Altair Feko
Feko addresses the broadest set of high-frequency electromagnetic simulation applications allowing teams to optimize wireless connectivity, including 5G, ensure electromagnetic compatibility (EMC), and perform radar cross section (RCS) and scattering analysis. From antenna simulation and placement, radio coverage, network planning, and spectrum management, to electromagnetic compatibility (EMC/EMI), radome modeling, bio-electromagnetics and RF devices, Feko combines with other Altair tools to optimize system performance through machine learning and reduce modeling time for complex systems.
Why Feko ?
Drive Design with Simulation
A comprehensive package of solvers with true hybridization for efficient design, analysis and optimization of connected products, electromagnetic compatibility compliance, and radar technologies
A better user experience
Simplified workflows from geometry modeling to results visualization, and scripting for advanced data manipulation, ensure Feko’s speed and accuracy is easy to apply.
Ongoin expansion and innovation
Ensure wireless connectivity, compatibility, and radar performance with advanced features
Capabilities
One product, multiple solver
Feko includes many different solvers to cover all applications and for cross validation purposes
True Solver Hybridization
Feko provides industry leading hybridized solvers to efficiently analyze complex and electrically large problems
Solver Accuracy and Performance
Extensive validation ensures accuracy, ongoing development of solver performance, parallel scaling of multi-CPU resources, and GPU-based solver acceleration provides computational efficiency
More Specialized Solutions
Use the most advanced and reliable commercial CMA solver. Other specialized solutions include, cable modeling, collocation interference, ultrasonic systems, and virtual test drives and flights
Complete Connectivity Workflow
Feko offers a unique workflow combining installed antenna performance with radio coverage and planning analysis applying fast and accurate wave propagation models
Design Optimization with Machine Learning
Fast and intelligent optimization using design of experiments and machine learning for antenna design and placement applications
