Using ASTM Standard Guide G 88 To Identify and Rank System-Level Hazards in Large-Scale Oxygen Systems
Bibliographic record
Abstract
Performing hazards analyses and fire risk assessments on oxygen systems is critical to ensure that a system design has a low probability of ignition and a low consequence of ignition. Historically several different methods have been used to identify and evaluate fire hazards in oxygen systems. Most of these methods, however, are designed for detailed materials or component analyses, and can be impractical for large-scale oxygen systems with many components and even multiple end processes. Wendell Hull & Associates, Inc. (WHA), in conjunction with Oxygen Safety Consultants, Inc. and INCO Ltd., has developed an efficient approach to identify and evaluate hazards in large-scale oxygen systems. The WHA oxygen hazards and fire risk assessment process considers the important aspects of oxygen system safety as they relate to design, cleaning, operations and maintenance, and uses ASTM Standard Guide G 88 as a basis for quickly identifying and ranking system-level oxygen hazards. ASTM G 88 is a standard guide for oxygen system design containing many system-level factors known to contribute to ignition and propagation of fires. The WHA analysis process applies ASTM G 88 at the system level, using both schematic analysis and visual inspection to systematically assign a hazard severity ranking to all system components, allowing components that possess the greatest risk of ignition and fire propagation to be quickly identified and further evaluated. This paper describes the WHA oxygen hazards and risk assessment method, using ASTM G 88 to quickly identify and assign a hazards severity ranking to components in large-scale oxygen systems.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.018 |
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".