Semi-Lagrangian methods for parabolic problems in divergence form

Semi-Lagrangian methods have traditionally been developed in the framework of hyperbolic equations, but several extensions of the Semi-Lagrangian approach to diffusion and advection--diffusion problems have been proposed recently. These extensions are mostly based on probabilistic arguments and share the common feature of treating second-order operators in trace form, which makes them unsuitable for mass conservative models like the classical formulations of turbulent diffusion employed in computational fluid dynamics. We propose here some basic ideas for treating second-order operators in divergence form. A general framework for constructing consistent schemes in one space dimension is presented, and a specific case of nonconservative discretization is discussed in detail and analysed. Finally, an extension to (possibly nonlinear) problems in an arbitrary number of dimensions is proposed. Although the resulting discretization approach is only of first order in time, numerical results in a number of test cases highlight the advantages of these methods for applications to computational fluid dynamics and their superiority over to more standard low order time discretization approaches

The Forecasting Performance of Dynamic Factor Models with Vintage Data

We present a comparative analysis of the forecasting performance of two dynamic factor models, the Stock and Watson (2002a, b) model and the Forni, Hallin, Lippi and Reichlin (2005) model, based on vintage data. Our dataset that contains 107 monthly US “first release” macroeconomic and financial vintage time series, spanning the 1996:12 to 2017:6 period with monthly periodicity, extracted from the Bloomberg database† . We compute real-time one-month-ahead forecasts with both models for four key macroeconomic variables: the month-on-month change in industrial production, the unemployment rate, the core consumer price index and the ISM Purchasing Managers’ Index. First, we find that both the Stock and Watson and the Forni, Hallin, Lippi and Reichlin models outperform simple autoregressions for industrial production, unemployment rate and consumer prices, but that only the first model does so for the PMI. Second, we find that neither models always outperform the other. While Forni, Hallin, Lippi and Reichlin’s beats Stock and Watson’s in forecasting industrial production and consumer prices, the opposite happens for the unemployment rate and the PMI

Keck Imaging of Binary L Dwarfs

We present Keck near-infrared imaging of three binary L dwarf systems, all of which are likely to be sub-stellar. Two are lithium dwarfs, and a third exhibits an L7 spectral type, making it the coolest binary known to date. All have component flux ratios near 1 and projected physical separations between 5 and 10 AU, assuming distances of 18 to 26 pc from recent measurements of trigonometric parallax. These surprisingly similar binaries represent the sole detections of companions in ten L dwarf systems which were analyzed in the preliminary phase of a much larger dual-epoch imaging survey. The detection rate prompts us to speculate that binary companions to L dwarfs are common, that similar-mass systems predominate, and that their distribution peaks at radial distances in accord both with M dwarf binaries and with the radial location of Jovian planets in our own solar system. To fully establish these conjectures against doubts raised by biases inherent in this small preliminary survey, however, will require quantitative analysis of a larger volume-limited sample which has been observed with high resolution and dynamic range.Comment: LaTex manuscript in 13 pages, 3 postscript figures, Accepted for publication in the Letters of the Astrophysical Journal; Postscript pre-print version available at: http://www.hep.upenn.edu/PORG/papers/koerner99a.p

Dynamic models for Large Eddy Simulation of compressible flows with a high order DG method

The impact of dynamic models for applications to LES of compressible flows is assessed in the framework of a numerical model based on high order discontinuous finite elements. The projections onto lower dimensional subspaces associated with lower degree basis functions are used as LES filter, along the lines proposed in Variational Multiscale templates. Comparisons with DNS results available in the literature for plane and constricted channel flows at Mach numbers 0.2, 0.7 and 1.5 show clearly that the dynamic models are able to improve the prediction of most key features of the flow with respect to the Smagorinsky models employed so far in a VMS-DG context

Reliability of a 2-Bout exercise test on a Wattbike cycle ergometer

Purpose: To determine the intraday and interday reliability of a 2 × 4-min performance test on a cycle ergometer (Wattbike) separated by 30 min of passive recovery (2 × 4MMP). Methods: Twelve highly trained cyclists (mean ± SD; age = 20 ± 2 y, predicted VO2max = 59.0 ± 3.6 mL · kg–1 · min–1) completed six 2 × 4MMP cycling tests on a Wattbike ergometer separated by 7 d. Mean power was measured to determine intraday (test 1 [T1] to test 2 [T2]) and interday reliability (weeks 1–6) over the repeated trials. Results: The mean intraday reliabilities of the 2 × 4MMP test, as expressed by the typical error of measurement (TEM, W) and coefficient of variation (CV, %) over the 6 wk, were 10.0 W (95% confidence limits [CL] 8.2–11.8), and 2.6% (95%CL 2.1–3.1), respectively. The mean interday reliability TEM and CV for T1 over the 6 wk were 10.4 W (95%CL 8.7–13.3) and 2.7% (95%CL 2.3–3.5), respectively, and 11.7 W (95%CL 9.8–15.1) and 3.0% (95%CL 2.5–3.9) for T2. Conclusion: The testing protocol performed on a Wattbike cycle ergometer in the current study is reproducible in highly trained cyclists. The high intraday and interday reliability make it a reliable method for monitoring cycling performance and for investigating factors that affect performance in cycling events