PSI - Issue 64

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ScienceDirect Structural Integrity Procedia 00 (2023) 000 – 000 Structural Integrity Procedia 00 (2023) 000 – 000 Available online at www.sciencedirect.com Available online at www.sciencedirect.com ScienceDirect Available online at www.sciencedirect.com ScienceDirect

www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia

Procedia Structural Integrity 64 (2024) 418–425

SMAR 2024 – 7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures Modelling of Hybrid Steel-SMA Shear Walls with Local Strain and SMAR 2024 – 7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures Modelling of Hybrid Steel-SMA Shear Walls with Local Strain and

Reinforcement Considerations Austin Martins-Robalino a *, Dan Palermo a a York University, 4700 Keele St, Toronto M3J 1P3, Canada Reinforcement Considerations Austin Martins-Robalino a *, Dan Palermo a a York University, 4700 Keele St, Toronto M3J 1P3, Canada

Abstract The incorporation of Super-elastic (SE) Shape Memory Alloys (SMAs), such as Nitinol (Nickel-Titanium), presents a method of passively improving the damage resiliency of traditional reinforced concrete structural elements. This resiliency can be of particular use in seismic applications owing to the super-elastic behavior allowing for increased recentering. Currently available experimental data on hybrid slender shear walls incorporating both steel and SE-SMAs has demonstrated the recentering improvements while also highlighting that use of SE-SMAs tend to cause the formation of a predominant crack that controls the response. The ability to more accurately predict this behaviour through numerical modelling would allow for better understanding of the salient parameters affecting the response of hybrid slender shear walls. The paper herein presents a numerical modelling methodology that considered the impacts of local strain concentration as a result of a singular predominant crack formation during reverse-cyclic loading. This modelling was performed in VecTor2, a non-linear two-dimensional finite element program, in conjecture with experimental data of a hybrid steel-SMA slender shear wall and a steel-only reinforced concrete companion wall. The use of a tension stiffening constitutive model which considered local fracture was found to improve the displacement prediction capabilities of models. Additional considerations which were investigated included local reinforcement properties to reflect conditions at the wall base and accounting for the impact of strain gauge instrumentation on the location of rupture of the reinforcement. The results provide insight into the numerical modeling that captures the local strain and reinforcement conditions present in hybrid steel-SMA and reinforced concrete slender shear walls. © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers Keywords: Finite Element Analysis; Super-elastic Shape Memory Alloy; Nitinol; Slender Shear Wall; Seismic Resilience Abstract The incorporation of Super-elastic (SE) Shape Memory Alloys (SMAs), such as Nitinol (Nickel-Titanium), presents a method of passively improving the damage resiliency of traditional reinforced concrete structural elements. This resiliency can be of particular use in seismic applications owing to the super-elastic behavior allowing for increased recentering. Currently available experimental data on hybrid slender shear walls incorporating both steel and SE-SMAs has demonstrated the recentering improvements while also highlighting that use of SE-SMAs tend to cause the formation of a predominant crack that controls the response. The ability to more accurately predict this behaviour through numerical modelling would allow for better understanding of the salient parameters affecting the response of hybrid slender shear walls. The paper herein presents a numerical modelling methodology that considered the impacts of local strain concentration as a result of a singular predominant crack formation during reverse-cyclic loading. This modelling was performed in VecTor2, a non-linear two-dimensional finite element program, in conjecture with experimental data of a hybrid steel-SMA slender shear wall and a steel-only reinforced concrete companion wall. The use of a tension stiffening constitutive model which considered local fracture was found to improve the displacement prediction capabilities of models. Additional considerations which were investigated included local reinforcement properties to reflect conditions at the wall base and accounting for the impact of strain gauge instrumentation on the location of rupture of the reinforcement. The results provide insight into the numerical modeling that captures the local strain and reinforcement conditions present in hybrid steel-SMA and reinforced concrete slender shear walls. © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers Keywords: Finite Element Analysis; Super-elastic Shape Memory Alloy; Nitinol; Slender Shear Wall; Seismic Resilience © 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers

* Corresponding author. E-mail address: austinmr@yorku.ca * Corresponding author. E-mail address: austinmr@yorku.ca

2452-3216 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers 2452-3216 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers

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