Functional Architecting Techniques - Applications to Space Operations Design
Bibliographic record
Abstract
Historically, space systems have been developed using a physical architecture as the primary basis for design; structured functional architectures were the purview of network and software systems designers. Space operations design has thus frequently followed a hardware operations-centric thread. After Mobile Satellite Ventures (MSV) selected Boeing Space and Intelligence Systems to build and operate a Space Based Network (SBN) for their next generation Mobile Satellite System, Boeing determined that functional architecting techniques could bring added benefits to the system and operations development program. Boeing’s MSV SBN is a large scale space system that when deployed will provide ubiquitous 4G mobile coverage to the entire North American continent and beyond. The SBN features two large Boeing 702 GeoMobile satellites as well as 4 ground based beamforming-equipped dual gateway stations located across the US and Canada. This system and operations design effort and the relatively short time frame allowed by the customer’s business plan has called for rapid implementation of the functional architecture development process. Functional decomposition was performed on the MSV system, allowing development of a functional architecture for a system that had no previous architectural precedence. Additionally, the MSV program elected to use both the IDEF0 modeling method and the integration of DOORS® (for requirements management) with SLATE FI (functional architecture definition) for formalization of the functional architecture. This enabled the ability to import system requirements into SLATE FI to achieve an integrated architecture. This integration allowed the functional architecting process to rapidly support both the system and systems operations design processes, adding to the robustness and quality of derived program requirements and operational concepts. Derived from explicit operational scenarios, systems operations functions were explicitly defined and linked to the system architecture, with clear mapping to system functions and requirements, as well as allocated to hardware and software elements. Operational products for the Space Based Network, such as procedures, tools and training, could thus be built up around the operations aspects of the functional architecture in a straightforward manner. Boeing’s MSV program has been a pathfinder for the application of functional architecting to space systems and operations design. The functional architecture developed for the MSV program has provided many benefits to the overall system engineering process. Boeing has also integrated the customer’s outer shell network architecture and CONOPS into the SBN architecture and operations model which has significantly reduced program risk. While the MSV SBN is a space-based communications system, the operations architecting techniques demonstrated are fully applicable to other space applications; these methods can benefit future system developments in both the commercial and civil space operations arenas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".