http://148.72.244.84/xmlui/handle/123456789/1 2026-04-18T09:37:55Z 2026-04-18T09:37:55Z كرار معلك حنون http://148.72.244.84/xmlui/handle/xmlui/2688 2024-02-20T08:22:18Z 2022-01-01T00:00:00Z

Structural Behavior Of Smart Beams Reinforced With Super Elastic Shape Memory Alloy Rebar (SMA) كرار معلك حنون Abstract Reinforced concrete beam with shape memory alloy rebar (SMA) is a new type of smart beam that is an important part of smart seismic structural systems developed to decrease the effects of earthquakes while maintaining approximately the same load carrying capacity as compared with conventional concrete beams. Shape memory alloy rebar has the ability to recover its normal shape after exposure to loads by removing loads or exposure to heat, and this property is so important in terms of enhancing seismic structural performance. In this thesis, an experimental investigation is carried out to study concrete beams for two effective types of loads, monotonous loads and repeated loads and the behaviour of normal reinforced concrete beams The experimental program tests eight normal beams with dimensions of 1450mm×250mm×150mm. The specimens are divided into three groups according to the percentage of SMA rebars that reinforced beams in bottom longitudinal direction. Each group included four beams, two as reference beams and two as variations which had reinforcing details similar to the other. The two reference beams are reinforced with steel bars in the longitudinal direction representing flexural reinforcement, which acts as control beams in the three groups. The first group has a percentage of the SMA rebars in flexural reinforcement, 25% of the total flexural reinforcement. The second group beam has a percentage of the SMA rebars in flexural reinforcement, 50% of the total flexural iv reinforcement. The third group beam has a percentage of the SMA rebars in flexural reinforcement, 75% of the total flexural reinforcement. For the three groups, one beam was tested by monotonic load and compared to a reference that tested by monotonic load, and last beam is tested by repeated load within a specific protocol and compared by a reference beam that tested also by repeated load The experimental results showed that the ultimate load decreased by using SMA bars in (25%, 50%, 75% ) of total flexural reinforcement about (2.66,18.93, 44.66%) respectively, in the case of monotonic loading and (9.825%, 21.776%, 42.78 %) in case of repeated loading. The deflection increased by using SMA in (25%, 50%, 75% ) percentage of total flexural reinforcement about (14.45%, 19.18%, 3.491%) respectively, in case of monotonic loading and (18.8%, 6.213%, 3.084%) in case of repeated loading. The ductility increased by using SMA bars in (25%, 50%, 75% ) of total flexural reinforcement about (37.446%, 92.4%, 18.116%) respectively, in case of repeated loading, while in case of monotonic loading, ductility increased by using SMA bar in (25%, 50%, 75%) of total flexural reinforcement about (32.05%, 73.89%, 3.236%). The Absorbed energy increased by using SMA bars in (25%) of total flexural reinforcement about (5.15%, 12.24%) in case of monotonic and repeated loading, respectively, while by using SMA bars in (50%,75%) of total flexural reinforcement in case monotonic loading, Absorbed energy decreased about (9.26%, 42.48%), and in case of repeated loading it decreased about (14.55%, 28.08%). The Nitinol alloy had a positive effect in reducing distortions, as well as a relative return of the beams to its original place.

2022-01-01T00:00:00Z حيدر قاسم http://148.72.244.84/xmlui/handle/xmlui/16963 2026-01-04T08:55:37Z 2025-01-01T00:00:00Z

نموذج التعلم العميق للكشف عن متلازمة المباني المريضة حيدر قاسم

2025-01-01T00:00:00Z نيكار م شفيق http://148.72.244.84/xmlui/handle/xmlui/16962 2026-01-04T08:32:32Z 2025-01-01T00:00:00Z

نهج التعلم الآلي القائم على تخطيط كهربية الدماغ للكشف المبكر عن مرض الزهايمر في العراق نيكار م شفيق

2025-01-01T00:00:00Z مروة عبد الكريم http://148.72.244.84/xmlui/handle/xmlui/16961 2026-01-04T07:53:46Z 2025-01-01T00:00:00Z

اختيار الميزات الهجينة ونماذج التعلم العميق لاكتشاف الأدوية مروة عبد الكريم

2025-01-01T00:00:00Z