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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

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↗
DOE OSTI2020

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↗
DOE OSTI2023

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↗
DOE OSTI2025

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↗
DOE OSTI2021

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↗
DOE OSTI2022

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↗
DOE OSTI2023

Spy in the GPU-box: Covert and Side Channel Attacks on Multi-GPU System

The deep learning revolution has been enabled in large part by GPUs, and more recently accelerators, which make it possible to carry out computationally demanding training and inference in acceptable times. As the size of machine learning networks and workloads continues to increase, multi-GPU machines have emerged as an important platform offered on High Performance Computing and cloud data centers. Since these machines are shared among multiple users, it becomes increasingly important to protect applications against potential attacks. In this paper, we explore the vulnerability of Nvidia's DGX multi-GPU machines to covert and side channel attacks. These machines consist of a number of discrete GPUs that are interconnected through a combination of custom interconnect (NVLink) and PCIe connections. We reverse engineer the interconnected cache hierarchy and show that it is possible for an attacker on one GPU to cause contention on the L2 cache of another GPU. We use this observation to first develop a covert channel attack across two GPUs, achieving the best bandwidth of around 4 MB/s. We also develop a prime and probe attack on a remote GPU allowing an attacker to recover the cache access pattern of another workload. This access pattern can be used in any number of side channel attacks: we demonstrate a proof of concept attack that fingerprints the application running on the remote GPU, with high accuracy. We also develop a proof of concept attack to extract hyperparameters of a machine learning workload. Our work establishes for the first time the vulnerability of these machines to microarchitectural attacks and can guide future research to improve their security.

Dutta, Sankha↗
DOE OSTI2021

Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments

The study presented here focuses on performance characteristics and trade-offs associated with running machine-learning tasks in multi-GPU environments on both on-site cloud computing resources and commercial cloud services (Azure). Specifically, this study examines these tradeoffs by examining the performance of training and fine-tuning of transformer-based deep-learning (DL) networks on clinical notes and data, a task of critical importance in the medical domain. To this end, we perform DL-related experiments on the widely deployed NVIDIA V100 GPUs and on the newer A100 GPUs connected via NVLink or PCIe. This study analyzes the execution time of major operations to train DL models and investigate popular options to optimize each of them. We examine and present the findings on the impacts that various operations (e.g. data loading into GPUs, training, fine-tuning), optimizations, and system configurations (single vs. multi-GPU, NVLink vs. PCIe) have on the overall training performance.

Begoli, Edmon↗
DOE OSTI2021

Mechanism of Microseismic Generation During Hydraulic Fracturing - With Evidence From HFTS 2 Observations

The objective of this study is to understand how microseismic events are generated during hydraulic fracturing, as well as the role of geomechanical conditions (i.e., stress and mechanical stratigraphy) in this process. In the industry, microseismic event clouds have been generally used as an “outer-boundary” of the “stimulated reservoir volume” (SRV). However, by comparing with other surveillance data (Low frequency Distributed Acoustic Sensing, or LF-DAS strain) in the Hydraulic Fracturing Test Site (HFTS) 2 experiment, we show that this assumption is fundamentally flawed. The HFTS 2 data has three unique observations that have not been commonly observed in other datasets: 1. Due to influence of offset pad depletion, microseismic data shows that hydraulic fractures from the child well can propagate over 3000 feet into the depleted low stress zone. 2. By comparing microseismic and horizontal fiber LF-DAS strain data, we observe that microseismic event cloud does not necessarily reflect the created hydraulic fracture volume. Particularly, the extent of microseismic event clouds near heel stages are much shorter than what is shown with LF-DAS strain data. 3. Microseismic event magnitudes are larger in the depleted regions. Through geomechanical analysis, we demonstrate that the “bedding-plane-slip” model is likely the mechanism for microseismic generation during hydraulic fracturing. Furthermore, this model successfully explains the above field observations from HFTS 2 experiment. We also provide a quantitative relationship connecting the microseismic event magnitude with fracture width increment and layer mechanical property contrast.

58 GEOSCIENCES↗
DOE OSTI2022

Interpretation of HFTS 2 Microseismic Data Using Bedding-Plane-Slip Mechanism

Summary The objective of this study is to understand how microseismic events are generated during hydraulic fracturing, as well as the role of geomechanical conditions (i.e., stress and mechanical stratigraphy) in this process. In the industry, microseismic event clouds have been generally used as an “outer boundary” of the “stimulated reservoir volume” (SRV). However, by comparing with other surveillance data (low-frequency distributed acoustic sensing, or LF-DAS, strain) in the Hydraulic Fracturing Test Site (HFTS) 2 experiment, we show that this assumption is fundamentally flawed. The HFTS 2 data have three unique observations that have not been commonly observed in other datasets: (1) Due to the influence of offset pad depletion, microseismic data show that hydraulic fractures from the child well can propagate over 3,000 ft into the depleted low-stress zone. (2) By comparing microseismic and horizontal fiber LF-DAS strain data, we observe that the microseismic event cloud does not necessarily reflect the created hydraulic fracture volume. Particularly, the extent of microseismic event clouds near heel stages is much shorter than what is shown with LF-DAS strain data. (3) Microseismic event magnitudes are larger in the depleted regions. Through geomechanical analysis, we demonstrate that the “bedding-plane-slip” model is likely the mechanism for microseismic generation during hydraulic fracturing. This model successfully explains the above field observations from the HFTS 2 experiment. We also provide a quantitative relationship connecting the microseismic event magnitude with fracture width increment and layer mechanical property contrast.

Engineering↗
DOE OSTI2021

Alignment of the magnetic field in star-forming regions and why it might be difficult to observe

ABSTRACT Magnetic fields are an important component of the interstellar medium (ISM) and exhibit strongly varying field strengths and a non-trivial correlation with the gas density. Its dynamical impact varies between individual regions of the ISM and correlates with the orientation of the field with respect to the gas structures. Using high-resolution magneto-hydrodynamical simulations of the ISM, we explore the connection between the orientation of the field and the dynamical state of the gas. We find that the onset of gravitational instability in molecular gas above a density of $\rho \sim 10^{-21}\, \mathrm{g\, cm}^{-3}$$(n\sim 400\, \mathrm{cm}^{-3})$ coincides with an alignment of the magnetic field lines and the gas flow. At this transition, the gradient of the density changes from mainly perpendicular to preferentially parallel to the field lines. A connection between the three-dimensional alignment and projected two-dimensional observables is non-trivial, because of a large dispersion of the magnetic field orientation along the line of sight. The turbulent correlation lengths can be small compared to the typical integration lengths. As a consequence, the small-scale signal of the orientation can sensitively depend on the line of sight or the dynamical state of the cloud can fluctuate stochastically or be completely averaged out. With higher spatial resolution more small-scale structures are resolved, which aggravates the link between magneto-hydrodynamical quantities and projected observables.

Girichidis, Philipp (ORCID:0000000293009914)↗
DOE OSTI2023

Responses of the AC/DC Global Electric Circuit to Volcanic Electrical Activity in the Hunga Tonga-Hunga Ha'apai Eruption on 15 January 2022

Responses of the AC and DC global electric circuits (GECs) to the large eruption of the Hunga Tonga-Hunga Ha'apai (HT-HH) volcano on 15 January 2022 are discussed. The AC-related investigation is based on Schumann resonance (SR) measurements from six stations on four continents. The DC-related investigation utilizes atmospheric electric field (potential gradient, PG) measurements from six recording stations in Europe and the USA. According to data from the GLD360 and WWLLN lightning detection networks, the peak lightning stroke rate, 83/s, was dominated by negative polarity lightning, but the distributions of positive and negative lightning discharges in latitude and longitude around the volcano differed. A global intensification of SR is apparent in connection with the enhanced lightning activity caused by the eruption. SR data-based results confirm that the lightning activity in the eruption dominated the naturally occurring global activity for a period of about 1 hr. The highly localized increase in lightning activity over HT-HH was a unique point source of SR excitation. PG measurements suggest that impulse-like charging of the DC GEC, by ~15%, via negative cloud-to-ground lightning strokes took place twice during the eruption. A time constant of 7 or 8 min has been inferred for near-surface PG changes due to these enhancements. This could be the first direct measurement of the time constant of the GEC near the Earth's surface, as well as the first observation of the direct charging of the DC GEC by a unique atmospheric electrified source.

58 GEOSCIENCES↗
DOE OSTI2025

EDX ClaiMM

EDX ClaiMM is a centralized data & analytical platform designed to revolutionize U.S. critical minerals and materials (CMM) activities. By providing a robust digital infrastructure, ClaiMM will accelerate the combination, leveraging, and rapid utilization of vital data, advanced tools, and cutting-edge research advancements in CMM. This adaptive digital research hub connects the CMM community to essential knowledge products and offers access to interoperable datasets, databases, models, software, and tools from the National Energy Technology’s (NETL’s) Energy Data eXchange (EDX) and other authoritative sources, serving both public and private sectors. EDX ClaiMM delivers AI-informed solutions to address fundamental knowledge gaps and fosters the innovation of new techniques for enhanced characterization and recovery of CMMs within the U.S. By leveraging cloud-hosted, scalable digital infrastructure, ClaiMM meets public–private applied energy needs. It equips the CMM community with priority digital resources that harness on-site and cloud compute capabilities, enabling big data storage, advanced processing, analytics, and visualization.

Critical Materials; Critical Minerals; Rare Earth ↗
DOE OSTI2023

CASTLE: Conflict Analysis Strategy Testing Laboratory Environment v.1.0.0

SAND2024-01743O The Conflict Analysis Strategy Testing Laboratory Environment (CASTLE) is a software framework that enables and simplifies building a novel, turn-based strategy game in which it can define its own rules, maps, pieces, and interactions. The software is for novice to experienced programmers with some knowledge of Unity3D, a tool used in game production. CASTLE includes a library of common game mechanics used for strategic wargames and traditional board games, such as cards, tokens, dice, and grid maps. It follows design principles popularized by the video game industry and uses singletons for managing portions of the code. CASTLE builds on Unity's component-based design and can respond to engine events during execution. Among the numerous user-friendly features: Build games quickly and cost-effectively Network in real-time and apply data to new games developed on the framework Host multiple participants online Connect rule- or machine learning-based agents to a CASTLE game to serve as opponents or to simulate games Collect data collection from players and in-game behaviors Create a survey to gather demographics or opinions from players Store data locally or save it to an external database through Representational State Transfer (REST) functions CASTLE, which was prototyped using Microsoft Azure, is also designed for easily distributing online games using popular cloud services. The multiplayer functionality includes an agent interface, allowing developers to construct AI players that can substitute for humans in any of the games. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fabian, Nathan↗
DOE OSTI2025

Classification of Cloud Particle Imagery and Thermodynamics (COCPIT): A New Databasing Tool for the Characterization of Cloud Particle Images Captured During DOE Field Campaigns

The Department of Energy for decades has explored the earth system and atmosphere through research and deployment of in-situ and remote sensing platforms during field campaigns. Among these datasets exists a vast supply of cloud particle images that provide visual insight into the complex microphysics in the clouds that span our globe. The millions of images collected over decades of deployments provides a unique opportunity to further our understanding of our atmosphere down to the crystal size. This work over the past 5 years has sought to organize these images into digestible datasets that can then be used by scientists to further our understanding of microphysics. A machine learning model was developed that categorizes over 1.5 million images across 11 weather events with over 90% accuracy according to particle type. The database was then extended to include dimensional characteristics of the particle as well as co-location of environmental properties, such as temperature and water content. Then, to initialize the connection between these data and our understanding of how crystals form and grow, weather research and forecasting simulations were run to generate the growth histories of the classified crystals. This research culminates with 2 databases per event: (1) a database of all classified crystals and their dimensional and environmental properties and (2) simulated growth histories of each crystal. Finally, a user interface was created to allow researchers to explore data statistics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Cool circumgalactic gas in galaxy clusters: connecting the DESI legacy imaging survey and SDSS DR16 Mg ιι absorbers

Herein we investigate the cool gas absorption in galaxy clusters by cross-correlating Mg II absorbers detected in quasar spectra from data release 16 of the Sloan Digital Sky Survey (SDSS) with galaxy clusters identified in the Dark Energy Spectroscopic Instrument (DESI) survey. We find significant covering fractions (⁠1–5percent within r 500 , depending on the chosen redshift interval), ~4–5 times higher than around random sightlines. While the covering fraction of cool gas in clusters decreases with increasing mass of the central galaxy, the total Mg II mass within r 500 is none the less ~10 times higher than for SDSS luminous red galaxies. The Mg II covering fraction versus impact parameter is well described by a power law in the inner regions and an exponential function at larger distances. The characteristic scale of the transition between these two regimes is smaller for large equivalent width absorbers. Cross-correlating Mg II absorption with photo–z selected cluster member galaxies from DESI reveals a statistically significant connection. The median projected distance between Mg II absorbers and the nearest cluster member is ~200 kpc, compared to ~500 kpc in random mocks with the same galaxy density profiles. We do not find a correlation between Mg II strength and the star formation rate of the closest cluster neighbour. This suggests that cool gas in clusters, as traced by Mg II absorption, is: (i) associated with satellite galaxies, (ii) dominated by cold gas clouds in the intracluster medium, rather than by the interstellar medium of galaxies, and (iii) may originate in part from gas stripped from these cluster satellites in the past.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Boundary-Layer Gradients in New Particle Formation Field Campaign Report

Atmospheric new particle formation (NPF) followed by growth of the particles to ~50-150 nm is estimated to account for over 50% of the particles that can activate cloud droplets. As such, NPF and the subsequent growth plays a critical role in our ability to understand how aerosols affect cloud life cycle, properties, and processes and more generally the Earth’s radiative balance. NPF and growth is known to occur throughout the troposphere including in both the boundary layer and the free troposphere. The majority of NPF and growth observations, however, come from surface-based measurements within the boundary layer. Measurements of the vertical distribution of NPF and growth are sparse and thus insufficient to test many of the hypotheses that attempt to explain connections between NPF and boundary-layer transport and meteorology. The purpose of this campaign was to investigate the vertical distribution of NPF and growth at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A low-mass hub–filament with double centre revealed in NGC 2071-North

We present the first analysis in NGC 2071-North as a resolved hub–filament featuring a double centre. This ∼1.5 × 1.5 pc 2 scale filament hub contains ∼500 M ⊙ . Seen from Planck, magnetic field lines may have facilitated the gathering of material at this isolated location. The energy balance analysis, supported by infalling gas signatures, reveals that these filaments are currently forming stars. Herschel 100 $\mu$m emission concentrates in the hub, at IRAS 05451+0037 and LkHα 316, and presents diffuse lobes and loops around them. We suggest that such a double centre could be formed, because the converging locations of filament pairs are offset, by 2.3 arcmin (0.27 pc). This distance also matches the diameter of a hub ring, seen in column density and molecular tracers, such as HCO + (1–0) and HCN (1–0), that may indicate a transition and the connection between the hub and the radiating filaments. We argue that all of the three components of the emission star LkHα 316 are in physical association. We find that a ∼0.06-pc-sized gas loop, attached to IRAS 05451+0037, can be seen at wavelengths all the way from the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS)-i to Herschel 100 $\mu$m. These observations suggest that both protostars at the double hub centre are interacting with the cloud material. In our 13 CO data, we do not seem to find the outflow of this region that was identified in the 1980s with much lower resolution.

79 ASTRONOMY AND ASTROPHYSICS↗