5 research outputs found

    Development and Verification of a Finite Element Model of a Fixed-Wing Unmanned Aerial System for Airborne Collision Severity Evaluation

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    Unmanned aircraft systems (UASs) pose a potential threat to general aviation/commercial aircraft as UASs are increasingly incorporated into the National Airspace System. This overarching research is aimed at addressing the severity of a UAS mid-air collision with another aircraft. This study is primarily focused on the development of a finite element (FE) model of a ~4 lb fixed-wing UAS (FW-UAS) which will be used to evaluate the severity of small UAS mid-air collisions to manned aircraft. A series of impact tests were performed at the University of Dayton Research Institute - Impact Physics Lab, to study the impact behavior of the high-density components of the FW-UAS (i.e., motor, and battery). For each of the tests, a simulation was set up with the same initial conditions, and boundary conditions as the physical test and the same output parameters were correlated with the test results. A series of numerical stability checks were also performed using the validated FW-UAS FE model to ensure the stability of the explicit dynamic procedures. Simulated impacts between the FW-UAS FE model and targets (deformable flat plate, rigid flat plate, and rigid knife-edge) were performed as stability checks. The FW-UAS FE model developed in this work facilitated the evaluation of the severity of FW-UAS mid-air collision to commercial and business jet airframes performed at and in conjunction with National Institute for Aviation Research. A series of worst-case scenarios involving impacts between the FW-UAS and commercial narrow-body transport and business jet airframes were simulated. For each simulated impact, an impact severity index value was assigned to characterize the relative threat to a given aircraft. In addition, a UAS frangibility study was performed to assess key UAS design features that result in reduced damage to target air vehicles. A “pusher” engine configuration was modeled where the high-density motor is located aft of the UAS’s forward fuselage. Positioning the high-density motor in the aft fuselage played an important role in reducing the impact damage severity

    Fatigue and Crack-Growth Behavior in a Titanium Alloy under Constant-Amplitude and Spectrum Loading

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    A titanium alloy (Ti-6Al-4V STOA) plate material was provided by the University of Dayton Research Institute from a previous U.S. Air Force high-cycle fatigue study. Fatigue-crack-growth tests on compact, C(T), specimens have been previously performed at Mississippi State University on the same material over a wide range in rates from threshold to near fracture for several load ratios (R = Pmin/Pmax). These tests used the compression pre-cracking method to generate fatigue-crack-growth-rate data in the near-threshold regime. Current load-reduction procedures were found to give elevated thresholds compared to compression pre-cracking methods. A crack-closure model was then used to determine crackront constraint and a plasticity-corrected effective stress-intensityactor-range relation over a wide range in rates and load ratios. Some engineering estimates were made for extremely slow rates (small-crack behavior), below the commonly defined threshold rate. Single-edge-notch-bend, SEN(B), fatigue specimens were machined from titanium alloy plates and were fatigue tested at two constant-amplitude load ratios (R = 0.1 and 0.5) and a modified Cold-Turbistan engine spectrum. Calculated fatigue lives from FASTRAN, a fatigue-life-prediction code, using small-crack theory with an equivalent-initiallaw-size (semi-circular surface flaw) of 9 µm in radius at the center of the semi-circular edge notch fit the constant-amplitude test data fairly well, but underpredicted the spectrum loading results by about a factor of 2 to 3. Life predictions made with linear-cumulative damage (LCD) calculations agreed fairly well with the spectrum tests

    Hyper-Velocity Impact Performance of Foldcore Sandwich Composites

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    A foldcore is a novel core made from a flat sheet of any material folded into a desired pattern. A foldcore sandwich composite (FSC) provides highly tailorable structural performance over conventional sandwich composites made with honeycomb or synthetic polymer foam cores. Foldcore design can be optimized to accommodate complex shapes and unit cell geometries suitable for protective shielding structures This work aims to characterize hypervelocity impact (\u3e 2000 m/s, HVI) response and corresponding damage morphologies of carbon fiber reinforced polymer (CFRP) FSCs. A series of normal (0° impact angle) and oblique (45° impact angle) HVI (~3km/s nominal projectile velocity) impact tests were performed on CFRP FSC targets to understand the effects of projectile impact on redirected debris formation, and variable debris cloud expansion. HVI damage in FSC targets were assessed using visual inspection and high-speed imaging analysis. The results from the present study indicate that debris cloud propagation and expansion are strongly influenced by foldcore impact location/angle and open-channel direction. This work serves as a baseline study to understand HVI response of FSC targets and to identify critical FSC design parameters to optimize HVI mitigation performance

    Hypervelocity Impacts on Honeycomb Core Sandwich Panels Filled with Shear Thickening Fluid

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    The use of honeycomb core sandwich panels filled with a shear thickening fluid (STF) as a component of spacecraft micrometeoroid/orbital debris (MMOD) shielding was investigated using hypervelocity impact (HVI) testing. Incorporating a STF into shielding has the potential to reduce damage to the core and the likelihood of back-side facesheet perforation in the event of a HVI. The sandwich panels tested consisted of 1.27 cm thick hexagonal aluminum honeycomb core bonded between 0.064 cm thick aluminum facesheets. The STF displayed a marked rise in viscosity with increasing shear rate above a critical shear rate. It was based on low molecular weight polyethylene glycol (PEG) and hydrophilic fumed silica. Sandwich panel target specimens filled with the STF were subjected to HVIs by 1 mm diameter stainless steel spheres at nominal temperatures of -80â—¦C or 21â—¦C with nominal impact velocities of 4.8 km/s or 6.8 km/s. Additional specimens filled with PEG only were also impacted for comparison. Visual inspections and X-ray computerized tomography were used to assess impact damage. All of the panels experienced perforation of the impacted facesheet, facesheet bulging, localized delamination, and the formation of a cavity in the damaged core. STF-filled panels sustained significantly less damage than PEG-filled panels. None of the STF-filled panels were completely perforated during impact. In contrast, one of the PEG-filled panels impacted at the peak velocity was perforated. The remaining PEG-filled panel sustained substantially more honeycomb core damage and facesheet-core delamination compared to an analogous STF-filled panel. Sandwich panels filled with the STF provide superior HVI mitigation in comparison to panels filled with a Newtonian fluid (i.e., PEG). These experiments show that incorporation of STFs into MMOD shielding components has the po-tential to dramatically improve the HVI penetration resistance over a broad range of impact velocities and temperature

    ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

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    The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use
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