SlideShare une entreprise Scribd logo
1  sur  48
Télécharger pour lire hors ligne
Modelling & Simulation of CubeSat-based
Missions' Concept of Operations
An application using Arcadia/Capella
Danilo Pallamin de Almeida
Introducing Myself
Danilo Pallamin de Almeida
● MSc. Space Systems Engineering & Management @INPE
○ NanosatC-Br2 – SPORT – CRON-1 CubeSat missions
● Mechatronics Engineer @EESC/USP
● Space exploration enthusiast & advocate for democratized access to space
● Why I got into modelling:
○ The higher the complexity of a system, the greater the significance of communication
○ Models can greatly improve communication in engineering
● Currently - Systems Engineer @ EnduroSat
Summary
● Introduction
● INPE/CPRIME’s “ForPlan” Satellite Simulator
● Conops2M Modelling Process
● Example Model
● CapellaToForplan (C2F) Plugin
● Trade-study example
Introduction
● Work developed during Masters @Brazil’s National Institute for
Space Research (INPE)
○ 2018-2020
○ Dr. Fátima Mattiello Francisco & Dr. Fabiano Luis de Sousa
● Began by investigating modelling practices to assist the early-stage
design phase of Space Missions
● Operation scenario simulation is used for trade-studies at INPE’s
Concurrent Engineering Center CPRIME
○ ForPlan Simulator
● Resulted in a modelling process developed to guide the modelling
of CubeSat-based missions and their CONOPS for early-stage
design studies, preparing for operation scenario simulation
○ Generic (Non-specific) Mission Model
○ NanosatC-Br2 Model
INPE’s CPRIME
Concept of Operations (CONOPS)
● How the system will operate to meet stakeholder expectations
● Description of the system’s characteristics from an operational perspective.
● CONOPS at early stages include:
○ Initial physical and logical architecture – space and ground segments
○ Interfaces between elements of the architecture
○ Mission objectives and constraints analysis
○ Operation timelines, modes and scenarios
○ End-to-end communications strategy and data-flow
○ Power and data budget analysis
● Different institutions use different documentation standards
○ European Cooperation for Space Standardization (ECSS): MOCD, MAR, SSUM
○ Large documentation volume, redundant information
○ Use of models can concentrate & simplify – especially for CubeSats (“simpler” operation)
Why Capella/Arcadia
● Integrated tool & method
○ Methodological Guidance – Great combination for a
step-by-step process
● Open source tool
○ Reduced barriers of entry
○ Allowed for our plugin development
● Domain-specific Modelling Language
○ Intuitive & comprehensive – friendly when discussing
model with people not used to model standards
● Great previous experiences from colleagues (former
INPE students)
○ Community
Source: Arcadia/Capella website
● Introduction
● INPE/CPRIME’s “ForPlan” Satellite Simulator
● Conops2M Modelling Process
● Example Model
● CapellaToForplan (C2F) Plugin
● Trade-study example
INPE/CPRIME’s ForPlan Satellite Simulator
● Functional simulation of satellites and associated
ground segment to reflect operational scenarios of
the mission under analysis
● Verification of mission concept of operations
● Early stage studies at CPRIME
● Simulation core modules​
○ Space environment​
○ Equipment​
○ Power​
○ OBDH / TT&C
● Written in Julia
○ INPE’s Dr. Ronan A. Chagas
○ https://www.ronanarraes.com/
○ ronan.arraes@inpe.br
INPE/CPRIME’s ForPlan Satellite Simulator
Modelled simulator
functions
Required inputs
from the user
Configuring ForPlan
# 2. Equipment list
# ==============================================================================
equip_1= ForplanSimulatorCore.Equipment{Float64}(
name = "OBC",
f! = ForplanSimulatorCore.equip_always_on!,
params = [torb, 0.0, 0.383, 30.0])
equip_2= ForplanSimulatorCore.Equipment{Float64}(
name = "Receiver",
f! = ForplanSimulatorCore.equip_always_on!,
params = [torb, 0.0, 0.193, 0.0])
equip_3= ForplanSimulatorCore.Equipment{Float64}(
name = "Transmitter",
f! = ForplanSimulatorCore.equip_on_ground_station!,
params = [torb, 0.0, 0.0, 1.078, 0.0, 0.0, 0])
equip_4= ForplanSimulatorCore.Equipment{Float64}(
name = "Magnetometer",
f! = RoiOp,
params = [torb, 0.016, 96.0,
[[-60.0, 0.0, -90.0, -20.0]]])
equip_5= ForplanSimulatorCore.Equipment{Float64}(
name = "EPS",
f! = ForplanSimulatorCore.equip_always_on!,
params = [torb, 0.0, 0.250, 0.0])
Core method
Equipment name
Operation function
Operation parameters
Equipment instance
● Introduction
● INPE/CPRIME’s “ForPlan” Satellite Simulator
● Conops2M Modelling Process
● Example Model
● CapellaToForplan (C2F) Plugin
● Trade-study example
Conops2M Modelling Process
● Developed based on Arcadia
● A set of sequential steps
○ generate a model of a space mission concept
of operations
○ prepare operation scenarios for simulation
● Begin at high-level abstraction: Mission
objectives as operation capabilities
● Iteratively decompose functions until we reach
equipment-level on spacecraft & facilities for
ground segment
● Model parameters for operation scenario
simulation
○ Transform model into simulator input
Generating the Simulator Configuration Script
● ForPlan is configured through a Julia script
● Capella is Eclipse-based
○ Language built on EMF
○ Capella 1.3.1
● Developed a plugin to retrieve model elements and generate Julia
code based on their attributes
○ ADVANCE Project – Budapest University of Technology and Economics
○ Bence Graics & Dr. Vince Molnár
○ Xtend
■ Specifically designed for model transformation and code generation
● Defined rules for a Class Diagram architecture and the creation of
class instances according to each model element
○ Traverse instance models and derive arbitrary code
● Introduction
● INPE/CPRIME’s “ForPlan” Satellite Simulator
● Conops2M Modelling Process
● Example Model
● CapellaToForplan (C2F) Plugin
● Trade-study example
NanosatC-Br2 Mission
● Second satellite NanosatC-BR programme
○ INPE & UFSM Cooperation​
● Scientific & Technological mission:​
○ Collect data to better understand the Magnetic Anomaly
of the Southern Atlantic (SAMA) (SLP Payload)
○ Collect data to better understand the formation of
plasma bubbles in the ionosphere (SLP Payload)​
○ Validate in-orbit the Fault Tolerant Attitude
Determination System (SDATF Payload)
○ Validate in-orbit a radiation tolerant FPGA and
ASIC system (SMDH Payload)
● Develop human resources with experience in
space mission
NanosatC-BR2 moments after completing AIT at LIT​
Operational Analysis
Define objectives
as Operational
Capabilities
Associate
capabilities to
entities and actors
involved
“What the users of
the system need to
accomplish”
Operational Activities and Architecture
System Analysis
Define System
boundaries and
what your sollution
will perform
Logical Data Flow – Non-specific mission
Logically how data
will be collected
Ground Segment
Functions
Space Segment
Functions
External actor
functions
Logical Data Flow – Br2
How each payload
will collect data
Logical Architecture – Br2
Separate into
Space and Ground
Segments
Physical Data Flow – Space Segment – Non-specific Mission
Decompose
logical
functions into
equipment-
level functions
Basic platform
functions
Physical Data Flow – Space Segment – Br2
Physical Architecture – Space Segment
Allocate
functions to
equipment at
the desired
subdivision
level
Iterative
process –
decomposing
functions into
specific
equipment
Physical Data Flow – Ground Segment
Decompose
logical functions
for Ground Station
& Mission Control
Center
Represent the
functional flow for
how users will acces
data
Physical Architecture – Ground Segment
Exchange Scenarios
● Introduction
● INPE/CPRIME’s “ForPlan” Satellite Simulator
● Conops2M Modelling Process
● Example Model
● CapellaToForplan (C2F) Plugin
● Trade-study example
CapellaToForplan (C2F) Plugin
● Class Diagram
○ Organized in Data Packages
○ No support for multiple meta-levels
● Each Data Package has specific
conversion rules
○ Hard-coded names
● Each Class has specific attributes
● Equipment OperationFunction()
○ AlwaysOn, OnGroundStation,
TimedOp, RoiOp
Class Diagram – NanosatC-Br2
Class Diagram – Adding Property Values
Class Diagram – Operation Function
CapellaToForplan (C2F) Plugin
C2F Plugin Execution – Script Generation
Automatic Generated Code Example
Summary
● Introduction
● INPE/CPRIME’s “ForPlan” Satellite Simulator
● Conops2M Modelling Process
● Example Model
● CapellaToForplan (C2F) Plugin
● Trade-study example
NanosatC-Br2 Trade-Study Example
● NCBR2 had already passed design phase
● However, payloads and their operation were altered during development
● Power & Data budget limitations
● 3 Operation Scenarios balancing payload operation time with power and data budgets
● Polar orbit
● 2 Ground Stations
○ Natal & Santa Maria
● 2600 mAh battery pack
● No Sun-pointing
Scenario 1
● Three payloads AlwaysOn
○ Max operation parameters
● Battery depleted in 34 hours
● Data through the roof
Scenario 2
● TimedOp – 1 Payload each orbit
● Power balance stable
● Still too much data
Scenario 3
● SLP as RoiOP
○ AMAS & Equator
● 1 Orbit each for SMDH and SDATF
○ Lower sampling frequency
○ Lower data volume
● Valid operation scenario
○ Agreed with stakeholders
○ Using simulation results
Conclusion
● Model from mission operation objectives to initial architecture for simulation and analysis
● Quick way to generate different operation scenarios without having to directly code for the simulator
○ Also simpler than manually coding for every scenario
○ Can go directly to class diagram
● Result were used to drive the final CONOPS for NCBR2 mission
● Arcadia & Capella were great for developing the models and the process
○ Short learning curve for the basics
Danilo Pallamin de Almeida
Space Systems Engineer, MSc.
danilopallamin@gmail.com
danilo@endurosat.com
+359 089 959 3221
inpe.br/crs/nanosat/missao/nanosatc_br2
inf.mit.bme.hu
Thanks for
listening!
Any questions??
Danilo Pallamin de Almeida
Space Systems Engineer, MSc.
danilopallamin@gmail.com
danilo@endurosat.com
+359 089 959 3221
inpe.br/crs/nanosat/missao/nanosatc_br2
inf.mit.bme.hu
Danilo Pallamin de Almeida
Space Systems Engineer, MSc.
danilopallamin@gmail.com
danilo@endurosat.com
+359 089 959 3221
inpe.br/crs/nanosat/missao/nanosatc_br2
inf.mit.bme.hu

Contenu connexe

Tendances

STPA Analysis of Automotive Safety Using Arcadia and Capella
STPA Analysis of Automotive Safety Using Arcadia and CapellaSTPA Analysis of Automotive Safety Using Arcadia and Capella
STPA Analysis of Automotive Safety Using Arcadia and CapellaDavid Hetherington
 
Strategies and Tools for Model Reuse with Capella
Strategies and Tools for Model Reuse with CapellaStrategies and Tools for Model Reuse with Capella
Strategies and Tools for Model Reuse with CapellaObeo
 
Tailoring Arcadia Framework in Thales UK
Tailoring Arcadia Framework in Thales UKTailoring Arcadia Framework in Thales UK
Tailoring Arcadia Framework in Thales UKObeo
 
System of systems modeling with Capella
System of systems modeling with CapellaSystem of systems modeling with Capella
System of systems modeling with CapellaObeo
 
Scripting with Python to interact with Capella model
Scripting with Python to interact with Capella modelScripting with Python to interact with Capella model
Scripting with Python to interact with Capella modelObeo
 
CapellaDays2022 | CILAS - ArianeGroup | CILAS feedback about Capella use
CapellaDays2022 | CILAS - ArianeGroup | CILAS feedback about Capella useCapellaDays2022 | CILAS - ArianeGroup | CILAS feedback about Capella use
CapellaDays2022 | CILAS - ArianeGroup | CILAS feedback about Capella useObeo
 
Unleash the power of functional chains with Capella 1.3.1
Unleash the power of functional chains with Capella 1.3.1Unleash the power of functional chains with Capella 1.3.1
Unleash the power of functional chains with Capella 1.3.1Obeo
 
[ Capella Day 2019 ] Augmenting requirements with models to improve the artic...
[ Capella Day 2019 ] Augmenting requirements with models to improve the artic...[ Capella Day 2019 ] Augmenting requirements with models to improve the artic...
[ Capella Day 2019 ] Augmenting requirements with models to improve the artic...Obeo
 
MBSE and Model-Based Testing with Capella
MBSE and Model-Based Testing with CapellaMBSE and Model-Based Testing with Capella
MBSE and Model-Based Testing with CapellaObeo
 
From Model-based to Model and Simulation-based Systems Architectures
From Model-based to Model and Simulation-based Systems ArchitecturesFrom Model-based to Model and Simulation-based Systems Architectures
From Model-based to Model and Simulation-based Systems ArchitecturesObeo
 
Simulation with Python and MATLAB® in Capella
Simulation with Python and MATLAB® in CapellaSimulation with Python and MATLAB® in Capella
Simulation with Python and MATLAB® in CapellaObeo
 
Simplifying MBSE Tasks with Capella and MapleMBSE
Simplifying MBSE Tasks with Capella and MapleMBSESimplifying MBSE Tasks with Capella and MapleMBSE
Simplifying MBSE Tasks with Capella and MapleMBSEObeo
 
[Capella Day 2019] Model execution and system simulation in Capella
[Capella Day 2019] Model execution and system simulation in Capella[Capella Day 2019] Model execution and system simulation in Capella
[Capella Day 2019] Model execution and system simulation in CapellaObeo
 
Easily enrich capella models with your own domain extensions
Easily enrich capella models with your own domain extensionsEasily enrich capella models with your own domain extensions
Easily enrich capella models with your own domain extensionsObeo
 
CapellaDays2022 | SIEMENS | Expand MBSE into Model-based Production Engineeri...
CapellaDays2022 | SIEMENS | Expand MBSE into Model-based Production Engineeri...CapellaDays2022 | SIEMENS | Expand MBSE into Model-based Production Engineeri...
CapellaDays2022 | SIEMENS | Expand MBSE into Model-based Production Engineeri...Obeo
 
CapellaDays2022 | COMAC - PGM | How We Use Capella for Collaborative Design i...
CapellaDays2022 | COMAC - PGM | How We Use Capella for Collaborative Design i...CapellaDays2022 | COMAC - PGM | How We Use Capella for Collaborative Design i...
CapellaDays2022 | COMAC - PGM | How We Use Capella for Collaborative Design i...Obeo
 
Introduction to Capella and Arcadia with a Simple System
Introduction to Capella and Arcadia with a Simple SystemIntroduction to Capella and Arcadia with a Simple System
Introduction to Capella and Arcadia with a Simple SystemObeo
 
Connecting Textual Requirements with Capella Models
Connecting Textual Requirements with Capella Models Connecting Textual Requirements with Capella Models
Connecting Textual Requirements with Capella Models Obeo
 
Improving MBSE maturity with open-source tool Capella
Improving MBSE maturity with open-source tool Capella Improving MBSE maturity with open-source tool Capella
Improving MBSE maturity with open-source tool Capella Obeo
 
Automotive architecture examples with EAST-ADL models
Automotive architecture examples with EAST-ADL modelsAutomotive architecture examples with EAST-ADL models
Automotive architecture examples with EAST-ADL modelsJuha-Pekka Tolvanen
 

Tendances (20)

STPA Analysis of Automotive Safety Using Arcadia and Capella
STPA Analysis of Automotive Safety Using Arcadia and CapellaSTPA Analysis of Automotive Safety Using Arcadia and Capella
STPA Analysis of Automotive Safety Using Arcadia and Capella
 
Strategies and Tools for Model Reuse with Capella
Strategies and Tools for Model Reuse with CapellaStrategies and Tools for Model Reuse with Capella
Strategies and Tools for Model Reuse with Capella
 
Tailoring Arcadia Framework in Thales UK
Tailoring Arcadia Framework in Thales UKTailoring Arcadia Framework in Thales UK
Tailoring Arcadia Framework in Thales UK
 
System of systems modeling with Capella
System of systems modeling with CapellaSystem of systems modeling with Capella
System of systems modeling with Capella
 
Scripting with Python to interact with Capella model
Scripting with Python to interact with Capella modelScripting with Python to interact with Capella model
Scripting with Python to interact with Capella model
 
CapellaDays2022 | CILAS - ArianeGroup | CILAS feedback about Capella use
CapellaDays2022 | CILAS - ArianeGroup | CILAS feedback about Capella useCapellaDays2022 | CILAS - ArianeGroup | CILAS feedback about Capella use
CapellaDays2022 | CILAS - ArianeGroup | CILAS feedback about Capella use
 
Unleash the power of functional chains with Capella 1.3.1
Unleash the power of functional chains with Capella 1.3.1Unleash the power of functional chains with Capella 1.3.1
Unleash the power of functional chains with Capella 1.3.1
 
[ Capella Day 2019 ] Augmenting requirements with models to improve the artic...
[ Capella Day 2019 ] Augmenting requirements with models to improve the artic...[ Capella Day 2019 ] Augmenting requirements with models to improve the artic...
[ Capella Day 2019 ] Augmenting requirements with models to improve the artic...
 
MBSE and Model-Based Testing with Capella
MBSE and Model-Based Testing with CapellaMBSE and Model-Based Testing with Capella
MBSE and Model-Based Testing with Capella
 
From Model-based to Model and Simulation-based Systems Architectures
From Model-based to Model and Simulation-based Systems ArchitecturesFrom Model-based to Model and Simulation-based Systems Architectures
From Model-based to Model and Simulation-based Systems Architectures
 
Simulation with Python and MATLAB® in Capella
Simulation with Python and MATLAB® in CapellaSimulation with Python and MATLAB® in Capella
Simulation with Python and MATLAB® in Capella
 
Simplifying MBSE Tasks with Capella and MapleMBSE
Simplifying MBSE Tasks with Capella and MapleMBSESimplifying MBSE Tasks with Capella and MapleMBSE
Simplifying MBSE Tasks with Capella and MapleMBSE
 
[Capella Day 2019] Model execution and system simulation in Capella
[Capella Day 2019] Model execution and system simulation in Capella[Capella Day 2019] Model execution and system simulation in Capella
[Capella Day 2019] Model execution and system simulation in Capella
 
Easily enrich capella models with your own domain extensions
Easily enrich capella models with your own domain extensionsEasily enrich capella models with your own domain extensions
Easily enrich capella models with your own domain extensions
 
CapellaDays2022 | SIEMENS | Expand MBSE into Model-based Production Engineeri...
CapellaDays2022 | SIEMENS | Expand MBSE into Model-based Production Engineeri...CapellaDays2022 | SIEMENS | Expand MBSE into Model-based Production Engineeri...
CapellaDays2022 | SIEMENS | Expand MBSE into Model-based Production Engineeri...
 
CapellaDays2022 | COMAC - PGM | How We Use Capella for Collaborative Design i...
CapellaDays2022 | COMAC - PGM | How We Use Capella for Collaborative Design i...CapellaDays2022 | COMAC - PGM | How We Use Capella for Collaborative Design i...
CapellaDays2022 | COMAC - PGM | How We Use Capella for Collaborative Design i...
 
Introduction to Capella and Arcadia with a Simple System
Introduction to Capella and Arcadia with a Simple SystemIntroduction to Capella and Arcadia with a Simple System
Introduction to Capella and Arcadia with a Simple System
 
Connecting Textual Requirements with Capella Models
Connecting Textual Requirements with Capella Models Connecting Textual Requirements with Capella Models
Connecting Textual Requirements with Capella Models
 
Improving MBSE maturity with open-source tool Capella
Improving MBSE maturity with open-source tool Capella Improving MBSE maturity with open-source tool Capella
Improving MBSE maturity with open-source tool Capella
 
Automotive architecture examples with EAST-ADL models
Automotive architecture examples with EAST-ADL modelsAutomotive architecture examples with EAST-ADL models
Automotive architecture examples with EAST-ADL models
 

Similaire à Modeling & Simulation of CubeSat-based Missions'Concept of Operations

Planning Mode Simulator: A simulation tool for studying ALMA's scheduling be...
 Planning Mode Simulator: A simulation tool for studying ALMA's scheduling be... Planning Mode Simulator: A simulation tool for studying ALMA's scheduling be...
Planning Mode Simulator: A simulation tool for studying ALMA's scheduling be...Arturo Hoffstadt
 
Profiling & Testing with Spark
Profiling & Testing with SparkProfiling & Testing with Spark
Profiling & Testing with SparkRoger Rafanell Mas
 
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving SystemsPRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving SystemsNECST Lab @ Politecnico di Milano
 
Parallel Application Performance Prediction of Using Analysis Based Modeling
Parallel Application Performance Prediction of Using Analysis Based ModelingParallel Application Performance Prediction of Using Analysis Based Modeling
Parallel Application Performance Prediction of Using Analysis Based ModelingJason Liu
 
byteLAKE's expertise across NVIDIA architectures and configurations
byteLAKE's expertise across NVIDIA architectures and configurationsbyteLAKE's expertise across NVIDIA architectures and configurations
byteLAKE's expertise across NVIDIA architectures and configurationsbyteLAKE
 
Portfolio control version sn_v5
Portfolio control version sn_v5Portfolio control version sn_v5
Portfolio control version sn_v5Samuel Narcisse
 
Portofolio Control Version SN
Portofolio Control Version SNPortofolio Control Version SN
Portofolio Control Version SNSamuel Narcisse
 
SiriusCon2016 - Modelling Spacecraft On-board Software with Sirius
SiriusCon2016 - Modelling Spacecraft On-board Software with SiriusSiriusCon2016 - Modelling Spacecraft On-board Software with Sirius
SiriusCon2016 - Modelling Spacecraft On-board Software with SiriusObeo
 
Optimized Multi-agent Box-pushing - 2017-10-24
Optimized Multi-agent Box-pushing - 2017-10-24Optimized Multi-agent Box-pushing - 2017-10-24
Optimized Multi-agent Box-pushing - 2017-10-24Aritra Sarkar
 
lecture_GPUArchCUDA04-OpenMPHOMP.pdf
lecture_GPUArchCUDA04-OpenMPHOMP.pdflecture_GPUArchCUDA04-OpenMPHOMP.pdf
lecture_GPUArchCUDA04-OpenMPHOMP.pdfTigabu Yaya
 
Kubernetes Introduction
Kubernetes IntroductionKubernetes Introduction
Kubernetes IntroductionMiloš Zubal
 
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...Data Con LA
 
RECAP: The Simulation Approach
RECAP: The Simulation ApproachRECAP: The Simulation Approach
RECAP: The Simulation ApproachRECAP Project
 
Performance Characterization and Optimization of In-Memory Data Analytics on ...
Performance Characterization and Optimization of In-Memory Data Analytics on ...Performance Characterization and Optimization of In-Memory Data Analytics on ...
Performance Characterization and Optimization of In-Memory Data Analytics on ...Ahsan Javed Awan
 
Rally--OpenStack Benchmarking at Scale
Rally--OpenStack Benchmarking at ScaleRally--OpenStack Benchmarking at Scale
Rally--OpenStack Benchmarking at ScaleMirantis
 
Porting an MPI application to hybrid MPI+OpenMP with Reveal tool on Shaheen II
Porting an MPI application to hybrid MPI+OpenMP with Reveal tool on Shaheen IIPorting an MPI application to hybrid MPI+OpenMP with Reveal tool on Shaheen II
Porting an MPI application to hybrid MPI+OpenMP with Reveal tool on Shaheen IIGeorge Markomanolis
 
Spark Summit EU talk by Josef Habdank
Spark Summit EU talk by Josef HabdankSpark Summit EU talk by Josef Habdank
Spark Summit EU talk by Josef HabdankSpark Summit
 

Similaire à Modeling & Simulation of CubeSat-based Missions'Concept of Operations (20)

Planning Mode Simulator: A simulation tool for studying ALMA's scheduling be...
 Planning Mode Simulator: A simulation tool for studying ALMA's scheduling be... Planning Mode Simulator: A simulation tool for studying ALMA's scheduling be...
Planning Mode Simulator: A simulation tool for studying ALMA's scheduling be...
 
Profiling & Testing with Spark
Profiling & Testing with SparkProfiling & Testing with Spark
Profiling & Testing with Spark
 
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving SystemsPRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems
 
Parallel Application Performance Prediction of Using Analysis Based Modeling
Parallel Application Performance Prediction of Using Analysis Based ModelingParallel Application Performance Prediction of Using Analysis Based Modeling
Parallel Application Performance Prediction of Using Analysis Based Modeling
 
byteLAKE's expertise across NVIDIA architectures and configurations
byteLAKE's expertise across NVIDIA architectures and configurationsbyteLAKE's expertise across NVIDIA architectures and configurations
byteLAKE's expertise across NVIDIA architectures and configurations
 
Portfolio control version sn_v5
Portfolio control version sn_v5Portfolio control version sn_v5
Portfolio control version sn_v5
 
Portofolio Control Version SN
Portofolio Control Version SNPortofolio Control Version SN
Portofolio Control Version SN
 
SiriusCon2016 - Modelling Spacecraft On-board Software with Sirius
SiriusCon2016 - Modelling Spacecraft On-board Software with SiriusSiriusCon2016 - Modelling Spacecraft On-board Software with Sirius
SiriusCon2016 - Modelling Spacecraft On-board Software with Sirius
 
Optimized Multi-agent Box-pushing - 2017-10-24
Optimized Multi-agent Box-pushing - 2017-10-24Optimized Multi-agent Box-pushing - 2017-10-24
Optimized Multi-agent Box-pushing - 2017-10-24
 
lecture_GPUArchCUDA04-OpenMPHOMP.pdf
lecture_GPUArchCUDA04-OpenMPHOMP.pdflecture_GPUArchCUDA04-OpenMPHOMP.pdf
lecture_GPUArchCUDA04-OpenMPHOMP.pdf
 
cug2011-praveen
cug2011-praveencug2011-praveen
cug2011-praveen
 
Kubernetes Introduction
Kubernetes IntroductionKubernetes Introduction
Kubernetes Introduction
 
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
 
RECAP: The Simulation Approach
RECAP: The Simulation ApproachRECAP: The Simulation Approach
RECAP: The Simulation Approach
 
ltu-cover6899158065669445093
ltu-cover6899158065669445093ltu-cover6899158065669445093
ltu-cover6899158065669445093
 
SparkNet presentation
SparkNet presentationSparkNet presentation
SparkNet presentation
 
Performance Characterization and Optimization of In-Memory Data Analytics on ...
Performance Characterization and Optimization of In-Memory Data Analytics on ...Performance Characterization and Optimization of In-Memory Data Analytics on ...
Performance Characterization and Optimization of In-Memory Data Analytics on ...
 
Rally--OpenStack Benchmarking at Scale
Rally--OpenStack Benchmarking at ScaleRally--OpenStack Benchmarking at Scale
Rally--OpenStack Benchmarking at Scale
 
Porting an MPI application to hybrid MPI+OpenMP with Reveal tool on Shaheen II
Porting an MPI application to hybrid MPI+OpenMP with Reveal tool on Shaheen IIPorting an MPI application to hybrid MPI+OpenMP with Reveal tool on Shaheen II
Porting an MPI application to hybrid MPI+OpenMP with Reveal tool on Shaheen II
 
Spark Summit EU talk by Josef Habdank
Spark Summit EU talk by Josef HabdankSpark Summit EU talk by Josef Habdank
Spark Summit EU talk by Josef Habdank
 

Plus de Obeo

Digitally assisted design for safety analysis
Digitally assisted design for safety analysisDigitally assisted design for safety analysis
Digitally assisted design for safety analysisObeo
 
INCOSE IS 2023 | You deserve more than the best in class MBSE tool
INCOSE IS 2023 | You deserve more than the best in class MBSE toolINCOSE IS 2023 | You deserve more than the best in class MBSE tool
INCOSE IS 2023 | You deserve more than the best in class MBSE toolObeo
 
Gestion applicative des données, un REX du Ministère de l'Éducation Nationale
Gestion applicative des données, un REX du Ministère de l'Éducation NationaleGestion applicative des données, un REX du Ministère de l'Éducation Nationale
Gestion applicative des données, un REX du Ministère de l'Éducation NationaleObeo
 
Sirius Web Advanced : Customize and Extend the Platform
Sirius Web Advanced : Customize and Extend the PlatformSirius Web Advanced : Customize and Extend the Platform
Sirius Web Advanced : Customize and Extend the PlatformObeo
 
Sirius Web 101 : Create a Modeler With No Code
Sirius Web 101 : Create a Modeler With No CodeSirius Web 101 : Create a Modeler With No Code
Sirius Web 101 : Create a Modeler With No CodeObeo
 
Sirius Project, Now and In the Future
Sirius Project, Now and In the FutureSirius Project, Now and In the Future
Sirius Project, Now and In the FutureObeo
 
Visualizing, Analyzing and Optimizing Automotive Architecture Models using Si...
Visualizing, Analyzing and Optimizing Automotive Architecture Models using Si...Visualizing, Analyzing and Optimizing Automotive Architecture Models using Si...
Visualizing, Analyzing and Optimizing Automotive Architecture Models using Si...Obeo
 
Defining Viewpoints for Ontology-Based DSLs
Defining Viewpoints for Ontology-Based DSLsDefining Viewpoints for Ontology-Based DSLs
Defining Viewpoints for Ontology-Based DSLsObeo
 
Development of DSL for Context-Aware Mobile Applications
Development of DSL for Context-Aware Mobile ApplicationsDevelopment of DSL for Context-Aware Mobile Applications
Development of DSL for Context-Aware Mobile ApplicationsObeo
 
SimfiaNeo - Workbench for Safety Analysis powered by Sirius
SimfiaNeo - Workbench for Safety Analysis powered by SiriusSimfiaNeo - Workbench for Safety Analysis powered by Sirius
SimfiaNeo - Workbench for Safety Analysis powered by SiriusObeo
 
Get into MBSE-MBSA process with a dedicated toolchain
Get into MBSE-MBSA process with a dedicated toolchainGet into MBSE-MBSA process with a dedicated toolchain
Get into MBSE-MBSA process with a dedicated toolchainObeo
 
Capella annual meeting 2022
Capella annual meeting 2022Capella annual meeting 2022
Capella annual meeting 2022Obeo
 
Générez automatiquement vos diagrammes d'architecture | Webinaire Obeo SmartEA
Générez automatiquement vos diagrammes d'architecture | Webinaire Obeo SmartEAGénérez automatiquement vos diagrammes d'architecture | Webinaire Obeo SmartEA
Générez automatiquement vos diagrammes d'architecture | Webinaire Obeo SmartEAObeo
 
Capella (once again) in space, meeting nanosatellites
Capella (once again) in space, meeting nanosatellitesCapella (once again) in space, meeting nanosatellites
Capella (once again) in space, meeting nanosatellitesObeo
 
Identifier et suivre les applications à risque pour des processus métier | We...
Identifier et suivre les applications à risque pour des processus métier | We...Identifier et suivre les applications à risque pour des processus métier | We...
Identifier et suivre les applications à risque pour des processus métier | We...Obeo
 

Plus de Obeo (15)

Digitally assisted design for safety analysis
Digitally assisted design for safety analysisDigitally assisted design for safety analysis
Digitally assisted design for safety analysis
 
INCOSE IS 2023 | You deserve more than the best in class MBSE tool
INCOSE IS 2023 | You deserve more than the best in class MBSE toolINCOSE IS 2023 | You deserve more than the best in class MBSE tool
INCOSE IS 2023 | You deserve more than the best in class MBSE tool
 
Gestion applicative des données, un REX du Ministère de l'Éducation Nationale
Gestion applicative des données, un REX du Ministère de l'Éducation NationaleGestion applicative des données, un REX du Ministère de l'Éducation Nationale
Gestion applicative des données, un REX du Ministère de l'Éducation Nationale
 
Sirius Web Advanced : Customize and Extend the Platform
Sirius Web Advanced : Customize and Extend the PlatformSirius Web Advanced : Customize and Extend the Platform
Sirius Web Advanced : Customize and Extend the Platform
 
Sirius Web 101 : Create a Modeler With No Code
Sirius Web 101 : Create a Modeler With No CodeSirius Web 101 : Create a Modeler With No Code
Sirius Web 101 : Create a Modeler With No Code
 
Sirius Project, Now and In the Future
Sirius Project, Now and In the FutureSirius Project, Now and In the Future
Sirius Project, Now and In the Future
 
Visualizing, Analyzing and Optimizing Automotive Architecture Models using Si...
Visualizing, Analyzing and Optimizing Automotive Architecture Models using Si...Visualizing, Analyzing and Optimizing Automotive Architecture Models using Si...
Visualizing, Analyzing and Optimizing Automotive Architecture Models using Si...
 
Defining Viewpoints for Ontology-Based DSLs
Defining Viewpoints for Ontology-Based DSLsDefining Viewpoints for Ontology-Based DSLs
Defining Viewpoints for Ontology-Based DSLs
 
Development of DSL for Context-Aware Mobile Applications
Development of DSL for Context-Aware Mobile ApplicationsDevelopment of DSL for Context-Aware Mobile Applications
Development of DSL for Context-Aware Mobile Applications
 
SimfiaNeo - Workbench for Safety Analysis powered by Sirius
SimfiaNeo - Workbench for Safety Analysis powered by SiriusSimfiaNeo - Workbench for Safety Analysis powered by Sirius
SimfiaNeo - Workbench for Safety Analysis powered by Sirius
 
Get into MBSE-MBSA process with a dedicated toolchain
Get into MBSE-MBSA process with a dedicated toolchainGet into MBSE-MBSA process with a dedicated toolchain
Get into MBSE-MBSA process with a dedicated toolchain
 
Capella annual meeting 2022
Capella annual meeting 2022Capella annual meeting 2022
Capella annual meeting 2022
 
Générez automatiquement vos diagrammes d'architecture | Webinaire Obeo SmartEA
Générez automatiquement vos diagrammes d'architecture | Webinaire Obeo SmartEAGénérez automatiquement vos diagrammes d'architecture | Webinaire Obeo SmartEA
Générez automatiquement vos diagrammes d'architecture | Webinaire Obeo SmartEA
 
Capella (once again) in space, meeting nanosatellites
Capella (once again) in space, meeting nanosatellitesCapella (once again) in space, meeting nanosatellites
Capella (once again) in space, meeting nanosatellites
 
Identifier et suivre les applications à risque pour des processus métier | We...
Identifier et suivre les applications à risque pour des processus métier | We...Identifier et suivre les applications à risque pour des processus métier | We...
Identifier et suivre les applications à risque pour des processus métier | We...
 

Dernier

The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...
The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...
The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...ranjana rawat
 
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...Christo Ananth
 
KubeKraft presentation @CloudNativeHooghly
KubeKraft presentation @CloudNativeHooghlyKubeKraft presentation @CloudNativeHooghly
KubeKraft presentation @CloudNativeHooghlysanyuktamishra911
 
Top Rated Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...
Top Rated  Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...Top Rated  Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...
Top Rated Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...Call Girls in Nagpur High Profile
 
Generative AI or GenAI technology based PPT
Generative AI or GenAI technology based PPTGenerative AI or GenAI technology based PPT
Generative AI or GenAI technology based PPTbhaskargani46
 
University management System project report..pdf
University management System project report..pdfUniversity management System project report..pdf
University management System project report..pdfKamal Acharya
 
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELL
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELLPVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELL
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELLManishPatel169454
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxAsutosh Ranjan
 
Thermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptThermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptDineshKumar4165
 
Thermal Engineering Unit - I & II . ppt
Thermal Engineering  Unit - I & II . pptThermal Engineering  Unit - I & II . ppt
Thermal Engineering Unit - I & II . pptDineshKumar4165
 
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdfONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdfKamal Acharya
 
Thermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VThermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VDineshKumar4165
 
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and workingUNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and workingrknatarajan
 
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...SUHANI PANDEY
 
Online banking management system project.pdf
Online banking management system project.pdfOnline banking management system project.pdf
Online banking management system project.pdfKamal Acharya
 
Double rodded leveling 1 pdf activity 01
Double rodded leveling 1 pdf activity 01Double rodded leveling 1 pdf activity 01
Double rodded leveling 1 pdf activity 01KreezheaRecto
 

Dernier (20)

Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort ServiceCall Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
 
The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...
The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...
The Most Attractive Pune Call Girls Budhwar Peth 8250192130 Will You Miss Thi...
 
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
 
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
 
KubeKraft presentation @CloudNativeHooghly
KubeKraft presentation @CloudNativeHooghlyKubeKraft presentation @CloudNativeHooghly
KubeKraft presentation @CloudNativeHooghly
 
Top Rated Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...
Top Rated  Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...Top Rated  Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...
Top Rated Pune Call Girls Budhwar Peth ⟟ 6297143586 ⟟ Call Me For Genuine Se...
 
Generative AI or GenAI technology based PPT
Generative AI or GenAI technology based PPTGenerative AI or GenAI technology based PPT
Generative AI or GenAI technology based PPT
 
NFPA 5000 2024 standard .
NFPA 5000 2024 standard                                  .NFPA 5000 2024 standard                                  .
NFPA 5000 2024 standard .
 
University management System project report..pdf
University management System project report..pdfUniversity management System project report..pdf
University management System project report..pdf
 
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELL
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELLPVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELL
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELL
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptx
 
Thermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptThermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.ppt
 
Thermal Engineering Unit - I & II . ppt
Thermal Engineering  Unit - I & II . pptThermal Engineering  Unit - I & II . ppt
Thermal Engineering Unit - I & II . ppt
 
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdfONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
 
Thermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VThermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - V
 
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and workingUNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
 
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Kothrud ( Pune ) Call ON 8005736733 Starting From 5K to ...
 
Online banking management system project.pdf
Online banking management system project.pdfOnline banking management system project.pdf
Online banking management system project.pdf
 
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar ≼🔝 Delhi door step de...
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar  ≼🔝 Delhi door step de...Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar  ≼🔝 Delhi door step de...
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar ≼🔝 Delhi door step de...
 
Double rodded leveling 1 pdf activity 01
Double rodded leveling 1 pdf activity 01Double rodded leveling 1 pdf activity 01
Double rodded leveling 1 pdf activity 01
 

Modeling & Simulation of CubeSat-based Missions'Concept of Operations

  • 1.
  • 2.
  • 3.
  • 4. Modelling & Simulation of CubeSat-based Missions' Concept of Operations An application using Arcadia/Capella Danilo Pallamin de Almeida
  • 5. Introducing Myself Danilo Pallamin de Almeida ● MSc. Space Systems Engineering & Management @INPE ○ NanosatC-Br2 – SPORT – CRON-1 CubeSat missions ● Mechatronics Engineer @EESC/USP ● Space exploration enthusiast & advocate for democratized access to space ● Why I got into modelling: ○ The higher the complexity of a system, the greater the significance of communication ○ Models can greatly improve communication in engineering ● Currently - Systems Engineer @ EnduroSat
  • 6.
  • 7. Summary ● Introduction ● INPE/CPRIME’s “ForPlan” Satellite Simulator ● Conops2M Modelling Process ● Example Model ● CapellaToForplan (C2F) Plugin ● Trade-study example
  • 8. Introduction ● Work developed during Masters @Brazil’s National Institute for Space Research (INPE) ○ 2018-2020 ○ Dr. Fátima Mattiello Francisco & Dr. Fabiano Luis de Sousa ● Began by investigating modelling practices to assist the early-stage design phase of Space Missions ● Operation scenario simulation is used for trade-studies at INPE’s Concurrent Engineering Center CPRIME ○ ForPlan Simulator ● Resulted in a modelling process developed to guide the modelling of CubeSat-based missions and their CONOPS for early-stage design studies, preparing for operation scenario simulation ○ Generic (Non-specific) Mission Model ○ NanosatC-Br2 Model INPE’s CPRIME
  • 9. Concept of Operations (CONOPS) ● How the system will operate to meet stakeholder expectations ● Description of the system’s characteristics from an operational perspective. ● CONOPS at early stages include: ○ Initial physical and logical architecture – space and ground segments ○ Interfaces between elements of the architecture ○ Mission objectives and constraints analysis ○ Operation timelines, modes and scenarios ○ End-to-end communications strategy and data-flow ○ Power and data budget analysis ● Different institutions use different documentation standards ○ European Cooperation for Space Standardization (ECSS): MOCD, MAR, SSUM ○ Large documentation volume, redundant information ○ Use of models can concentrate & simplify – especially for CubeSats (“simpler” operation)
  • 10. Why Capella/Arcadia ● Integrated tool & method ○ Methodological Guidance – Great combination for a step-by-step process ● Open source tool ○ Reduced barriers of entry ○ Allowed for our plugin development ● Domain-specific Modelling Language ○ Intuitive & comprehensive – friendly when discussing model with people not used to model standards ● Great previous experiences from colleagues (former INPE students) ○ Community Source: Arcadia/Capella website
  • 11. ● Introduction ● INPE/CPRIME’s “ForPlan” Satellite Simulator ● Conops2M Modelling Process ● Example Model ● CapellaToForplan (C2F) Plugin ● Trade-study example
  • 12. INPE/CPRIME’s ForPlan Satellite Simulator ● Functional simulation of satellites and associated ground segment to reflect operational scenarios of the mission under analysis ● Verification of mission concept of operations ● Early stage studies at CPRIME ● Simulation core modules​ ○ Space environment​ ○ Equipment​ ○ Power​ ○ OBDH / TT&C ● Written in Julia ○ INPE’s Dr. Ronan A. Chagas ○ https://www.ronanarraes.com/ ○ ronan.arraes@inpe.br
  • 13. INPE/CPRIME’s ForPlan Satellite Simulator Modelled simulator functions Required inputs from the user
  • 14. Configuring ForPlan # 2. Equipment list # ============================================================================== equip_1= ForplanSimulatorCore.Equipment{Float64}( name = "OBC", f! = ForplanSimulatorCore.equip_always_on!, params = [torb, 0.0, 0.383, 30.0]) equip_2= ForplanSimulatorCore.Equipment{Float64}( name = "Receiver", f! = ForplanSimulatorCore.equip_always_on!, params = [torb, 0.0, 0.193, 0.0]) equip_3= ForplanSimulatorCore.Equipment{Float64}( name = "Transmitter", f! = ForplanSimulatorCore.equip_on_ground_station!, params = [torb, 0.0, 0.0, 1.078, 0.0, 0.0, 0]) equip_4= ForplanSimulatorCore.Equipment{Float64}( name = "Magnetometer", f! = RoiOp, params = [torb, 0.016, 96.0, [[-60.0, 0.0, -90.0, -20.0]]]) equip_5= ForplanSimulatorCore.Equipment{Float64}( name = "EPS", f! = ForplanSimulatorCore.equip_always_on!, params = [torb, 0.0, 0.250, 0.0]) Core method Equipment name Operation function Operation parameters Equipment instance
  • 15. ● Introduction ● INPE/CPRIME’s “ForPlan” Satellite Simulator ● Conops2M Modelling Process ● Example Model ● CapellaToForplan (C2F) Plugin ● Trade-study example
  • 16. Conops2M Modelling Process ● Developed based on Arcadia ● A set of sequential steps ○ generate a model of a space mission concept of operations ○ prepare operation scenarios for simulation ● Begin at high-level abstraction: Mission objectives as operation capabilities ● Iteratively decompose functions until we reach equipment-level on spacecraft & facilities for ground segment ● Model parameters for operation scenario simulation ○ Transform model into simulator input
  • 17. Generating the Simulator Configuration Script ● ForPlan is configured through a Julia script ● Capella is Eclipse-based ○ Language built on EMF ○ Capella 1.3.1 ● Developed a plugin to retrieve model elements and generate Julia code based on their attributes ○ ADVANCE Project – Budapest University of Technology and Economics ○ Bence Graics & Dr. Vince Molnár ○ Xtend ■ Specifically designed for model transformation and code generation ● Defined rules for a Class Diagram architecture and the creation of class instances according to each model element ○ Traverse instance models and derive arbitrary code
  • 18. ● Introduction ● INPE/CPRIME’s “ForPlan” Satellite Simulator ● Conops2M Modelling Process ● Example Model ● CapellaToForplan (C2F) Plugin ● Trade-study example
  • 19. NanosatC-Br2 Mission ● Second satellite NanosatC-BR programme ○ INPE & UFSM Cooperation​ ● Scientific & Technological mission:​ ○ Collect data to better understand the Magnetic Anomaly of the Southern Atlantic (SAMA) (SLP Payload) ○ Collect data to better understand the formation of plasma bubbles in the ionosphere (SLP Payload)​ ○ Validate in-orbit the Fault Tolerant Attitude Determination System (SDATF Payload) ○ Validate in-orbit a radiation tolerant FPGA and ASIC system (SMDH Payload) ● Develop human resources with experience in space mission NanosatC-BR2 moments after completing AIT at LIT​
  • 20. Operational Analysis Define objectives as Operational Capabilities Associate capabilities to entities and actors involved “What the users of the system need to accomplish”
  • 22. System Analysis Define System boundaries and what your sollution will perform
  • 23. Logical Data Flow – Non-specific mission Logically how data will be collected Ground Segment Functions Space Segment Functions External actor functions
  • 24. Logical Data Flow – Br2 How each payload will collect data
  • 25. Logical Architecture – Br2 Separate into Space and Ground Segments
  • 26. Physical Data Flow – Space Segment – Non-specific Mission Decompose logical functions into equipment- level functions Basic platform functions
  • 27. Physical Data Flow – Space Segment – Br2
  • 28. Physical Architecture – Space Segment Allocate functions to equipment at the desired subdivision level Iterative process – decomposing functions into specific equipment
  • 29. Physical Data Flow – Ground Segment Decompose logical functions for Ground Station & Mission Control Center Represent the functional flow for how users will acces data
  • 30. Physical Architecture – Ground Segment
  • 32. ● Introduction ● INPE/CPRIME’s “ForPlan” Satellite Simulator ● Conops2M Modelling Process ● Example Model ● CapellaToForplan (C2F) Plugin ● Trade-study example
  • 33. CapellaToForplan (C2F) Plugin ● Class Diagram ○ Organized in Data Packages ○ No support for multiple meta-levels ● Each Data Package has specific conversion rules ○ Hard-coded names ● Each Class has specific attributes ● Equipment OperationFunction() ○ AlwaysOn, OnGroundStation, TimedOp, RoiOp
  • 34. Class Diagram – NanosatC-Br2
  • 35. Class Diagram – Adding Property Values
  • 36. Class Diagram – Operation Function
  • 38. C2F Plugin Execution – Script Generation
  • 40. Summary ● Introduction ● INPE/CPRIME’s “ForPlan” Satellite Simulator ● Conops2M Modelling Process ● Example Model ● CapellaToForplan (C2F) Plugin ● Trade-study example
  • 41. NanosatC-Br2 Trade-Study Example ● NCBR2 had already passed design phase ● However, payloads and their operation were altered during development ● Power & Data budget limitations ● 3 Operation Scenarios balancing payload operation time with power and data budgets ● Polar orbit ● 2 Ground Stations ○ Natal & Santa Maria ● 2600 mAh battery pack ● No Sun-pointing
  • 42. Scenario 1 ● Three payloads AlwaysOn ○ Max operation parameters ● Battery depleted in 34 hours ● Data through the roof
  • 43. Scenario 2 ● TimedOp – 1 Payload each orbit ● Power balance stable ● Still too much data
  • 44. Scenario 3 ● SLP as RoiOP ○ AMAS & Equator ● 1 Orbit each for SMDH and SDATF ○ Lower sampling frequency ○ Lower data volume ● Valid operation scenario ○ Agreed with stakeholders ○ Using simulation results
  • 45. Conclusion ● Model from mission operation objectives to initial architecture for simulation and analysis ● Quick way to generate different operation scenarios without having to directly code for the simulator ○ Also simpler than manually coding for every scenario ○ Can go directly to class diagram ● Result were used to drive the final CONOPS for NCBR2 mission ● Arcadia & Capella were great for developing the models and the process ○ Short learning curve for the basics
  • 46. Danilo Pallamin de Almeida Space Systems Engineer, MSc. danilopallamin@gmail.com danilo@endurosat.com +359 089 959 3221 inpe.br/crs/nanosat/missao/nanosatc_br2 inf.mit.bme.hu Thanks for listening! Any questions??
  • 47. Danilo Pallamin de Almeida Space Systems Engineer, MSc. danilopallamin@gmail.com danilo@endurosat.com +359 089 959 3221 inpe.br/crs/nanosat/missao/nanosatc_br2 inf.mit.bme.hu
  • 48. Danilo Pallamin de Almeida Space Systems Engineer, MSc. danilopallamin@gmail.com danilo@endurosat.com +359 089 959 3221 inpe.br/crs/nanosat/missao/nanosatc_br2 inf.mit.bme.hu