June 1-3, 2015 in Dolní Morava, Czech Republic

Conference for numerical simulation

Jun 6-8, 2016 in Würzburg

Conference for technical aspects in the design and use of modern connectors

Jun 7-8, 2016 in Munich

Computer-aided engineering conference in the automotive industry.

Jun 12-15, 2016 in Linz

Challenges in Forming High-Strength Sheets

Jun 6, 2016 in Winterthur

Conference for numerical simulation


Library RDO Journal Weimar Optimization and Stochastic Days Newsletter Quarter 2_2016 Dynardo...

Dynardo GmbH is proud to announce that Dynardo’s optiSLang, leading edge software for CAE-based...

Release note optiSLang 5.0.0 more information about optiSLang 5 more information about optiSLang...



Jun 6-8, 2016 in Weimar

Jun 9 in Vienna
Aug 10, 2016 in Lein.-Echt.
Sep 7, 2016 in Renens
Nov 16, 2016 in Berlin
Nov 22, 2016 in Aadorf

Jun 22 in Hanover
Sep 30, 2016 in Lein.-Echt.
Dec 9, 2016 in Grafing

Aug 12, 2016 in Lein.-Echt.
Nov 18, 2016 in Berlin
Nov 24, 2016 in Aadorf

Webinar: optiSLang and ANSYS Maxwell

Only the parameterization of an FE model and the efficient scanning of the design space enable leveraging the full potential of electromagnetic simulations in Maxwell. This webinar will demonstrate an exemplary sequence of steps of analyzing the data, understanding the physics, and pursuing optimization goals using a 2D motor model implemented in Maxwell and coupled to optiSLang.

Employing simulations one generally aims at problem understanding and the utilization of gained  knowledge for target-oriented design optimization. Various optimization goals, such as energy efficiency, vibration damping, resonance control, field quantities and topology, cannot be treated independently. At the same time, production and application conditions such as tolerances or failure-determining random processes affect the performance of the design.

optiSLang allows a targeted and methodical approach taking into account constraints and existing computing resources. Statistics-based assessments of non-linear system interactions expand the physical understanding of processes in virtual product development.


Metamodel of Optimal Prognosis (MOP) for the torque ripple amplitude
Reference geometry (left) / optimized geometry (right)
Optimized controller signal
Optimized torque signal in comparison with reference case

1. Overview of optiSLang's graphical user interface

2. Analysis of a transient 2D simulation of a commutated electric motor

  • Representation of the simulation in the optiSLang GUI
  • Sensitivity study – examining indicators of energy efficiency, torque, and torque ripples
  • Metamodels as a tool for analyzing non-linear interactions
  • Identification of goal conflicts and design tradeoffs
  • Optimization – dealing with conflicting goals, defining a scalar objective function, combining global and local optimizations

3. Process integration

  • Alternatives: direct coupling or via ANSYS Workbench
  • Real-valued responses and signals
  • Ways of parallelizing the computations


Dipl.-Phys. Markus Stokmaier

to be announced
Please register not later than 1 day prior to the event date.


9-10 am and 4-5 pm (local time-Berlin)

free of charge