35 research outputs found

    Experimental evaluation of methods for improving diffuser-exit total-pressure profiles for a side-inlet model at Mach number 1.91

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    Distortion effects of the following model additions or changes were studied: (1) constant-area mixing lengths at the end of the subsonic diffuser, (2) screens with systematic variations in mesh and flow-area blockage, (3) bleeds slots on the inlet cowl, and (4) a simulated compressor hub. Data at a diffuser-exit Mach number of 0.36 are compared with data of a similar study at Mach 0.20. At the higher Mach number, the same length of constant-area mixing was less effective in reducing total-pressure distortions, while the use of screens was more effective

    Characteristics of Five Ejector Configurations at Free-Stream Mach Numbers from 0 to 2.0

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    Thrust, air-handling, and base-pressure characteristics of five ejector configurations were investigated in the Lewis 8-by 6-foot wind tunnel at free-stream Mach numbers from 0 to 2.0 over ranges of primary-jet pressure ratio up to 24 and corrected secondary weight-flow ratio up to 13 percent. The ejector-shroud geometries varied from convergent to divergent. Base pressure ratio and ejector performance were interrelated by means of an exit-momentum parameter. Correlations, to at least a first approximation, with base pressure ratio, of both internal-ejector-flow separation and external-flow separation over the model boattail were shown. Furthermore, it was shown that magnitudes and exact trends in base pressure ratio depended largely, and in a complicated fashion, on ejector geometry and amount of secondary flow. External-stream effects on ejector jet thrust were determined for a typical schedule of jet-engine pressure ratios. With the exception of the ejector having the largest (1.81) shroud-exit-to primary-diameter ratio, there were no stream effects at Mach numbers from 1.5 to 2.0 and variations from quiescent-air thrust data were less than 2.5 percent at the subsonic speed investigated

    Performance of Twin-duct Variable-geometry Side Inlets at Mach Numbers of 1.5 to 2.0

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    Supersonic wind tunnel test of twin-duct variable geometry side inlet

    The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

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    OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19

    SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

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    This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe
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