Stochastic Load Modeling of Ship Structures under Correlated Wave Pulses and Stochastic Voyage Process

_ This study develops a stochastic load model for ship structures that accounts for the temporal correlation of wave-induced load pulses and the stochastic process governing voyage duration. The distribution of the extreme values of the still water bending moment and its combination with wave-induced bending moment is formulated using a stochastic renewal process, accounting for the possible nonexponential distribution of voyage duration and the associated uncertainty across different ship operations. The correlated wave-induced loads are modeled as a stochastic Markov process, and closed-form expressions are derived to estimate the extreme value distribution of the load combination. The applicability and accuracy of the proposed approaches are investigated for an Aframax tanker under full load conditions, and the results obtained are compared with those of existing formulations. In addition, the impact of different stochastic processes, voyage duration models, and wave correlation on the extreme value distribution of ship structural loads is investigated. The proposed approaches are straightforward and can be readily adopted in practical engineering applications for probabilistic load modeling of ship structures. In addition, they can be extended to perform reliability analysis of ship hull girders at the ultimate limit state by incorporating a statistical description of the structural capacity. Keywords still water load effects; wave-induced load effects; stochastic process; temporal correlation; load combination

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Publication Details

Journal
Journal of Ship Research
Published
2026-05-12
DOI
https://doi.org/10.5957/josr.12240026
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
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article

Stochastic Load Modeling of Ship Structures under Correlated Wave Pulses and Stochastic Voyage Process

A. Kakaie, C J R Santos Soares
Journal of Ship Research
Probabilistic and Robust Engineering Design
article

Stochastic Load Modeling of Ship Structures under Correlated Wave Pulses and Stochastic Voyage Process

A. Kakaie, C J R Santos Soares
article en

Abstract

_ This study develops a stochastic load model for ship structures that accounts for the temporal correlation of wave-induced load pulses and the stochastic process governing voyage duration. The distribution of the extreme values of the still water bending moment and its combination with wave-induced bending moment is formulated using a stochastic renewal process, accounting for the possible nonexponential distribution of voyage duration and the associated uncertainty across different ship operations. The correlated wave-induced loads are modeled as a stochastic Markov process, and closed-form expressions are derived to estimate the extreme value distribution of the load combination. The applicability and accuracy of the proposed approaches are investigated for an Aframax tanker under full load conditions, and the results obtained are compared with those of existing formulations. In addition, the impact of different stochastic processes, voyage duration models, and wave correlation on the extreme value distribution of ship structural loads is investigated. The proposed approaches are straightforward and can be readily adopted in practical engineering applications for probabilistic load modeling of ship structures. In addition, they can be extended to perform reliability analysis of ship hull girders at the ultimate limit state by incorporating a statistical description of the structural capacity. Keywords still water load effects; wave-induced load effects; stochastic process; temporal correlation; load combination

Journal of Ship Research
University of Lisbon (PT), Centre for Research in Anthropology (PT)
Openalex Percentile: Top 6%
Probabilistic and Robust Engineering Design
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Stochastic Load Modeling of Ship Structures under Correlated Wave Pulses and Stochastic Voyage Process — A. Kakaie, C J R Santos Soares · Journal of Ship Research (2026) | TGRS Research Map | TGRS