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BEAST Building Sustainable Data Infrastructure for NASA Thermal Protection ResearchNASA’s current data infrastructure for thermal protection system (TPS) research remains fragmented and project-specific. Arcjet test results are often stored as spreadsheets summarizing individual campaigns, with raw data scattered across local drives or cloud folders. Once projects conclude, these datasets are difficult to locate or reuse, and the absence of standardized metadata, version control, and provenance tracking limits cross-campaign analysis and long-term reproducibility.

To address these limitations, we developed the BEAST (Backend for Experiment Analysis, Storage, and Traceability) platform, a centralized database that ingests, structures, and visualizes arcjet data. BEAST provides queryable access to time-series and metadata records, enabling statistical analysis, material property tracking, and reproducible cross-test comparison. The system embeds version control, facility-configuration tracking, and material-sample lineage within a unified, searchable framework, establishing a sustainable foundation for data-driven TPS development. Beyond archival functions, BEAST streamlines facility operations through automated report generation, component-usage tracking, and interactive dashboards for operators and analysts. A shared web interface further supports coordinated test planning between principal investigators and test engineers.

Under the same initiative, companion tools extend automation to data generation and analysis. arcjetCV applies computer vision and machine learning to high-speed video to extract real-time measurements of material recession and shock standoff, while STARscan provides rapid 3D surface reconstructions of test samples before and after exposure. All tools share BEAST’s data schema and provenance model, enabling seamless integration of imagery, mesh, and metadata.

The BEAST ecosystem represents a critical step toward reproducible, data-rich, and efficient operations across NASA’s arcjet facilities linking data management, automation, and analysis to enhance scientific fidelity and mission readiness.
Document ID
20250010261
Acquisition Source
Ames Research Center
Document Type
Presentation
Authors
Alexandre Quintart
(Flying Squirrel, Inc. Hampton, United States)
Magnus Haw
(Ames Research Center Mountain View, United States)
Sebastian Colom
(Analytical Mechanics Associates (United States) Hampton, United States)
Date Acquired
November 11, 2025
Subject Category
Computer Programming and Software
Documentation and Information Science
Meeting Information
Meeting: 15th Ablation Workshop
Location: Las Cruces, NM
Country: US
Start Date: November 18, 2025
End Date: November 20, 2025
Sponsors: New Mexico State University
Funding Number(s)
CONTRACT_GRANT: NNA15BB15C
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
NASA Technical Management
Keywords
Data Visualization
Machine Learning
Automation
TPS
Data Traceability
database
Recession tracking
photogrammetry
arc jet
3D reconstruction
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