Density Measurements in the Base Flow Region of HRV Afterbody-Nozzle Configuration

A preliminary study to document the mean density field using Background Oriented Schlieren (BOS) has been carried out on a 1:10 scaled model of HSTDV afterbodynozzle configuration system at a freestream Mach number of 3.5 with unit Reynolds number of 38x106 per meter. The results show that the mean density field is quite adequately captured with the BOS technique with the derived Schlieren results matching well with conventional Schlieren images and with density data derived from pressure measurements on the ramp. While the data at nozzle exit is not reliable due to strong asymmetric 3D effects, presumably due to the flow expansion on the cowl lip influencing the flow field in the vicinity, the results show that flow field variable like density shows local effects better (e.g. local effect of the cowl extension) and this has been captured by the BOS whereas the wall static pressures do not show this effect. Streamwise variation of the density along the jet centerline and parallel to the ramp are presented showing that useful quantitative information can be extracted through this technique. The results would be useful for CFD code

Tracking and mixed-ability grouping in secondary school mathematics classrooms: a case study

This paper reports the findings of a retrospective study of ‘tracked’ grouping in a mathematics department in a co-educational comprehensive school in Greater London. Tracking consisted here of just two tracks, a 'fast track' for the top 25-30% of a cohort, and 'mixed tracks' for the remainder. The paper outlines the reasons for introducing tracking and explores the effects of this through analysis of interviews with teachers and data on the progress of students from age 14 to age 16. The teachers reported that tracking impacted differently on different students, and this is borne out by the quantitative data. It was not possible to provide for ‘setting’ across all the mathematics classrooms in the focal cohort, and one mixedability class was created. The use of analysis of covariance (ANCOVA) models shows that fast-track students were not significantly advantaged by their placement in these tracks, but the progress of students in the mixed-ability group showed a significant interaction between progress and prior attainment, with placement in the mixed-ability group conferring a significant advantage on lower-attaining students, while the disadvantage to higher attaining students was much smaller

Convolutional Dictionary Regularizers for Tomographic Inversion

There has been a growing interest in the use of data-driven regularizers to solve inverse problems associated with computational imaging systems. The convolutional sparse representation model has recently gained attention, driven by the development of fast algorithms for solving the dictionary learning and sparse coding problems for sufficiently large images and data sets. Nevertheless, this model has seen very limited application to tomographic reconstruction problems. In this paper, we present a model-based tomographic reconstruction algorithm using a learnt convolutional dictionary as a regularizer. The key contribution is the use of a data-dependent weighting scheme for the l1 regularization to construct an effective denoising method that is integrated into the inversion using the Plug-and-Play reconstruction framework. Using simulated data sets we demonstrate that our approach can improve performance over traditional regularizers based on a Markov random field model and a patch-based sparse representation model for sparse and limited-view tomographic data sets

Magnetic Non-Potentiality of Solar Active Regions and Peak X-Ray Flux of the Associated Flares

Predicting the severity of the solar eruptive phenomena like flares and Coronal Mass Ejections (CMEs) remains a great challenge despite concerted efforts for several decades. The advent of high quality vector magnetograms obtained from Hinode (SOT/SP) has increased the possibility of meeting this challenge. In particular, the Spatially Averaged Signed Shear Angle (SASSA) seems to be an unique parameter to quantify the non-potentiality of the active regions. We demonstrate the usefulness of SASSA for predicting the flare severity. For this purpose we present case studies of the evolution of magnetic non-potentiality using 115 vector magnetograms of four active regions namely ARs NOAA 10930, 10960, 10961 and 10963 during December 08-15, 2006, June 03-10, 2007, June 28-July 5, 2007 and July 10-17, 2007 respectively. The NOAA ARs 10930 and 10960 were very active and produced X and M class flares respectively, along with many smaller X-ray flares. On the other hand, the NOAA ARs 10961 and 10963 were relatively less active and produced only very small (mostly A and B-class) flares. For this study we have used a large number of high resolution vector magnetograms obtained from Hinode (SOT/SP). The analysis shows that the peak X-ray flux of the most intense solar flare emanating from the active regions depends on the magnitude of the SASSA at the time of the flare. This finding of the existence of a lower limit of SASSA for a given class of X-ray flare will be very useful for space weather forecasting. We have also studied another non-potentiality parameter called mean weighted shear angle (MWSA) of the vector magnetograms along with SASSA. We find that the MWSA does not show such distinction as the SASSA for upper limits of GOES X-Ray flux of solar flares, however both the quantities show similar trends during the evolution of all active regions studied.Comment: 25 pages, 5 figures, accepted for publication in the Astrophysical Journa