23 research outputs found
Investments in Romania before and after the E.U. accession
The investments are still an important factor for economic and social development through their implications, structure and quality. An analysis of the investments role in our country can be achieved only by having in view both Retrospective and the prospective context. The present paper analyses economic efficiency of investments as well as the role of investments in economy, as an economic growth factor. Overall, this paper has implications for research examining the investment efficiency and the economic consequences on our country between 2000 and 2008, namely before and after Romania accession to E.U.Investments; Efficiency; Economic growth
Bayesian calibration of interatomic potentials for binary alloys
Developing reliable interatomic potential models with quantified predictive
accuracy is crucial for atomistic simulations. Commonly used potentials, such
as those constructed through the embedded atom method (EAM), are derived from
semi-empirical considerations and contain unknown parameters that must be
fitted based on training data. In the present work, we investigate Bayesian
calibration as a means of fitting EAM potentials for binary alloys. The
Bayesian setting naturally assimilates probabilistic assertions about uncertain
quantities. In this way, uncertainties about model parameters and model errors
can be updated by conditioning on the training data and then carried through to
prediction. We apply these techniques to investigate an EAM potential for a
family of gold-copper systems in which the training data correspond to
density-functional theory values for lattice parameters, mixing enthalpies, and
various elastic constants. Through the use of predictive distributions, we
demonstrate the limitations of the potential and highlight the importance of
statistical formulations for model error.Comment: Preprint, 28 pages, 18 figures, accepted for publication in
Computational Materials Science on 7/11/202
Compressive sensing adaptation for polynomial chaos expansions
Basis adaptation in Homogeneous Chaos spaces rely on a suitable rotation of
the underlying Gaussian germ. Several rotations have been proposed in the
literature resulting in adaptations with different convergence properties. In
this paper we present a new adaptation mechanism that builds on compressive
sensing algorithms, resulting in a reduced polynomial chaos approximation with
optimal sparsity. The developed adaptation algorithm consists of a two-step
optimization procedure that computes the optimal coefficients and the input
projection matrix of a low dimensional chaos expansion with respect to an
optimally rotated basis. We demonstrate the attractive features of our
algorithm through several numerical examples including the application on
Large-Eddy Simulation (LES) calculations of turbulent combustion in a HIFiRE
scramjet engine.Comment: Submitted to Journal of Computational Physic