Developing a Regression Model for Predicting the Seismic Input Energy of RC Buildings Using 6 February 2023 Kahramanmaraş Earthquake

Bilal Balun

Makale detayları

Developing a Regression Model for Predicting the Seismic Input Energy of RC Buildings Using 6 February 2023 Kahramanmaraş Earthquake

Yazarlar:

Bilal Balun

Yayıncı:

Bingol University

Ana Başlıklar:

Bilgi Güvenliği Yönetimi

Dergi:

Türk Doğa ve Fen Dergisi Vol.13 Issue 1, pp.142-151

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001314171

pISSN:

2149-6366

Anahtar kelimeler:

Özet:

 Energy-based seismic analysis and structural design require understanding the seismic input energy response of reinforced concrete buildings subjected to strong ground motions. Thus, calculating and predicting input energies becomes of great importance. The object of this study is to introduce a regression model for predicting the seismic input energies of reinforced concrete buildings using the 6 February 2023 Kahramanmaraş earthquake. For this purpose, three regular 3, 6 and 9-storey residential reinforced concrete buildings are designed. Input energy response histories of buildings subjected to a set of horizontal acceleration histories of 67 stations of the February 6 Kahramanmaraş earthquake were obtained. Subsequently, the ground motion parameters were used to estimate the input energies. It was revealed that acceleration-based parameters generally had better consequences than velocity-based parameters in low periods, while the opposite was the case in high periods. This study proposed new equations in which multiple ground motion parameters are combined to better reflect input energy from a single parameter. As the height and period of the buildings increase, the multiple linear regression coefficient decreases and the estimation of input energy becomes difficult with the ground motion parameters.

 Energy-based seismic analysis and structural design require understanding the seismic input energy response of reinforced concrete buildings subjected to strong ground motions. Thus, calculating and predicting input energies becomes of great importance. The object of this study is to introduce a regression model for predicting the seismic input energies of reinforced concrete buildings using the 6 February 2023 Kahramanmaraş earthquake. For this purpose, three regular 3, 6 and 9-storey residential reinforced concrete buildings are designed. Input energy response histories of buildings subjected to a set of horizontal acceleration histories of 67 stations of the February 6 Kahramanmaraş earthquake were obtained. Subsequently, the ground motion parameters were used to estimate the input energies. It was revealed that acceleration-based parameters generally had better consequences than velocity-based parameters in low periods, while the opposite was the case in high periods. This study proposed new equations in which multiple ground motion parameters are combined to better reflect input energy from a single parameter. As the height and period of the buildings increase, the multiple linear regression coefficient decreases and the estimation of input energy becomes difficult with the ground motion parameters.

 Energy-based seismic analysis and structural design require understanding the seismic input energy response of reinforced concrete buildings subjected to strong ground motions. Thus, calculating and predicting input energies becomes of great importance. The object of this study is to introduce a regression model for predicting the seismic input energies of reinforced concrete buildings using the 6 February 2023 Kahramanmaraş earthquake. For this purpose, three regular 3, 6 and 9-storey residential reinforced concrete buildings are designed. Input energy response histories of buildings subjected to a set of horizontal acceleration histories of 67 stations of the February 6 Kahramanmaraş earthquake were obtained. Subsequently, the ground motion parameters were used to estimate the input energies. It was revealed that acceleration-based parameters generally had better consequences than velocity-based parameters in low periods, while the opposite was the case in high periods. This study proposed new equations in which multiple ground motion parameters are combined to better reflect input energy from a single parameter. As the height and period of the buildings increase, the multiple linear regression coefficient decreases and the estimation of input energy becomes difficult with the ground motion parameters.

 Energy-based seismic analysis and structural design require understanding the seismic input energy response of reinforced concrete buildings subjected to strong ground motions. Thus, calculating and predicting input energies becomes of great importance. The object of this study is to introduce a regression model for predicting the seismic input energies of reinforced concrete buildings using the 6 February 2023 Kahramanmaraş earthquake. For this purpose, three regular 3, 6 and 9-storey residential reinforced concrete buildings are designed. Input energy response histories of buildings subjected to a set of horizontal acceleration histories of 67 stations of the February 6 Kahramanmaraş earthquake were obtained. Subsequently, the ground motion parameters were used to estimate the input energies. It was revealed that acceleration-based parameters generally had better consequences than velocity-based parameters in low periods, while the opposite was the case in high periods. This study proposed new equations in which multiple ground motion parameters are combined to better reflect input energy from a single parameter. As the height and period of the buildings increase, the multiple linear regression coefficient decreases and the estimation of input energy becomes difficult with the ground motion parameters.

Makale detayları

Developing a Regression Model for Predicting the Seismic Input Energy of RC Buildings Using 6 February 2023 Kahramanmaraş Earthquake

Yazarlar:

Bilal Balun

Yayıncı:

Bingol University

Ana Başlıklar:

Bilgi Güvenliği Yönetimi

Dergi:

Türk Doğa ve Fen Dergisi Vol.13 Issue 1, pp.142-151

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001314171

pISSN:

2149-6366

Kahramanmaraş earthquake

Input energy

Multiple regression

Correlation

Sayı

Makale detayları

Developing a Regression Model for Predicting the Seismic Input Energy of RC Buildings Using 6 February 2023 Kahramanmaraş Earthquake

Yazarlar: Bilal Balun

Yayıncı: Bingol University

Ana Başlıklar: Bilgi Güvenliği Yönetimi

Dergi: Türk Doğa ve Fen Dergisi Vol.13 Issue 1, pp.142-151

Belge Tipi: Makale

Yayın Tarihi: 3/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001314171

pISSN: 2149-6366

Kahramanmaraş earthquake

Input energy

Multiple regression

Correlation

Sayı

Yazarlar:

Bilal Balun

Yayıncı:

Bingol University

Ana Başlıklar:

Bilgi Güvenliği Yönetimi

Dergi:

Türk Doğa ve Fen Dergisi Vol.13 Issue 1, pp.142-151

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001314171

pISSN:

2149-6366