ISSN:
1573-8922
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
Abstract Tests of cross-ply composite tubes were performed under combined axial and torsional loading up to failure. Strength properties and failure mechanisms were evaluated with reference to the biaxiality ratio of the loading. The scattering of the biaxial strength data was analyzed using the Weibull distribution. The axial contraction of carbon fiber-reinforced plastic (CFRP) tubes under biaxial loading was investigated theoretically and experimentally. Artificial neural networks were introduced to predict the failure strength using the algorithm of the error back-propagation. The prediction was also made by the Tsai-Wu theory using the experimental data and by the combined optimized tensor-polynomial theory. A comparison shows that the artificial neural network has the smallest root-mean square (RMS) error of the three prediction methods. The prediction of the axial contraction of the tubes correlates well with the results of a linear variable differential transformer (LVDT) of the testing machine. From the phenomenological analysis of the failure and the fractographic observations of the fracture surface, three types of failure modes and microscopic failure were investigated, depending on the biaxiality ratio, and the corresponding failure mechanisms are suggested.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF02256140
