In recent years, industry and government have begun adopting Model Based Engineering (MBE) practices in an unprecedented way. No longer exclusively the domain of isolated experts, MBE has been implemented across the full product lifecycle. This success is, however, giving rise to new challenges. The ability to share disparate models across teams, organizational boundaries, and among communities of practice is important for collaboration on complex projects. Model reuse is important because it minimizes the need to “re-invent the wheel” for each new project or initiative. Additionally, organizations face the challenge of model traceability and results repeatability. Both these qualities are critical in the lifecycle of an engineering product, and far too often is not attended to until a crisis occurs. Phoenix Integration proposes to address these challenges by developing an analysis model sharing platform, coupled with a reliable and repeatable way of deploying those analysis models. This platform will be easy-to-use, web-based, and built on the Git version control system. This model-sharing platform will have provision for documentation, tags and metadata. Software containerization is used to ensure a stable and repeatable analysis execution platform. This ensures that given a set of inputs, running the same analysis or workflow will always yield the same results. Shared analyses and workflows would be easily run in ModelCenter®, as well as on web-interfaces. It will rely on cloud computing resources with on-demand provisioning and execute the analyses and workflows on them when requested. Additionally, published analyses and workflows would be verified automatically whenever supporting software versions change.
A successful project will help NASA further advance the MBE vision and will help enable more comprehensive, broader, and deeper modeling efforts across all of NASA’s programs. Specifically, the project will help NASA to share engineering models and workflows across teams, organizational boundaries, and among communities of practice. It will also enable model traceability, repeatability and reusability. These capabilities will directly benefit ongoing and future NASA projects and initiatives, such as the Mars 2020 and Europa Clipper missions.
We propose developing an easy-to-use analysis sharing platform, while enabling reliable model executions. Executing these analyses on cloud computing resources opens the possibility of easy accessibility, including automatic model verification. This can be used across all areas of engineering, including those in the aerospace & defense, automotive, scientific research and heavy industries.