Use of the KSVM-based system for the definition, validation and identification of the incisional hernia recurrence risk factors.

BACKGROUND: Incisional hernia is one of the most common complications after abdominal surgery with an incidence rate of 11 to 20% post laparotomy. Many different factors can be considered as risk factors of incisional hernia recurrence. The aim of this study is to confirm and to validate the incisional hernia recurrence risk factors and to identify and to validate new ones. METHODS: In the period from July 2007 to July 2017, 154 patients were selected and subjected to incisional hernia repair. The surgical operations were conducted under general anaesthesia. Patients received antibiotic prophylaxis when indicated, according to the hospital prophylaxis scheme. Inclusion criteria of the study were single operator case studies and open laparotomy for incisional hernia repair. The statistical analysis proposed to identify and to verify the risk factors for recurrence of incisional hernia is the Support Vector Machine (SVM). The analysis was conducted verifying 34 risk factors. RESULTS: The data analysis confirmed the known correlations showed in the international literature with a greater incidence of comorbidities such as diabetes 37%, dyslipidaemia and hypercholesterolemia with a cumulative incidence of 16%; tobacco smoke - by combining categories smokers and ex-smokers - reach 46%, COPD 16% and hypertension 51%. CONCLUSIONS: The analysis of the data therefore confirmed the correlations showed in the international literature. A KSVM-based system to classify incisional hernia recurrence has been presented. The type of prosthesis and the site of its implant also play a significant role in the development of the recurrence. Sensitivity (86,25%), Specificity (87,14%), Negative Predictive Value (84,72%), Precision (88,46%), Accuracy (86,67%), and Error (13,33%) scores obtained using the proposed technique highlight the validity for the relapse's classification methodology.

Inspection of additive-manufactured layered components.

Laser powder deposition (LPD) is a rapid additive manufacturing process to produce, layer upon layer, 3D geometries or to repair high-value components. Currently there is no nondestructive technique that can guarantee absence of flaws in LPD products during manufacturing. In this paper a laser ultrasonic technique for in-line inspection of LPD components is proposed. Reference samples were manufactured from Inconel and machined flaws were created to establish the sensitivity of the technique. Numerical models of laser-generated ultrasonic waves have been created to gain a deeper understanding of physics, to optimize the set-up and to verify the experimental measurements. Results obtained on two sets of reference samples are shown. A proof-of-concept prototype has been demonstrated on some specific deposition samples with induced flaws, that were confirmed by an ultra-high sensitivity X-ray technique. Experimental outcomes prove that typical micro-defects due to the layer-by-layer deposition process, such as near-surface and surface flaws in a single layer deposit, can be detected.

Numerical study for a new methodology of flaws detection in train axles.

Train loads and travel speeds have increased over time, requiring more efficient non-destructive inspection methods. Railway axles are critical elements; despite being designed to last more than 20 years several cases of premature failure have been recorded. Train axles are inspected regularly, but the limits associated to the traditional inspection technologies create a growing interest towards new solutions. Here a novel non-destructive inspection method of in-service axles based on non-contact data collection is presented. The propagation of surface waves, generated by a thermo-elastic laser source, is investigated using a finite element method based on dynamic explicit integration. Coupled thermo-mechanical simulations allow visualization of the ultrasonic field guiding the definition of the optimal NDT setup. The geometry of the axle and of the elements mounted on it is accurately reproduced; moreover the press fit effect caused by the wheel and the bearing rings is implemented. The current NDT techniques for railway axles require removing wheels and other components from the axle. The presented scheme uses non-contact ultrasonic generation and detection allowing non-contact in-service inspection of railway axles at trackside station. The numerical results are promising and encourage us to test the new approach experimentally.

Surface waves on cylindrical solids: numerical and experimental study.

The use of Rayleigh waves enables the solution of several important inspection problems. Propagation of surface waves along straight boundaries has been properly studied but investigations about their propagation on cylindrical surfaces are not sufficient, despite they can be still of interest for NDE applications. It has been proved experimentally that a surface wave pulse suffers a phase shift during its propagation along a cylindrical surface. A numerical approach has been developed to efficiently study these effects for different materials, curvatures and frequencies. This study can help the scientific community to better understand the phenomenon, quite complex and not yet fully explored.