Prediction of physical workload in reduced gravity

Abstract

As we plan for long-term living and working in low-gravity environments, a system to predict mission support requirements, such as food and water, becomes critical. Such a system must consider the workload imposed by physical tasks for efficient estimation of these supplies. An accurate estimate of human energy expenditure on a space station or lunar base is also necessary to allocate personnel to tasks, and to assign work-rest schedules. An elemental analysis approach for predicting one's energy expenditure in industrial jobs was applied to low-gravity conditions in this paper. This was achieved by a reduction of input body and load weights in a well-accepted model, in proportion to lowered gravity, such as on the moon. Validation was achieved by applying the model to Apollo-era energy expenditure data. These data were from simulated lunar gravity walking studies, observed Apollo 14 walking, simulated lunar gravity upper body torquing, and simulated lunar gravity cart pulling. The energy expenditure model generally underpredicted high energy expenditures, and overpredicted low to medium energy expenditures. The predictions for low to medium workloads were, however, within 15-30% of actual values. Future developmental work will be necessary to include the effects of traction changes, as well as other nonlinear expenditure changes in reduced gravity environments.