Corrosiveness to copper from petroleum products by Copper Strip test
13. Report
13.1 Report the corrosiveness in accordance with one of the classifications listed in Table 1. State the duration of the test and the test temperature in the following format:
Corrosion copper strip (Xh / Y°C), Classification Zp where:
X = test duration, in hours,
Y = test temperature, °C,
Z = classification category (that is, 1, 2, 3, or 4), and
p = classification description for the corresponding Z (for example, a, b).
14. Precision and Bias
14.1 In the case of pass/fail data, no generally accepted method for determining precision is currently available, except for gasoline sample types (see 14.1.1 and 14.1.2). Bias has not been determined for this test method.
14.1.1 Based on a 2008 gasoline interlaboratory study that was conducted, involving 18 laboratories receiving a randomized set of 12 gasoline samples, it was determined that pre-polished copper strips provided statistically "equivalent" results as compared to manually prepared copper strips (that is, the degree of predictable disagreement between pre-polished and manually polished copper strips was not statistically significant). In addition, the precision information in 14.1.2 was determined by the statistician as part of this study.
14.1.2 Since results by this test method are nonnumerical and involve multi-categoric rating classifications (for example, 1, 2, 3, and 4) and classification descriptions (for example, a, b, c, etc.), conventional D02 statistical techniques, such as Practice D6300, are not suitable for determining precision. Instead, a statistical simulation approach was used to mathematically assess the "degree of disagreement" under repeatability ("r") and reproducibility ("R") conditions for the ILS data set. Based on the statistical approach followed, no statistically significant difference in disagreement percentages between r and R conditions was determined for rating classifications in category 1, 2, and 3. For rating classification 4 however, samples showed more within-classification disagreement. Based on this information, the statistician determined that in the long run, the precision of the analysis (that is, both "r" and "R") is that there is nominally a 5% chance that a difference between any two ratings will exceed the criteria in Table 2.
15. Keywords
15.1 automotive gasoline; aviation gasoline; aviation turbine fuel; copper corrosion; copper strip; corrosiveness to copper; natural gasoline
