Macroscopic Fluctuations in the Density of Water

Aleksandrov, V.S.; Badenko, L. A.; Snegov, V. S.

doi:10.1023/b:mete.0000029874.77156.7b

Cited by 4 publications

(4 citation statements)

References 1 publication

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“…Another picture is formed when the minimal admissible concentration difference between the touching water objects with different compositions is high enough for the interphase tension to be higher than the elasticity coefficient of the grid of hydrogen bridges. In such cases, judging by laboratory data (11,12), turbulent mass transport forms near the phase interface, accompanied by density fluctuations, protuberance formation, opalescence, and an increase in the megahertz dielectric permittivity. Such phenomena should be expected in the zones near sites where high-pollution wastewater is discharged into river flow.…”

Section: Discussionmentioning

confidence: 99%

Structural water self-organization in river flow

Rozental¹,

Fedotov²

2023

BIJCEES

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Application of neural-network methods revealed relationships between hydrological and hydrochemical characteristics of water flow, suggesting structural self-organization of substances dissolved in water in the form of micro layering. In particular, the coefficient of correlation between the concentrations of such substances in some cases reaches its nearly maximal value (0.99), combining with the high weights of neural network edges. This can be supposed to be due to the mechanical and chemical interactions in river flow with the participation of Van der Waals forces, hydration, and sorption. Other factors, not taken into account, can also have their effect, in particular those responsible for the fluctuations of the parameters of order, determining the singular contributions to the dynamic characteristics of the non-linear system under consideration. Such can be the cyclic oscillations of the characteristics under control with an amplitude decreasing with a decrease in the intensity of the pollution/selfpurification processes in water medium and increasing with an increase in this intensity. The obtained information, in addition to its direct purpose as a means to study the nature and properties of fresh water, is a necessary condition for the effective control of water resource quality and water management activity.

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Section: Discussionmentioning

confidence: 99%

Structural water self-organization in river flow

Rozental¹,

Fedotov²

2023

BIJCEES

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“…They provide measurement accuracy with an accuracy of δ0 = ±0.02%. The most accurate calibration tool is the primary standard with the error δ0 = 2•10 -4 % [19].…”

Section: Discussionmentioning

confidence: 99%

“…The density of water varies within ±0.0000135g/cm 3 . This value can significantly affect the sensor reading, causing an error of 0.00135% [19].…”

Section: Discussionmentioning

confidence: 99%

Imitation Modeling of the Flow Control Information System Elements

Gudkov¹,

Piskaev²,

Zhashkova³

et al. 2019

Proceedings of the VIII Science and Technology Conference “Contemporary Issues of Geology, Geophysics and Geo-Ecology of the No

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A number of issues related to the construction of an information processing system in a Coriolis flow meter using simulation models are considered. The paper presents simulation models of a straight-tube Coriolis flowmeter built in a Matlab/Simulink simulation environment. A simulation of the operation of the flow meter under various conditions of the flow of a liquid medium was carried out, and external vibration effects were simulated on both the flowmeter and its pipeline elements. On the basis of the obtained experimental data, the parameters of the data processing system were selected. The problems of the influence of external influences and ways to eliminate it are considered. In addition to external influences that adversely affect the accuracy of measurements, various physical limitations determining the maximum achievable accuracy of Coriolis flowmeters are analyzed. The processes of dynamic changes in the physical properties of bodies related to their molecular structure are considered, as well as technical and technological processes that can make changes to the accuracy parameters of a measuring device due to the variation of parameters of structural elements.

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“…The wood samples were then placed into the capsule and submerged into the water making sure to lower the capsule to the same level as it was zeroed. The reading on the OHAUS scale was recorded as the volume of the sample after determining the proper density of the water at room temperature (20 ºC), which was done by treating the scale reading as unitless and multiplying that reading by the density of water at 20 ºC (0.998199 g/cm 3 ) (Aleksandrov et al 2004). Density samples were oven-dried at 105 ºC until a constant mass was achieved.…”

Section: Wood Densitymentioning

confidence: 99%