Computational Fluid Dynamics for Reactor Design & Safety-Related - - PowerPoint PPT Presentation

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Computational Fluid Dynamics for Reactor Design & Safety-Related - - PowerPoint PPT Presentation

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NSE Nuclear Science & Engineering at MIT science : systems : society Computational Fluid Dynamics for Reactor Design & Safety-Related Applications Emilio Baglietto emiliob@mit.edu Massachusetts

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SLIDE 1

Massachusetts Institute of Technology

NSE

Nuclear Science & Engineering at MIT science : systems : society

Computational Fluid Dynamics for Reactor Design & Safety-Related Applications

Emilio Baglietto

emiliob@mit.edu

web.mit.edu/newsoffice/2012/baglietto-better-reactors.html

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STAR Korean Conference 2013

Better reactors grow from better simulations

An Industrial/Research/Academic view

Wearing multiple hats:

Massachusetts Institute of Technology

  • Assistant Professor of Nuclear Science and

Engineering, Massachusetts Institute of Technology.

  • Deputy Lead TH Methods Focus Area,

CASL – a US Department of Energy HUB.

  • Nuclear Industry Sector Specialist

CD-adapco

  • Member of NQA-1 Software Subcommittee.

Disclaimer: the following slides are intended for general discussion. They represent the personal view of the author and not that of MIT, CASL or the ASME NQA-1 Software Subcommittee.

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STAR Korean Conference 2013

Better reactors grow from better simulations

  • Nuclear Industry Competitiveness

 CFD for Nuclear Reactor Design  Leveraging the research/academia efforts

  • Computational Microscopes

 Multi-scale Applications  CFD as Multi-physics platform

  • CFD for Advanced Reactor Concepts

 Fast Reactors Fuel  VHTRs – virtual experiments

  • CFD for Safety Related Applications

 The US-NRC example

Contents

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SLIDE 4

Emilio Baglietto - Nuclear Science & Engineering at MIT

Background

  • 2011- present

Assistant Professor of Nuclear Science and Engineering, MIT

  • 2006-2011

Director Nuclear Application, CD-adapco

  • 2004-2006

Research Associate, Tokyo Institute of Technology

2012 2009

PBMR

2005

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SLIDE 5

STAR Korean Conference 2013

Better reactors grow from better simulations

CASL: The Consortium for Advanced Simulation of Light Water Reactors

A DOE Energy Innovation Hub for Modeling & Simulation of Nuclear Reactors

Task 1: Develop computer models that simulate nuclear power plant operations, forming a “virtual reactor” for the predictive simulation of light water reactors.

Task 2: Use computer models to reduce capital and operating costs per unit of energy, ……

5

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SLIDE 6

Emilio Baglietto - Nuclear Science & Engineering at MIT

  • Local T&H conditions such as

pressure, velocity, cross flow magnitude can be used to address challenge problems:

  • GTRF
  • FAD
  • Debris flow and blockage
  • The design TH questions under

normal operating and accident conditions such as:

  • Lower plenum flow anomaly
  • Core inlet flow mal-distribution
  • Pressure drop
  • Turbulence mixing coefficients

input to channel code

  • Lift force
  • Cross flow between fuel

assemblies

  • Bypass flow
  • The local low information can be used

as boundary conditions for micro scale models.

Model 1 Model 2

A “Typical” Multi-Scale Problem

Full-core performance is affected by localized phenomena

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SLIDE 7

Emilio Baglietto - Nuclear Science & Engineering at MIT

STAR-CCM+ Platform for Multiphysics

High Fidelity T-H / Neutronics / CRUD / Chemistry Modeling

Petrov, V., Kendrick, B., Walter, D., Manera, A., Impact of fluid-dynamic 3D spatial effects

  • n the prediction of crud deposition in a 4x4 PWR sub-assembly - NURETH15, 2013
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SLIDE 8

Emilio Baglietto - Nuclear Science & Engineering at MIT

STAR-CCM+ Platform for Multiphysics

High Fidelity T-H / Neutronics / CRUD / Chemistry Modeling

Petrov, V., Kendrick, B., Walter, D., Manera- NURETH15, 2013

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SLIDE 9

STAR Korean Conference 2013

Better reactors grow from better simulations

Not only Fuel Related Applications

10

Mature Applications

  • Fuel

 Pressure Drops  Crud (CIPS/CILC)  Vibrations (GTRF)

  • System and BOP

 Transient Mixing  Hot Leg Streaming  Thermal Striping  SG performance  Cooling Towers Interference

  • Fuel Cycle and Beyond Design

Basis Applications

 Spent fuel transportation and

Storage

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SLIDE 10

Emilio Baglietto - Nuclear Science & Engineering at MIT

Multiphase CFD

… better physical understanding

boiling heat transfer DNB void fraction

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SLIDE 11

STAR Korean Conference 2013

Better reactors grow from better simulations

Improved Spacers Design

CFD Predictions of DNB

13

  • J. Yan, et al - Evaluating Spacer Grid CHF Performance

by High Fidelity 2-Phase Flow Modeling – TOPFUEL2013

  • CFD–based CHF modeling development

being performed by Westinghouse Nuclear Fuel.

  • 5x5 test bundle PWR experiment from

the ODEN CHF test facility were modeled in CFD using the latest 2-phase boiling model.

  • Excellent trend agreement in CHF

predictions.

  • Novel understanding of fundamental

physics allows improving the CHF performance.

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SLIDE 12

STAR Korean Conference 2013

Better reactors grow from better simulations

14

  • J. Yan, et al - Evaluating Spacer Grid CHF Performance by High Fidelity 2-Phase Flow Modeling – TOPFUEL2013

Improved Spacers Design

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SLIDE 13

RCIC SYSTEM

19

MO MO HO HO

Control valve Turbine stop valve

#2

TIME

70 HOURS 20 HOURS #3

TIME

RCIC RCIC

  • M. Pellegrini, M. Naitoh, E. Baglietto
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SLIDE 14

UNITS 2 & 3: PCV PRESSURE

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0.2 0.4 0.6 3/11 12:00 3/12 0:00 3/12 12:00 3/13 0:00 3/13 12:00

Primary containment vessel pressure (MPa [abs])

Date/time

U N I T 2 U N I T 3 EARTHQUAKE 3/11 14:46

  • M. Pellegrini, M. Naitoh, E. Baglietto
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SLIDE 15

SPARGER MAIN DIFFERENCES

21 0.283 m 1.275 m

2577 mm 0.680 m

D = 0.025 m D=0.010 m 0.033 m 0.036 m 0.065 m

U N I T 3 U N I T 2

VERTICAL JET HORIZONTAL JETS

  • M. Pellegrini, M. Naitoh, E. Baglietto
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SLIDE 16

1F3 GEOMETRY

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sparger Detail of holes mesh size Elements size in the pool = 0.1~0.2 m Region A size = 1 mm Region B size = 2 mm Region B

~ 8 m

Pool pressure boundary

  • M. Pellegrini, M. Naitoh, E. Baglietto
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SLIDE 17

1F3 TEMPERATURE IN THE SPARGER

23

steam flow

Tpool = 30°C

~ 3.0 m

Large water head creates differences between mass flow rate between holes in the vertical direction 2 seconds real time Region A Region B

  • M. Pellegrini, M. Naitoh, E. Baglietto
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POOLEX STB-28-4 EXPERIMENT

24 Experimental results

  • Large visible chugging

phenomenon

  • Bubble collapse time = 80 ms
  • Bubble diameter = 380 mm
  • Collapse speed = 3 m/s

pool detail facility sketch

T pool = 62 °C Steam Mass Flux = 8 kg/m2s

steam inlet

380 mm 219.1 mm

  • M. Pellegrini, M. Naitoh, E. Baglietto
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SLIDE 19

PRELIMINARY RESULTS: CHUGGING

25

1.00 0.75 0.50 0.25 0.00

volume fraction

PIPE MOUTH

0.3 kg/s 0.3 kg/s

Flow enters the pool. Large turbulence is created, increased condensation CONDENSATION MASS TRANSFER

  • M. Pellegrini, M. Naitoh, E. Baglietto
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SLIDE 20
  • M. Pellegrini, M. Naitoh, E. Baglietto

FIRST BUBBLE ANALYSIS GROWTH

26

STB-28-4 MEASUREMENTS STAR-CCM+ RESULTS Animation

  • f the first

bubble

  • Chugging phenomenon can be recreated only for the first bubble
  • Bubble collapse velocity and phenomenon stability is highly dependent on

the modeling assumptions

  • More physical investigation and sensitivity analysis is required
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SLIDE 21

STAR Korean Conference 2013

Better reactors grow from better simulations

And what about advanced concepts?

27

NuScale Power

ASTRID

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SLIDE 22

ORNL Geometry and Instrumentation

28

Images from Fontana et al. [6]

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SLIDE 23

Model Geometry

 Modeling inlet region of the test

section shown to be important

29

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SLIDE 24

In-Bundle Comparison

  • 0.5

0.5 1 1.5 2 5 10 15 20 25 30 35 exp a b c

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 Compare to 36 different thermocouples for each case

 Plot below shows the experimental measurement for each

thermocouple matches the at least one of the CFD probes

 Analyze the whole data set

 CDF of all the error of the measurement and nearest probe for

all data points for all 7 cases

40% 50% 60% 70% 80% 90% 100%

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SLIDE 25

Emilio Baglietto - Nuclear Science & Engineering at MIT

DNS-grade Pebble Bed Flow Modelling

  • Impact:
  • A DNS database for pebble bed

simulations to support industrial applications

  • Optimization of flow and temperature

distribution allowing improved fuel performance and reliability

  • Solution: Quasi-DNS simulations

have been used to collect a virtual database and develop improved simulation guidelines based on RANS modeling.

  • Challenge: Accurately predict the

flow and heat transfer in random beds of pebble fuel cooled by helium.

  • The tight geometrical configuration

does not allow accurate experimental measurements

  • Shams et al. Nuclear Engineering and

Design, Vol. 242-261-263 - 2012-2013

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SLIDE 26

STAR Korean Conference 2013

Better reactors grow from better simulations

  • Better Reactors Grow from Better Simulations

 I strongly believe this! 3D CFD results allow better understanding, more generality and fast prototyping.

  • Mature Single Phase Applications

 A large number of validated applications for LWRs.  Fundamental Design tool for Advanced and Innovative Concepts [LMFBR, VHTR, MoltenSalt …]

  • Multiphase CFD is stepping up

 Already applied for design, successfully.  Drastically enhanced robustness will derive from more physically based closures.

Some Conclusions