1641
V O L U M E 23, NO. 11, N O V E M B E R 1 9 5 1 Table 111. Basic and Total Nitrogen Content of Various Samples Pu’itrogen,Weight2C, Basic Total
Description Crude Shale Oils South Africa (Salermo retort) Scotland (Pumpherston retort) France (Pumpherston retort) Colorado (N-T-U retort)” Colorado (gae Row retort) Colorado (Fischer assay retort) Shale Oil Distillates Colorado primary naphtha (N-T-U retort)“ Swedish crude naphtha (Ljungstrom retort) Colorado Dieeel-range oil (N-T-U retort)O Colorado straight-run gas oil (K-T-U retort) Gasoline Coker distillate E’iirnace oil
Petroleum
0.62 0.60 0.07 0.07 0.98 0.98 1.02 0.0026 0.10 0.057
Various Crude nitrogen bases from cracked naphtha (shale oil) Crude nitrogen bases from gas oil (shale oil) G u m from oxidized shale naphtha U.O.P. inhibitor No. 5 (N,S-diisobutyl-p-phenylenediamine) 4
0.41 0.41 0.41 0.41 0.47 0.47 1,12 1,14 1.23 1.24 1,13 1,14
8.86 8.83 3.46 1.86 12.3
miscibility than the amount suggested tends to obscure the end point of a titration. Analysis of a mixture of pyrrole, cresol, and 2,4,6-trimethylpyridine in hydrocarbon solvent gave a basic nitrogen value that agrees with the nitrogen content from the substituted pyridine only.
0.85
...
-\PPLlC4TlOIS
...
In order to examine the versatilit) oi the method, a vaiietj of shale oil and petroleum samples selected to cover a range of nitrogen concentrations and physical characteristics were titrated for basic nitrogen content. Total nitrogen, as determined by the Kjeldahl procedure, is noted for comparison Table I11 shows the rrsults of these analyws.
0.77
0.90 i.94 . I .
2.11 2.12 1.87
...
0.94
...
VRECISION AND ACCURACY
... 1.61 ...
The precision of the method when applied to shale oils is approximately 2%. .4 series of determinations on redistilled pyridine (99.9 mole pure) gave results averaging within 1% of the true value.
0.11
1.79 0.004 0.30 0.140 9.10
...
3.42 7.62 12.5
Exchange sample ( I ) .
LITERATURE CITED
(1) Ball, J. R., and Van Meter, Robin, ASAI.. CHEM.,23, 1632 (1951). ( 2 ) Conant, J. B., Hall, S . F., and Werner, T. H., J. Am. Chem. SOC.,49, 3047-61, 3062-70 (1927); 50, 2367-86 (1928); 52, 4436-50, 5115-28 (1930). (3) Fritz, J. S., .%SAL. CHEY.,22, 1025-9 (1950). (4) Kolthoff, I. l f , , and Stenger, V. A, “Volumetric Analyeis,” Val. I, p. 254, Table 11, New York, Interscience Publishers, 1942.
( 5 ) Lange’s “Handbook of Chemistry,” 7th ed.. $1. 1410, Sandusky,
pounds represented by isopropylthiophene and thiacyclopentane show no titration response. Hydrocarbons do not interfere although the addition of considerably more toluene to promote
Handbook Publishers, 1949. (6) Tizzard, H. T., 6.Cheni. Soc. (London),97, 24i7-90 (1910). (7) Wittmann, G., Angew. Chem.. 60, 33-6 (1948). RECEIVED 1Iarch 5, 1951.
Evaluation of Tread Wear DIETRICH G . STECHERT AND THOMAS D. BOLT Gates Rubber Co., Denver, Golo.
A need was realized for a tire wear rating in which all available measurements of tread depth are used, and which is independent of the mileage to which a tire has been tested. Possibilities of terminating tests early for economic reasons were anticipated. A method of analyzing tread wear measurements was developed, based on the hypothesis, substantiated by test results gathered during 2.5 years, that the log-log graph of tread depth loss versus mileage is linear. A single tire wear rating, independent of mileage, can be determined, which is considerably more reliable than the usual ratio of tread depth loss per mile at a certain mileage. The proposed method of analysis allows for more economical utilization of a tire test fleet and a more rapid turnover of ideas.
T
HE rate of ~ e i tofr a tire in service depends primarily on the
design of the tire, the properties of its component?, and the conditions to which it is subjected in service. This implies that problems of tire design and development are very complex, as must be well realized by those engaged in this type of work. The degree of success that can be achieved in tire development will, to a certain extent, depend on the availability of a simple and reliable method of analyzing experimental measurements on tire wear. In fact, great value would lie in a method that could serve as an industry standard. I t has been the common practice to use as a tire rating the last available meaeurement of miles per 0.001 inch of tread wear in a tire tept. The practice has a definite disadvantage in that con-
siderable emphasis is placed OII thc Inst measurenient, and all measurements prior to the last are diwegarded. Furthermore, such a rating may be unreliable, as it may, and in general does, vary with niileage. A method has been developed in which all esperirnental measurements of nonskid depth taken during a test run are incorporated in a single rating of tread wear for each tire tested. Essentially, the method consists of the utilization of a certain functional rclationship between nonskid loss and mileage. METHOD OF ANALYSIS
The proposed method of analyzing tread wear measurements is based on the hypothesis, substantiated by test results gathered
ANALYTICAL CHEMISTRY
1642
per hour a t night for passenger care, and 50 miles per hour day and night for trucks. Inflation Tested a t Initial Tire pressures are checked periodi% of Pressure Test cally. Tires are usually tested Figure Type of Test Tire Size Rated Load Lb./Sq. Idch Period Test Variables a t certain loads above rated 1 and 2 Fleet 7.60-16 low 114 24 Dec. '49- Tread stocks loads. Passenger test cars are pressure Apr. '50 3 a n d 4 Fieet 6.00-16 132 28 Nov. '47- Tread stocks and tire cords weight-compensrtted t o g i v e Feb. '48 equal loadin on all four wheels, s Fleet 10.00-20 145 70 Dec. '49- Competitive tires: different among whicf~tires are rotated Apr. '50 tire designs, stocks, cords, etc. Tread center and a p p r o x i m a t e l y e v e r y 1700 shoulder wear evaluation miles. On trucks, rotation is 6 and 7 Field service: 10.00-20 Varying 70 .Jan. '49- Tread stocks in half-and-half among drive wheels only. -411 traotor-trailer Bept. '49 tires transports wheels of test vehicles are 8 Field service: 6.50-15 Varying Varyinr Oct. '50- Camelback stooks containing checked for alignment weekly. taxicabs Nov. '50 breakout material The highest and lowest atmosDheric temDeratures of each day dong the paved test course are recorded; the averages of these over the duration of a test give some indication of the temperaduring 2.6 years, that the mathematical relationship of nonskid ture conditions of the test. Sonskid depth is measured every loss, y, or the decrease in nonskid depth from its initial value, t u 1700 miles to the nearest 0.001 inch at several equidistant points distance z over which the tire has been teeted is of the poaei around the tire. The field-service tests on tractor-trailer transports were contype: ducted in the Kansas City area primarily on paved highways. y = axb Tires were rotated about every SO00 miles among the drive wheels onlv. The field tests on taxicabs were made in the Denver area Plotted on log-log graph paper, y versus z is thus a straight line under any but controlled conditions. (see Figures 1 through 8). Constants a and b can be determined from the experimental data by means of a linear regression oi The data of these evaluations are shown graphically in Figure 1 log y on log z using the method of least squares. a and b define through 8 together with their regression lines. For the great wear-resistance properties of a particular tread stock in a tire of variety of test conditions and test variables shown in Table I, given design under given test conditions. the log-log graphs of nonpkid loss versus mileage are linear to a very high degree. No denial of this linearity has been found in the great volume of DISTANCE, 1000 MILES tire testing that has been conducted in 2.5 years by the Gates Rubber Co. This linearity is the basis for the proposed method of analysis of nonskid loss mileage data in evaluations of tread wear.
Table I.
Details of Some Tread Wear Tests
ANALYSIS OF GRAPHS
Mileages to baldness were computed for the data of Figures 1 through 8, and are indicated by short vertical lines a t the upper ends of the regression lines. A discussion of a comparisn of bald mileages to determine etatisticallv significant difference.. is gwen a t t h r end of this paper.
6
DISTANCE, 1000 MILES 8 10 w 304050
DISTANCE, 1000 M l E S Figure 1
If it is desirable to have a single rating, one of several may be used: 1. Mileage to baldness-that is, to the point on the regression line a t which total nonskid loes is equal to the initial nonskid depth. 2. Miles per 0.001-inch nonskid loss at baldness-that is, mileage to baldness divided by the initial nonskid depth in thousandths of an inch. In a relative evaluation of tires, thlh rating allows the comparison of mileages to baldness compenEated for any differencesin initial nonskid depths that may exist. 3. Amount of nonskid loss, taken from the regression line, at an arbitrarily chosen mileage. I t is best to upe a figure bawd on a relatively high mileage. APPLICATIONS OF METHOD
The proposed method of analysis has been applied to a large variety of tires in a great number of widely differht types of evaluations. Examples of some of these are listed in Table I, including both fleet and field service teats. Some information on test conditions may be of interest. Fleet tests were conducted by the tire test fleet of the Gates Rubber Co. in Arizona from November 1947 t o April 1950. Driving speeds are 60 miles per hour in the daytime and 50 miles
7.60-15 TIRES
o~c.39 -MAR.'W 4
6
810
20
30 40
DISTANCE, 1000 MILES Figure 2
Some facts about these regression lines should be noted, because they may suggest interesting investigation8 of tire road wear. In Figures 1 and 2 three tires of each of four stocks were tested. For each stock, the second tire was tested a t a higher mean atmospheric temperature than the first, and the third a t a higher temperature than the second (see Table 11). The results seem to indicate that the lower the temperature, the less the slope of the regression line, and the greater the mileage to baldness.
1643
V O L U M E 23, NO. 11, N O V E M B E R 1 9 5 1 Summary of Test Results
Table 11.
Mean
so.of
Tires Tested
Figure 'I'e+t Variables 1 and 2 S t u c k .4 Stock
s o . of I'ointe
s
1 1 1
H
4
3 I' 40-
F.
.4
b
52 57 60
- 0,8399
- 1.0447
-0,9056
0 8665 1 ,0672 1.0415
-0,9807 - 1.1533 - 1,0890
0.9595 1.0611 1,0527 0.8382 1.0487 0.9446
1
h
!I
ti
6
52 68 62
1 1
8
p1
-0.8709
62
-0.9216
53 62 62
0.8252 -0.7985 0.9358 -0.8928 - 1.0161 1.0371 - 0 . 3 2 5 6 0.7596 -0.4910 0 7189 - 0.5316 0.7649 -0,7135 0.7750
1
a
1 1
s
08
6
1
3 a n d l S t o c k C. curd 1 Stock C , cord 2 Stock A . curd 2 Stock B. curd 2 5 Treed renter, Cu. I Tread atioulder. Co. I Tread renter Co. I1 T r a d shuulder. C o . I1 6 arid 7 Stock A. truck 1 Stock B, trurk 1 Stock A. truck 2 Stock B. truck 2 Stock A, truck 3 Stock C, truck 3 Stock A . trucks 4 and 3 Stock C. trucks 4 and 3 Stock A. cahs 1 and 1 Stock B, cahe 1 a n d 2 Stock -4,cab 3 Stock B, cah 3
Constrtnts of
k:z,,R e g r e s s i o n Line
ii
30 51 50 51
34 33 3J
6
G 8
30
1
11
2
10
2 2
11
r,8 58 60 60
11 0 9 8 6
1,
/'
n
-1:
8 10 10
..
..
1 1 1 1
.. ..
>
-1.1703
- 0.6300 - 0.7.503 - 0.3886 -0,7418
0.8425 0.8754 0.7049 0 8663
-0.4183 -0.0772 - 0 . A867 - 0 , 1355 - 0 . 4684 -0.4472 -0 2321 -0 2607
0.9662 0.7686 1,0082 0.7804 0.9640 0.9698 0.8334 0.8610
-0.8830 -0 7349 - 0.6326 - 0,5579
1.1636 1,0520 1.0056 1.0134
Figures 3 and 4 are of a tread stock and tire cord Bald Orig. SE evaluation. Each combination Mileage, 111.'0 001 Depth. 0, ool 1000 at of stocks and cords was tested Miles Baldnes. Inch in six tires. Mean atmospheric 358 40.60 113.4 temperatures varied very little 31,40 357 88.0 3.59 26.26 70.4 during the test period. -4sta357 39.64 111.0 tistical comparison of the bald 357 40.52 113.5 360 36.56 101.6 mileages of stock C, cord 1, 49.76 3.56 139.8 and stock C, cord 2, is given 4 4 , 07 358 123.4 3.57 36.37 101.9 below. 43.55 358 121.6 In Figure 5 two tires of each 360 35.53 98.7 359 32.73 91.2 manufacturer w e r e t e s t e d . 360.0 26.36 73.8 Xonskid 10s. readings were 3.56.: 28.24 79.2 obtained in the center as well 27.38 357.7 76.5 357.8 43.15 120.6 as shoulder regions of the tread. 444.5 29.54 66,: Both were plotted as straight 531.5 451.0 33:61 74:5 lines on log-log paper. Figure 407.5 ... ... 5 gives an indication of the 1819 54.58 120 0 1817 64.84 120., uniformity of wear across the 1824 68.03 149.2 1826 61.63 135.1 tread: The company I tires 1821 61.41 134.9 wore less evenly, as the slopes 1811 57.32 126.6 1826 61.96 135.7 of the center and shoulder lines 1818 58.30 128.3 are different. Furthermore, the 316 14.57 46.1 315 14.87 47.2 company I tirea had consider317 13.41 42.3 ably more nonskid left in the 819 34.4 10.98 tread shoulder area when the tread centers were bald than the commnv I1 tires. In Figures 6 and 7 the total nonskid loss of the four drive wheel tires of each truck was plotted against mileage. The regression lines for truck 1 illustrate how misleading a rating of miles per 0.001-inrh nonskid loss taken at 15,000 or 20,000 miles can be, for a t such points stock A appears t o be definitely superior t o R , whereas actually both had about the same bald mileage.
- -
DISTANCE, 1000 MILES 4 6 810 20
30 40
'
30-
DISTANCE, 1000 MILES
3 4
50 40
I
z
3
6 810
4
Z O W
6 810
20 30
A
MANUFACTURED BY
-- - . . . -
A
I
DISTANCE, 1000 M I L E S Figure .'1 DISTANCE, 1000 MlLES
3
4
6
810
20
/
30
V
40-
30 -
I
4
6
810
2030
DISTANCE, 1000 MILES Figure 5
2 3 4 -~
6 810 to 30 DISTANCE, 1000 MILES Figure 4
40
Truck 2 shoxved a himilar large difference in slopes between atock8 A snd B. The evaluation of stocks A and C on trucks 4 and 5 resulted in data that scattered more from the regression lines than similar data on truck 3 alone. This is probably due to the fact that a test made on only one vehicle is a better controlled test than one made partly on one and partly on another vehicle. I n spite of this, and in spite of the crossing lines of trucks 4 and 5,the bald mileages fall in the same relative position in the two cases. Figure 8 pertains to tests of camelback (recapping material) containing breakout material for increased traction on mowcovered roads. Here the tests on cabs 1 and 2 seem to show con-
1644
ANALYTICAL CHEMISTRY
siderably less difference in bald mileage of the two stocks than that on cab 3. The above remarks on tests conducted partially on one and partially on another vehicle apply here as well. SIGNIFICAXCE OF WEAR-MILEAGE RELATION
The question may be asked: Why should the nonskid lossmileage curve be of the power type? A satisfactory answer cannot be furnished. If nonskid loss y is plotted against mileage x on linear graph paper, a curve papsing through the origin results.
DISTANCE, 1000 MILES
52-IO F 8 - TESTED ON TRUCK 1 t
M9 4 P
L3
‘?
82 20 30 40 60 DISTANCE, 1000 MILES
Figure 6
Mathematically y would increase without limit as x does. The curve would be concave toward the x-axis or toward the y-axis, depending on whether constant b is less or greater than unity, implying a decreasing or increasing rate of wear, respectively, as the test progresses. In most) cases it was found that b is less than unity (see Table 11), which means a decreasing rate of wear. This may be due to an increase in tread contact area caused by the growth of the tire, and to the geometry of the tread pattern and voids. Changes in tread radius during the test and in the tread movement pattern on the road may be partly responsible. bnother possible factor is a change in abrasion resistance of tread st,ocks with t,ime on test due to possible continued vulcanization, osidation, and other effects. The increasing rate of wear ;n the case of camelback containing breakout material is probably due, a t least in part, t o a decreasing contact area as breakout material is lost, and possibly to a decrease in abrasion resistance. In the evaluation reported in Figures 1 and 2 the change in b from less than to greater than unity with an increase in mean atmospheric temperature is probably due to a change in the abrasion resistance. STATISTICAL ANALYSIS OF TIRE WEAR
Linear Regression. The constants, a and b, in the relationship y = azb, which may also be writ’ten log y = log a b log 2, where y is nonskid loss and x is mileage, can be determined from a linear regression of Y = log y o n X = log z according to the equa-
+
tinns.
Dx = n Z X 2 - ( Z X ) z where n = number of pairs of values of X and I.’ Constants A and b reported in Table I1 were determined for y expressed in 0.1 inch and r in 1000 miles. Thus in the case of the first tire reported in the table: log y
=
- 0.8399
Whenx = 1,or 1000 miles, y 0.1446, or 0.015 inch.
=
+ 0.8665 log x
antilog A
=
antilog ( -0.8399)
=
In Table I1 in the case of Figures 3 to 7 data for several tires in each case were pooled. Where tread stocks, tire constructions, etc., are to be compared, individual regressions will have to be made for each tire, as explained below. I t is recommended that the first rot,ation cycle, in which a tire has been run once on each of the several wheel positions, be considered as a break-in cycle. Data obtained subsequent to the break-in cycle are then to be used in the regression. It is best t o use a number of datum points which is a multiple of four, if rotation is among four positions, so that there is equal represent,ation among positions. The distances covered for each position should be over the same test course and of equal length. Furthermore, it has been t’he practice to start any passenger tire test on front positions using dummy tires on rear positions, until the time of the first rotation for a particular vehicle. Mileage to Baldness. After A and b have been determined the mileage t o baldness, d,can be computed from log 2’ = (log y’-A)/b, where g’ is the initial tread depth. If desired, and this may be preferable, y’ may be defined as the initial tread depth minus an arbitrary depth such as 0.050 inch, in which case the tire would be considered bald when a tread depth of 0.050 inch has been reached. I t is common practice to measure tread depths a t the same ten points (in the center void, or alterhately on either side of the center rib) equally spaced around a tire throughout a test. The average of these ten readings is then computed for each mileage. The bald mileage determined from these i d 1 then be a function of he average appearance of the tire. If in a certain test four tires of the same population have been tested on the same car under identical driving and road conditions, then limits of uncertainty of the mean bald mileage can be computed from the four individual values. The method for doing t.his is given by the .hiencan Society for Testing >faterials ( I ).
Table 111. Comparison of Two Tire Constructions Car 1
2 3
Time Period 1 2 1
2
1
2
___
Bald Mileages for Tire Constructions c-223,120 23,360 25,150 24,860 32,010 28,410 34,350 33,300 25,060 26,640 23,200 27,280
c-1
Differences in Bald Mileages 240 - 290 3600 - 1050 1580 4080
-
~ ~ _ _ _ _ _ _ _ ~ . ~ _ _
Differences in Mileages to Baldness. In comparative tests of two different tread stocks under the same controlled conditions, such as in a half-and-half tire, or tires on test with frequent periodic rotation on the same car with the same driver over the same period of time, the question may arise whether the difference in bald mileages is great enough to be statistically significant. Or, what is the probability that the ratings of two tread stocks, in terms of bald mileages, could be estimates of identical true or objective values? The authors have found that in many testing programs a statistical t test for paired variates can answer the question. An example would probably explain this best. I n the testing illustrated in Figures 3 and 4 four tire constructions were investigated. A set comprised of one of each of the four constructions was tested on each of three cars over the same test course and over approximately the same time interval ~ i t h periodic rotation. Subse uently another set was tested in a similar manner on each of %e cars: Weather and road conditions as well as the effects of car and driver were therefore the same for each set of four tires. Thus, in order to compare two. of the constructions, such as C-1 and C-2, a t test for paired variates is in order. Table I11 shows the bald mileages computed as explained above for each of the six tires of each construction tested, as well as the differences in bald mileages of C-1 and C-2. The mean difference, d , is 1280 miles. The standard error of this mean is:
V O L U M E 2 3 , N O . 11, N O V E M B E R 1 9 5 1
Here n is the number of differences; in this case 6. Now the = 1.446. For 2 mean divided by its standard error is to be significantly different from zero, the mean divided by the standard error would have to be 2.571 or greater. This value is taken from a table of Student’s t , available in numerous texts on statistics ( d ) , for n - 1 = 5 degrees of freedom and a probability level of 0.05. As 1.466 is lees than 2.571, the conclusion is that the available data do not indicate any significant difference in means for tire constructions C-1 and C-2. In fact, the probability of no difference lies between 0.20 and 0.30. I t has been generally accepted that for a significant difference this probability must be lese than 0.05. The bald mileages of Table 111 were computed from all available dat:i, up t o about 23,000 miles. If bald mileages are computed 011 t h e basis of eight datum points (beyond the initial break-in cycle), i n this case up to about 12,000 miles, a t test for paired variates leads to the same conclusion as above-that is, no significant difference in C-1 and C-2, the probability of no difference being between 0.50 and 0.60. If this process is repeated for 12 and 16 datum points, up to about 17,000 and 21,000 miles, respectively, the probability of no difference is between 0.20 and 0.30. Furthermore, for each tire the differences in bald mileage based on eight points and based on all the available points were computed. The average difference was 1400 miles, and on test was not shown to be significantly different from zero. When this procedure was repeated for 12 and 16 points, the average differences were 560 and 180 miles, respectively, and both were not shown to be significantly different from zero. Thus little was gained in testing tires beyond t,he first 8 or 12 datum points after the break-in cycle, other than somewhat more accurate estimates of the bald mileages.
1645 ured directly, in principle. In practice, it is difficult thus to measure bald mileage directly, because tread depths are usually obtained a t certain specified intervals. Interpolation or extrapolation may be necessary. There are a number of ways in yhich this could be done. I t is the authors’ opinion, bmed on experience, that the use of a power type curve is one effective way, which also allows determination of bald mileage from a test discontinued prior to baldness. It is obvious that this analysis is based on the hypothesis of a power-type relationship between tread loss and mileage. This can be justified only on the basis of the euamination of a large number of diverse cases. Instead of determining the average bald mileage, it is possible to obtain a total of ten values for each tire, one for each point a t which measurements are made. A measure of the variance around one tire, which will also include experimental errors of measurement, can thus be obtained. The magnitude of experimental errors can be obtained by making several sets of measurements around each tire. An analysis of variance could then be performed to determine the effects of tread compounds, the variation of tires of the same tread, variations within a tire, esperimental errors, and possible interactions.
DISTANCE, 1000 MILES 2 3 4 6 8 1 0
1520
Tire wear can be measured in several ways. Some investigators ( 3 , 6) have expressed tire wear in terms of rate of wear and analyzed variance of the data to isolate the effects of tread compounds, tires, rotation cycles, rubbers, blacks, vehicle, wheel position, test conditions, and various interactions of these effects. Tests were designed to allow mch analyses to be made. hluch can be learned about the wear of tires and the effect of test conditionF if data are analyzed in this manner.
DISTANCE, 1000 MILES
Figure 8
The estent to which one should go in obtaining and analyzing tread wear data depends to a great extent on the magnitude of the differences t o be measured. In general, the smaller these differences, the greater the amount of replication needed, and vice versa. CONCLUSION
Figure 7
I t is the authors’ opinion that mileage to baldness is another valuable measure of tire weor, especially in view of the fact that the user of tires judges not only on the basis of rate of wear by examining his tires periodically, hut also, and possibly primarily, on the basis of the distance he can cover before his tires are bald. If tires are tested to the point where the tread depth is 0 or 0.050 inch, whichever is desired, the bald mileage can be meas-
The observed existence of a linear log-log relationship between nonskid loss and mileage in a great number of widely different types of tests may be exploited in order to realize substantial savings in the road testing of tires for tread wear. In many evaluations it is common practice for the Gates Rubber Co. to test tires to one half initial nonskid depth or to some arbitrary mileage only. The regression line and mileage to baldness are then determined. Of course, the greater the amount of data, and the more accurately controlled the conditions of testing, the more reliable will be the mileage to baldness. If in tread wear evaluations tests were terminated prior to baldness, about $180 could be saved for each passenger tire tested, and $490 for each truck tire, for every 10,000 miles. One investigation, to determine the effect of three different tire designs on tread wear, was made a t a total cost of $2200. If all tires had been tested to baldness, the cost would have been approximately $4600. In comparison with former common practice, the application of the proposed method of analysis of tire wear measurements can
ANALYTICAL CHEMISTRY
1646 result in more reliable tread wear evaluations, more economical utilization of the tire test fleet, and a more rapid turnover of ideas. ACKNOWLEDGMENT
The authors wish to thank the Gates Rubber CO.for the
LITERATURE CITED
(1) Am. SOC. Testmg Materials, “A.S.T.;LI. Manual Control of AMaterials,”Part 3, 1951.
011
Quahty
(2) Buist, J. *M., India Rubber
J.,121,180 (Aug. 4,1951). (3) Buist, J. M., et al., T r a m . I n s f . Rubber I d . , 26,288 (1950). (4) Freeman, H. A., “Industrial Statistics,” New York, John I T dey
Migration of Materials During Accelerated Aging by the Oxygen Pressure Method RlARION B. FACKLER
AND
JOHN S. RUGG, The Gates Rubber Co.. Denver, Colo.
This work was undertaken in an attempt to find the causes of unexpected variations in data on oxygen aging of vulcanized rubber and to show quantitatively the effects of a phenomenon which had been recognized previously but had received little study. It was shown that materials such as sulfur, accelerators, antioxidants, and metallic salts migrate from stock to stock during accelerated aging by the oxygen-pressure method, the effect is large enough to
T
HE oxygen-preesure method of accelerated aging is well established among the test techniques used by the rubber industry. A great deal of work has been done in evaluating the effect of various factors which influence the test data (4-,Q) and standard test procedures have been established ( 2 ) . I n spite of this, variations which are beyond normal experimental error still occur, especially n-hen unlike stocks are aged together in a bomb. AE a result of this type of teqt discrepancy this invefitigation was undertaken.
A I
I
B I
I/
I I
!
I
I
1860 23dOi 2600 lOd0 2400 TENSILE (psi) Figure 1. Comparison of Group and Individual Aging Characteristics of Typical Natural Rubber Tread Formulation Three diffsxent antioxidants
Several workers (8, 7, 9) have recognized the fact that when a heterogeneous group of stecks is aged in a single bomb, some materials migrate from one stock to another and act to change the apparent age resistance of all the stocks in the group. This action may serve either to increase or decrease t,heapparent resist-
be significant, and the results are unpredictable. The oxygen-pressure method of accelerated aging is well established in the rubber industry. A great deal of work has been done, which now must be. w n sidered of doubtful value because more than one stock was aged in a bomb at a time. Many specifications permit “community aging.” I t is rewmmended that specifications and practice be ohanged to specify individual bombs for each unlike stock.
ance to oxidation, depeiiding upon the nature of the migratory material and the stocks involved. .-i search of the 1iterat)ureon the subject failed to disclose specific materials which shon- this effect or the ext,ent to which the migration affected physical properties. This work shows that migration is not limited to any one material and that t,he effect,s on the stock:, are large enough to cause significant errors in test data. Because a primary purpose of an accelerated aging t,est is to rate the relative reeistancc to oxidation Jvhich is afforded to a stock hy an antioxidant. the majority of the data in this report are concerned with antioxidant. migration. However, the data show that materials such as sulfur, accelerators, anti copper salt8 also migrate and change appawnt age resistancrl. It is probable that the migratory tendencies are not limited to the relatively few materials mentioned in this report, but these are representative and probably cause the niofit drastic changes in physical properties. A very extensive investigat,ion would be necessary to classify d l conipounding materials into migrat,ory or nonmigratory p u p s . TEST METHODS
All aging wm carried out in Bierer-Davis oxygen bombs (2). -411 agings were made st 48 hours a t 80’ C. under 300 pounds per square inch ox gen ressure. Six samples of each stock were aged under e a c i con&tion, unless otherwise noted. All 8am Ies were from the same mix and the same cure. The bomb chamgers were thoroughly cleaned to remove any residual material from previous tests. Each stock was aged alone in the bomb and also In combination with other stocks. Tensile strength, per cent elongation, and Shore A durometer valuea were obtained. ANTIOXIDANT MIGRATION
Figure 1 shows the age resistance of a group of natural rubber tread-type stocks, identical except for antioxidant. To aeaure that the differences in test data were not due to accidental teat variations, repeated tests were made from a aingle mix and cure
