Sina Basereh

Sina Basereh
  • Doctor of Philosophy
  • University at Buffalo, State University of New York

About

13
Publications
2,666
Reads
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99
Citations
Current institution
University at Buffalo, State University of New York
Additional affiliations
August 2017 - present
University at Buffalo, State University of New York
Position
  • Research Assistant
August 2016 - August 2017
University at Buffalo, State University of New York
Position
  • Research Assistant
Education
August 2016 - June 2021
University at Buffalo, State University of New York
Field of study
  • Structural Engineering
September 2011 - June 2015
University of Tehran
Field of study
  • Civil Engineering

Publications

Publications (13)
Presentation
Slender reinforced concrete structural walls are efficient lateral force resisting systems. However, many existing walls designed based on pre-modern seismic code provisions are expected to fail in a brittle manner, due to inadequate amount of shear reinforcement, poorly confined boundary elements, or poor detailing. A new method for retrofitting s...
Conference Paper
Full-text available
Many reinforced concrete (RC) buildings built before the adoption of modern seismic codes in high seismic regions need to be retrofitted to perform well in a major earthquake. This study introduces a new retrofit method for code-deficient reinforced concrete shear walls that are vulnerable to non-ductile failure modes due to improper detailing or l...
Article
This paper investigates a novel retrofit strategy for code-deficient reinforced-concrete (RC) shear walls that are vulnerable to undesirable failure modes. The strategy combines weakening by partially cutting the wall base and self-centering by adding post-tensioning. RC walls in need of retrofit were analyzed under lateral cyclic loading using thr...
Conference Paper
Full-text available
FEMA P-807-1 offers guidelines and suggestions for assessing the seismic stability of multi-unit wood-frame buildings with vulnerable first levels. The document has extensive technical information on the anticipated seismic failure performance of "soft-story" structures in both unretrofitted and retrofitted states. It provides practicable advice to...
Article
Full-text available
This paper demonstrates the efficacy of a new reinforced concrete shear wall seismic retrofit method through a series of nonlinear static and incremental dynamic analyses. Unlike traditional retrofit methods, the method investigated aims to convert conventional walls into self‐centering walls whose behavior is governed by rocking and flexure. The r...
Article
Full-text available
This paper presents an innovative method to quantify damage based on surface cracks of reinforced concrete shear walls (RCSWs). The key idea is to use artificial intelligence and convert crack patterns to graphs. In this method, the mathematics of graph theory is used to extract information (graph‐based features) from crack patterns and use them fo...
Conference Paper
Full-text available
An increasing number of jurisdictions in California have enacted mandatory retrofit programs for wood-frame, multi-unit, soft-story buildings, and the most recently signed budget of the state of California appropriates $250M of financial assistance for retrofit of high-risk, weak-story multifamily buildings. Many mandatory retrofit programs allow s...
Conference Paper
Full-text available
Traditional retrofit methods typically focus on increasing strength/stiffness of the structure. This may increase seismic demand on the structure and could lead to excessive damage during a seismic event. This paper presents an alternative retrofit method which integrates concepts from selective weakening and self-centering (rocking) to achieve low...
Chapter
Damage signs in concrete elements and structures appear on the surface in the form of cracks. Precise detection of existing crack pattern provides a reliable basis for updating the structural parameters of damaged concrete elements and predicting future behavior. Several studies have developed crack detection methods based on image processing of cr...

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