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Wyniki wyszukiwania dla: REINFORCED CONCRETE SHEAR WALL MACHINE LEARNING ALGORITHM SEISMIC FAILURE PROBABILITY OPTIMIZATION ALGORITHM SEISMIC PERFORMANCE CURVE SEISMIC RETROFIT
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublikacjaEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany 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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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, 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...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity 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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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Seismic probabilistic assessment of steel and reinforced concrete structures including earthquake-induced pounding
PublikacjaRecent earthquakes demonstrate that prioritizing the retrofitting of buildings should be of the utmost importance for enhancing the seismic resilience and structural integrity of urban structures. To have a realistic results of the pounding effects in modeling process of retrofitting buildings, the present research provides seismic Probability Factors (PFs), which can be used for estimating collision effects without engaging in...
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Introducing a Computational Method to Retrofit Damaged Buildings under Seismic Mainshock-Aftershock Sequence
PublikacjaRetrofitting damaged buildings is a challenge for engineers, since commercial software does not have the ability to consider the local damages and deformed shape of a building resulting from the mainshock record of an earthquake before applying the aftershock record. In this research, a computational method for retrofitting of damaged buildings under seismic mainshock-aftershock sequences is proposed, and proposed computational...
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Numerical Study on Seismic Response of a High-Rise RC Irregular Residential Building Considering Soil-Structure Interaction
PublikacjaThe objective of the present study is to investigate the importance of soilstructure interaction effects on the seismic response of a high-rise irregular reinforced-concrete residential building. In order to conduct this research, a detailed three-dimensional structure model was subjected to various earthquake excitations, also including a strong mining tremor. Soil-foundation flexibility was represented using the spring-based...
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Probabilistic seismic assessment of RC box-girder highway bridges with unequal-height piers subjected to earthquake-induced pounding
PublikacjaThis paper uses the probabilistic seismic assessment to study the effects of pounding and irregularity on the seismic behavior of typical concrete box-girder bridges with four levels of altitudinal irregularity. To extend the results for all bridges in the same class, uncertainty related to the earthquake, structural geometries, and materials are considered. Pounding is likely to take place in two cases: the first one concerns...
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Fragility analysis of structural pounding between adjacent structures arranged in series with various alignment configurations under near‑field earthquakes
PublikacjaA major cause of local to total damages is related to structural pounding in a large number of past earthquakes. In general, these collisions take place as a result of differences in the dynamic characteristics of the colliding structures. To acquire a better perception of the behavior of structures, in this paper, three structures featuring different heights are modeled in series and with various configurations next to each other...