Analysis of Offshore Platform Structural Integrity Under ‎Extreme Weather Conditions

  • Authors

    • S. Sudarsanan Department of Nautical Science, AMET University, Kanathur, Tamil Nadu, India
    • B. Santhakumar Department of Nautical Science, AMET University, Kanathur, Tamil Nadu, India
    https://doi.org/10.14419/e0q0kb52

    Received date: May 10, 2025

    Accepted date: May 29, 2025

    Published date: July 8, 2025

  • Climate Change; Weather Conditions; Challenges; Integrity

  • Abstract

    Extreme weather patterns have caused damage and destruction all around the world in recent years, making climate change a more urgent ‎concern. To comprehend the consequences of climate extremes for risk and resilience, new methods for evaluating their incidence, ‎distribution, and dependency are needed. Risk and resilience assessment is a difficult work because of the complexity of climate systems, ‎complex ecosystem-climatic interactions, interdependence of climate extremes, and predominant nonstationary. Furthermore, the risk posed ‎by extreme weather events depends on a variety of factors, including exposure and vulnerability, in addition to the severity of the extremes ‎themselves. Accurately estimating the likelihood of a hazardous physical event and how it interacts with exposure and susceptibility factors ‎including population, infrastructure, environmental services, and economic assets are critical to risk reduction and climate change adaptation. ‎Therefore, in order to further assess the implications for risk and resilience in the context of climate change, a deeper comprehension of the ‎climate extremes in terms of their occurrence, dependency on various causes, dynamics, and predictability is required. The study conducted ‎to provide a thorough evaluation of India's extreme weather conditions and their consequences for risk and resilience is presented in this ‎thesis. The thesis's first section explains how nonlinearity and determinism have changed over the past century in India's temperature and ‎precipitation profiles. A time series' nonlinear component can be quantified by comparing variance measures, which is what the Delay Vector ‎Variance (DVV) approach is used for this inquiry. The findings demonstrate that temperature and precipitation both show significant ‎nonlinearity and declining predictability, especially in the nation's most extreme climate zones.

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  • How to Cite

    Sudarsanan, S., & Santhakumar, B. (2025). Analysis of Offshore Platform Structural Integrity Under ‎Extreme Weather Conditions. International Journal of Basic and Applied Sciences, 14(SI-1), 191-196. https://doi.org/10.14419/e0q0kb52