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Technical Paper

Enhancement of the Sequence IIIG by the Study of Oil Consumption

2004-06-08
2004-01-1893
The Sequence IIIG is a newly developed 100 hour test used to evaluate the performance of crankcase engine oils in the areas of high temperature viscosity increase, wear, deposits, pumpability, and ring sticking for the North American GF-4 standard. Data from the ASTM Precision Matrix, completed in the spring of 2003, along with early reference data from the Lubricant Test Monitoring System (LTMS) showed unexpected test results for selected oils and indicated that percent viscosity increase and pumpability were highly correlated with oil consumption. This correlation led to an intensive study of the factors that influence oil consumption and an attempt to compensate for non-oil related oil consumption through a model based adjustment of the results. The study and scrutiny of the IIIG data has led to more uniform oil consumption in the test and improved test precision, and has eliminated the need for a correction equation based on non-oil related oil consumption.
Technical Paper

Use of Virtual Tests in Establishing BOI/VGRA

2002-10-21
2002-01-2675
The Engine Oil Industry Base Oil Interchange (BOI) and Viscosity Grade Read Across (VGRA) guidelines developed by the American Petroleum Institute (API) provide a means to significantly reduce the time to market for current technology oils. The guidelines also allow conversion of a fraction of the millions of dollars spent each year on engine testing in pursuit of API engine oil licensing into research testing and the development of fundamental knowledge. In the past, guidelines have been developed based upon a general assessment of minimal engine test data. Recently, however, regression models have been used to assess Base Oil and Viscosity Grade effects. The use of statistical regression models and Virtual Tests in determining effects to establish BOI and VGRA has several advantages. These advantages, demonstrated through an example and a case study, include volume of data and breadth of data.
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