Engineering Analysis of Stochastic Mechanics for Nuclear ... › sites › bigdata... · AP1000...

Westinghouse Non-Proprietary Class 3 © 2018 Westinghouse Electric Company LLC. All Rights Reserved.

1

Gregory Banyay, P.E. (presenter)Michael DrudyBrian Golchert, Ph.D.Matthew KelleyScott SidenerClarence Worrell, P.E.

Engineering Analysis of Stochastic Mechanics for Nuclear Power Plants at Westinghouse

Big Data for Nuclear Power Plants Workshop 2018The Ohio State University, Columbus, OH

2


Abstract• The design and analysis, as well as the operations and maintenance (O&M) of

nuclear power plants involves the accumulation and evaluation of large heterogeneous data sets which have implications to both plant safety and financial performance. This heterogeneity is manifested in the multiplicity of physics, time scales, and general data structure. Uncertainty pervades such data sets thus rendering nondeterministic engineering analysis methods (i.e., “analytics”) of paramount importance.

• This presentation highlights two specific successful projects within which Westinghouse has successfully made value-added use of large data sets combined with analytics methods and uncertainty quantification (UQ).

– The first project involves the evaluation of flow-induced vibration (FIV) associated with the startup of a new plant design, including the Comprehensive Vibration Assessment Program (CVAP) and companion Hot Functional Testing (HFT).

– The second project involves the development of a semi-empirical prognostic reliability model to simulate baffle-former bolt degradation attributed to Irradiation Assisted Stress Corrosion Cracking (IASCC).

• While those two projects represent a small sample of recently completed projects, Westinghouse is presently moving towards making analytics-based enhancements to engineering services offerings in the areas such as Condition Based Maintenance (CBM) and Structural Health Monitoring (SHM), and Probabilistic Risk Assessment (PRA), and that vision is briefly described.


3

Synopsis - The Comprehensive Vibration Assessment Program (CVAP) for AP1000® Plant Reactor Internals

AP1000 is a trademark or registered trademark in the United States of Westinghouse Electric Company LLC, its subsidiaries and/or its affiliates. This mark may also be used and/or registered in other countries throughout the world. All rights reserved.

4


Background – Nuclear Regulator Requirements• U.S. NRC Regulatory Guide 1.20 – Comprehensive Vibration

Assessment Program for Reactor Internals during Preoperational and Initial Startup Testing

• Four (4) Primary Elements for CVAP to meet Reg. Guide 1.201) Vibration Analysis Program

• Predictions• Acceptance criteria

2) Vibration Measurement Program• Full-scale, Full-flow, Approximate operational temperatures

3) Inspection Program4) Documentation of Results

• Pre-Test report with predictions and acceptance criteria• 60-day Post-Test report – basic results (can load fuel afterwards)• 180-day Post-Test report – full FIV analysis report

Completed in 2017

5


AP1000 Plant• The lead unit is Sanmen 1 in China (south of Shanghai)

Now Operating!

7


AP1000 Plant Reactor Configuration• Generation 3+ Pressurized Water Reactor (PWR)• Flow rate (Q) = 315,000 gpm• Tcold = 535, Thot = 612 °F• Four Reactor Coolant Pumps• Two Steam Generators• Direct Vessel Injection

Lead Plant is now operating in China!

8


RVI OverviewReactor VesselClosure HeadNot Shown

9


AP1000 Plant Reactor Internals – Historical Precedent• Although Reg. Guide 1.20 classifies the AP1000 Plant

Reactor Internals as prototype due to various first-of-a-kind (FOAK) design features, the majority of the AP1000 Plant Reactor Internals design is similar to existing plants that have been safely operating for many years.

Legacy Westinghouse plant experience has provided insight to AP1000 Plant CVAP

Doel 4

10


AP1000 Plant Reactor Internals – Historical Precedent• Sub-scale model testing

– 124

, 122

, and 17

scale tests have been performed for legacy 3-loop and 4-loop plants• 1/7-scale test performed specifically for AP1000 lower internals

– Demonstrated good agreement between scale model tests and Hot Functional Tests (HFT)* at H.B. Robinson (3-loop), Indian Point (4-loop), and Trojan

• HFT* at Trojan has verified the structural adequacy of the AP1000 Plant guide tube design as well as other RVI component configurations

Experimental Datasets accumulated from past experience proved invaluable on

the design of the AP1000 plant

* CVAP testing is a subset of overall plant testing known as Hot Functional Test (HFT)

11


Turbulence… is not easy to define, understand, and characterize… but it dominates the flow-induced response of primary equipment within a nuclear plant!

“When I meet God, I am going to ask him two questions: Why relativity? And why turbulence? I really believe he will have an answer to the first”

- Werner Heisenberg

Leonardo Da Vinci “sketches of turbulence”

12


AP1000 Plant Reactor Internals – Turbulence• A significant location of Turbulence is in the channel flow of

the Reactor Vessel Downcomer• Turbulence jetting through nozzles, buffeting on plates,

cross-flow and axial-flow around tubes and tube arrays all occur within the RVI

In general, Turbulence dominates the response of the RVI to Flow-Induced

Vibrations

𝑆𝑆𝐹𝐹𝑦𝑦 =12𝜌𝜌𝑈𝑈2𝐷𝐷

2

�𝐷𝐷𝑈𝑈� Φ �𝑓𝑓𝐷𝐷

𝑈𝑈

Generic Form of Turbulence Force Power Spectral Density (PSD) Function

13


AP1000 Plant Reactor Internals – Acoustics• Reactor Coolant Pump Pulsation

– Motor-driven Centrifugal Reactor Coolant Pump pulsates at shaft and blade-passing frequencies

– Variable Speed Reactor Coolant Pump (RCP’s)• Turbulence-Induced Acoustics at Low Frequencies

Acoustics could excite significant structural modes and thus require extensive analysis

Illustration of Acoustic Modes in Reactor Internals

Impeller/stator/ volute

Freq

Flow path

14


Finite Element Modeling

• A finite element model of the reactor system is dynamically subjected to FIV forcing functions

• The response of this model is used to develop CVAP predictions (expected measurements) and acceptance criteria

• Recently completed Surrogate-based Global Sensitivity Analysis (GSA) on System Finite Element Models– Generated large data sets through

computational Design of Experiment (DOE)

15


Illustration of Sensor Locations

~130 sensors+Sampled at 10 kHz+For ~6 month test duration+Historian data=A lot of Data

… then, store and transmit from China to Pittsburgh

Presenter

Presentation Notes

Sensor figure resides in non-prop CVAP WCAP

16


AP1000 Plant Reactor Internals – Signal Processing• A test results post-processing and plotting software has been

developed that has the following capabilities:– Multi-windowing options, filtering options (high, low, pass, notch)– Coherent noise reduction (Condition Spectral Density)– Autospectra / PSDs– Cross-Spectra / Coherence / Phase– Circumferential Wavenumber Decomposition– Mode shape phase plotter– Readily available integration of acceleration to displacement as well as

narrowband frequency range definition• Process/store complete covariance matrix (~ 130 sensors for CVAP

+ co-process with other plant sensors) • DAQ/software made measurement comparisons to acceptance

criteria during testing

Quick turnaround of complex analysis informed day-to-day activities during Hot Functional

Testing

17


Conclusions• The Westinghouse AP1000 Plant construction and Hot

Functional Testing (HFT) were successfully completed, and the pilot plant is now operational– Compliance with regulatory guidance has been demonstrated

• Extensive analyses have been performed to establish CVAP test predictions and acceptance criteria for which the structural response is driven by various FIV excitation mechanisms, including random turbulence and acoustic phenomena

• This involved the efficient processing, storage, transmittal, and analysis of large computational and experimental data sets

Flow-Induced Vibrations constitute very large data sets and played a critical role in

the completion of the AP1000 Plant


18

Predictive Modeling of Baffle Former Bolt Failures in Pressurized Water Reactors

19


Westinghouse-Designed Pressurized Water Reactor

Baffle-Former Bolts

20


Baffle-Former Bolts• Attach baffle plates to

former plates

• Austenitic stainless steel

• Highly irradiated

– > 20 dpa

• History of Failures

– Domestic/International

21


Historical Experience with BFBs

• 1989 Bugey– First inspection showing BFB

degradation in Europe (baffle jetting concern)

• 1990s Multiple inspections throughout French, Belgian, Japanese, and Korean plants

• 2010 DC Cook– Visual inspection first U.S. indication

of a larger issue– Limited inspection detected 42

degraded bolts• 2016-2018 Inspections continuing

at multiple US plants– Large-scale degradation observed at

Indian Point, Salem, and DC Cook

23


What is the Cause (or Causes) of BFB Degradation?

• Failure analysis conducted for many of these plants

• Conclusions on degradation mechanism:– Degradation initiated by irradiation-

assisted stress corrosion cracking (IASCC)

– Initiated cracks propagated by multiple mechanisms—IASCC, fatigue, overload

• Why are we seeing large clusters of degraded bolts now?– Clustering observed in one plant

design (4-Loop downflow)– Clusters of degraded bolts lead to

increased stress on surrounding bolts, accelerating further failures Some clear conclusions are

available but there is much left to understand

Intergranular IASCC at the edge of a boltshank fracture surface (McKinley et. al.)

24


Irradiation-Assisted SCC (IASCC)

Predictions of BFB Degradation must use these variables for IASCC as inputs

Stress

Material

Environment

Irradiation enhances all three components required for SCC

• Local Chemistry • Increased Hardness

• Active loading• Redistribution • Swelling • Thermal &

Irradiation stresses

• Radiolysis• Radiation• Primary Water

IASCC

27


Dos

e R

ate

Weibull Cumulative Distribution Function Variation

Variation with Dose at constant Stress

Stre

ss

Variation with Stress at constant Dose Rate

28


Example of Time Dependent Bolt Stresses With multiple inspections & bolt replacements

Predicting Time-Dependent Stresses in Individual Bolts is Critical for Accurate

Predictions

29


Simulation ModelSimulation Tool Interface Integrated FEA

Bolt Inspection Inputs (Octant Shown)

31


Effect of an Inspection and Replacement on Results

Inspection and Replacement Essentially “Reset the Clock”

Plant A

Plant D

Plant C Plant B

32

Westinghouse Proprietary Class 2 © 2017 Westinghouse Electric Company LLC. All Rights Reserved.

Example Time-Dependent Bolt Failure Pattern

Bolt Replacement and New Failures are Simulated

• Red = Higher Probability of Degradation

• Blue = Lower Probability of Degradation

33


Summary• The Westinghouse BFB predictive methodology is based on a

mechanistic understanding of BFB degradation and thus employs a semi-empirical paradigm

• Evaluation incorporates parameters from several sources– Finite element analysis of the baffle-former assembly– Operating experience from PWRs– Laboratory test results of IASCC

• Good comparisons have been demonstrated between model predictions and operating

• Application of model can support:– Pre-outage expectations:

• Outage duration, replacement bolt orders, manpower planning, etc.– Anti-clustering replacement recommendation– Re-inspection recommendation– Input to decision advisor tool

34


Conclusions• The design and analysis, as well as the operations and maintenance,

activities with which Westinghouse supports the nuclear industry involve the accumulation and intelligent use of vast and large data sets

• Successful analysis of such data sets has resulted in successful projects such as:– AP1000 Plant Comprehensive Vibration Assessment Program (CVAP)– Baffle-Former Bolt Predictive Modeling– Reactor Coolant Pump Turning Vane Bolt Reliability Modeling*– Fuel performance prediction using post-irradiation exams and

experimental testing*• … which is leading to further technological investments targeting:

– Condition Based Maintenance (CBM) and Structural Health Monitoring (SHM)*• Both active (i.e., pumps) and passive (i.e., pipes) components

– Dynamic Probabilistic Risk Assessment*– Computational methods for stochastic simulation of:

• structural mechanics, fluid dynamics, acoustics, fracture mechanics, and multi-physics (i.e., Departure from Nucleate Boiling (DNB))*

* - Not detailed within this presentation, but additional detail can be provided if desired.

Date post:	28-May-2020
Category:	Documents
Upload:	others
View:	5 times
Download:	0 times

Engineering Analysis of Stochastic Mechanics for Nuclear ... › sites › bigdata... · AP1000...

Documents