Advanced Engineering
Automated Design-Space Exploration with Synapse + OrcaFlex
Zeta Subsea combines OrcaFlex dynamic analysis with Synapse optimisation to systematically explore complex offshore engineering design spaces.
Instead of manually changing parameters and repeating simulations, our workflow automatically evaluates design configurations against defined engineering variables, constraints and objectives.
Traditional offshore analysis often relies on repeated manual iterations: modify the model, run the simulation, review the results and repeat.
Our Synapse + OrcaFlex workflow connects these steps into an automated optimisation loop.
01
Define
Zeta Subsea
The engineering problem, design variables, constraints and objectives.
02
Generate
Synapse
Candidate configurations are created from the defined design space.
03
Simulate
OrcaFlex
Each configuration is analysed as a dynamic offshore system.
04
Evaluate
OrcaFlex results
Responses are extracted and checked against project requirements.
05
Optimise
Synapse
Feasible solutions and trade-offs guide the next design iterations.
Results feed the next design iteration back into Synapse, closing the optimisation loop.
Synapse manages the design variables, objectives and constraints. OrcaFlex evaluates the physical response of each configuration. Results are automatically returned to the optimisation workflow to guide the next design iterations.
Define the parameters that can change, together with the engineering constraints and optimisation objectives.
Typical design variables
Candidate configurations are automatically generated and analysed in OrcaFlex.
Relevant results are automatically extracted and checked against project requirements.
Typical checks
Synapse uses the simulation results to explore feasible solutions and identify engineering trade-offs between competing objectives.
The workflow can be adapted to offshore systems that can be represented by design variables, engineering constraints and measurable objectives.
Configuration, buoyancy, geometry, loads, curvature and clearance.
Flexible risers, lazy-wave configurations and other OrcaFlex-based riser design studies.
Line geometry, anchor positions, pretension, offsets, loads and multi-objective design studies.
Parametric assessment and repeated simulation workflows for installation engineering.
Systematic evaluation of large design spaces and interacting engineering parameters.
Evaluate a much wider set of configurations than is normally practical through manual iteration.
Assess candidate designs against several engineering requirements simultaneously.
Understand trade-offs between feasible solutions using multi-objective optimisation.
Automate model updates, simulation execution, result extraction and iterative evaluation.
Numerical simulation of the offshore system and calculation of the engineering response.
Optimisation environment used to manage variables, constraints, objectives and iterative design-space exploration.
Engineering formulation, software integration, OrcaFlex automation, model development and interpretation of the resulting design solutions.
Simulation provides the response. Optimisation guides the search. Engineering defines the solution.
A Synapse + OrcaFlex workflow was applied to a lazy-wave flexible riser design problem using multiple design variables, engineering constraints and competing objectives.
The workflow was also applied to a MetOcean buoy mooring system to explore the trade-off between structural loading and total mooring length.
The optimisation produces a Pareto frontier that helps visualise the trade-offs between feasible solutions.
View technical demonstration on LinkedInThe Synapse + OrcaFlex integration has also been applied in research studies addressing optimisation problems for floating offshore wind systems.
These studies demonstrate automated model generation, simulation execution, results extraction and optimisation workflows for mooring systems and dynamic power cables.
Problems involving multiple design variables, constraints, competing objectives or repeated OrcaFlex simulations can be strong candidates for an optimisation-driven approach.
Tell us what you need to evaluate and we can assess whether the problem is suitable for automated design-space exploration.
