Appli plications cations of f CFD and d Desi sign gn Exp - - PowerPoint PPT Presentation

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Appli plications cations of f CFD and d Desi sign gn Exp - - PowerPoint PPT Presentation

Nov 29, 2022 216 likes •687 views

Appli plications cations of f CFD and d Desi sign gn Exp xplorat loration ion in the Energy rgy & Power r industr dustry Jim m Rya yan Des esig ign Expl plorati ration on wit ith CFD FD in in E Ener ergy gy & P

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SLIDE 1

Appli plications cations of f CFD and d Desi sign gn Exp xplorat loration ion in the Energy rgy & Power r industr dustry

Jim m Rya yan

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SLIDE 2
  • Design Exploration: key concepts and examples
  • A “Maturity Model” for Engineering Simulation
  • Gas Turbines
  • Turbine blade cooling

with Conjugate Heat Transfer (CHT)

  • Combustor liner cooling

with Conjugate Heat Transfer (CHT)*

  • Combustor flows, temperatures, and emissions*
  • Centrifugal Pumps & Hydro Turbines

Des esig ign Expl plorati ration

  • n wit

ith CFD FD – in in E Ener ergy gy & P & Power er in indu dustry

2

*This topic is beyond the scope of this presentation

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SLIDE 3

3

Gas Turbines Steam Turbines Compressors Combustion Heat Exchangers Balance of Plant

(Ducting, SCRs, etc.)

Pumps & Hydro Turbines

Energy & Power Simulation Solutions

Fans Nuclear Renewables

(Wind, Solar)

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SLIDE 4

Solve & Visualize Import Geometry Mesh Set Up Physics

Change Design

(geometry and physics)

# of Designs Time

Design #N+1 Design #N

Des esig ign Expl plorati ration

  • n wit

ith STAR-CCM+ CCM+

4

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SLIDE 5

A Maturit ity y Mode del for r Engi ginee eerin ing g Sim imula lati tion

  • n

Validate Troubleshoot Predict Explore Optimize

Explore digitally, Confirm physically

Ultimate Goal: Discover Better Designs Faster

Critical inversion point (from reactive to proactive engineering)

= Feasible = Infeasible

Objective 1 Objective 2

5

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SLIDE 6

Des esig ign Expl plorati ration

  • n Concepts

epts: : Hea eat Excha hange ger r exampl mple

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SLIDE 7

Temperature Change (degrees) Pressure Drop (Pascals)

Pareto Front of Best Designs

= a Best Design = a Design iteration

= Design improvement (i.e., Better designs) Baseline Design

Des esig ign Expl plorati ration

  • n Concepts

epts: : Hea eat Excha hange ger r exampl mple

Heat Exchanger Objectives:

7

1) Maximize Heat Transfer (Temperature Change) 2) Minimize Pressure Drop

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SLIDE 8

SHERPA Benchmark Example Des esig ign Expl plorati ration

  • n Concepts

epts: : Hea eat Excha hange ger r exampl mple

8

SHERPA

Change design variables Responses

STAR-CCM+

NOTE: Single Objective History Plots shown here for visualization purposes

/ Optimate+

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SLIDE 9
  • Com
  • mpone

ponents nts

  • Multi-disciplinary process automation
  • Scalable high performance computing
  • Efficient exploration (optimization, DOE)
  • Sensitivity & robustness assessment
  • Step

eps:

  • Drag and drop process definition
  • Assignment of compute resources (HPC)
  • Define design variables, ranges, constraints
  • Define responses of interest
  • Explore, optimize, process results
  • Assess sensitivity & robustness

Des esig ign Expl plorati ration

  • n wit

ith HEEDS

Modeler Explorer

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MDX = Multi-disciplinary Design eXploration

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SLIDE 10

2 Sim imil ilar r but Dif iffer eren ent t Envir ironm

  • nmen

ents ts for Des esig ign Expl plorati ration

  • n

10

HEEDS Solver HEEDS Solver

Optim imat ate+

for Design Exploration within STAR-CCM+ IDENTICAL IDENTICAL DIFFERENT

HEE EEDS DS

for General CAE and MDX

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SLIDE 11

Duct ct Fl Flow w Des esig ign Expl plorat

  • ration

ion

11

  • Challenge: With flow through a

duct, rapidly assess changes in pressure due to different turning-vane configurations

  • Solution: Automated design

exploration using STAR-CCM+ with parameterized 3D-CAD and Optimate

  • Impact:
  • Find better designs
  • Speed-up time-to-results by as

much as 10X

  • Accelerate time-to-market

Turning Vanes:

  • Uniform, finite thickness
  • 0.10m < Radius < 0.50m
  • Vane count: 1 to 10

1.5 m 1.0 m 2.0 m 1.0 m 0.5 m 0.5 m 0.5 m N = 4 R = 0.15 N = 4 R = 0.30 N = 4 R = 0.45 N = 7 R = 0.15 N = 7 R = 0.30 N = 7 R = 0.45 N = 10 R = 0.15 N = 10 R = 0.30 N = 10 R = 0.45

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SLIDE 12

STAR-CCM+ CFturbo SHERPA High Power Required Optimal Design

Pareto Front

Baseline Design

Violates Constraint

Baseline Design

Flow rate = 400 m3/h Pressure head = 30 m

Power required = 38.4 kW

Optimized Design

Flow rate = 400 m3/h Pressure head = 30 m

Power required = 36.0 kW

STAR-CCM+ CFturbo SHERPA

“I can now obtain better pump designs faster by spending more time on engineering decision-making, and less time on model setup & data transfer.”

– Ed Bennett, VP of Fluids Engineering, Mechanical Solutions Inc. (MSI)

  • Impact:
  • Power reduced by 6%
  • Found 33 improved designs;

not just 1 that is “good enough”

  • Scalable platform for optimization

and multi-disciplinary simulations

  • Solution:
  • Parametric blade design (3rd-party)
  • Flow simulation (STAR-CCM+)
  • Process automation (HEEDS)
  • Optimization (HEEDS)
  • Challenge:

1) Modify impeller to increase pump

efficiency; minimize power required

2) Obtain set of lowest-power pump designs

for set of outlet pressures

SHERPA

Requirements Performance Optimization

STAR-CCM+ CFturbo

Cen entrif ifuga ugal l Pump mp Des esig ign Expl plorat

  • ration

ion

12

6% improvement!

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SLIDE 13

Fluid/Solid mesh considerations for increased solution fidelity: Geometry capturing Conformal interfaces Prism layers

GT Blade de Cooli ling g through

  • ugh CHT

13

Fluid Solid

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SLIDE 14

Fluid/Solid mesh considerations Polyhedral cells allow for accurate representation of complex geometry

GT Blade de Cooli ling g through

  • ugh CHT

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Fluid Solid

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SLIDE 15

Fluid/Solid mesh considerations Conformal meshes along the entire Fluid/Solid interface yields increased accuracy

GT Blade de Cooli ling g through

  • ugh CHT

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Fluid Solid

3 Prism Layers

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SLIDE 16

Engi ginee eerin ing g Sim imula lati tion

  • n Maturi

rity ty Mode del Validate Troubleshoot Predict Explore Optimize

Ultimate Goal: Discover Better Designs Faster

= Feasible = Infeasible

Objective 1 Objective 2

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SLIDE 17

NASA Mark II test vane Turbulence Models Transition Model Settings

B&B &B-AGEM GEMA: A: Gas Turbin bine e Blade de Cooli ling

  • Challenge: Reduce cost & effort to develop

and upgrade gas turbine engines while ensuring proper temperature levels

  • Solution: Validated Conjugate Heat Transfer (CHT)

simulations with STAR-CCM+

  • Impact:
  • Rapid, reliable A-to-B comparisons
  • Significantly improved cooling efficiency

(needed for increased firing temperatures)

  • Reduced costs; fewer experimental tests

“STAR-CCM+, with its high level of automation, meshing capabilities and high solution accuracy, is the best commercial CAE tool to perform fast and accurate simulations of conjugate heat transfer.” – René Braun, B&B-AGEMA Before Upgrade After Upgrade

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SLIDE 18

Engi ginee eerin ing g Sim imula lati tion

  • n Maturi

rity ty Mode del Validate Troubleshoot Predict Explore Optimize

Ultimate Goal: Discover Better Designs Faster

= Feasible = Infeasible

Objective 1 Objective 2

18

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SLIDE 19

Presented at the 2014 STAR-Global conference in Vienna The role of CHT analysis in the design process for cooled gas turbine components

– Design process of the Kawasaki L30A – Upgrade of an E-class gas turbine – Novel film cooling technologies

Conjug jugate e Hea eat Transfer er (CHT) Case S e Study dy

19

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SLIDE 20

Kawasaki L30A is the highest efficiency industrial 30 MW GT Full conjugate heat transfer analysis of the first stage vane

Des esig ign of the L3 e L30A 0A

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SLIDE 21

Boundary Conditions:

  • For primary gas path: stagnation

inlet & pressure outlet specified

  • For sealing inlets: mass flow inlet

specified

  • For cooling inlets (hub and shroud):

stagnation inlet specified

For cooling holes: mass flow is calculated (i.e., not specified)

Des esig ign of the L3 e L30A 0A

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SLIDE 22

All internal geometric detail retained Modeled metal inserts to capture impingement cooling effect

Des esig ign of the L3 e L30A 0A

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SLIDE 23

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Des esig ign of the L3 e L30A 0A

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SLIDE 24

Polyhedral mesh with prism layers 13.8M cells Conformal fluid-solid interface valuable for CHT

Des esig ign of the L3 e L30A 0A

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SLIDE 25

Des esig ign of the L3 e L30A 0A

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SLIDE 26

Des esig ign of the L3 e L30A 0A

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SLIDE 27

Full conjugate heat transfer (CHT) analysis of the first-row turbine vane Analysis included all geometric detail including vane internals and inserts Very good agreement of results (simulation VS. experiment) Provided a detailed understanding of thermal profile and potential issues

Des esig ign of the L3 e L30A 0A

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SLIDE 28

Engi ginee eerin ing g Sim imula lati tion

  • n Maturi

rity ty Mode del Validate Troubleshoot Predict Explore Optimize

Ultimate Goal: Discover Better Designs Faster

= Feasible = Infeasible

Objective 1 Objective 2

29

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SLIDE 29

(1) (2) (3)

b=29° „ear angle“

Anti-Kidney Vortex

2 1

ad f ,

2 1

Double Jet Film Cooling

cylindrical hole

ad f ,

film cooling effectiveness

hole exit Kidney Vortex Pair

  • Impact:
  • 300% improvement in cooling

effectiveness vs. shaped holes

  • Turbine can run at increased

temperatures enabling increased GT efficiency

  • Solution: Innovative “Nekomimi”

film cooling holes concept verified and improved by using:

  • Flow simulation (STAR-CCM+)
  • Parametric hole designs (NX)
  • Process automation (HEEDS)
  • Automated exploration (HEEDS)
  • Challenge: Increase GT efficiency while

avoiding scorched turbine blades, downtime

KH KHI: Innovati tive e Turbin ine e Blade de Cooli ling

0.1 0.2 0.3 0.4 0.5 0.6 0.7 5 10 15 20 25 30

Film Cooling Effectiveness [-] x/D [-]

shaped 1st Nekomimi manufactured Nekomimi 3rd variation Nth variation + 300 %

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SLIDE 30

Pred edic icti ting g pu pump mp flow pe performan rmance ce vir irtual ually ly

Inlet Atmospheric pressure @ outlet Blades rotating at 2900 RPM Goal: Produce pump Performance Curves via simulation (Flow vs. Delta Pressure)

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SLIDE 31

Pred edic icti ting g pu pump mp flow pe performan rmance ce vir irtual ually ly

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SLIDE 32

Robust, ust, streaml eamlin ined ed mode delin ing g & me & meshin ing

700,000 polyhedral cells including 2 prism layers for better flow accuracy

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SLIDE 33

Robust, ust, streaml eamlin ined ed mode delin ing g & me & meshin ing 2 prism layers

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SLIDE 34

Pred edic icti ting g pu pump mp flow pe performan rmance ce vir irtual ually ly

Low Flow Rate High Flow Rate

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SLIDE 35

Cavit itati tion

  • n in

insid ide a do double le-sucti suction

  • n pu

pump mp

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SLIDE 36

Suction Inlet Volute Impeller Inlet Total Pressure – 175 kPa Inlet Total Pressure – 80 kPa Inlet Total Pressure – 40 kPa Inlet Total Pressure – 27 kPa Inlet Plane of symmetry

  • Impact:
  • Clear understanding of pump performance

across wide operating range

  • Confidence in pump design through

simulation

  • Unsteady solution with cavitation
  • Poly meshed (~5M cells)
  • CAD geometry; half-model

with splitter; 1 blade passage cyclically patterned

  • Solution:
  • Challenge: Accurately predict

pump performance at BEP (+/-) as well cavitation occurrence

Sim imula lati tion

  • n of Compl

plex, x, Uns Unstea eady dy Fl Flows

Energy & Power

“STAR-CCM+ has all of the features required to solve extremely complex problems in hydraulic turbomachinery”

– Edward Bennett, Ph.D., VP of Fluids Engineering

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SLIDE 37

A centrifugal pump consisting of multiple stages, designed to provide large amounts of total developed head (TDH)

Multist istage ge Pump mp (showi wing g Fl Flow Domain in)

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SLIDE 38

Prim imary Station ionary/R y/Rota tati ting g Inter erface aces s and B d Bounda darie ies

39

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SLIDE 39

Sec econd

  • ndary Station

ionary/R y/Rota tati ting g Inter erfaces ces and d Bounda dari ries es

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SLIDE 40

STAR-CCM+ CM+ Mes esh Handl dles es Comple mplex x Fl Flow Pat Paths

Include critical leakage flow paths!

41

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SLIDE 41

Multist istage ge Cen entrif ifuga ugal l Pump mp

  • Flow Physic

ysics

  • Complex, transient flow through 360 degrees
  • Stationary and rotating domains
  • Unsteady forced response
  • Complex secondary flows
  • Relevant

nt STAR-CCM CM+ + feature ures s to facilitat litate a solutio tion

  • Unsteady flow solver
  • Unsteady cavitation model
  • Unsteady stationary/rotating interfaces
  • Advanced unstructured CFD meshing from CAD geometry
  • Parallel capability for large size and economical time to solution

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SLIDE 42

Pred edic icti ting g pu pump mp flow pe performan rmance ce vir irtual ually ly

359 GPM 1100 GPM

Q-H Curve

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SLIDE 43

STAR-CCM+ CM+ Fl Flow Vis isuali liza zati tions

  • ns

1100 GPM 359 GPM

44

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SLIDE 44

Customer

  • mer Succ

ccess ess

“STAR-CCM+ has been successfully used by Mechanical Solutions to solve extremely complex problems in hydraulic turbomachinery.” “STAR-CCM+ has all of the features required for an advanced, accurate CFD code, specifically:

  • Advanced geometry modeling and CAD capture
  • Relevant physical models to capture advanced flow physics
  • Post-processing tools that facilitate flow diagnosis and
  • ptimization”
  • - Ed Bennett, VP Fluids Engineering, MSI

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SLIDE 45

Engi ginee eerin ing g Sim imula lati tion

  • n Maturi

rity ty Mode del Validate Troubleshoot Predict Explore Optimize

Explore digitally, Confirm physically

Ultimate Goal: Discover Better Designs Faster

Critical inversion point (from reactive to proactive engineering)

= Feasible = Infeasible

Objective 1 Objective 2

46