Enhanced Chemical Dispersion Using the Propeller Wash from Response Vessels

2008 ◽  
pp. 67-67
Author(s):  
T. Nedwed ◽  
W. Spring
Keyword(s):  
Chemical Dispersion

Removal of Downhole Strontium Sulphate Scales By Chemical Dispersion Technique

1998 ◽  
Author(s):  
A.P. Maithani ◽  
A.K. Sah ◽  
Ramashish Rai ◽  
Gyan Singh
Keyword(s):  
Chemical Dispersion ◽  
Dispersion Technique

scholarly journals Low‐temperature oxidation of metal nanoparticles obtained by chemical dispersion

2020 ◽  
Vol 15 (7) ◽  
pp. 461-464 ◽  
Author(s):  
Ella L. Dzidziguri ◽  
Elena N. Sidorova ◽  
Jansaya E. Yahiyaeva ◽  
Dmitriy Yu. Ozherelkov ◽  
Alexander A. Gromov ◽  
...  
Keyword(s):  
Low Temperature ◽  
Metal Nanoparticles ◽  
Low Temperature Oxidation ◽  
Temperature Oxidation ◽  
Chemical Dispersion

scholarly journals Development of an Algorithm for Chemically Dispersed Oil Spills

2020 ◽  
Vol 7 ◽  
Author(s):  
Merv F. Fingas ◽  
Kaan Yetilmezsoy ◽  
Majid Bahramian
Keyword(s):  
Wind Speed ◽  
Water Column ◽  
Oil Spills ◽  
Regression Equations ◽  
Oil Viscosity ◽  
Mixing Depth ◽  
Chemical Dispersion ◽  
Closed Form Solutions ◽  
Dispersed Oil ◽  
Chemically Dispersed Oil

An algorithm utilizing four basic processes was described for chemical oil spill dispersion. Initial dispersion was calculated using a modified Delvigne equation adjusted to chemical dispersion, then the dispersion was distributed over the mixing depth, as predicted by the wave height. Then the droplets rise to the surface according to Stokes’ law. Oil on the surface, from the rising oil and that undispersed, is re-dispersed. The droplets in the water column are subject to coalescence as governed by the Smoluchowski equation. A loss is invoked to account for the production of small droplets that rise slowly and are not re-integrated with the main surface slick. The droplets become less dispersible as time proceeds because of increased viscosity through weathering, and by increased droplet size by coalescence. These droplets rise faster as time progresses because of the increased size. Closed form solutions were provided to allow practical limits of dispersibility given inputs of oil viscosity and wind speed. Discrete solutions were given to calculate the amount of oil in the water column at specified points of time. Regression equations were provided to estimate oil in the water column at a given time with the wind speed and oil viscosity. The models indicated that the most important factor related to the amount of dispersion, was the mixing depth of the sea as predicted from wind speed. The second most important factor was the viscosity of the starting oil. The algorithm predicted the maximum viscosity that would be dispersed given wind conditions. Simplified prediction equations were created using regression.

Evaluating crude oil chemical dispersion efficacy in a flow-through wave tank under regular non-breaking wave and breaking wave conditions

2009 ◽  
Vol 58 (5) ◽  
pp. 735-744 ◽  
Author(s):  
Zhengkai Li ◽  
Kenneth Lee ◽  
Thomas King ◽  
Michel C. Boufadel ◽  
Albert D. Venosa
Keyword(s):  
Crude Oil ◽  
Breaking Wave ◽  
Wave Tank ◽  
Chemical Dispersion ◽  
Flow Through ◽  
Wave Conditions

Selection of Chemical Hazard Prediction Models for Plant Safety and Control Room Habitability Evaluations

2013 ◽  
Author(s):  
Mary C. Richmond ◽  
Ping K. Wan ◽  
Brady P. Dague ◽  
Kyra W. Davis
Keyword(s):  
Model Selection ◽  
Prediction Models ◽  
Dispersion Model ◽  
The United States ◽  
Cloud Formation ◽  
Chemical Dispersion ◽  
Chemical Release ◽  
Design Basis ◽  
The Impact ◽  
Selection Of

Assuring the protection of people and the environment from unnecessary exposure to radiation is of great concern to nuclear electric power generators and regulators. In order to secure and maintain a license for operation of a nuclear power plant in the United States, the applicant is required to assess postulated scenarios to determine if an accidental chemical release either onsite or offsite will result in a design-basis event. When determining design-basis events, accident categories such as fire, explosion and/or toxic vapor cloud formation are considered. Evaluations must consider whether the postulated accidental chemical release will result in operator impairment or damage to safety related structures, systems or components (SSCs), either of which may prevent safe shutdown of the nuclear plant. A critical step in performing such safety evaluations is selection of an appropriate model which will most closely reflect the behavior of a chemical release in the scenario under consideration. Many chemical dispersion models are available for use in safety evaluations for accidental chemical releases; however, it is imperative that the model selected be appropriate for the postulated release conditions. Model selection should be based on careful evaluation of factors such as release location, meteorological conditions, terrain, chemical inventory and storage conditions, as well as the physical and chemical properties of the chemical under consideration in the postulated release. Failure to select a model suitable for the conditions under which the chemical is released or to appropriately evaluate the physical properties of the chemical and the corresponding limitations of the model may result in underpredicting or overpredicting the impact of a fire, explosion or toxic chemical release. Underpredicting could leave the facility susceptible to damage of safety related SSCs or lead to operator impairment both of which may affect the ability of the plant to safely operate following an accident. While overpredicting the impacts could lead to unnecessary and costly overdesign. This paper will address the considerations that must be evaluated when selecting a chemical dispersion model and will illustrate the importance of model selection in performing nuclear safety evaluations through examples and case studies.

Application of entropy analysis of in situ droplet-size spectra in evaluation of oil chemical dispersion efficacy

2011 ◽  
Vol 62 (10) ◽  
pp. 2129-2136 ◽  
Author(s):  
Zhengkai Li ◽  
Kenneth Lee ◽  
Thomas King ◽  
Haibo Niu ◽  
Michel C. Boufadel ◽  
...  
Keyword(s):  
Droplet Size ◽  
Entropy Analysis ◽  
Size Spectra ◽  
Chemical Dispersion
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