fatigue lifetime
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Steel wire ropes are frequently subjected to dynamic reciprocal bending movement over sheaves or drums in cranes, elevators, mine hoists, and aerial ropeways. This kind of movement initiates fatigue damage on the ropes. It is a quite significant case to know bending cycles to failure of rope in service, which is also known as bending over sheave fatigue lifetime. It helps to take precautions in the plant in advance and eliminate catastrophic accidents due to the usage of rope when allowable bending cycles are exceeded. To determine the bending fatigue lifetime of ropes, experimental studies are conducted. However, bending over sheave fatigue testing in laboratory environments require high initial preparation cost and a long time to finalize the experiments. Due to those reasons, this chapter focuses on a novel prediction perspective to the bending over sheave fatigue lifetime of steel wire ropes by means of artificial neural networks.

In the present study, the authors attempted to predict the fatigue lifetime of a real-scale integral concrete bridge with H-shaped steel piles resulting from working and environmental conditions. In this regard, various types of nonproportional variable amplitude loads were applied on the bridge, such as temperature variations and sea waves clash. To this end, CATIA software was used to model the real-scale bridge with its accessories, such as a concrete deck, concrete anchors (walls), I-shaped concrete beams (Ribs), and steel piles. Subsequently, stress analysis was performed to determine the critical area apt to fail. The results showed that steel piles are the most critical bridge components. As a result, in future analysis, the purpose will be to study this critical area, and the effect of relative humidity on the fatigue properties of concrete was ignored. Subsequently, the time history of stress tensor components in the critical area was obtained by performing transient dynamic analysis. Various well-known equivalent stress fatigue theories (von Mises, Findley, Dang Van, McDiarmid, Carpinteri–Spagnoli, Modified Findley, Modified McDiarmid, and Liu–Zenner) were utilized to calculate the equivalent stress caused by the simultaneous effect of temperature variations and sea waves clash. Eventually, the fatigue life of the structure was predicted by employing the rainflow counting algorithm and the Palmgren–Miner damage accumulation rule. The results indicated a reduction in the multiaxial fatigue life of the structure under the simultaneous effects of two phenomena, the daily temperature variations and the sea waves clash, of approximately 87% and 66%, respectively, compared with the fatigue life of the structure under either the effect of temperature changes or the effect of sea waves clash, separately. Therefore, it was necessary to consider all the cyclic loads in the structural design step to estimate the fatigue life of the structure. Moreover, the findings of this case study revealed that the lowest value of multiaxial fatigue lifetime is related to the application of the Liu-Zenner criterion. In other words, this criterion is more conservative than the other used criteria.