Enabling Ontology-driven Workflows for ACO's Dyreqt Modeling Framework

Project Objective

This proposal seeks to upgrade the Advance Concepts Office (ACO) Dyreqt modeling framework with ontological reasoning and data structures, an advancement that will dramatically improve productivity by enabling automation of large portions of the campaign architecting process.

Project Description

The ACO relies heavily on its in-house developed Dyreqt modeling framework for solving multidisciplinary analysis and optimization problems, performing systems analysis studies, and synthesizing exploration campaigns. Dyreqt regularly solves problems made up of thousands of models and hundreds of thousands of variables. The current bottleneck in workflows using Dyreqt lies in the custom scripting required to implement architecting logic and functional requirements into the problem specification. This up-front step in the workflow frequently dwarfs the actual analysis time, as it is a primarily manual process. This project will explore introducing an ontology and logical reasoning engine to enable automation of large portions of the problem specification, providing a higher level "language" in which Dyreqt problems can be constructed.

Project Results and Conclusions

This project researched, developed, and successfully completed a proof-of-concept for adopting ontology-driven workflows in early-stage space exploration campaign formulation and synthesis. Demonstrations of ontological reasoning on functional architectures, ontology-based domain specific languages (both textual and graphical), application program interfaces (APIs), and ontological model transformation engines and model libraries validated the necessary steps to enable a highly automated and intelligent space systems architecting workflow. As a result of this investment, all of these developments reached a maturity level where they are now ready to be implemented into the Dyreqt framework.

Combined with Dyreqt’s existing capabilities for multidisciplinary design, analysis, and optimization, ontology‑driven workflows are expected to deliver benefits by improving consistency in campaign definitions and interfaces, reducing manual scripting and rework and enabling broader reuse of modular model libraries across studies. Using semantically aligned textual and graphical domain specific languages (DSL)s, with service interfaces (e.g., Dyreqt‑as‑a‑Service and SPAIDE), supports interoperability and greater efficiency for NASA’s concurrent engineering teams, while containerized and cloud‑native execution provides scalable computing for complex system‑of‑systems trades. These changes should help NASA make more timely, evidence‑informed decisions and modestly lower cost and schedule risk on early‑phase analyses (e.g., Moon‑to‑Mars). For Dyreqt users, ontology‑enabled workflows simplify system‑model development and help avoid inconsistencies in the earliest phases of systems engineering, contributing to steadier iteration velocity and greater rigor.

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