There is a large amount of useful information from past experimental tests, which are usually ignored in test-setup for the new ones. Variation of assumptions, materials, test procedures, and test objectives make it difficult to choose the right model for validation of the numerical models. Results from different experiments are sometimes in conflict with each other, or have minimum correlation. Furthermore, not all these information are easily accessible for researchers and engineers. Therefore, this paper presents the results of a comprehensive study on different experimental models for steel plate and reinforced concrete shear walls. A unique library of up to 13 parameters (mechanical properties and geometric characteristics) affecting the strength, stiffness and drift ratio of the shear walls are gathered including their sensitivity analysis. Next, a predictive meta-model is developed based on artificial neural network. It is capable of forecasting the responses for any desired shear wall with good accuracy. The proposed network can be used to as an alternative to the nonlinear numerical simulations or expensive experimental test.
Humans are living in an uncertain world, with daily risks confronting them from various low to high hazard events, and the COVID-19 pandemic has created its own set of unique risks. Not only has it caused a significant number of fatalities, but in combination with other hazard sources, it may pose a considerably higher multi-risk. In this paper, three hazardous events are studied through the lens of a concurring pandemic. Several low-probability high-risk scenarios are developed by the combination of a pandemic situation with a natural hazard (e.g., earthquakes or floods) or a complex emergency situation (e.g., mass protests or military movements). The hybrid impacts of these multi-hazard situations are then qualitatively studied on the healthcare systems, and their functionality loss. The paper also discusses the impact of pandemic’s (long-term) temporal effects on the type and recovery duration from these adverse events. Finally, the concept of escape from a hazard, evacuation, sheltering and their potential conflict during a pandemic and a natural hazard is briefly reviewed. The findings show the cascading effects of these multi-hazard scenarios, which are unseen nearly in all risk legislation. This paper is an attempt to urge funding agencies to provide additional grants for multi-hazard risk research.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.