scholarly journals Elevation Calculation of Bottom Deck Based on Stochastic Process and Compound Distribution

2021 ◽  
Vol 9 (7) ◽  
pp. 697
Author(s):  
Guilin Liu ◽  
Chi Nie ◽  
Yi Kou ◽  
Yi Yang ◽  
Daniel Zhao ◽  
...  
Keyword(s):  
Wave Height ◽  
Measured Data ◽  
American Petroleum Institute ◽  
Return Level ◽  
Statistical Characteristics ◽  
Distribution Model ◽  
Offshore Platforms ◽  
Type Distribution ◽  
New Model ◽  
Compound Distribution

In the design of offshore platforms, the height of the bottom deck directly affects the safety and engineering cost of the entire platform. It is a very important scale parameter in platform planning. The American Petroleum Institute (API) specification shows that the key to determining the height of the bottom deck lies in the wave height and calculation of the return level of the water increase. Based on the perspective of stochastic processes, this paper constructs a new distribution function model for joint parameter estimation of the marine environment. The new model uses a family of random variables to show the statistical characteristics of design wave height and water increase in both time and space, with extreme value expanded EED-I type distribution used as marginal distribution. The new model performs statistical analysis on the measured hydrological data of the Naozhou Station during the flood period from 1990 to 2016. The Gumbel–Copula structure function is used as the connection function, and the compound distribution model of the wave height and the water increase is used to obtain the joint return level of the wave height and the water increase and through which the bottom deck height of the area is calculated. The results show that the stochastic compound distribution improves the issue of the high design value caused by simple superposition of univariate return levels. The EED-I type distribution still has good stability under the condition of less measured data. Thus, under the premise of ensuring the safety of the offshore platform, less measured data can still be used to calculate the height of the bottom deck more accurately.

scholarly journals Design Wave Height Parameter Estimation Model Reflecting the Influence of Typhoon Time and Space

2021 ◽  
Vol 9 (9) ◽  
pp. 950
Author(s):  
Guilin Liu ◽  
Pengfei Xu ◽  
Yi Kou ◽  
Fang Wu ◽  
Yi Yang ◽  
...  
Keyword(s):  
Storm Surge ◽  
Wave Height ◽  
Estimation Method ◽  
Coastal Areas ◽  
Return Level ◽  
Distribution Model ◽  
Time And Space ◽  
New Model ◽  
Design Wave Height ◽  
Time Periods

Typhoon storm surge disasters are one of the main restrictive factors of sustainable development in coastal areas. They are one of several important tasks in disaster prevention and reduction in coastal areas and require reasonable and accurate calculations of wave height in typhoon-affected sea areas to predict and resist typhoon storm surge disasters. In this paper, the design wave height estimation method based on the stochastic process and the principle of maximum entropy are theoretically advanced, and it can provide a new idea as well as a new method for the estimation of the return level for marine environmental elements under the influence of extreme weather. The model uses a family of random variables to reflect the influence of a typhoon on wave height at different times and then displays the statistical characteristics of wave height in time and space. At the same time, under the constraints of the given observations, the maximum uncertainty of the unobtainable data is maintained. The new model covers the compound extreme value distribution model that has been widely used and overcomes the subjective interference of the artificially selected distribution function—to a certain extent. Taking the typhoon wave height data of Naozhou Observatory as an example, this paper analyzes the probability of typhoon occurrence frequency at different times and the characteristics of typhoon intensity in different time periods. We then calculate the wave height return level and compare it with traditional calculation models. The calculation results show that the new model takes into account the time factor and the interaction between adjacent time periods. Furthermore, it reduces the subjective human interference, so the calculated results of the typhoon’s influence on wave height return level are more stable and accurate.

scholarly journals Wave Height Distributions and Rogue Waves in the Eastern Mediterranean

2021 ◽  
Vol 9 (6) ◽  
pp. 660
Author(s):  
Sagi Knobler ◽  
Daniel Bar ◽  
Rotem Cohen ◽  
Dan Liberzon
Keyword(s):  
Wave Height ◽  
Eastern Mediterranean ◽  
Rogue Waves ◽  
Distribution Model ◽  
Storm Events ◽  
Order Model ◽  
Deep Seawater ◽  
Wave Heights ◽  
Storm Characteristics ◽  
Buoy Data

There is a lack of scientific knowledge about the physical sea characteristics of the eastern part of the Mediterranean Sea. The current work offers a comprehensive view of wave fields in southern Israel waters covering a period between January 2017 and June 2018. The analyzed data were collected by a meteorological buoy providing wind and waves parameters. As expected for this area, the strongest storm events occurred throughout October–April. In this paper, we analyze the buoy data following two main objectives—identifying the most appropriate statistical distribution model and examining wave data in search of rogue wave presence. The objectives were accomplished by comparing a number of models suitable for deep seawater waves. The Tayfun—Fedele 3rd order model showed the best agreement with the tail of the empirical wave heights distribution. Examination of different statistical thresholds for the identification of rogue waves resulted in the detection of 99 unique waves, all of relatively low height, except for one wave that reached 12.2 m in height which was detected during a powerful January 2018 storm. Characteristics of the detected rogue waves were examined, revealing the majority of them presenting crest to trough symmetry. This finding calls for a reevaluation of the crest amplitude being equal to or above 1.25 the significant wave height threshold which assumes rogue waves carry most of their energy in the crest.

scholarly journals Wave energy dissipation in the mangrove vegetation off Mumbai, India

2017 ◽  
Author(s):  
Samiksha S. Volvaiker ◽  
Ponnumony Vethamony ◽  
Prasad K. Bhaskaran ◽  
Premanand Pednekar ◽  
MHamsa Jishad ◽  
...  
Keyword(s):  
Energy Dissipation ◽  
Drag Coefficient ◽  
Wave Height ◽  
Wave Attenuation ◽  
Coastal Region ◽  
Measured Data ◽  
Vegetation Density ◽  
Mangrove Vegetation ◽  
Wave Height Attenuation ◽  
Set Up

Abstract. Coastal regions of India are prone to sea level rise, cyclones, storm surges and human induced activities, resulting in flood, erosion, and inundation. The primary aim of the study is to estimate wave attenuation by mangrove vegetation using SWAN model in standalone mode, as well as SWAN nested with WW3 model for the Mumbai coastal region. To substantiate the model results, wave measurements were carried out during 5–8 August 2015 at 3 locations in a transect normal to the coast using surface mounted pressure level sensors under spring tide conditions. The measured data presents wave height attenuation of the order of 52 %. The study shows a linear relationship between wave height attenuation and gradual changes in water level in the nearshore region, in phase with the tides. Model set-up and sensitivity analyses were conducted to understand the model performance to vegetation parameters. It was observed that wave attenuation increased with an increase in drag coefficient (Cd), vegetation density, and stem diameter. For a typical set-up for Mumbai coastal region having vegetation density of 0.175 per m2, stem diameter of 0.3 m and drag coefficient varying from 0.4 to 1.5, the model reproduced attenuation, ranging from 49 to 55 %, which matches well with the measured data. Spectral analysis performed for the cases with and without vegetation very clearly portrays energy dissipation in the vegetation area as well as spectral changes. This study has the potential of improving the quality of wave prediction in vegetation areas, especially during monsoon season and extreme weather events.

Development of Operational Limit Diagrams for Offshore Lifting Procedures

2015 ◽  
Author(s):  
Leonardo Roncetti ◽  
Fabrício Nogueira Corrêa ◽  
Carl Horst Albrecht ◽  
Breno Pinheiro Jacob
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Technological Development ◽  
Automatic Generation ◽  
Dynamic Responses ◽  
Offshore Platforms ◽  
Peak Period ◽  
Significant Wave ◽  
Wave Heights ◽  
Offshore Crane

Lifting operations with offshore cranes are fundamental for proper functioning of a platform. Despite the great technological development, offshore cranes load charts only consider the significant wave height as parameter of environmental load, neglecting wave period, which may lead to unsafe or overestimated lifting operations. This paper aims to develop a method to design offshore crane operational limit diagrams for lifting of personnel and usual loads, in function of significant wave height and wave peak period, using time domain dynamic analysis, for a crane installed on a floating unit. The lifting of personnel with crane to transfer between a floating unit and a support vessel is a very used option in offshore operations, and this is in many cases, the only alternative beyond the helicopter. Due to recent fatal accidents with lifting operations in offshore platforms, it is essential the study about this subject, contributing to the increase of safety. The sea states for analysis were chosen covering usual significant wave heights and peak periods limits for lifting operations. The methodology used the SITUA / Prosim software to obtain the dynamic responses of the personnel transfer basket lifting and container loads on a typical FPSO. Through program developed by the author, it was implemented the automatic generation of diagrams as a function of operational limits. It is concluded that using this methodology, it is possible to achieve greater efficiency in the design and execution of personnel and routine load lifting, increasing safety and a wider weather window available.

scholarly journals Application to Engineering and Medical Data Using Three-Parameter Exponential Model

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Waleed Almutiry ◽  
Amani Abdullah Alahmadi ◽  
Ibrahim Elbatal ◽  
Ibrahim E. Ragab ◽  
Oluwafemi Samson Balogun ◽  
...  
Keyword(s):  
Simulation Analysis ◽  
Residual Life ◽  
Quantile Function ◽  
Exponential Model ◽  
Statistical Characteristics ◽  
Mean Residual Life ◽  
New Model ◽  
Conditional Moments ◽  
Mean Inactivity Time ◽  
Real World Datasets

This paper is devoted to a new lifetime distribution having three parameters by compound the exponential model and the transmuted Topp-Leone-G. The new proposed model is called the transmuted Topp-Leone exponential model; it is useful in lifetime data and reliability. The new model is very flexible; its pdf can be right skewness, unimodal, and decreasing shaped, but the hrf of the suggested model can be unimodal, constant, and decreasing. Numerous statistical characteristics of the new model, notably the quantile function, moments, incomplete moments, conditional moments, mean residual life, mean inactivity time, and entropy are produced and investigated. The system’s parameters are estimated using the maximum likelihood approach. All estimators should be theoretically convergent, which is supported by a simulation analysis. Finally, two real-world datasets from the engineering and medical disciplines explore the new model’s relevance and adaptability in comparison to the alternatives models such as the beta exponential, the Marshall–Olkin generalized exponential, the exponentiated Weibull, the modified Weibull, and the transmuted Burr type X models.

scholarly journals Estimation of Contaminants for Direct Imaging of Exoplanets: Constraint on the Stellar Distribution Model with both NIR and Deep Imaging Data

2013 ◽  
Vol 8 (S299) ◽  
pp. 42-43
Author(s):  
Mihoko Konishi ◽  
Hiroshi Shibai ◽  
Taro Matsuo ◽  
Kodai Yamamoto ◽  
Jun Sudo ◽  
...  
Keyword(s):  
Point Sources ◽  
Distribution Model ◽  
Model Parameters ◽  
Imaging Data ◽  
Direct Imaging ◽  
Distribution Models ◽  
New Model ◽  
Deep Imaging

AbstractThere are faint contaminants near primary stars in the direct imaging of exoplanets. Our goal is to estimate statistically the ratio of exoplanets in the detected batch of point sources by calculating the fraction of contamination. In this study, we compared the detected number of stars with the number of contaminants predicted by our model. We found that the observed number of faint stars were fewer than the predicted results towards the Pleiades and GOODS-South field when the parameters of the conventional stellar distribution models were employed. We thus estimated new model parameters in correspondence to the results of the observations.

Analysing the correlation between vehicle responses and track irregularities using dynamic simulations and measurements

2019 ◽  
Vol 234 (2) ◽  
pp. 170-182 ◽  
Author(s):  
Tomas Karis ◽  
Mats Berg ◽  
Sebastian Stichel
Keyword(s):  
Simulated Data ◽  
Measured Data ◽  
Statistical Characteristics ◽  
Acceptance Testing ◽  
Dynamic Simulations ◽  
Track Maintenance ◽  
Track Stiffness ◽  
Suspension Stiffness ◽  
Unsprung Mass ◽  
Track Irregularities

Track irregularities play a key role in vehicle response, but it is not uncommon to find irregularities with similar statistical characteristics giving very different vehicle behaviour. It is therefore important to find a consistent way of describing track irregularities, which better matches the vehicle behaviour to facilitate an efficient track maintenance and vehicle acceptance testing. Various proposals have been made to resolve this issue, although with limited success. In the present paper, a methodology to break down the track–vehicle interaction into steps, by analysing the irregularity–response correlation in detail, is applied to both the measured and simulated data of a passenger coach. The results show a very good agreement and a high correlation coefficient between the vertical axle box acceleration and the second spatial derivative of the vertical track irregularities when analysing the simulated data, but not for the measured data. Parameter variations are carried out through simulations, in which the vertical track stiffness, vehicle unsprung mass, vertical primary suspension and different combinations of track irregularities are varied. The results show that track stiffness mainly affects the axle box acceleration whereas the primary vertical suspension stiffness and unsprung mass predominantly affect the vertical wheel–rail forces. Therefore, it is important to understand the influence of track stiffness, especially with the help of the measured data, and the methods that reduce its influence should be investigated in future works.

scholarly journals A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Huashan Li ◽  
Fei Cao ◽  
Xianlong Wang ◽  
Weibin Ma
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Statistical Error ◽  
Global Solar Radiation ◽  
Measured Data ◽  
Temperature Data ◽  
New Model ◽  
Climatic Regions ◽  
Monthly Average ◽  
Temperature Records

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China.

Forecasting Marine and Structural Integrity Parameters for Offshore Platforms

2015 ◽  
Author(s):  
Igor Prislin ◽  
Reza Jafarkhani ◽  
Soma Maroju
Keyword(s):  
Machine Learning ◽  
Data Management ◽  
Structural Integrity ◽  
Operational Risk ◽  
Computer Programs ◽  
Measured Data ◽  
Offshore Platforms ◽  
Integrity Monitoring ◽  
Design Values ◽  
Paper Address

Marine and structural integrity monitoring for offshore platforms is the cornerstone for managing operational risk and safety. Measuring platform responses and loads enables comparisons with design values thus ensuring that the risk does not exceed the designed limits. This paper discusses an advanced data management that is based on machine learning, a set of specialized computer programs that can learn and generalize the platform responses from measured data. The programs should produce sufficiently accurate predictions in previously unseen cases. Examples provided in the paper address capabilities for forecasting the marine and structural integrity parameters.

scholarly journals Reliability and robustness of rainfall compound distribution model based on weather pattern sub-sampling

2010 ◽  
Vol 7 (5) ◽  
pp. 6757-6792
Author(s):  
F. Garavaglia ◽  
M. Lang ◽  
E. Paquet ◽  
J. Gailhard ◽  
R. Garçon ◽  
...  
Keyword(s):  
Probabilistic Method ◽  
Extreme Rainfall ◽  
Distribution Model ◽  
Data Series ◽  
Hydrological Simulation ◽  
Data Set ◽  
Weather Pattern ◽  
Pareto Distributions ◽  
Compound Distribution ◽  
Reliability And Robustness

Abstract. Design floods for EDF (Électricité de France, French electricity company) dam spillways are now computed using a probabilistic method named SCHADEX (Climatic-Hydrological Simulation of Extreme Floods) based on an extreme rainfall model named the MEWP (Multi Exponential Weather Pattern) distribution. This probabilistic model provides estimates of extreme rainfall quantiles using a mixture of exponential distributions. Each exponential distribution applies to a specific sub-sample of rainfall observations, corresponding to one of eight typical atmospheric circulation patterns that are relevant for France and the surrounding area. The aim of this paper is to validate the MEWP model by assessing its reliability and robustness with rainfall data from France, Spain and Switzerland. Data include 37 long series for the period 1904–2003, and a regional data set of 478 rain gauges for the period 1954–2005. Two complementary properties are investigated: (i) the reliability of estimates, i.e. the agreement between the estimated probabilities of exceedance and the actual exceedances observed on the dataset; (ii) the robustness of extreme quantiles and associated confidence intervals, assessed using various sub-samples of the long data series. New specific criteria are proposed to quantify reliability and robustness.The MEWP model is compared to standard models (seasonalised Generalised Extreme Value and Generalised Pareto distributions). In order to evaluate the suitability of the exponential model used for each weather pattern (WP), a general case of the MEWP distribution, using Generalized Pareto distributions for each WP, is also considered. Concerning the considered dataset, the exponential hypothesis of asymptotic behaviour of each seasonal and weather pattern rainfall records, appears to be reasonable. The results highlight: (i) the interest of WP sub-sampling that lead to significant improvement in reliability models performances; (ii) the low level of robustness of the models based on at-site estimation of shape parameter; (iii) the MEWP distribution proved to be robust and reliable, demonstrating the interest of the proposed approach.

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