BETA CAE Systems announces v21.1.0 of its software suite
As 2020 ends, new products are already being released now in 2021, BETA CAE a well-known Greek simulation software house is offering its latest version of its software suite – “v21.1.0” which its says will allow users to “minimize simulation turnaround time and accelerate the automatic setup for workflows and processes”.
The all brand new version offers a plethora of features to unlock new potential for simulation in design and analysis, as well as a range of upgrades and performance improvements for existing workflows.
BETA CAE have released the following highlights for users to examine.
Diversifying multidisciplinary capabilities in ANSA
The introduction of Electronic CAD (eCAD), as well as Electromagnetics, triggers a new potential in our pre-processing fields of expertize and widen the areas of simulation to new perspectives.
In a similar manner, the introduction of Thermal support for Marc and Pam-Crash solvers paves the way for more efficient pre-processing methods.
One step further, and loyal to our goal to provide steady, but at the same time efficient and swift model management techniques, we empowered Modular Environment with extended capabilities. Collaboration with remote users is now further facilitated, allowing the transfer of DM objects between different DMs, the benefits of which are further augmented by the new capability of data compression.
From the discipline-oriented perspective, the already introduced Marc interface gains ground with even more dedicated capabilities, whereas Actran offers extended functionality with numerous additional features. In a similar manner, Crash & Safety fields offer a progressing interface for Impetus solver, along with numerous newly introduced tools for other applications, such as Marionette Positioning for Pam-Crash analysis.
Not to be missed, the enriched optimization capabilities that vest the new version with a new potential for topology optimization, as well as the ability to morph and modify models through VR and Collaboration in ANSA.
Optimization gaining ground with EPILYSIS
The brand new v21.1.0 heads straight for uplifted optimization with the output of shape optimization results in HDF5 format for SOL200. On top of that, enhancements in Contacts algorithm, in sectors such as Penetration checking and output of intermediate results, give boost to the accuracy in engineering solutions and come hand-in-hand with noteworthy enhancements in memory and disk usage peaks reported in .f04 file.
Elevating post-processing capabilities with META
Boosting graphics performance even more, the brand new GPU Accelerated Smooth Light Calculations provide faster first animation loop with less memory consumption, whereas the ability to place annotations around models in real-time, ensures more dynamic post-processing interaction.
Moreover, acknowledging and further promoting post-processing needs and capabilities in the area of Web Collaboration, its interface has arrived with an uplifted look & feel, hosting pages, windows and states for even smoother user interaction.
Vast developments have also taken place in the NVH domain, by the direct support of enforced excitation on tire patch in Modal Response and FRF Assembly, using the large mass method.
Other areas that have recently gained ground in META v21.1.0 are the Crash & Safety, hosting a new tool for the automatic report generation of Human Body Models results. This comes along with a significant speed-up when reading FEMZIP LS-DYNA results, by providing the ability to select and read multiple results simultaneously. On top of that, major performance improvements have also been tracked in ERF and ERF FEMZIP. Specifically, the loading time of ERF and ERF FEMZIP files has been accelerated by approximately 30-35% for both loading geometry and results. The aforementioned implementations, coupled with the support of ERF FEMZIP v11 libraries, boost the overall performance to even greater extend.
Machine Learning in BETA products branching out
Further expanding Machine Learning (ML) potential via its integration in KOMVOS through ANSA, as implemented in prior versions, the brand new version offers advanced capabilities for incremental learning, as well as a fine tuning of Machine Learning parameters, such as Train / Test ratio, Cross Validation and Confidence level.
On top of that, the introduction and implementation of ML Toolkit v2.0, the new version of Tensorflow (2.2.1), offers an updated and synchronized packaging for both Linux & Windows.