Turbine CFD Analysis
Theory and Physics
Overview
What's the difference between turbine CFD and compressor CFD?
Turbines are on the side that extracts energy from the fluid. Since the flow accelerates, large-scale separation like in compressors is less likely to occur. Instead, blade cooling, secondary flow losses, and transonic shock waves become the main challenges.
Stage Work and Isentropic Efficiency
How is turbine work expressed?
Output and efficiency are defined from the Euler equation.
$h_{02s}$ is the enthalpy after isentropic expansion. For modern design levels, $\eta_{is}=90\sim92\%$ for HP stages and $88\sim90\%$ for LP stages in gas turbines.
Blade Loading Coefficient
How do you evaluate the magnitude of blade loading?
The Zweifel blade loading coefficient is the standard.
$s$: pitch, $c_x$: axial chord. $Z_w \approx 0.8$ has been considered the traditional optimum, but recent high-load designs are also researching $Z_w > 1.0$.
Software Selection
What software is used for turbine CFD?
Ansys CFX + TurboGrid is the most widely used among aero-engine manufacturers. NUMECA FINE/Turbo is efficient for multi-stage turbine setup and is used by companies like Rolls-Royce. STAR-CCM+ has strengths in CHT (Conjugate Heat Transfer) analysis for turbine blade cooling.
Rankine Cycle and CFD——The Intersection of Thermodynamics and Fluid Dynamics
In CFD analysis of steam turbines, thermodynamic equations of state are essential in addition to the Navier-Stokes equations. The ideal gas approximation completely breaks down in high-pressure stages, requiring coupling with IAPWS-IF97 (International Standard Equation of State for Water and Steam). This equation of state is a complex polynomial with dozens of coefficients, and embedding it into a CFD solver increases computational cost by about 20%. Since a 0.1% improvement in Rankine cycle thermal efficiency corresponds to annual fuel cost savings of hundreds of millions of yen for large power plants, the accuracy of the equation of state is a directly economically relevant issue.
Physical Meaning of Each Term
- Temporal Term $\partial(\rho\phi)/\partial t$: Imagine the moment you turn on a faucet. At first, water comes out spluttering and unstable, but after a while, it becomes a steady flow, right? This "period of change" is described by the temporal term. The pulsation of blood flow from a heartbeat, and the flow fluctuation each time an engine valve opens and closes are all unsteady phenomena. So what is steady-state analysis? Looking only at "after sufficient time has passed and the flow has settled down"—meaning setting this term to zero. This significantly reduces computational cost, so solving first with a steady-state approach is a basic CFD strategy.
- Convection Term $\nabla \cdot (\rho \mathbf{u} \phi)$: What happens if you drop a leaf into a river? It gets carried downstream by the flow, right? This is "convection"—the effect where fluid motion transports things. Warm air from a heater reaching the far corner of a room is also because the "carrier," air, transports heat via convection. Here's the interesting part—this term includes "velocity × velocity," making it nonlinear. That is, as the flow becomes faster, this term rapidly strengthens, making control difficult. This is the root cause of turbulence. A common misconception: "Convection and conduction are similar" → They are completely different! Convection is carried by flow, conduction is transmitted by molecules. There is an order of magnitude difference in efficiency.
- Diffusion Term $\nabla \cdot (\Gamma \nabla \phi)$: Have you ever left milk in coffee? Even without stirring, after a while, it naturally mixes, right? That's molecular diffusion. Now a question—honey and water, which flows more easily? Obviously water, right? Honey has high viscosity ($\mu$), so it flows poorly. Higher viscosity strengthens the diffusion term, making the fluid move "sluggishly." In low Reynolds number flow (slow, viscous), diffusion is dominant. Conversely, in high Re number flow, convection overwhelms, and diffusion becomes a minor player.
- Pressure Term $-\nabla p$: When you push a syringe plunger, liquid shoots out forcefully from the needle tip, right? Why? Because the plunger side is high pressure, the needle tip is low pressure—this pressure difference provides the force that pushes the fluid. Dam discharge works on the same principle. On a weather map, where isobars are tightly packed? That's right, strong winds blow. "Flow is generated where there is a pressure difference"—this is the physical meaning of the pressure term in the Navier-Stokes equations. A point of confusion here: "Pressure" in CFD is often gauge pressure, not absolute pressure. When switching to compressible analysis, if results become strange, it might be due to confusion between absolute/gauge pressure.
- Source Term $S_\phi$: Heated air rises—why? Because it becomes lighter (lower density) than its surroundings, so it's pushed up by buoyancy. This buoyancy is added to the equation as a source term. Other examples: chemical reaction heat from a gas stove flame, Lorentz force acting on molten metal in a factory's electromagnetic pump... These are all actions that "inject energy or force into the fluid from the outside," expressed by the source term. What happens if you forget the source term? In natural convection analysis, forgetting buoyancy means the fluid doesn't move at all—a physically impossible result where warm air doesn't rise in a room with the heater on in winter.
Assumptions and Applicability Limits
- Continuum Assumption: Valid for Knudsen number Kn < 0.01 (molecular mean free path ≪ characteristic length)
- Newtonian Fluid Assumption: Shear stress and strain rate have a linear relationship (non-Newtonian fluids require viscosity models)
- Incompressibility Assumption (for Ma < 0.3): Treat density as constant. For Mach numbers above 0.3, compressibility effects must be considered
- Boussinesq Approximation (Natural Convection): Consider density changes only in the buoyancy term, using constant density in other terms
- Non-applicable Cases: Rarefied gases (Kn > 0.1), supersonic/hypersonic flow (shock wave capturing required), free surface flow (VOF/Level Set etc. required)
Dimensional Analysis and Unit Systems
| Variable | SI Unit | Notes / Conversion Memo |
|---|---|---|
| Velocity $u$ | m/s | When converting from volumetric flow rate for inlet conditions, pay attention to cross-sectional area units |
| Pressure $p$ | Pa | Distinguish between gauge and absolute pressure. Use absolute pressure for compressible analysis |
| Density $\rho$ | kg/m³ | Air: approx. 1.225 kg/m³ @20°C, Water: approx. 998 kg/m³ @20°C |
| Viscosity $\mu$ | Pa·s | Be careful not to confuse with kinematic viscosity $\nu = \mu/\rho$ [m²/s] |
| Reynolds Number $Re$ | Dimensionless | $Re = \rho u L / \mu$. Indicator for laminar/turbulent transition |
| CFL Number | Dimensionless | $CFL = u \Delta t / \Delta x$. Directly related to time step stability |
Numerical Methods and Implementation
Importance of Blade Cooling
How is turbine blade cooling handled in CFD?
HP turbine inlet gas temperatures reach 1500–1800°C, far exceeding the heat resistance limit of blade materials (about 1000°C for Ni-based superalloys). Internal cooling passages and film cooling are used to lower the blade surface temperature.
Cooling Model Hierarchy
How do you incorporate cooling into CFD?
There are multiple levels depending on the trade-off between accuracy and cost.
| Level | Model | Computational Cost | Accuracy |
|---|---|---|---|
| L0 | No Cooling Flow (Adiabatic Wall) | Lowest | Baseline evaluation without cooling |
| L1 | Source Term (Mass/Energy Injection) | Low | Rough estimate for film cooling |
| L2 | Discrete Hole (Individual Cooling Hole BC) | Medium | Quantitative evaluation of film effectiveness |
| L3 | Resolved Cooling Holes (Holes Meshed) | High | Highest accuracy but high engineering effort |
| L4 | CHT (Fluid + Solid Coupling) | Highest | Predicts internal blade temperature distribution |
Are L3 and L4 practical?
L3/L4 for a single blade row is practical as a Singleton calculation. STAR-CCM+'s CHT is highly rated for this application. L3/L4 for multi-stage is currently at the research level.
Film Cooling Effectiveness
How do you evaluate the effectiveness of film cooling?
It is defined by the adiabatic film cooling effectiveness.
$T_g$: Mainstream gas temperature, $T_{aw}$: Adiabatic wall temperature, $T_c$: Cooling air temperature. $\eta_f = 0$ means no cooling, $\eta_f = 1$ means perfect cooling. In CFD, it is calculated by outputting the adiabatic wall temperature on the blade surface.
The Birth of Wet Steam CFD——Numerical Methods in the Mist
In the final stages of steam turbines, steam condenses and droplets form, which collide with blade surfaces causing erosion. The numerical method for handling this "wet steam" was established in the 1990s, requiring a unique approach combining classical homogeneous condensation models with nanometer-scale droplet nucleation theory. Even today, wet steam CFD has computational costs 3–5 times higher than single-phase gas, and assumptions about droplet size distribution can change efficiency predictions by more than 1%.
Upwind Differencing (Upwind)
1st Order Upwind: Large numerical diffusion but stable. 2nd Order Upwind: Improved accuracy but risk of oscillations. Essential for high Reynolds number flows.
Central Differencing (Central Differencing)
2nd order accuracy, but numerical oscillations occur for Pe number > 2. Suitable for low Reynolds number diffusion-dominated flows.
TVD Schemes (MUSCL, QUICK, etc.)
Maintain high accuracy while suppressing numerical oscillations via limiter functions. Effective for capturing shock waves and steep gradients.
Finite Volume Method vs Finite Element Method
FVM: Naturally satisfies conservation laws. Mainstream in CFD. FEM: Advantageous for complex shapes and multi-physics. Mesh-free methods like SPH are also developing.
CFL Condition (Courant Number)
Explicit method: CFL ≤ 1 is the stability condition. Implicit method: Stable even for CFL > 1, but affects accuracy and iteration count. LES: CFL ≈ 1 recommended. Physical meaning: Information should not travel more than one cell per time step.
Residual Monitoring
Convergence is judged when residuals for continuity, momentum, and energy equations drop by 3–4 orders of magnitude. The mass conservation residual is particularly important.
Relaxation Factors
Typical initial values: Pressure: 0.2–0.3, Velocity: 0.5–0.7. If diverging, lower the relaxation factor. After convergence, increase to accelerate.
Internal Iterations for Unsteady Calculations
Iterate within each time step until a steady solution converges. Guideline for internal iterations: 5–20 times. If residuals fluctuate between time steps, review the time step size.
Analogy for the SIMPLE Method
The SIMPLE method is an "alternating adjustment" technique. First, velocity is tentatively calculated (predictor step), then pressure is corrected so that mass conservation is satisfied with that velocity (corrector step), and then velocity is revised using the corrected pressure—this back-and-forth is repeated to approach the correct solution. It resembles two people leveling a shelf: one adjusts the height, the other balances it, and they repeat this alternately.
Analogy for Upwind Differencing
Upwind differencing is a method that "stands in the river flow and prioritizes information from upstream." A person in the river looking downstream cannot tell where the water comes from—it reflects the physics that upstream information determines downstream. Although it's first-order accurate, it is highly stable because it correctly captures the flow direction.
Practical Guide
Turbine Blade Row Mesh
Is the mesh for turbine blade rows the same as for compressors?
The basic structure is the same, but there are turbine-specific considerations.
- Trailing Edge Thickness: Turbine blades have very thin trailing edges (0.3–0.8mm). Sufficient cells are needed around the trailing edge in the O-grid.
- Cooling Holes: Local refinement around cooling holes is necessary for L2/L3 models.
- Transonic Regions on Blade Surface: Resolution of supersonic patches on the suction side and trailing edge shock waves.
If the trailing edge is 0.3mm, the mesh must be quite fine, right?
The O-grid around the trailing edge should have at least 10 cells radially, and the wake region immediately behind the trailing edge should also have a fine mesh. TurboGrid's trailing edge cutoff function can control the trailing edge shape.
Transonic Turbine Blade Row
Does turbine flow become supersonic?
In HP turbines, the blade-to-blade Mach number reaches 1.1–1.3. After accelerating to supersonic speed on the suction side, oblique shock waves are emitted from the trailing edge. Accurate prediction of this Trailing Edge Shock System, where the shock wave impinges on the adjacent blade, is crucial for CFD accuracy.
How much mesh is needed to resolve shock waves?
It is recommended that the cell size orthogonal to the shock wave direction be less than 0.5% of the chord length, with at least 10 cells before and after the shock. Adaptive Mesh Refinement (AMR) to concentrate mesh at shock wave locations is also effective. AMR functions in Fluent or STAR-CCM+ can be used.
Performance Prediction Accuracy
What is the accuracy of turbine CFD?
| Metric | Accuracy |
|---|---|
| Stage Efficiency (Multi-stage) | ±0.5–1.5 points |
| Blade Surface Pressure Distribution | Good (qualitatively matches experiment) |
| Blade Surface Heat Transfer Coefficient | ±10–20% (depends on turbulence model) |
| Trailing Edge Shock Wave Location | ±2% of chord |
The Baptism of High Temperature and Pressure——Steam Tur
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