Advanced science.  Applied technology.


Computational Reliability Analysis & Uncertainty Quantification

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SwRI staff develop and apply state-of-the-art probabilistic analysis tools to address challenging technology questions. These tools have been used successfully in complex, large-scale engineering applications across a wide variety of commercial sectors and government agencies. Many of these tools are implemented in our reliability and integrity software codes, such as the NESSUS software.

The SwRI staff has extensive experience and expertise with developing accurate and efficient probabilistic analysis techniques for predicting reliability in high-consequence engineering applications. When sufficient data are available, sophisticated and highly accurate statistical models of the inputs are developed and incorporated in the probabilistic analysis. In other cases where only sparse data are available, the staff has developed a novel method to incorporate expert opinion into the probabilistic analysis without introducing biases in the representation of the data using standard probabilistic models.


  • Statistical quantification of uncertainty
  • Estimation of extreme events
  • Time-series analysis
  • Random field modeling
  • Folding expert opinion into probabilistic analysis
  • Optimal decision making with incomplete information

Experience & Applications

  • Development and implementation of new probabilistic algorithms
  • Simulation of complex systems
  • Tailored probabilistic solutions for complex systems
  • Application in a wide range of sectors (government, automotive, aerospace, etc.)

Analysis Tools

  • NESSUS® software development
  • Integration of existing deterministic software in probabilistic tools
  • Development of customized routines and tools (FORTRAN, Matlab, etc.)