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Data driven condition assessment of railway infrastructure
Published in Hiroshi Yokota, Dan M. Frangopol, Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations, 2021
C. Hoelzl, V. Dertimanis, E. Chatzi, D. Winklehner, S. Züger, A. Oprandi
Fractal analysis is a method that was originally developed as a way to approximate the length of the coastline of Great Britain. Using Euclidian geometry, the coastline can be approximated using a polygonal chain. The term of fractal dimension first appeared in 1967 in a paper on self-similarity written by Benoit Mandelbrot (Mandelbrot B. 1967). The fractal dimension corresponds to the statistical indicator of how the ratio between the details in a pattern changes with the measurement scale.
Evaluation of elastic and adhesive properties of solids by depth-sensing indentation
Published in The Journal of Adhesion, 2021
Nikolay V. Perepelkin, Ivan I. Argatov, Feodor M. Borodich
To fit experimental data with a parametric force–displacement curve we have introduced a new objective functional of the BG method based on the concept of ODF. However, fitting a parametric curve to a set of points normally requires to determine the unknown values of the parameter corresponding to individual data points which increases the number of unknowns drastically and slows down computations. To address this issue of the above direct fitting approach the following additional extension of the BG method has been suggested. It has been proposed to carry out fitting of the theoretical force–displacement curve to experimental data points by means of a two-stage process. On the preliminary first stage (the pre-fitting stage) data points are fitted with an auxiliary curve. The auxiliary curve is supposed to have simplest possible mathematical form which allows to implement advanced data fitting/filtering techniques like ODF quickly and effectively. The pre-fitting curve has been taken as simple as a polygonal chain which is fitted to experimental data using the ODF technique. On the second stage the theoretical force–displacement curve is fitted to the auxiliary one by means of minimization of the square of the norm of difference of the two functions. The objective functional has been formulated in a way that does not require computation of unknown values of the parameter. Numerical simulations showed that the pre-fitting stage does not have significant influence on the accuracy of identification of the values of the reduced contact modulus and the work of adhesion.
A novel method to calculate the magnetic field of a solenoid generated by a surface current element
Published in Waves in Random and Complex Media, 2022
Mostafa Behtouei, Bruno Spataro, Luigi Faillace, Martina Carillo, Moreno Comelli, Luigi Palumbo, Alessandro Variola, Mauro Migliorati
WebNIR [11] (Web-based tools for assessing occupational exposure to Non-Ionizing Radiation), a portal collecting a series of tools for dissemination and calculation developed as part of a collaboration with other research institutions on exposure to electromagnetic fields, has been developed at the Institute of Applied Physics ‘Nello Carrara’ of the National Research Council (IFAC-CNR). One of these tools, still under development, allows the user to define different types of configurations of conductors (polygonal chains, catenaries, coils, solenoids), define both their geometric and electrical characteristics (current, phase, waveform) and calculate the value of magnetic flux density in correspondence to a set of regularly distributed points in the space (the calculation grid). Two different approaches have been used to perform the calculation: (1) since the field of a segment traversed by current is known, any geometry can be approximated by a polygonal chain consisting of an arbitrarily large number of segments; calculating the field generated by each of them, the resulting field is given by the sum of the individual contributions; (2) for a circular loop, the analytical solution of the field in the space is known [8, 12]: consequently, the field generated by geometries consisting of a set of circular loops (e.g.: coils, solenoids) is determined exactly by considering the elementary contribution of each loop. An ‘internal validation’ of the software results has been carried out by comparing the results obtained by applying, in the case of a solenoid: the formulation using the complete elliptic integrals of first and second kind [12] the formulation that uses the hypergeometric function [8] where, We can demonstrate that the magnetic field components obtained by two different methods are identical following the below equations: where and are the complete elliptic integrals of the first and second kind, respectively.the approximate calculation in which the helix which constitutes the solenoid is approximated with a polygonal chain. The number of segments constituting the single loop has been progressively increased in different tests (in detail, the loop was approximated with 20, 200 and 2000 segments).The result obtained in the first 2 cases is coincident up to the 13th digit: the 2 formulations are equivalent and the discrepancies are due to the approximations implicit in the libraries used. In particular, the language used to perform the calculations is Python 3.9 and the library scipy.special deals with calculating elliptic integrals and hypergeometric functions.