Statistical analysis of sloshing-induced random impact pressures

Abstract

This article presents the statistical analysis of sloshing-induced random impact pressure. To obtain the pressure signal, three-dimensional sloshing model tests were conducted at two different filling depths. Several different methods were applied to identify sloshing peaks and to define the rise and decay times of the peak pressure signals. Statistical properties acquired from these methods were compared, and their consistency and/or discrepancy were observed. In addition, 200-h duration test data were acquired by running forty 5-h tests under each test condition. Based on the long-duration test data, the uncertainty of the test results with respect to the test duration was studied using the bootstrap method.

Observation on sloshing flow and hydrodynamic pressures on cylindrical liquefied natural gas tank with swash bulkhead

“…Figure 5 shows the average of the 10 highest peak pressures to verify the validity of the experiments with 500 cycles. 18,19 The peak pressures are the normalized static pressure at the bottom of the fully loaded tank, where ρ, g, and H represent the fluid density, gravitational acceleration, and tank height, respectively. Figure 5 shows a case where the pitch motion amplitude was 6° and the excitation frequency ratio was 0.894 at the 0.70 H filling height condition.…”

Outlier analysis of sloshing impact loads on liquid ship cargo

“…It is well known that such kind of deviations are not due to the physical error but is not the physical error but rarely occurring event due to insufficient simulation time. 13,14,16 The proposed fitting outlier analysis which will be explained bellows, can helps to produce an analysis result similar to that of a longer experiment even with relatively short experimental data. In order to perform fitting outlier analysis, it is necessary to assume that the probability distribution of the peak values of the sloshing impacts can be expressed as particular extreme distribution function (three-parameter Weibull distribution function in this study).…”

“…12 Furthermore, either short-term or long-term model test is suggested, according to our experiment, the recommended minimum time for model test seems significantly lower than the time for convergent pressure prediction. [13][14][15][16] This paper introduces an outlier analysis method, which can improve the convergence through the statistical analysis of experimental values lacking convergence, and is based on the doctoral thesis of Kim 17 and also extending the study of Kim and Kim. 18 In this study, a new method is proposed to detect and treat anomalies in the sloshing model experiment data.…”

Study on tank shape for sloshing assessment of LNG vessels under unrestricted filling operation

“…Here, x should be larger than the location parameter d. The method of moments was applied to estimate these three parameters; the first three model moments, mean (l), variance (r 2 ), and skewness (c 1 ) were matched with the corresponding sample moments [16].…”