Issue 76

Fracture and Structural Integrity 76 (2026); International Journal of the Italian Group of Fracture

A. J. Abdulridha, I. S. I. Harba, A. A. M. AL-Shaar https://youtu.be/5Q2eBu3lVL4 Seismic performance of steel frames with a hybrid bracing system combining concentric steel bracing and friction dampers ………………….………………....................................................... 129-153 A. Sulamanidze https://youtu.be/D3qEBtnbY1k The influence of temperature on the deformation behavior, strength and fracture mechanism of the heat-resistant Nickel-based alloy EI698-VD …………………………………………... 154-168 L. Wang, F. Gao https://youtu.be/PhWmEIyrelQ Effects of machining methods on uniaxial tensile properties of 75 μ m thick 304L stainless steel foil …………..…………………………………………………………………….. 169-182 H. Walid, N. Boumechra https://youtu.be/mAYSeW3cj_k Numerical assessment of the seismic vulnerability of the historical earthen remains of the Mansourah enclosure (Tlemcen, Algeria): influence of geometry and identification of critical damage zones ……………………………………………………………………….. 183-211 D.S. Lobanov, A.V. Lykova, A.M. Pankov https://youtu.be/Gs9exA9yk8c Effect of external operational damage on the mechanical behavior of GFRP under quasi-static and fatigue loading ..................................................................................................................... 212-222 A. Krishnappa, S. Ramesh, R. Siddagangappa, S. Ashokkumar, M. Vatnalmath, V. Auradi, M. Nagaral https://youtu.be/BAQW-IIVOBw Influence of hybrid nano Al 2 O 3 –ZrO 2 reinforcements on microstructure, fracture toughness and fractographic behaviour of Al6061 alloy ………………………………………….…….. 223-237 H. Houari, B. Aour, S. Ramtani, F. Benalia, S. Barboura https://youtu.be/4YPkPDDQZgc Numerical and experimental study of the behavior of a polyamide during the ECAE process using a 105° die ………………………………………………………………...…... 238-264 N. Majed, A. Nasr, W. Bel Haj Sghaier, M. Youssef https://youtu.be/ilYAu4YkCPU Predicting fatigue limits of defective A356-T6 and A357-T6 cast aluminum alloys using a hybrid empirical–machine learning approach ............................................................................... 265-276

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