scholarly journals Effect of dissolved-gas concentration on bulk nanobubbles generation using ultrasonication

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jeong Il Lee ◽  
Byung-Seung Yim ◽  
Jong-Min Kim
Keyword(s):  
Surface Tension ◽  
Tensile Strength ◽  
Size Distribution ◽  
Ultrasonic Irradiation ◽  
Liquid Water ◽  
Bubble Growth ◽  
Nucleation And Growth ◽  
Dissolved Gas ◽  
Gas Concentration

Abstract In this study, the effects of dissolved-gas concentration in liquid water on the nucleation and growth of bubbles and nanobubble (NB) generation were investigated by measuring the concentration and size distribution of NBs. Three types of liquids with different dissolved-gas concentrations—undersaturated, saturated, and supersaturated deionized (DI) water—were prepared, and NBs were generated via ultrasonic irradiation. As the dissolved-gas concentration increased, a large number of bubbles with relatively large diameters (several tens of micrometers or more) were generated, but the NB concentration decreased. The surface tension decreased with an increase in the dissolved gas concentration, and thus, the tensile strength which required for bubble growth became lower. Therefore, there were barely any NBs in supersaturated conditions because of the accelerated nucleation and bubble growth.

Nucleation and Growth of Bubbles in Elastomers

1971 ◽  
Vol 44 (5) ◽  
pp. 1363-1379 ◽  
Author(s):  
Charles W. Stewart
Keyword(s):  
Surface Tension ◽  
Homogeneous Nucleation ◽  
Nucleation And Growth ◽  
Experimental Results ◽  
Dissolved Gas ◽  
Rate Of Growth ◽  
High Degree ◽  
Approximate Expressions ◽  
Temperature Surface

Abstract The theory of homogeneous nucleation of bubbles is combined with an expression, for their rate of growth in elastomers to obtain approximate expressions for calculating the number of bubbles formed under a high degree of supersaturation. Experimental results are given for several elastomers with argon as the dissolved gas under a variety of foaming conditions. The theory adequately describes the manner in which the number of bubbles formed depends on the temperature, surface tension of the polymer, and permeability of the dissolved gas.

The nucleation of cavities at grain boundaries

1987 ◽  
Vol 45 ◽  
pp. 288-291
Author(s):  
P. J. Goodhew
Keyword(s):  
Surface Tension ◽  
Surface Energy ◽  
Grain Boundaries ◽  
Radiation Damage ◽  
Impurity Concentration ◽  
Driving Force ◽  
Nucleation And Growth ◽  
Phase Boundaries ◽  
Cavity Nucleation ◽  
Spherical Bubble

Cavity nucleation and growth at grain and phase boundaries is of concern because it can lead to failure during creep and can lead to embrittlement as a result of radiation damage. Two major types of cavity are usually distinguished: The term bubble is applied to a cavity which contains gas at a pressure which is at least sufficient to support the surface tension (2g/r for a spherical bubble of radius r and surface energy g). The term void is generally applied to any cavity which contains less gas than this, but is not necessarily empty of gas. A void would therefore tend to shrink in the absence of any imposed driving force for growth, whereas a bubble would be stable or would tend to grow. It is widely considered that cavity nucleation always requires the presence of one or more gas atoms. However since it is extremely difficult to prepare experimental materials with a gas impurity concentration lower than their eventual cavity concentration there is little to be gained by debating this point.

Understanding gas bubble trauma in an era of hydropower expansion: how do fish compensate at depth?

2020 ◽  
Vol 77 (3) ◽  
pp. 556-563 ◽  
Author(s):  
Naomi K. Pleizier ◽  
Charlotte Nelson ◽  
Steven J. Cooke ◽  
Colin J. Brauner
Keyword(s):  
Bubble Growth ◽  
Gas Bubble ◽  
Hydroelectric Dams ◽  
Dissolved Gas ◽  
Empirical Relationships ◽  
Lethal Effects ◽  
Exposed Fish ◽  
Total Dissolved Gas ◽  
Rainbow Trout Oncorhynchus Mykiss ◽  
The Relationship

Hydrostatic pressure is known to protect fish from damage by total dissolved gas (TDG) supersaturation, but empirical relationships are lacking. In this study we demonstrate the relationship between depth, TDG, and gas bubble trauma (GBT). Hydroelectric dams generate TDG supersaturation that causes bubble growth in the tissues of aquatic animals, resulting in sublethal and lethal effects. We exposed fish to 100%, 115%, 120%, and 130% TDG at 16 and 63 cm of depth and recorded time to 50% loss of equilibrium and sublethal symptoms. Our linear model of the log-transformed time to 50% LOE (R2 = 0.94) was improved by including depth. Based on our model, a depth of 47 cm compensated for the effects of 4.1% (±1.3% SE) TDG supersaturation. Our experiment reveals that once the surface threshold for GBT from TDG supersaturation is known, depth protects rainbow trout (Oncorhynchus mykiss) from GBT by 9.7% TDG supersaturation per metre depth. Our results can be used to estimate the impacts of TDG on fish downstream of dams and to develop improved guidelines for TDG.

Evolution of cluster size distribution in nucleation and growth processes

1991 ◽  
Vol 136 (3) ◽  
pp. 181-197 ◽  
Author(s):  
J. Bartels ◽  
U. Lembke ◽  
R. Pascova ◽  
J. Schmelzer ◽  
I. Gutzow
Keyword(s):  
Size Distribution ◽  
Cluster Size ◽  
Nucleation And Growth ◽  
Cluster Size Distribution ◽  
Growth Processes

A Liquid Water Model That Explains the Variation of Surface Tension of Water with Temperaure

2001 ◽  
Vol 40 (Part 1, No. 3A) ◽  
pp. 1467-1471 ◽  
Author(s):  
Arshad Khan ◽  
M. Rezwan Khan ◽  
M. Ferdouse Khan ◽  
Fahima Khanam
Keyword(s):  
Surface Tension ◽  
Liquid Water ◽  
Water Model

A micromechanistic model of microstructure development during the combustion synthesis process

1995 ◽  
Vol 10 (4) ◽  
pp. 962-980 ◽  
Author(s):  
Yangsheng Zhang ◽  
Gregory C. Stangle
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Combustion Synthesis ◽  
Growth Parameters ◽  
Experimental Studies ◽  
Nucleation And Growth ◽  
Synthesis Process ◽  
Product Phase ◽  
Nucleation Sites ◽  
Rate Of Increase

The influence of the key nucleation and grain growth parameters on (i) the evolution of the microstructure of the product phase (on a microscopic level) and (ii) the combustion synthesis process (on a macroscopic level) were investigated for the combustion synthesis process in the Nb-C system. This work is an integral part of the continuing effort1–3 to develop a more complete theoretical model for combustion synthesis processes in general. In particular, the nucleation and growth of the NbC(s) product phase from the supersaturated liquid Nb/C mixture that appears briefly during the combustion synthesis process was treated in a greater detail by using a decidedly more sophisticated treatment of the nucleation and growth process (as developed in the field of rapid solidification and welding). It was shown that the microstructure of the NbC(s) product phase, including the evolution of the grain size and the size distribution, and the development of the grain's morphology, as well as the combustion wave velocity, are significantly influenced by the total number density of the nucleation sites, nmax, that are present in the system. The grain size distribution was shown to possess a monosize distribution, since during the combustion synthesis process the rate of increase of the degree of local undercooling was very high so that the nucleation process took place (locally) during a very brief period of time. This work provides a sound basis for developing a better control of the microstructure, and for a better understanding and interpretation of the results of related experimental studies.

Development of the Grain Size Distribution During the Crystallization of an Amorphous Solid

2011 ◽  
Vol 1308 ◽  
Author(s):  
Andreas Bill ◽  
Ralf B. Bergmann
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Growth Rates ◽  
Amorphous Solid ◽  
Amorphous Solids ◽  
Nucleation And Growth ◽  
Analytic Description ◽  
Silicon Thin Films ◽  
Random Nucleation

ABSTRACTWe present an overview of the theory developed over the last few years to describe the crystallization of amorphous solids. The microstructure of the crystallizing solid is described in terms of the grain size distribution (GSD). We propose a partial differential equation that captures the physics of crystallization in random nucleation and growth processes. The analytic description is derived for isotropic and anisotropic growth rates and allows for the analysis of different stages of crystallization, from early to full crystallization. We show how the timedependence of effective nucleation and growth rates affect the final distribution. In particular, we demonstrate that for cases described by the Kolmogorov-Avrami-Mehl-Johnson (KAMJ) model applicable to a large class of crystallization processes a lognormal type distribution is obtained at full crystallization. The application of the theory to the crystallization of silicon thin films is discussed.

scholarly journals Prototype System for the Detection of Volatile Hydrocarbons in Water

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 734
Author(s):  
Alexey A. Vasiliev ◽  
Mikhail Yu. Yablokov ◽  
Andrey V. Sokolov
Keyword(s):  
Oil And Gas ◽  
Detection System ◽  
Prototype System ◽  
Dissolved Gas ◽  
Dissolved Methane ◽  
Gas Concentration ◽  
Volatile Hydrocarbons ◽  
Oil And Gas Fields ◽  
Gas Fields ◽  
System Prototype

Detection of dissolved methane and volatile hydrocarbons in water is a problem met inleakage localization during exploitation of underwater pipelines, oil and oil product spill over watersurface, geological exploration work for the localization of oil and gas fields under water, etc. Thisproblem can be solved by the application of detection system based on tubular selective membranepermeable for volatile organics and impenetrable for liquid water. Carrier gas (air) flowing throughthis tube is saturated with dissolved gas and then gas concentration is measured usingsemiconductor or other gas sensor. The system prototype was tested under laboratory conditionsand demonstrated low limit of gas detection (~20 ppb by mass of dissolved methane in water) andshort response time (~10 s).

scholarly journals Prediction Model for Dissolved Gas Concentration in Transformer Oil Based on Modified Grey Wolf Optimizer and LSSVM with Grey Relational Analysis and Empirical Mode Decomposition

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 422 ◽  
Author(s):  
Bing Zeng ◽  
Jiang Guo ◽  
Fangqing Zhang ◽  
Wenqiang Zhu ◽  
Zhihuai Xiao ◽  
...  
Keyword(s):  
Prediction Model ◽  
Ambient Temperature ◽  
Grey Relational Analysis ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Dissolved Gas ◽  
Gas Concentration ◽  
Relational Analysis ◽  
Mode Decomposition ◽  
Grey Relational

Oil-immersed transformer is one of the most important components in the power system. The dissolved gas concentration prediction in oil is vital for early incipient fault detection of transformer. In this paper, a model for predicting the dissolved gas concentration in power transformer based on the modified grey wolf optimizer and least squares support vector machine (MGWO-LSSVM) with grey relational analysis (GRA) and empirical mode decomposition (EMD) is proposed, in which the influence of transformer load, oil temperature and ambient temperature on gas concentration is taken into consideration. Firstly, GRA is used to analyze the correlation between dissolved gas concentration and transformer load, oil temperature and ambient temperature, and the optimal feature set affecting gas concentration is extracted and selected as the input of the prediction model. Then, EMD is used to decompose the non-stationary series data of dissolved gas concentration into stationary subsequences with different scales. Finally, the MGWO-LSSVM is used to predict each subsequence, and the prediction values of all subsequences are combined to get the final result. DGA samples from two transformers are used to verify the proposed method, which shows high prediction accuracy, stronger generalization ability and robustness by comparing with LSSVM, particle swarm optimization (PSO)-LSSVM, GWO-LSSVM, MGWO-LSSVM, EMD-PSO-LSSVM, EMD-GWO-LSSVM, EMD-MGWO-LSSVM, GRA-EMD-PSO-LSSVM and GRA-EMD-GWO-LSSVM.

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