In our 2nd part of a series on the Adjoint solver, learn how recent developments have focused solely on improving the usefulness of the Adjoint solver for real-world customer problems - allowing for definition of multiple objectives; expanding to include more physics; and allowing more user control over geometry modifications and constraints.
When dealing with a significant number of variables in our simulations, design engineers often find it challenging to work out which variables are the most important, and how to best tune these variables to improve performance. Learn how ANSYS optiSLang now offers a compelling proposition for answering these questions while giving engineers even more tools for exploring the possible performance envelope within key design parameters.
Learn about Augmented Reality (AR) technology that was showcased at 2017 National Manufacturing Week / Austech: including the ability to augment pressure contours on the front and rear wings of the MMS racecar, as well as visualise the animated flow streamlines being released forward of the front wing. Students from MMS are using these AR CFD results to collaborate more effectively in a multi-disciplinary team environment where not everyone is a CFD expert and hopefully achieve their ultimate goals of maximising downforce on the front/rear wings and optimising the aerodynamic performance of their racecar.
Many fluids we encounter in industry do not strain linearly with respect to viscous shear and are thus considered non-Newtonian. This post explores how to model non-Newtonian viscosity of fluids in ANSYS CFD, using blood as an example.
ANSYS Polyflow is designed to simulate blow moulding and extrusion processes, as well as mixing of complex rheology liquids, film casting, extruder screw simulation, gravity assisted gob forming, glass pressing and mould filling. Many companies deliver a fast ROI of within 1 year using Polyflow for polymer processing simulations.
What's changed in the world of multiphase flow modelling in the past 2-3 years? As always, an understanding of the physics of the system that you are modelling remains the number one priority, however, a number of new developments will help you address a wider range of multiphase flows and in a faster and more effective way.