Mark Hepokoski

A systematic approach to the development and validation of adaptive manikins

Recent advances in computation technologies have facilitated computer simulation of human physiological regulation mechanisms at high spatial and temporal resolution. Improvements in manufacturing techniques and control strategies have resulted in the development of advanced thermal manikins. However, the broader acceptance of human thermophysiological simulation via modelling and measurement tools is limited by the scarce public domain resources and availability of validation data supporting such tools [1]. In this study a systematic approach to the development and validation of thermophysiology models and adaptive manikins was developed. This approach is based on both the evaluation of manikin responsiveness - to be able to follow the course of human physiological responses, and the adequate validation of an adaptive manikin against human experiments representing groups with increasing complexity of exposure.

Improving the accuracy of infrared measurements of skin temperature

In principle, infrared (IR) imagery of exposed skin and clothing can provide a valuable source of data for thermo-physiological studies. In practice, and despite the fall in the cost of IR cameras, infrared imagery is not universally collected during human subject testing. One reason for this may be the relatively poor accuracy of IR cameras (typically ±2 °C). The repeatability of the measurements taken with a particular IR camera (both spatially and temporally) is much better than its accuracy, i.e., close to the cameras sensitivity. An IR cameras sensitivity (and repeatability) is typically on the order of hundredths of a degree Celsius. Consequently, a reference with known temperature and emissivity placed in the cameras field-of-view when taking measurements can provide two potential benefits: First, measurement error can be reduced by using a calibration procedure. Second, IR imagery taken by different IR cameras during different test episodes can be directly compared.

A thermo-physiological description of a 50th percentile Western female.

Thermophysiological models are used to predict thermal sensation, thermal comfort and human effectiveness for a wide range of environmental conditions. Typically, such models are based on the anatomy and physiological responses of an adult male. The objective of this study was to develop an adult female model and test it against experimental results from the literature.

Improved EO/IR target and background scene simulation with MuSES using a rapid fluid flow solver

The ability to accurately predict electro-optical signatures for high-value targets in an outdoor scene is a tremendous asset for defense agencies. In the thermal infrared wavebands, physical temperature is the primary contributor to imager-detected radiance. Consequently, enhancements to the fidelity of thermal predictions are desirable, and convection estimates are often the most significant source of uncertainty. One traditional method employed by MuSES applies a single global convection coefficient across the entire scene, and assumes that all exposed surfaces are in contact with the ambient air temperature. This results in a rapid prediction of convection coefficients for a large scene that changes dynamically with wind speed but lacks localized detail concerning how each target surface can experience a different convection coefficient and local air temperature. In practice, wind speed and directions typically change frequently, which coupled with the thermal mass of most targets reduces the negative impacts this approach can have on thermal predictions; numerous validations of MuSES predictions bear this out. Computational fluid dynamics (CFD) simulations provide additional spatial fidelity in the calculation of localized convection coefficients and air temperatures but only at great computational cost. A fully transient outdoor scene simulation would be nearly impossible. Boundary layers near surfaces must be resolved with a fine mesh, creating a numerical problem difficult to solve for large spatial scales when spanning large periods of simulated time. In this paper, a novel thermal fluid flow solver is presented. This proprietary flow solver models fluid flow at the spatial resolution and accuracy needed for convective heat transfer at the scale viewed by EO/IR (Electro-optical/Infrared) sensors, avoiding the burdens associated with conventional CFD codes. Many of the same Navier-Stokes equations are solved, albeit in simpler form. ThermoAnalytics-developed correlations directly calculate convection coefficients based on local bulk flow conditions of temperature, velocity, and pressure. The resulting accuracy is a large step beyond using a constant convection correlation universally across the scene. Intelligent simplification of the flow equations provides robust efficiency, requiring minimal effort and expertise compared to CFD codes.

Multiwaveband simulation-based signature analysis of camouflaged human dismounts in cluttered environments with TAIThermIR and MuSES

The ability to predict electro-optical (EO) signatures of diverse targets against cluttered backgrounds is paramount for signature evaluation and/or management. Knowledge of target and background signatures is essential for a variety of defense-related applications. While there is no substitute for measured target and background signatures to determine contrast and detection probability, the capability to simulate any mission scenario with desired environmental conditions is a tremendous asset for defense agencies. In this paper, a systematic process for the thermal and visible-through-infrared simulation of camouflaged human dismounts in cluttered outdoor environments is presented. This process, utilizing the thermal and EO/IR radiance simulation tool TAIThermIR (and MuSES), provides a repeatable and accurate approach for analyzing contrast, signature and detectability of humans in multiple wavebands. The engineering workflow required to combine natural weather boundary conditions and the human thermoregulatory module developed by ThermoAnalytics is summarized. The procedure includes human geometry creation, human segmental physiology description and transient physical temperature prediction using environmental boundary conditions and active thermoregulation. Radiance renderings, which use Sandford-Robertson BRDF optical surface property descriptions and are coupled with MODTRAN for the calculation of atmospheric effects, are demonstrated. Sensor effects such as optical blurring and photon noise can be optionally included, increasing the accuracy of detection probability outputs that accompany each rendering. This virtual evaluation procedure has been extensively validated and provides a flexible evaluation process that minimizes the difficulties inherent in human-subject field testing. Defense applications such as detection probability assessment, camouflage pattern evaluation, conspicuity tests and automatic target recognition are discussed.