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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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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-T-471: Improvement of Gamma Knife Treatment Planning Through Tumor Control Probability for Metastatic Brain Tumors

Purpose: The dose–volume histogram (DVH) has been normally accepted as a tool for treatment plan evaluation. However, spatial information is lacking in DVH. As a supplement to the DVH in three-dimensional treatment planning, the differential DVH (DDVH) provides the spatial variation, the size and magnitude of the different dose regions within a region of interest, which can be incorporated into tumor control probability model. This study was to provide a method in evaluating and improving Gamma Knife treatment planning. Methods: 10 patients with brain metastases from different primary tumors including melanoma (#1,#4,#5, #10), breast cancer (#2), prostate cancer (#3) and lung cancer (#6–9) were analyzed. By using Leksell GammaPlan software, two plans were prepared for each patient. Special attention was given to the DDVHs that were different for different plans and were used for a comparison between two plans. Dose distribution inside target and tumor control probability (TCP) based on DDVH were calculated, where cell density and radiobiological parameters were adopted from literature. The plans were compared based on DVH, DDVH and TCP. Results: Using DVH, the coverage and selectivity were the same between plans for 10 patients. DDVH were different between two plans for each patient. The paired t-test showed no significant difference in TCP between the two plans. For brain metastases from melanoma (#1, #4–5), breast cancer (#2) and lung cancer (#6–8), the difference in TCP was less than 5%. But the difference in TCP was about 6.5% for patient #3 with the metastasis from prostate cancer, 10.1% and 178.7% for two patients (#9–10) with metastasis from lung cancer. Conclusion: Although DVH provides average dose–volume information, DDVH provides differential dose– volume information with respect to different regions inside the tumor. TCP provides radiobiological information and adds additional information on improving treatment planning as well as adaptive radiotherapy. Further clinical validation is necessary.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-EF-207-08: Improve Cone Beam CT Using a Synchronized Moving Grid, An Inter-Projection Sensor Fusion and a Probability Total Variation Reconstruction

Purpose: To present a cone beam computed tomography (CBCT) system, which uses a synchronized moving grid (SMOG) to reduce and correct scatter, an inter-projection sensor fusion (IPSF) algorithm to estimate the missing information blocked by the grid, and a probability total variation (pTV) algorithm to reconstruct the CBCT image. Methods: A prototype SMOG-equipped CBCT system was developed, and was used to acquire gridded projections with complimentary grid patterns in two neighboring projections. Scatter was reduced by the grid, and the remaining scatter was corrected by measuring it under the grid. An IPSF algorithm was used to estimate the missing information in a projection from data in its 2 neighboring projections. Feldkamp-Davis-Kress (FDK) algorithm was used to reconstruct the initial CBCT image using projections after IPSF processing for pTV. A probability map was generated depending on the confidence of estimation in IPSF for the regions of missing data and penumbra. pTV was finally used to reconstruct the CBCT image for a Catphan, and was compared to conventional CBCT image without using SMOG, images without using IPSF (SMOG + FDK and SMOG + mask-TV), and image without using pTV (SMOG + IPSF + FDK). Results: The conventional CBCT without using SMOG shows apparent scatter-induced cup artifacts. The approaches with SMOG but without IPSF show severe (SMOG + FDK) or additional (SMOG + TV) artifacts, possibly due to using projections of missing data. The 2 approaches with SMOG + IPSF removes the cup artifacts, and the pTV approach is superior than the FDK by substantially reducing the noise. Using the SMOG also reduces half of the imaging dose. Conclusion: The proposed technique is promising in improving CBCT image quality while reducing imaging dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-F-304-04: Radiosurgery for Vestibular Schwannomas: Tumor Control Probability Analyses and Recommended Reporting Standards

Stereotactic Body Radiation Therapy (SBRT) was introduced clinically more than twenty years ago, and many subsequent publications have reported safety and efficacy data. The AAPM Working Group on Biological Effects of Hypofractionated Radiotherapy/SBRT (WGSBRT) extracted published treatment outcomes data from extensive literature searches to summarize and construct tumor control probability (TCP) and normal tissue complication probability (NTCP) models for six anatomical regions: Cranial, Head and Neck, Thoracic, Abdominal, Pelvic, and Spinal. In this session, we present the WGSBRT’s work for cranial sites, and recurrent head and neck cancer. From literature-based data and associated models, guidelines to aid with safe and effective hypofractionated radiotherapy treatment are being determined. Further, the ability of existing and proposed radiobiological models to fit these data is considered as to the ability to distinguish between the linear-quadratic and alternative radiobiological models such as secondary cell death from vascular damage, immunogenic, or bystander effects. Where appropriate, specific model parameters are estimated. As described in “The lessons of QUANTEC,” (1), lack of adequate reporting standards continues to limit the amount of useful quantitative information that can be extracted from peer-reviewed publications. Recommendations regarding reporting standards are considered, to enable such reviews to achieve more complete characterization of clinical outcomes. 1 Jackson A, Marks LB, Bentzen SM, Eisbruch A, Yorke ED, Ten Haken RK, Constine LS, Deasy JO. The lessons of QUANTEC: recommendations for reporting and gathering data on dose-volume dependencies of treatment outcome. Int J Radiat Oncol Biol Phys. 2010 Mar 1;76(3 Suppl):S155–60. Learning Objectives: Describe the techniques, types of cancer and dose schedules used in treating recurrent H&N cancers with SBRT List the radiobiological models that compete with the linear-quadratic model in explaining the results of hypofractionated RT Describe the dose/volume metrics that are considered safe in SBRT treatment of tumors near the optic structures. Discuss the efficacy of hypofractionation and dosing schedules used in treating vestibular schwannomas Identify some difficulties in modeling TCP and NTCP for cranial tumors treated with hypofractionation. One moderator, Dr. Grimm, designed and holds intellectual property rights to the DVH Evaluator software tool which is an FDA-cleared product in commercial use, and can analyze some of this data. No others have relevant conflicts of interest.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-207B-11: Optimizing Tumor Control Probability in Radiation Therapy Treatment - Application to HDR Cervical Cancer

Purpose: The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor-control-probability(TCP) with an acceptable normal-tissue-complication probability(NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. We design treatment plans that optimize TCP directly and contrast them with the clinical dose-based plans. PET image is incorporated to evaluate gain in TCP for dose escalation. Methods: We build a nonlinear mixed integer programming optimization model that maximizes TCP directly while satisfying the dose requirements on the targeted organ and healthy tissues. The solution strategy first fits the TCP function with a piecewise-linear approximation, then solves the problem that maximizes the piecewise linear approximation of TCP, and finally performs a local neighborhood search to improve the TCP value. To gauge the feasibility, characteristics, and potential benefit of PET-image guided dose escalation, initial validation consists of fifteen cervical cancer HDR patient cases. These patients have all received prior 45Gy of external radiation dose. For both escalated strategies, we consider 35Gy PTV-dose, and two variations (37Gy-boost to BTV vs 40Gy-boost) to PET-image-pockets. Results: TCP for standard clinical plans range from 59.4% - 63.6%. TCP for dose-based PET-guided escalated-dose-plan ranges from 63.8%–98.6% for all patients; whereas TCP-optimized plans achieves over 91% for all patients. There is marginal difference in TCP among those with 37Gy-boosted vs 40Gy-boosted. There is no increase in rectum and bladder dose among all plans. Conclusion: Optimizing TCP directly results in highly conformed treatment plans. The TCP-optimized plan is individualized based on the biological PET-image of the patients. The TCP-optimization framework is generalizable and has been applied successfully to other external-beam delivery modalities. A clinical trial is on-going to gauge the clinical significance. Partially supported by the National Science Foundation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Artificial Reasoning System for Symptom-Based Conditional Failure Probability Estimation Using Bayesian Network

Advances in nuclear power technologies require enhanced capabilities for operator advice and autonomous control. One of the first tasks in the development of such capabilities is the formulation of symptom-based conditional failure probabilities for structures, systems, and components (SSCs) of interest, for which the primary goal is to aid plant personnel in deducing the probabilistic performance status of the monitored SSCs and in detecting impending faults/failure. The task of conditional failure probability estimation is a bidirectional inference problem and shall be logically tackled by the Bayesian network (BN) approach. As a knowledge-based artificial intelligence tool and a probabilistic graphical model, BN offers the capability of reasoning under uncertainty and graphical representation emulating the physical behavior of the target SSC. This paper provides a systematic overview of the BN technique and the software tools for handling implementation of BN models, along with the associated knowledge representation and reasoning paradigm. Both operational data and expert judgement can be readily incorporated into the knowledge base of a BN model. The challenges with data availability are highlighted, and the general approach to target SSC identification is presented. Our focus is upon failure-prone and risk-important balance of plant assets, especially cases having strong operator involvement. An exemplary case study on the failure of a motor-driven centrifugal pump is also conducted to demonstrate the usefulness and technical feasibility of the proposed artificial reasoning system using an expert system shell.

Zhao, Xingang↗
DOE OSTI2016

Imprecise Probability Methods for Weapons UQ

Building on recent work in uncertainty quanti cation, we examine the use of imprecise probability methods to better characterize expert knowledge and to improve on misleading aspects of Bayesian analysis with informative prior distributions. Quantitative approaches to incorporate uncertainties in weapons certi cation are subject to rigorous external peer review, and in this regard, certain imprecise probability methods are well established in the literature and attractive. These methods are illustrated using experimental data from LANL detonator impact testing.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

Interactions of aquatic animals with the ORPC OCGen® in Cobscook Bay, Maine: Monitoring behavior change and assessing the probability of encounter with a deployed MHK device

Commercial viability of the marine hydrokinetic (MHK) energy industry is contingent on numerous and diverse factors. A major factor is the effects deployed devices have on animals. This factor is multi-faceted since it is dependent on the availability of appropriate scientific approaches to detect these effects. One of the animal groups with overlapping distributions of MHK devices are fishes. As such, individual fish behavior is likely to be influenced by the presence and operation of MHK devices. Depending on the scale of deployment there are implications for changes to essential fish habitat and effects that can be explored during deployment of a single device yet most changes are likely to be realized when multiple devices are deployed over large areas. It is not only important to document these effects and examine the need for mitigation, but also determine whether the methods involved can be used within the economic constraints of this nascent industry. The results presented in this report benefit the MHK industry by providing transferrable environmental monitoring approaches for MHK projects, specifically related to the interactions between static and dynamic tidal turbines and fish. In addition, some of the data can be used to generalize conditions (e.g., the temporal periodicity of fish presence in tidal regions and probability of fish encountering a device) at other MHK sites with similar physical conditions and fish assemblages. Ocean Renewable Power Company, LLC (ORPC) deployed and tested a prototype OCGen® tidal module in Cobscook Bay, Maine, in the summer of 2014. University of Maine researchers proposed an approach to inform other researchers, regulators, and industry members of the effects of this deployment on fish. While the approach was specifically applied to the OCGen® module, results are applicable to other pilot projects and inform future array deployments. Research funded under this grant allowed us to quantify fish presence as well as individual and group-level behavior changes in the presence of the deployed OCGen® module along with a bottom support frame from a previously deployed device (TidGen®). Specific objectives associated with fish behavior changes were (1) continuation of two long-term datasets: (a) stationary down-looking hydroacoustic dataset near an MHK device (group-level) and (b) stationary side-looking hydroacoustics near the bottom-support frame of a previously deployed MHK device (individual-level); (2) application of new processing methods to down-looking hydroacoustic datasets to improve fish species identification (group-level); and (3) development of an encounter probability model using data on fish abundance, vertical distribution, and behavior.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Low-Probability High-Consequence (LPHC) Failure Events in Geologic Carbon Sequestration Pipelines and Wells: Framework for LPHC Risk Assessment Incorporating Spatial Variability of Risk

If Carbon dioxide Capture and Storage (CCS) is to be effective in mitigating climate change, it will need to be carried out on a very large scale. This will involve many thousands of miles of dedicated high-pressure pipelines in order to transport many millions of tonnes of CO 2 annually, with the CO 2 delivered to many thousands of wells that will inject the CO 2 underground. The new CCS infrastructure could rival in size the current U.S. upstream natural gas pipeline and well infrastructure. This new infrastructure entails hazards for life, health, animals, the environment, and natural resources. Pipelines are known to rupture due to corrosion, from external forces such as impacts by vehicles or digging equipment, by defects in construction, or from the failure of valves and seals. Similarly, wells are vulnerable to catastrophic failure due to corrosion, cement degradation, or operational mistakes. While most accidents involving pipelines and wells will be minor, there is the inevitable possibility of accidents with very high consequences, especially to public health. The most important consequence of concern is CO 2 release to the environment in concentrations sufficient to cause death by asphyxiation to nearby populations. Such accidents are thought to be very unlikely, but of course they cannot be excluded, even if major engineering effort is devoted (as it will be) to keeping their probability low and their consequences minimized. This project has developed a methodology for analyzing the risks of these rare but high-consequence accidents, using a step-by-step probabilistic methodology. A key difference between risks for pipelines and wells is that the former are spatially distributed along the pipe whereas the latter are confined to the vicinity of the well. Otherwise, the methodology we develop for risk assessment of pipeline and well failures is similar and provides an analysis both of the annual probabilities of accident sequences of concern and of their consequences, and crucially the methodology provides insights into what measures might be taken to mitigate those accident sequences identified as of concern. Mitigating strategies could address reducing the likelihood of an accident sequence of concern, or reducing the consequences, or some combination. The methodology elucidates both local and integrated risks along the pipeline or at the well providing information useful to decision makers at various levels including local (e.g., property owners and town councils), regional (e.g., county and state representatives), and national levels (federal regulators and corporate proponents).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Zirconium and Yttrium (p, d) Surrogate Nuclear Reactions: Measurement and determination of gamma-ray probabilities: Experimental Physics Report

This technical report documents the surrogate reaction method and experimental results used to determine the desired neutron induced cross sections of 87 Y(n,g) and the known 90 Zr(n,g) cross section. This experiment was performed at the STARLiTeR apparatus located at Texas A&M Cyclotron Institute using the K150 Cyclotron which produced a 28.56 MeV proton beam. The proton beam impinged on Y and Zr targets to produce the nuclear reactions 89 Y(p,d) 88 Y and 92 Zr(p,d) 91 Zr. Both particle singles data and particle-gamma ray coincident data were measured during the experiment. This data was used to determine the γ-ray probability as a function of energy for these reactions. The results for the γ-ray probabilities as a function of energy for both these nuclei are documented here. For completeness, extensive tabulated and graphical results are provided in the appendices.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Performance Comparison of Circular and Spherical Error Probable Estimators

This report compares the performance of three Circular Error Probable (CEP) estimators: the Grubbs-Patnaik estimator, a new, non-iterative, radial-integration estimator, and a median estimator. It also compares the performance of two Spherical Error Probable (SEP) estimators. The performance of each estimator is assessed in terms of bias, uncertainty, robustness, and computational complexity. Robustness is evaluated with respect to outliers, variations in the underlying statistical distribution characterizing munition impact positions, and impact-position measurement errors. The performance assessments indicate the radial-integration and Grubbs-Patnaik estimators perform nearly identically providing the statistical distribution of impact-position coordinates is jointly normal with zero means. In that case, both estimators outperform the median estimator by about 2% relative to the true CEP in terms of estimator uncertainty. The bias performance of the radial-integration and median estimators is close to zero for jointly normal impacts, however, the Grubbs-Patnaik estimator can be significantly biased for jointly normal impacts with non-zero means. When the statistical distribution characterizing impact positions is known, but not jointly normal, the radial-integration estimator is superior. In this case, the median estimator also outperforms the Grubbs-Patnaik estimator but is not quite as good as the radial-integration estimator. If the statistical distribution characterizing impacts is unknown and not jointly normal, or if distribution parameters are difficult or impractical to estimate, or if test data is corrupted with outliers, then the median estimator dramatically outperforms the other estimators, especially in terms of estimation bias. Unexpectedly, measurement noise did not significantly degrade the performance of any of the estimators, except for cases with signal to noise ratios less than five. Although the Grubbs-Patnaik estimator has remained the gold standard for CEP estimation for over half a century, the performance assessments indicate the new, non-iterative, radial-integration estimator and the median estimator offer significant advantages and, in most practical real-world conditions, are superior estimators. These estimators are also useful for SEP estimation whereas the Grubbs-Patnaik estimator does not extend to three dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Efficient Failure Probability Calculations and Modeling Interface Debonding in TRISO Particles with BISON

This document constitutes completion of the NEAMS milestone, which is titled Demonstrate efficiency improvements in TRISO failure probability calculations and the effect of debonding on fission product transport in TRISO fuel particles in Bison . In this report we present the development of the following: (1) the anisotropic elasticity model of pyrolytic carbon and extended material models using the local coordinate system for aspherical particle geometry; (2) a capability of modeling interface debonding in TRISO particles; and (3) an efficient high-fidelity approach to calculate the failure probability of TRISO particles. Benchmark problems and AGR-2 tests are used to verify the models and demonstrate these new capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Comprehensive uncertainty quantification (UQ) for full engineering models by solving probability density function (PDF) equation

This report details a new method for propagating parameter uncertainty (forward uncertainty quantification) in partial differential equations (PDE) based computational mechanics applications. The method provides full-field quantities of interest by solving for the joint probability density function (PDF) equations which are implied by the PDEs with uncertain parameters. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known apriori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the driving (dynamics) term of the PDEs based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the dynamics term of the governing PDEs. The efficacy of the method is demonstrated by applying it to two target problems: solid mechanics explicit dynamics with uncertain material model parameters, and reacting hypersonic fluid mechanics with uncertain chemical kinetic rate parameters. A minimally invasive implementation of the method for representative codes SPARC (reacting hypersonics) and NimbleSM (finite- element solid mechanics) and associated software details are described. For solid mechanics demonstration problems the method shows order of magnitudes improvement in accuracy over traditional stochastic collocation. For the reacting hypersonics problem, the method is implemented as a streamline integration and results show very good accuracy for the approximate sample solutions of re-entry flow past the Apollo capsule geometry at Mach 30.

42 ENGINEERING↗
DOE OSTI2022

Exceedance Probabilities and Recurrence Intervals for Extended Power Outages in the United States

Power outages cause significant economic and societal impacts. An increasing likelihood of extreme weather coupled with aging grid infrastructure is leading to a higher prevalence of extended power outages, which can leave customers without power for multiple days or even weeks. Planners at the facility, local, state, and federal levels are interested in resilience solutions to reduce the impacts of extended power outages. Resilience solutions—such as installing backup systems, integrating microgrid solutions, weatherizing buildings, and hardening distribution and transmission components—can reduce the consequences of extended power outages, but these solutions come with increased capital costs. Conducting cost-benefit analyses is important for determining which steps to take to mitigate the impact of power outages without investing in ineffective and cost-prohibitive resilience solutions. The expected benefits of resilience investments depend on the frequency of power outages of various durations, particularly extended outages lasting several hours, days, or weeks. A significant barrier to resilience planning is the lack of publicly available data on the frequency and duration of extended power outages. The absence of outage duration information severely limits the ability to conduct quantitative cost-benefit analyses of resilience investments. This report provides estimates of recurrence intervals and conditional exceedance probabilities for major power outages by U.S. region between 2015 and 2021. Additionally, we provide estimates for grid management, particularly outages caused by California’s public safety power shutoffs (PSPS), and for natural outages caused by major hurricanes. Outage recurrence intervals are the average number of years between outage events, and conditional exceedance probabilities are the likelihoods that a customer who experiences a major power outage will experience an outage exceeding a given duration. Major outage events are those that affect 10,000 or more customers, as defined by the U.S. Department of Energy’s (DOE’s) Electric Emergency Incident and Disturbance Report, called OE-417 (DOE 2020). These results can be applied to determine the likelihood of experiencing long-duration outages, which can be integrated into cost-benefit analyses of resilience solutions and broader energy resilience studies. We developed a methodology to estimate customer outage durations for extended outage events using publicly available data on customer outages. Shorter-duration power outages are relatively common, with customers experiencing on average more than one power outage each year lasting fewer than 12 hours. An outage event lasting between 1 day and 1 week is expected to occur between once every 16 years and once every 42 years, depending on the region, with an average recurrence rate of once every 32 years across the contiguous United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Clear-Sky Probability for the 2023 Annular Solar Eclipse and the 2024 Total Solar Eclipse Using the NREL National Solar Radiation Database

The National Renewable Energy Laboratory (NREL) and collaborators have created a clear-sky probability analysis to help guide viewers to the 2023 annular solar eclipse and the 2024 total solar eclipse. Using cloud and solar data from the NREL National Solar Radiation Database (NSRDB), the analysis provides cloudless-sky probabilities specific to the date, time, and location of each eclipse with a 4-km resolution. Though not intended to be an eclipse weather forecast, the detailed maps can help guide eclipse enthusiasts to likely optimal viewing locations. Additionally, high-resolution data are presented for the centerline of the path of each eclipse, representing the likelihood for cloudless skies and atmospheric clarity. The NSRDB provides industry, academia, and other stakeholders with high-resolution solar irradiance data to support feasibility analyses for photovoltaic and concentrating solar power generation projects.

14 SOLAR ENERGY↗
DOE OSTI2022

Exceedance Probabilities and Recurrence Intervals for Extended Power Outages in the United States

This report provides estimates of recurrence intervals and conditional exceedance probabilities for major power outages by U.S. region between 2015 and 2021. Additionally, we provide estimates for grid management, particularly outages caused by California’s public safety power shutoffs (PSPS), and for natural outages caused by major hurricanes. Outage recurrence intervals are the average number of years between outage events, and conditional exceedance probabilities are the likelihoods that a customer who experiences a major power outage will experience an outage exceeding a given duration. Major outage events are those that affect 10,000 or more customers, as defined by the U.S. Department of Energy’s (DOE’s) Electric Emergency Incident and Disturbance Report, called OE-417 (DOE 2020). These results can be applied to determine the likelihood of experiencing long-duration outages, which can be integrated into cost-benefit analyses of resilience solutions and broader energy resilience studies.

Ericson, Sean↗
DOE OSTI2026

Turbine Damage Probability

Damage probability maps for offshore wind turbines exposed to tropical cyclones (TCs) under both historical and future climate scenarios along the U.S. Atlantic and Gulf Coasts are presented in this dataset. TCs are generated using the Risk Analysis Framework for Tropical Cyclones (RAFT), forced by CMIP6 historical and future global climate simulations. Maximum wind speeds for 20- and 50-year TCs are processed through a fragility function specific to offshore wind (OSW) turbines in order to estimate the probability of damage – specifically yielding and buckling – based on wind speed intensity.

17 WIND ENERGY↗
DOE OSTI2016

z ≳ 7 galaxies with red SPITZER/IRAC [3.6]–[4.5] colors in the full CANDELS data set: The brightest-known galaxies at z ∼ 7–9 and a probable spectroscopic confirmation at z = 7.48

We identify four unusually bright (H {sub 160,AB} < 25.5) galaxies from Hubble Space Telescope (HST) and Spitzer CANDELS data with probable redshifts z ∼ 7–9. These identifications include the brightest-known galaxies to date at z ≳ 7.5. As Y-band observations are not available over the full CANDELS program to perform a standard Lyman-break selection of z > 7 galaxies, we employ an alternate strategy using deep Spitzer/IRAC data. We identify z ∼ 7.1–9.1 galaxies by selecting z ≳ 6 galaxies from the HST CANDELS data that show quite red IRAC [3.6]−[4.5] colors, indicating strong [O iii]+Hβ lines in the 4.5 μm band. This selection strategy was validated using a modest sample for which we have deep Y-band coverage, and subsequently used to select the brightest z ≥ 7 sources. Applying the IRAC criteria to all HST-selected optical dropout galaxies over the full ∼900 arcmin{sup 2} of the CANDELS survey revealed four unusually bright z ∼ 7.1, 7.6, 7.9, and 8.6 candidates. The median [3.6]−[4.5] color of our selected z ∼ 7.1–9.1 sample is consistent with rest-frame [O iii]+Hβ EWs of ∼1500 Å in the [4.5] band. Keck/MOSFIRE spectroscopy has been independently reported for two of our selected sources, showing Lyα at redshifts of 7.7302 ± 0.0006 and 8.683{sub −0.004}{sup +0.001}, respectively. We present similar Keck/MOSFIRE spectroscopy for a third selected galaxy with a probable 4.7σ Lyα line at z {sub spec} = 7.4770 ± 0.0008. All three have H{sub 160}-band magnitudes of ∼25 mag and are ∼0.5 mag more luminous (M {sub 1600} ∼ −22.0) than any previously discovered z ∼ 8 galaxy, with important implications for the UV luminosity function (LF). Our three brightest and highest redshift z > 7 galaxies all lie within the CANDELS-EGS field, providing a dramatic illustration of the potential impact of field-to-field variance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Probability of Forming Gaps in the GD-1 Stream by Close Encounters of Globular Clusters

One of the most intriguing properties of the GD-1 stellar stream is the existence of three gaps. If these gaps were formed by close encounters with dark matter subhalos, the GD-1 stream opens an exciting window through which we can see the size, mass, and velocity distributions of the dark matter subhalos in the Milky Way. However, in order to use the GD-1 stream as a probe of the dark matter substructure, we need to disprove that these gaps are not due to the perturbations from baryonic components of the Milky Way. Here we ran a large number of test-particle simulations to investigate the probability that each of the known globular clusters (GCs) can form a GD-1-like gap, by using the kinematical data of the GD-1 stream and GCs from Gaia early data release 3 and by fully taking the observational uncertainty into account. We found that the probability that all of the three gaps were formed by GCs is as low as 1.7 × 10 -5 , and the expected number of gaps formed by GCs is only 0.057 in our fiducial model. Our result highly disfavors a scenario in which GCs form the gaps. Given that other baryonic perturbers (e.g., giant molecular clouds) are even less likely to form a gap in the retrograde-moving GD-1 stream, we conclude that at least one of the gaps in the GD-1 stream was formed by dark matter subhalos if the gaps were formed by flyby perturbations.

79 ASTRONOMY AND ASTROPHYSICS↗