Reliability analysis &amp; performance-based code calibration for slabs/walls of protective structures subject to air blast loading

Bhuyan, Kasturi; Sharma, Hrishikesh

doi:10.1016/j.ress.2022.108751

Reliability Engineering & System Safety

2022

DOI: 10.1016/j.ress.2022.108751

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Reliability analysis & performance-based code calibration for slabs/walls of protective structures subject to air blast loading

Kasturi Bhuyan¹,

Hrishikesh Sharma²

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Cited by 8 publications

References 55 publications

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Probabilistic modeling of ballistic penetration in reinforced concrete panels

Dar,

Alagappan

2024

Structural Concrete

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Studying ballistic impact on reinforced concrete (RC) structures is essential for enhancing the safety and cost‐effectiveness of these structures. The depth of penetration (DOP) and residual velocity (RV) of projectiles are critical design parameters requiring precise quantification to improve the ballistic‐resistant design. Traditional empirical models are available for quantifying these parameters but are deterministic and often yield inaccurate results due to the inherent uncertainties in ballistic impacts. This paper introduces a probabilistic approach to quantify DOP and RV accurately. Bayesian inference models are developed using dimensionless explanatory functions to estimate these parameters in RC panels under hard projectile impacts, accounting for associated uncertainties. Numerical modeling is performed using LS‐Dyna, and the model is validated against experimental data from past studies. Data from refined numerical simulations, along with available experiments from the literature, are utilized to develop the probabilistic models. The findings reveal the significant influence of projectile and concrete properties, as well as the projectile's incidence angle, on DOP and RV. The probabilistic models developed are validated with previous experimental results, demonstrating their reliability and accuracy. Consequently, robust design formulae are proposed for estimating DOP and RV for RC panels under hard projectile impacts, providing a valuable tool for precise impact assessments in engineering applications.

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Probabilistic modeling of ballistic penetration in reinforced concrete panels

Dar,

Alagappan

2024

Structural Concrete

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Data-driven reliability framework for qualitative damage states of reinforced concrete beams under blast loading

Almustafa,

Balomenos,

Nehdi

2023

Engineering Structures

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Development of design guidelines using probabilistic framework for the development of smart thickening fluid based ultra resistant adaptive kinematic soft human armor (SURAKSHA)

Kumar¹,

Saxena²,

Sharma³

et al. 2023

Reliability Engineering & System Safety

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Reliability analysis & performance-based code calibration for slabs/walls of protective structures subject to air blast loading

Cited by 8 publications

References 55 publications

Probabilistic modeling of ballistic penetration in reinforced concrete panels

Probabilistic modeling of ballistic penetration in reinforced concrete panels

Data-driven reliability framework for qualitative damage states of reinforced concrete beams under blast loading

Development of design guidelines using probabilistic framework for the development of smart thickening fluid based ultra resistant adaptive kinematic soft human armor (SURAKSHA)

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