Cerebral Blood Flow Based Computer Modeling of Gz-Induced Effects [supporting dataset]

Abstract of the final report is stated below for reference: There is continued interest in acceleration (G) effects in civil aviation, as G-induced loss of consciousness (G-LOC), impaired consciousness, and visual effects play a role in aerobatic, agricultural, and military aviation accidents. Methods: A software model (the Civil Aerospace Medical Institute G-Effects Model [CGEM]) based on physical and physiological variables related to inflight tissue resupply, using oxygen flow as a proxy for supply availability, was developed to evaluate risk of G-LOC and related phenomena in aeronauts. Aeronauts were modeled using several parameters, including sex, cardiovascular fitness, and other common modifiers such as G-suits, positive pressure breathing gear, anti-G straining and other muscle-tensing. The software was validated by comparison with experimental data from the peer-reviewed literature. Results: CGEM predicted physiological effects of Gz exposure accurately, particularly for rapid onset rates. Predicted times to G-LOC and absolute incapacitation periods were consistently within one standard deviation of pooled results obtained during centrifuge experiments using U.S. Navy (USN) and U.S. Air Force (USAF) pilots. Predictions of G tolerance based on visual effects onset also compared well with published data, as did evaluation of symptoms expected during a difficult aerobatic maneuver. Discussion: CGEM is a new tool for civil and military aviation. Rather than providing a simple G tolerance number, through proper selection of parameters flight surgeons, pilots, and accident investigators can gain insight into changes in risk from factors such fatigue, medications, dehydration, and anti-G countermeasures used.


  • English

Media Info

  • Media Type: Dataset
  • Edition: v1.0.1
  • Dataset publisher:



Subject/Index Terms

Filing Info

  • Accession Number: 01883992
  • Record Type: Publication
  • Created Date: May 31 2023 10:16AM