Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

Integration of NDE Reliability and Fracture Mechanics

The Pacific Northwest Laboratory is conducting a four-phase program for measuring and evaluating the effectiveness and reliability of in-service inspection (lSI} performed on the primary system piping welds of commercial light water reactors (LWRs). Phase I of the program is complete. A survey was made of the state of practice for ultrasonic rsr of LWR primary system piping welds. Fracture mechanics calculations were made to establish required nondestrutive testing sensitivities. In general, it was found that fatigue flaws less than 25% of wall thickness would not grow to failure within an inspection interval of 10 years. However, in some cases failure could occur considerably faster. Statistical methods for predicting and measuring the effectiveness and reliability of lSI were developed and will be applied in the "Round Robin Inspections" of Phase II. Methods were also developed for the production of flaws typical of those found in service. Samples fabricated by these methods wilI be used in Phase II to test inspection effectiveness and reliability. Measurements were made of the influence of flaw characteristics {i.e., roughness, tightness, and orientation) on inspection reliability. These measurernents, as well as the predictions of a statistical model for inspection reliability, indicate that current reporting and recording sensitivities are inadequate

Power laws and inverse motion modelling: application to turbulence measurements from satellite images

In the context of tackling the ill-posed inverse problem of motion estimation from image sequences, we propose to introduce prior knowledge on flow regularity given by turbulence statistical models. Prior regularity is formalised using turbulence power laws describing statistically self-similar structure of motion increments across scales. The motion estimation method minimises the error of an image observation model while constraining second-order structure function to behave as a power law within a prescribed range. Thanks to a Bayesian modelling framework, the motion estimation method is able to jointly infer the most likely power law directly from image data. The method is assessed on velocity fields of 2-D or quasi-2-D flows. Estimation accuracy is first evaluated on a synthetic image sequence of homogeneous and isotropic 2-D turbulence. Results obtained with the approach based on physics of fluids outperform state-of-the-art. Then, the method analyses atmospheric turbulence using a real meteorological image sequence. Selecting the most likely power law model enables the recovery of physical quantities, which are of major interest for turbulence atmospheric characterisation. In particular, from meteorological images we are able to estimate energy and enstrophy fluxes of turbulent cascades, which are in agreement with previous in situ measurements