Efficient Simulation Method for First Passage Problem of Linear Systems Subjected to Non-Gaussian Excitations

2022 ◽  
Vol 148 (1) ◽  
Author(s):  
Zhao Zhao ◽  
Zhao-Hui Lu ◽  
Chun-Qing Li ◽  
Yan-Gang Zhao
Keyword(s):  
Linear Systems ◽  
Simulation Method ◽  
First Passage ◽  
Efficient Simulation ◽  
Non Gaussian ◽  
First Passage Problem

Efficient Simulation Method to Predict Green Water Loads on Superstructures

2015 ◽  
Author(s):  
Lasse Theilen ◽  
Ole Detlefsen ◽  
Moustafa Abdel-Maksoud ◽  
Michael Bohm
Keyword(s):  
Simulation Method ◽  
Computational Effort ◽  
Numerical Prediction ◽  
Green Water ◽  
Impact Loads ◽  
Operational Conditions ◽  
Efficient Simulation ◽  
Non Linear ◽  
Linear Behaviour

The numerical prediction of green water loads on super-structures is challenging due to the high number of required calculations to identify the critical operational conditions in the seaway which lead to overcoming seawater on deck. Further, the simulation of the non-linear behaviour of water on the deck and the prediction of impact loads require high computational effort. This paper presents an efficient three-step approach to simulate green water loads. The application of the developed procedure will be demonstrated on a mega yacht geometry.

On first passage times of sticky reflecting diffusion processes with double exponential jumps

2020 ◽  
Vol 57 (1) ◽  
pp. 221-236 ◽  
Author(s):  
Shiyu Song ◽  
Yongjin Wang
Keyword(s):  
Diffusion Processes ◽  
First Passage Time ◽  
Passage Time ◽  
Explicit Solutions ◽  
First Passage ◽  
Uhlenbeck Process ◽  
Double Exponential ◽  
Upper Level ◽  
First Passage Problem ◽  
Passage Times

AbstractWe explore the first passage problem for sticky reflecting diffusion processes with double exponential jumps. The joint Laplace transform of the first passage time to an upper level and the corresponding overshoot is studied. In particular, explicit solutions are presented when the diffusion part is driven by a drifted Brownian motion and by an Ornstein–Uhlenbeck process.

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