Properties of optical ducts, their chromatism and its effects on astronomical refraction

The fundamental quadrature governing light rays in a spherically symmetrical medium is first recalled. A rigorous discussion of some qualitative properties of its solutions follows, using the Young-Kattawar diagram which leads to a geometric formulation of the ray curvature. The case of an optical duct is deepened, analyzing transfer curves for different positions of the observer with respect to the duct. New analytical expressions for their wavelength dependence are derived, and their numerical consequences are coherent with computer simulations.Comment: in Frenc

La photométrie des éclipses de Lune, vue par František Link : commentaire historique

International audienc

Pharmacist orientation to rural and remote practice: how are we doing?

Methods: Information was gathered from the four students using narrative techniques, with their journals describing both personal and professional experiences. Content Analysis was then applied to the data, using the Social Representation Theory. Students were also required to generate an orientation brochure, appropriate for a pharmacist commencing employment in a rural and remote location

Short review on the refractive index of air as a function of temperature, pressure, humidity and ionization

The empirical law of Gladstone-Dale is insufficient for high-precision studies using the refractivity of a gas: this is not exactly proportional to its density, and the gas may not be properly described as perfect. An optical Mariotte temperature allows making a comparative analysis of the results given by various authors. The effect of hygrometry on the refractivity at visible wavelengths is historically traced and its small effect on the astronomical refraction angle numerically shown. Finally at infrared and radio wavelengths, the effects of the humidity in the lower atmosphere can be strong; as for the ionosphere, its curvature plays an essential role for the astronomical refraction angle unlike in the visible.Comment: in Frenc

Assessment of Neural Network Augmented Reynolds Averaged Navier Stokes Turbulence Model in Extrapolation Modes

A machine-learned (ML) model is developed to enhance the accuracy of turbulence transport equations of Reynolds Averaged Navier Stokes (RANS) solver and applied for periodic hill test case, which involves complex flow regimes, such as attached boundary layer, shear-layer, and separation and reattachment. The accuracy of the model is investigated in extrapolation modes, i.e., the test case has much larger separation bubble and higher turbulence than the training cases. A parametric study is also performed to understand the effect of network hyperparameters on training and model accuracy and to quantify the uncertainty in model accuracy due to the non-deterministic nature of the neural network training. The study revealed that, for any network, less than optimal mini-batch size results in overfitting, and larger than optimal batch size reduces accuracy. Data clustering is found to be an efficient approach to prevent the machine-learned model from over-training on more prevalent flow regimes, and results in a model with similar accuracy using almost one-third of the training dataset. Feature importance analysis reveals that turbulence production is correlated with shear strain in the free-shear region, with shear strain and wall-distance and local velocity-based Reynolds number in the boundary layer regime, and with streamwise velocity gradient in the accelerating flow regime. The flow direction is found to be key in identifying flow separation and reattachment regime. Machine-learned models perform poorly in extrapolation mode, wherein the prediction shows less than 10% correlation with Direct Numerical Simulation (DNS). A priori tests reveal that model predictability improves significantly as the hill dataset is partially added during training in a partial extrapolation model, e.g., with the addition of only 5% of the hill data increases correlation with DNS to 80%.Comment: 50 pages, 18 figure