Induction heating of turbine blade: case study

Turbine blades are the heart of modern engines and power systems, operating under extreme temperatures and stresses. Their manufacturing demands absolute precision, especially during processes like welding, where preheating is essential to prevent defects and ensure long-term performance.

Induction heating has emerged as the preferred method for this preheating, offering control and energy efficiency. However, achieving uniform temperature distribution across the complex geometries of turbine blades remains a challenge for engineers.

 

This is where simulation technology transforms the game. By virtually modeling and optimizing the induction heating process, engineers can overcome the limitations of traditional methods.

In this case study, we explore the challenges of induction heating turbine blades, reveal how simulation software provides an innovative solution, and highlight the transformative results it delivers for manufacturers aiming to stay competitive in high-stakes industries like aerospace and power generation.

What is the challenge?

Turbine blades, being critical components of aircraft engines and power plants, demand the highest levels of precision in manufacturing. Induction heating is often used to preheat these blades for welding or other joining processes. The goal is to achieve uniform temperature distribution, ensuring structural integrity and performance.

However, achieving this uniformity is easier said than done. Turbine blades are often made of superalloys with complex geometries, leading to uneven heating and potential hotspots. Additionally, improper preheating can cause microstructural defects, affecting the blade’s long-term durability. Engineers often struggle with:

• Complex geometries: Uneven temperature distribution due to the intricate shapes of turbine blades.
• Material sensitivity: Superalloys require precise control over heating rates to prevent structural damage.
• Optimization time: Traditional trial-and-error methods for designing inductors can take weeks and still yield suboptimal results.

What is the solution?

The answer lies in simulation-driven design, where advanced software tools model and optimize the induction heating process virtually. Using simulation software, engineers can visualize how the electromagnetic fields interact with the turbine blade, ensuring consistent heat distribution.

In the attached simulation image, the heating process of a turbine blade is illustrated in real-time, showcasing the precision achieved through virtual testing.

Let’s take a look into the simulation, using CENOS Induction Heating simulation software.

In this quick animation, we actually demonstrate 10 design iterations. You can see the coil shape design changes and how it affects the heating process. With CENOS this is a quick and simple automated process. You can use virtually any CAD modeling software of your choice.

 

In the first iterations, you can see that the first coil design heated the trailing edge of the blade way too much. It may not be intuitive how much larger the coil should be, but simulation helps you to determine the exact size.

As you can see, the inductor around the trailing edge had to be made significantly larger to achieve uniform temperature. Due to more uniform heating, the heating time was also reduced from 125s to 50s thus saving the welder’s time.

This also saves the machinist’s time. While this inductor is relatively simple, testing different geometries in the lab would be much, much more time consuming and expensive. Simulation also allows to quickly test other turbine blade geometries with the same inductor.

By simulation software, engineers can:

• Optimize inductor design: Quickly iterate and refine coil designs to achieve uniform heating.
• Predict temperature distribution: Accurately model heat flow within the blade, eliminating trial-and-error guesswork.
• Save time and resources: Complete optimization in hours instead of weeks, reducing costs and speeding up production cycles.

The simulation software ensures that every detail, from the blade’s geometry to its material properties, is factored into the design. This process not only improves efficiency but also minimizes the risk of defects during welding or other downstream processes.

Analysis of the simulation

Let’s look into some more details of this simulation.

Magnetic flux density in the induction heating process

Key insights:

• This image illustrates the magnetic flux lines generated during the induction heating process around the turbine blade.
• The intensity of the magnetic flux density is color-coded, showing areas of higher flux concentration near the inductor coils.
• Engineers can identify how the electromagnetic fields interact with the blade, pinpointing regions of effective heat transfer.

Value for engineers:

• Visualizing the magnetic flux density helps engineers optimize the placement and geometry of inductor coils for uniform heating.
• It provides insights into reducing energy losses by minimizing areas of excessive flux leakage or hotspots.

Heat distribution and current density visualization

 

 

Key insights:

• The image displays the thermal distribution on the turbine blade’s surface, with a gradient indicating temperature changes from the base to the edges.
• Current density is overlaid, showing how electric currents flow through the material to generate heat.
• Areas of high temperature correspond to regions of higher current density, emphasizing the role of induction currents.

Value for engineers:

• Engineers can evaluate whether the heating is uniform across the blade’s complex geometry.
• It assists in determining the effectiveness of inductor design and material conductivity in achieving desired temperature profiles.

Visualization of current density and flow

 

Key insights:

• This image provides a more detailed view of the current density distribution within the turbine blade, overlaid with directional flow lines.
• The gradient highlights regions where eddy currents are most intense, which are crucial for localized heating.
• The direction of current flow helps engineers understand the interaction between the inductor’s magnetic field and the workpiece.

Value for engineers:

• This visualization allows engineers to refine inductor coil configurations to avoid areas of insufficient or excessive heating.
• It aids in troubleshooting issues such as uneven temperature distribution or energy inefficiency by identifying problematic areas in the design.

What is the result?

For engineers and manufacturers, the results are transformative. Induction heating, when optimized with simulation, enables:

• Better precision: Achieve uniform temperatures across complex geometries, improving the quality of welded joints.
• Enhanced durability: Prevent material defects, ensuring the blade withstands extreme operational conditions.
• Faster time-to-market: Reduce the development cycle of induction heating processes from weeks to hours.

In the fiercely competitive aerospace and power generation industries, every advantage counts. By adopting simulation-driven solutions for induction heating, engineers can stay ahead of the curve, delivering high-quality turbine blades that meet stringent industry standards.