1. LSST Telescope and Site Observatory Control System Interface Review Scheduler Design Francisco Delgado

2. Addressing the Charge 2.Is the OCS design mature enough to support (i) the analysis of compliance with the requirements and (ii) the definition of interfaces? 9.Are the plans for implementing the OCS are adequate and realistic, including budget, schedule, and organization/management structure? Are the deliverables for the Scheduler and the Operations Simulator well defined and the corresponding resources properly aligned between the OCS and Systems Engineering teams? Are the deliverables for communication middleware well defined and the assigned resources adequate? Scheduler Design OCS Interface Review Tucson, Arizona September 10-11, 20142

3. Scheduling the LSST Survey LSST as a robotic observatory Survey is automatic Multiple science goals Combine area distribution with temporal sampling Dynamic adaptation to weather Flexibility for survey adjustments during operations Flexibility for changes in science programs LSST as a robotic observatory Survey is automatic Multiple science goals Combine area distribution with temporal sampling Dynamic adaptation to weather Flexibility for survey adjustments during operations Flexibility for changes in science programs Scheduler Design 3OCS Interface Review Tucson, Arizona September 10-11, 2014

4. Requirements Flow down Science Requirements Document LPM-17 Science Requirements Document LPM-17 Scheduler Requirements LSE-190 Scheduler Requirements LSE-190 Observatory System Specifications LSE-30 Observatory System Specifications LSE-30 LSST System Requirements LSE-29 LSST System Requirements LSE-29 OpSim Requirements LSE-189 OpSim Requirements LSE-189 Observatory Control System Requirements LSE-62 Observatory Control System Requirements LSE-62 Science Book Metrics Requirements DOC-15319 Metrics Requirements DOC-15319 Science Collaborations Scheduler Design 4OCS Interface Review Tucson, Arizona September 10-11, 2014

5. Scheduler Design 5OCS Interface Review Tucson, Arizona September 10-11, 2014 Scheduler Requirements Traceability

6. Scheduler concepts Sky field map, tiling regions, a target is a field/filter combination. Fully configurable set of concurrent competing science programs. Sky brightness dynamically modeled for each sky field with look- ahead window. Comprehensive observatory kinematic model for slew time optimizations. Target score balances science value and time cost Sky field map, tiling regions, a target is a field/filter combination. Fully configurable set of concurrent competing science programs. Sky brightness dynamically modeled for each sky field with look- ahead window. Comprehensive observatory kinematic model for slew time optimizations. Target score balances science value and time cost Scheduler Design 6OCS Interface Review Tucson, Arizona September 10-11, 2014

7. Observatory Control System Scheduler Design 7OCS Interface Review Tucson, Arizona September 10-11, 2014

8. Scheduler Design 8OCS Interface Review Tucson, Arizona September 10-11, 2014 Scheduler Internal Block Diagram Control Observatory Telemetry Environmental Conditions Observed Targets Selected Targets Database Conductor Optimizer Observatory Kinematic Model Slew Time Estimations Astronomical Sky Scheduling Data Suggested Targets Science Programs Observation History Calibration Engineering Programs Calibration Targets Science Targets Scheduler

9. Scheduler internal communications Scheduler Design 9OCS Interface Review Tucson, Arizona September 10-11, 2014 Science Program N Observation History Calibration Programs Observatory Kinematic Model Astronomical Sky Conductor Optimizer Scheduling Data Science Program 1 … communications middleware

10. Science Programs parameters Sky region. Number of visits per field in each filter. Cadence constraints for revisits or sequences. Airmass limits. Sky brightness constraints. Seeing requirements. Activation times. Sky region. Number of visits per field in each filter. Cadence constraints for revisits or sequences. Airmass limits. Sky brightness constraints. Seeing requirements. Activation times. Scheduler Design 10OCS Interface Review Tucson, Arizona September 10-11, 2014

11. Scheduler Design 11OCS Interface Review Tucson, Arizona September 10-11, 2014 Science Programs classes  Area distribution programs  Designed to obtain uniform distribution  Basic parameter: goal visits per filter  Look-ahead info: future available time for the targets  Time distribution programs  Designed to obtain specified intervals in sequences  Basic parameter: time window for visits interval  Look-ahead info: visibility for next intervals  Area distribution programs  Designed to obtain uniform distribution  Basic parameter: goal visits per filter  Look-ahead info: future available time for the targets  Time distribution programs  Designed to obtain specified intervals in sequences  Basic parameter: time window for visits interval  Look-ahead info: visibility for next intervals

12. Selecting the next visit  Dynamic and adaptive process for each visit:  Each science program:  analyzes its assigned sky region and selects the candidate targets that comply with its requirements.  computes the science merit for each selected target according to its own distribution and cadence constraints.  The conductor optimizer combines the targets and their science merit from all the science programs.  The observatory model computes the slew time cost for each target from the current position.  The target with the highest overall rank is selected.  Dynamic and adaptive process for each visit:  Each science program:  analyzes its assigned sky region and selects the candidate targets that comply with its requirements.  computes the science merit for each selected target according to its own distribution and cadence constraints.  The conductor optimizer combines the targets and their science merit from all the science programs.  The observatory model computes the slew time cost for each target from the current position.  The target with the highest overall rank is selected. Scheduler Design 12OCS Interface Review Tucson, Arizona September 10-11, 2014

13. Scheduler Design 13OCS Interface Review Tucson, Arizona September 10-11, 2014 Select Next Visit

14. Look-ahead  A time window is defined for a number of nights to the future.  For each target from the candidates list:  Airmass and sky-brightness are pre-calculated.  Visibility is determined from each science program constraints.  Science programs have this look-ahead information for improving time distribution and efficiency in sequences.  A time window is defined for a number of nights to the future.  For each target from the candidates list:  Airmass and sky-brightness are pre-calculated.  Visibility is determined from each science program constraints.  Science programs have this look-ahead information for improving time distribution and efficiency in sequences. Scheduler Design 14OCS Interface Review Tucson, Arizona September 10-11, 2014

15. Operations Simulator System simulation and prototype for the Scheduler Validate observatory design Design science programs to achieve SRD Develop an efficient LSST scheduling strategy Systems engineering trade off studies Support Commissioning and Operations System simulation and prototype for the Scheduler Validate observatory design Design science programs to achieve SRD Develop an efficient LSST scheduling strategy Systems engineering trade off studies Support Commissioning and Operations Scheduler Design 15OCS Interface Review Tucson, Arizona September 10-11, 2014

16. Scheduler Design 16OCS Interface Review Tucson, Arizona September 10-11, 2014 OpSim requirements Simulate Operations visit by visit for 10 years Simulate Observatory (Telescope & Camera kinematics, slew & track) Simulate Environment (clouds, seeing, sky brightness) Prototype Scheduler (targets generation and scheduling algorithms) Set of proposals, SRD defined universal plus auxiliary projects Flexibility for algorithm experimentation Simulate Operations visit by visit for 10 years Simulate Observatory (Telescope & Camera kinematics, slew & track) Simulate Environment (clouds, seeing, sky brightness) Prototype Scheduler (targets generation and scheduling algorithms) Set of proposals, SRD defined universal plus auxiliary projects Flexibility for algorithm experimentation

17. OpSim Architecture Scheduler Design 17OCS Interface Review Tucson, Arizona September 10-11, 2014

18. Environment Models slalib for sun & moon Sophisticated sky brightness model using the Krisciunas and Schaeffer model with twilight. Actual seeing historic measurements from the site. Actual clouds historic record from the site. slalib for sun & moon Sophisticated sky brightness model using the Krisciunas and Schaeffer model with twilight. Actual seeing historic measurements from the site. Actual clouds historic record from the site. Scheduler Design 18OCS Interface Review Tucson, Arizona September 10-11, 2014

19. Observatory Model Second order kinematic model for the slew activities  Mount Azimuth with cable wrap.…………………….  Mount Altitude……………………………………………….  Mount Settle time…………………………………………..  Dome Azimuth………………………………………………..  Dome Altitude………………………………………………..  Rotator Angle…………………………………………………. Delay model for Camera  filter change……………………………………………………  Shutter time……………………………………………………  exposure time…………………………………………………  Readout time…………………………………………………. Active Optics correction………………………………………….. Second order kinematic model for the slew activities  Mount Azimuth with cable wrap.…………………….  Mount Altitude……………………………………………….  Mount Settle time…………………………………………..  Dome Azimuth………………………………………………..  Dome Altitude………………………………………………..  Rotator Angle…………………………………………………. Delay model for Camera  filter change……………………………………………………  Shutter time……………………………………………………  exposure time…………………………………………………  Readout time…………………………………………………. Active Optics correction………………………………………….. Scheduler Design 19OCS Interface Review Tucson, Arizona September 10-11, 2014 slewexposure

20. Scheduler Design 20OCS Interface Review Tucson, Arizona September 10-11, 2014 OpSim activity diagram of a visit

21. OpSim implementation Python language for the logic and data handling C++ for libraries, such as slalib 20k lines of code approx. Typical 10 year run takes 50 hours in personal computers MySQL database with 22 tables for the history of visits, slews and sequences, sky conditions, etc. Python language for the logic and data handling C++ for libraries, such as slalib 20k lines of code approx. Typical 10 year run takes 50 hours in personal computers MySQL database with 22 tables for the history of visits, slews and sequences, sky conditions, etc. Scheduler Design 21OCS Interface Review Tucson, Arizona September 10-11, 2014

22. Sky coverage per filter Scheduler Design 22OCS Interface Review Tucson, Arizona September 10-11, 2014

23. OpSim & Scheduler configuration System 117 parameters, including the site, sky model and the kinematic model Scheduler 11 parameters for controlling the algorithms Survey 130 approx. parameters for each the science programs Typical set of 5 programs 3600 sky fields Parameters for depth per color Parameters for sequence cadences Sky brightness limits Airmass limits Seeing limits System 117 parameters, including the site, sky model and the kinematic model Scheduler 11 parameters for controlling the algorithms Survey 130 approx. parameters for each the science programs Typical set of 5 programs 3600 sky fields Parameters for depth per color Parameters for sequence cadences Sky brightness limits Airmass limits Seeing limits Scheduler Design 23OCS Interface Review Tucson, Arizona September 10-11, 2014

24. Scheduler Design 24OCS Interface Review Tucson, Arizona September 10-11, 2014 Scheduler Telemetry History Control Targets Image Quality Scheduler Interfaces in OCS OCS Application communications middleware TCS EFD DMCS OCS Sequencer Visits Sched Telem CCS Cmd Visits

25. Scheduler Design 25OCS Interface Review Tucson, Arizona September 10-11, 2014 Scheduler Telemetry History Control Targets Image Quality Scheduler Interfaces in OPSIM OPSIM Simulation kernel OPSIM Simulation kernel communications middleware OPSIM Telescope Model OPSIM Telescope Model OPSIM DB OPSIM DB OPSIM Simulation kernel OPSIM Simulation kernel Visits Sched Telem Cmd Visits OPSIM Weather Model OPSIM Weather Model

26. Scheduler Inputs/Outputs  Inputs  Control  Mode  Downtime  Degraded  Telemetry  Observatory conditions  Environment conditions  Forecast  History  Past observations  Visits  Current observation  Image Quality  Quality parameters  Outputs  Targets  Scheduling telemetry  Inputs  Control  Mode  Downtime  Degraded  Telemetry  Observatory conditions  Environment conditions  Forecast  History  Past observations  Visits  Current observation  Image Quality  Quality parameters  Outputs  Targets  Scheduling telemetry Scheduler Design 26OCS Interface Review Tucson, Arizona September 10-11, 2014

27. Scheduler Development Partition  Design & Implementation (T&S)  API  Architecture  Coding  System parameters  Conductor/Optimizer  Scheduling Data  Generic Science Program  Calibration Engineering Programs  Design & Implementation (T&S)  API  Architecture  Coding  System parameters  Conductor/Optimizer  Scheduling Data  Generic Science Program  Calibration Engineering Programs Scheduler Design 27OCS Interface Review Tucson, Arizona September 10-11, 2014  Cadence & Algorithms (SE Simulation)  Science cases  Algorithms  Survey and Scheduling parameters  Coding  Observatory Kinematic Model  Astronomical Sky  Specific Science Programs  Observations History  Cadence & Algorithms (SE Simulation)  Science cases  Algorithms  Survey and Scheduling parameters  Coding  Observatory Kinematic Model  Astronomical Sky  Specific Science Programs  Observations History

28. Deliverables Telescope & Site Systems Engineering Simulation Systems Engineering Simulation Scheduler Team Scheduler API OCS environment OPSIM environment Scheduler Code & Framework Scheduler Cadence & Algorithms Scheduler Design 28OCS Interface Review Tucson, Arizona September 10-11, 2014

29. Summary  Scheduler design integrated with OCS architecture.  OCS telemetry architecture enables the use of any variable for scheduling purposes.  Partition and architecture makes for a flexible implementation.  Designed to allow a distributed deployment.  Scheduling strategies have been extensively tested in OpSim.  Simple scheduling algorithms applied to thousands of competing targets produce emerging behavior to solve a complex problem.  Scheduler design integrated with OCS architecture.  OCS telemetry architecture enables the use of any variable for scheduling purposes.  Partition and architecture makes for a flexible implementation.  Designed to allow a distributed deployment.  Scheduling strategies have been extensively tested in OpSim.  Simple scheduling algorithms applied to thousands of competing targets produce emerging behavior to solve a complex problem. Scheduler Design 29OCS Interface Review Tucson, Arizona September 10-11, 2014

30. End of Presentation

31. Backup slides Scheduler Design 31OCS Interface Review Tucson, Arizona September 10-11, 2014

32. LSST Introduction The Large Synoptic Survey Telescope is a complex hardware – software system of systems, making up a highly automated observatory in the form of an 8.4m wide-field telescope, a 3.2 billion pixel camera, and a peta-scale data processing and archiving system. The survey consists of a continuous cadence of visits covering the entire observable sky in 6 different colors with different specifications for depth and time intervals for multiple science programs.

33. LSST Control Hierarchy DDS publish/subscribe Topics for Commands, Telemetry and Events Scheduler Design 33OCS Interface Review Tucson, Arizona September 10-11, 2014

34. DDS COMMUNICATIONS MIDDLEWARE (Commands, Telemetry, Events) OCS Applicati on CCS Interface OCS Remote OCS Sequenc er OCS Mainten. OCS Telemetr y OCS Monitor OCS Operator OCS Schedule r DMCS Interface TCS Enviro n. Contro ller TCS Enclos ure Contro ller TCS Rot/He x Contro ller TCS Mount Contro ller TCS M2 Contro ller TCS M1M3 Contro ller TCS Optics Contro ller Calibrat ion TCS Operat or TCS Pointin g Kernel TCS Appl. TCS Wavefro nt Interface MUX DEMUX MUX DEMUX Camera Guider Interface ILC Networ k Temper. ILC Networ k Devic e Contr ol Devic e Contr ol Devic e Contr ol Devic e Contr ol ILC Networ k Surface Science Data Interface : : DDS Communications NON DDS Communications Auxiliary Telescop e OCS Engineerin g Facility DB Alignm ent Auxilia ry Equip ment -Distributed Control System -Scalable Architecture -Loosely-coupled systems -Interfaces defined by the information model -Connectivity complexity managed by the data bus LSST CONTROL ARCHITECTURE Scheduler Design 34OCS Interface Review Tucson, Arizona September 10-11, 2014

35. OCS communications Scheduler Design 35OCS Interface Review Tucson, Arizona September 10-11, 2014 DDS COMMUNICATIONS MIDDLEWARE (Commands, Telemetry, Events) OCS Application OCS Remote OCS Sequencer OCS Maintenance OCS Telemetry OCS Monitor OCS Operator OCS Scheduler OCS Scheduler

36. Scheduler Design 36OCS Interface Review Tucson, Arizona September 10-11, 2014 Simulation Operations Scheduler Telescope Telemetry Weather Telemetry Downtime Status Telescope Model Weather Model Downtime Model Observatory Database Survey Database Observatory Control System (OCS) Scheduler Selected Targets Simulation Kernel Telemetry Environmental Conditions Observed Targets Control Database Simulation Params Scheduling Params Telemetry Environmental Conditions Observed Targets Control Selected Targets Database OpSim includes Scheduler prototype

37. Scheduler Composition Scheduler Design 37OCS Interface Review Tucson, Arizona September 10-11, 2014

38. Model Based Systems Engineering (MBSE) The LSST uses MBSE to capture the high level system development The language is SysML The tool is Enterprise Architect The model captures and relates: – Requirements – Interfaces – Overall System Architecture – Components Structure – System Behavior – Operational Definitions Document 9336 “Using SysML for MBSE Analysis of the LSST System

39. Model-Based Systems Engineering Scheduler Design 39OCS Interface Review Tucson, Arizona September 10-11, 2014

40. OCS requirements flow-down Science Requirements Document is the parent for all requirements flow down. LPM-17 LSST System Requirements (high level what the LSST is and must do) LSE-29 Observatory System Specifications (high level how the LSST will do what it must) LSE-30 Observatory Control System Requirements (Subsystem Requirements) LSE-62

41. Scheduler Architecture Scheduler Design 41OCS Interface Review Tucson, Arizona September 10-11, 2014

42. Selecting the next visit  Dynamic and adaptive process for each visit:  Each science program:  analyzes its assigned sky region and selects the candidate targets (field/filter) that comply with its requirements for airmass, sky-brightness and seeing.  computes the science merit for each selected target according to its own distribution and cadence requirements.  The conductor optimizer combines the targets from all the science programs and using the observatory model incorporates the slew cost to obtain an overall rank.  The target with the highest rank is selected.  Dynamic and adaptive process for each visit:  Each science program:  analyzes its assigned sky region and selects the candidate targets (field/filter) that comply with its requirements for airmass, sky-brightness and seeing.  computes the science merit for each selected target according to its own distribution and cadence requirements.  The conductor optimizer combines the targets from all the science programs and using the observatory model incorporates the slew cost to obtain an overall rank.  The target with the highest rank is selected. Scheduler Design 42OCS Interface Review Tucson, Arizona September 10-11, 2014

43. Scheduling Visits

44. Area distribution programs –Designed to obtain uniform distribution –Basic parameter: goal visits per filter –Field-filters receiving visits reduce their rank, while not observed Field-filters increase their rank. Scheduler Design 44OCS Interface Review Tucson, Arizona September 10-11, 2014

45. Area distribution with look-ahead –availableTime is the addition of the future time windows when the target (field-filter) is visible for the science program. –targetMerit gives a normalized range of values –These example equations balance the area distribution taking into account the future availability of the field-filter Scheduler Design 45OCS Interface Review Tucson, Arizona September 10-11, 2014

46. Time distribution programs –Designed to obtain specified intervals –Basic parameter: time window for visits interval –Each field has a sequence of visits with time intervals. –This rank envelope promotes visits as close to the desired intervals as target competition allows Scheduler Design 46OCS Interface Review Tucson, Arizona September 10-11, 2014

47. Sequence Possibilities  One single sequence per field  Multiple subsequences per field, different filters  Option for collecting pairs of visits in any subsequence  Option for combining area with time distribution  Option for collecting deep drilling sequences, back-to-back visits changing filters  Option for nested subsequences Scheduler Design 47OCS Interface Review Tucson, Arizona September 10-11, 2014

48. Sequences filtering with look ahead –A science program with sequences evaluates the look ahead visibility of the field-filter series of visits given a start time. –A list of possible start times is populated for each sequence. –The goal is to start only feasible sequences increasing the efficiency Scheduler Design 48OCS Interface Review Tucson, Arizona September 10-11, 2014

49. Science Proposals balance –This equations promote a balanced progress in the competing science proposals Scheduler Design 49OCS Interface Review Tucson, Arizona September 10-11, 2014

50. Summary  Powerful tool for designing the survey and systems engineering  OpSim was key on site-selection, validation of telescope-camera specifications, and demonstrated that the science requirements could be met.  OpSim-Scheduler as a prototype for OCS-Scheduler.  OpSim as a simulation environment for the Scheduler prototype.  OpSim will be evolved into an operational tool for survey assessment and planning.  New look-ahead capabilities and scheduling algorithms in development.  Powerful tool for designing the survey and systems engineering  OpSim was key on site-selection, validation of telescope-camera specifications, and demonstrated that the science requirements could be met.  OpSim-Scheduler as a prototype for OCS-Scheduler.  OpSim as a simulation environment for the Scheduler prototype.  OpSim will be evolved into an operational tool for survey assessment and planning.  New look-ahead capabilities and scheduling algorithms in development. Scheduler Design 50OCS Interface Review Tucson, Arizona September 10-11, 2014

51. Operations Simulator Verify the specifications of LSST hardware and survey against SRD Experiment with sets of science programs Experiment scheduling algorithms and strategies Systems engineering trade off studies Refine requirements for OCS Scheduler

52. Operations Simulator Software package for simulating the 10 years survey in a visit by visit, slew by slew detail. Detailed kinematic model of the telescope+camera+dome Sophisticated sky model, calculating sky brightness using the Krisciunas and Schaeffer model. It tracks the sun and moon using SLALIB routines. Actual seeing and clouds historic tables from the site. Multiple science programs that implement a cadence that satisfies the science requirements.

53. Operations Simulator Requirements Simulate Operations Simulate Observatory (Telescope & Camera kinematics, slew & track) Simulate Environment (clouds, seeing, sky brightness) Prototype Scheduler (targets generation and scheduling algorithms) Set of proposals, SRD defined universal plus key projects Flexibility for algorithm experimentation

54. OpSim requirements in SysML

55. OpSim components

56. OpSim activities

57. Scheduler Target List Scheduler Design 57OCS Interface Review Tucson, Arizona September 10-11, 2014

58. OpSim: start night

59. Scheduler: update target list

60. OpSim Telescope model parameters # speed in degrees/second # acceleration in degrees/second**2 DomAlt_MaxSpeed = 1.75 DomAlt_Accel = 0.875 DomAlt_Decel = 0.875 DomAz_MaxSpeed = 1.5 DomAz_Accel = 0.75 DomAz_Decel = 0.75 TelAlt_MaxSpeed = 3.5 TelAlt_Accel = 3.5 TelAlt_Decel = 3.5 TelAz_MaxSpeed = 7.0 TelAz_Accel = 7.0 TelAz_Decel = 7.0 # not used in slew calculation Rotator_MaxSpeed = 3.5 Rotator_Accel = 1.0 Rotator_Decel = 1.0 # absolute position limits due to cable wrap # the range [0 360] must be included TelAz_MinPos = -270.0 TelAz_MaxPos = 270.0 Rotator_MinPos = -90.0 Rotator_MaxPos = 90.0 Rotator_FollowSky = False # Times in sec Filter_MoveTime = 120.0 Settle_Time = 3.0 # In azimuth only DomSettle_Time = 1.0 Readout_Time = 2.0 # Delay factor for Open Loop optics correction, # in units of seconds/(degrees in ALT slew) TelOpticsOL_Slope = 1.0/3.5 # Table of delay factors for Closed Loop optics correction # according to the ALT slew range. # _AltLimit is the Altitude upper limit in degrees of a range. # The lower limit is the upper limit of the previous range. # The lower limit for the first range is 0 # _Delay is the time delay in seconds for the corresponding range. TelOpticsCL_Delay = 0.0 TelOpticsCL_AltLimit = 9.0 # 0 delay due to CL up to 9 degrees in ALT slew TelOpticsCL_Delay = 20.0 TelOpticsCL_AltLimit = 90.0 Scheduler Design 60OCS Interface Review Tucson, Arizona September 10-11, 2014

61. Detailed slew simulation Session ID: 271number of nights: 365number of exposures: 173999 exposures/night: 476.7 average slew time: 9.79s statistics for angle TelAlt: min= 15.1d max= 86.5d avg= 54.9d std= 14.2d statistics for angle TelAz: min=-270.0d max= 270.0d avg= -19.0d std= 99.8d statistics for angle RotPos: min= -90.0d max= 90.0d avg= -9.4d std= 52.1d slew activity for DomAlt: active= 90.5% of slews, active avg= 3.47s, total avg= 3.14s, max= 22.05s, in critical path= 0.0% with avg= 0.00s cont= 0.00s slew activity for DomAz: active= 90.5% of slews, active avg= 5.55s, total avg= 5.02s, max=106.25s, in critical path= 0.8% with avg= 83.63s cont= 0.64s slew activity for TelAlt: active= 90.5% of slews, active avg= 3.47s, total avg= 3.14s, max= 22.05s, in critical path= 38.2% with avg= 3.69s cont= 1.41s slew activity for TelAz: active= 90.5% of slews, active avg= 4.87s, total avg= 4.41s, max=105.94s, in critical path= 45.3% with avg= 5.83s cont= 2.64s slew activity for Rotator: active= 90.5% of slews, active avg= 4.68s, total avg= 4.23s, max= 54.81s, in critical path= 3.9% with avg= 16.18s cont= 0.63s slew activity for Filter: active= 2.2% of slews, active avg=120.00s, total avg= 2.67s, max=120.00s, in critical path= 2.2% with avg=120.00s cont= 2.67s slew activity for TelOpticsOL: active= 90.5% of slews, active avg= 0.99s, total avg= 0.89s, max= 18.55s, in critical path= 16.9% with avg= 1.89s cont= 0.32s slew activity for Readout: active= 99.7% of slews, active avg= 1.00s, total avg= 1.00s, max= 1.00s, in critical path= 0.0% with avg= 0.00s cont= 0.00s slew activity for Settle: active= 99.7% of slews, active avg= 1.00s, total avg= 1.00s, max= 1.00s, in critical path= 75.9% with avg= 1.00s cont= 0.76s slew activity for TelOpticsCL: active= 3.1% of slews, active avg= 22.87s, total avg= 0.71s, max= 40.00s, in critical path= 3.1% with avg= 22.87s cont= 0.71s Session ID: 271number of nights: 365number of exposures: 173999 exposures/night: 476.7 average slew time: 9.79s statistics for angle TelAlt: min= 15.1d max= 86.5d avg= 54.9d std= 14.2d statistics for angle TelAz: min=-270.0d max= 270.0d avg= -19.0d std= 99.8d statistics for angle RotPos: min= -90.0d max= 90.0d avg= -9.4d std= 52.1d slew activity for DomAlt: active= 90.5% of slews, active avg= 3.47s, total avg= 3.14s, max= 22.05s, in critical path= 0.0% with avg= 0.00s cont= 0.00s slew activity for DomAz: active= 90.5% of slews, active avg= 5.55s, total avg= 5.02s, max=106.25s, in critical path= 0.8% with avg= 83.63s cont= 0.64s slew activity for TelAlt: active= 90.5% of slews, active avg= 3.47s, total avg= 3.14s, max= 22.05s, in critical path= 38.2% with avg= 3.69s cont= 1.41s slew activity for TelAz: active= 90.5% of slews, active avg= 4.87s, total avg= 4.41s, max=105.94s, in critical path= 45.3% with avg= 5.83s cont= 2.64s slew activity for Rotator: active= 90.5% of slews, active avg= 4.68s, total avg= 4.23s, max= 54.81s, in critical path= 3.9% with avg= 16.18s cont= 0.63s slew activity for Filter: active= 2.2% of slews, active avg=120.00s, total avg= 2.67s, max=120.00s, in critical path= 2.2% with avg=120.00s cont= 2.67s slew activity for TelOpticsOL: active= 90.5% of slews, active avg= 0.99s, total avg= 0.89s, max= 18.55s, in critical path= 16.9% with avg= 1.89s cont= 0.32s slew activity for Readout: active= 99.7% of slews, active avg= 1.00s, total avg= 1.00s, max= 1.00s, in critical path= 0.0% with avg= 0.00s cont= 0.00s slew activity for Settle: active= 99.7% of slews, active avg= 1.00s, total avg= 1.00s, max= 1.00s, in critical path= 75.9% with avg= 1.00s cont= 0.76s slew activity for TelOpticsCL: active= 3.1% of slews, active avg= 22.87s, total avg= 0.71s, max= 40.00s, in critical path= 3.1% with avg= 22.87s cont= 0.71s Scheduler Design 61OCS Interface Review Tucson, Arizona September 10-11, 2014

62. Survey database analysis Simulation Survey Tools for Analysis and Reporting (SSTAR). Automatic analysis from the output DB. Statistics, charts and metrics. Scheduler Design 62OCS Interface Review Tucson, Arizona September 10-11, 2014

63. Filter Map Scheduler Design 63OCS Interface Review Tucson, Arizona September 10-11, 2014

64. Joint completeness comparison Scheduler Design 64OCS Interface Review Tucson, Arizona September 10-11, 2014

65. Organization Telescope & Site Systems Engineering Simulation Systems Engineering Simulation Scheduler Team Engineering Lead SW Scheduler Scientist SW SE Science Lead Simulation Runs Scheduler Design 65OCS Interface Review Tucson, Arizona September 10-11, 2014

66. Design Validation using MBSE The following slides show an example of the triad validation methodology for the OCS design. From LSST Observatory all the way to the OCS Scheduler Kinematic model structure component, flowing top down through the corresponding requirements and behavior.

67. Scheduler structure traceability to requirements

68. OCS Requirements Organization

69. OCS Requirements Context

70. OCS Scheduler Requirements

71. OpSim structure traceability to requirements

72. Perform Survey Activity

73. Perform Science Observations Validation Scheduler Design 73OCS Interface Review Tucson, Arizona September 10-11, 2014

74. Select Target Validation Scheduler Design 74OCS Interface Review Tucson, Arizona September 10-11, 2014

75. Rank Targets validation Scheduler Design 75OCS Interface Review Tucson, Arizona September 10-11, 2014

76. Summary Powerful tool for survey designing and systems engineering OpSim was key on site-selection, telescope-camera specifications validation, and finding a survey that fulfilled the science requirements. OpSim-Scheduler as a prototype for OCS-Scheduler, reducing the risk on a critical component. OpSim can be evolved into an operational tool for survey assessment and planning. OpSim as a simulation environment for the Scheduler prototype Scheduler arquitecture designed for flexibility and multiple goals Scheduler Design 76OCS Interface Review Tucson, Arizona September 10-11, 2014