Issues in the Development of Automatic Thermal Control for Portable Life Support Systems

Smith, Leslie F.; Campbell, Anthony B.; Nair, Satish S.; Miles, John B.; Webbon, Bruce W.

doi:10.4271/941383

Cited by 9 publications

(2 citation statements)

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“…Automatic cooling control would resolve these problems by matching cooling to actual needs, and relieve the individual from a distracting task [1]. Several attempts have been made to develop an automatic inlet temperature controller based on various inputs such as oxygen consumption rate, heart rate, skin temperature, sweat rate, ear canal temperature, carbon dioxide production, LCG inlet temperature, temperature change across LCG, and LCG heat removal rate [29,63]. Even though these controllers work for certain conditions, they do not work well over the wide range of conditions experienced by the astronaut [63] and have not found widespread implementation [3].…”

Section: Performance Issuesmentioning

confidence: 99%

“…The one dimensional thermoregulatory models discussed so far are inappropriate to use when the boundary conditions vary significantly around the body. Examples of such situations include the accidental cold immersion victim who is floating in a buoyant survival suit [17], and the nonuniform thermal environments experienced by astronauts during EVAs [63]. In addition, if one intends to compute very accurate temperature profiles within a body segment, one needs to consider the inhomogeneous and asymmetrical tissue composition [6].…”

Section: Multi-dimensional Thermoregulatory Modelsmentioning

confidence: 99%

See 1 more Smart Citation

An Improved Thermoregulatory Model for Cooling Garment Applications With Transient Metabolic Rates

Westin

Kapat

Chow

2008

Volume 10: Heat Transfer, Fluid Flows, and Thermal Systems, Parts A, B, and C

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Current state-of-the-art thermoregulatory models do not predict body temperatures with the accuracies that are required for the development of automatic cooling control in liquid cooling garment (LCG) systems. Automatic cooling control would be beneficial in a variety of space, aviation, military, and industrial environments for optimizing cooling efficiency, for making LCGs as portable and practical as possible, for alleviating the individual from manual cooling control, and for improving thermal comfort and cognitive performance. In this study, we adopt the Fiala thermoregulatory model, which has previously demonstrated state-of-the-art predictive abilities in air environments, for use in LCG environments. We validate the numerical formulation with analytical solutions to the bioheat equation, and find our model to be accurate and stable with a variety of different grid configurations. We then compare the thermoregulatory model's tissue temperature predictions with experimental data where individuals, equipped with an LCG, exercise according to a 700 W rectangular type activity schedule. The root mean square (RMS) deviation between the model response and the mean experimental group response is 0.16°C for the rectal temperature and 0.70°C for the mean skin temperature, which is within state-of-the-art variations. However, with a mean absolute body heat storage error BHS ε of 9.7 W·h, the model fails to satisfy the ±6.5 W·h accuracy that is required for the automatic LCG cooling control development.In order to improve model predictions, we modify the blood flow dynamics of the thermoregulatory model. Instead of using step responses to changing requirements, we introduce exponential responses to the muscle blood flow and the vasoconstriction command. We find that such modifications have an insignificant effect on temperature predictions. However, a new iv vasoconstriction dependency, i.e. the rate of change of hypothalamus temperature weighted by the hypothalamus error signal (ΔT hy ·dT hy /dt), proves to be an important signal that governs the thermoregulatory response during conditions of simultaneously increasing core and decreasing skin temperatures, which is a common scenario in LCG environments. With the new ΔT hy ·dT hy /dt dependency in the vasoconstriction command, the BHS ε for the exercise period is reduced by 59% (from 12.9 W·h to 5.2 W·h). Even though the new BHS ε of 5.8 W·h for the total activity schedule is within the target accuracy of ±6.5 W·h, BHS ε fails to stay within the target accuracy during the entire activity schedule. With additional improvements to the central blood pool formulation, the LCG boundary condition, and the agreement between model set-points and actual experimental initial conditions, it seems possible to achieve the strict accuracy that is needed for automatic cooling control development. v ACKNOWLEDGMENTS

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