Reduced order models for aerodynamic applications, loads and MDO

Reduced Order Models (ROMs) have found widespread application in fluid dynamics and aerodynamics. In their direct application to Computational Fluid Dynamics (CFD) ROMs seek to reduce the computational complexity of a problem by reducing the number of degrees of freedom rather than simplifying the physical model. Here, parametric nonlinear ROMs based on high-fidelity CFD are used to provide approximate flow solutions, but at lower evaluation time and storage than the original CFD model. ROMs for both steady and unsteady aerodynamic applications are presented. We consider ROMs combining proper orthogonal decomposition (POD) and Isomap, which is a manifold learning method, with interpolation methods as well as physics-based ROMs, where an approximate solution is found in the POD-subspace by minimizing the corresponding steady or unsteady flow-solver residual. In terms of the nonlinear unsteady least-squares ROM algorithm, we present the details of an improved accelerated greedy missing point estimation procedure which is usedin the online phase to select a subset of the unsteady residual for reasons of computational efficiency during the online prediction phase. The issue of how to best train the ROM with high-fidelity CFD data is also addressed. The goal is to train ROMs that yield a large domain of validity across all parameters and flow conditions at the expense of a relatively small number of CFD solutions. The different ROM methods are demonstrated on a wide-body transport aircraft configuration at transonic flow conditions. The steady ROMs are used to predict the static aeroelastic loads in the context of multidisciplinary optimization (MDO), where a structural model is to be sized for the (aerodynamic) loads. They are also used in a process where an a priori identification of the most critical static load cases is of interest and the sheer number of load cases to be considered does not lend itself to high-fidelity CFD. The unsteady nonlinear least-squares ROM approach is applied to modeling discrete gusts of different amplitude and length in the context of rapid evaluation of gust-induced air loads

Successful percutaneous transgluteal embolization of a complex arteriovenous malformation feeding a hypogastric artery aneurysm

Pelvic arteriovenous malformation (AVM) is a rare condition mostly requiring a complex therapeutic strategy. The surgical approach is challenging and burdened by relatively high mortality and morbidity rates. No guidelines are available for the endovascular treatment of AVM because the literature is limited to small case series and case reports. We present a complex case of a pelvic AVM associated with an internal iliac artery aneurysm in a patient previously treated with a common to external prosthetic substitution for aneurysm and proximal ligation of internal iliac artery

Use of Contrast-Enhanced Ultrasound in Carotid Atherosclerotic Disease: Limits and Perspectives

Contrast-enhanced ultrasound (CEUS) has recently become one of the most versatile and powerful diagnostic tools in vascular surgery. One of the most interesting fields of application of this technique is the study of the carotid atherosclerotic plaque vascularization and its correlation with neurological symptoms (transient ischemic attack, minor stroke, and major stroke) and with the characteristics of the “vulnerable plaque” (surface ulceration, hypoechoic plaques, intraplaque hemorrhage, thinner fibrous cap, and carotid plaque neovascularization at histopathological analysis of the sample after surgical removal). The purpose of this review is to collect all the original studies available in literature (24 studies with 1356 patients enrolled) and to discuss the state of the art, limits, and future perspectives of CEUS analysis. The results of this work confirm the reliability of this imaging study for the detection of plaques with high risk of embolization; however, a shared, user-friendly protocol of imaging analysis is not available yet. The definition of this operative protocol becomes mandatory in order to compare results from different centers and to validate a cerebrovascular risk stratification of the carotid atherosclerotic lesions evaluated with CEUS

KIC 7599132: an ellipsoidal variable in a close SB1 system

In this paper, we present a spectroscopic and photometric analysis of the suspected ellipsoidal variable star KIC 7599132. New spectroscopic observations have been obtained with Catania Astrophysical Observatory Spectropolarimeter. From the fit of Hα and Hβ, we determined the effective temperature and gravity of the primary component, Teff = 10200 ± 150 K and log g = 4.1 ± 0.1, while from a number of metal lines, we derive the rotational velocity, v esin i = 60 ± 2 km s-1. We found almost solar abundances with the exception of silicon (0.50 dex) overabundance. A Bayesian analysis, based on the comparison between observational data and theoretical predictions of PROSECCO evolutionary models, allows us to estimate the mass and the age of the primary. We obtained M1 = 2.4 ± 0.2 M☉ and τs = 3.8 _{-0.7}^{+0.9} Myr. A new model for the system was obtained combining Kepler photometric time series (Q0-Q17) and our radial velocities by using the code PHOEBE. As a result, the system appears to be a detached binary system with a mass ratio q = 0.30 ± 0.01, a semimajor axis a = 7.3 ± 0.1 R☉ and an inclination angle i = 35° ± 2°. This modelling allowed us to derive: M2 = 0.7 ± 0.1 M☉, R1 = 3.0 ± 0.2 R☉, and R2 = 1.5 ± 0.2 R☉. Numerical simulations show that if the secondary star had been hotter than 4000 K, we would have observed its spectral features in our spectra

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data