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SOPS: The Science Operations Planning System for the first ESA Lunar Mission SMART-1

SOPS: The Science Operations Planning System for the first ESA Lunar Mission SMART-1. System Level View. Targets. Operational Constraints. Scientific goals. Mission Objectives. Pointing Profile?. PORs. Payload. What is a Science Operation Planning System?. Scheduling.

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SOPS: The Science Operations Planning System for the first ESA Lunar Mission SMART-1

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  1. SOPS: The Science Operations Planning System for the first ESA Lunar Mission SMART-1

  2. System Level View Targets Operational Constraints Scientific goals Mission Objectives Pointing Profile? PORs Payload What is a Science Operation Planning System? Scheduling Environmental Constraints Operation Time Lines Principal Investigator Simulation Science Opportunity Window

  3. System Level View • MIRA Request • Observation Request • SPL • … • ITLs • PORs • PTRs • … What I would like to do Science Operations Planning System Consolidated and conflict-free Plan for operations of Payload!!! Output Input What are the constraints • Environmental Constraints • Thermal Constraints • Payload Constraints • S/C sub-systems constraints • … Interface Interface

  4. System Level View • Input: What I want • Concrete request including required Execution Time: •  Take an image of Target YYY in Orbit ZZZ •  Perform a dust particle analyse as long as possible in the time window XXX • Generic Input without concrete execution time: •  Take an Image of Target XXX, whenever the distance is YYY and the • local solar elevation angle is ZZZ and …. • Perform a dust particle analyse as long as possible, whenever the • concentration of particles is higher than XXX and S/C Thrusters are off • and …

  5. System Level View • Input: What are the constraints • Environmental Constraints: Local Solar Elevation and Azimuth angles, • distances, phase angles, particle concentration, target visibilities, … • Thermal Constraints: Max illumination of panel XXX shall be YYY for max • duration of ZZZ, pre-defined Thermal profiles for operational phases • Resource Constraints: Power consumption, Data generation, Satellite Orientation • S/C and Sub-System Constraints: Reaction wheels saturation, Star tracker blindings, • Slew times between two satellite orientations, .. • Payload Constraints: Interference between different Payloads and S/C, Internal • payload constraints, Mode level constraints

  6. Science Operations Planning Concepts Decentralized Science Operation Planning through Conflict Resolving Centralized Science Opportunity Analysing Operation Planning through Conflict Avoidance

  7. System Requirements • Management of all relevant operational Data • Performing environmental and sub/system level simulations • Analysing the simulation results and identifying available science opportunity windows • Selecting some of available science opportunities  Resource management and conflict resolution  Prioritising and selecting among overlapping science opportunity windows • Preparation of the final, consolidated science operations planning products  Detailed operational Timeline files  Detailed S/C orientation/pointing request files • Tracking of all performed observations and achieved scientific objectives of the mission.

  8. System Architecture Observation Requests Payload Information Target Definitions Constraint Definitions Operation Planning Knowledgebase Operation Profiles Scientific Objectives Pointing Profiles Performed Observations ITL Environmental Model PTR Operational Opportunity Windows POR Payload Models Science Opportunity Analyzer Visualisation Modules Simulator S/C Sub-System Models Science Opportunity Windows Thermal Model Planner & Scheduler Operation Plan Generator Slew Est. Model FCT/FDT MDS Systems

  9. Process Flow View of the System Science and Technology Operation Coordination Consolidated/ Constraint Free Plan

  10. Management of all relevant operational Data Underlying Technologies • J2EE: Container managed Enterprise Java Beans • Relational, SQL-based database • Web-Client: Servlets and Java Server Pages Modelled Knowledgebase Entities • Target • Target group • Payload • Constraint Type • Constraint • Science Theme • Observation Profile • Payload Operations Profile • Observation Request • Performed Observations • Science Opportunities • Orbits, Planning Cycles

  11. SOPS Knowledgebase

  12. Performing environmental and sub/system level simulations PTB: Project Test Bed Existing Simulator based on EuroSim Frame-Work Reports changes in the environmental properties as events Result of one week simulation: 45 MB ASCII event file 004_23:32:06 LM_LSE_70_80_START (COUNT = 4170001) 004_23:32:14 LM_VIS_ALG_20_30_START (COUNT = 1980041) 004_23:32:14 LM_VIS_ALG_30_90_END (COUNT = 1980041) 004_23:32:15 LM_VIS_LIM_END (COUNT = 2110041) 004_23:32:15 LM_VIS_LIM_END (COUNT = 4870042) 004_23:32:17 LM_VIS_LIM_END (COUNT = 1980041) 004_23:32:17 LM_VIS_LIM_END (COUNT = 4880042) 004_23:32:19 LM_VIS_LIM_START (COUNT = 2230041) 004_23:32:23 LM_VIS_ALG_5_10_START (COUNT = 2170041) 004_23:32:23 LM_VIS_ALG_10_20_END (COUNT = 2170041) 004_23:32:24 LM_VIS_LIM_END (COUNT = 1920041) 004_23:32:25 LM_VIS_LIM_START (COUNT = 1930041)

  13. Science Operations Analyzer • 100s of opportunities per week • Visibility and geometry constraints • Different pointing modes • nadir, cross-track, tracking, inertial • Conflicting pointing • Platform thermal constraints • Payload geometric constraints • e.g Sun in FoV. • Payload maintenance • No ground station schedule

  14. Science Operations Analyzer

  15. Science Operations Analyzer

  16. Science Operations Analyzer

  17. Science Operations Analyzer

  18. Science Operations Analyzer #----------------------Orbit 2319 126_07:26:21 AM_PHT_MOR_START (COUNT = 1010001) 126_07:26:40 AM_PHT_MOR_START (COUNT = 4240002) 126_07:26:40 POLAR_MON_START (COUNT = 4240001) 126_07:27:53 AM_PHT_MOR_START (COUNT = 1000003) 126_07:29:08 AM_MAPPING_START (COUNT = 4220001) 126_07:29:08 D_CIXS_GLOBAL_MAPPING_START (COUNT = 4220001) 126_07:29:08 SIR_POLE_TO_POLE_START (COUNT = 4220001) 126_07:33:16 AM_PHT_MOR_END (COUNT = 1010001) 126_07:34:04 AM_PHT_MOR_END (COUNT = 4240002) 126_07:34:04 POLAR_MON_END (COUNT = 4240001) 126_07:35:15 AM_PHT_MOR_END (COUNT = 1000003) Underlying Technology • J2EE Client • Server – Client Architecture • TCP/IP connection to the knowledgebase • Platform independence • Import / Export Functionality • Generation of interface documents for other ESA planning software #CDT BLOCK 126_05:18:24 STOC INERT_START ( POINTING_AXIS = X OBJECT = EARTH SLEW_POLICY = SMOOTH YDIR = POSITIVE ) 126_05:48:24 STOC INERT_END #Light side start 126_07:26:21 STOC NADIR_START ( OBJECT_TO_BE_POINTED = Z SLEW_POLICY = SMOOTH YDIR = POSITIVE ) #Light side end 126_09:18:49 STOC NADIR_END #WOL + Inertial Cool Down start 126_09:47:21 STOC INERT_START ( OBJECT = WOL SLEW_POLICY = SMOOTH YDIR = POSITIVE ) #End of WOL 126_11:28:07 STOC INERT_END #Light side start 126_12:25:24 STOC NADIR_START ( OBJECT_TO_BE_POINTED = Z SLEW_POLICY = SMOOTH YDIR = POSITIVE )

  19. Science Operations Scheduler • Constraint-Based Scheduling and optimizing using the constraint programming library of the Fraunhofer FIRST,firstCS • Pure CSP modeling of the scheduling problem • Finding an optimized solution using Labeling algorithms (Reduction of Domains) • Research Study (not part of the official SOPS development work) final CS cs = new CS(); //Task 1 Variable start = new Variable(0, 12); Variable duration = new Variable(9); Variable end = new Variable(9, 15); Sum s = new Sum(start,duration,end); Cs.add(sum); ...

  20. Tracking and Analysing of Performed Observations • The results of analysing/planning sessions are feed back into the same knowledgebase: • Planning Cycles • Orbits • Communication Opportunities • Science Opportunities • Performed Observations • - All entities are time-taged and inter-related. • - Any kind of queries (SQL or prepared Masks) can be carried out to perform detailed scientific analysis. • - Closing the loop in the planning by taking the planning history and future into account.

  21. SOPS Features Summary • Single Repository for all relevant information about science operations in a knowledgebase • Web-based and easy access via the Internet to the knowledgebase • Platform independent Java client for analyzing, scheduling, visualizing and planning • Identification of all available science opportunity windows in a planning cycle • Several visualization forms of analyzing results • Partly automated scheduling of the identified science opportunity windows • Generating interface files for other ESA planning software and the flight control team • Reporting and Tracking functionality for all performed observations

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