Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cloud connected”

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 361 records · Page 20

A very low frequency radio astronomy observatory on the Moon

Because of terrestrial ionospheric absorption, very little is known of the radio sky beyond 10 m wavelength. An extremely simple, low cost very low frequency radio telescope is proposed, consisting of a large array of short wires laid on the lunar surface, each wire equipped with an amplifier and a digitizer, and connected to a common computer. The telescope could do simultaneous multifrequency observations of much of the visible sky with high resolution in the 10 to 100 m wavelength range, and with lower resolution in the 100 to 1000 m range. It would explore structure and spectra of galactic and extragalactic point sources, objects, and clouds, and would produce detailed quasi-three-dimensional mapping of interstellar matter within several thousand parsecs of the Sun.

Douglas, James N.↗

Perception of interstellar structure - Facing complexity

Some orthodox notions concerning the structure and evolution of star-forming regions are challenged; it is proposed that they arise largely by a dual process in which conceptual models are fashioned after categories which are in great part reflections of observational limitations, and the models are projected onto interpretations of data. Several examples are discussed. The need for internal support of molecular clouds is questioned. It is suggested that the inverse density-size relation often claimed for clouds and accounted for by several theoretical models is an artifact caused by limited dynamic range column density detectability, selection bias, distance uncertainties, and internal density gradients, and is contradicted by several unbiased surveys. Column density structures mapped with a large spatial and column density dynamic range are found to be dominated by irregular, connected, and nested forms on all sides. These features and a technique for the quantification of the complex structure are illustrated with a densely-sampled column density image of the Taurus region constructed from IRAS data.

Scalo, John↗

The HI Environment of Nearby Lyman-alpha Absorbers

We present the results of a VLA and WSRT search for H I emission from the vicinity of seven nearby clouds, which were observed in Ly-alpha absorption with HST toward Mrk 335, Mrk 501, and PKS 2155-304. Around the absorbers, we searched a volume of 4O' x 40' x 1000 km/s; for one of the absorbers we probed a velocity range of only 600 km/s. The H I mass sensitivity (5 sigma) very close to the lines of sight varies from 5 x 10(exp 6) solar mass at best to 5 x 10(exp 8) solar mass at worst. We detected H I emission in the vicinity of four out of seven absorbers. The closest galaxy we find to the absorbers is a small dwarf galaxy at a projected distance of 68 h(exp -1) kpc from the sight line toward Mrk 335. This optically uncataloged galaxy has the same velocity (V = 1970 km/s) as one of the absorbers, is fainter than the SMC, and has an H I mass of only 4 x 10(exp 7) solar mass. We found a somewhat more luminous galaxy at exactly the velocity (V = 5100 km/s) of one of the absorbers toward PKS 2155-304 at a projected distance of 230 h(exp -1) kpc from the sight line. Two other, stronger absorbers toward PKS 2155-304 at V approx. 17,000 km/s appear to be associated with a loose group of three bright spiral galaxies, at projected distances of 300 to 600 h(exp -1) kpc. These results support the conclusions emerging from optical searches that most nearby Ly-alpha forest clouds trace the large-scale structures outlined by the optically luminous galaxies, although this is still based on small-number statistics. We do not find any evidence from the H I distribution or kinematics that there is a physical association between an absorber and its closest galaxy. While the absorbing clouds are at the systemic velocity of the galaxies, the H I extent of the galaxies is fairly typical, and at least an order of magnitude smaller than the projected distance to the sight line at which the absorbers are seen. On the other hand, we also do not find evidence against such a connection. In total, we detected H I emission from five galaxies, of which two were previously uncataloged and one did not have a known redshift. No H I emission was detected from the vicinity of the two absorbers, which are located in a void and a region of very low galaxy density; but the limits are somewhat less stringent than for the other sight lines. These results are similar to what has been found in optically unbiased H I surveys. Thus, presence of Ly-alpha absorbers does not significantly alter the H I detection rate in their environment.

VanGorkom, J. H.↗

Self-Assembled Thermoresponsive Molecular Brushes as Nanoreactors for Asymmetric Aldol Addition in Water

The manipulation and tunability of self-assembled block copolymers through external stimuli presents an attractive strategy to develop smart polymer-based nanoreactors as supports for non-orthogonal tandem catalysis. We report on thermoresponsive core-shell micelles based on poly[norbornene-poly(2-methyl-2-oxazoline-block-2-propyl-2-oxazoline)]-graft-poly[norbornene L-proline] (P[NB-P(MeOx-b-PropOx)]-graft-P[NB-L-proline]) as catalyst supports for L-proline. These molecular brushes exhibit large differences in lower critical solution temperature behavior and nanostructure size in water depending on the chain-lengths and proline connectivity. L-Proline-mediated aldol reactions expose the efficiency by which the molecular brushes self-assemble into micelles. Molecular brushes with an extended backbone show higher activity and selectivity, suggesting better core-shell segregation of the micelles and exclusion of water from the catalytic site. Catalytic efficiencies are not improved above the cloud point temperature, the catalytic be-havior is rather sensitive to conformational changes of the polymer chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interstellar/Precometary Organic Material and the Photochemical Evolution of Complex Organics

During the past two decades ground-, air-, and space-based infrared spectroscopic observations, combined with realistic laboratory simulations, have revolutionized our understanding of interstellar ice and dust, the raw materials from which planets, comets and stars form. Most interstellar material is concentrated in Large molecular clouds where simple molecules are formed by dust grain and gas phase reactions. Gaseous species striking the cold (10 K) dust will stick, forming an icy grain mantle. This accretion, coupled with energetic particle bombardment and UV photolysis, will produce a complex chemical mixture containing volatile, non-volatile, and isotopically fractionated species. Ices in molecular clouds contain the very simple molecules H2O, CH3OH, CO, CO2, H2, and perhaps some NH3 and H2CO, as well as more complex species including nitriles and ketones or esters. The evidence for these compounds as well as carbon rich materials such as polycyclic aromatic hydrocarbons (PAHs), microdiamonds, and amorphous carbon will be reviewed and the possible connections with comets and meteorites will be presented in the first part of the talk. The second part of the presentation will focus on interstellar/precometary ice photochemical evolution. The chemical composition and photochemical evolution of realistic interstellar/pre-cometary ice analogs containing methanol will be discussed. ultraviolet photolysis of these ices produces H2, H2CO, CO2, CO, CH4, HCO, and more complex molecules. Infrared spectroscopy, H-1 and C-13 nuclear magnetic resonance (NMR) spectroscopy, and gas chromatography-mass spectrometry demonstrate that when ices representative of interstellar grains and comets are exposed to UV radiation at low temperature a series of moderately complex organic molecules are formed in the ice including: CH3CH2OH (ethanol), HC(=O)NH2 (formamide), CH3C(=O)NH2 (acetamide), and R-C(integral)N (nitriles). Several of these are already known to be in the interstellar medium, and their presence indicates the importance of grain processing. After warming to room temperature what remains is an organic residue composed primarily of Hexamethylenetetramine (HMT, C6H12N4), with lesser amounts of polyoxymethylene related species (POMs), amides, and ketones. This is in sharp contrast to the organic residues produced by irradiating ices which do not contain methanol (unrealistic interstellar ice analogs) or thermally promoted polymerization-type reactions in unirradiated realistic ice mixtures. Here HMT is only a minor product in a residue dominated by a mixture of polyoxymethylene related species. The implications, for infrared astronomy and astrochemistry, of high concentrations of HMT in interstellar and cometary ices may be profound. The ultraviolet photolysis of HMT frozen in H20 ice produces the "XCN" band observed in the spectra of protostellar objects and laboratory ices, as well as carbon oxides and other nitriles. Thus, HMT may be a precursor of XCN in protostellar objects and a source of CN and CO in the tail of comets. Also, HMT is known to hydrolyze under acidic conditions to yield ammonia and formaldehyde as well as amino acids. Thus, HMT may have been a source of organic material delivered to the early earth by comets.

Allamandola, Lou J.↗

A Machine Learning Correction Model of the Winter Clear-Sky Temperature Bias over the Arctic Sea Ice in Atmospheric Reanalyses

Atmospheric reanalyses are widely used to estimate the past atmospheric near-surface state over sea ice. They provide boundary conditions for sea ice and ocean numerical simulations and relevant information for studying polar variability and anthropogenic climate change. Previous research revealed the existence of large near-surface temperature biases (mostly warm) over the Arctic sea ice in the current generation of atmospheric reanalyses, which is linked to a poor representation of the snow over the sea ice and the stably stratified boundary layer in the forecast models used to produce the reanalyses. These errors can compromise the employment of reanalysis products in support of polar research. Here, we train a fully connected neural network that learns from remote sensing infrared temperature observations to correct the existing generation of uncoupled atmospheric reanalyses (ERA5, JRA-55) based on a set of sea ice and atmospheric predictors, which are themselves reanalysis products. The advantages of the proposed correction scheme over previous calibration attempts are the consideration of the synoptic weather and cloud state, compatibility of the predictors with the mechanism responsible for the bias, and a self-emerging seasonality and multidecadal trend consistent with the declining sea ice state in the Arctic. The correction leads on average to a 27% temperature bias reduction for ERA5 and 7% for JRA-55 if compared to independent in situ observations from the MOSAiC campaign (respectively, 32% and 10% under clear-sky conditions). These improvements can be beneficial for forced sea ice and ocean simulations, which rely on reanalyses surface fields as boundary conditions.

54 ENVIRONMENTAL SCIENCES↗

Accelerating Nuclear-Integrated Data Centers in the USA: SWOT Analysis, Power-Thermal Management Strategies, and Industrial-Scale Demonstration and Potential Deployment

Driven by the growth in digital services, cloud computing, AI, and manufacturing, data centers face rising energy demands that challenge traditional power sources and cooling efficiency. This study explores using nuclear power to meet these demands, focusing on accelerated reactor technology deployment and highlighting needs such as N+1/N+2 power supplies and integrated power-thermal management. A SWOT analysis addresses grid connectivity, reactors, and site selection, particularly DOE sites. Reactor technology demonstration and deployment could be accelerated by leveraging test facilities such as MARVEL, MAGNET, TED, FAS, DOME, LOTUS, ATR, Energy System Proving Grounds, and upcoming Energy Launch Pads, along with modeling and simulation tools such as RELAP5, MOOSE, VERA, RAVEN, and FORCE. The potential power and thermal management options, including various cooling technologies, waste-heat utilization, and an industrial-scale demonstration plan, aim to accelerate the integration of nuclear power and data centers in the USA, while emphasizing community and stakeholder engagement and synergistic efforts.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Bimodal SLD Ice Accretion on a NACA 0012 Airfoil Model

An initial ice shape database has been created to document ice accretions on a 21-inch chord NACA 0012 airfoil model resulting from an exposure to a Supercooled Large Droplet (SLD) icing cloud with a bimodal droplet distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. The icing conditions used in the test matrix were based upon previously measured ice shapes on the same model to connect the current database to previously measured information. Ice shapes resulting from the bimodal distribution as well as from equivalent standard droplet distributions were obtained and compared. Results indicate that the ice shapes resulting from the bimodal droplet distributions had higher mass and volume values than their standard distribution equivalents as well as having icing limits that extended further back on the chord of the model.

aircraft icing↗

Science Objectives of the ACCP/AOS Millimeter- and Submillimeter-Wave Radiometers

Passive microwave radiometers provide highly useful information regarding the Earth system by measuring thermal emission (from the surface and atmosphere) that is reflected, absorbed, and scattered by the surface and the atmosphere. As such, radiometers have been instrumental across Earth-observing concepts with heritage tracing back to the Nimbus era, and clouds and precipitation have been key geophysical phenomena these sensors have targeted. As millimeter-wave (particularly ≥85 GHz) and submillimeter-wave technologies have advanced, the applicability of microwave radiometers has expanded to encompass falling snow and ice clouds, respectively. Given the strong heritage of microwave radiometry and the emergence of submillimeter-wave sensors for sensing falling snow and ice clouds, the National Academies’ 2017 Decadal Survey for Earth Science and Applications from Space recommended passive sensors covering these wavelengths be included in observing systems that address the Aerosols, Clouds, Convection, and Precipitation (ACCP) combined designated observable. To showcase the capabilities for addressing the ACCP science objectives, we will provide an overview of the passive microwave capabilities envisioned for the Atmosphere Observing System (AOS, part of the recently unveiled NASA Earth System Observatory), including descriptions of the radiometers for the inclined and polar orbits and the primary geophysical variables of interest related to ice-phase clouds and precipitation. We will also discuss secondary science objectives, such as precipitation mapping, that can be achieved with the ACCP/AOS radiometers. Examples from the analyses performed for the ACCP/AOS architecture study and subsequent sensor definition exercises will be presented, outlining the basis for the radiometer configuration within the context of the overarching ACCP/AOS goals to elucidate the connections between atmospheric dynamics, weather (including extreme events), air quality, and climate.

Ian S Adams↗

Interstellar organics and possible connections with the carbonaceous components of meteorites and IDPs

Studying the chemical and isotopic composition of interstellar ice and dust provides insight into the composition and chemical history of the solid bodies in the solar nebula and the nature of the materials subsequently brought into the inner part of the solar system by comets and meteorites. It is now possible to probe the composition of these microscopic interstellar particles. High quality IR spectra of many different astronomical sources (some associated with dark molecular clouds, and others in the diffuse interstellar medium) are now available. Comparisons of these spectra with laboratory spectra and complex organic components of these materials are discussed.

Allamandola, L. J.↗

Further Examinations of Bimodal SLD Ice Accretion in the NASA Icing Research Tunnel

An ice shape database has been created to document ice accretions on a 72-inch chord NACA 23012 airfoil model resulting from an exposure to a Supercooled Large Drop (SLD) icing cloud with a bimodal drop size distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. The icing conditions used in the test matrix were based upon previously measured ice shapes on the same model to connect the current database to previously measured information. Ice shapes resulting from the bimodal distribution as well as from equivalent mono-modal drop size distributions were obtained and compared. Results indicate that the ice shapes resulting from the bimodal drop size distributions had higher mass and volume values than their mono-modal distribution equivalents as well as having icing limits that extended further back on the chord of the model.

Aircraft↗

Assessing Customer Experience and Business Models around Price-to-Device Communication and Smart Control Pathways in CalFlexHub

California is facing three major challenges in electrical grid operation: renewable overgeneration, steep evening ramping, and growing peak demand. The state has identified dynamic retail price response as a key strategy evidenced by CPUC’s Dynamic Rates proceeding and CEC’s Load Management Standards. Furthermore, the CEC launched a $16M “California Load Flexibility Research and Deployment Hub (CalFlexHub)” administered by Berkeley Lab to accelerate price-response flexible load technologies in buildings and EV charging. There are more than 16 laboratory and field demonstration projects in CalFlexHub, each demonstrating innovative automated price-response technologies. CalFlexHub tests various pathways through which hourly price signals and triggered control commands are communicated to load-flexible devices such as smart thermostats, heat pumps, water heaters, and EVs. We identified seven unique communication and control pathways, which involve combinations of third-party cloud, device OEM’s cloud, building central gateway, and local controller in between the price server and the load-flexible devices. It is important for utilities and policy makers to understand the long-term implications of each pathway in designing future programs and creating related policies and mandates for market transformation. We propose an evaluation framework including the following aspects: ● Functionality: connectivity and uptime, resilience, and optimization; ● Customer experience: simplicity in setup, troubleshooting support, continuity, customer choice, first cost, and ongoing cost; ● Business model and scalability: advance interoperability, holistic solution, bridge unique gap, customer base, and value streams and pricing structures. In this paper, we identify emerging business models associated with each communication pathway and discuss their positive features and challenges from the above aspects.

Liu, Jingjing↗

The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) Activity for Continental Shallow Convection

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility recently initiated the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) activity focused on shallow convection at ARM’s Southern Great Plains (SGP) atmospheric observatory in Oklahoma. LASSO is designed to overcome an oft-shared difficulty of bridging the gap from point-based measurements to scales relevant for model parameterization development, and it provides an approach to add value to observations through modeling. LASSO is envisioned to be useful to modelers, theoreticians, and observationalists needing information relevant to cloud processes. LASSO does so by combining a suite of observations, LES inputs and outputs, diagnostics, and skill scores into data bundles that are freely available, and by simplifying user access to the data to speed scientific inquiry. The combination of relevant observations with observationally constrained LES output provides detail that gives context to the observations by showing physically consistent connections between processes based on the simulated state. A unique approach for LASSO is the generation of a library of cases for days with shallow convection combined with an ensemble of LES for each case. The library enables researchers to move beyond the single-case-study approach typical of LES research. The ensemble members are produced using a selection of different large-scale forcing sources and spatial scales. Since large-scale forcing is one of the most uncertain aspects of generating the LES, the ensemble informs users about potential uncertainty for each date and increases the probability of having an accurate forcing for each case.

54 ENVIRONMENTAL SCIENCES↗

Automatic point Cloud Building Envelope Segmentation (Auto-CuBES) using Machine Learning

Modern retrofit construction practices use 3D point cloud data of the building envelope to obtain the as-built dimensions. However, manual segmentation by a trained professional is required to identify and measure window openings, door openings, and other architectural features, making the use of 3D point clouds labor-intensive. In this study, the Automatic point Cloud Building Envelope Segmentation (Auto-CuBES) algorithm is described, which can significantly reduce the time spent during point cloud segmentation. The Auto-CuBES algorithm inputs a 3D point cloud generated by commonly available surveying equipment and outputs a wire-frame model of the building envelope. Unsupervised machine learning methods were used to identify facades, windows, and doors while minimizing the number of calibration parameters. Additionally, Auto-CuBES generates a heat map of each facade indicating non-planar characteristics that are crucial for the optimization of connections used in overclad envelope retrofits. With a scan resolution of 3 mm, the resulting window dimensions showed a mean absolute error of 4.2 mm compared to manual laser measurements.

Maldonado Puente, Bryan↗

High Resolution Nature Runs and the Big Data Challenge

NASA's Global Modeling and Assimilation Office at Goddard Space Flight Center is undertaking a series of very computationally intensive Nature Runs and a downscaled reanalysis. The nature runs use the GEOS-5 as an Atmospheric General Circulation Model (AGCM) while the reanalysis uses the GEOS-5 in Data Assimilation mode. This paper will present computational challenges from three runs, two of which are AGCM and one is downscaled reanalysis using the full DAS. The nature runs will be completed at two surface grid resolutions, 7 and 3 kilometers and 72 vertical levels. The 7 km run spanned 2 years (2005-2006) and produced 4 PB of data while the 3 km run will span one year and generate 4 BP of data. The downscaled reanalysis (MERRA-II Modern-Era Reanalysis for Research and Applications) will cover 15 years and generate 1 PB of data. Our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS), a specialization of the concept of business process-as-a-service that is an evolving extension of IaaS, PaaS, and SaaS enabled by cloud computing. In this presentation, we will describe two projects that demonstrate this shift. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS. MERRA/AS enables MapReduce analytics over MERRA reanalysis data collection by bringing together the high-performance computing, scalable data management, and a domain-specific climate data services API. NASA's High-Performance Science Cloud (HPSC) is an example of the type of compute-storage fabric required to support CAaaS. The HPSC comprises a high speed Infinib and network, high performance file systems and object storage, and a virtual system environments specific for data intensive, science applications. These technologies are providing a new tier in the data and analytic services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. In our experience, CAaaS lowers the barriers and risk to organizational change, fosters innovation and experimentation, and provides the agility required to meet our customers' increasing and changing needs

big data analysis↗

Datum: A Scientific Metadata Catalog

The data catalog market is currently flooded with a myriad of different products, but none serve the scientific community well. There are cloud-native tools like Databricks, Snowflake,to on-premise solutions like Collibra and Datahub. The common failing of all these tools however, is their inability to serve the scientific data community directly. Most catalogs are targeted towards financial, health, or user data - not sensor or scientific domain data. They also prioritize integrations that often don’t exist or are just starting to be used in the scientific realm - all while ignoring common scientific tools and file types. Datum is a catalog which targets the scientific data directly, including the tools and networks in which those tools are used. We work with the producers and consumers of the data where they are, targeting cloud and on-premise with a focus on classified networks. Datum is an Erlang/Elixir application. Technical Features Note: The features listed below are still under development and may change, slightly, upon final delivery of the product. File Formats - Datum has the ability to read additional metadata and provides processing pipelines for the following file formats: Plain Text, PDF, LaTeX, HTML, Open Document Format (.odt), XML, CSV/TSV (and other standard delimiters), OpenDocument Database and Spreadsheets, Geo-Referenced TIFF, Common Data Format, HDF/HDF5, LabView TDMS, Excel, DeltaTables, Parquet, Apache Iceberg, Apache Hudi and many others. Metadata Collection - Scanners for the local and networked file systems and cloud storage providers. Network integration with common databases such as MSSQL and MySQL. User Plugin System - Users are able to provide either file processing, metadata extraction, or sampling plugins in the programming language of their choice. Authentication/Authorization -: OIDC integration, SCIM provisioning and EntraID integration out of the box. Full user and group management system with a “least privilege” operating mode. Governance - Customizable data governance platform; dictate and enforce required metadata, enforce data embargos, and enforce user agreements and NDAs before data access. Ability to create health checks on data, rejecting abandoned or poorly curated data and automatically removing it from the search index. Ability for users to submit corrections. Search - Semantic search is a first class citizen. No licenses to expensive, external software required. Integrated use of vectors and vector-based search allows for AI agent integration at all levels of operation. Metadata Model - Display and control data’s lineage and connections to other data and data directories. Data is modeled after a filesystem - an organization instantly recognizable and navigable by most any user. CLI and SDK - Ships with a Command Line Interface (CLI) tool and with a fully-featured Python SDK. This allows for rapid and programmatic use of Datum by every level of user. Minimal Infrastructure - Datum ships as a single executable file and can be run on any operating system and most CPU architectures. Datum has no reliance on external databases, search indexing tools, or other outside services - and it runs equally well on edge computing devices, cloud services, or in a clustered HPC environment.

darrington, john↗

Identifying and tracking bubbles and drops in simulations: A toolbox for obtaining sizes, lineages, and breakup and coalescence statistics

Knowledge of bubble and drop size distributions in two-phase flows is important for characterizing a wide range of phenomena, including combustor ignition, sonar communication, and cloud formation. The physical mechanisms driving the background flow also drive the time evolution of these distributions. Accurate and robust identification and tracking algorithms for the dispersed phase are necessary to reliably measure this evolution and thereby quantify the underlying mechanisms in interface-resolving flow simulations. The identification of individual bubbles and drops traditionally relies on an algorithm used to identify connected regions. This traditional algorithm can be sensitive to the presence of spurious structures. A cost-effective refinement is proposed to maximize volume accuracy while minimizing the identification of spurious bubbles and drops. An accurate identification scheme is crucial for distinguishing bubble and drop pairs with large size ratios. The identified bubbles and drops need to be tracked in time to obtain breakup and coalescence statistics that characterize the evolution of the size distribution, including breakup and coalescence frequencies, and the probability distributions of parent and child bubble and drop sizes. An algorithm based on mass conservation is proposed to construct bubble and drop lineages using simulation snapshots that are not necessarily from consecutive time steps. These lineages are then used to detect breakup and coalescence events, and obtain the desired statistics. Accurate identification of large-size-ratio bubble and drop pairs enables accurate detection of breakup and coalescence events over a large size range. Accurate detection of successive breakup and coalescence events requires that the snapshot interval be an order of magnitude smaller than the characteristic breakup and coalescence times to capture these successive events while minimizing the identification of repeated confounding events. Together, these algorithms serve as a toolbox for detailed analysis of two-phase simulations, and enable insights into the mechanisms behind bubble and drop formation and evolution in flows of practical importance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The CO Emission in the Taffy Galaxies (UGC 12914/15) at 60 pc Resolution. I. The Battle for Star Formation in the Turbulent Taffy Bridge

We present Atacama Large Millimeter/submillimeter Array observations at a spatial resolution of $0^{"}_{.}2$ (60 pc) of CO emission from the Taffy galaxies (UGC 12914/5). The observations are compared with narrowband Paα, mid-IR, radio continuum and X-ray imaging, plus optical spectroscopy. The galaxies have undergone a recent head-on collision, creating a massive gaseous bridge that is known to be highly turbulent. The bridge contains a complex web of narrow molecular filaments and clumps. The majority of the filaments are devoid of star formation, and fall significantly below the Kennicutt–Schmidt relationship for normal galaxies, especially for the numerous regions undetected in Paα emission. Within the loosely connected filaments and clumps of gas we find regions of high velocity dispersion that appear gravitationally unbound for a wide range of likely values of X CO . Like the "Firecracker" region in the Antennae system, they would require extremely high external dynamical or thermal pressure to stop them dissipating rapidly on short crossing timescales of 2–5 Myr. We suggest that the clouds may be transient structures within a highly turbulent multiphase medium that is strongly suppressing star formation. Despite the overall turbulence in the system, stars seem to have formed in compact hotspots within a kiloparsec-sized extragalactic H ii region, where the molecular gas has a lower velocity dispersion than elsewhere, and shows evidence for a collision with an ionized gas cloud. Like the shocked gas in the Stephan's Quintet group, the conditions in the Taffy bridge shows how difficult it is to form stars within a turbulent, multiphase, gas.

79 ASTRONOMY AND ASTROPHYSICS↗