Computational Fluid Dynamics for Reactor Design & …download.star-russian-conference.ru/star2014/SRC2014_CD-adapco... · Massachusetts Institute of Technology NSE Nuclear Science

Massachusetts Institute of Technology

NSENuclear Science & Engineering at MIT

science : systems : society

Computational Fluid Dynamics for Reactor Design &

Safety-Related ApplicationsEmilio Baglietto

[email protected]/newsoffice/2012/baglietto-better-reactors.html

STAR Russian Conference 2014Better reactors grow from better simulations

An Industrial/Research/Academic viewWearing 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 SpecialistCD-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.


Nuclear Industry Competitiveness CFD for LWR Operation / life extension An update on CASL related activities

Supporting Advanced Reactor Design SFRs fuel assembly for ultra-long operation VHTRs – virtual experiments

CFD towards Safety Related Applications A post Fukushima example Quality Assurance Requirements for Safety Related

Applications

Contents

Emilio Baglietto - Nuclear Science & Engineering at MIT

CASL: The Consortium for Advanced Simulation of Light Water ReactorsA DOE Energy Innovation Hub for Modeling & Simulation of Nuclear Reactors

Task 1: Develop computer models that simulate nuclear power plantoperations, forming a “virtual reactor” for the predictive simulation of LWRs.Task 2: Use computer models to reduce capital and operating costs perunit of energy, ……


A “Typical” Multi-Scale ProblemFull-core performance is affected by localized phenomena

• Local T&H conditions such as pressure, velocity, cross flow magnitude can be used to address challenge problems: oGTRF oFADoDebris flow and blockage• The design TH questions under normal operating and accident conditions such as:oLower plenum flow anomalyoCore inlet flow mal-distributionoPressure dropoTurbulence mixing coefficients

input to channel codeoLift forceoCross flow between fuel

assembliesoBypass flow

• The local low information can be used as boundary conditions for micro scale models.

PWR Model

Phase 2 Extensions• BWRs• SMRs


LWRs… not only Fuel Related Applications 6

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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Acc

eler

atio

n A

mpl

itud

e, g

RM

SSpan Number

Test Data VITRAN Simulation

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1 2 3 4 5 6 7

Dis

plac

emen

t Am

plit

ude,

µm

RM

S

Span Number

Test Data VITRAN Simulation

CFD Forcing / VITRANValidation

Fuel rod acceleration vibration amplitude

Fuel rod displacement vibration amplitude

A. M. Elmahdi, R. Lu, M. E. Conner, Z. Karoutas, E. Baglietto, 2011 - Flow Induced Vibration Forces on a Fuel Rod by LES CFD Analysis, Proceedings of the NURETH14 Conference, Toronto, Ontario, Canada.


Tightly Coupled Loads

8

0

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Forc

e (

N)

Element Number

RMS Forces: 10 m/s Coupled

0

0.05

0.1

0.15

1 2 3 4 5 6 7 8 9

Forc

e (

N)

Element Number

RMS Forces: 10 m/s Uncoupled

S.A. Tan-Torres - Coupled Fluid Structure Simulations for Application to Grid-to-Rod Fretting – M.S Thesis, MIT, May 2014.


STAR-CCM+ Platform for MultiphysicsHigh Fidelity T-H / Neutronics / CRUD / Chemistry Modeling

Petrov, V., Kendrick, B., Walter, D., Manera, A., Impact of fluid-dynamic 3D spatial effects on the prediction of crud deposition in a 4x4 PWR sub-assembly - NURETH15, 2013


STAR-CCM+ Platform for MultiphysicsHigh Fidelity T-H / Neutronics / CRUD / Chemistry Modeling

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


Improved Spacers DesignCFD Predictions of DNB

11J. 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.


12J. Yan, et al - Evaluating Spacer Grid CHF Performance by High Fidelity 2-Phase Flow Modeling – TOPFUEL2013

Improved Spacers Design



ORNL Geometry and Instrumentation

Fontana, M.H et al., 1973. Temperature Distribution in a 19-Rod Simulated LMFBR Fuel Assembly in

a Hexagonal Duct – Record of Experimental Data. Oak Ridge National Laboratory, Oak Ridge, TN.


In-Bundle Comparison 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

-0.5

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0.5

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exp

a

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c40%

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-0.0100

-0.0050

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0.0100

1,8 2,3 4,17 5,6 7,25 9,26 10,11 12,13 14,15 16,31 18,32 19,20 21,22 23,24

SC

CFD

Type 1


-0.0100

-0.0050

0.0000

0.0050

0.0100

1,6 2,11 3,4 5,20 7,24 8,9 10,27 12,28 13,14 15,16 17,18 19,33 21,34 22,23

SC

CFD

Type 2


-0.0100

-0.0050

0.0000

0.0050

0.0100

1,2 3,14 4,5 6,23 7,8 9,10 11,12 13,29 15,30 16,17 18,19 20,21 22,35 24,36

SC

CFD

Type 3


Reference• J.W. Fricano, E. Baglietto, 2014 - A quantitative CFD benchmark for

Sodium Fast Reactor fuel assembly modeling, Annals of Nuclear Energy 64 (2014) 32–42.


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


Quasi-DNS on Polyhedral Grids

~3.7 Million Points

Initializ. Synthetic Eddy Method

Flow / Solver Incompressible / Segregated flow

Time Discr. Second Order Implicit

Space Discretization Bounded central 5 % upwinding

Average CFL 0.5 (< 1)

Inlet – outlet Periodic Forced with mass flow rate


Science ChallengeA. Shams, F. Roelofs, E.M.J. Komen and E. Baglietto - CALIBRATION OF A PEBBLE BED CONFIGURATION FOR DIRECT NUMERICAL SIMULATION – NURETH14


High Resolution LES Database for Randomly Stacked Bed

23


Reference• A. Shams, F. Roelofs, E.M.J. Komen, E. Baglietto, 2014 - Large Eddy

Simulation of a Randomly Stacked Nuclear Pebble Bed - Computers & Fluids, Volume 96, 302-321.

• A. Shams, F. Roelofs, E.M.J. Komen, E. Baglietto, 2013 - Large eddy simulation of a nuclear pebble bed configuration, Nuclear Engineering and Design 261 (2013) 10– 19.

• A. Shams, F. Roelofs, E.M.J. Komen, E. Baglietto, 2013 - Numerical simulations of a pebble bed configuration using hybrid (RANS–LES) methods, Nuclear Engineering and Design 261 (2013) 201– 211.

• A. Shams, F. Roelofs, E.M.J. Komen, E. Baglietto, 2013 - Quasi-direct numerical simulation of a pebble bed configuration. Part I: Flow (velocity) field analysis, Nuclear Engineering and Design 263 (2013) 473–489.

• A. Shams, F. Roelofs, E.M.J. Komen, E. Baglietto, 2013 - Quasi-direct numerical simulation of a pebble bed configuration, Part-II: Temperature field analysis, Nuclear Engineering and Design 263 (2013) 490–499.

• A. Shams, F. Roelofs, E.M.J. Komen, E. Baglietto, 2012 - Optimization of a Pebble Bed Configuration for Quasi-direct Numerical Simulation – Nuclear Engineering and Design 242 (2012) 331–340.

RCIC SYSTEM 25

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

UNITS 2 & 3: PCV PRESSURE 26

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U N I T 3EARTHQUAKE

3/11 14:46


SPARGER MAIN DIFFERENCES 27

0.283 m

1.275 m2577 mm

0.680 m

D = 0.025 m

D=0.010 m0.033 m

0.036 m

0.065 m

U N I T 3U N I T 2VERTICAL JET HORIZONTAL

JETS


1F3 GEOMETRY 28

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

Regio

n B

~ 8 m

Pool pressure boundary


1F3 TEMPERATURE IN THE SPARGER 29

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


POOLEX STB-28-4 EXPERIMENT 30

Experimental results

• Large visible chugging

phenomenon

• Bubble collapse time = 80 ms

• Bubble diameter = 380 mm

• Collapse speed = 3 m/s

pool detailfacility sketch

T pool = 62 °CSteam Mass Flux = 8 kg/m2s

steam inlet

380 mm

219.1 mm


PRELIMINARY RESULTS: CHUGGING 31

1.00

0.75

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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



FIRST BUBBLE ANALYSIS GROWTH 32

STB-28-4 MEASUREMENTS

STAR-CCM+ RESULTS

Animation

of 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


CFD for Safety-Related Design and Analysis

CFD is undoubtedly becoming a fundamental instrument in the Safety Analyst Toolbox.

CFD offers a unique opportunity for improved physical understanding

Leads to more general applicability Reduced need for empirical

calibration, which means “lower costs!”

Challenge: Provide a path for application of CFD in

Safety Analysis. Assure that the process will capture all

“critical characteristics” of the application. Make the process “Applicable”.

33


The process:Commercial Grade Dedication

U.S. NRC Regulatory Guide 1.28 Rev. 4, June 2010

NQA-1-2008 with NQA-1a-2009 addendum

NQA-1-2012 Non-Mandatory Appendix (NMA)

EPRI 2012 - CGD Guidance for Safety-Related Design and Analysis

34


NQA-1-2012 Non-Mandatory Appendix (NMA)CC Description Acceptance Criteria Method of VerificationHost computer operating environment

The manufacture and model number of the host assembly or computer hardware computer program is intended to reside. This critical characteristic is applicable to all computer programs.

Host computer operating environment criteria must match the purchase specification. This should include the manufacturer name and model from a supplier’s catalog. (e.g., Dell PowerEdge T110 Tower Server, IBM AIX & System, and Dell Precision T3500 Workstation, Siemens Simatic S7-400)

Verified through one or more of the following:o Inspection of receipt inspection

documentation (Method 1)o Inspection of test system operating

system identifiers. (Method 1)

Host computer operating system identifier

Vendor name, operating system version, service packs or patch identifiers that are needed for the computer to be executed. This critical characteristic is applicable to all computer programs.

Host computer operating system identifier must match the identifier in the vendor product list (e.g., Microsoft Windows 7, UNIX Operating System Version 5.1, B-5, and Yokogawa Pro-Safe-RS R2.01.00)




Software Name

The full name of the software. It should be the same identifier as used for during the procurement/acquisition process. This critical characteristic is applicable to all computer programs.

Software name must match the product name from vendor catalog. (e.g., CFAST, Wolfram Mathematica 8, Monte Carlo N-Particle Transport Code System (MCNP5), Emerson valve Link, and Organic Concatenater)




Software Version Identifier

The complete version identifier including any patches. This critical characteristic is applicable to all computer programs.

Software version identifier must match the product identifier from the vendor catalog that includes software name-major functional version, minor functional version. corrective revision (e.g., CFAST-05.00.01, Hotspot-02.07.01, Emerson valve Link-02.04-13, and Organic Concatenater-3.1b)





How does it apply to CFD4 Categories of Critical Characteristics Identification i.e., version, build date, release name, or part or catalog number

Physical physical media (e.g., CD, tapes, downloads, or remote access)

Performance/Functional required functionality of the computer program to perform its safety

function and the accuracy of its results Dependability (unique to computer programs) Evaluation to develop judgment regarding built-in quality Includes attributes related to the supplier’s software development

process such as review of the computer program’s lifecycle processes and output documentation, review of configuration management activities, testing and V&V activities, and other activities.


Conclusions

Yes, it can be done and it has been done. The CGD process provides a robust and flexible framework

to adopt CFD for Safety Analysis. The CGD process requires rigorous assessment of the

“functionality of the computer program to perform its safety function and the accuracy of its results”.

For CFD this means understanding of the physical models and VUQ of the models on the intended application.

The CGD formalizes a process that is applied to all Safety-Related Design and Analysis.

Can we apply CFD to Safety-Related Design and Analysis ?

Documents

Computational Fluid Dynamics for Reactor Design & …download.star-russian-conference.ru/star2014/SRC2014_CD-adapco... · Massachusetts Institute of Technology NSE Nuclear Science