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Monte Carlo Simulation Tool Determines Logistical Support Resources Scenarios
August 16, 2011

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Researchers at NASA's Johnson Space Center have developed a Monte Carlo simulation tool that assists the International Space Station (ISS) program with determining logistics support resources. The functional Availability Simulation Tool (fASTER) simulates a multitude of different operational scenarios and allows for the effects of complex program resource restrictions and constraints including, crew maintenance time, carrier upmass capability, and sparing postulate. fASTER uses orbital replacement unit (ORU) reliability data and operational constraints to compute an average expected availability over time at the ORU level and at the functional level. Based on the expected ORU failure rate distribution, the model uses a random number generator process to simulate failures over the life of the station. The tool runs on a desktop personal computer and uses an intuitive user interface that facilitates fast set-up of each model simulation.


  • Precise: Produces consistently accurate predictions
  • Flexible: Suits ever-changing configuration and operational priorities
  • Quantified: Measures risks to logistics support requirements
  • Productive: Reduces potential data errors and training time due to descriptive input screens and data field automation


  • Organizations designing, planning, and supporting new space vehicles

Licensing and Partnering Opportunity

This technology is being made available through JSC's Technology Transfer and Commercialization Office, which seeks to transfer technology into and out of NASA to benefit the space program and U.S. industry. NASA invites companies to consider licensing this technology for commercial applications.

Contact Information

If you would like more information about this technology or about NASA's technology transfer program, please contact:

Technology Transfer and Commercialization Office
NASA's Johnson Space Center
Phone: 281-483-3809
E-mail: jsc-techtran@mail.nasa.gov

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Page Last Updated: January 16th, 2014
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