Citation

Rafaels KA, Bass CR, Panzer MB, Salzar RS. J. Trauma 2010; 69(2): 368-374.

Affiliation

Departments of Biomedical Engineering (K.A.R.) and Mechanical Engineering (R.S.S.), Center for Applied Biomechanics, University of Virginia, Charlottesville, Virginia; and; Department of Biomedical Engineering (C.R.D.B., M.B.P.), Duke University, Durham, North Carolina.

Copyright

(Copyright © 2010, Lippincott Williams and Wilkins)

DOI

10.1097/TA.0b013e3181e88122

PMID

20699746

Abstract

BACKGROUND:: Long-duration blasts are an increasing threat with the expanded use of thermobaric and other novel explosives. Other potential long-duration threats include large explosions from improvised explosive devices, weapons caches, and other explosives including nuclear explosives. However, there are very few long-duration pulmonary blast injury assessments, and use of short-duration exposure injury metrics is inappropriate as the injury mechanism for long-duration exposures is likely different from that of short-duration exposures. METHODS:: This study develops an injury model for long-duration (>10 milliseconds positive overpressure phase) blasts with sharp rising overpressures. For this study, data on more than 2,730 large animal experiments were collected from more than 55 experimental studies on blast. From this dataset, nearly 850 large animal experiments were selected with positive phase overpressure durations of 10 milliseconds or more. Various models were evaluated to determine the best fit of injury risk as a function of pressure and duration. A linear logistic regression was performed on the experimental data for threshold injury and lethality in terms of pressure and duration. The effects of mass, pressure, and duration scaling were all evaluated, and two goodness-of-fit indicators were used to assess the different models. RESULTS AND CONCLUSIONS:: New injury risk assessment curves were determined for both incident and reflected pressure conditions for reflecting surface and free-field exposures. Position dependent injury risk curves were also determined. The resulting curves are an improvement to existing assessments, because they use actual data to demonstrate theoretical assumptions on the injury risk.

Language: en