YUANSUAN | ENGINEERING AI PLATFORM
Connect physics, data and engineering knowledge to model problems, compare designs and validate results.
Represent engineering problems through models, explore solution spaces through computation, organize task execution through intelligence
Broader modeling
Model complex engineering problems with physics and data to predict the effects of change
Larger exploration spaces
Compare alternatives through prediction, inverse analysis and optimization
More complex tasks
Understand goals, coordinate capabilities and advance engineering tasks
Task-aware scheduling · Parallel solving · Elastic scaling
HPC centers · GPU clusters · Cross-region coordination
Commercial CAE solvers · Open CAE solvers · In-house CAE solvers
Commercial data-driven models · Open data-driven models · In-house data-driven models
Simulation data · Test data · Operational data
Defined conditions · Traceable sources · Separate training and validation
Set goals and constraints, compare alternatives through computation and check results against independent data
Set wind conditions, power targets and load limits
Model responses with physics and calibrate with operating data
Vary rotor speed and blade pitch; compare power and loads
Check predictions against independent data and define operating limits
Reuse models, workflows and validation rules; solve each set of inputs independently
Wind turbine control · Technical illustration
Check numerical accuracy, compare independent data and define the scope of use
Is the calculation accurate enough?
Refine the mesh or time step under the same conditions and check key responses, residuals and conservation
Set convergence criteria for the required accuracy before physical validation
Do predictions match observations?
Compare power, loads and other key responses with test or operating data excluded from training and calibration
Assess prediction error alongside data uncertainty against agreed engineering criteria
Which operating conditions apply?
Define operating limits and error bounds from validation coverage, model assumptions and engineering criteria
Check each input against the applicable range; validate new conditions and update the method version
Engineering basisConclusions, errors and scope of use
Model version · Calculation conditions · Validation recordsYears of engineering computation support modeling, exploration and the execution of complex tasks.
Organize modeling, exploration and execution around a goal
Extend solving capability within accuracy and cost constraints
Represent real engineering problems as computable models
Turn engineering equations into computed results
Supports large-scale engineering computation
Start with your engineering problem, agree on the goals and constraints, and choose a method together.
