A. Francavilla

Bio: A. Francavilla is an academic researcher from University of Bari. The author has contributed to research in topics: Physics & Structural engineering. The author has an hindex of 2, co-authored 2 publications receiving 417 citations.

Optimization of shape to minimize stress concentration

Abstract: The problem of minimizing stress concentrations in machinery components is formulated as one of unconstrained minimization by incorporating all ‘side’ constraints on design variables by use of penalty functions. Design parameters describing the transition are determined for an optimal fillet in a tension bar, as well as for a piston-rod ‘eye’. The procedure is generally applicable.

Association between obesity and frequency of high-grade prostate cancer on biopsy in men: A single-center retrospective study

Abstract: The present study aimed to investigate the relationship between BMI and the prostate cancer (PCa) risk at biopsy in Italian men. Retrospective analyses of the clinical data of 2,372 consecutive men undergoing ultrasound-guided multicore (≥10) prostate biopsy transrectally between May 2010 and December 2018 were performed. BMIs were categorized, according to Western countries' classification of obesity, as follows: <18.5 kg/m2 (underweight), 18.5-24.99 kg/m2 (normal weight), 25-30 kg/m2 (overweight) and >30 kg/m2 (obese). The distribution of patients undergoing biopsy was compared with a model population from the official survey data. Patient characteristics and the relationships between characteristics were investigated using correlation analysis, ANOVA, Kruskal-Wallis and Dunn's tests. The present study estimated the influence on cancer incidence not only of BMI but also of other patient characteristics using multi-variable logistic modelling and compared, using the models, the expected outcomes for patients who differed only in BMI. From a sample of 2,372 men, the present study enrolled 1,079 men due to a lack of clinical data [such as prostate specific antigen (PSA) and BMI data] in the other patients undergoing prostate biopsy. Their distribution was significantly different from the model distribution with the probability of undergoing biopsy increasing with increasing BMI. The median age was 69.4 years. The median BMI was 26.4 kg/m2, while the median PSA level was 7.60 ng/ml. In total, the biopsies detected PCa in 320 men (29.7%) and high-grade PCa (HGPCa) in 218 men (20.2%). Upon applying the aforementioned Western countries' criteria for BMI categories, there were 4 (0.4%) underweight, 318 (29.5%) of normal weight, 546 (50.6%) overweight, and 211 (19.6%) obese patients. ANOVA/Kruskal-Wallis tests revealed that overweight and obese men were younger than the normal-weight men, while there was no statistical difference in their PSA values. Furthermore, 29.3% of normal-weight men, 29.5% of overweight men and 29.9% of obese men were diagnosed with PCa, while 19.5% of normal-weight men, 20.1% of overweight men and 21.8% of obese men were affected by severe cancer. BMI was found to be positively correlated with PCa risk and negatively correlated with both age and PSA level. Age and PSA level were both positively correlated with PCa risk, while digital rectal examination (DRE) outcome was strongly indicative of PCa discovery if the test outcome was positive. Logistics models attributed a positive coefficient to BMI when evaluated against both PCa risk and HGPCa risk. In patients having a negative DRE outcome who differed only in BMI, logistic regression showed a 60% increased risk of PCa diagnosis in obese patients compared with in normal-weight patients. This risk difference increased when other characteristics were less indicative of PCa (younger age/lower PSA), while it decreased when patient characteristics were more indicative (older age/higher PSA, positive DRE). In conclusion, the present study demonstrated that, in men with higher BMIs, the risk of PCa is higher. The relative difference in risk between low and high BMI is most pronounced in younger patients having a lower PSA level and a negative DRE outcome.

An Application of ARIMA modelling to air pollution concentrations during covid pandemic in Italy

Abstract: Since the COVID-19 pandemic began, space and ground-based observations have shown how Earth’s atmosphere has observed significant reductions in some air pollutants. Many studies, all over the world, demonstrated how the governmental restrictions imposed because of the spreading of the virus had positive and negative effects on the environment. In this paper, authors discuss how the levels of concentrations of some pollutants varied, in two case studies in Italy, because of the imposed lockdown during the coronavirus pandemic. The extent of the variations CO and PM10 has been evaluated by comparing data registered by local monitoring stations, related to the baseline February-May, of three different years, 2018, 2019 and 2020. In order to better assess the variation of the temporal trend of pollutants before (2018, 2019) and during COVID-19 lockdown (2020) proper physic-mathematical models have been applied to the datasets. The calibration and validation of AutoRegressive Integrated Moving Average (ARIMA) models on interesting series of CO and PM10 data complete the work.

Structural shape optimization — a survey

Abstract: This paper is a survey of structural shape optimization with an emphasis on techniques dealing with shape optimization of the boundaries of two- and three-dimensional bodies. Attention is focused on the special problems of structural shape optimization which are due to a finite element model which must change during the optimization process. These problems include the requirement for sophisticated automated mesh generation techniques and careful choice of design variables. They also include special problems in obtaining sufficiently accurate sensitivity derivatives.

A solution method for planar and axisymmetric contact problems

Abstract: SUMMARY A solution procedure for the analysis of planar and axisymmetric contact problems involving sticking, frictional sliding and separation under large deformations is presented. The contact conditions are imposed using the total potential of the contact forces with the geometric compatibility conditions, which leads to contact system matrices and force vectors. Some key aspects of the procedure arc the contact matrices, the use of distributed tractions on the contact segments for deciding whether a node is sticking, sliding or releasing and the evaluation of the nodal point contact forces. The solutions to various sample problems are presented to demonstrate the applicability of the algorithm. Much progress has been made during recent years in the development of computational capabilities for general analysis of certain nonlinear effects in solids and structures. In each of these developments, quite naturally, the first step was the demonstration of some ideas and possibilities for the analyses under consideration, and then the research and development for reliable and general techniques was undertaken. The second step proved in many cases much more difficult, and in the case of capabilities for analysis of contact problems has yielded few general results. Although some of the first complex contact problems have been solved using the finite element method quite some time ago,'- and much interest exists in the research and solution of contact problems (see, for example, References 4-1 5), there is still a great deaiwf effort necessary for the development of a reliable, general and cost-effective algorithm for the practical analysis of such problems. This is largely due to the fact that the analysis of contact problems is computationally extremely difficult, even for the simplest constitutive relations used. Much of the difficulty lies in that the boundary conditions of the bodies under consideration are not known prior to the analysis, but they depend on the solution variables. The aim in our research is the development of a solution algorithm for analysis of general contact conditions which shall include the possibilities to analyse: contact between flexible-flexible and rigid--flexible bodies; sticking or sliding conditions (with or without friction); large relative motions between bodies; repeated contact and separation between the bodies. Since the large deformation motion of the individual bodies can in many cases be analysed already quite effectively,'6 an algorithm of the above nature will certainly enlarge, very