Simcenter simulation and testing solutions help engineering departments simulate, optimize and verify critical performance aspects of complex products. Simcenter uniquely combines system simulation, 3D CAE and test.
How digitalization is transforming pharmaceutical scale-up from lab to production The pharmaceutical industry has always been a challenging business due…
The new Simcenter FLOEFD 2406 software release enhances integration across Simcenter portfolio with import from Simcenter Flotherm XT software, introduces…
Simcenter solutions rank well in Simulation & CAE software by your peers on G2. Read the reviews now about the best simulation software!
Exploring new hydraulic concepts for your future heavy equipment with system simulation
Learn about Simcenter Testlab software for data collection, analytics, and modeling, and watch the free on-demand webinar for even more insights.
A blog on linkages between design, performance, and lifetime considering thermal Ohm’s law, thermal management of electronics and insight from Wendy Luiten
Automotive companies are fully engaged in the development and delivery of safe automated driving systems. Despite the significant technological progress…
New Simcenter 3D Materials Engineering, an efficient vibration fatigue solver, improvements to the ray acoustics solver and many other enhancements to help you meet to meet complex engineer challenges
Facilitating innovation in thermal integration of electric machines Efficiency regulations for electrical machines are placing greater demands on electrical machine…
The Simcenter STAR-CCM+ academic program aims to help students get access to the full commercial version of Simcenter STAR-CCM+ through their academic affiliation. Learn how
What is the future of powertrain NVH testing if (hybrid-) electric cars are so quiet? Find out the answer here and join the free on-demand webinar about it.
In this blog post, we discuss how artificial neural networks aid in mechatronic systems development. We will use examples from different phases of the vehicle systems development cycle. We will also explore the applicability of various types of neural networks for a variety of engineering tasks.
