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Comparison of the estimation results carried out to identify of effective dam operation regime showed that at the operation regime developed by SANIIRI the reservoir sedimentation intensity is lower for 1.4 times than at the real one. Incoming and outflowing
balance of sediments in the reservoir will happen at the reservoir capacity of 680-700 Mio m3 (what means 30% of design volume), what will take place at the present operation regime by 2019-2020, but at the improved operation terms — by 2030.
References:
1. Barishnikov N. B. Anthropogenic impact on river bed evolution. - Leningrad publishing. LGM, - 1990.
2. Berkovich K. M. Channel processes in the rivers in the area of influence ofreservoirs. Faculty ofGeography, - Moscow State University, - 2012.
3. Ikramova M., Khodjiev A. Tuyamuyun water works operation improvement. Agriculture of Uzbekistan, - Vol. 4, - 2008.
4. Estimation of channel water balances. Methodical instructions for Hydro Meteorological Services. Saint Petersburg, GIDROME-TEOIZDAT, - 2007.
5. Savitchev O. G., Krasnoshyokov S. Y., Nalivayko N. G. Regulation of river flow. Tomsk Polytechnic University. - Tomsk, - 2009.
6. Shmakova M. V. The methodology of calculation of sediment discharge for unstudied rivers. - Cheboksary, Perfectum edition, - 2012.
7. Skrilnikov V., Keberle S., Beleskov B. Improving efficiency of water reservoirs. - Tashkent, Mekhnat Printing, - 1987.
Yusubov Faxraddin Vali, Azerbaijan State Oil and Industry University, Department «Technology of oil and industry ecology» Baku, professor in technical sciences, E-mail: yus_fax@mail.ru Shixaliyev Karam Seyfi, Azerbaijan State Oil and Industry University, Department «<Orqanic substances and technology of high molecular composition», professor of chemical sciences E-mail: kerem_shixaliyev@mail.ru Abdullayeva Maya Yadigar, Azerbaijan State Oil and Industry University, Department«Technology of oil and industry ecology» Baku, PhD in chemical sciences, E-mail: mayaabdullayeva@hotmail.com
Determination of optimal parameters of purification water surface from oil and oil products by sorbent on the basis of worn automobile tires
Abstract: The article describes an identification of optimal parameters for surface water purification from oil and oil
products by sorbent based on worn automotive tires. In thus Optimal parameters for water surface purification from oil and oil products by sorbent have been found out on the basis of constructed regression model of the process.
Keywords: rubber crumb, sorbent, purification of water surface, method of experiment planning, mathematical model.
Sorbents are known to be used on eliminating environmental pollution in case of oil and oil product spills from tankers and oil pipes in reservoirs. However, all known sorbents don't provide required extent of purification and it takes much time to absorb oil and oil products. Rubber, being an elastomer material with a unique complex of properties is a large-tonnage product of chemical technology, one of the final products of oil and gas refining chain which is widely applied in different branches of industry and every day life. The scale of production of rubber products as well as formed rubber wastes are rather high [1; 2].
The tread of tires is produced from tread rubber (TR) on the basis of butadiene-styrene and divinyl rubber mixture BSR + SDR (70: 30), containing 50 mass fraction of technical carbon [3; 4].
The investigations carried out by us showed that crumb of rubber tread (CRT) differs from other tire rubber crumbs because of high rigidity, when crushed it doesn't roll up but has elastic grid structure, thus it has high adsorption surface.
Besides all mentioned characteristics of tread tire allowed to obtain on its basis not conglutinated rubber crumb with dimensions 0,06-0,08 mm, without applying additional materials and to use it successfully. Obtained results are shown in Tables 1; 2
Tablel. - Association between water surface purification rate and amount of sorbent
Sorbent amount, gr Amount of oil spill Amount of absorbed oil, gr Oil absorption coefficient Rate of water surface purification,%
0,5 10 2,5 5 25
1,0 10 5,0 5 50
1,5 10 7,5 5 75
2,0 10 10 5 100
Determination of optimal parameters of purification water surface from oil and oil products by sorbent on the basis.
Table 2. - Oil absorption rate
Time for oil absorption second Oil absorption rate,%
Known sorbent Suggested sorbent
60 145 -
5 - 350
10 - 420
15 - 500
20 - 500
Sorbent can also be used for purification of industrial drain from oil and oil products (Table 3). The main feature of rubber crumb as a sorbent is its similarity to oil floatation.
Due to its lattice structure, the crumb of tread tire swells in the oil and provides its retention. As a result, agglomerate having much lower density than water is formed on the treated surTable 3. — Technical characteristics of sorbent based on worn tires
face and occupies much smaller area in comparison with sorbed oil slick. This agglomerate is easily collected by any mechanical technique, for example, by means of metal mesh buckets. After maximum oil separation obtained agglomerate was reused by us and then was applied for road asphalt modification. Obtained data are shown in tables 4-6.
Indicators Value
Absorption mass capacity of oil products, kg/kg Shelltic W 14-20
Apparent density kg/m 85
Particle size, mm 0.06-0.09
Trapping and holding of vapor and odors,% 98
Thermal stability, Co 200
pH of water extract 5.5-6.5
Abrasivity missing
Purification efficiency of industrial drain from oil products,% 99.1
Purification efficiency of water from heavy metals (Pb, Cu, Cr),% 88.3-99.5
Purification efficiency of water from hydrocarbons,% 99.5-99.6
Purification efficiency of water from pesticides,% 99.4-99.9
Table 4. - Obtained content of mass fraction of samples after modification
Samples
Component name 1 2 3 4 5
Content of mass fraction
Bitumen 100 100 100 100 100
TR 2 4 6 8 10
Sulphur - - - 1 2
Table 5. - Physico-mechanical properties of composition on the basis of rubber dust
№ Indicators Samples
1 2 3 4 5
1 Needle penetration at 25 °C 38 72 100 71 96
2 Softening temperature, °C 49 68 82 56 75
3 Brittleness temperature, °C -10 -10 -26 -8 -20
4 Extensibility at 25, °C 40 60 70 55 60
5 Density, gr/sm 3 2,34 2,36 2,38 2,2 2,4
6 Temperature changes at T=65 °C 7 6 6 6 6
7 Strength limit at 20 °C 2,4 3,0 3,5 3,1 3,4
50 0C 0,9 1,0 1,2 1,1 1,3
Table 6. — Indicators of physico- mechanical properties of asphalt concrete mixtures
Indicators Samples
1 2 3 4
Strength limit under compression, MPa at temperature 20 °C 50 0C 2,2 0,9 - - -
Water resistance coefficient under sustained water satura-tion,% in volume 0,86 0,90 0,94 0,90
Water resistance coefficient 0,90 - 0,95 0,89
Soaking%, in volume 0,6 0,9 0,5 1,0
Residual poposity,% in volume 2,1 2,4 2,0 2,3
Using experimental planning method (7,8), there are shown investigations on applying crumb of rubber as a sorbent for purification water surface from oil and oil products with the purpose of
constructing regression mathematical model on the basis of its optimization. Basic input and output parameters of the examined process have been determined on the basis of numerous investigations.
Table 7. - Physico-mechanical indicators of macadam and mastic asphalt concrete MMA-15 while injecting CRT into aggregates
№ Indicators Standard norms 0% 0,1% 0,2% 0,3% 0,5%
31015-2002 CRT CRT CRT CRT CRT
1 Density, gr/sm3 - 2,38 2,39 2,395 2,406 2,4108
2 Residual porosity,% 2,0-4,0 3,64 3,57 3,13 2,46 1,83
3 Water saturation,% in volume 1,5-4,0 3,07 2,68 2,52 2,33 2,05
4 Strength limit under compression, MPa at
temperature: 200 °C 2,5 3,51 4,08 4,26 4,59 4,72
500 0C 0,70 0,72 0,78 0,85 0,89 0,92
5 Coefficient of water resistance - 3,85 0,88 0,90 0,92 0,94
6 Coefficient of water resistance under sus- 0,75 0,83 0,84 0,87 0,89 0,91
tained water saturation (15 days)
7 Crack resistivity-tensile strength limit at temperature °C, MPa 3,0-6,5 3,95 4,36 4,58 4,75 4,66
8 Coefficient of interior friction tg 0,94 0,91 0,92 0,92 0,93 0,93
9 Shear adhesion at temperature 500 °C, MPa 0,20 0,20 0,32 0,55 0,59 0,63
10 Adhesive fluidity indicator,% 0,20 0,20 0,19 0,15 0,13 0,11
Table 8. - Basic factor levels and their change limits
Name Real factor values
Basic level 1,25 6,5 6,5
Change limit 0,1 1 1
Lowest change limit 0,5 3 3
Highest change limit 2,0 10 10
Table 9. - Planning test for water surface purification and oil products on the basis of sorbent crumb rubber, obtained on the basis of tire tread parts of worn automobile tires
Sorbent amount, gr Oil spill amount, gr Amount of absorbed oil, gr. Level of water surface purifi-ca-tion,% y
Encoded values Real values Encoded values Real values Encoded values Real values
+1 2.0 + 1 10 10 10 100
+1 2.0 + 1 10 3.0 3,0 70
+ 1 2.0 -1 3 10 10 100
+ 1 2.0 -1 3 3.0 3.0 70
-1 0.5 + 1 10 10 10 100
-1 0.5 + 1 10 3.0 3.0 30
-1 0.5 -1 3 10 10 70
-1 0.5 -1 3 3.0 3.0 30
The basic output parameter process is the level of water surface purification- yi actors influencing on parameter process are X1 - sorbent amount, X2 - oil spill amount, X3 - amount of absorbed oil. The table shows basic factor levels and their limit changes. Rototable-plan - method of experiment planning (8-10) was usedto investigate crumb of rubber tread as a sorbent for purification water surface from oil and oil products. When examined in a lab unit matrix planning was worked out and experiments were carried out according to rototable plan the results of which are shown in table 8.
Dependence of each output parameter process y-, - on output factors Xj (j=1, 3) we'll represent in the following polynomial type: Y = b0 + b1X1 + b2X2 + b3X3 + bnX1X2 + bl3X,X, + b23X2X3 + b123X1X2X3 (1)
where - Xl - process factors, b - coefficient evaluation of regression equations defining linear effects and interaction effects.
Regression equation coefficients were defined by familiar formula (1)
b = , (2)
' N v '
Where - (l)equation coefficients; N - total number of carried out experiments; Xi - encoded and real values of basic process factors.
The following regression equation coefficients have been obtained:
b0 = 95.331, b1 = 0.380,b2 = 0.460,b3 = -0.400, b12 = 0.017, b13 = -0.001,
where -
b„ =-0.018,b,„ =-0.0067
The following regression equation has been obtained on the basis formula (2) accounts:
Y = 95.331 + 0.380X, + 0.460X, - 0.400X3 + 0.017X.X, - , s
1 2 3 1 2 (3)
A nm V V A A1 Q V V A V V "V v '
Effect of temperature of steady heating components of cotton-seed at drying process
Then, statistical analyses of obtained regression equation were a) Experiment errors;
carried out (3): b) Value of regression equation coefficients (3)
References:
1. Shershnev, P. P., - 1998, Russian Federation Patent - No 2108147.
2. Kablov V. F., Jeltobryukhov V. F., Mikhalchuk T. A., Kargin Y. N., - 2000, Russian Federation Patent - No 2148024.
3. Karayev S. F., Shikhaliyev K. Ecological issues of oil and oil products and new methods for treatment of oil and oil products from water surface, Hannover (in Russian), - 2014, P. 444.
4. Akhnazarova S. L., Kafarov V. V., "Optimization of an experiment in chemistry and chemical technology" (in Russian), - 2001, P. 41-42.
5. Yusubov, F. V., Zeynalov, R. I., Ibragimov, Ch.Sh., J. Chemistry and technology of fuel and oil (in Russian). - Moscow, Russia, - 2001 (1), P. 41-42.
6. Shikhaliyev K. S., Bilalov Y. M., Ibragimov S. M., J. Azerbaijan Oil Industry (in Azerbaijani) - Baku, - 2010 (8), P. 60-62.
7. Aliyeva S. F., Chemistry J. and petrochemistry (in Azerbaijani), - Baku, Elm, - 2004 (3), P. 60-62.
8. Yusubov F. V., Mamedov E. A., Chemistry J. and technology of fuel and oil (in Russian), - Moscow, - 2012 (2), P. 48-51.
9. Yusubov F. V., Chemistry J. and technology of fuel and oil (in Russain), - Moscow, - 2007 (4), P. 16-18.
10. Yusubov F. V., Zeynalov F. V., Ibragimov Ch.Sh. Applied Chemistry J. (in Russian), - Moscow, - 2001 (69), P. 59-62.
Parpiyev Azimjan, Tashkent institute of textile and light industry, doctor of technical sciences, professor, E-mail: abdul-malik@umail.uz. Kayumov Abdul-malik, Tashkent institute of textile and light industry, research associate — the competitor, E-mail: abdul-malik2017@mail.ru.
Pardayev Hanimkul, Tashkent institute of textile and light industry, Ph. D., Associate Professor, E-mail: hanimkul@bk.ru
Effect of temperature of steady heating components of cotton-seed at drying process
Abstract: The problem of temperature regime effect on the heating cotton-seed components in the drum (cylindrical) dryers have not been studied profoundly. In the article were received mechanisms (principles) of heating cotton-seed components in the drum dryers in relation to the initial of cotton-seed humidity; and mechanisms (principles) of efficiency ofmaterial which is drying. Keywords: drying, cotton-seed, fiber, seed, temperature, heating, humidity, uniformity.
Introduction: One of the present-day quotes in organization of dry process is studying the heating temperature of cotton-seed components at process of its thermal deprive. Apparently, the less temperature of heating amount is the less probability of getting worse of its natural properties.
There [1] have been determined the mechanisms (principles) of initial humidity and temperature of dry agent on the heating of cotton-seed components. But the productivity of dry drum with humid cotton-seed has not been taken into consideration in the article, and the research was done by initial humidity till 14%.
Experimental researches: Our researches were done on the dryer 2SB-10 with humid cotton-seed by dry agent temperature T=100 and 200 °C, by productivity 3,5 and 10 t/h. The research object was cotton-seed of variety C-6524, and industrial sort II, with initial humidity W=10,5 and 22,3 percent.
Tests have been done in-one, two, and three times (multiply) drying.
Analysis of receiving regress equations shows that all accepted factors have been highly influenced on the output parameters either independently or during interaction.
Processing of experiments results on the computer let us to get the individual regress equations for each dry multiplicity [2].
The regress equation for the one-time drying of fiber heating temperature is:
Y=47,7-4,29X1-3,79X2+11,2X2-0,79X1X2-2,79X1X3 -
-1,29 X2X3
The regress equation of temperature of heating seeds: Y=41,08-3,41X,-2,33X+9,58X3-0,83X,X-1,91X,X3-
c ' ' 1 ' 2 ' 3 1 2 ' 13
-0,83X1X2X3
The regress equation for two-times drying of fiber temperature heating is:
Y = 59,6-5,12X1-6,5X2+12,9X3-3,5X1X3-1,87X2X3 The regress equation of temperature of heating seeds:
Yc = 53,16-4,75X1-5,75 X2+11,0X3-2,75 X1X3-1,25X2X3 The regress equation for three-times drying temperature of heating fibers:
Y = 74,37-6,875X19,12X2+ 19,37X3 -4,75X1X3-2,12X2X3 The regress equation of temperature of heating seeds:
Yc = 68,75-6,5X1-7,25X2 + 17,5X3 + 4,75X1XJ-1,5X2X3
