Fuel Consumption Minimization Procedure of Sail-assisted Motor Vessel based on a Systematic Meshing of the Explored Area

International audienc

Uncertainty quantification for wind energy applications

Uncertainties are omni-present in wind energy applications, both in external conditions (such as wind and waves) as well as in the models that are used to predict key quantities such as costs, energy yield, and fatigue loads. This report summarizes and reviews the application of uncertainty quantification techniques to wind energy problems. In th

Chaos and Turbulent Nucleosynthesis Prior to a Supernova Explosion

Three-dimensional (3D), time dependent numerical simulations, of flow of matter in stars, now have sufficient resolution to be fully turbulent. The late stages of the evolution of massive stars, leading up to core collapse to a neutron star (or black hole), and often to supernova explosion and nucleosynthesis, are strongly convective because of vigorous neutrino cooling and nuclear heating. Unlike models based on current stellar evolutionary practice, these simulations show a chaotic dynamics characteristic of highly turbulent flow. Theoretical analysis of this flow, both in the Reynolds-averaged Navier-Stokes (RANS) framework and by simple dynamic models, show an encouraging consistency with the numerical results. It may now be possible to develop physically realistic and robust procedures for convection and mixing which (unlike 3D numerical simulation) may be applied throughout the long life times of stars. In addition, a new picture of the presupernova stages is emerging which is more dynamic and interesting (i.e., predictive of new and newly observed phenomena) than our previous one.Comment: 11 pages, 2 figures, Submitted to AIP Advances: Stardust, added figures and modest rewritin

On the generation of probabilistic forecasts from deterministic models

Most of the methods that produce space weather forecasts are based on deterministic models. In order to generate a probabilistic forecast, a model needs to be run several times sampling the input parameter space, in order to generate an ensemble from which the distribution of outputs can be inferred. However, ensemble simulations are costly and often preclude the possibility of real-time forecasting. We introduce a simple and robust method to generate uncertainties from deterministic models, that does not require ensemble simulations. The method is based on the simple consideration that a probabilistic forecast needs to be both accurate and well calibrated (reliable). We argue that these two requirements are equally important, and we introduce the Accuracy-Reliability cost function that quantitatively measures the trade-off between accuracy and reliability. We then define the optimal uncertainties as the standard deviation of the Gaussian distribution that minimizes the cost function. We demonstrate that this simple strategy, implemented here by means of a deep neural network, produces accurate and well-calibrated forecasts, showing examples both on synthetic and real-world space weather data

The Extraordinarily Rapid Expansion of the X-ray Remnant of Kepler's Supernova (SN1604)

Four individual high resolution X-ray images from ROSAT and the Einstein Observatory have been used to measure the expansion rate of the remnant of Kepler's supernova (SN 1604). Highly significant measurements of the expansion have been made for time baselines varying from 5.5 yrs to 17.5 yrs. All measurements are consistent with a current expansion rate averaged over the entire remnant of 0.239 (+/-0.015) (+0.017,-0.010) % per yr, which, when combined with the known age of the remnant, determines the expansion parameter m, defined as $R\propto t^m$, to be 0.93 (+/-0.06) (+0.07,-0.04). The error bars on these results include both statistical (first set of errors) and systematic (second set) uncertainty. According to this result the X-ray remnant is expanding at a rate that is remarkably close to free expansion and nearly twice as fast as the mean expansion rate of the radio remnant. The expansion rates as a function of radius and azimuthal angle are also presented based on two ROSAT images that were registered to an accuracy better than 0.5 arcseconds. Significant radial and azimuthal variations that appear to arise from the motion of individual X-ray knots are seen. The high expansion rate of the X-ray remnant appears to be inconsistent with currently accepted dynamical models for the evolution of Kepler's SNR.Comment: 14 pages, including 7 postscript figs, LaTeX, emulateapj. Accepted by Ap