Ansys optiSLang

All turbomachinery designs need to be optimized for efficiency​

• Compared with traditional optimization approaches optiSLang helps to unlock performance potentials by means of:​
  • Effective handling of large number of parameter​
  • Combining multiple physics​ simulations
  • Taking care of robustness/reliability in the optimization process​
  • Minimizing the need for prototypes, and associated expenses
  • Automating the optimization process to reduce development time

• Competitors may provide comparable results of product performance, but have strong limitations in parametric optimization.
• In addition, changes in design geometry for competitor software options are limited or even non-existent.
• In general optiSLang’s advantage over build-in optimization is manifold:
  • Enables parametric changes on every physics (mechanical, electrical, thermal, etc.)
  • Quantifying the effect of uncertainties which is fundamental for underlying design basis.
  • optiSLang is solver agnostic, working with any solver including tools created in-house

Ansys optiSLang, Case Study | Robustness Evaluation and RDO of a Centrifugal Compressor Impeller 

Evaluate & Validate Automotive Controller Software Functions

• Reduce the number of necessary simulations to evaluate probabilities of failure
• Probabilities of failure analyses for different ECU, territories, sensors, etc.
• Automated controller calibration: manual tweaks are replaced by smart optimization of the PID control parameters

• In general, optiSLang’s advantage over competitive optimization tools is manifold:
  • Works with all solvers, especially Ansys solvers
  •  No expert knowledge about algorithms is needed, and therefore, accessible to any engineer
  • Much more flexibility and efficiency with optiSLang
  • Instantly toggle 2D/3D parametric design simulations

Ansys OptiSLang, Case Study | Safety Assessment of Automated Driver Assistance System (ADAS)

Increase Product Performance

• optiSLang enables the full optimization potentials due to​:
  • Effective handling of huge number of parameter​s, objectives and constraints (from fabrication, space, other physics, costs) 
• Enhanced Design understanding
  • Top-to-Bottom product robustness consideration within the optimization process​
  • Accelerate product development process and reduce prototype expenses

• Third-Party Solver Integration –
  •  Have a third-party solver your team is already comfortable with?  No sweat, stay with your tool.  OptiSLang connects with every solver.
• Compatible with in-house created analysis tools (excel, python, etc.
  • We can automate and extent the workflow beyond its capabilities to increase the number of parameters for greater design optimization potential.
• Time for Internal Adoption
  • Changing the process will be fast; the time savings & increased improvements are rewarding, and noticed quickly.  

Ansys optiSLang, Case Study | Parameter Identification & Analysis of Underground Laboratories 

• Flexible Workflows for Electric Motors Development
• Metamodels can be used as FMU
• Multi-Domain, Multi-Criteria enable to take care of:
  • Electrical, Thermal, Mechanical, NVH, Safety and Cost aspects
    • Decision support in early design phase
    • Performance Map, Drive Cycle Optimization
• Integration of results in system simulation, including:
  • Powertrains
  • Inverters
  • Batteries
  • Accelerometers
  • …and more!

• Competitors may provide comparable results of product performance, but have strong limitations in parametric optimization.
• In addition, changes in design geometry for competitor software options are limited or even non-existent.
• In general optiSLang’s advantage over build-in optimization is manifold:
  •  Works best with Ansys AEDT (Maxwell) and MotorCAD
  • Enables parametric changes on every level (mechanical, electrical, thermal, etc.)
  • Quantifying the effect of uncertainties is fundamental for underlying design basis

Ansys OptiSLang, Case Study | Light Construction of Power Lathe Chucks 

Improve Product Performance by Pushing the Boundaries

• Fulfill tremendous amount of optimization criteria (including restrictions from manufacturing, installation space, FEM, regulations etc.)
• Fulfill performance and robustness demands at the same time
• Explore manufacturing technologies of optical systems
• Identify adequate input tolerances and potential savings
• Predict output data that can not be accurately or not efficiently simulated or measured

• In regards to optics-based optimization, competitors may advertise sensitivity analysis’ capability, but only consider linear effects, and no interactions between parameters are considered.
• In addition, changes in design geometry for competitor software options are limited or even non-existent.
• In competitors tolerance analysis’, engineers need to invest thousands of designs in order to proof very low probabilities of failure whereas with optiSLang, only a hundred of design simulations are needed.  Not to mention, optiSLang is the gold-standard in terms of speed of said simulations and accuracy.

Ansys optiSLang, Case Study | Parameter Influences on the Laser Processing of Ceramics w/ Ultra Short Pulses 

Precise Simulation for Power Transmission

• Reduce physical prototypes
• High fidelity solution and a wholistic perspective of performance
• Identify best possible design
• Proof reliability of performance
• Automate the optimization process
• Reduce development time
• Physics based decision making – not based on ‘looks right’ conjecture

• Competitors may provide comparable results of product performance, but have strong limitations in parametric optimization.
• In addition, changes in design geometry for competitor software options are limited or even non-existent.
• In general optiSLang’s advantage over build-in optimization is manifold:
  •  Works best with Ansys AEDT (Maxwell), but also integrates with third-party applications
  • Enables parametric changes on every level (mechanical, electrical, thermal, etc.)
  • Quantifying the effect of uncertainties is fundamental for underlying design basis

Ansys OptiSLang, Case Study | Optimization of Fiber Composite Components in Yacht Racing