NOS Testbed (NOS-T) Documentation
The New Observing Strategies Testbed (NOS-T) is a comprehensive digital engineering environment designed to develop, test, mature, and socialize new operating concepts and technology for NASA’s New Observing Strategies initiative. NOS-T provides a framework for scientists, engineers, and mission planners to model, simulate, and analyze novel observational approaches across various space science disciplines.
Key Capabilities
Distributed Simulation Framework: Connect multiple simulation components through standardized Advanced Message Queuing Protocol (AMQP) messaging protocols
Managed Application Architecture: Synchronize and control simulation components with built-in time management and state control
Schema-Based Communication: Leverage standardized message schemas for consistent data exchange between applications
Flexible Deployment Options: Run simulations locally or deploy to cloud environments like AWS
Example Test Suites: Build on existing scenarios like FireSat+, Science Event Dashboard, and Snow Observing Systems
Scalability Testing: Validate performance under varying message loads and simulation complexities
Visualization & Analysis Tools: Visualize simulation results through integrated dashboards and analysis tools
Who Should Use NOS-T?
Scientists developing new observation strategies for space missions
Engineers designing spacecraft systems and instruments
Mission planners optimizing science return and resource utilization
Researchers evaluating observation trade-offs and capabilities
Program managers assessing technology readiness and performance metrics
Getting Started
New to NOS-T? We recommend:
Read the Overview to understand NOS-T fundamentals
Follow the Installation guide to set up your environment
Work through tutorials in Learning Resources
Explore Example Test Suites to see NOS-T in action
Support and Community
Report issues on our GitHub repository
Attend virtual workshops and training sessions
- Contact the NOS-T team:
PI: Paul T. Grogan, paul.grogan@asu.edu
Research Scientist: Emmanuel M. Gonzalez, emmanuelgonzalez@asu.edu