Technology Category
- Sensors - Flow Meters
- Sensors - Liquid Detection Sensors
Applicable Industries
- Electrical Grids
- Semiconductors
Applicable Functions
- Product Research & Development
Use Cases
- Digital Twin
- Virtual Reality
Services
- Hardware Design & Engineering Services
About The Customer
The customer in this case study is not explicitly mentioned. However, it can be inferred that the customer is a manufacturer or designer of axial fans, seeking to improve the efficiency and air flow capacity of their product. The customer likely operates in the turbomachinery industry, where the design and optimization of fans, turbines, and other rotating machinery are critical. They require a solution that not only enhances the performance of their product but also integrates seamlessly with their existing workflow. The customer values efficiency, productivity, and the ability to leverage their available hardware resources to the fullest extent.
The Challenge
The case study revolves around the optimization of an axial fan's design using TCFD® and CAESES® software. The primary challenge was to develop a new, highly efficient fan or improve the parameters of an existing one. The existing axial fan had specific parameters, including a diameter of 280 mm, RPM of 3000, maximum power of 100 W, maximum pressure of 410 Pa, maximum air capacity of 1100 m3/h, and peak efficiency of 69%. The study aimed to maximize the fan's efficiency in the range of flow rates from 576 m3/h to 1296 m3/h and increase the air flow capacity. The challenge also involved creating a smart and efficient turbomachinery design optimization workflow by connecting the two software packages, TCFD® and CAESES®.
The Solution
The solution involved creating a fan geometry using CAESES®, which provides a CAD environment for robust and easy geometry variation, efficient parametrization, and simulation-ready export. A CFD simulation setup template for the exported geometry was created in TCFD® and returned back into the CAESES® software connector. An optimization process in CAESES® was preset, and each geometry variation was automatically processed and simulated with TCFD®. The axial fan flow domain was created to fit CFD requirements, and the geometry was split into rotor and stator domains. The optimization process involved a complex set of tasks, including a global sensitivity analysis (Sobol) and a local analysis (TSearch) in the neighborhood of the best design obtained from the global analysis. The objective function was defined as a sum of efficiencies for all six simulated points imported from TCFD®.
Operational Impact
Quantitative Benefit
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