Bibliographic record
Abstract
THOSE OF US ASSOCIATED WITH THE PETROLEUM industry know that crude oil and the various petroleum fractions and products derived from it consist of a complex mixture of various components, mostly hydrocarbons. Some of these components are quite volatile, and some are not so volatile. It is fairly recognized that the different petroleum fractions and products have inherent volatility characteristics. Volatility is defined as the tendency or ability of a material to change from a liquid state to gaseous state. When dealing with petroleum products, the principal volatility characteristics that are significant are distillation, vapor pressure, and flammability. This manual deals with the practice of distillation and vapor pressure measurement either in the laboratory or at on-line facilities. Although flammability characteristics of various petroleum products measured by flash point determination provide significant volatility information, this work specifically excludes discussion of flash point measurement because there is a separate manual currently being written on the subject of flash point measurement in petroleum products. The chapters that follow provide information and discussions on the different aspects of measuring distillation and vapor pressure characteristics, with the purpose of clarifying and providing a better understanding of the various test methods. This work focuses on current standard test methods used by practitioners of distillation and vapor pressure measurements in the petroleum industry world-wide. Specifically, the standard test methods discussed are American Society for Testing and Materials (ASTM International) test methods, recognizing that there are equivalent and/or similar standard test methods in other countries as well. A cross reference of ASTM with other national standards from various countries (if known or available) are given in the appropriate chapters. The significance and use of the measured distillation and vapor pressure characteristics are covered in the chapters on specific petroleum products, such as spark-ignition engine fuels, diesel and other middle distillate fuels, aviation fuels, crude oil, liquefied petroleum gas, and hydrocarbon solvents. Laboratory testing or measurement of the various properties and characteristics of various petroleum fractions and products serves to provide information about these materials, which can be used for research purposes, refinery plant control, and verifying the conformance to specified values in product specifications. Necessarily, the complexity of the test methods used must be consistent with the accuracy required to provide convenient and timely data about the characteristics of the materials being tested. The test methods must be standardized so that reproducible results may be obtained by different operators in various region or parts of the world using similar test equipment. ASTM test methods are widely used all over the world, and the test methods and specifications covered in this work are prime examples of standardized test methods that have withstood the test of time since their early inception.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.149 | 0.111 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".