Probabilistic demand models and performance-based fragility estimates for concrete protective structures subjected to missile impact

Jaswanth Gangolu, Ajay Kumar, Kasturi Bhuyan and Hrishikesh Sharma

Reliability Engineering and System Safety, 2022, vol. 223, issue C

Abstract: The manifold missile attacks upon structures and deficiency of codal provisions motivated the current study to develop probabilistic demand models for protective structures subjected to hard missile impact. These energy-based models are estimated using a defined performance-based design framework (PBD) with three performance levels associated with four damage states, i.e. from minor damage to total collapse. The evaluation of unknown model parameters is constructed using the Bayesian approach. The current and upcoming range of structural variables is chosen for numerical experimental design. LS-DYNA, a finite element (FE) numerical method, is used to generate necessary probabilistic data of Reinforced Concrete (RC) & Prestressed Concrete (PC) panels subject to a hard missile. Novel formulations for local damages of a target, such as perforation limit of RC panel & Ballistic limit of the missile for RC & PC panels, are estimated. The developed demand models are used to assess the fragility estimation of either panel under chosen performance levels for a containment structure located in Tarapur, Palghar, India. An accurate fragility plot and comparative study shows the consistency of probabilistic models with test results. These models consider aleatory and epistemic uncertainties in modeling, material & geometrical properties, strain rate & inertia effect, and complex interaction involved in an impact scenario.

Keywords: Probabilistic demand models; Performance-based design; Protective structures; Missile impact; Local damages; Reinforced & pre-stressed concrete structures; Fragility analysis (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:223:y:2022:i:c:s0951832022001582

DOI: 10.1016/j.ress.2022.108497

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