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Institution

University of Bergamo

EducationBergamo, Italy
About: University of Bergamo is a education organization based out in Bergamo, Italy. It is known for research contribution in the topics: Context (language use) & Population. The organization has 1399 authors who have published 5914 publications receiving 101251 citations. The organization is also known as: Università degli Studi di Bergamo & Universita degli Studi di Bergamo.


Papers
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Journal ArticleDOI
TL;DR: Analysis of the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Italy might help political leaders and health authorities to allocate enough resources, including personnel, beds, and intensive care facilities, to manage the situation in the next few days and weeks.

2,470 citations

Journal ArticleDOI
TL;DR: The 1st International Workshop on High-Order CFD Methods was successfully held in Nashville, Tennessee, on January 7-8, 2012, just before the 50th Aerospace Sciences Meeting as mentioned in this paper.
Abstract: After several years of planning, the 1st International Workshop on High-Order CFD Methods was successfully held in Nashville, Tennessee, on January 7-8, 2012, just before the 50th Aerospace Sciences Meeting. The American Institute of Aeronautics and Astronautics, the Air Force Office of Scientific Research, and the German Aerospace Center provided much needed support, financial and moral. Over 70 participants from all over the world across the research spectrum of academia, government labs, and private industry attended the workshop. Many exciting results were presented. In this review article, the main motivation and major findings from the workshop are described. Pacing items requiring further effort are presented. © 2013 John Wiley & Sons, Ltd.

838 citations

Journal ArticleDOI
TL;DR: In this article, the normal impact of liquid drops onto solid, dry surfaces has been studied experimentally, using high-resolution digital photography, and the focus of the quantitative determination of these parameters on the drop spreading upon impact and on the phenomenological description of the outcomes.
Abstract: The normal impact of liquid drops onto solid, dry surfaces has been studied experimentally, using high-resolution digital photography. A large number of parameters were varied in a systematic manner. The focus of this paper is the quantitative determination of the influence of these parameters on the drop spreading upon impact and on the phenomenological description of the outcomes. Dimensional similarity of the spreading can only be achieved for the very early stage of the impact process. At later stages, the number of influencing factors increases, generally precluding any universal correlation. Particular emphasis is placed on the influence of the wettability and the surface roughness on spreading.

776 citations

Journal ArticleDOI
TL;DR: It is demonstrated that viscoelasticity can reduce turbulence and suppress cavitation, and subsequently increase the injector’s volumetric efficiency.
Abstract: We identify the physical mechanism through which newly developed quaternary ammonium salt (QAS) deposit control additives (DCAs) affect the rheological properties of cavitating turbulent flows, resulting in an increase in the volumetric efficiency of clean injectors fuelled with diesel or biodiesel fuels. Quaternary ammonium surfactants with appropriate counterions can be very effective in reducing the turbulent drag in aqueous solutions, however, less is known about the effect of such surfactants in oil-based solvents or in cavitating flow conditions. Small-angle neutron scattering (SANS) investigations show that in traditional DCA fuel compositions only reverse spherical micelles form, whereas reverse cylindrical micelles are detected by blending the fuel with the QAS additive. Moreover, experiments utilising X-ray micro computed tomography (micro-CT) in nozzle replicas, quantify that in cavitation regions the liquid fraction is increased in the presence of the QAS additive. Furthermore, high-flux X-ray phase contrast imaging (XPCI) measurements identify a flow stabilization effect in the region of vortex cavitation by the QAS additive. The effect of the formation of cylindrical micelles is reproduced with computational fluid dynamics (CFD) simulations by including viscoelastic characteristics for the flow. It is demonstrated that viscoelasticity can reduce turbulence and suppress cavitation, and subsequently increase the injector’s volumetric efficiency.

704 citations

Journal ArticleDOI
TL;DR: The framework takes advantage of the integration of image processing, geometric analysis and mesh generation techniques, with an accent on full automation and high-level interaction, to be performed in the context of large-scale studies.
Abstract: We present a modeling framework designed for patient-specific computational hemodynamics to be performed in the context of large-scale studies. The framework takes advantage of the integration of image processing, geometric analysis and mesh generation techniques, with an accent on full automation and high-level interaction. Image segmentation is performed using implicit deformable models taking advantage of a novel approach for selective initialization of vascular branches, as well as of a strategy for the segmentation of small vessels. A robust definition of centerlines provides objective geometric criteria for the automation of surface editing and mesh generation. The framework is available as part of an open-source effort, the Vascular Modeling Toolkit, a first step towards the sharing of tools and data which will be necessary for computational hemodynamics to play a role in evidence-based medicine.

686 citations


Authors

Showing all 1455 results

NameH-indexPapersCitations
Andrea Carlo Marini123123672959
Valerio Re8191233409
Ilaria Vai7555223103
Pierangela Samarati6433021722
Andrea Remuzzi6223515134
Koen Frenken5425114459
Bo Rothstein5321214216
Antonio Capone504119406
Alfredo Vittorio De Massis491858020
Enrico Molinari472387979
Stefano Paraboschi461729210
Giancarlo Mauri445168478
Kenneth Button434107605
Francesco Svelto411875083
Marco Marengo402456307
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202325
2022101
2021519
2020497
2019403
2018375