Bayesian probabilistic representation of complex systems: With application to wave load modeling

2021 ◽  
Author(s):  
Sebastian T. Glavind ◽  
Henning Brüske ◽  
Erik D. Christensen ◽  
Michael H. Faber
Keyword(s):  
Complex Systems ◽  
Probabilistic Representation ◽  
Wave Load ◽  
Load Modeling

Reliability Study of a North-Sea Jack-Up Under Action of Wave-in-Deck, SH- and SV-Seismic Waves Considering Spud-Can-Soil Interaction

2010 ◽  
Author(s):  
M. Reza Emami Azadi
Keyword(s):  
North Sea ◽  
Seismic Waves ◽  
Soil Parameters ◽  
Wave Load ◽  
Load Modeling ◽  
Annual Probability ◽  
Plate Elements ◽  
Hyper Elastic ◽  
Interaction Modeling ◽  
Jack Up

In the current study, the effect of spud-can-soil interaction modeling as well as wave load modeling and sea-state on the reliability index of a three-leg North-sea drilling type jack-up platform is studied. The platform has operated in depths of 95–105m and its three main legs modeled as pipe elements and the main deck is also modeled using general beam and also shell/plate elements. The spud-can foundation is modeled using elasto-plastic, hyper-elastic springs as well as spud-model of usfos using a general non-associative plasticity model. The wave-in-deck load is considered using API-RP2A [1], Shell and Statoil models. The SH and SV-seismic waves are considered separately at spud-can base as scaled. The preliminary results of this study showed that the annual probability of failure for the Jack-up platform is significantly affected by the random-sea and wave-in-deck modeling as well as spud-can-soil interaction modeling and soil parameters. Study of importance factors indicated that more refined spud-can-soil interaction modeling as well as wave-in-deck load modeling might improve the calculation models and hence reduce their associated uncertainty in reliability analysis of jack-up type platform.

A Stochastic Model for the Inheritance of the Cancer Proneness Phenotype

1987 ◽  
Vol 26 (03) ◽  
pp. 117-123
Author(s):  
P. Tautu ◽  
G. Wagner
Keyword(s):  
Stochastic Model ◽  
Gaussian Process ◽  
Covariance Function ◽  
Neoplastic Disease ◽  
Disease Phenotype ◽  
Probabilistic Representation ◽  
Temporal Behaviour ◽  
Continuous Trait ◽  
Continuous Parameter ◽  
Level Zero

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.

Complex systems-operational approaches

1990 ◽  
Vol 160 (7) ◽  
pp. 163-164
Author(s):  
Boris B. Kadomtsev
Keyword(s):  
Complex Systems
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