better simulations Emilio Baglietto emiliob@mit.edu Massachusetts - - PowerPoint PPT Presentation

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better simulations Emilio Baglietto emiliob@mit.edu Massachusetts - - PowerPoint PPT Presentation

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NSE Nuclear Science & Engineering at MIT science : systems : society Better reactors grow from better simulations Emilio Baglietto emiliob@mit.edu Massachusetts web.mit.edu/newsoffice/2012/baglietto-better-reactors.htm l Institute of

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Massachusetts Institute of Technology

NSE

Nuclear Science & Engineering at MIT science : systems : society

Better reactors grow from better simulations

Emilio Baglietto

emiliob@mit.edu

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

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SLIDE 2

STAR Chinese 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 Chinese 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  Extreme Heat Removal

Contents

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STAR Chinese 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

  • perating costs per unit of energy, ……

4

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Emilio Baglietto - Nuclear Science & Engineering at MIT

DeCART STAR-CCM+ Drekar Common Input

VERA

Hydra-TH system front-end COBRA-TF MPACT

VIPRE-W

Baseline

ANC9 BOA VABOC

LIME Trilinos DAKOTA MOOSE Thermal-Hydraulics Neutronics Thermo- Mechanics Chemistry Geometry / Mesh / DataTransferKit (DTK) MAMBA PEREGRINE XSProc Denovo RELAP5

Virtual Environment for Reactor Applications

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Emilio Baglietto - Nuclear Science & Engineering at MIT

Date 1984 1997 2000 2007 2011 Cost/GFLOPS $15million $30,000 $640 $48 $1.80

What does workstation mean?

OAK RIDGE, Tenn., Nov. 12, 2012 — The DOE Oak Ridge National Laboratory is again home to the most powerful computer in the world – Titan is a Cray XK7 system that contains 18,688 nodes, capable of a theoretical peak speed of 27 petaflops

  • VERA platform options
  • laptops, workstations, clusters, HPC systems (current vs. future)

What does workstation mean? you can get a 1.4 TF/s desk-side box with up to 512 GB, 16 CPU cores and ~900 GPU cores today

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Emilio Baglietto - Nuclear Science & Engineering at MIT

CFD Model CAD Model Drawings

  • RPV ID 173”, 193/4 Fuel Assemblies,13,944 fuel rods (fuel pellets,

helium gap), 434 spacers, 148,224 mixing vanes; 1.2 billion cells

4-Loop Westinghouse PWR Multi-Physics Model Development

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Emilio Baglietto - Nuclear Science & Engineering at MIT

  • RPV ID 173”, 193/4 Fuel Assemblies,13,944 fuel rods (fuel pellets,

helium gap), 434 spacers, 148,224 mixing vanes; 1.2 billion cells

4-Loop Westinghouse PWR Multi-Physics Model Development

Results Mesh

CFD Model

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SLIDE 9

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 10

Emilio Baglietto - Nuclear Science & Engineering at MIT

Thermal Hydraulics & Neutronics Coupling

CFD + Neutronics full depletion cycle simulation: 14 state points, total time required for a complete depletion cycle: 44 hours on 1028 cores. 44 hours /depletion-cycle proves that high fidelity CFD & Neutronics coupling is practical for engineering design for finalizing core design. The results will provide hot spot, boiling areas for CILC and crud simulation, fuel center line temperature, peak cladding temperature, and cross flow for GTRF. ANC power

Full Power 150MW*DAYS 1000MW*DAYS 2000MW*DAYS

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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 12

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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Emilio Baglietto - Nuclear Science & Engineering at MIT

Multiphase CFD

… better physical understanding

boiling heat transfer DNB void fraction

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STAR Chinese Conference 2013

Better reactors grow from better simulations

Improved Spacers Design

CFD Predictions of DNB

16

  • 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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STAR Chinese Conference 2013

Better reactors grow from better simulations

17

  • 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 16

RCIC SYSTEM

22

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 17

UNITS 2 & 3: PCV PRESSURE

23

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 18

SPARGER MAIN DIFFERENCES

24 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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1F3 GEOMETRY

25

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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1F3 TEMPERATURE IN THE SPARGER

26

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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SLIDE 21

POOLEX STB-28-4 EXPERIMENT

27 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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PRELIMINARY RESULTS: CHUGGING

28

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 23
  • M. Pellegrini, M. Naitoh, E. Baglietto

FIRST BUBBLE ANALYSIS GROWTH

29

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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Emilio Baglietto - Nuclear Science & Engineering at MIT

Spent Fuel Simulations

PVP2012-78491: CFD ANALYSES OF THE TN-24P PWR SPENT FUEL STORAGE CASK

  • R. A. Brewster, E. Baglietto, E. Volpenhein, C. Bajwa
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STAR Chinese Conference 2013

Better reactors grow from better simulations

  • The overall mesh consists of

about 18 million cells

  • Of these, approximately 2

million are in the fluid domain

  • Dominantly Polyhedral

Cells

  • Porous blocks meshed

using trimmed hexa

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STAR Chinese Conference 2013

Better reactors grow from better simulations

Example of Analysis Results

Cask Temperatures Basket Temperatures Total power dissipation in cask = 20,640 Watts

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STAR Chinese Conference 2013

Better reactors grow from better simulations

Comparison of measured and computed temperatures in the fuel assemblies - (using thermocouple lances) Measured and computed temperatures

  • n the basket, inner cask wall and outer

cask wall - (thermocouple lances and surface thermocouples)

Example of Analysis Results

Measurements on TN-24P under different conditions at Idaho National Laboratory, ca. 1987

  • 54 thermocouples measured temperatures in the fuel assemblies and basket surface
  • 14 thermocouples measured temperatures on the inner surface of the cask body
  • 35 thermocouples measured temperatures on the cask exterior
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STAR Chinese Conference 2013

Better reactors grow from better simulations

Modeling “Full Detail” of Fuel Assembly

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STAR Chinese Conference 2013

Better reactors grow from better simulations

And what about advanced concepts?

35

NuScale Power

ASTRID

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Emilio Baglietto - Nuclear Science & Engineering at MIT

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ORNL Geometry and Instrumentation

37

Images from Fontana et al. [6]

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Model Geometry

 Modeling inlet region of the test

section shown to be important

38

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In-Bundle Comparison

  • 0.5

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

39

 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 34

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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Emilio Baglietto - Nuclear Science & Engineering at MIT

100 200 300 400

q" DT=Twall- Tsaturation

Heat flux versus excess temperature

total boiling mixture convection

Nucleate

q" =qmax* (ΔT/DT1)k1 k1 > 0

Transition I

q" = parabolic

Transition II

q" =qmax*(ΔT/DT2)k2

k2<0

qmax qmax DT1 DT2

Challenging Extreme Heat Removal

  • Impact:
  • One-of-a-kind predictive capability

for extreme heat removal

  • Essential support to ITER critical

heat flux margin evaluation

  • Solution: An advanced transition

boiling model, capable of predicting heat transfer across all regimes, include post-dryout. Validated for fluxes 1-10 MW/m2

  • Challenge: design of water-cooled

first wall “hypervapotrons” for ITER, which may encounter heat fluxes as high as 5 MW/m2.

“Extreme Heat Removal for the Largest research project in the World”

D.L Youchison, et al. - Prediction Of Critical Heat Flux In Plasma Facing Components Using Computational Fluid Dynamics – TOFE 2010

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STAR Chinese 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