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- Fabio Nobile

Discipline name
H-index
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
41
Citations
11,951
117
World Ranking
940
National Ranking
18

Engineering and Technology
D-index
33
Citations
7,479
99
World Ranking
4032
National Ranking
55

- Mathematical analysis
- Statistics
- Algorithm

Fabio Nobile spends much of his time researching Mathematical analysis, Mathematical optimization, Orthogonal collocation, Fluid–structure interaction and Applied mathematics. His Mathematical analysis research incorporates themes from hp-FEM and Extended finite element method. His work in Mathematical optimization covers topics such as Robin boundary condition which are related to areas like Domain decomposition methods and Navier–Stokes equations.

Fabio Nobile integrates several fields in his works, including Orthogonal collocation, Sparse grid and Random field. His research in Fluid–structure interaction intersects with topics in Compressibility, Numerical stability and Calculus. His Applied mathematics research includes themes of Numerical analysis and Finite element method.

- A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (1173 citations)
- A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data (704 citations)
- Added-mass effect in the design of partitioned algorithms for fluid-structure problems (609 citations)

His primary areas of study are Applied mathematics, Monte Carlo method, Mathematical analysis, Mathematical optimization and Technical report. The Applied mathematics study combines topics in areas such as Discretization, Partial differential equation, Polynomial and Finite element method. His Monte Carlo method study combines topics in areas such as Uncertainty quantification, Algorithm, Estimator and Aerodynamics.

His Algorithm research focuses on Fluid–structure interaction and how it relates to Interaction problem. The Boundary value problem research Fabio Nobile does as part of his general Mathematical analysis study is frequently linked to other disciplines of science, such as Orthogonal collocation, therefore creating a link between diverse domains of science. Fabio Nobile has researched Sparse grid in several fields, including Elliptic pdes, Sparse approximation, Galerkin method and Collocation.

- Applied mathematics (40.61%)
- Monte Carlo method (21.83%)
- Mathematical analysis (20.52%)

- Applied mathematics (40.61%)
- Monte Carlo method (21.83%)
- Algorithm (16.59%)

Fabio Nobile mainly investigates Applied mathematics, Monte Carlo method, Algorithm, Technical report and Rank. His studies deal with areas such as Partial differential equation, Finite element method, Basis function, Discretization and Collocation as well as Applied mathematics. His study in Monte Carlo method is interdisciplinary in nature, drawing from both Aerodynamics, Mathematical optimization, Statistical physics and Contact mechanics.

His work carried out in the field of Rank brings together such families of science as Tangent space, Linear combination and Random field. His work is dedicated to discovering how Tangent space, Navier–Stokes equations are connected with Mathematical analysis and other disciplines. His study on Laplace operator is often connected to Helmholtz resonator as part of broader study in Mathematical analysis.

- Uncertainty Quantification of geochemical and mechanical compaction in layered sedimentary basins (14 citations)
- Dual Dynamically Orthogonal approximation of incompressible Navier Stokes equations with random boundary conditions (13 citations)
- Analysis of stochastic gradient methods for PDE-constrained optimal Control Problems with uncertain parameters (12 citations)

- Mathematical analysis
- Statistics
- Algorithm

His primary scientific interests are in Applied mathematics, Monte Carlo method, Mathematical analysis, Finite element method and Algorithm. Within one scientific family, Fabio Nobile focuses on topics pertaining to Adaptive algorithm under Applied mathematics, and may sometimes address concerns connected to Elliptic partial differential equation and Collocation. Fabio Nobile combines subjects such as Aerodynamics, Semi-infinite, Estimator, Statistical physics and Mathematical optimization with his study of Monte Carlo method.

His studies in Mathematical optimization integrate themes in fields like Shape optimization and Probability density function. Many of his research projects under Mathematical analysis are closely connected to Wavelet, Advection and Diffusion reaction with Wavelet, Advection and Diffusion reaction, tying the diverse disciplines of science together. His Finite element method research includes elements of Basis, Finite difference, Partial differential equation, Statistical model and Numerical analysis.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

Ivo Babus caron;ka;Fabio Nobile;Rau´l Tempone.

SIAM Journal on Numerical Analysis **(2007)**

1607 Citations

A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data

F. Nobile;R. Tempone;C. G. Webster.

SIAM Journal on Numerical Analysis **(2008)**

1144 Citations

Added-mass effect in the design of partitioned algorithms for fluid-structure problems

Paola Causin;Jean-Frédéric Gerbeau;Fabio Nobile.

Computer Methods in Applied Mechanics and Engineering **(2005)**

1051 Citations

On the coupling of 3D and 1D Navier-Stokes equations for flow problems in compliant vessels

Luca Formaggia;Jean Frédéric Gerbeau;Fabio Nobile;Alfio Quarteroni;Alfio Quarteroni.

Computer Methods in Applied Mechanics and Engineering **(2001)**

697 Citations

An Anisotropic Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data

F. Nobile;R. Tempone;C. G. Webster.

SIAM Journal on Numerical Analysis **(2008)**

644 Citations

Numerical approximation of fluid-structure interaction problems with application to haemodynamics

Fabio Nobile.

**(2001)**

407 Citations

A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

Ivo Babuška;Fabio Nobile;Raúl Tempone.

Siam Review **(2010)**

380 Citations

Numerical Treatment of Defective Boundary Conditions for the Navier--Stokes Equations

L. Formaggia;J.-F. Gerbeau;F. Nobile;A. Quarteroni.

SIAM Journal on Numerical Analysis **(2002)**

368 Citations

Multiscale Modelling of the Circulatory System: a Preliminary Analysis

Luca Formaggia;Fabio Nobile;Alfio Quarteroni;Alessandro Veneziani.

Computing and Visualization in Science **(1999)**

349 Citations

Fluid-structure partitioned procedures based on Robin transmission conditions

Santiago Badia;Fabio Nobile;Christian Vergara.

Journal of Computational Physics **(2008)**

324 Citations

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Publications: 21

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