A Paris Law Based Mesh Independent Numerical Methodology for the Simulation of Fatigue Driven Delamination in Composites

Delamination evolution under cyclic loading is one of the most important research topics for the application of composite materials to aerospace, naval, automotive and, in general, transportation fields. Large experimental campaigns are needed to assess the fatigue behavior of Carbon Fiber Reinforced Polymers (CFRPs), which may result extremely time and cost consuming. Nevertheless, composite materials design needs to take into account the evolution of fatigue driven damage. Subsequently, the development of efficient and robust computational finite element methodologies to evaluate progression of delamination in composite structural components subjected to cyclic loading conditions has become relevant. In this paper, a numerical finite element procedure able to simulate the fatigue driven delamination growth is introduced. A Paris-law based cycle jump strategy, combined with the Virtual Crack Closure Technique (VCCT) approach, has been implemented in the commercial Finite Element Code ANSYS MECHANICAL via the Ansys Parametric Design Language (APDL). The main advantages of the proposed numerical procedure, named FT-SMXB, are related to its independence on the time step and element size in the frame of incremental analyses. The procedure has been preliminary validated, in this research study, at coupon level, by comparing the numerical results to literature experimental data on a unidirectional graphite/epoxy Double Cantilever Beam (DCB) specimen. The significant agreement between the obtained numerical results and the literature experimental benchmark data confirms the accuracy and the potential of the proposed methodology

Identification of surgically-induced longitudinal lesions of the equine deep digital flexor tendon in the digital flexor tendon sheath using contrast-enhanced ultrasonography: an ex-vivo pilot study

BACKGROUND: Longitudinal tears in the lateral aspect of the deep digital flexor tendon are the most common causes of pain localised to the equine digital flexor tendon sheath. However conventional ultrasonographic techniques provide limited information about acute lesions. Ultrasonographic contrast agents are newly developed materials that have contributed to advancement in human diagnostic imaging. They are currently approved for intravenous use in human and animal models. In this study we described intrathecal use in the horse. This study was undertaken to evaluate the reliability of standard and angle contrast-enhanced ultrasonography to detect and characterize surgically-induced longitudinal lesions in the deep digital flexor tendons. In this pilot study surgically-induced lesions were created in the lateral aspect of the deep digital flexor tendon within the digital flexor tendon sheath in 10 isolated equine limbs to generate a replicable model for naturally occurring lesions. Another 10 specimens were sham operated. All the limbs were examined ultrasonographically before and shortly after the intrasynovial injection of an ultrasound contrast agent containing stabilised microbubbles. The images were blindly evaluated to detect the ability to identify surgically-created lesions. The deep digital flexor tendons were dissected and a series of slices were obtained. The depth of longitudinal defects identified with contrast-enhanced ultrasound scans was compared to the real extent of the lesions measured in the corresponding gross tendon sections. RESULTS: Contrast-enhanced ultrasonography with both angle and standard approach provided a significant higher proportion of correct diagnoses compared to standard and angle contrast ultrasonography (p < 0.01). Contrast-enhanced ultrasonography reliably estimated the depth of surgically-induced longitudinal lesions in the deep digital flexor tendons. CONCLUSION: Contrast-enhanced ultrasound of the digital flexor tendon sheath could be an effective tool to detect intrasynovial longitudinal tears of the deep digital flexor tendon, although an in vivo study is required to confirm these results for naturally occurring lesions

Face Authentication using Speed Fractal Technique

In this paper, a new fractal based recognition method, Face Authentication using Speed Fractal Technique (FAST), is presented. The main contribution is the good compromise between memory requirements, execution time and recognition ratio. FAST is based on Iterated Function Systems (IFS) theory, largely studied in still image compression and indexing, but not yet widely used for face recognition. Indeed, Fractals are well known to be invariant to a large set of global transformations. FAST is robust with respect to meaningful variations in facial expression and to the small changes of illumination and pose. Another advantage of the FAST strategy consists in the speed up that it introduces. The typical slowness of fractal image compression is avoided by exploiting only the indexing phase, which requires time O(D log (D)), where D is the size of the domain pool. Lastly, the FAST algorithm compares well to a large set of other recognition methods, as underlined in the experimental results

BIRD: Watershed Based IRis Detection for mobile devices

Communications with a central iris database system using common wireless technologies, such as tablets and smartphones, and iris acquisition out of the field are important functionalities and capabilities of a mobile iris identification device. However, when images are acquired by means of mobile devices under uncontrolled acquisition conditions, noisy images are produced and the effectiveness of the iris recognition system is significantly conditioned. This paper proposes a technique based on watershed transform for iris detection in noisy images captured by mobile devices. The method exploits the information related to limbus to segment the periocular region and merges its score with the iris' one to achieve greater accuracy in the recognition phase

Ricerca sapienza. dal passato nel futuro

Il repertorio più aggiornato dei principali progetti di ricerca di Sapienza Università di Roma in tutti gli ambiti dello scibile umano: dalla storia antica all'astronautica, dalla medicina alla paleontologia, dall'informatica alle scienze umane, aggiornato alla fine del 2015. Ogni ricerca è illustrata attraverso un'intervista al docente responsabile del team, corredata di foto inedite e grafici esplicativi ed arricchita da un'ampia bibliografia

Kinematic Approach for a Global-Local Coupling: Compressive Behaviour of a Delaminated Panel:

A kinematic approach to global/local coupling has been applied to investigate the behaviour of a delaminated stiffened composite panel, by using an in-house finite element based procedure. The delamination growth phenomenon has been simulated by employing fracture elements implemented in the B2000++® code, which are based on the Modified Virtual Crack Closure Technique (MVCCT); this technique is able to compute the energy release rate on the delamination front for each fracture mode. A very fine three-dimensional mesh in the delaminated region has been considered in order to obtain a good prediction of the delamination growth. The rest of the structure has been modelled by means of shell elements. A global/local approach based on point-wise multipoint constraint has been implemented in the in-house-code and used to connect shell meshes to solid ones. A numerical application on a delaminated composite stiffened panel taken from literature has been introduced. Models characterized by different levels of complexity, i.e. without delamination, with delamination, with delamination growth have been considered and compared to understand the effectiveness of the introduced kinematic approach

Normal Maps vs. Visible Images: Comparing Classifiers and Combining Modalities

This work investigates face recognition based on normal maps, and the performance improvement that can be obtained when exploiting it within a multimodal system, where a further independent module processes visible images. We first propose a technique to align two 3D models of a face by means of normal maps, which is very fast while providing an accuracy comparable to well-known and more general techniques such as Iterative Closest Point (ICP). Moreover, we propose a matching criterion based on a technique which exploits difference maps. It does not reduce the dimension of the feature space, but performs a weighted matching between two normal maps. In the second place, we explore the range of performance soffered by different linear and non linear classifiers, when applied to the normal maps generated from the above aligned models. Such experiments highlight the added value of chromatic information contained in normal maps. We analyse a solid list of classifiers which we reselected due to their historical reference value (e.g. Principal Component Analysis) or to their good performances in the bidimensional setting (Linear Discriminant Analysis, Partitioned Iterated Function Systems). Last but not least, we perform experiments to measure how different ways of combining normal maps and visible images can enhance the results obtained by the single recognition systems, given that specific characteristics of the images are taken into account. For these last experiments we only consider the classifier giving the best average results in the preceding ones, namely the PIFS-based one