Dynamic modeling of crew performance for long duration space missions

Sara Goudarzi, Jim Cavazzoni, Arend-Jan Both

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations


Long duration space mission crews will have to perform a myriad of tasks under extreme conditions for exploratory and settlement missions. The primary goal for any mission is the achievement of specific scientific endeavors and the maintenance of a safe crew environment. Stressors such as isolation, confinement, microgravity, extraneous work schedules, and crew heterogeneity are examples of elements that may alter the consistency of crew performance. It is critical to predict the influence of such stressors on crew performance for designing successful and safe mission scenarios. In order to assist in the future planning of long duration space missions, the Systems Integration, Modeling and Analysis team of the NJ-NSCORT has developed an interactive top-level model of an Advanced Life Support System (ALSS). Specifically, this dynamic ALSS model consists of a biomass production unit, a food-processing unit, a waste processing and resource recovery unit, and a crew model that defines human requirements. The crew model, which had previously been developed as a simple tool to examine physical requirements such as calorie intake and oxygen consumption based upon habitat conditions and specific human characteristics, has now been expanded to include physiological and psychological stressors to better determine overall crew performance. This expanded crew model will aid in estimating crew time requirements more effectively for varying mission scenarios, and may be used for evaluating how planned and random external and internal events affect crew performance.

Original languageEnglish (US)
StatePublished - Dec 1 2002
Event32nd International Conference on Environmental Systems - San Antonio, TX, United States
Duration: Jul 15 2002Jul 18 2002


Other32nd International Conference on Environmental Systems
Country/TerritoryUnited States
CitySan Antonio, TX

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering


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