ASTM E799-2003(2009) 3750 Standard Practice for Determining Data Criteria and Processing for Liquid Drop Size Analysis《液滴大小分析用测定数据判别和数据处理的标准规范》.pdf

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1、Designation: E799 03 (Reapproved 2009)Standard Practice for DeterminingData Criteria and Processing for Liquid Drop Size Analysis1This standard is issued under the fixed designation E799; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revis

2、ion, the year of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1. Scope1.1 This practice gives procedures for determining appro-priate sample size, size class widths, character

3、istic drop sizes,and dispersion measure of drop size distribution. The accuracyof and correction procedures for measurements of drops usingparticular equipment are not part of this practice. Attention isdrawn to the types of sampling (spatial, flux-sensitive, orneither) with a note on conversion req

4、uired (methods notspecified). The data are assumed to be counts by drop size. Thedrop size is assumed to be the diameter of a sphere ofequivalent volume.1.2 The analysis applies to all liquid drop distributionsexcept where specific restrictions are stated.2. Referenced Documents2.1 ASTM Standards:2E

5、 1296 Terminology Relating to Liquid Particle Statistics2.2 ISO Standards:133201 Particle Size Analysis-Laser Diffraction Methods392761 Representation of Results of Particle Size Analysis-Graphical Representation392722 Calculation of Average Particle Sizes/ Diametersand Moments from Particle Size Di

6、stribution33. Terminology3.1 Definitions of Terms Specific to This Standard:3.1.1 spatial, adjdescribes the observation or measure-ment of drops contained in a volume of space during such shortintervals of time that the contents of the volume observed donot change during any single observation. Exam

7、ples of spatialsampling are single flash photography or laser holography.Anysum of such photographs would also constitute spatial sam-pling. A spatial set of data is proportional to concentration:number per unit volume.3.1.2 flux-sensitive, adjdescribes the observation of mea-surement of the traffic

8、 of drops through a fixed area duringintervals of time. Examples of flux-sensitive sampling are thecollection for a period of time on a stationary slide or in asampling cell, or the measurement of drops passing through aplane (gate) with a shadowing on photodiodes or by usingcapacitance changes. An

9、example that may be characterized asneither flux-sensitive nor spatial is a collection on a slidemoving so that there is measurable settling of drops on the slidein addition to the collection by the motion of the slide throughthe swept volume. Optical scattering devices sensing continu-ously may be

10、difficult to identify as flux-sensitive, spatial, orneither due to instantaneous sampling of the sensors and themeasurable accumulation and relaxation time of the sensors.For widely spaced particles sampling may resemble temporaland for closely spaced particles it may resemble spatial. Aflux-sensiti

11、ve set of data is proportional to flux density: numberper (unit area 3 unit time).3.1.3 representative, adjindicates that sufficient data havebeen obtained to make the effect of random fluctuationsacceptably small. For temporal observations this requiressufficient time duration or sufficient total o

12、f time durations. Forspatial observations this requires a sufficient number of obser-vations.Aspatial sample of one flash photograph is usually notrepresentative since the drop population distribution fluctuateswith time. 1000 such photographs exhibiting no correlationwith the fluctuations would mos

13、t probably be representative.Atemporal sample observed over a total of periods of time thatis long compared to the time lapse between extreme fluctua-tions would most probably be representative.3.1.4 local, adjindicates observations of a very small part(volume or area) of a larger region of concern.

14、3.2 Symbols:SymbolsRepresentative Diameters:3.2.1 ( Dpq) is defined to be such that:4Dpqp2q!5(iDip(iDiq(1)1This practice is under the jurisdiction ofASTM Committee E29 on Particle andSpray Characterization and is the direct responsibility of Subcommittee E29.02 onNon-Sieving Methods.Current edition

15、approved Nov. 1, 2009. Published February 2010. Originallyapproved in 1981. Last previous edition approved in 2003 as E799 03. DOI:10.1520/E0799-03.2For referenced ASTM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annual Book of ASTMStandar

16、ds volume information, refer to the standards Document Summary page onthe ASTM website.3Available from American National Standards Institute (ANSI), 25 W. 43rd St.,4th Floor, New York, NY 10036, http:/www.ansi.org.4This notation follows: Mugele, R.A. and Evans, H.D., “Droplet Size Distribu-tion in S

17、prays,” Ind. Engnrg. Chem. Vol 43, No. 6 (1951), pp. 1317-1324.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.where:D= the overbar in Ddesignates an averagingprocess,(pq)pq = the algebraic power of Dpq,p and q = the integers 1, 2, 3

18、 or 4,Di= the diameter of the ith drop, and(i= the summation of Dipor Diq, representingall drops in the sample.0=pand q = values 0, 1, 2, 3, or 4.(iDi0is the total number of drops in the sample, and someof the more common representative diameters are:D10= linear (arithmetic) mean diameter,D20= surfa

19、ce area mean diameter,D30= volume mean diameter,D32= volume/surface mean diameter (Sauter), andD43= mean diameter over volume (De Broukere or Her-dan).See Table 1 for numerical examples.3.2.2 DNf,DLf,DAf, and DVfare diameters such that thefraction, f, of the total number, length of diameters, surfac

20、earea, and volume of drops, respectively, contain precisely all ofthe drops of smaller diameter. Some examples are:DN0.5= number median diameter,DL0.5= length median diameter,DA0.5= surface area median diameter,DV0.5= volume median diameter, andDV0.9= drop diameter such that 90 % of the total liquid

21、volume is in drops of smaller diameter.See Table 2 for numerical examples.3.2.3log Dgm! 5 (ilog Di!/n (2)where:n = number of drops,Dgm= the geometric mean diameter3.2.4DRR5 DVF(3)where:f = 1 1/e .6321DRR= Rosin-Rammler Diameter fitting the Rosin-Rammler distribution factor (See Terminology E1296)3.2

22、.5 Dkub= upper-boundary diameter of drops in the kthsize class.3.2.6 Dklb= lower-boundary diameter of drops in the kthsize class.4. Significance and Use54.1 These criteria5and procedures provide a uniform basefor analysis of liquid drop data.5. Test Data5.1 Specify the data as temporal or spatial. I

23、f the data cannotbe so specified, describe the sampling procedure. Also specifywhether the data are local (that is, in a very small section of thespace of liquid drop dispersion), and whether the data arerepresentative (that is, a good description of the distribution ofconcern). Report the fluids, f

24、luid properties, and pertinentoperating conditions.5.1.1 A graph form for reporting data is given in Fig. 1.5.2 Report the largest and smallest drops of the entiresample, the number of drops in each size class, and the class5These criteria ensure that processing probably will not introduce error gre

25、aterthan 5 % in the computation of the various drop sizes used to characterize the spray.TABLE 1 Sample Data Calculation TableSize Class Bounds(Diameterin Micrometres)ClassWidthNo. ofDrops inClassSum of Dirin Each Size ClassAVol. %in ClassBCum. %by Vol.DiDi2Di3Di4240360 120 65 19.5 3 1035.9 3 1061.8

26、 3 1091. 3 10120.005 0.005360450 90 119 48.2 19.6 8.0 3 0.021 0.026450562.5 112.5 232 117.4 59.7 30.5 16 0.081 0.107562.5703 140.5 410 259.4 164.8 105.2 67 0.280 0.387703878 175 629 497.2 394.7 314.5 252 0.837 1.2248781097 219 849 838.4 831.3 827.6 827 2.202 3.42610971371 274 990 1221.7 1513.7 1883.

27、2 2352 5.010 8.43613711713 342 981 1512.7 2342.1 3641.1 5683 9.687 18.12317132141 428 825 1589.8 3076.1 5976.2 11657 15.900 34.02321412676 535 579 1394.5 3372.5 8189.2 19965 21.788 55.81126763345 669 297 894.1 2702.8 8203.5 24999 21.826 77.63733454181 836 111 417.7 1578.2 5987.6 22807 15.930 93.5674

28、1815226 1045 21 98.8 466.5 2212.1 10532 5.885 99.45352266532 1306 1 5.9 34.7 348.5 1534 0.547 100.000Totals of Dirin (k = 6109 8915.3 3 10316562.6 3 10637729.0 3 109100695 3 1012entire sample DN0.5= 1300 D10= 1460 D21= 1860 D32= 2280 D43= 2670D20= 1650 D31= 2060D30= 1830DV0.5= 2540 Worst case class

29、width348.5377295 0.009 Relative Span 5 DV0.92 DV0.5!/DV0.55 390014200/2530 5 0.986692676 1 33453 0.21826 5 0.024Less than 1%, adequate sample size Adequate class sizesAThe individual entries are the values for each k as used in 5.2.1 (Eq 1) for summing by size class.BSUM Di3in size class divided by

30、SUM Di3in entire sample.E799 03 (2009)2boundaries. Also report the sampling volume, area, and lapseof time, if available and applicable.5.3 Estimate the total volume of liquid in the sample thatincludes measured drops and the liquid in the sample that is notmeasured. (The volume outside the range of

31、 sizes permitted bythe measuring technique might be estimated by graphicalextrapolation of a histogram or by a curve fitting technique.)5.4 The ratio of the volume of the largest drop to the totalvolume of liquid in the sample should be less than the tolerablefractional error in the desired represen

32、tation. See Table 1. Allof the drops in the sample at the large-drop end of thedistribution should be measured. This criterion is a good “ruleof thumb” to determine a minimum sample size. The value ofD10is greatly affected by the smallest drops measured.5.5 Ninety-nine percent of the volume of liqui

33、d representedby the data should be in size classes such that no size class hasboundaries with a ratio greater than 3:2. For the majority ofsize classes, this ratio should not exceed 5:4. The 99 %condition exempts size classes having diameters smaller thanDV0.01. These criteria assure that processing

34、 probably will notintroduce errors greater than 5 % in the computation of thevarious drop diameters cited in this practice. The criteria maybe relaxed for measurements where this degree of accuracy isunattainable.5.6 (Dkub Dklb)/(Dkub+ Dklb) multiplied by the liquid vol-ume in the kth class and divi

35、ded by the total volume of liquidin the sample shall be less than 0.05 for every class. See TableI. Use of the same criterion for a size class created by lumpingthe estimated volume below the boundary of measurementprovides a test for determining the need for some type of curvefitting. It may be nec

36、essary to relax this requirement for caseswhere this degree of accuracy is unattainable.6. Data Processing6.1 Transformations of Data:6.1.1 If drop motions are essentially free from recirculationthrough the region of observation, spatial data can be trans-formed to flux-sensitive data by multiplying

37、 the number ofTABLE 2 Example of Log Normal Curve with Upper BoundData Collected May 2, 1979 Computer Analysis May 2, 1979Upper Bound Diameter (m) Normal Curve, % Adjusted Data, % Data, %360.00 0.006 0.005 0.005450.00 0.027 0.027 0.026562.50 0.109 0.108 0.107703.00 0.389 0.387 0.387878.00 1.227 1.22

38、4 1.2241097.00 3.421 3.426 3.4261371.00 8.407 8.437 8.4361713.00 18.109 18.124 18.1232141.00 34.080 34.024 34.0232676.00 55.551 55.811 55.8113345.00 77.828 77.637 77.6374181.00 93.648 93.568 93.5675226.00 99.481 99.453 99.4536532.00 100.000 100.000 100.000For Computing Curve AveragesLargest drop dia

39、meter = 6532.00 mSmallest drop diameter = 240.00 mFraction of normal curve = 0.999995Normal Curve Simple Calculation(Gaussian Limits4.55457 to 4.53257)D10= 1464.91 1459.37 m (length mean diameter)D20= 1646.44 1646.57 m (surface mean diameter)D30= 1824.85 1832.39 m (volume mean diameter)D21= 1850.45

40、1857.79 m (surface/length mean diameter)D31= 2036.73 2053.27 m (volume/length mean diameter)D32= 2241.75 2269.32 m (sauter mean diameter)D43= 2615.67 2670.75 m (mean diameter over volume)DV0.5= 2534.53 2533.31 m (volume median diameter)DN0.5= 1303.62 1304.71 m (number median diameter)Average of Abso

41、lute Relative Deviation from DV0.5by Volume = 0.311Relative Span = (DV0.900DV0.100)/ DV0.5(DV0.9DV0.1)/DV0.5= (3913.74 1437.21)/2534.53= 0.977Normal curve % FD! 51=p*2DEL lnSADXM 2 DDe2z2dzwhere:A = 1.8941DEL = 1.17206XM = 7335.30F(D) = accumulative fraction of liquid volume in drops having diameter

42、 less than D.E799 03 (2009)3drops in each size class by the average velocity of drops forthat size class at the sample location. If this transformation isperformed, the exact procedure shall be noted.6.1.2 If evaporation corrections are applied, the procedureshall be described and the magnitude of t

43、he corrections shall berecorded.6.1.3 If corrections are applied to account for drops outsidethe boundaries represented by the data, the procedure shall bedescribed. Likewise, if the overall distribution is established byblending several distributions, the procedure shall be de-scribed.6.1.4 If curv

44、e fitting (for example, to the upper-limit lognormal, Rosin-Rammler or Nukiyama-Tanasawa equation) isused in the data processing, the mathematical function6andminimization criteria, including any weighting factors appliedto the data, shall be given. The quality of fit shall be showngraphically or by

45、 tabular comparison with the data. When thereare corrections or transformations, the comparison shall bemade with the adjusted data.6.2 Calculations involving size classes:6.2.1 When data are reported by size classes rather than asindividual drop diameters, the representative diameters, Dpq,may be c

46、alculated from summations defined as follows:(iDir5 (kDkubr 1 12 Dklbr 1 1! NkDkub2 Dklb!r 1 1!(4)where:r = corresponds to the selected value of p or q in theexpression for Dpqas stated in 4.2.1, andNk= the number of drops in the kth size class.This calculation is based on the assumption of a linear

47、increase in the accumulation of counts as a function ofdiameter within each size class. If the data satisfy the criteria in5.5 and 5.6, the results based on either of the following twoformulas will differ by less than 8 % from that based on theabove (preferred) Eq 1.(iDir5 (kDkubr1 Dklbr23 Nk(5)(iDi

48、r5 (k SDkub1 Dklb2Dr3 Nk(6)6Examples are found in Mugele and Evans, loc. cit.; in Tishkoff, J. M., and Law,C. K. “Applications of a Class of Distribution Functions to Drop Size Data byLogarithmic Least Squares Technique,” Trans. ofASME, Vol. 99, Ser.A, No. 4, Oct.1977; and in Goering, C. E. and Smit

49、h, D. B.,“ Equations for Droplet SizeDistributions in Sprays,” Trans. of ASAE, Vol. 21, No. 2, 1978, pp. 209216.FIG. 1 Sample Data GraphE799 03 (2009)46.2.2 To obtain the values described in 4.2.2, the fractionalvalues (number, length, area or volume) accumulated betweenthe minimum drop size in the sample and the upper bounds ofthe respective size classes shall be plotted against the corre-sponding upper bound diameters, see Fig. 1.The desired valuescan then be read from the graph.The calculations sha