Fracture propagation and stress corrosion in the case of dissimilar laser hybrid welded joints

The paper addresses the fracture propagation and stress corrosion behaviour of laser hybrid welds achieved between low carbon steel and stainless steel thin sheets. The crack propagation within these overmatched in strength welds was investigated by crack tip opening displacement (CTOD) on CT specimens notched transverse to the weld. A Digital Image Correlation System was used to qualify and estimate the initial crack length obtained by fatigue. The results are associated with the fractographic examinations of various regions of laser hybrid joints. Stress corrosion behaviour of the joint is also discussed.

Overall and local mechanical behaviour of dissimilar laser welded joints

The present investigation addresses the overall and local mechanical performance of dissimilar joints of low carbon steel (CS) and stainless steel (SS) thin sheets achieved by laser welding in case of heat source displacement from the weld gap centreline towards CS. Microstructure characterization and residua! strain scanning, carried out by neutron diffraction, were used to assess the joints features. It was found that the heat source position influences the base metals dilution and the residua! stress field associated to the welding process; the transverse residual stress is smaller than for the longitudinal component, of magnitudes close to the parent CS yield strength. Furthermore, compressive transverse residual stresses were encountered at the SS-weld interface. The tensile behavior of the joint different zones assessed by using a video-image based system (VIC-2D) reveals that the residual stress field, together with the positive difference in yield between the weld metal and the base materials protects the joint from being piastically deformed. The tensile loadings of flat transverse specimens generate the strain localization and failure in CS, far away from the weld.En este trabajo se exponen los resultados de una investigacion sobre el comportamiento mecanico de soldaduras disimiles acero inoxidable-acero al carbono, realizadas para unir chapas delgadas, desplazando la fuente de calor del eje longitudinal de la union soldada por laser sobre el acero al carbono. Se han determinado las caracteristicas microestructurales de la union soldada, las tensiones residuales generadas (mediante difraccion de neutrones) y las curvas tension-deformacion locales y globales, mediante medidas locales de deformacion empleando el sistema VIC-2D "video image correlation". El desplazamiento de la fuente de calor infiuye en la dilution de los metales base y el campo de tensiones residuales asociado al proceso de soldeo; las tensiones residuales medidas en direction longitudinal se aproximan al limite elastico del acero al carbono, mientras que las tensiones residuales transversales son menores, e incluso de compresion. El ensayo a traccion de la union soldada revela que las tensiones residuales y la diferencia de limite elastico entre los metales base y la soldadura propician que la rotura se produzca por inestabilidad plastica del acero al carbono, lejos de la soldadura, sin que la union plastifique.

Brain tissue segmentation on Diffusion Weighted Magnetic Resonance data

Introduction Diffusion weighted Imaging (DWI) techniques are able to measure, in vivo and non-invasively, the diffusivity of water molecules inside the human brain. DWI has been applied on cerebral ischemia, brain maturation, epilepsy, multiple sclerosis, etc. [1]. Nowadays, there is a very high availability of these images. DWI allows the identification of brain tissues, so its accurate segmentation is a common initial step for the referred applications. Materials and Methods We present a validation study on automated segmentation of DWI based on the Gaussian mixture and hidden Markov random field models. This methodology is widely solved with iterative conditional modes algorithm, but some studies suggest [2] that graph-cuts (GC) algorithms improve the results when initialization is not close to the final solution. We implemented a segmentation tool integrating ITK with a GC algorithm [3], and a validation software using fuzzy overlap measures [4]. Results Segmentation accuracy of each tool is tested against a gold-standard segmentation obtained from a T1 MPRAGE magnetic resonance image of the same subject, registered to the DWI space. The proposed software shows meaningful improvements by using the GC energy minimization approach on DTI and DSI (Diffusion Spectrum Imaging) data. Conclusions The brain tissues segmentation on DWI is a fundamental step on many applications. Accuracy and robustness improvements are achieved with the proposed software, with high impact on the application’s final result.

MBIS: Multivariate Bayesian Image Segmentation Tool

We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multi-channel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.

Development and characterization of an FK photovoltaic concentrator for maximum conversion efficiency

The outdoor measurements of a single-cell concentrator PV module reaching a regressed 35.6% efficiency and a maximum peak efficiency of 36.0% (both corrected @Tcell=25ºC) are presented. This is the result of the joint effort by LPI and Solar Junction to demonstrate the potential of combining their respective state-of-the-art concentrator optics and solar cells. The LPI concentrator used is an FK, which is an advanced nonimaging concentrator using 4-channel Köhler homogenization, with a primary Fresnel lens and a refractive secondary made of glass. Solar Junction’s cell is a triplejunction solar cell with the A-SLAMTM architecture using dilute-nitrides.

Quantitative evaluation of patient-specific conforming hexahedral meshes of abdominal aortic aneurysms and intraluminal thrombus generated from MRI

A novel method for generating patient-specific high quality conforming hexahedral meshes is presented. The meshes are directly obtained from the segmentation of patient magnetic resonance (MR) images of abdominal aortic aneu-rysms (AAA). The MRI permits distinguishing between struc-tures of interest in soft tissue. Being so, the contours of the lumen, the aortic wall and the intraluminal thrombus (ILT) are available and thus the meshes represent the actual anato-my of the patient?s aneurysm, including the layered morpholo-gies of these structures. Most AAAs are located in the lower part of the aorta and the upper section of the iliac arteries, where the inherent tortuosity of the anatomy and the presence of the ILT makes the generation of high-quality elements at the bifurcation is a challenging task. In this work we propose a novel approach for building quadrilateral meshes for each surface of the sectioned geometry, and generating conforming hexahedral meshes by combining the quadrilateral meshes. Conforming hexahedral meshes are created for the wall and the ILT. The resulting elements are evaluated on four patients? datasets using the Scaled Jacobian metric. Hexahedral meshes of 25,000 elements with 94.8% of elements well-suited for FE analysis are generated.

Estimation of modal parameters in structures using multiple time history records

In Operational Modal Analysis of structures we often have multiple time history records of vibrations measured at different time instants. This work presents a procedure for estimating the modal parameters of the structure processing all the records, that is, using all available information to obtain a single estimate of the modal parameters. The method uses Maximum Likelihood Estimation and the Expectation Maximization algorithm. Finally, it has been applied to various problems for both simulated and real structures and the results show the advantage of the joint analysis proposed.

Assessment of CTF boiling transition and critical heat flux modeling capabilities using the OECD/NRC BFBT and PSBT benchmark databases

Over the last few years, the Pennsylvania State University (PSU) under the sponsorship of the US Nuclear Regulatory Commission (NRC) has prepared, organized, conducted, and summarized two international benchmarks based on the NUPEC data—the OECD/NRC Full-Size Fine-Mesh Bundle Test (BFBT) Benchmark and the OECD/NRC PWR Sub-Channel and Bundle Test (PSBT) Benchmark. The benchmarks’ activities have been conducted in cooperation with the Nuclear Energy Agency/Organization for Economic Co-operation and Development (NEA/OECD) and the Japan Nuclear Energy Safety (JNES) Organization. This paper presents an application of the joint Penn State University/Technical University of Madrid (UPM) version of the well-known sub-channel code COBRA-TF (Coolant Boiling in Rod Array-Two Fluid), namely, CTF, to the steady state critical power and departure from nucleate boiling (DNB) exercises of the OECD/NRC BFBT and PSBT benchmarks. The goal is two-fold: firstly, to assess these models and to examine their strengths and weaknesses; and secondly, to identify the areas for improvement.

Characterisation of laser hybrid welded dissimilar joints

The investigation addresses the over-all performance of dissimilar joints of low carbon steel and stainless steel thin sheets achieved by laser hybrid welding. First, the technological de-velopment of dissimilar laser hybrid welding of thin sheets is briefly pre-sented. Joint characterisation by means of macro and microstructural examination and hardness tests is fur-ther described. Microhardness testing was used as an alternative and effi-cient mean of assessing the changes in mechanical properties of difficult to characterize areas, like HAZ and fu-sion zone of these thin sheets Laser-GMA dissimilar welded joints. The overall tensile performance of the joint is discussed together with the weld metal strength overmatching. The ten-sile tests results indicate that in case of transversally loaded joints, the po-sitive difference in yield strength between the weld metal and the base materials (overmatching welds) may reduce the weight of the structure, without diminishing its strength.

Mechanical behavior and residual stress field of dissimilar laser welded joints

The present investigation addresses the mechanical behavior and residual stress field of dissimilar joints produced by laser welding. Microstructure characterization and residual strain scanning, carried out by neutron diffraction, were used to assess the joints features. It was found that the heat source position influences the base metals dilution and the residual stress field associated to the welding process. The tensile behavior of the joint, different zones achieved by using a video-image based system (VIC-2D) reveals that the residual stress field, together with the positive difference in yield between the weld metal and the base materials protects the joint from being plastically deformed.

3D segmentations of neuronal nuclei from confocal microscope image stacks

In this paper, we present an algorithm to create 3D segmentations of neuronal cells from stacks of previously segmented 2D images. The idea behind this proposal is to provide a general method to reconstruct 3D structures from 2D stacks, regardless of how these 2D stacks have been obtained. The algorithm not only reuses the information obtained in the 2D segmentation, but also attempts to correct some typical mistakes made by the 2D segmentation algorithms (for example, under segmentation of tightly-coupled clusters of cells). We have tested our algorithm in a real scenario?the segmentation of the neuronal nuclei in different layers of the rat cerebral cortex. Several representative images from different layers of the cerebral cortex have been considered and several 2D segmentation algorithms have been compared. Furthermore, the algorithm has also been compared with the traditional 3D Watershed algorithm and the results obtained here show better performance in terms of correctly identified neuronal nuclei.

A new label fusion method using graph cuts: application to hippocampus segmentation

The aim of this paper is to develop a probabilistic modeling framework for the segmentation of structures of interest from a collection of atlases. Given a subset of registered atlases into the target image for a particular Region of Interest (ROI), a statistical model of appearance and shape is computed for fusing the labels. Segmentations are obtained by minimizing an energy function associated with the proposed model, using a graph-cut technique. We test different label fusion methods on publicly available MR images of human brains.

Overall vs. local mechanical behaviour of ferritic austenitic steel joints made by laser welding

The present investigation addresses the overall and local mechanical performance of dissimilar joints of low carbon steel (CS) and stainless Steel (SS) thin sheets achieved by laser welding in case of heat source displacement from the weld gap centreline towards CS. Welding was performed on a Nd:YAG laser DY033 (3300 W) in a continuos wave (CW), keyhole mode. The tensile behavior of the joint different zones assessed by using a video-image based system (VIC-2D) reveals that the residual stress field, together with the positive difference in yield between the weld metal and the base materials protects the joint from being plastically deformed. The tensile loadings of flat transverse specimens generate the strain localization and failure in CS, far away from the weld.

Conditional density approximations with mixtures of polynomials

Mixtures of polynomials (MoPs) are a non-parametric density estimation technique especially designed for hybrid Bayesian networks with continuous and discrete variables. Algorithms to learn one- and multi-dimensional (marginal) MoPs from data have recently been proposed. In this paper we introduce two methods for learning MoP approximations of conditional densities from data. Both approaches are based on learning MoP approximations of the joint density and the marginal density of the conditioning variables, but they differ as to how the MoP approximation of the quotient of the two densities is found. We illustrate and study the methods using data sampled from known parametric distributions, and we demonstrate their applicability by learning models based on real neuroscience data. Finally, we compare the performance of the proposed methods with an approach for learning mixtures of truncated basis functions (MoTBFs). The empirical results show that the proposed methods generally yield models that are comparable to or significantly better than those found using the MoTBF-based method.

Investigations on the distribution of air transport traffic and CO2 emissions within the European Union

This study analyses the structure of air traffic and its distribution among the different countries in the European Union, as well as traffic with an origin or destination in non-EU countries. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO2 emissions data. The segmentation of air traffic in terms of distance permits an assessment of air transport competition with surface transport modes. The results show a clear concentration of traffic in the five larger countries (France, Germany, Italy, Spain and UK), in terms of RPKs. In terms of distance the segment between 500 and 1000 km in the EU, has more flights, passengers, RTKs and CO2 emissions than larger distances. On the environmental side, the distribution of CO2 emissions within the EU Member States is presented, together with fuel efficiency parameters. In general, a direct relationship between RPKs and CO2 emissions is observed for all countries and all distance bands. Consideration is given to the uptake of alternative fuels. Segmenting CO2 emissions per distance band and aircraft type reveals which flights contribute the most the overall EU CO2 emissions. Finally, projections for future CO2 emissions are estimated, according to three different air traffic growth and biofuel introduction scenarios.