Having benefited from model-based design’s utility in simulation, verification and production implementation, organizations are looking to model-based techniques to ease the burden of compliance with industry standards and enable integration testing via simulation on multi-organizational programs.
High-integrity programs requiring compliance with industry standards such as DO-178B (guidelines for determining whether software will perform safely in an airborne environment) present unique challenges. The increased burdens of testing and artifact generation significantly increase cost.
Model-based design helps engineers achieve certification to safety standards by supporting requirement traceability, verification and documentation. Those capabilities span multiple design stages. For example, requirements linked to models are inserted as comments in generated code. Qualification kits, available for several verification tools, can reduce the amount of manual review needed.
It is also increasingly common for organizations to adopt model-based design on large programs spanning multiple organizations.
Doing so allows system-level performance to be assessed and integration issues to be uncovered much earlier in the design process. When detailed models from multiple organizations are combined, resulting models can contain hundreds of thousands of blocks. Modeling tools, such as Simulink, have evolved to meet such challenges with improved support for large-scale modeling, including support for composite models from other model files and support for signal buses.
Modeling standards are also becoming important for multi-organizational programs. Much as coding standards were adopted to facilitate team development and sharing of source code, modeling standards are being developed to support collaboration at the model level.
For example, the “Orion Guidance, Navigation and Control [GN&C] Matlab and Simulink Standards” document describes the modeling standards and guidelines that the Orion Crew Exploration Vehicle flight dynamics team used for GN&C algorithm development. The standards provide guidelines for aspects of the GN&C models—including stylistic rules, modeling tool selection and configuration settings—that affect model readability as well as the generated code.
As model-based design evolves, it is enabling a diverse and expanding group of organizations to improve efficiency, increase reuse and meet the challenges of developing aerospace and defense systems.
About the author:
Matt Behr is aerospace and defense industry marketing manager at MathWorks.
David Patterson, known for his pioneering research that led to RAID, clusters and more, is part of a team at UC Berkeley that recently made its RISC-V processor architecture an open source hardware offering. We talk with Patterson and one of his colleagues behind the effort about the opportunities they see, what new kinds of designs they hope to enable and what it means for today’s commercial processor giants such as Intel, ARM and Imagination Technologies.