A 1,000kW hydroturbine was optimized by applying automated Design Space Exploration with minimal user interaction, resulting in a design with improved efficiency and power output.

The objective was to find improved performance within an existing casing by varying wicket gate and runner blade design at current conditions (namely pressure differential). A total of 25 design variations were generated within the turbomachinery design software CFturbo. The batch output from CFturbo was fed seamlessly into an automated study within the Design Manager in computational fluid dynamics analysis software STAR-CCM+.

HubSpot Video

Animation showing all 25 design variations evaluated

HubSpot Video

Zoomed in view of the wicket gate and runner geometry/orientation for all 25 design variations

The computational study for all designs was completed automatically without user intervention on MSI's high-performance computing cluster in less than 24 hours of runtime. The outputs of the analysis were compiled and compared, demonstrating clear design advantages for improved efficiency and power output.

Design variables and results table

Design Variables and Results Table, Baseline Design is Design 13

Optimal vs Baseline DesignResults in Parallel Plot, Each Line Representing Individual Candidate Design - Best Design (blue) Resulted in Net Gains of Efficiency and Power Output with Approximately Same Massflow and Reduced Exit Swirl

The results of the study concluded:

  1. Eight designs yielded improved efficiency, with the best being Design 20
  2. Improved power and efficiency achieved at the same mass flow as the original design
  3. Improved exit swirl
  4. Twenty-five designs analyzed automatically, with runtime less than 24 hours

For an in-depth webinar on how the design and analysis tools were integrated for this example, click the button below.

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