Alternative Environmental Contours for Marine Structural Design—A Comparison Study1

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
Erik Vanem ◽  
Elzbieta M. Bitner-Gregersen
Keyword(s):  
Monte Carlo ◽  
Structural Design ◽  
Significant Wave Height ◽  
Joint Distribution ◽  
Traditional Approach ◽  
Physical Space ◽  
Probability Density Functions ◽  
Density Functions ◽  
New Approach ◽  
Rosenblatt Transformation

A new approach to estimate environmental contours in the original physical space by direct Monte Carlo simulations rather than applying the Rosenblatt transformation has recently been proposed. In this paper, the new and the traditional approach to estimating the contours are presented and the assumptions on which they are based are discussed. The different results given by these two methods are then compared in a number of case studies. Simultaneous probability density functions are fitted to the joint distribution of significant wave height and wave period for selected ocean locations and environmental contours are estimated for both methods. Thus, the practical consequences of the choice of approach are assessed. Particular attention is given to mixed sea systems. In these situations, the two approaches to environmental contours may be very different while for other wave conditions the contours are similar.

Alternative Environmental Contours for Marine Structural Design: A Comparison Study

2014 ◽  
Author(s):  
Erik Vanem ◽  
Elzbieta M. Bitner-Gregersen
Keyword(s):  
Structural Design ◽  
Joint Distribution ◽  
Traditional Approach ◽  
Physical Space ◽  
Probability Density Functions ◽  
Density Functions ◽  
Comparison Study ◽  
New Approach ◽  
Contour Lines ◽  
Wind Sea

A new approach to estimating environmental contours has recently been proposed, where the contours are estimated in the original physical space by Monte Carlo simulations from the joint distribution directly rather than applying the Rosenblatt transformation. In this paper, the new and the traditional approach to estimating the contours are presented and the assumptions on which they are based are discussed. The different results given by these two methods are then compared in a number of case studies. Simultaneous probability density functions are fitted to the joint distribution of significant wave height and wave period for selected ocean locations and, for each area, environmental contours are estimated for both methods. The chosen locations are characterised by different wave climates. Thus, the practical consequences of the choice of approach are assessed. Particular attention is given to mixed sea systems, i.e. a combination of wind sea and swell. In these situations, the new approach for environmental contours may fail to identify realistic conditions along some parts of the contours while for other wave conditions the contours are quite similar. The paper also briefly discusses possible ways of amending the new approach to estimating the contours to obtain more realistic conditions all along the contour lines.

Probabilistic Optimal Design Using Successive Surrogate Probability Density Functions

1990 ◽  
Author(s):  
R. J. Eggert ◽  
R. W. Mayne
Keyword(s):  
Probability Density ◽  
Optimization Method ◽  
Probability Density Functions ◽  
Density Functions ◽  
Matching Method ◽  
Design Constraint ◽  
New Approach ◽  
Function Formulation ◽  
The Moment ◽  
Theoretical Considerations

Abstract Probabilistic optimization using the moment matching method and the simulation optimization method are discussed and compared to conventional deterministic optimization. A new approach based on successively approximating probability density functions, using recursive quadratic programming for the optimization process, is described. This approach incorporates the speed and robustness of analytical probability density functions and improves accuracy by considering simulation results. Theoretical considerations and an example problem illustrate the features of the approach. The paper closes with a discussion of an objective function formulation which includes the expected cost of design constraint failure.

An Approach to the Intermediate State of the Distributed Internal Fields on Muon Site

2019 ◽  
Vol 966 ◽  
pp. 476-482
Author(s):  
Muhamad Darwis Umar ◽  
Isao Watanabe
Keyword(s):  
Intermediate State ◽  
Muon Spin ◽  
Golden Rule ◽  
Probability Density Functions ◽  
Density Functions ◽  
New Approach ◽  
High Tc ◽  
Muon Site ◽  
Spin Depolarization ◽  
Superconducting Oxides

We show a new approach to provide anaysis functions of the muon-spin depolarization in order to describe the intermediate state between Gaussian and Lorentzian behavior. The Kubo Golden Rule (KGR) formula was used to mix the Gaussian and Lorentzian probability density functions. The result confirmed that the KGR formula can analytically explain the intermediate states. The current study suggests a new approach to investigate the so-called pseudogap state of high-Tc superconducting oxides.

Distances in Gaussian point sets

1985 ◽  
Vol 97 (3) ◽  
pp. 515-524 ◽  
Author(s):  
Peter Clifford ◽  
N. J. B. Green
Keyword(s):  
Probability Density ◽  
Generating Functions ◽  
Joint Distribution ◽  
Probability Density Functions ◽  
Density Functions ◽  
Point Sets ◽  
Point Configuration ◽  
Moment Generating Functions ◽  
Gaussian Point ◽  
Normally Distributed

AbstractThe joint distribution of the n(n− l)/2 distances between n normally distributed points in d dimensions is studied. Moment generating functions and probability density functions are obtained. It is shown that when n = d the squared distances are jointly exponentially distributed subject only to the constraint that a valid n point configuration is prescribed. In the case n = d = 3 the distributions of the ordered distance are obtained explicitly.

A New Approach to Probability in Engineering Design and Optimization

1984 ◽  
Vol 106 (1) ◽  
pp. 5-10 ◽  
Author(s):  
J. N. Siddall
Keyword(s):  
Probability Density ◽  
Engineering Design ◽  
Probability Distributions ◽  
Probability Density Functions ◽  
Density Functions ◽  
New Approach ◽  
Design And Optimization ◽  
Evolutionary Technique ◽  
Probability And Statistics

The anomalous position of probability and statistics in both mathematics and engineering is discussed, showing that there is little consensus on concepts and methods. For application in engineering design, probability is defined as strictly subjective in nature. It is argued that the use of classical methods of statistics to generate probability density functions by estimating parameters for assumed theoretical distributions should be used with caution, and that the use of confidence limits is not really meaningful in a design context. Preferred methods are described, and a new evolutionary technique for developing probability distributions of new random variables is proposed. Although Bayesian methods are commonly considered to be subjective, it is argued that, in the engineering sense, they are really not. A general formulation of the probabilistic optimization problem is described, including the role of subjective probability density functions.

scholarly journals EXTREMAL STATISTICS OF STORM SURGES BY TYPHOON

1984 ◽  
Vol 1 (19) ◽  
pp. 8
Author(s):  
Yoshito Tsuchiya ◽  
Yoshiaki Kawata
Keyword(s):  
Probability Density ◽  
Return Period ◽  
Storm Surges ◽  
Probability Density Functions ◽  
Density Functions ◽  
Tidal Variation ◽  
New Approach ◽  
Probability Of Occurrence ◽  
Typhoon Track ◽  
Tidal Data

The objective of this paper is to propose a new approach based on the direction of the typhoon track for determining the probability of occurrence of extremal tides due to storm surges, as well as their return period. The study includes the effects of periods in tidal data and of tidal variation stemming from extensive reclamation along coasts on the fitness of the extremal data to probability density functions. The method is justified by application to an analysis of the probability of occurrence of storm surges in Osaka bay.

scholarly journals Comments on Copula Functions and Their Relationship to Probability Density Functions

2020 ◽  
pp. 1115-1122
Author(s):  
Ahmed AL-Adilee ◽  
Ola Hassan
Keyword(s):  
Probability Density ◽  
Statistical Inference ◽  
Joint Distribution ◽  
Probability Density Functions ◽  
Distribution Functions ◽  
Density Functions ◽  
Copula Functions ◽  
Statistical Inferences ◽  
Dependence Structures

Copulas are very efficient functions in the field of statistics and specially in statistical inference. They are fundamental tools in the study of dependence structures and deriving their properties. These reasons motivated us to examine and show  various types of copula functions and their families. Also, we separately explain each method that is used to construct each copula in detail with different examples. There are various outcomes that show the copulas and their densities with respect to the joint distribution functions. The aim is to make copulas available to new researchers and readers who are interested in the modern phenomenon of statistical inferences.

NEARLY EXACT OPTION PRICE SIMULATION USING CHARACTERISTIC FUNCTIONS

2012 ◽  
Vol 15 (07) ◽  
pp. 1250047 ◽  
Author(s):  
CAROLE BERNARD ◽  
ZHENYU CUI ◽  
DON MCLEISH
Keyword(s):  
Characteristic Function ◽  
Probability Density ◽  
Option Price ◽  
Probability Density Functions ◽  
Heston Model ◽  
Characteristic Functions ◽  
Density Functions ◽  
New Approach ◽  
Black Scholes ◽  
Unbiased Estimates

This paper presents a new approach to perform a nearly unbiased simulation using inversion of the characteristic function. As an application we are able to give unbiased estimates of the price of forward starting options in the Heston model and of continuously monitored Parisian options in the Black-Scholes framework. This method of simulation can be applied to problems for which the characteristic functions are easily evaluated but the corresponding probability density functions are complicated.

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