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Bruno Carpentieri

Free University of Bozen-Bolzano Italy

Bruno Carpentieri obtained a Laurea degree in Applied Mathematics in 1997 from Bari University. Then he furthered his Ph.D. studies in Computer Science at the Institut National Polytechnique de Toulouse (INPT), France. After a post-doctoral appointment at the Institute of Mathematics and Scientific Computing, University of Graz, and as a consultant for an European project in cardiac modeling at CRS4 in Sardinia, Italy, he served as an Assistant Professor at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, and as a Reader in Applied Mathematics at the School of Science and Technology, Nottingham Trent University in UK. Since May 2017, he has been holding an Associate Professor appointment in Applied Mathematics at the Faculty of Computer Science, University of Bozen-Bolzano, Italy. His research interests are in the fields of Applied Mathematics, Numerical Linear Algebra, and High-Performance Computing. Bruno Carpentieri served as a member of the scientific advisory board of several conference panels in computational mathematics and high-performance scientific computing (ENUMATH07, Beteq09, Beteq08, Beteq07, CEM11, CEM13, CEM15, CEM17, CEM18, HPC2014, HPC2015, HPC2016, HPC2017, HPC2018, HPC2019, ICBCB 2017, HPC/SmartTechCon2017, review team member of CSAE2019 and MLIS 2019). He is an Editorial Board Member of the Journal of Applied Mathematics, an Editorial Committee Member of Mathematical Reviews (American Mathematical Society), and a reviewer of about 30 scientific journals in numerical analysis and scientific computing. He has supervised 20 student projects at BSc, MSc, and Ph.D. levels, and he is the author of about 100 publications that appeared in peer-reviewed scientific journals.

5books edited

3chapters authored

Latest work with IntechOpen by Bruno Carpentieri

Fusion power may offer a long-term energy supply with an uninterrupted power delivery, a high power-generation density, and no greenhouse gas emissions, contributing to preventing the worst effects of climate change and making an enduring contribution to future energy supply. However, the intense conditions inside a fusion power plant (extreme temperatures and high magnetic fields necessary for nuclear fusion) call for addressing several potential problems. These include the development of new materials with extremely high heat tolerances and low enough vapor pressure and the design of mechanical structures that can withstand the electromagnetic force generated as well as feedback controllers to measure and counteract the unstable modes of evolution of the plasma, to name a few. The future of nuclear fusion as an efficient alternative energy source depends largely on techniques that enable us to control these instabilities. Mathematical modelling and physical experiments attempt to overcome some of the hindrances posed by these complexities. This book provides a comprehensive overview of the current state of the art in this fascinating and critically important field of pure and applied physics, mathematics, and engineering, presenting some of the most recent developments in theory, modelling, algorithms, experiments, and applications.

Advances in Fusion Energy Research

Advances in Fusion Energy Research

Edited by Bruno Carpentieri

Books edited

Recent Developments in the Solution of Nonlinear Differential Equations

Recent Developments in the Solution of Nonlinear Differential Equations

Edited by Bruno Carpentieri

Advances in Dynamical Systems Theory, Models, Algorithms and Applications

Advances in Dynamical Systems Theory, Models, Algorithms and Applications

Edited by Bruno Carpentieri

Applied Mathematics

Applied Mathematics

Edited by Bruno Carpentieri

Chapters authored

Fast Preconditioned Krylov Methods for Boundary Integral Equations in Electromagnetic Scattering

By Bruno Carpentieri

Part of the book: Trends in Electromagnetism

Multilevel Variable-Block Schur-Complement-Based Preconditioning for the Implicit Solution of the Reynolds- Averaged Navier-Stokes Equations Using Unstructured Grids

By Bruno Carpentieri and Aldo Bonfiglioli

Implicit methods based on the Newton’s rootfinding algorithm are receiving an increasing attention for the solution of complex Computational Fluid Dynamics (CFD) applications due to their potential to converge in a very small number of iterations. This approach requires fast convergence acceleration techniques in order to compete with other conventional solvers, such as those based on artificial dissipation or upwind schemes, in terms of CPU time. In this chapter, we describe a multilevel variable-block Schur-complement-based preconditioning for the implicit solution of the Reynolds-averaged Navier-Stokes equations using unstructured grids on distributed-memory parallel computers. The proposed solver detects automatically exact or approximate dense structures in the linear system arising from the discretization, and exploits this information to enhance the robustness and improve the scalability of the block factorization. A complete study of the numerical and parallel performance of the solver is presented for the analysis of turbulent Navier-Stokes equations on a suite of three-dimensional test cases.

Part of the book: Computational Fluid Dynamics

An Effective H2-LU Preconditioner for Iterative Solution of MQS Integral-Based Formulation P

By Salvatore Ventre, Bruno Carpentieri, Gaspare Giovinco, Antonello Tamburrino, Fabio Villone and Guglielmo Rubinacci

We present iterative solution strategies for solving efficiently Magneto-Quasi-Static (MQS) problems expressed in terms of an integral formulation based on the electric vector potential. Integral formulations give rise to discrete models characterized by linear systems with dense coefficient matrices. Iterative Krylov subspace methods combined with fast compression techniques for the matrix-vector product operation are the only viable approach for treating large scale problems, such as those considered in this study. We propose a fully algebraic preconditioning technique built upon the theory of H2-matrix representation that can be applied to different integral operators and to changes in the geometry, only by tuning a few parameters. Numerical experiments show that the proposed methodology performs much better than the existing one in terms of ability to reduce the number of iterations of a Krylov subspace method, especially for fast transient analysis.

Part of the book: Advances in Fusion Energy Research

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