Air gaps entrapped in protective clothing are known as one of the major factors affecting heat transfer through multiple layers of flexible clothing fabrics. The identification and quantification of the air gaps are two aspects of a multidisciplinary research effort directed toward improving the flame/thermal protective performance of the clothing. Today's three-dimensional (3-D) whole body digitizers, which provide accurate representations of the surface of the human body, can be a novel means for visualizing and quantifying the air gaps between the wearer and his clothing. In this paper we discuss how images from a 3-D whole body digitizer are used to determine local and global distributions of air gaps and the quantification of air gap sizes in single and multilayer clothing systems dressed on a thermal manikin. Examples are given that show concordance between air gap distributions and burn patterns obtained from full-scale manikin fire tests. We finish with a discussion of the application of air gap information to bench-scale testing to improve the protective performance of current flame/thermal protective clothing.

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The head represents approximately 9% of the body area exposed in combat yet receives approximately 20% of all "hits." The desirability of protecting this vital structure would appear self-evident. Helmet design is a complex issue. Factors that designers of United States Army helmets thoughtfully consider include weight, ballistic qualities of the construction material, balance, helmet-to-person interface (comfort), maintenance of vision and hearing, equipment and weapon compatibility, ease of modification, available materials and manufacturing techniques, durability, ease of decontamination, disposability, and cost. The envisioned future role of the infantryman will make the interplay among these factors even more daunting.

The use of 3D scanning systems for the capture and measurement of human body dimensions is becoming commonplace. While the ability of available scanning systems to record the surface anatomy of the human body is generally regarded as acceptable for most applications, effective use of the images to obtain anthropometric data requires specially developed data extraction software. However, for large data sets, extraction of useful information can be quite time consuming. A major benefit therefore is to possess an automated software program that quickly facilitates the extraction of reliable anthropometric data from 3D scanned images. In this paper the accuracy and variability of two fully automated data extraction systems (Cyberware WB-4 scanner with Natick-Scan software and Hamamatsu BL Scanner with accompanying software) are examined and compared with measurements obtained from traditional anthropometry. In order to remove many confounding variables that living humans introduce during the scanning process, a set of clothing dressforms was chosen as the focus of study. An analysis of the measurement data generally indicates that automated data extraction compares favorably with standard anthropometry for some measurements but requires additional refinement for others.

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