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At least 991 records · Page 55

Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region

The project Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Rocky Mountain Carbon Capture and Storage (RMCCS) project investigated multiple geologic formations and characterized a local site on the Colorado Plateau for future CCS opportunities. The RMCCS project focused on the Cretaceous Dakota, Jurassic Entrada, and Pennsylvanian Weber Sandstones, the three largest regional formations. All formations in this project are potential CO2 storage resources for future power plants, natural gas processing plants, cement plants, and oil shale development projects. The area adjacent to Craig, Colorado, (Sand Wash Basin) was the area selected for detailed geologic characterization on the RMCCS project. The basin was selected in part because the geology can be extrapolated to other sites on the Colorado Plateau. Field mapping and seismic surveys were conducted to identify and evaluate the basin's structural configuration. A 9,745-foot deep characterization well was drilled to collect 131 feet of core and a suite of geophysical well log data. Petrophysical tests on samples of core were used to calibrate geophysical log data, which can be used to obtain storage resource estimates and evaluate associated uncertainty as well as simulate the hydrologic behavior of injected CO2. A detailed analysis of the primary formations (Dakota, Entrada and Weber sandstones) yielded a more accurate CO2 storage resource assessment for these formations within the Colorado Plateau; RMCCS estimates indicate a total CO2 storage resource of more than 38,000 million metric tons. The characterization of the Sand Wash Basin (2-D seismic surveys, multiple well logs and lithological, petrophysical and geochemical analyses) allowed for a detailed 3-D model to be constructed. The model served as the framework for analyses ranging from CO2 storage resource, injectivity, and subsurface flow to uncertainty estimates to evaluation of risk.

2-D seismic↗

Subtask 1.8 - Investigation of Improved Conductivity and Proppant Applications in the Bakken Formation

Given the importance of hydraulic fracturing and proppant performance for development of the Bakken and Three Forks Formations within the Williston Basin, a study was conducted to evaluate the key factors that may result in conductivity loss within the reservoirs. Various proppants and reservoir rock cores were exposed to several different fracturing and formation fluids at reservoir conditions. The hardness of the rock cores and the strength of the proppants were evaluated prior to and following fluid exposure. In addition, the conductivity of various proppants, as well as formation embedment and spalling, was evaluated at reservoir temperatures and pressures using actual reservoir rock cores. The results of this work suggest that certain fluids may affect both rock and proppant strength, and therefore, fluid exposure needs to be considered in the field. In addition, conductivity decreases within the Bakken Formation appear to be a function of a variety of factors, including proppant and rock strength, as well as formation embedment and spalling. The results of this study highlight the need for advanced conductivity testing, coupled with quantification of formation embedment and spalling. Given the importance of proppant performance on conductivity loss and, ultimately, oil recovery, better understanding the effects of these various factors on proppant and rock strength in the field is vital for more efficient production within unconventional oil and gas reservoirs.

02 PETROLEUM↗

Preliminary Formation Analysis for Compressed Air Energy Storage in Depleted Natural Gas Reservoirs: A Study for the DOE Energy Storage Systems Program

The purpose of this study is to develop an engineering and operational understanding of CAES performance for a depleted natural gas reservoir by evaluation of relative permeability effects of air, water and natural gas in depleted natural gas reservoirs as a reservoir is initially depleted, an air bubble is created, and as air is initially cycled. The composition of produced gases will be evaluated as the three phase flow of methane, nitrogen and brine are modeled. The effects of a methane gas phase on the relative permeability of air in a formation are investigated and the composition of the produced fluid, which consists primarily of the amount of natural gas in the produced air are determined. Simulations of compressed air energy storage (CAES) in depleted natural gas reservoirs were carried out to assess the effect of formation permeability on the design of a simple CAES system. The injection of N 2 (as a proxy to air), and the extraction of the resulting gas mixture in a depleted natural gas reservoir were modeled using the TOUGH2 reservoir simulator with the EOS7c equation of state. The optimal borehole spacing was determined as a function of the formation scale intrinsic permeability. Natural gas reservoir results are similar to those for an aquifer. Borehole spacing is dependent upon the intrinsic permeability of the formation. Higher permeability allows increased injection and extraction rates which is equivalent to more power per borehole for a given screen length. The number of boreholes per 100 MW for a given intrinsic permeability in a depleted natural gas reservoir is essentially identical to that determined for a simple aquifer of identical properties. During bubble formation methane is displaced and a sharp N 2 -methane boundary is formed with an almost pure N 2 gas phase in the bubble near the borehole. During cycling mixing of methane and air occurs along the boundary as the air bubble boundary moves. The extracted gas mixture changes as a function of time and proximity of the bubble boundary to the well. For all simulations reported here, with a formation radius above 50 m the maximum methane composition in the produced gas phase was less than 0.5%. This report provides an initial investigation of CAES in a depleted natural gas reservoir, and the results will provide useful guidance in CAES system investigation and design in the future.

Gardner, William Payton↗

Subtask 2.17 - CO 2 Storage Efficiency in Deep Saline Formations

As the field of carbon capture and storage (CCS) continues to advance, and large-scale implementation of geologic carbon dioxide (CO 2 ) storage progresses, it will be important to understand the potential of geologic formations to store meaningful amounts of CO 2 . Geologic CO 2 storage in deep saline formations (DSFs) has been suggested as one of the best potential methods for reducing anthropogenic CO 2 emission to the atmosphere, and as such, updated storage resource estimation methods will continue to be an important component for the widespread deployment of CCS around the world. While there have been several methodologies suggested in the literature, most of these methods are based on a volumetric calculation of the pore volume of the DSF multiplied by a storage efficiency term and do not consider the effect of site-specific dynamic factors such as injection rate, injection pattern, timing of injection, pressure interference between injection locations, and overall formation pressure buildup. These volumetric methods may be excellent for comparing the potential between particular formations or basins, but they have not been validated through real-world experience or full-formation injection simulations. Several studies have also suggested that the dynamic components of geologic storage may play the most important role in storing CO 2 in DSFs but until now have not directly compared CO 2 storage resource estimates made with volumetric methodologies to estimates made using dynamic CO 2 storage methodologies. In this study, two DSFs, in geographically separate areas with geologically diverse properties, were evaluated with both volumetric and dynamic CO 2 storage resource estimation methodologies to compare the results and determine the applicability of both approaches. In the end, it was determined that the dynamic CO 2 storage resource potential is timedependent and it asymptotically approaches the volumetric CO 2 storage resource potential over very long periods of time in the two systems that were evaluated. These results indicate that the volumetric assessments can be used as long as the appropriate storage efficiency terms are used and it is understood that it will take many wells over very long periods of time to fully realize the storage potential of a target formation. This subtask was funded through the Energy & Environmental Research Center (EERC)– U.S. Department of Energy (DOE) Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FC26-08NT43291. Nonfederal funding was provided by the IEA Greenhouse Gas R&D Programme.

54 ENVIRONMENTAL SCIENCES↗

High-Burnup-Structure (HBS): Model Development in MARMOT for HBS Formation and Stability Under Radiation and High Temperature

A detailed phase field model for the formation of High Burnup Structure (HBS) was developed and implemented in MARMOT. The model treats the HBS formation as an irradiation-induced recrystallization. The model takes into consideration the stored energy associated with dislocations formed under irradiation. The accumulation of radiation damage, hence, increases the system free energy and triggers recrystallization. The increase in the free energy due to the formation of new grain boundaries is offset by the reduction in the free energy by creating dislocation-free grains at the expense of the deformed grains. The model was first used to study the growth of recrystallized flat and circular grains. The model reults were shown to agree well with theorrtical predictions. The case of HBS formation in UO2 was then investigated. It was found that a threshold dislocation density of (or equivalently a threshold burn-up of 33-40 GWd/t) is required for HBS formation at 1200K, which is in good agrrement with theory and experiments. In future studies, the presence of gas bubbles and their effect on the formation and evolution of HBS will be considered.

36 MATERIALS SCIENCE↗

Navy Flight Testing Environmental Data Transfer Format Standard

This document outlines key elements of a data format standard for transferring Navy environmental flight test data between members of the Collaborative Environments Characterization Working Group (CECWG). The plan applies to measured data as well as analyzed or processed data. This plan is intended to foster a more productive collaboration between CECWG members by providing a common interface format such that each agency only has to receive and transmit data in one common format. Ideally, each agency is thus only responsible for translating formats between the native format of each agency’s respective database of flight measurements and this common data transfer format.

97 MATHEMATICS AND COMPUTING↗

A simple json format for storing and exchanging code calculation and experimental results

Calculation codes and code systems give their results in a plethora of different formats and/or files. For instance, MCNP gives a user the MCNP specific output file, the mctal file, the ptrac file, etc. while PARTISN has a PARTISN specific output file and a number of binary files with various kinds of information about the calculation. However, the results we are interested in are always the same. These can be single values such as the effective multiplication factor k eff or the effective delayed neutron fraction β eff . It can be histogram data (such as particle spectra, reaction rates, sensitivity profiles, etc.) or even pointwise data (for example the nuclide composition as a function of time, etc.). It is also worthwhile to note that this would also apply to experimental data that we may wish to compare with as well. Calculation and experimental results can basically be split into two components: attributes (or metadata) and the actual result itself. Attributes represent information about the result that are not necessarily required for its’ interpretation but that are still good to have. Often, these attributes are what we will want to filter results on. This means that these attributes are often the answer to specific questions we may have about the result. The following is a non exhaustive list of such basic questions: what type of result is it: e.g. the effective multiplication factor k eff , the effective delayed neutron fraction β eff , etc.; which case does it relate to: e.g. a specific ICSBEP case such as PU-MET-FAST-001-001; which code and version produced this result: e.g. MCNP 6.2, etc.; which nuclear data library was used to obtain the result: e.g. ENDF/B-VIII.0 or JEFF 3.3; which nuclide and reaction does it apply to (for reaction rates and sensitivity profiles); which volume in the geometry was it calculated in? The second component of the calculation or experimental result is the actual numerical data of the result. It is this data that we want to compare, exchange, plot, interpret, etc. It consists of values with optional uncertainties and units. It also includes the underlying structure (if any structure is required to interpret the result). Depending on the type of result, it may be a single value (e.g. the effective multiplication factor), an array of values (e.g. a reaction rate or particle spectrum) or even a multidimensional array. In order to exchange results between different organisations, for instance for benchmarking, people often resort to spreadsheets or custom text files that need to be filled out. While this approach works well if little information is to be exchanged, it can become cumbersome when dealing with large amounts of data (like for instance particle spectra for thousands of cases). In addition, such an approach does not always capture the metadata we may be interested in to allow for automated processing of these files. The purpose of this report is to propose a standardised json structure to store any type of result and present an associated python interface to interact with these results directly. For such a structure to be useful, it must fulfill a specific set of functional requirements that we try to meet with this proposal. The format must allow for the calculation result to stand by itself. This means that we should not have to look in multiple places to be able to understand it. For example, if the result relates to a particle spectrum, the group structure in which the result is given should be stored with it. The format should be code agnostic. This means that we do not need to know where it came from to understand it. The format should be result type agnostic. This means that the format must be generic enough so that we can even use it for results we have not thought of yet. The format should be relatively easy to interact with through different scripting or programming languages (i.e. the machine interface) while still providing a clean structure that can be used directly by any human.

97 MATHEMATICS AND COMPUTING↗

Elucidating the formation mechanisms of zeolites using data-driven modelling and in-situ characterization

Zeolites are the main solid catalysts used by the chemical industry. The use of zeolites in separations and as shape selective catalysts requires control of the width and connectivity of their pores. 235 distinct zeolite frameworks have been synthesized to date, of over 2 million that have been proposed. Recent work indicates that the limitation is in large part kinetic: new synthetic pathways are required to access new zeolites. Organic cations are used to direct the synthesis towards specific zeolites. However, the molecular mechanisms by which cations direct the nucleation towards specific zeolites is not known. Elucidating these mechanisms is key to realize new zeolites for catalysis and separations, and is the focus of this project. This project developed and implemented a synergistic, data-driven computational and experimental approach to resolve the molecular pathways of nucleation, growth, and polymorph selection of zeolites and the role of organic cations in directing their formation. The project developed computationally efficient and accurate models for the study of the nucleation and growth of pure silica zeolites in molecular simulations, using machine learning with data from experiments. Simulations with these models were integrated with scanning tunneling electron microscopy, computer vision, and deep learning to unveil the molecular pathways of formation of a zeolite. Of particular interest in this project was to elucidate the role of amorphous precursors in the nucleation of the zeolite. Previous experiments indicate that zeolites are born within non-crystalline aggregates in which the silicates and organic cations have local and medium range order similar to that of the zeolite. The organic cations that direct the formation of zeolites and those that direct the formation of ordered mesoporous silicas are similar. We hypothesized that the frustrated attraction that for large organic cations leads to the formation of stable mesophases that direct the synthesis of mesoporous silicas, could promote the formation of metastable mesophases that can assist in the nucleation and polymorph selection of zeolites. The simulations resolved how structure directing agents build crystalline order and showed that mesoscopic pre-ordering occurs is not required to facilitate the nucleation of zeolites, because the synthesis occurs at high driving forces, where the barriers for nucleation are negligible. This project unveiled that polymorph selection in zeolite synthesis occurs after nucleation, opening a distinct area of control through the kinetics of growth and not through nucleation barriers.

36 MATERIALS SCIENCE↗

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerating CO2 Storage Site Characterization through a New Understanding of Favorable Formation Properties and the Impact of Core-Scale Heterogeneities

CO2 sequestration in deep geologic formations can permanently reduce atmospheric CO2 emissions and help to abate climate change. Target formations must undergo a time- and resource-intensive site evaluation process, assessing storage capacity, environmental safety, and suitability for CO2 trapping via reactive transport models based on data from a limited number of core samples. As such, simulations are often simplified and omit heterogeneities in formation properties that may be significant but are not well understood. To facilitate more rapid site assessment, this work first defines the aquifer properties of favorable storage formations through the analysis of promising and active storage sites. Data show quartz is the most prevalent formation mineral with carbonate minerals, highly reactive with injected CO2, present in over 75% of formations. Porosity and permeability data are highly clustered at 10–30% and 10–1000 mD. Field-scale reactive transport simulations are then constructed and used to analyze CO2 trapping efficiency. The models consider porosity and carbonate mineral heterogeneity as well as the impacts of typical temperature gradients. Simulated sequestration efficiencies are compared to results from a comparable homogenous model to understand the implications of aquifer non-uniformities. The results show a lower sequestration efficiency in the homogeneous model during the injection phase. During the post-injection phase, the homogenization of porosity and carbonate mineralogy results in a higher sequestration efficiency. Incorporating the temperature gradient also increases the sequestration efficiency. Importantly, the maximum deviation between the homogeneous and heterogeneous simulations at the end of the 50-year study period is only ~10%. Larger impacts may be incurred for properties outside the defined, promising ranges suggested here.

Environmental Sciences & Ecology↗

INSIDE-OUT PLANET FORMATION. III. PLANET–DISK INTERACTION AT THE DEAD ZONE INNER BOUNDARY

The Kepler mission has discovered more than 4000 exoplanet candidates. Many of them are in systems with tightly packed inner planets. Inside-out planet formation (IOPF) has been proposed as a scenario to explain these systems. It involves sequential in situ planet formation at the local pressure maximum of a retreating dead zone inner boundary (DZIB). Pebbles accumulate at this pressure trap, which builds up a pebble ring and then a planet. The planet is expected to grow in mass until it opens a gap, which helps to both truncate pebble accretion and also induce DZIB retreat that sets the location of formation of the next planet. This simple scenario may be modified if the planet undergoes significant migration from its formation location. Thus, planet–disk interactions play a crucial role in the IOPF scenario. Here we present numerical simulations that first assess the degree of migration for planets of various masses that are forming at the DZIB of an active accretion disk, where the effective viscosity is undergoing a rapid increase in the radially inward direction. We find that torques exerted on the planet by the disk tend to trap the planet at a location very close to the initial pressure maximum where it formed. We then study gap opening by these planets to assess at what mass a significant gap is created. Finally, we present a simple model for DZIB retreat due to penetration of X-rays from the star to the disk midplane. Overall, these simulations help to quantify both the mass scale of first (“Vulcan”) planet formation and the orbital separation to the location of second planet formation.

79 ASTRONOMY AND ASTROPHYSICS↗

HOW GALACTIC ENVIRONMENT REGULATES STAR FORMATION

In a new simple model I reconcile two contradictory views on the factors that determine the rate at which molecular clouds form stars—internal structure versus external, environmental influences—providing a unified picture for the regulation of star formation in galaxies. In the presence of external pressure, the pressure gradient set up within a self-gravitating turbulent (isothermal) cloud leads to a non-uniform density distribution. Thus the local environment of a cloud influences its internal structure. In the simple equilibrium model, the fraction of gas at high density in the cloud interior is determined simply by the cloud surface density, which is itself inherited from the pressure in the immediate surroundings. This idea is tested using measurements of the properties of local clouds, which are found to show remarkable agreement with the simple equilibrium model. The model also naturally predicts the star formation relation observed on cloud scales and at the same time provides a mapping between this relation and the closer-to-linear molecular star formation relation measured on larger scales in galaxies. The key is that pressure regulates not only the molecular content of the ISM but also the cloud surface density. I provide a straightforward prescription for the pressure regulation of star formation that can be directly implemented in numerical models. Predictions for the dense gas fraction and star formation efficiency measured on large-scales within galaxies are also presented, establishing the basis for a new picture of star formation regulated by galactic environment.

79 ASTRONOMY AND ASTROPHYSICS↗

HOW ENVIRONMENT AFFECTS GALAXY METALLICITY THROUGH STRIPPING AND FORMATION HISTORY: LESSONS FROM THE ILLUSTRIS SIMULATION

Recent studies have found higher galaxy metallicities in richer environments. It is not yet clear, however, whether metallicity-environment dependencies are merely an indirect consequence of environmentally dependent formation histories, or of environmentally related processes directly affecting metallicity. Here, we present a first detailed study of metallicity-environment correlations in a cosmological hydrodynamical simulation, in particular, we focus on the Illustris simulation. Illustris galaxies display similar relations to those observed. Utilizing our knowledge of simulated formation histories, and leveraging the large simulation volume, we construct galaxy samples of satellites and centrals with matching formation histories. This allows us to find that ∼1/3 of the metallicity-environment correlation is due to different formation histories in different environments. This is a combined effect of satellites (in particular, in denser environments) having on average lower z = 0 star formation rates (SFRs), and of their older stellar ages, even at a given z = 0 SFR. Most of the difference, ∼2/3, however, is caused by the higher concentration of star-forming disks of satellite galaxies, as this biases their SFR-weighted metallicities toward their inner, more metal-rich parts. With a newly defined quantity, the “radially averaged” metallicity, which captures the metallicity profile but is independent of the SFR profile, the metallicities of satellites and centrals become environmentally independent once they are matched in formation history. We find that circumgalactic metallicity (defined as rapidly inflowing gas around the virial radius), while sensitive to environment, has no measurable effect on the metallicity of the star-forming gas inside the galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

PANCHROMATIC HUBBLE ANDROMEDA TREASURY. XVI. STAR CLUSTER FORMATION EFFICIENCY AND THE CLUSTERED FRACTION OF YOUNG STARS

We use the Panchromatic Hubble Andromeda Treasury survey data set to perform spatially resolved measurements of star cluster formation efficiency (Γ), the fraction of stellar mass formed in long-lived star clusters. We use robust star formation history and cluster parameter constraints, obtained through color–magnitude diagram analysis of resolved stellar populations, to study Andromeda’s cluster and field populations over the last ∼300 Myr. We measure Γ of 4%–8% for young, 10–100 Myr-old populations in M31. We find that cluster formation efficiency varies systematically across the M31 disk, consistent with variations in mid-plane pressure. These Γ measurements expand the range of well-studied galactic environments, providing precise constraints in an H i-dominated, low-intensity star formation environment. Spatially resolved results from M31 are broadly consistent with previous trends observed on galaxy-integrated scales, where Γ increases with increasing star formation rate surface density (Σ{sub SFR}). However, we can explain observed scatter in the relation and attain better agreement between observations and theoretical models if we account for environmental variations in gas depletion time ( τ {sub dep}) when modeling Γ, accounting for the qualitative shift in star formation behavior when transitioning from a H{sub 2}-dominated to a H i-dominated interstellar medium. We also demonstrate that Γ measurements in high Σ{sub SFR} starburst systems are well-explained by τ {sub dep}-dependent fiducial Γ models.

79 ASTRONOMY AND ASTROPHYSICS↗

ON THE STAR FORMATION PROPERTIES OF VOID GALAXIES

We measure the star formation properties of two large samples of galaxies from the SDSS in large-scale cosmic voids on timescales of 10 and 100 Myr, using H α emission line strengths and GALEX FUV fluxes, respectively. The first sample consists of 109,818 optically selected galaxies. We find that void galaxies in this sample have higher specific star formation rates (SSFRs; star formation rates per unit stellar mass) than similar stellar mass galaxies in denser regions. The second sample is a subset of the optically selected sample containing 8070 galaxies with reliable H i detections from ALFALFA. For the full H i detected sample, SSFRs do not vary systematically with large-scale environment. However, investigating only the H i detected dwarf galaxies reveals a trend toward higher SSFRs in voids. Furthermore, we estimate the star formation rate per unit H i mass (known as the star formation efficiency; SFE) of a galaxy, as a function of environment. For the overall H i detected population, we notice no environmental dependence. Limiting the sample to dwarf galaxies still does not reveal a statistically significant difference between SFEs in voids versus walls. These results suggest that void environments, on average, provide a nurturing environment for dwarf galaxy evolution allowing for higher specific star formation rates while forming stars with similar efficiencies to those in walls.

79 ASTRONOMY AND ASTROPHYSICS↗

THE LOCATION, CLUSTERING, AND PROPAGATION OF MASSIVE STAR FORMATION IN GIANT MOLECULAR CLOUDS

Massive stars are key players in the evolution of galaxies, yet their formation pathway remains unclear. In this work, we use data from several galaxy-wide surveys to build an unbiased data set of ∼600 massive young stellar objects, ∼200 giant molecular clouds (GMCs), and ∼100 young (<10 Myr) optical stellar clusters (SCs) in the Large Magellanic Cloud. We employ this data to quantitatively study the location and clustering of massive star formation and its relation to the internal structure of GMCs. We reveal that massive stars do not typically form at the highest column densities nor centers of their parent GMCs at the ∼6 pc resolution of our observations. Massive star formation clusters over multiple generations and on size scales much smaller than the size of the parent GMC. We find that massive star formation is significantly boosted in clouds near SCs. However, whether a cloud is associated with an SC does not depend on either the cloud’s mass or global surface density. These results reveal a connection between different generations of massive stars on timescales up to 10 Myr. We compare our work with Galactic studies and discuss our findings in terms of GMC collapse, triggered star formation, and a potential dichotomy between low- and high-mass star formation.

79 ASTRONOMY AND ASTROPHYSICS↗

VLA AND ALMA IMAGING OF INTENSE GALAXY-WIDE STAR FORMATION IN z ∼ 2 GALAXIES

We present ≃0.″4 resolution extinction-independent distributions of star formation and dust in 11 star-forming galaxies (SFGs) at z = 1.3–3.0. These galaxies are selected from sensitive blank-field surveys of the 2′ × 2′ Hubble Ultra-Deep Field at λ = 5 cm and 1.3 mm using the Karl G. Jansky Very Large Array and Atacama Large Millimeter/submillimeter Array. They have star formation rates (SFRs), stellar masses, and dust properties representative of massive main-sequence SFGs at z ∼ 2. Morphological classification performed on spatially resolved stellar mass maps indicates a mixture of disk and morphologically disturbed systems; half of the sample harbor X-ray active galactic nuclei (AGNs), thereby representing a diversity of z ∼ 2 SFGs undergoing vigorous mass assembly. We find that their intense star formation most frequently occurs at the location of stellar-mass concentration and extends over an area comparable to their stellar-mass distribution, with a median diameter of 4.2 ± 1.8 kpc. This provides direct evidence of galaxy-wide star formation in distant blank-field-selected main-sequence SFGs. The typical galactic-average SFR surface density is 2.5 M {sub ⊙} yr{sup −1} kpc{sup −2}, sufficiently high to drive outflows. In X-ray-selected AGN where radio emission is enhanced over the level associated with star formation, the radio excess pinpoints the AGNs, which are found to be cospatial with star formation. The median extinction-independent size of main-sequence SFGs is two times larger than those of bright submillimeter galaxies, whose SFRs are 3–8 times larger, providing a constraint on the characteristic SFR (∼300 M {sub ⊙} yr{sup −1}) above which a significant population of more compact SFGs appears to emerge.

79 ASTRONOMY AND ASTROPHYSICS↗

Star Formation Activity Beyond the Outer Arm. I. WISE -selected Candidate Star-forming Regions

The outer Galaxy beyond the Outer Arm provides a good opportunity to study star formation in an environment significantly different from that in the solar neighborhood. However, star-forming regions in the outer Galaxy have never been comprehensively studied or cataloged because of the difficulties in detecting them at such large distances. We studied 33 known young star-forming regions associated with 13 molecular clouds at R {sub G} ≥ 13.5 kpc in the outer Galaxy with data from the Wide-field Infrared Survey Explorer ( WISE ) mid-infrared all-sky survey. From their color distribution, we developed a simple identification criterion of star-forming regions in the outer Galaxy with the WISE color. We applied the criterion to all the WISE sources in the molecular clouds in the outer Galaxy at R {sub G} ≥ 13.5 kpc detected with the Five College Radio Astronomy Observatory (FCRAO) {sup 12}CO survey of the outer Galaxy, of which the survey region is 102.°49 ≤ l ≤ 141.°54, −3.°03 ≤ b ≤ 5.°41, and successfully identified 711 new candidate star-forming regions in 240 molecular clouds. The large number of samples enables us to perform the statistical study of star formation properties in the outer Galaxy for the first time. This study is crucial to investigate the fundamental star formation properties, including star formation rate, star formation efficiency, and initial mass function, in a primordial environment such as the early phase of the Galaxy formation.

79 ASTRONOMY AND ASTROPHYSICS↗