SwRI Software

• 3DStress^®
  3DStress^® interactively analyzes the tendency for geological faults and fractures to slip or dilate based on a user-specified three-dimensional stress state.
  
  
• COATLIFE
  COATLIFE is a life-prediction software developed at SwRI under DOE and EPRI sponsorship, for predicting the remaining life of combustion turbine coatings in land-based gas turbine machines.  COATLIFE 4.0 is currently utilized or evaluated by a number of plant operators for assessing coating conditions during service.
  
  
• DARWIN^® 
  DARWIN calculates the probability of fracture of gas turbine engine components and other highly stressed mechanical systems by integrating 2D and 3D finite element models and stress analysis results, fatigue crack formation and growth analyses, material anomaly data, probability of anomaly detection, and inspection schedules. Specialized analysis modes include hard alpha anomalies in titanium rotors, materials with large numbers of inherent anomalies, and surface damage in all rotor materials. The software also indicates the regions of the component most likely to fracture, and the risk reduction associated with single and multiple inspections. DARWIN received an R&D 100 Award in 2000.
  
  
• NASGRO^®
  NASGRO is a suite of fracture mechanics and fatigue crack growth analysis computer programs that perform assessments of structural life, compute stress intensity factors, and process and store fatigue crack growth properties. Working closely with NASA and industry, SwRI releases new versions of NASGRO annually with many new features. Recent enhancements include many new K solutions, residual stress capabilities, increased speed, new GUIs, residual strength diagrams, spectrum editing, temperature effects, cyclic shakedown models, cycle counting algorithms, and a revised material database. NASGRO received an R&D 100 Award in 2003 and the NASA Software of the Year award in 2003.
  
  
• NESSUS^®
  NESSUS is an award-winning computer program employing state-of-the-art methods for performing probabilistic analysis of structural/mechanical systems. NESSUS can be used to assess component/system reliability, to identify important random variables, to provide information for risk-based decision analysis and reliability-based optimization, and develop designs that are more cost-effective and reliable than those developed using traditional deterministic design methods.
  
  
• Olympus DISS^®
  Olympus DISS® is a web-based geographical data and information sharing system designed to search and retrieve geographic data at its source. Olympus DISS® uses established data standards, reference such as the Federal Geographic Data Committee standard, providing a flexible mechanism to build applications upon.
  
  
• Project Information Management System (PIMS)
  PIMS is an integrated web-based project management tool that allows project managers to coordinate and complete many project management activities online, using any web browser. PIMS supports many functions in individual modules, such as action item tracking, risk management, online checklists, non-conformance reporting, and document and image management.  Each of these modules can be customized to meet the needs of different projects, and one module -- the custom module -- can be designed completely by project managers to track any function. 
  
  
• RAPTOR^®
  The Rapid Automotive Performance Simulator (RAPTOR^®) is an award-winning commercial off-the-shelf (COTS) modular simulation software for configuring, assessing and optimizing system performance for any on-highway vehicle allowing engineers to model and test virtual vehicle systems.
  
  
• Southwest Data Display and Analysis System (SDDAS™)
  SDDAS™ is a flexible multi-mission/ multi-instrument software system intended to support space physics data analysis. SDDAS allows data in distributed archives from many different satellites and other sources to be displayed and analyzed using a diverse set of graphical applications. Rather than emphasizing the cataloging of data, the SDDAS stresses the ability to visualize data quickly. The SDDAS approach is adaptable to advances in computer technology, thus giving the scientist a toolbox that can bridge the gap between data and scientific insight.

   

January 24, 2012