A Procedure for the Fatigue Life Prediction of Straight Fibers Pneumatic Muscles

Different from the McKibben pneumatic muscle actuator, the straight fibers one is made of an elastomeric tube closed at the two ends by two heads that ensure a mechanical and pneumatic seal. High stiffness threads are placed longitudinally into the wall of the tube while external rings are placed at some sections of it to limit the radial expansion of the tube. The inner pressure in the tube causes shortening of the actuator. The working mode of the muscle actuator requires a series of critical repeated contractions and extensions that cause it to rupture. The fatigue life duration of a pneumatic muscle is often lower than traditional pneumatic actuators. The paper presents a procedure for the fatigue life prediction of a straight-fibers muscle based on experimental tests directly carried out with the muscles instead of with specimens of the silicone rubber material which the muscle is made of. The proposed procedure was experimentally validated. Although the procedure is based on fatigue life duration data for silicone rubber, it can be extended to all straight-fibers muscles once the fatigue life duration data of any material considered for the muscles is known.

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A New Multiparameter Model for Multiaxial Fatigue Life Prediction of Rubber Materials

Polymers ◽

10.3390/polym12051194 ◽

2020 ◽

Vol 12 (5) ◽

pp. 1194

Author(s):

Rafael Tobajas ◽

Daniel Elduque ◽

Elena Ibarz ◽

Carlos Javierre ◽

Luis Gracia

Keyword(s):

Fatigue Life ◽

Life Prediction ◽

Experimental Testing ◽

Experimental Tests ◽

Relevant Information ◽

Fatigue Tests ◽

Multiaxial Fatigue ◽

Fatigue Life Prediction ◽

Proposed Model ◽

Predicted Values

Most of the mechanical components manufactured in rubber materials experience fluctuating loads, which cause material fatigue, significantly reducing their life. Different models have been used to approach this problem. However, most of them just provide life prediction only valid for each of the specific studied material and type of specimen used for the experimental testing. This work focuses on the development of a new generalized model of multiaxial fatigue for rubber materials, introducing a multiparameter variable to improve fatigue life prediction by considering simultaneously relevant information concerning stresses, strains, and strain energies. The model is verified through its correlation with several published fatigue tests for different rubber materials. The proposed model has been compared with more than 20 different parameters used in the specialized literature, calculating the value of the R2 coefficient by comparing the predicted values of every model, with the experimental ones. The obtained results show a significant improvement in the fatigue life prediction. The proposed model does not aim to be a universal and definitive approach for elastomer fatigue, but it provides a reliable general tool that can be used for processing data obtained from experimental tests carried out under different conditions.

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Adaptive Neural Network Modelling in Fatigue life Prediction under Load History effects

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.284-286.1266 ◽

2011 ◽

Vol 284-286 ◽

pp. 1266-1270

Author(s):

M. Abdul Razzaq ◽

Kamal A. Ariffin ◽

Ahmed El Shafie ◽

Shahrum Abdullah ◽

Z. Sajuri ◽

...

Keyword(s):

Fatigue Life ◽

Crack Growth ◽

Life Prediction ◽

Experimental Tests ◽

Fatigue Life Prediction ◽

Load History ◽

Adaptive Neural Network ◽

Network Modelling ◽

History Effects ◽

Point Bend

Artificial intelligence (AI) techniques and in particular, adaptive neural networks (ANN) have been commonly used in order to Fatigue life prediction. The aim of this paper is to consider a new crack propagation principle based on simulating experimental tests on three point-bend (TPB) specimens, which allow predicting the fatigue life and fatigue crack growth rate (FCGR). An important part of this paper is estimation of FCG rate related to different load histories. The effects of different load histories on the crack growth life are obtained in different representative simulation and experiments.

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Rapid Characterization of Fatigue Performance With Application to Additive Manufactured Components

Volume 10B: Structures and Dynamics ◽

10.1115/gt2020-14727 ◽

2020 ◽

Author(s):

Dino A. Celli ◽

M.-H. Herman Shen ◽

Onome E. Scott-Emuakpor ◽

Tommy J. George

Keyword(s):

Experimental Data ◽

Fatigue Life ◽

Life Prediction ◽

Prediction Method ◽

Experimental Tests ◽

Parameter Selection ◽

Process Parameter ◽

Fatigue Life Prediction ◽

Fatigue Performance ◽

Cycles To Failure

Abstract The aim of this paper is to provide a fatigue life prediction method which can concurrently approximate both SN behavior as well as the inherent variability of fatigue efficiently with a limited number of experimental tests. The purpose of such a tool is for the quality assessment and verification of components using Additive Manufacturing (AM) processes and other materials with a limited knowledgebase. Interest in AM technology is continually growing in many industries, such as aerospace, automotive, or biomedical. But components often result in highly variable fatigue performance. The determination of optimal process parameters for the build process can be an extensive and costly endeavor due to either a limited knowledgebase or proprietary restrictions. Quantifying the significant variability of fatigue performance in AM components is a challenging task as there are many causes including machine to machine differences, recycles of powder, and process parameter selection. Therefore, a life prediction method which can rapidly determine the fatigue performance of a material with little or no prior information of the material and a limited number of experimental tests is developed as an aid in process parameter selection and fatigue performance qualification. This is performed by using a previously developed and simplistic energy based fatigue life prediction method, or Two Point method, to predict the inherent variability associated with fatigue performance. The proposed approach is verified by using predicted distributions of stress and cycles to failure and comparing with experimental data at 104 and 106 cycles to failure. SN life prediction is modeled via a modified Random Fatigue Limit (RFL) model where the two RFL model parameters are evaluated using Bayesian statistical inference and stochastic sampling techniques for distribution estimation. This is performed in a dynamic way such that the life prediction model is continually updated with the generation of experimental data.

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Multi-Axial Fatigue Life Prediction of a Composite Structural Component

ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis, Volume 1 ◽

10.1115/esda2010-24220 ◽

2010 ◽

Author(s):

Laura Vergani ◽

Chiara Colombo

Keyword(s):

Fatigue Life ◽

Structural Component ◽

Life Prediction ◽

Failure Modes ◽

Glass Fibers ◽

Axial Loading ◽

Experimental Tests ◽

Fatigue Life Prediction ◽

The Matrix ◽

Fibers Orientation

Aim of this work is to test and understand the mechanical behavior of a composite material used to build a structural component, in particular a corner beam of a bus cabin. This component is obtained by means of the pultrusion technique and presents random and longitudinal E-glass fibers as reinforce, while the matrix is a vinyl-ester resin. A series of experimental tests was performed on specimens cut out from this beam. Different fibers orientation with respect to the direction of load application were considered: longitudinal (0°), normal (90°) and inclined (45°), thus both in uni-axial and multi-axial loading conditions. A static and fatigue characterization was carried out to identify the mechanical behaviors and the failure modes in these directions. Obtained fatigue data are then interpolated by fitting parameters required for models of fatigue life prediction.

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