Neda Asgarkhani
Zatrudnienie
- Ph.D. student w Gdasnk university of technology
Słowa kluczowe Pomoc
- data-driven techniques
- buckling-restrained braced frame machine-learning algorithm residual interstory drift seismic retrofit seismic performance curve seismic failure probability
- computational method - damaged-building - retrofitting of buildings - mainshock-aftershock sequence
- computational method, active learning, ensemble machine-learning mod-el, retrofitting structures, mainshock-aftershock sequence.
- computational optimization
- cross-sectional area
- dome structures.
- double-stage yield buckling-restrained brace steel slit damper experimental validation cyclic loading test novel bracing system seismic retrofit energy dissipation devices
- fiber-reinforced polymer
- high-performance alkali-activated concrete compressive strength cost and carbon emission machine learning algorithms steel fiber
Media społecznościowe
Wybrane publikacje
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
Many studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
Complexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
Nowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
wyświetlono 875 razy