Fractional viscoelastic behaviour under stochastic temperature process
| Autor: | Mario Di Paola, Alberto Di Matteo, Natalia Colinas-Armijo |
|---|---|
| Přispěvatelé: | Colinas Armijo, N., DI PAOLA, M., DI MATTEO, A. |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Time-Temperature Superposition Principle
Gaussian Aerospace Engineering Ocean Engineering 02 engineering and technology Condensed Matter Physic Fractional calculu 01 natural sciences Viscoelasticity 010305 fluids & plasmas Stress (mechanics) symbols.namesake Superposition principle 0203 mechanical engineering 0103 physical sciences Gaussian stochastic proce Mathematics Civil and Structural Engineering Mechanical Engineering Mathematical analysis Spectral density Statistical and Nonlinear Physics Condensed Matter Physics Fractional calculus Linear viscoelasticity 020303 mechanical engineering & transports Creep Time–temperature superposition Nuclear Energy and Engineering symbols Statistical and Nonlinear Physic |
| Popis: | This paper deals with the mechanical behaviour of a linear viscoelastic material modelled by a fractional Maxwell model and subject to a Gaussian stochastic temperature process. Two methods are introduced to evaluate the response in terms of strain of a material under a deterministic stress and subjected to a varying temperature. In the first approach the response is determined making the material parameters change at each time step, due to the temperature variation. The second method, takes advantage of the Time–Temperature Superposition Principle to lighten the calculations. In this regard, a stochastic characterisation for the Time–Temperature Superposition Principle method is proposed for a Gaussian stochastic temperature process. A numerical example, based on experimental data of an epoxy resin at different temperatures, is presented to simulate a creep test under a Gaussian stochastic temperature process with assigned power spectral density function. Comparison between the two considered methods is shown, and the accuracy of the proposed stochastic characterisation is assessed. |
| Databáze: | OpenAIRE |
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