Varian Medical Systems unveils computer aided engineering software Attila4MC

10 May 2016 (Last Updated May 10th, 2016 18:30)

US-based medical technology company Varian Medical Systems has unveiled its new computer aided engineering (CAE) software to simplify the process of designing shielding and radiological protection systems.

US-based medical technology company Varian Medical Systems has unveiled its new computer aided engineering (CAE) software to simplify the process of designing shielding and radiological protection systems.

The new Attila4MC software offers engineers using Monte Carlo N-Particle Code (MCNP) in their product design with an intuitive graphical user interface (GUI) which simplifies and speeds up the calculation process.

Varian expects to use the software for research involving medical physics and nuclear engineering.

"Attila4MC enables organisations to more effectively incorporate Monte Carlo simulation results into their product designs."

Varian Attila Product Line senior manager Greg Failla said: "Our goal in developing Attila4MC was to help MCNP users be more productive.

"Attila4MC enables organisations to more effectively incorporate Monte Carlo simulation results into their product designs, and we are committed to helping users improve the ease, speed, and confidence of their calculations."

The software features capabilities to assist the engineers to overcome analysis related obstacles including a robust computer-aided design (CAD); GUI based calculation setup and automated variance reduction.

Using Attila4MC is said to reduce the analysis cycle and promote an efficient utilisation of the detailed Monte Carlo simulation resulting in the safety, reliability and performance of the products they are developing.

Varian also offers an optional CAD add-on with Attila4MC, providing part-time users the full power of solid modeling at their fingertips.

STEAG Energy Services nuclear physics deputy head Birgit Wortmann said: "We are convinced that Attila4MC provides a good opportunity to run MCNP simulations faster and provide more timely results."