A Three-Level MBSE Logical Design Framework and Requirements-Traceability Validation for ICF Ultrafast Imaging Diagnostics Instruments

Abstract

The ultrafast evolution of the physical process in the laser driven inertial confinement (ICF) fusion requires ultrafast imaging diagnostic instruments. The traditional commercial instruments are not able to meet the ICF experiment requirement. It is a technical challenge to develop the diagnostic instruments with an extreme capability. This work proposes a three-layer MBSE logical design framework for an ultrafast framing imager. The framework comprises an operational analysis layer, a system design layer, and a component design layer. Using SysML as the unified modeling language, it progressively decomposes the experimental objective of acquiring picosecond-scale plasma-evolution images into system indicators, functional nodes, logical components, and module-level parameters. Methodologically, the study establishes a bidirectional requirements-traceability mechanism and introduces a parameter-budget model for temporal-resolution allocation. Taking system temporal resolution <= 80 ps as the representative case, a complete decomposition chain is constructed from the user requirement down to trigger-synchronization jitter, gating-pulse jitter, and MCP response time. Process-based comparative analysis further confirms the effectiveness of the framework in requirement allocation, change-impact localization, and cross-disciplinary collaboration. The case study shows that, at the same problem scale, the MBSE approach reduces the time required for requirement-to-module allocation from approximately 6.4 h to 2.1 h, and shortens the impact-localization time for tightening the target from 0 ps to 50 ps from 47 min to 11 min, while significantly reducing omissions. Model statistics indicate that the case includes 5 user requirements, 8 system indicators, 17 functional nodes, 12 key interfaces, and 46 traceability links, demonstrating not only conceptual value but also maintainability at a practical engineering scale. The proposed method therefore provides a useful foundation for the systematic design, rapid iteration, and subsequent automated verification of laser-fusion diagnostic equipment.