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Architectural Design Space Exploration

Explore the design space for communication satellite constellations to optimize system performance and minimize costs using trade approaches, simulations, and optimization methods.

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Architectural Design Space Exploration

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  1. Prof. Olivier de Weck, Darren Chang Unit 2 Architectural DesignSpace Exploration Communications Satellite Constellations

  2. Outline • Motivation • Traditional Approach • Conceptual Design (Trade) Space Exploration • CS2 - Simulator • Conclusions Communications Satellite Constellation 50 satellites 5 planes h=800 km National Aerospace Institute @ NASA LaRC

  3. Traditional Approach • Decide what kind of service should be offered • Conduct a market survey for this type of service • Derive system requirements • Define an architecture for the overall system • Conduct preliminary design • Obtain FCC approval for the system • Conduct detailed design analysis and optimization • Implement and launch the system • Operate and replenish the system as required • Retire once design life has expired National Aerospace Institute @ NASA LaRC

  4. Existing Big LEO Systems Individual Iridium Satellite Individual Globalstar Satellite National Aerospace Institute @ NASA LaRC

  5. Conceptual Design (Trade) Space Design (Input) Vector Simulator Performance Capacity Cost Can we quantify the conceptual system design problem using simulation and optimization? National Aerospace Institute @ NASA LaRC

  6. Design (Input) Vector X Design Space • The design variables are: • Constellation Type: C • Orbital Altitude: h • Minimum Elevation Angle: emin • Satellite Transmit Power: Pt • Antenna Size: Da • Multiple Access Scheme MA: • Network Architecture: ISL Astro- dynamics Satellite Design Network C: 'walker' h: 2000 emin: 12.5000 Pt: 2400 DA: 3 MA: 'MFCD' ISL: 0 This results in a 1440 full factorial, combinatorial conceptual design space X1440= National Aerospace Institute @ NASA LaRC

  7. Objective Vector (Output) J Consider • Performance (fixed) • Data Rate per Channel: R=4.8 [kbps] • Bit-Error Rate: pb=10-3 • Link Fading Margin: 16 [dB] • Capacity • Cs: Number of simultaneous duplex channels • Clife: Total throughput over life time [min] • Cost • Lifecycle cost of the system (LCC [$]), includes: • Research, Development, Test and Evaluation (RDT&E) • Satellite Construction and Test • Launch and Orbital Insertion • Operations and Replenishment • Cost per Function, CPF [$/min] Cs: 1.4885e+005 Clife: 1.0170e+011 LCC: 6.7548e+009 CPF: 6.6416e-002 J1440= National Aerospace Institute @ NASA LaRC

  8. Number of spot beams Satellite Mass Number of gateways Number of Satellites Launch vehicle selection Number of orbital planes CS2 Simulator Structure Constants Vector Input Vector p x constellation spacecraft cost launch link budget market satellite network Output Vector J Note: Only partial input-output relationships shown National Aerospace Institute @ NASA LaRC

  9. Governing Equations Energy per bit over noise ratio: a) Physics-Based Models (Link Budget) b) Empirical Models (Spacecraft) Scaling models derived from FCC database National Aerospace Institute @ NASA LaRC

  10. Benchmarking Benchmarking is the process of validating a simulation by comparing the predicted response against reality. National Aerospace Institute @ NASA LaRC

  11. If actual demand is below capacity, there is a waste If demand is over the capacity, market opportunity may be missed Demand distribution Probability density function waste under cap Traditional Approach • The traditional approach for designing a system considers architectures to be fixed over time. • Designers look for a Pareto Optimal solution in the Trade Space given a targeted capacity. 1 10 Iridium actual Iridium simulated Lifecycle Cost [B$] Globalstar actual Pareto Front Globalstar simulated 0 10 3 4 5 6 7 10 10 10 10 10 Global Capacity Cs [# of duplex channels] National Aerospace Institute @ NASA LaRC

  12. Conclusions • The goal is not to rewrite the history of LEO constellations but to identify weaknesses of the traditional approach • We designed a framework to reveal economic opportunities for staged deployment strategies • The method is general enough to be applied to similar design problems – uses optimization • Reconfiguration needs to be studied in detail and many issues have to be solved: • Estimate DV and transfer time for different propulsion systems • Study the possibility of using a Tug to achieve reconfiguration • Response time • Service Outage National Aerospace Institute @ NASA LaRC

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