scholarly journals Calculation of Joint Return Period for Connected Edge Data

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 300 ◽  
Author(s):  
Guilin Liu ◽  
Baiyu Chen ◽  
Zhikang Gao ◽  
Hanliang Fu ◽  
Song Jiang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Correlation Analysis ◽  
Wave Height ◽  
Joint Distribution ◽  
Measured Data ◽  
Two Dimensional ◽  
Ocean Engineering ◽  
Extreme Wave ◽  
Correlation Measure ◽  
Copula Functions

For better displaying the statistical properties of measured data, it is particularly important to select a suitable multivariate joint distribution model in ocean engineering. According to the characteristics and properties of Copula functions and the correlation analysis of measured data, the nonlinear relationship between random variables can be captured. Additionally, the models based on the Copula theory have more general applicability. A series of correlation measure index, derived from Copula functions, can expand the correlation measure range among variables. In this paper, by means of the correlation analysis between the annual extreme wave height and the corresponding wind speed, their joint distribution models were studied. The newly established two-dimensional joint distribution functions of the extreme wave height and the corresponding wind speed were compared with the existing two-dimensional joint distributions.

scholarly journals Double Entropy Joint Distribution Function and Its Application in Calculation of Design Wave Height

Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 64 ◽  
Author(s):  
Guilin Liu ◽  
Baiyu Chen ◽  
Song Jiang ◽  
Hanliang Fu ◽  
Liping Wang ◽  
...  
Keyword(s):  
Distribution Function ◽  
Maximum Entropy ◽  
Wave Height ◽  
Joint Distribution ◽  
Height Function ◽  
Copula Function ◽  
Wave Period ◽  
Ocean Engineering ◽  
Joint Distribution Function ◽  
Design Wave Height

Wave height and wave period are important oceanic environmental factors that are used to describe the randomness of a wave. Within the field of ocean engineering, the calculation of design wave height is of great significance. In this paper, a periodic maximum entropy distribution function with four undetermined parameters is derived by means of coordinate transformation and solving conditional variational problems. A double entropy joint distribution function of wave height and wave period is also derived. The function is derived from the maximum entropy wave height function and the maximum entropy periodic function, with the help of structures of the Copula function. The double entropy joint distribution function of wave height and wave period is not limited by weak nonlinearity, nor by normal stochastic process and narrow spectrum. Besides, it can fit the observed data more carefully and be more widely applicable to nonlinear waves in various cases, owing to the many undetermined parameters it contains. The engineering cases show that the recurrence level derived from the double entropy joint distribution function is higher than that from the extreme value distribution using the single variables of wave height or wave period. It is also higher than that from the traditional joint distribution function of wave height and wave period.

Global Trends in Extreme Wind Speed and Wave Height

2013 ◽  
Author(s):  
I. R. Young ◽  
S. Zieger ◽  
J. Vinoth ◽  
A. V. Babanin
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Global Climate ◽  
Extreme Value ◽  
Global Perspective ◽  
Ocean Engineering ◽  
Change Analysis ◽  
Data Set ◽  
Wind Speeds ◽  
Extreme Wind

Satellite observations of the ocean surface provide a powerful method for acquiring global data on wind speed and wave height. Radar altimeters have now been in operation for more than 25 years, providing a reasonably long term data set with global coverage. This paper presents data from a fully calibrated and validated altimeter dataset. The dataset provides the basis for obtaining a global perspective of a number of parameters critical to ocean engineering design, ship operations and global climate change. Analysis of the data provides ocean climatology of mean monthly values of wind speed and wave height useful for ship operations. The data set is also sufficiently long to provide extreme value (i.e. 100-year return period) estimates of wind speed and wave height. The paper presents such values and describes the approaches most appropriate to obtain statistically significant extreme value estimates from such satellite data. With a data set of this length, it is possible to investigate whether there have been statistically significant changes in the wind and wave climates over the period. Careful trend analysis of the extensive data set shows that there has been a statistically significant increasing trend in mean wind speed over the period. The corresponding increase in wave height is less clear. There is also evidence to suggest that extreme wind speeds and wave heights are increasing and the data set is analysed to investigate these trends. The paper clearly shows the value of this dataset and its application to a range of engineering problems.

Global Hierarchical Models for Wind and Wave Contours: Physical Interpretations of the Dependence Functions

2020 ◽  
Author(s):  
Andreas F. Haselsteiner ◽  
Aljoscha Sander ◽  
Jan-Hendrik Ohlendorf ◽  
Klaus-Dieter Thoben
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Hierarchical Models ◽  
Significant Wave Height ◽  
Joint Distribution ◽  
Environmental Data ◽  
Contour Method ◽  
Dependence Function ◽  
Significant Wave ◽  
Estimated Parameters

Abstract Applications such as the design of offshore wind turbines requires the estimation of the joint distribution of variables like wind speed, wave height and wave period. The joint distribution can then be used, for example, to define design load cases using the environmental contour method. Often the joint distribution is described using so-called global hierarchical models. In these models, one variable is taken as independent and the other variables are modelled to be conditional on this variable using particular dependence functions. In this paper, we propose to use dependence functions that offer physical interpretation. We define a novel dependence function that describes how the median of the zero-up-crossing period increases with significant wave height and a novel dependence function that describes how the median significant wave height increases with wind speed. These dependence functions allow us to reason about the physical meaning, even when we extrapolate outside the range of a given sample of environmental data. In addition, we can analyze the estimated parameters of the dependence function to speculate which kind of sea dominates at a given site. We fitted statistical models with the proposed dependence functions to six datasets and analyzed the estimated parameters. Then we calculated environmental contours based on these estimated joint distributions. The environmental contours had physically reasonable shapes, even at areas that were outside the datasets that were used to fit the underlying distributions.

Design Parameter Estimation of Wave Height and Wind Speed With Bivariate Copulas

2013 ◽  
Author(s):  
Shanshan Tao ◽  
Sheng Dong ◽  
Yinghui Xu
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Random Variables ◽  
Joint Probability ◽  
Environmental Parameters ◽  
Gumbel Distribution ◽  
Bohai Bay ◽  
Base Shear ◽  
Extreme Wave ◽  
Probability Models

The data of annual extreme wave height and corresponding wind speed at a platform in Bohai Bay is hindcasted by a numerical model from 1970 to 1993. Common-used design probability distributions, such as Gumbel distribution, Weibull distribution, and lognormal distribution are applied to fit the data of extreme wave height and concomitant wind speed, respectively. Then the best-fitted marginal distributions of annual extreme wave height and wind speed can be selected. Bivariate normal copula and Frank copula are utilized to construct joint distribution of these two random variables. Based on empirical base shear equation of the on-site fixed jacket platform, the maximum base shear can be calculated under the same joint return period of the wave height and wind speed. The results show that the proposed joint probability models constructed by bivariate copulas result in lower the design environmental parameters because of the consideration of correlation between random variables. Eventually the investment cost of marginal oil fields could be relatively reduced.

scholarly journals THE PREDICTION OF EXTREME VALUE WIND SPEEDS AND WAVE HEIGHTS FROM SATELLITE DATA

2018 ◽  
pp. 1
Author(s):  
Alicia Takbash ◽  
Ian Young
Keyword(s):  
Wind Speed ◽  
Numerical Model ◽  
Wave Height ◽  
Satellite Data ◽  
Extreme Values ◽  
Essential Element ◽  
Extreme Value ◽  
Ocean Engineering ◽  
Wind Speeds

The prediction of extreme value (e.g. 1 in 100 year) estimates of wind speed and wave height is an essential element of coastal and ocean engineering design. Despite decades of research on the statistics of extreme values, the consistent limitation faced by practitioners is the requirement for a long (20 plus years) dataset at the location of interest. Long term insitu buoy deployments have started to provide useful records in some geographic locations. Long term numerical model hindcasts have also proved useful. However, buoy deployments are seldom at the location of interest and the accuracy of numerical model hindcasts more than 20 years in the past is questionable. This paper will investigate the use of long-term satellite data sets of wind speed and wave height to provide global estimates of extreme values.

scholarly journals Thermal Performance Analysis of Heat Collection Wall in High-Rise Building Based on the Measurement of Near-Wall Microclimate

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 2023
Author(s):  
Ruixin Li ◽  
Yiwan Zhao ◽  
Gaochong Lv ◽  
Weilin Li ◽  
Jiayin Zhu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Structural Design ◽  
Theoretical Basis ◽  
Thermal Process ◽  
Measured Data ◽  
Passive Heating ◽  
High Rise ◽  
And Performance ◽  
Wall Components ◽  
Near Wall

Near-wall microenvironment of a building refers to parameters such as wind speed, temperature, relative humidity, solar radiation near the building’s façade, etc. The distribution of these parameters on the building façade shows a certain variation based on changes in height. As a technology of passive heating and ventilation, the effectiveness of this application on heat collection wall is significantly affected by the near-wall microclimate, which is manifested by the differences, and rules of the thermal process of the components present at different elevations. To explore the feasibility and specificity of this application of heat collection wall in high-rise buildings, this study uses three typical high-rise buildings from Zhengzhou, China, as research buildings. Periodic measurements of the near-wall microclimate during winter and summer were carried out, and the changing rules of vertical and horizontal microclimate were discussed in detail. Later, by combining these measured data with numerical method, thermal process and performance of heat collection wall based on increasing altitude were quantitatively analyzed through numerical calculations, and the optimum scheme for heat collection wall components was summarized to provide a theoretical basis for the structural design of heat-collecting wall in high-rise buildings.

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