FieldView Parallel Export from ANSYS® Fluent® 16.0
ANSYS Fluent 16.0 provides the capability to export results to FV-UNS while maintaining the partitioning established for a FLUENT parallel solution. The file is fully compatible with FieldView Parallel allowing for the substantial time savings from parallel processing. Every FieldView license will support at least 8 processor cores. FieldView Parallel will readily scale to 64 processors and beyond. The export files can be automatically generated during the solver run.
Surface Export – From the ANSYS Fluent TUI a new option called “fieldview-unstruct-surfaces” creates a surface only FV-UNS export, where the user selects the exported surfaces from a list of boundary conditions and post-processing surfaces (iso-surfaces, planes…).
- Surface export for Parallel FieldView – A surface export made from a parallel session of Fluent will maintain the partitioning of the surfaces, and the resulting file can thus be read in parallel by FieldView.
- Interior surfaces may be selected for export in Fluent 16.0. This is a longstanding request and is useful in applications like integrating flow rate or seeding streamlines on control surfaces. Please contact our support team for information about how to use this new feature.
FieldView and FLUENT – Power for Unsteady Simulations
Unsteady simulations are often post-processed and reviewed using FieldView XDB files which are a fraction of the size of volume data. Exporting surface data, reading into FieldView Parallel and then having FieldView post-process and produce XDB files can be entirely automated. This workflow delivers lightweight XDB files for review in FieldView or by the free XDBview reader. When exporting from ANSYS FLUENT, the resulting file can be read into FieldView in parallel, dramatically reducing the read-in time.
Choose the right export for your data: Quick Start – Working with FLUENT16 data in FieldView (PDF)
The latest release of FieldView, Version 15, is coming in late October. This is the first FieldView release created under our Agile development process. Participating users have seen their requests implemented in prototypes along the way and are already seeing benefits.
Among the improvements coming in the new release:
- Increased performance and control over extract generation (XDBs), with the new option to retain thresholds from FieldView through to the XDB file.
- An improved reader for OpenFOAM data which will allow the computation of more accurate iso-surfaces at the border between partitions.
- Introduction of XDBView, a new standalone viewer for FieldView XDBs which is open licensed and can be freely shared among colleagues.
- Easier access to about 50 colormaps and user defined ones straight from the interface.
- Resolution of a bug related to the 3D mouse support improves performance for users without 3D mouse tools.
- For users rendering very large surfaces, FieldView 15 will reduce the memory footprint while maintaining a very good level of performance.
FieldView 15 will address many more feature requests and improvements. Stay tuned for more details as the release nears.
Our FieldView 15 Beta program will commence soon. Please contact your sales or support rep if you would like to be included in the beta program.
Intelligent Light delivered a keynote presentation at the VINAS User Conference in Shinagawa, Japan.
How the Automotive Industry is Pushing the Limits of CFD Post-Processing with FieldView
Yves-Marie, Lefebvre, FieldView Product Chief
CFD Engineers working in the automotive industry are being asked to simulate increasingly complex systems and phenomena, while having to deal with strong time and cost constraints. This is probably the reason why an increasing number of them are switching to FieldView, after trying other commercial or open source post-processors. In this presentation, we’ll review three automotive industrial examples, covering areas as different as engine thermal validation, external aero and internal combustion, which used the same technology (FieldView’s automation, high performance graphics and data extracts capabilities) but applied in different ways, thanks to the help of Intelligent Light’s Services Team. What these three companies had in common was the need to do more with the same hardware, whether that’s getting their post-processing results faster or being able to interact with large transient results in a way it had never been done before.
Download the Presentation
“Yves-Marie Lefebvre, FieldView
Product Chief, with members of the Concordia SAE Racing Team, at the SAE 2014 World
I was pleased to meet with the Concordia University Team at the the SAE World Congress in Detroit. This photos was taken a the event (I’m on the right) with the newly unveiled vehicle and team members.
IL sponsors the team through our University Partners Program and the team uses FieldView to gain meaningful insights from their CFD analysis.
Good luck to the Concordia SAE Supermileage Team!
An Innovative Transient Post-Processing Approach for a Full Car Thermal Validation Study
Full car CFD simulation using STAR-CCM+ solutions. FieldView post-processing enables large scale transient cases to be productively analyzed. To be presented at the 2014 STAR Global Conference.
STAR-CCM+ and FieldView have been used, through an extract based post-processing workflow, to analyze a very large transient simulation case. This method not only allowed monitoring of simulation results over time, such as the maximum temperature of thousands of car parts and their comparison with the critical temperature of each material, but also allowed investigation of transient phenomena interactively in order to gain better understanding. To our knowledge, this work is unprecedented in the automotive industry.
Intelligent Light is proud of our partnership with CD-adapco. At the 2014 STAR Global Conference, Yves-Marie Lefebvre, FieldView Product Chief, shared leading edge techniques and capabilities developed from our work with CD-adapco and leaders in automotive engineering. The presentation demonstrated just how much CFD data can be efficiently created and utilized, compressing analysis cycles and delivering value from large scale, unsteady STAR-CCM+ simulations.