Modeling environmental loads and structural responses

Any maritime activity is exposed to variable environment, waves, winds and, in larger scales, storms and consequences of climate change. Safety of sea transports, risk assessment in maritime activities, depend on adequate descriptions of sea variability and of the interaction of structures with environment. The choice of models and appropriate statistical procedures to fit models to observed loads is crucial and requires engineering judgment and stochastic analysis. That is why we propose a cooperative project between marine design and statistical sciences, for environment modeling of the sea´s variability. The purpose of the project is to better describe present, and predict future, variability of sea conditions. A new class of models, based on Laplace distribution, will be used. The models are more flexible to describe the asymmetries observed in waves and storms. At present, huge data sets containing space-time climate and meteorological data are collected and made available for scientists. We will use these for risk mitigation by developing statistical models, and create tools for analysis, estimation, and model checking. The main focus will be modeling, measurement, and planning methods to avoid catastrophic fatigue failures in marine structures. We will study multiaxial fatigue damage accumulation and apply the models developed on container ships in harsh seas. Further, means to predict risks for low cycle fatigue in severe storms will also be developed.


Igor Rychlik (contact)

at Mathematical Sciences, Mathematical Statistics

Wengang Mao

Docent at Shipping and Marine Technology, Marine Structures and Hydrodynamics

Jonas Ringsberg

Professor at Shipping and Marine Technology, Marine Structures and Hydrodynamics


Swedish Research Council (VR)

Funding years 2012–2015

Related Areas of Advance and Infrastructure

Materials Science

Area of Advance


Area of Advance

Sustainable Development

Chalmers Driving Force

Basic Sciences

Chalmers Roots



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Scientific journal article - peer reviewed

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