Application of the probability density functional in the description of random wave processes

1977 ◽  
Vol 20 (4) ◽  
pp. 366-373
Author(s):  
Yu. N. Makov ◽  
R. V. Khokhlov
Keyword(s):  
Probability Density ◽  
Density Functional ◽  
Random Wave ◽  
Wave Processes ◽  
Probability Density Functional

Relation between mechanism of soil removal from fabrics and a parameter derived from probability density functional method for washing force analysis

2018 ◽  
Vol 89 (11) ◽  
pp. 2236-2246 ◽  
Author(s):  
Masaru Oya
Keyword(s):  
Probability Density ◽  
Density Functional ◽  
Soil Removal ◽  
Density Functional Method ◽  
Functional Method ◽  
Water Soluble ◽  
Oily Soil ◽  
Force Analysis ◽  
Removal Mechanisms ◽  
Probability Density Functional

The probability density functional method is one of the washing force analysis methods that combines the classical kinetic analysis of detergency method and risk calculation method using probability density function. This paper discusses the relation between soil removal mechanisms and the value of σ rl, which is one of the two parameters used in the probability density functional method. Four repetitive washing tests were conducted using test fabrics soiled with iron(III) oxide, carbon black, four kinds of water-soluble dyes and three kinds of oily dyes, and the removal (%) was analyzed with the probability density functional method. The results show that the range of σ rl varied with removal mechanisms; mechanical removal of particle soil (0.01–0.6), dissolution into water of water-soluble soil (0.3–1.4), solubilization of oily soil into surfactant micelle (1.0–2.0) and emulsification or dispersion of oily soil (≥3.0). This tendency can be used for estimating the removal mechanism of any washing system where the soil type is unknown.

scholarly journals Kinetic analysis of hemoglobin detergency by probability density functional method

PLoS ONE ◽  
2020 ◽  
Vol 15 (8) ◽  
pp. e0237255
Author(s):  
Miyako Oya ◽  
Yosuke Taniguchi ◽  
Naoaki Fujimura ◽  
Karen Miyamoto ◽  
Masaru Oya
Keyword(s):  
Kinetic Analysis ◽  
Probability Density ◽  
Density Functional ◽  
Density Functional Method ◽  
Functional Method ◽  
Probability Density Functional

Investigation on the Probabilistic Distribution of the Stress Range of Net Cage Floater of Fish Cage for Fatigue Life Prediction

2018 ◽  
Author(s):  
Xiao-Dong Bai ◽  
Yun-Peng Zhao ◽  
Guo-Hai Dong ◽  
Chun-Wei Bi
Keyword(s):  
Fatigue Life ◽  
Probability Density ◽  
Limit State ◽  
Frequency Domain Analysis ◽  
Random Wave ◽  
Stress Range ◽  
Fish Farms ◽  
Short Term ◽  
Element Analysis ◽  
Distribution Of Stress

The failure risk of fish cages has increased in the harsher environmental conditions as fish farms have moved into the open sea in recent years. Fatigue failure is an important limit state for the floating system of the fish cage under the long-term action of waves. This study is presented to investigate the applicable probability density function for estimating fatigue life of the high-density polyethylene (HDPE) floating collars. The stress response of the floating collars system in random wave is firstly analyzed based on the finite element analysis combined with a hydrodynamic model. The stress histories of floating collars under each sea state are counted using the rainflow method as a benchmark for fatigue frequency domain analysis. The distribution of stress range was fitted by various probability density functions including Rayleigh, Weibull, Gamma and generalized extreme value (GEV) distributions. Comparisons of the estimated fatigue life using different distributions with rainflow statistic results were performed. Results indicate fatigue estimation based on the GEV and Gamma distributions by removing the negligible low stress range give much more accurate fatigue damage results of the short-term stress range distribution. While Weibull distribution overestimates the fatigue lifetime of the floating collar based on the short-term distribution of stress ranges.

Sign in / Sign up

Export Citation Format

Share Document