1,721,153 research outputs found
A simple and effective approach for thermo-mechanical modelling of composite superconducting wires
No full textThe ability to compute accurately the strain field in Nb3Sn filaments is a crucial point in cable design, due to the significant strain sensitivity of niobium-tin wires. Due to its heterogeneity, a straightforward numerical simulation of a cable, taking into account all the details of the microstructure, would result in an enormous number of unknowns. As an alternative, multiscale approaches can be used to deal with this kind of problem, to understand the behaviour across the various scales. In this framework, a simple and efficient approach to obtain the homogenized properties of a heterogeneous strand is proposed here. This approach is developed for the non-linear, thermo-mechanical field. It consists of the solutions to some boundary value problems formulated on a suitably chosen statistically representative volume element of the wire. Two bronze-route strands and one internal-tin strand are considered and the equivalent parameters are obtained. Finally, the cool down and the subsequent application of a tensile axial load are simulated taking into account the homogenized wires. Computed results are shown to be in excellent agreement with measured stress-strain curves
A rheological approach for elasto-plastic behaviour of superconducting strands
No full textSuperconducting (SC) strands are composite materials: they are usually made of a normal metal matrix where superconducting filaments are embedded. The main purpose of this paper consists in developing a simple but effective approach based on rheological models, to simulate the global elastic-plastic behavior of SC wires. In particular, starting from Prandtl generalized scheme, the strand elastic modulus and elastic-plastic tangent modulus are obtained at different temperatures. The wire mechanics is studied by taking into consideration both the longitudinal behavior (along the axis of the wire) and the transversal one (on the plane section of the wire itself). Concerning the longitudinal axis, the constitutive materials are represented by a system of mechanisms arranged in parallel: normal metals are represented by a series of springs and frictional devices, while superconducting filaments are considered as a single spring, because of their elastic properties. Concerning the transversal behavior, the scheme is more complex, therefore the cross section is subdivided into stripes. Each stripe, which is represented by a series of springs and frictional devices, is arranged in parallel with the other ones. Finally, to show the effectiveness of the presented method, three different wires are taken into consideration and results obtained are compared with numerical ones previously calculated by means of virtual testing homogenization and finite element (FE) analysis. The presented approach allows studying the elastic- plastic behavior of complex composite materials in a simple way, without the need of FE method or the use of complex homogenization techniques
A combined Finite Element - Artificial Neural Network approach for multiscale modeling of hierarchical structures
No full textIn this paper we present a combined finite element (FE) – artificial neural network (ANN) approach for the multi-scale modeling of cables made of LTS materials.
At first different aspects of ANN use in non-linear analysis of hierarchical composite are shown. The possibility to model via ANNs the *homogenized material behavior* starting from a relatively small set of suitable virtual or real experiments is discussed. ANN based procedures can also be exploited in a multi-scale analysis as a tool for the *stress-strain recovery* at the structure lower levels. For example, in SC cables a map of the strain state at the wire and filament scale is needed. The related unsmearing procedure is numerically very costly. An ANN, acting in recall mode during the execution of the homogenization loops, allows for a considerably improved computational efficiency.
Secondly, the *cable mechanical behavior* is analyzed, namely the influence of the hierarchical helix geometry on the stiffness of the cable. It is proven how the stiffness matrix of these structures is different from the usual matrix of Euler-Bernoulli beams.
Finally, a significant application for the *design of cables* is shown. ANNs can be used to investigate the dependence of the stiffness coefficients upon the twist pitches of the multi-level helixes.
The final goal of this research is to substitute, at each level, a bundle of wires with a single equivalent wire, having the characteristics computed on the bundle of the previous scale. The presented hybrid finite element–artificial neural network approach is exploited to this aim, showing that suitably trained ANNs can replace the module that usually provides the stiffness matrix in an FE code. In the end, some real cable examples are shown, where results obtained via the FE method are compared with those calculated by an ANN-FE procedure
Identification of contamination flux in a domain of porous media as an inverse problem solved with Artificial Neural Networks
No full textAfter a short introduction and main issues associated with inverse problem, three examples are chosen to illustrate the application of Artificial Neural Networks in the inverse problems solution. For a steady state convection problem, assuming given concentration field values in a few measurement points and values of hydraulic head in the same piezometers, the source of the concentration and its intensity are deduced using Artificial Neural Networks (ANNs). The same method is used for identification of diffusivity vector. To illustrate the reliability of the procedure, the case of randomly perturbed data is presented. The main conclusion states that the soft method seems to be very automatic and convenient in solving a large family of inverse problems
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