scholarly journals ON THE METHODOLOGY OF SELECTING DESIGN WAVE HEIGHT

1988 ◽  
Vol 1 (21) ◽  
pp. 67 ◽  
Author(s):  
Yoshimi Goda
Keyword(s):  
Data Analysis ◽  
Least Square Method ◽  
Distribution Functions ◽  
Least Square ◽  
Type I ◽  
Extreme Wave ◽  
Empirical Formulas ◽  
Wave Data ◽  
Design Wave Height ◽  
Wave Heights

A statistically-rational method of extreme wave data analysis is presented. A combination of the Fisher-Tippett type I and the four Weibull distributions is proposed as the candidates of distribution functions. The least square method is used for data fitting. The best plotting position formula for each function is determined by the Monte Carlo method with 10,000 simulations per sample size. Confidence intervals of estimated extreme wave heights for given return periods are evaluated by simulations and expressed in the form of empirical formulas, for both the cases when the true distribution is known and unknown. An example of extreme wave data analysis is given.

Extrapolation of Historical Storm Data for Estimating Design-Wave Heights

1971 ◽  
Vol 11 (01) ◽  
pp. 23-37 ◽  
Author(s):  
C. Petrauskas ◽  
P.M. Aagaard
Keyword(s):  
Wave Height ◽  
Distribution Functions ◽  
Extreme Value Statistics ◽  
Return Periods ◽  
Improved Method ◽  
Design Wave Height ◽  
Straight Line ◽  
Wave Heights ◽  
Computerized Procedures ◽  
Selection Of

Abstract An improved method is presented for selecting offshore structure design waves by extrapolating historical storm data to obtain extreme value statistics. The method permits flexibility in choice of distribution functions through use of computerized procedures, estimates extrapolated wave-height procedures, estimates extrapolated wave-height uncertainty due to small sample size, and includes criteria for judging whether or not given wave-height values can be represented by one or more of the distributions implemented in the method. The relevance of uncertainty to selection of design-wave heights is discussed and illustrated. Introduction The problem of selecting design-wave heights for offshore platforms has many facets, ranging from the development of oceanographic data to the selection of the prudent level of engineering risk for a particular installation. This paper deals only with part of the problem; it describes an improved method for using the small available amount of wave-height information to estimate the extreme value statistics and associated uncertainties for the large storm waves that have a very low probability of occurrence. probability of occurrence. Hindcast wave-height information for design-wave studies usually covers a period of historical record that is shorter than the return period selected for acceptable engineering risk. Return periods commonly used for selection design waves are 100 years or more, but good meteorological data, on Which the calculated wave heights are based, can rarely be obtained for periods covering more than 50 to 60 years. As a consequence, extrapolations to longer return periods are necessary. Present methods for making the extrapolation employ probablistic models through the use of special probability graph papers on which a family of distribution functions plot as straight lines. The wave heights are plotted vs their "plotting-position" return period, and a straight line fitted to the plotted data is extended beyond the data to estimate extreme wave heights for return periods of interest. The methods are described in periods of interest. The methods are described in numerous technical papers and books; Refs. 1 through 5 are examples. The shortcomings of the present commonly used methods are:the straight line drawn through the data is in most cases visually fit to the data, thus is subject to error; andno information is available on the uncertainty of the resulting extrapolation. These shortcomings have been discussed by many authors and many of their concepts influenced this study. The improved method presented in this paper offers:greater flexibility in the choice of distributions through computerized procedures,guidelines for picking the "best" distribution from several implemented in the method, andprocedures for estimating the uncertainty of procedures for estimating the uncertainty of extrapolated wave heights. CONDENSED CONCLUSIONS Procedures described in this paper for extrapolating hindcast storm-wave heights and estimating uncertainty intervals to the extrapolated values are recommended as aids in selecting the design-wave height. The results of the extrapolating procedure and related uncertainty considerations procedure and related uncertainty considerations are only aids to help the engineer assess the risks associated with his design. The actual selection of the design-wave height is a matter of engineering judgment. The choice is subjective and will vary according to the risk chosen for the design. Further consideration of ways to decrease the span of be uncertainty intervals is warranted. Increasing the number of years represented in the sample along with the number of storms is a direct way to decrease the span. In the areas of the world having poor weather records the sample size will be marginal for many years to come. SPEJ P. 23

scholarly journals Marshall-Olkin Generalized Pareto Distribution: Bayesian and Non Bayesian Estimation

2020 ◽  
pp. 21-33 ◽  
Author(s):  
Hanan Haj AHmad ◽  
Ehab Almetwally
Keyword(s):  
Loss Function ◽  
Bayesian Method ◽  
Pareto Distribution ◽  
Generalized Pareto Distribution ◽  
Least Square Method ◽  
Least Square ◽  
Estimation Methods ◽  
Model Parameters ◽  
Type I ◽  
Generalized Pareto

A new generalization of generalized Pareto Distribution is obtained using the generator Marshall-Olkin distribution (1997). The new distribution MOGP is more flexible and can be used to model non-monotonic failure rate functions. MOGP includes six different sub models: Generalized Pareto, Exponential, Uniform, Pareto type I, Marshall-Olkin Pareto and Marshall-Olkin exponential distribution. We consider different estimation procedures for estimating the model parameters, namely: Maximum likelihood estimator, Maximum product spacing, Least square method, weighted least square method and Bayesian Method. The Bayesian Method is considered under quadratic loss function and Linex loss function. Simulation analysis using MCMC technique is performed to compare between the proposed point estimation methods. The usefulness of MOGP is illustrated by means of real data set, which shows that this generalization is better fit than Pareto, GP and MOP distributions.

A Trajectory Evaluator by Sub-tracks for Detecting VOT-based Anomalous Trajectory

2022 ◽  
Vol 16 (4) ◽  
pp. 1-19
Author(s):  
Fei Gao ◽  
Jiada Li ◽  
Yisu Ge ◽  
Jianwen Shao ◽  
Shufang Lu ◽  
...  
Keyword(s):  
Data Analysis ◽  
Mobile Robots ◽  
State Of The Art ◽  
Least Square Method ◽  
Least Square ◽  
Visual Object ◽  
Massive Data ◽  
Trajectory Data ◽  
Visual Object Tracking ◽  
Research Hotspots

With the popularization of visual object tracking (VOT), more and more trajectory data are obtained and have begun to gain widespread attention in the fields of mobile robots, intelligent video surveillance, and the like. How to clean the anomalous trajectories hidden in the massive data has become one of the research hotspots. Anomalous trajectories should be detected and cleaned before the trajectory data can be effectively used. In this article, a Trajectory Evaluator by Sub-tracks (TES) for detecting VOT-based anomalous trajectory is proposed. Feature of Anomalousness is defined and described as the Eigenvector of classifier to filter Track Lets anomalous trajectory and IDentity Switch anomalous trajectory, which includes Feature of Anomalous Pose and Feature of Anomalous Sub-tracks (FAS). In the comparative experiments, TES achieves better results on different scenes than state-of-the-art methods. Moreover, FAS makes better performance than point flow, least square method fitting and Chebyshev Polynomial Fitting. It is verified that TES is more accurate and effective and is conducive to the sub-tracks trajectory data analysis.

scholarly journals Evaluation of extreme wave probability on the basis of long-term data analysis

2018 ◽  
Author(s):  
Kirill Bulgakov ◽  
Vadim Kuzmin ◽  
Shilov Dmitry
Keyword(s):  
Data Analysis ◽  
Wave Height ◽  
Significant Wave Height ◽  
Extreme Wave ◽  
Method Of Calculation ◽  
Significant Wave ◽  
Wave Heights ◽  
Term Data

Abstract. A method of calculation of wave height probability based on the significant wave height probability is described. An application of the method on the basis of long-term data analysis is presented. Examples of averaged annual and seasonal fields of extreme wave heights obtained by the above method are given.

scholarly journals Numerical modeling and experimental testing analysis of Assembled Rubber Metal Isolator

2020 ◽  
Vol 103 (3) ◽  
pp. 003685042095698
Author(s):  
Jida Wu ◽  
Chusheng Liu ◽  
Haishen Jiang ◽  
Zhenqian Wang
Keyword(s):  
Numerical Modeling ◽  
Experimental Testing ◽  
Structural Characteristics ◽  
Constitutive Models ◽  
Least Square Method ◽  
Maximum Error ◽  
Least Square ◽  
Maximum Relative Error ◽  
Empirical Formulas ◽  
Compression Process

In order to analyze the stiffness characteristics of Assembled Rubber Metal Isolator (ARMI) more accurately, the present work elaborates on the detailed numerical modeling and analysis process of the ARMI, considering prestressing condition. By comparing the applicability of different constitutive models, the reasonable parameters of the proposed Money-Revlon constitutive model were determined by rubber compression test and least square method. Considering the structural characteristics and complex constraints of the isolator, a step-by-step analysis method is described, based on the rigid-flexible coupling theory and the contact cutting algorithm. The full Newton-Raphson algorithm is used to simulate the mechanical behavior of elastic components in ARMI, during the whole compression-torsion deformation process, while the results are verified by theoretical calculation and practical experiments, respectively. For the assembly process, the maximum relative error between numerical results and empirical formulas is 3.97%. The derived torsional curve, under the simulated pre-stress conditions, is in good agreement with the experimental results, and the maximum error is less than 8.43%. The achieved accuracy is significantly improved, compared to the existing simulation model that does not consider the pre-compression process. The proposed approach provides an effective method for the analysis of same type vibration isolator.

Nonlinear Deepwater Extreme Wave Height and Modulation Wave Length Relation

2018 ◽  
Author(s):  
Ali Mohtat ◽  
Solomon C. Yim ◽  
Alfred R. Osborne ◽  
Ming Chen
Keyword(s):  
Probability Distribution ◽  
Modulational Instability ◽  
Wave Train ◽  
Wave Length ◽  
Distribution Functions ◽  
Unstable Wave ◽  
Order Effects ◽  
Linear Wave ◽  
Extreme Wave ◽  
Wave Heights

Prediction of extreme wave heights has always been a challenge in both the naval and energy industries. The survivability and safe operation and design of marine vehicles and devices are highly dependent on the probability distribution of the wave heights of extreme waves. In traditional linear approaches, researchers use various probability distribution functions mostly generated from field measurements and are usually modified with some statistical methods to account for the distribution of wave heights. These approaches do not take into account nonlinearity and instability in wave train behavior and solely relies on linear wave theory assumptions and perhaps some second order effects in more advanced probability models. This study emphasizes the application of modulation wavelengths and periods, resulting from modulational instability analysis of the nonlinear Schrödinger equation (NLS). In this study, state-of-the-art nonlinear Fourier analysis (NLFA) based on NLS is employed to calculate the unstable wave components. The resulting rise time and travel distance for such unstable modes and their maximum possible growth amplitudes are used to derive a range of probable occurrences. Numerical simulation results from CFD computations are used to examine the capability of such an approach in predicting the magnitude and location of extreme wave occurrence. It is shown that application of the proposed NLS-based analytical procedure enables a more accurate prediction of the extreme wave field.

Online Measurement Experiment and Data Analysis of the Slideway Straightness Motion Error for CMM

2014 ◽  
Vol 529 ◽  
pp. 329-333
Author(s):  
Fei Fei Wang ◽  
Wei Ming He
Keyword(s):  
Data Analysis ◽  
Coordinate Measuring Machine ◽  
Least Square Method ◽  
Least Square ◽  
Online Measurement ◽  
Motion Error ◽  
Means Of Measurement ◽  
Measurement Experiment ◽  
Measuring Machine ◽  
Straightness Error

The paper introduces the principle of the sequential two points (STP) method, using the error separation technique to isolate slideway straightness error and workpiece straightness error, by means of measurement and data analysis to study the slideway straightness error. Using least square method for fitting to improve the accuracy of three coordinate measuring machine. Last to assess and maintain the accuracy of the measurement machine.

scholarly journals Uncertainties of Estimating Extreme Significant Wave Height for Engineering Applications Depending on the Approach and Fitting Technique—Adriatic Sea Case Study

2020 ◽  
Vol 8 (4) ◽  
pp. 259 ◽  
Author(s):  
Marko Katalinić ◽  
Joško Parunov
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Adriatic Sea ◽  
Least Square Method ◽  
Initial Distribution ◽  
Least Square ◽  
Likelihood Method ◽  
Extreme Wave ◽  
Significant Wave

Studies on the extrapolation of extreme significant wave height, based on long-term databases, are extensively covered in literature. An engineer, working in the field of naval architecture, marine engineering, or maritime operation planning, when tackling the problem of extreme wave prediction, would typically follow relevant codes and standards. Currently, authorities in the field of offshore operation within its guidelines propose several methods: the initial-distribution, extreme value, and peak-over threshold approaches. Furthermore, for each proposed method, different mathematical fitting techniques are applicable to optimize the candidate distribution parameters: the least-square method, the method of moments, and the maximum likelihood method. A comprehensive analysis was done to determine the difference in the results depending on the choice of method and fitting technique. All combinations were tested on a long-term database for a location in the Adriatic Sea. The variability of the results and trends of extreme wave height estimates for long return periods are presented, and the limitations of certain methods and techniques are noted.

scholarly journals Faktor-Faktor yang mempengaruhi Minat Wakaf Masyarakat di Kota Lhokseumawe

2019 ◽  
Vol 3 (2) ◽  
pp. 81
Author(s):  
Falahuddin Falahuddin ◽  
Fuadi Fuadi ◽  
Muhammad Rizki Ramadhan
Keyword(s):  
Data Analysis ◽  
Least Square Method ◽  
Least Square ◽  
Primary Data ◽  
Test Results ◽  
Analysis Method ◽  
Religious Knowledge ◽  
Ordinary Least Square ◽  
Insignificant Effect ◽  
Community Interest

This research is to find out the factors that influence the community Waqf Interest in Lhokseumawe City. The data used are primary data with a sample of 100 respondents. The data analysis method uses multiple linear regression with OLS (Ordinary Least Square) method. The results showed that community religious knowledge had a positive and not significant effect on waqf interest in Lhokseumawe. Perception of Waqf has a positive and insignificant effect on community Waqf Interest in Lhokseumawe City, and Revenue has a positive and insignificant effect on Waqf Community Interest in Lhokseumawe City. The determination test results used were 4%. Keywords: Wakaf Interests, Religiosity Knowledge, Wakif Perception, Income.

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