Vulnerability assessment of building structures due to underground blasts using ANN and non-linear dynamic analysis. (December 2021)
- Record Type:
- Journal Article
- Title:
- Vulnerability assessment of building structures due to underground blasts using ANN and non-linear dynamic analysis. (December 2021)
- Main Title:
- Vulnerability assessment of building structures due to underground blasts using ANN and non-linear dynamic analysis
- Authors:
- Kumar, Sumit
Chandra Dutta, Sekhar
Goswami, Kundan
Mandal, Parthasarathi - Abstract:
- Abstract: Building structures near the mines area are prone to blast-induced ground vibration due to underground blasting. The level of ground vibration typically quantified as Peak Particle Velocity (PPV) is used to assess the vulnerability of the buildings. However, the PPV does not take into account the dynamic characteristics of the structure. To incorporate structural response in the design and assessment process, Artificial Neural Network (ANN) was used on underground blast data from the literature to obtain the Peak Ground Acceleration (PGA). Charge weight ( Q ), distance from the blasting point to the monitoring point ( D ) and soil's elastic constant ( E ) were taken as input to ANN and peak ground acceleration (PGA) was the output. Safe site distance for constructing structures was determined using non-linear time history analysis of structures having periods ranging from short to long duration, incorporating soil flexibility. The main findings highlight the shortcomings of considering PPV as the sole criteria for vulnerability assessment. The structural response such as interstorey drift, and damage level and locations must be taken into account. Highlights: The vulnerability of building structures under underground blast has been investigated using both PPV criterion and non-linear time history response of structures at different site distances. Artificial neural network (ANN) is used to predict PGA at different site distances, as ground excitation with differentAbstract: Building structures near the mines area are prone to blast-induced ground vibration due to underground blasting. The level of ground vibration typically quantified as Peak Particle Velocity (PPV) is used to assess the vulnerability of the buildings. However, the PPV does not take into account the dynamic characteristics of the structure. To incorporate structural response in the design and assessment process, Artificial Neural Network (ANN) was used on underground blast data from the literature to obtain the Peak Ground Acceleration (PGA). Charge weight ( Q ), distance from the blasting point to the monitoring point ( D ) and soil's elastic constant ( E ) were taken as input to ANN and peak ground acceleration (PGA) was the output. Safe site distance for constructing structures was determined using non-linear time history analysis of structures having periods ranging from short to long duration, incorporating soil flexibility. The main findings highlight the shortcomings of considering PPV as the sole criteria for vulnerability assessment. The structural response such as interstorey drift, and damage level and locations must be taken into account. Highlights: The vulnerability of building structures under underground blast has been investigated using both PPV criterion and non-linear time history response of structures at different site distances. Artificial neural network (ANN) is used to predict PGA at different site distances, as ground excitation with different combinations of site distances and charge weights is not available in the literature. Non-linear time history analyses of structures have been carried out incorporating soil flexibility for determining responses of structures with different lateral natural periods. Interstorey drift response of structures have been obtained typically for short, medium and long period structures. The level of damages have been compared as per the prescribed limits for performance-based design in well-accepted guidelines. … (more)
- Is Part Of:
- Journal of building engineering. Volume 44(2021)
- Journal:
- Journal of building engineering
- Issue:
- Volume 44(2021)
- Issue Display:
- Volume 44, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 44
- Issue:
- 2021
- Issue Sort Value:
- 2021-0044-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-12
- Subjects:
- Underground blasting -- PPV -- ANN -- PGA -- Non-linear dynamic analysis -- Interstorey drift
Building -- Periodicals
690.05 - Journal URLs:
- http://www.sciencedirect.com/science/journal/23527102 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.jobe.2021.102674 ↗
- Languages:
- English
- ISSNs:
- 2352-7102
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19862.xml