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

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

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

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.  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. System Requirements

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

9. Science and Technology Operation Coordination Process Flow View of the System 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 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) 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

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

18. 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 #----------------------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) #CDT BLOCK 126_05:18:24STOCINERT_START ( POINTING_AXIS = X OBJECT = EARTH SLEW_POLICY = SMOOTH YDIR = POSITIVE ) 126_05:48:24STOCINERT_END #Light side start 126_07:26:21STOCNADIR_START ( OBJECT_TO_BE_POINTED = Z SLEW_POLICY = SMOOTH YDIR = POSITIVE ) #Light side end 126_09:18:49STOCNADIR_END #WOL + Inertial Cool Down start 126_09:47:21STOCINERT_START ( OBJECT = WOL SLEW_POLICY = SMOOTH YDIR = POSITIVE ) #End of WOL 126_11:28:07STOCINERT_END #Light side start 126_12:25:24STOCNADIR_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

22. Target Coverage during the Push Broom 1 Phase of the Mission SMART-1 Results, achieved using SOPS Coverage Image from the ESA MAPPS tool

23. SMART-1 Results, achieved using SOPS Target Coverage during the Medium Solar Elevation Phase of the Mission

24. Implementation J2EE Architecture

25. Implementation

26. Services Provided by the J2EE Server: The J2EE security model lets you configure a web component or enterprise bean so that system resources are accessed only by authorized users. The J2EE transaction model lets you specify relationships among methods that make up a single transaction so that all methods in one transaction are treated as a single unit. JNDI lookup services provide a unified interface to multiple naming and directory services in the enterprise so that application components can access naming and directory services. The J2EE remote connectivity model manages low-level communications between clients and enterprise beans. After an enterprise bean is created, a client invokes methods on it as if it were in the same virtual machine.

27. Implementation Target Payload Target Group Facade Session Bean DataManager Entity EJBs With CMP J2EE Clients

28. Implementation