Multiple linear regression model of Golden apple's failure characteristics under repeated compressive load

Csaba Farkas, László Fenyvesi, Károly Petróczki

Multiple linear regression model of Golden apple's failure characteristics under repeated compressive load

Číslo: 1/2019
Periodikum: Potravinárstvo
DOI: 10.5219/1168

Klíčová slova: repeated load, fruit damage, analysis of variance, time to failure, mechanical fatigue

Pro získání musíte mít účet v Citace PRO.

Přečíst po přihlášení

Anotace: In this paper, the multiple linear regression model of mechanical properties related to the failure mechanism of apple tissue under repeated compressive load was investigated. More refined failure characteristics may lead to improved processing and logistics aspects of the given fruits. For our study, the following failure-related factors are considered during the cyclic measurements of Golden Delicious apples: the viscoelastic parameters, the dissipated energy, and the rupture point of the cell-structure, which is described with the time to failure parameter (TTF). For the determination of viscoelastic components, the three element Poynting-Thomson body was applied, and a closed-loop control system is identified with the measured creep data. From the hysteresis loop – in each cycle of the force-deformation parametric curve – the dissipated energy can be calculated with a numeric integration method. The rupture point of the fruit tissue – where the measuring pin is breaking through the peel and the cortex – is observed with a high-framerate video analysis, so that the time index of the failure point can be evaluated. The focus is to define the influence of the mentioned factors to the TTF parameter of the examined fruit material. During the statistical evaluation of the resulted data, the failure of time can be successfully determined with a multiple lienar regression model of the determined viscoelastic and dissipated energy variables. With the resulted equation, the failure time of Golden Delicious apples can be predicted based on the measured failure-related parameters obtained during the compressive load tests.