and vanish in the center. This model produces a fictitious yield stress for some of the wastes that do not exhibit yield phenomena. While over estimating the yield stress may be prudent, safe, and conservative for some applications (e.g., pump sizing to ensure that pumps can handle yield stresses), over estimating the rheology may be inaccurate and non-conservative for other applications (e.g., eroding settled particle beds). Therefore, this paper evaluates the slurry rheology of Hanford and Savannah River wastes using a more modern rheological model that fits the full range of experimental data. Although a bias has been recognized and alternative models proposed, the magnitude of this bias and the implications for tank waste have only been qualitatively suggested. The purpose of this paper is to evaluate quantitatively implications of the poor quality of fit between a Bingham model for rheology and experimental data at modest shear rates. We first demonstrate the magnitude of the bias between the data and the Bingham extrapolation. We then evaluate quantitatively the velocity profile under laminar conditions. This analysis shows that the bias may be large (hundreds of percent or more) at modest shear rates and that modest shear rates dominate pipe velocity profiles.

Rheology, Radioactive waste↗
DOE OSTI2020

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in-situ and remote sensing datasets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Magnitude and Waveform of Shock Waves Induced by X-ray Lasers in Water

The high energy densities deposited in materials by focused X-ray laser pulses generate shock waves which travel away from the irradiated region, and can generate complex wave patterns or induce phase changes. We determined the time-pressure histories of shocks induced by X-ray laser pulses in liquid water microdrops, by measuring the surface velocity of the microdrops from images recorded during the reflection of the shock at the surface. Measurements were made with ~30 µm diameter droplets using 10 keV X-rays, for X-ray pulse energies that deposited linear energy densities from 3.5 to 120 mJ/m; measurements were also made with ~60 µm diameter drops for a narrower energy range. At a distance of 15 µm from the X-ray beam, the peak shock pressures ranged from 44 to 472 MPa, and the corresponding time-pressure histories of the shocks had a fast quasi-exponential decay with positive pressure durations estimated to range from 2 to 5 ns. Knowledge of the amplitude and waveform of the shock waves enables accurate modeling of shock propagation and experiment designs that either maximize or minimize the effect of shocks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Lessons learned from the design and operation of a small-scale cross-flow tidal turbine

In 2023, a first-generation prototype of a small-scale marine current turbine was operated in Sequim Bay, Washington (USA) for 141 days. The system, referred to as the Turbine Lander, was the product of a laboratory-to-field effort to develop a system that enables enhanced ocean sensing or vehicle recharge in remote, energetic settings. The turbine consists of a vertical-axis, cantilevered rotor (1.19 m x 0.85 m) with four foils installed on a gravity foundation. A broader range of constraints including the deployment strategy, site characteristics, and estimated loads, drove the system’s design. This work presents the design, characterization, operation, and post-recovery engineering assessment of the Turbine Lander. Pre-deployment characterization efforts yielded a peak power coefficient of approximately 0.3 for the rotor, although system losses resulted in much lower water-to-wire efficiencies under most operating conditions. The results demonstrate the importance of co-design among key components of the powertrain and control systems to achieve acceptable system efficiency across operating conditions.

Co-design↗
DOE OSTI2023

Sea-level rise in Southwest Greenland as a contributor to Viking abandonment

The first records of Greenland Vikings date to 985 CE. Archaeological evidence yields insight into how Vikings lived, yet drivers of their disappearance in the 15th century remain enigmatic. Research suggests a combination of environmental and socioeconomic factors, and the climatic shift from the Medieval Warm Period (~900 to 1250 CE) to the Little Ice Age (~1250 to 1900 CE) may have forced them to abandon Greenland. Glacial geomorphology and paleoclimate research suggest that the Southern Greenland Ice Sheet readvanced during Viking occupation, peaking in the Little Ice Age. Counterintuitively, the readvance caused sea-level rise near the ice margin due to increased gravitational attraction toward the ice sheet and crustal subsidence. We estimate ice growth in Southwestern Greenland using geomorphological indicators and lake core data from previous literature. We calculate the effect of ice growth on regional sea level by applying our ice history to a geophysical model of sea level with a resolution of ~1 km across Southwestern Greenland and compare the results to archaeological evidence. The results indicate that sea level rose up to ~3.3 m outside the glaciation zone during Viking settlement, producing shoreline retreat of hundreds of meters. Sea-level rise was progressive and encompassed the entire Eastern Settlement. Moreover, pervasive flooding would have forced abandonment of many coastal sites. These processes likely contributed to the suite of vulnerabilities that led to Viking abandonment of Greenland. Sea-level change thus represents an integral, missing element of the Viking story.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

S-PLUS DR1 galaxy clusters and groups catalogue using PzWav

ABSTRACT We present a catalogue of 4499 groups and clusters of galaxies from the first data release of the multi-filter (5 broad, 7 narrow) Southern Photometric Local Universe Survey (S-PLUS). These groups and clusters are distributed over 273 deg2 in the Stripe 82 region. They are found using the PzWav algorithm, which identifies peaks in galaxy density maps that have been smoothed by a cluster scale difference-of-Gaussians kernel to isolate clusters and groups. Using a simulation-based mock catalogue, we estimate the purity and completeness of cluster detections: at S/N > 3.3, we define a catalogue that is 80 per cent pure and complete in the redshift range 0.1 < z < 0.4, for clusters with M200 > 1014 M⊙. We also assessed the accuracy of the catalogue in terms of central positions and redshifts, finding scatter of σR = 12 kpc and σz = 8.8 × 10−3, respectively. Moreover, less than 1 per cent of the sample suffers from fragmentation or overmerging. The S-PLUS cluster catalogue recovers ∼80 per cent of all known X-ray and Sunyaev-Zel’dovich selected clusters in this field. This fraction is very close to the estimated completeness, thus validating the mock data analysis and paving an efficient way to find new groups and clusters of galaxies using data from the ongoing S-PLUS project. When complete, S-PLUS will have surveyed 9300 deg2 of the sky, representing the widest uninterrupted areas with narrow-through-broad multi-band photometry for cluster follow-up studies.

Astronomy & Astrophysics↗
DOE OSTI2020

Spectroscopy of 30 P and the abundance of 29 Si in presolar grains

The astrophysical 29 Si(p,γ) reaction is expected to play a key role in determining the final 29 Si yields ejected in nova explosions. Such yields are used to accurately identify the stellar origins of meteoritic stardust and recently, distinctive silicon isotopic ratios have been extracted from a number of presolar grains. Here, the light-ion 28 Si( 3 He,p) fusion-evaporation reaction was used to populate low-spin proton-unbound excited states in the nucleus 30 P that govern the rate of the astrophysical 29 Si(p,γ) reaction. In particular, γ decays were observed from resonances up to E r = 500keV, and key resonances at 217 and 315 keV have now been identified as 2 + and 2¯ levels, respectively. Here, the present paper provides the first estimate of the 217-keV resonance strength and indicates that the strength of the 315-keV resonance, which dominates the rate of the 29 Si(p,γ) reaction over the entire peak temperature range of oxygen-neon novae, is higher than previously expected. As such, the abundance of 29 Si ejected during nova explosions is likely to be less than that predicted by the most recent theoretical models.

20 ≤ A ≤ 38↗