Curriculum
- 8 Sections
- 94 Lessons
- 10 Weeks
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- Module 1: OrcaFlex Python API and Environment Setup17
- 1.1Introduction to OrcaFlex automation
- 1.2Benefits of Python-driven engineering workflows
- 1.3Manual workflows versus automated workflows
- 1.4Introduction to OrcFxAPI
- 1.5Understanding OrcaFlex–Python interaction
- 1.6Python installation and environment configuration
- 1.7Installing and importing required Python libraries
- 1.8Importing OrcFxAPI
- 1.9Testing OrcaFlex connectivity through Python
- 1.10Understanding the OrcFxAPI object structure
- 1.11Working with Model objects
- 1.12Accessing OrcaFlex objects through Python
- 1.13Understanding properties, methods, and API calls
- 1.14Basic Python scripting patterns for OrcaFlex
- 1.15Working with variables, loops, functions, lists, and dictionaries
- 1.16File handling concepts for automation scripts
- 1.17Running a basic OrcaFlex Python script
- Module 2: Programmatic Model Creation and Object Management28
- 2.1Creating a new OrcaFlex model using Python
- 2.2Understanding model initialization
- 2.3Creating model objects programmatically
- 2.4Working with:
- 2.5Lines
- 2.6Vessels
- 2.7Buoys
- 2.8Anchors and connections
- 2.9Line types
- 2.10Shapes and other model components
- 2.11Naming and identifying model objects
- 2.12Setting object properties through scripts
- 2.13Configuring environmental conditions
- 2.14Defining water depth
- 2.15Setting wave conditions
- 2.16Configuring current parameters
- 2.17Configuring wind conditions where applicable
- 2.18Working with line properties
- 2.19Assigning line types and segment information
- 2.20Managing connections and coordinates
- 2.21Iterating through model objects
- 2.22Searching and filtering objects
- 2.23Bulk object manipulation
- 2.24Creating reusable Python functions
- 2.25Deleting and recreating objects programmatically
- 2.26Saving generated OrcaFlex models
- 2.27Applying automated file naming conventions
- 2.28Practical Exercise Create an OrcaFlex model through Python, configure key objects and environmental conditions, and save the generated model automatically.
- Module 3: Model Modification, Batch Processing and Parametric Studies26
- 3.1Loading existing OrcaFlex models through Python
- 3.2Reading current model configurations
- 3.3Accessing object properties
- 3.4Changing model parameters programmatically
- 3.5Updating line characteristics
- 3.6Modifying vessel properties
- 3.7Changing environmental conditions
- 3.8Updating object positions and connections
- 3.9Applying parameter changes across several objects
- 3.10Bulk modification techniques
- 3.11Automating repetitive model changes
- 3.12Creating model variants
- 3.13Parameter-driven model generation
- 3.14Introduction to batch processing
- 3.15Processing multiple OrcaFlex model files
- 3.16Folder and directory traversal
- 3.17Automatically identifying .dat and .sim files
- 3.18Creating parameter combinations
- 3.19Introduction to parametric studies
- 3.20Automating environmental variation studies
- 3.21Automating geometry and configuration variations
- 3.22Sensitivity analysis workflows
- 3.23Maintaining traceability between model variations
- 3.24Automated model naming and storage
- 3.25Practical Exercise
- 3.26Generate multiple OrcaFlex model variants by changing environmental and structural parameters using a single Python automation script.
- Module 4: Automated Simulation Execution and Management23
- 4.1Understanding simulation control through OrcFxAPI
- 4.2Running statics programmatically
- 4.3Running dynamic simulations through Python
- 4.4Checking simulation states
- 4.5Monitoring simulation progress
- 4.6Saving simulation results
- 4.7Managing .sim files automatically
- 4.8Executing multiple simulation cases
- 4.9Sequential batch simulation
- 4.10Automating simulation folders
- 4.11Detecting completed and failed simulations
- 4.12Handling interrupted simulation processes
- 4.13Managing simulation exceptions
- 4.14Restart and recovery concepts
- 4.15Recording simulation status
- 4.16Creating execution logs
- 4.17Managing large simulation sets
- 4.18Introduction to parallel processing
- 4.19Multiprocessing versus multithreading concepts
- 4.20Considerations for OrcaFlex licensing and computing resources
- 4.21Improving efficiency of automated simulation workflows
- 4.22Practical Exercise
- 4.23Execute several model cases automatically, track simulation status, save completed simulations, and record unsuccessful cases for review.
- Module 5: Automated Results Extraction and Post-Processing0
- Module 6: External Data Integration and Automated Reporting0
- Module 7: Advanced Python Automation Techniques in OrcaFlex0
- Module 8: Applied OrcaFlex Python Automation Case Studies0