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AVL FIRE

Latest News: Release AVL FIRE v2008

The release AVL FIRE v2008 amazes customers with added funtionalities to perfect their simulation processes and competitiors with the transformation of the software into the leading CFD tool in powertrain engineering.

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To meet consumer demands, automotive engineers require development tools which provide accurate representation of complex systems in the virtual world. The ever increasing number of design parameters of traditional and ‘alternative’ powertrain systems means that early concept analysis becomes increasingly important. Powertrain thermodynamic analysis using 3D computational fluid dynamics (CFD) tools is one such discipline.

Through years of development and advancements, AVL’s 3D CFD software FIRE™ fulfills these demands. FIRE is used every day by hundreds of powertrain engineers to accurately predict results in a flexible, robust and fast way. FIRE customers make design decisions earlier, and with greater confidence.

AVL FIRE™ is the leading simulation program in the field of combustion engine analysis and specialises in accurate prediction of engine gas exchange, mixture formation and combustion, as well as emissions and the exhaust gas aftertreatment.

High Fidelity System Simulation

The overall environment and individual components of FIRE enable application to any phase of the development process. The broad range of available models allows users to properly balance simulation effort and desired precision.

Powertrain Engineering Inside

AVL’s simulation tools are uniquely supported by over six decades of engine development experience. Our own consulting and services business depends on FIRE to deliver results, and provides our software team with invaluable insight into current and future requirements.

Close Link to Testing

The virtual inspection of engine phenomena with AVL FIRE™ supports shorter development times and the reduction of costs. New techniques, such as coupling to optimization tools, allows for the investigation of more design variations. The result is a more robust prototype on the test bed, allowing targeted testing, reduced development time, and a higher quality end-product.





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