NUREG/CR-6778

The Effects of Composition and

Heat Treatment on Hardening and

Embrittlement of Reactor Pressure

Vessel Steels

University of California at Santa Barbara

U.S. Nuclear Regulatory Commission

Office of Nuclear Regulatory Research

Washington, DC 20555-0001
AVAILABILITY OF REFERENCE MATERIALS

IN NRC PUBLICATIONS

NRC Reference Material

As of November 1999, you may electronically access

NUREG-series publications and other NRC records at

NRC's Public Electronic Reading Room at

htto://www.nrc.aov/readina-rm.html. Publicly released

records include, to name a few, NUREG-series

publications; Federal Register notices; applicant,

licensee, and vendor documents and correspondence;

NRC correspondence and internal memoranda;

bulletins and nformation notices; inspection and

investigative reports; licensee event reports; and

Commission papers and their attachments.

NRC publications in the NUREG series, NRC

regulations, and rdle 10, Eineigy, in the Code of

Federal Regulations may also be purchased from one

of these two sources.

1. The Superintendent of Documents

U.S. Govemment Printing Office

Mail Stop SSOP

Washington, DC 20402-0001

Intemet bookstore.gpo.gov

Telephone: 202-512-1800

Fax: 202-512-2250

2. The National Technical Information Service

Springfield, VA 22161-0002

www.ntis.gov

1-800-553-6847 or, locally, 703-605-6000

A single copy of each NRC draft report for comment is

available free, to the extent of supply, upon written

request as follows:

Address: Office of the Chief Information Officer,

Reproduction and Distribution

Services Section

U.. Nuclear Regulatory Commission

Washington, DC 20555-0001

E-mail: DSTRIBUTION@nrc.gov

Facsimile: 301-415-2289

Some publications in the NUREG series that are

posted at NRC's Web site address

http:/www.nrc.povfreadina-rm/doc-collectionslnurens

are updated periodically and may differ from the last

printed version. Although references to material found

on a Web site bear the date the material was accessed,

the material available on the date cited may

subsequently be removed from the site.

Non-NRC Reference Material

Documents available from public and special technical

libraries include all open literature items, such as

books, joumal articles, and transactions, Federal

Register notices, Federal and State legislation, and

congressional reports. Such documents as theses,

dissertations, foreign reports and translations, and

non-NRC conference proceedings may be purchased

from their sponsoring organization.

Copies of industry codes and standards used in a

substantive manner in the NRC regulatory process are

maintained atThe NRC Technical Library

Two White Flint North

11545 Rockville Pike

Rockville, MD 20852-2738

These standards are available in the library for

reference use by the public. Codes and standards are

usually copyrighted and may be purchased from the

originating organization or, if they are American

National Standards, fromAmerican National Standards Institute

11 West 4 2nd Street

New York, NY 10036-8002

www.ansi.org

212-42-4900

Legally binding regulatory requirements are stated

only in laws; NRC regulations; licenses, including

technical specifications; or orders, not in

NUREG-series publications. The views expressed

In contractor-prepared publications In this series are

not necessarily those of the NRC.

The NUREG series comprises (1) technical and

administrative reports and books prepared by the

staff (NUREG-XXXX) or agency contractors

(NUREG/CR-XXXX), (2) proceedings of

conferences (NUREGICP-XXXX), (3) reports

resulting from intemational agreements

(NUREG/IA-X)XX), (4) brochures

(NUREGIBR-XXXX), and (5) compilations of legal

decisions and orders of the Commission and Atomic

and Safety Licensing Boards and of Directors'

decisions under Section 2.206 of NRC's regulations

(NUREG-0750).

DISCLAIMER: This report was prepared as an account of work sponsored by an agency of the U.S. Govemment.-

Neither the U.S. Govemment nor any agency thereof, nor any employee, makes any warranty, expressed or

implied, or assumes any legal liability or responsibility for any third party's use, or the results of such use, of any

information, apparatus, product, or process disclosed in this publication, or represents that its use by such third

party would not infringe privately owned rights.
NUREG/CR-6778

The Effects of Composition and

Heat Treatment on Hardening and

Embrittlement of Reactor Pressure

Vessel Steels

Manuscript Completed: April 2002

Date Published: May 2003

Prepared by

G. R. Odette, G. E. Lucas, D. Klingensmith,

B. D. Wirth, D. Gragg

Department of Mechanical and Environmental Engineering

University of California at Santa Barbara

Santa Barbara, CA 93106

C. Santos, NRC Project Manager

Prepared for

Division of Engineering Technology

Office of Nuclear Regulatory Research

U.S. Nuclear Regulatory Commission

Washington, DC 20555-0001

NRC Job Code Y6396
NUREG/CR-6778, has been reproduced

from the best available copy.
ABSTRACT

This report addresses several important issues regarding possible revisions of RG 1.99 Rev. 2 to

predict irradiation induced hardening (Aay) and hence embrittlement manifested as shifts (AT) in the

41 J Charpy test transition temperature. We are developing a Aa, database from controlled, singlevariable experiments to map the individual and interactive effects of metallurgical and environmental

variables. The data are generated from a large matrix of composition-controlled alloys irradiated in

the Irradiation Variables Facility (IVAR) at the University of Michigan Ford Research Reactor. The

results provide quantitative and independent validation of the two component form of the

NUREG/CR-655 1 model, comprised of matrix feature (MF) and copper rich precipitate (CRP) terms.

The IVAR database also quantitatively supports: 1) the model treatments of a strong copper-nickel

interaction in the CRP term; 2) the treatment of phosphorous in the MF term; 3) an independent

validation of a maximum effective matrix copper level (Cu.) of around 0.3% following heat

treatment; and 4) a sensitivity of Cu. to nickel content. The IVAR database also shows: I)

manganese interaction with copper and nickel in the CRP contribution; 2) manganese and nickel

increase the MF term; 3) a somewhat unanticipated effect of flux and flux-composition interactions

on the fluence dependence of Aay and AT; and 4) a possible reduction in the effect of phosphorus at

higher copper.

iii
TABLE OF CONTENTS

ABSTRACT ........................... iii

LIST OF FIGURES .......................... vii

LIST OF TABLES .......................... ix

EXECUTIVE SUMMARY ........................... x

ACKNOWLEDGMENTS ........................... xii

NOMENCLATURE AND SYMBOLS ........... ............... xiii

I BACKGROUND AND INTRODUCTION .1

2 OBJECTIVES, STRATEGY, FOCUS AND ORGANIZATION OF THE REPORT . 4

3 MATERIALS, EXPERIMENTAL METHODS AND DATA ANALYSIS AND

EVALUATION PROCEDURE .6

3.1 Alloys And Specimens .6

3.2 Irradiations 7

3.3 Tensile Testing .18

3.4 Small Angle Neutron Scattering .19

3.5 Field Emission Gun Scanning Transnission Electron Microscopy .21

3.6 Electrical Resistivity Measurements .22

3.7 Seebeck Coefficient Measurements .23

4 EFFECTS OF COMPOSITION ON IRRADIATION HARDENING AND

EMBRITTLEMENT .24

4.1 Summary of the Data Trends .. 24

4.1.1 Copper Bearing Alloys .24

4.1.2 Low Copper Alloys .28

5 ANALYSIS OF THE COMPOSITIONAL TRENDS .33

5.1 Comparison of the IVAR Results With Predictions of the

NUREG/CR-6551 Model .. 33

5.2 The Microstructural Basis, Mechanisms and Models for the Composition

Dependence of Hardening and Embrittlement .. 36

5.2.1 Copper Rich Precipitates .36

5.2.2 Matrix Features .39

5.3 Discussion of Improvements in the NUREG Embrittlement

Correlation Model Treatment of Composition Effects . .40

6 EVALUATION OF THE MATRIX COPPER CONTENT .44

6.1 General Effects of Heat Treatment on 0 y and y . . .45

6.2 Estimates of Matrix Copper Levels 49

6.2.1 Estimates of Cum Based on Dsy Deviations From the Low Copper c

Trend Line .49

6.2.2 Estimates of Cum Based on VSR AcFy Trends and the Modified

NUREG/CR-6551 Aay Model .52

v
6.3 Microanalytical Assessments of Cum ..................................................... 58

6.3.1 Field Emission Gun Scanning Transmission Electron Microscopy ................. 58

6.3.2 Electrical Resistivity ..................................................... 58

6.3.3 Seebeck Coefficient ..................................................... 62

6.4 Summary and Discussion of the Dsy and Microanalytical Based Estimates

of CUm ................ 65

6.5 Small Angle Neutron Scattering Studies from the PB Experiment .............................. 66

7 A PRE-PRECIPlTATION MODEL FOR Cu ................................ 71

8 SUMMARY AND CONCLUSIONS ............................... 74

9 REFERENCES ............................... 76

APPENDIX A THE NUREG A, MODEL .. 80

APPENDIX B TENSILE DATA FOR T4, T14, VSR AND PB . .85

vi
LIST OF FIGURES

Figure Page

Figure 3-1 Specimen Baskets in the IVAR Facility ............................................................. 13

Figure 3-2 Schematic Design of the IVAR Irradiation Facility ................................................... 14

Figure 4-1 Variation of Auy with bulk copper in intermediate nickel alloys for the a) CM and

b) LV series ............................................................. 25

Figure 4-2 Variation of Aa. with nickel for a) 0.4 copper and b) 0.2 copper CM alloys;

c) comparison of Au, versus nickel for intermediate and high copper steels for T14;

d) Variation of AcY with nickel for high copper LV series steels (corresponding CM

alloys shown for comparison as small filled symbols) ........................... ................... 26

Figure 4-3 Variation of y with manganese for intermediate nickel, high copper CM and LV

steels ............................................................. 27

Figure 4-4 Variation of boy with boron, molybdenum, and chromium for a) PB and b) T14 ... 27

Figure 4-5 Variation of Au with phosphorous for a) low copper, low nickel; b) low copper,

intermediate niclel; and c) low copper, high nickel steels; d) Variation of phosphorous

sensitivity (B) with nickel; e) Comparison of Aay (P) for alloys with 0.02 and 0.11

copper ............................................................. 30

Figure 4-6 Variation of Ac, with nickel for a) low and b) high phosphorous steels .......... .......... 31

Figure 4-7 Variation of Aay with manganese for low copper CM alloys ................ .................... 31

Figure 4-8 Variation of Aar with carbon, nitrogen, boron and tramp elements (TE) for low copper

CM steels ............................................................. 32

Figure 5-1 Comparison of the NUREG-Acry model predictions with the data from the

capsule T14 ............................................................. 34

Figure 5-2 Comparison of the NUREG-Ac7 model predictions with the data from capsule T14

adjusted to 0.8% nickel and 0.005% phosphorous .................................................. 34

Figure 5-3 Comparison of the NUREG-AcTy model predictions of nickel dependence of

embrittlement with the T14 data for a) 0.4% copper and b) 0.2% copper steels ....... 35

Figure 54 Comparison of NUREG-A&, model predictions with AG data as a function of fluence

for low copper (0.02%) intermediate nickel (0.85%) CM alloys for both low

(0.005%, CM3) and high (0.04%, CM5) phosphorous levels ............... .................... 35

Figure 5-5 Volume fraction of CRP's estimated from SANS measurements on CM and LV

alloy for the PB capsule as a function of a) nickel for CM alloys, b) nickel for

LV alloys, and c) manganese for CM alloys; d) comparison of measured AaSJ with

values predicted from SANS microstructural parameters ................... ..................... 38

Figure 5-6 Variation of Aa, with a matrix chemistry factor given in Equation 5-2 for low copper

CM and LV steels for capsules T14 and PB. The unalloyed VM steels are shown

as filled triangles ............................................................. 42

Figure 5-7 Acy for various V-series alloys with no copper irradiated in PB ............ ................ 43

vii
Figure 5-8 a) Comparison of NUREG matrix feature predictions with low copper French power

reactor surveillance data; b) plot showing scatter in Aca, in low copper steel

irradiations in this study and unexplained differences between CM and LV alloys .... 43

Figure6-1 VariationofcywithPTfora)CM5, 11, 18b)CM3, 11, 19c)CM12, 13,20 ............ 47

Figure 6-2 Variation of Acr, with y, (unirradiated) for a) high (0.42%) copper CM alloys,

b) intermediate (0.8%) nickel 0.22% copper alloys ................................................. 48

Figure 6-3 Variation of Aa, with c for irradiated intermediate nickel alloys ............. ................. 48

Figure 6-4 Variation of Aa with c for intermediate nickel CM and LV alloys in capsules T14

(a and b), T4 (c and d) and PB (e andf) .......................................................... 51

Figure 6-5 Variation of Ac with SR condition for a) CM3, b) CM5, c) CMII, d) CM12,

e) CM13, f) C?I16, g) CM18, h) CMI9, i) CM 20 ................................................... 53

Figure 6-6 Aa, -based NUREG model prediction of the variation in Cum with SR time for

the VSR data for a) CM] 1, b) CMI2, c) CMI8, d) CM 19, e) CM20; f) Comparison

of high copper CM]9 to two lower Cu steels ......................................................... 56

Figure 6-7 Aa, -based NUREG model prediction of the variation in Cum with stress relief

time for the PB data for CM12, CMI8, CM 19, CM20 .............................................. 57

Figure 6-8 Idealized variation of resistivity with content C. of solute x ................. .................... 60

Figure 6-9 Variation of resistivity with copper content for a range of alloys ............. ................ 61

Figure 6-10 Variation of resistivity with copper content for a) CM, b) LV and c) as-tempered

CM alloys ............................................................. 63

Figure 6-11 Variation of Seebeck coefficient with copper content .64

Figure 6-12 Variation of Seebeck coefficient with copper content for a) stress-relieved CM,

b) as-tempered CM and c) LV-series alloys .68

Figure 6-13 Cum measurements from various techniques for a) CMI I, b) CM19, c) LC .69

Figure 6-14 Effects of tr on CRP features as measured by SANS on CM19 from the PB

capsule .70

Figure 7-1 Comparison of Cur to Cum for high copper CM alloys from VSR .72

Figure 7-2 Comparison of Cum from VSR data to predictions of Equations 7-2 through 7-4 .... 73

Figure 7-3 Comparison of Cum for CMI9 as a function of tr .73

Figure A-I Variation of Cc with AT. The dashed line shows the average .83

Figure A-2 Comparison measured Ao, with values predicted from NUREG model for T4 . 83

Figure A-3 Variation of the difference between predicted and measured Ac, with nickel . 84

viii
LIST OF TABLES

Table Page

Table 3-1 CM-Series Alloy Compositions and Heat Treatments ................................................ 8

Table 3-2 Stress Relief Anneal Matrix .......................................................... 9

Table 3-3 LV-Series Alloy Compositions and Heat Treatments ................................................. 9

Table 3-4 Commercial Steels ......................................................... 10

Table 3-5 VM-Series Alloy Composition ......................................................... 11

Table 3-6 Specimen Loadings for Capsules T4 and T14 ......................................................... 15

Table 3-7 Capsule loading for VSR ......................................................... 16

Table 3-8 Capsule loading for PB ......................................................... 17

Table 3-9 Irradiation Conditions ......................................................... 19

Table 4-I Summary of Compositional Dependence of Hardening in High Copper Steels ........ 29

Table 4-2 Summary of Compositional Dependence of Hardening in Low Copper Steels ........ 32

Table 6-1 Estimated Cum for Intermediate Nickel High Copper CM Alloys in VSR Study ....... 50

Table 6-2 Estimated Cum for Intermediate Nickel High Copper CM Alloys in Various

Capsules ......................................................... 50

Table 6-3 Estimated Cum for High Copper CM Alloys in VSR Study ................... ................... 57

Table 6-4 Estimated Cum for High Copper CM Alloys in PB Study ................... .................... 57

Table 6-5 Averaged Cum Following Heat Treatment at -590-610C ....................................... 58

Table 6-6 FEGSTEM Estimates of Cu,, for CM12, CM19 and CM20 ................... ................... 59

Table 6-7 Least Square Fit Calibration of Equations 6-7 and 6-8 ....................................... ,.64

Table 6-8 Microanalytical and Afl Based Estimates of Cum for Typical As-tempered and

Stress-relieved Conditions ...................................... 67

ix
EXECUTIVE SUMMARY

Safe operation of reactor pressure vessels requires evaluation of irradiation embrittlement by neutrons

leaking from the core. Embrittlement is currently monitored by measuring changes in the energytemperature curves of Charpy V-notch specimens irradiated in reactor surveillance programs.

Embrittlement is characterized in terms of reductions in the Charpy upper shelf energy (AUSE) and

elevations of the temperature at 41J (AT). The latter is the focus of this report. Prescriptions for

evaluating AT (and AUSE) for a particular steel and vessel exposure condition are provided in US

NRC Regulatory Guide 1.99 Revision 2 (RG 1.99/2). However, RG 1.99/2 was based on a rather

small database, assembled from the literature several years earlier, and reflects the limited

understanding of embrittlement mechanisms at that time.

Over the intervening years, both fundamental understanding of embrittlement mechanisms and the

surveillance database have grown, along with a recognition that complex interactions between the

irradiation and metallurgical variables control AT. Thus the synthesis of various sources of

information is the key to reliable embrittlement predictions. Recently a new AT correlation model

was developed based on statistical fits to the power reactor embritdement database (PREDB), using

equations that were both developed and vetted using physical models and independent sources of

pertinent data. The NUREG/CR-6551 Model (sometimes known as the Eason-Wright-Odette Model)

has been extensively scrutinized by the nuclear industry and researchers around the world. The

ASTM Subcommittee El 0.02 has led the independent evaluation of this work, and has considered the

NUREG model as a candidate for adoption for AT predictions in draft standard E900. The NUREG

model, and its progeny, are also under consideration for adoption in a preposed revision to RG

1.99/2.

The NUREG model has proven to be rather robust in these evaluations. It represents a significant

statistical improvement over RG 1.99/2, and is based on a much better physical model of

embrittlement. However specific issues have been raised, and new questions continue to emerge

regarding details of the model. The results presented in this report represent part of a larger overall

effort to address and resolve these issues. The technical approach involves developing an

independent embrittlement database from controlled, single-variable experiments. High-resolution

experimental maps of the individual and interactive effects of metallurgical and environmental

variables on embrittlement are derived from irradiation and post-irradiation testing of very large

experimental matrices. These studies take advantage of the relationship between AT and increases in

yield stress (Aay), which can be measured using small tensile specimens. These studies achieve

precise control and characterization of the embrittlement variables. Irradiations are carried out in the

Irradiation Variable Facility (IVAR) at the University of Michigan Ford Research Reactor. he large

experimental hsy database under development, will be complemented by an extensive effort to

characterize the micro(nano)structural changes responsible for Acy and AT. The collective results

will be analyzed and used to develop quantitative, mechanism-based embrittlement models.

This report focuses on a subset of important questions that must be answered in establishing a

technical basis for any future revision to RG 1.99/2. In particular the following issues are addressed,

and to a large extent resolved, by the VAR data and analysis reported here. These advances include:

1. Quantitative independent validation of the general two component form of the NUREG model

comprised of copper-independent matrix features and copper-dependent copper rich precipitates

(CRPs) terms.

x
2. Quantitative independent validation of the very strong interaction between copper and nickel in

the NUREG model CRP contribution to AT. The specific thermodynamic basis for this interaction

is described, along with an example from a larger supporting microstructural characterization

database.

3. Validation of the inclusion of phosphorous in the NUREG model, and strong support for its

approximate treatment in the matrix feature contribution to AT.

4. Validation of a maximum effective matrix copper level of around 0.3% following tempering and

stress relief heat treatments as found in the NUREG model. Strong support is also presented for

even lower maximum effective matrix copper levels of about 0.25% in low-to-intermediate nickel

steels, as well as evidence for corresponding levels in excess of 0.3% in high nickel steels. The

role of stress relief time and temperature on effective matrix copper levels is also elucidated and

represented in terms of a simple pre-precipitation model.

In addition, the database and analysis in this report also provides additional insight into several other

issues, which are further from closure. Resolution of these issues could lead to significant further

improvements in embrittlement forecasting. They include:

I. Possible sources of product form variability and data scatter in the CRP term. These include

embrittlement contributions from elements not explicitly accounted for in the NUREG model, like

manganese (interacting with nickel and copper), and effects of microstructural variations on the

fluence dependence of Acy and AT.

2. An unanticipated effect of flux and flux-composition interactions on the fluence dependence of

the CRP contribution to A;y and AT.

3. Effects of the unirradiated constitutive and Charpy properties on: a) the A&CF produced by a

specified embrittlement microstructure; and b) the relationship between A(y and AT. This work

has also identified new mechanisms that influence the effects the heat treatment on the

unirradiated microstructure and properties, hence, also on AGy and AT.

4. Possible sources of product form variability and data scatter in the matrix feature term, including

an increase in Acy with manganese and nickel.

5. A possible interaction reducing the effect of phosphorus at higher copper.

All of these issues, and several others, are the subject of ongoing research in the UCSB program.

xi
ACKNOWLEDGMENTS

The authors appreciate the advice and encouragement of Al Taboada, and Mike Vassilaros our

former project managers at the U. S. Nuclear Regulatory Commission and Carolyn Fairbanks our

current project manager. Al Taboada contributed enormously to the conceptual design of our

program and Mike Vassilaros was instrumental in tuming these concepts into realities. Carolyn Fairbanks has helped us in the completion of this part of the work and has provided sustained support for our research. The advice and support from other U.S. NRC staff are also appreciated. The staff

and students in our group at the University of California Santa Barbara, particularly Chris Cowan, have made important contributions to various parts of this research. The support of the collaborators

at ORNL, particularly Roger Stoller, Randy Nanstad, Mikhail Sokolov and Dennis Heatherly, as well

as the staff at the Ford Nuclear Reactor irradiation facility, particularly Phil Simpson, are greatly appreciated. We would also like thank the staff at AEA Technology, especially Amanada Kenway- Jackson, Colin English and Will Phythian, for their role in procuring alloys and performing FEGSTEM studies. The work was performed under U.S. NRC Contract 04-94-049.

xii
NOMENCLATURE AND SYMBOLS

SYMBOLS

Ai intercept of Acry sensitivity to ith specie

Bi slope of Acy sensitivity to ith specie

Cc ratio of AT to Aay

CF chemistry factor

C1 concentration of ith specie

Cubk bulk copper concentration

Cue effective copper concentration

Cum matrix copper concentration

Esr pre-precipitation effective activation energy

F neutron scattering factor

fi volume fraction of ith specie

f0 flux factor

ki resistivity coefficient of ith specie

k,r pre-precipitation rate coefficient

Ni number density of ith feature

Prt heat treatment temperature-time factor

q neutron scattering vector

r radius of ith feature

rip radius of ith feature at peak strength

rm mean radius of scattering feature

S Seebeck coefficient

Si Seebeck coefficient from ith contribution

tht heat treatment time

tsr stress relief time

Tht heat treatment temperature

AT 41J indexed Charpy transition temperature shift

AT3 shift due to ith contribution

Vj Volume of ith feature

0 scattering distribution fit parameter

x NUREG copper factor

* flux

fluence

Os neutron scattering angle relative to magnetic field

Ysr numerical constant for pre-precipitation rates

Ki Seebeck coefficient sensitivity to ith species

Ai strength of ith obstacle

p Resistivity

Pi contribution to resistivity of ith source

A p neutron scattering contrast

d/dSd SANS scattering intensity

a,i strength contribution from ith source

<su unirradiated obstacle yield strength contribution

ay yield strength

AaY change in yield strength

e superposition parameter

ASAXS Anomalous Small Angle X-ray Scattering

CRP Copper rich precipitate

xiii
FEGSTEM Field Emission Gun Scanning Transmission Electron

Microscope

FNR Ford Nuclear Reactor

HF High Flux

HT Heat Treatment

IVAR Irradiation Variables Facility IF Intermediate Flux

LF Low Flux

PIA Post-Irradiation Annealing SAW Submerged Arc Weld

SR Stress Relief

SSR Standard Stress Relief

SANS Small Angle Neutron Scattering TEP Thermoelectric Power

xiv
1 BACKGROUND AND INTRODUCTION

Accurate prediction of neutron irradiation

embrittlement of reactor pressure vessels is a key

component in structural integrity assessments for

both normal operation and during accident

transients [USNRC, 19861. Embrittlement is

currently empirically characterized in reactor

surveillance programs by measuring changes in

the Charpy V-notch transition energytemperature curves of representative vessel steels.

Data from surveillance programs are archived in

the Power Reactor Engineering Data Base

(PREDB) [Stallman et. al, 1994], compiled at

Oak Ridge National Laboratory. Charpy data

are usually represented as temperature shifts

indexed at 41J (AT) and reductions in the upper

shelf energy (USE). Regulatory procedures for

predicting embrittlement are described in US

NRC Regulatory Guide 1.99 Revision 2 (RG

1.99/2) published in 1988 [USNRC, 1988].

However, the AUSE and AT in RG 1.99/2 were

based on a rather small database, assembled

from the literature several years earlier and

reflect the limited understanding of

embrittlement mechanisms at that time.

Over recent years both fundamental

understanding of embrittlement mechanisms and

the surveillance database have grown, along with

a recognition that complex interactions between

the irradiation and metallurgical variables

control AT [Odette and Lucas, 1989, 1996,

1997, 1998; Odette, 1998; Buswell and Jones,

1993; Fisher and Buswell, 1987; Stoller, 1996;

Lott and Freyer; 1996, Bolton, et al, 1996;

McElroy and Lowe, 1996; English et al, 1997].

The irradiation variables include temperature

and exposure time, neutron flux, fluence and

spectrum. Metallurgical variables include

composition and processing history, which

combine to mediate the start-of-life alloy

microstructure and microchemistry. Elements

that are known, or thought, to influence AT

include copper, nickel, phosphorous, manganese,

and perhaps, silicon and nitrogen.

Corresponding processing and microstructural

variables are more difficult to parameterize, but

clearly include product form and temperingstress relief heat treatment. A myriad of other

factors, that mediate the start-of-life condition of

a steel, as represented by grain and subgrain

structures, dislocation densities and

arrangements, as well as carbide and other

second phase distributions, also play a role.

These microstructural factors are manifested in

terms of both the effect of the start-of-life

properties on embrittlement as well as their

effect on fine scale changes in the

microstructures caused by irradiation that alter

these properties.

An example of such complex metallurgical

effects, which are the focus of this report, is

provided by the interaction between copper,

nickel, manganese and stress-relief heat

treatment. Irradiation hardening, which is the

primary cause of embrittlement, increases with

increasing nickel and manganese content.

However, the effect of these elements acting in

tandem, is synergistic in steels containing a

significant amount of copper. Further at high

levels, the effective copper content is influenced

by the heat treatment because of preprecipitation of this element. The amount of

copper pre-precipitation appears to be

influenced by the alloy nickel content. Both the

heat treatment and composition in turn influence

the start-of-life alloy strength, which also affects

the irradiation hardening. Additional

combinations of these variables may influence

AT, but it is sufficient to conclude that such

interactions and synergisms can only be reliably

understood and accounted for based on insight

provided by combinations of careful, single

variable experiments and modeling. However, it

is also equally clear that such complexity, and

limitations in understanding, demand that

predictive models be derived from the most

realistic database available, currently represented

by the PREDB.

Thus the synthesis of various sources of

information is the key to reliable embrittlement

predictions. Recently a major advance in

implementing this paradigm was reported in

I
NUREGICR-6551 [Eason et al, 1988]. which

featured the following key elements in deriving

AT predictions.

1. The AT predictions were based on non-linear

least squares fits of correlation equations to a

carefully scrubbed, frozen version of the

PREDB.

2. The correlation equations were developed

based on understanding of key embrittlement

mechanisms.

3. Selection from among a large number of

statistically similar calibrated correlation

equations was based on both mechanistic

considerations and consistency with

independent sources of data, largely derived

from test reactor studies.

4. Both the limits of the correlation equations,

and the likelihood they would continue to be

refined, were recognized. Thus unless there

was a combination of mechanistic and

statistical significance dictating otherwise, the

correlation equations were kept as simple and

with as few degrees of freedom as possible.

The attendant compromises included use of

correlation equation forms that were

consistent with the demands of nonlinear data

fitting methods.

While the NUREG/CR-655I equations are fairly

robust and reliable, more importantly the overall

methodology established a framework for

continuing improvements in embrittlement

predictions and a basis to assess important gaps

in understanding. Significant issues that have

been identified include:

I. What are the sources of embrittlement

variability associated with product form, or

even vessel vendor, and the corresponding

underlying microstructural basis? Note this is

also an important issue related to other

sources of material variability, like weld

practice, heat affected zones, through

thickness variation of properties and, very

importantly, treatment of the relation of

surveillance materials to those in the vessel

itself, or the issue of surrogate materials.

2. What are the sources of large scatter and

differences with other database trends in the

copper-independent, so-called matrix feature

term?

3. What is the effective upper cut-off in copper

content; and how is this affected by other

variables, such as nickel and heat treatment,

and how is it best modeled in the correlation

equations?

4. What is the effect of phosphorous and how

can it be best modeled?

5. What are the effects of flux and time-attemperature? How are these factors

influenced by other variables and how are

they best treated in the correlation equations?

6. What variables, terms and mechanisms could

be missing from the existing correlation

equations? This includes interactions between

existing variables as well as variables that are

currently not accounted for.

The latter point deserves a brief elaboration.

Statistical methods, even using simple, nonphysical algebraic correlation equations,

generally can reasonably fit a database within

expected scatter and considering other sources

of uncertainties. However, various terms in such

models may be entirely non-physical, simply

acting as surrogates for real physical effects. Put

simply, the fitting model will force itself to work

as well as it can independent of the reality of

how it does it. At least to some extent, this

involves replacing something that is missing with

something that simply works (or, to say it

simply, pushing something in one place pops

something out in another place). Correlation

equations with a more solid physical basis suffer

similar limitations if they are not complete and

do not start with a balance of terms that are

physically based. Non-physical correlations

cannot be extrapolated and even fail within in

apparently valid regime when variable surrogacy

2
breaks down. Clearly, avoiding such traps

requires developing independent sources of data

and mechanistic understanding, which-is the

overarching goal of the work partially described

in this report.

3
2 OBJECTIVES, STRATEGY, FOCUS AND

ORGANIZATION OF THE REPORT

The UCSB embrittlement research program has

a number of objectives ranging from early

warnings of possible technical surprises, to

improving a broad array of integrity assessment

methods, such as the tasks in support of the

master curve method [ASTM E1921-97]. The

activities pertinent to this report relate

specifically to the issues listed at the end of the

previous section, viz. - developing an

independent database involving controlled,

single-variable experiments and mechanistic

models. This effort involves:

I. Developing high resolution experimental

embrittlement maps of the individual and

interactive effects of metallurgical and

environmental variables. This task involves

irradiation and post-irradiation testing of a

very large matrix of alloy/alloy conditionflux-fluence-temperature combinations with

precise control and characterization of the

embrittlement variables. The primary facility

is the Irradiation Variable Facility (IVAR) at

the University of Michigan Ford Research

Reactor.

2. Detailed pre and post-irradiation (as well as

annealing-reirradiation) microstructural

studies and focused mechanism experiments

in support of physical model development.

3. Development of detailed multiscale

embrittlement models that quantitatively treat

all key variables and variable interactions.

4. Synthesis of these results with other pertinent

information and ultimate application to

improved embrittlement correlation

equations fit to the PREDB.

A key element of the strategy to meet the first

objective is the use of yield stress changes (Acr,)

as a measure of embrittlement (AT). The a,;-

AT relation is well established [Odette et. a,

1985; Odette and Lucas, 1989]. but will be

further developed and quantified as part of this

work. The use of Aa, as the key property

enables establishing the embritttement maps

using small tensile specimens coupled with semiautomated testing. As a result very large

experimental matrices are practical. The use of

Aasy also has other advantages, such as generally

high precision and physical relationships to

other measures of embrittlement, such as shifts

in fracture toughness-temperature master curves

[Odette and He, 2000, in press]. The results

reported here are a small part of the much larger

overall study and focus on the specific effects of

compositional and heat treatment variations on

AGry

A wide variety of techniques are being used, in

combination, for microstructural

characterization and other mechanism studies.

Methods include small angle neutron and

anomalous x-ray scattering, atom probe,

transmission electron microscopy, post

irradiation annealing, electrical resistively and

the Seebeck coefficient. These studies are

ongoing and only limited, and in some cases

preliminary, results on small angle neutron

scattering, transmission electron microscopy,

electrical resistively and the Seebeck coefficient

are presented in this report.

Models of the key sub-processes mediating

embrittlement have been developed and

extensively used to improve the understanding

of the underlying mechanisms as well as to

guide and verify correlation model

development. Integration of these components

into a comprehensive quantitative embrittlement

model is underway. The results of modeling

pertinent to interpreting the experimental trends

are summarized briefly in this report, with

further details presented elsewhere [Odette and

Lucas, 1997, 1998; Odette, 1998] or in future

publications and reports.

The report is organized as follows. A description

of the steels examined in this study, the

4
experimental test methods and procedures for

the data analysis and evaluation are described in

Section 3. The Acy, for two sets (CM and LV) of

split melt UCSB alloys and a range of steels

acquired from other programs irradiated to

medium fluence between 0.48 and xO23nm 2

(E > I MeV) are presented in Section 4. Only a

limited number of medium fluence capsules

tested to date contain complete, or nearly

complete, matrices of the steels examined in this

program. These data are complemented by the

results for a more limited number of key UCSB

alloys contained in other medium fluence IVAR

capsules. An analysis and evaluation of these

results is presented in Section 5, by comparing

the AuY data to predictions of the NUREG/CR6551 model. Section 6 describes the effects of

systematic variations in stress relief time and

temperature on Ay; for a subset of the UCSB

CM alloys. This section includes the results of a

variety of characterization techniques used to

evaluate the matrix content of dissolved copper,

as well as estimates based on the A;,

measurements themselves. These results are

analyzed in Section 7 to assess the mechanisms

giving rise to stress relief effects, with particular

emphasis on maximum copper limits set by preprecipitation. Section 8 summarizes the overall

results and presents the main conclusions

derived from this study.

5
3 MATERIALS, EXPERIMENTAL METHODS AND DATA

ANALYSIS AND EVALUATION PROCEDURES

3.1 Alloys and Specimens

A large set of alloys was investigated in this

study. The alloys are classified in four general

categories:

I. The compositions of a large set of complex

A533B-type split melt steels (CM-series) are

shown in Table 3-1. A total of 31 variants

around a base composition were used to

evaluate the effects of both: a) combinations

of Cu (0.0 to 0.8%1), Ni (0.0 to 1.6%), Mn

(O to 1.6%) and P (0.005 to 0.040%)

contents; and b) single variable modifications

of Mo, N, C, B, Al and As/Sn/Sb contents. All

31 alloys contained about 0.005%Al and

0.25%Si. The alloys were fabricated in

collaboration with AEA Technology,

Harwell. Chemistries were determined by the

manufacturer, and spot checked for several

alloys upon receipt by a combination of

atomic absorption and interstitial element

analysis. Further verification of chemistries

is planned. For two of the irradiations, T4

and T14 (described below), the alloys

received a base heat treatment consisting of

an austenitization at 900°C for 0.5h, followed

by a salt bath quench at 450°C for 10min, an

air cool, tempering at 660°C for 4h: air cool

and a stress relief anneal at 607'C for 24 h,

followed by a slow cool at 8'C/h to 300*C,

and a subsequent air cool. This is referred to

as the standard stress relief (SSR) heat

treatment. The SSR yielded prior austenite

grain sizes of about 50±10 pm and

microstructures ranging from tempered

bainite (most CM alloys) to mixed tempered

ferrite-bainite. A complete microstructural

description for all the alloys will be provided

in a future report.

For one of the irradiations, VSR (described

below), nine of the alloys received altemate

I Compositions are given in weight per cent, unless stated

ortherwise

stress relief anneals; the alloys and the stress

relief anneal matrix are shown in Table 3-2.

Finally, for a piggy-back irradiation, PB

(described below), the 31 alloys were

irradiated in the as-tempered condition. In

addition, several of the alloys received the

following alternate heat treatments:

CM5: as-tempered plus aged 480 for

100 h, air cooled

CM8: salt bath quenched at 4000C after

austenitization, then tempered

CM12: as-tempered plus stress relieved

600'C 8 h, air cooled

CM18: as-tempered plus stress relieved

6000C 40h, air cooled

CMI9: as-tempered plus stress relieved

600'C 8, 40 and 80 h, air cooled

CM 19: salt bath quenched at 500'C after

austenitization, then tempered

CM20: as-tempered plus stress relieved

600'C 40h, air cooled

CM20: salt bath quenched at 500C after

austenitization, then tempered

CM23: salt bath quenched at 400C after

austenitization, then tempered

CM26: as-tempered plus aged 480' for

100 h, air cooled

2. The compositions and heat treatment for a

set of eight complex commercial type

bainitic model steels (LV-series) with

systematic variations in copper and nickel are

shown in Table 3-3. These steels have been

irradiated in previous programs at a variety

6
of conditions, primarily around 300°C,. and

are described in more detail elsewhere

[Odette and Lucas, 1989]. They have

microstructures and unirradiated properties

very similar to those in the CM-series.

3. The compositions and heat treatments for a

set of 13 commercial steels are shown in

Table 3-4. The commercial steel series

consists of: ) three welds (A, B, C) obtained

from Babcock and Wilcox, with a range of

copper contents from low (0.06) to high

(0.28), 2) a set of 5 welds (62W-73W)

prepared for and used in the HSSI program;

3) plate 02 of the A533B correlation monitor

material prepared for the HSST program; 4)

JRQ plate material developed for an IAEA

coordinated research program; and 5) a

Linde 0091 weld (EPRI C) prepared for and

used in previous EPRI-sponsored research.

Both baseline and irradiated data have been

obtained for all these steels and are largely

reported in the literature. The heat

treatments and compositions reported in

Table 3-4 were taken from the literature or

documentation supplied with the plate (e.g.,

JRQ).

4. The compositions and heat treatment for a set

of 18 simple split melt model iron and steel

alloys (VM-series) with systematic variations

in Cu, C, and N are shown in Table 3-5.

These alloys were also fabricated in

collaboration with AEA Technology,

Harwell. Chemistries were determined by the

manufacturer, and spot checked for several

alloys upon receipt by a combination of

atomic absorption and interstitial element

analysis. Further verification of chemistries

is planned. The microstructures of these

alloys are generally characterized by a wide

distribution of ferrite grain sizes (in some

cases duplex and/or with processing texture).

A complete microstructural description for

all the alloys will be provided in a future

report. Rapid quenchingwas carried out to

maintain copper in solution. These alloys

were used in this study to calibrate resistivity

and Seebeck coefficients as a function of

copper concentration as discussed in Section

6. In addition, several of the alloys were

irradiated in the PB and several other IVAR

capsules. However, only a limited number

have been tested and are reported here.

Sheet tensile specimens with a gage section 9

mm x 2 mm x 0.5 mm were prepared by

precision die punching heat treated coupons

lapped to 0.5±0.005 mm thick. The quality of

the die was monitored by punching and tensile

testing a variety of calibration metals after about

every 500 specimens had been punched.

Baseline tensile tests on unirradiated material

indicated some variability in properties in several

of the alloys. Hence, to reduce scatter in the

subsequent yield stress change measurements,

the end tabs of selected tensile specimens were

pre-indented to obtain Vickers microhardness

numbers. An average of 4 indentations were

made on the tab ends of the tensile specimens.

The microhardness values were used to help

identify which baseline values would be used for

the irradiated data to evaluate yield stress

change. This was complemented by a system to

keep track of the location in the billet from

which specimens were obtained, so that in high

variability cases, data from specimens from

similar regions could be used to evaluate yield

stress changes. Wafers comprised of the

interstitial pieces between tensile specimen

punch-outs were also included in some of the

irradiations for the purpose of microhardness

and/or microstructural characterization. Small

angle neutron scattering (SANS) specimens

1.135 cm x 1.2 cm x 2 mm were also machined

from selected materials and included in the

irradiations.

3.2 Irradiations

Results for four irradiations, designated T4, T14,

VSR, and PB are the primary focus of this

report. The specimens and materials included in

these irradiations are listed in Tables 3-6

through 3-8. The T4 and T14 capsules

contained tensile, wafer and SANS specimens of

all of the materials. The VSR capsule contained

specimens from the CM alloys subjected to the

7
Table 3-1. CM-Series Alloy Compositions and Heat Treatments

COMPOSITION (weight per cent)

Alloy Cu Ni Mn Cr Mo P N C Si S As/Sb Al B

(ppm) ISn (ppm)

CMI 0.01 0.01 1.67 0.04 0.56 0.003 <50 0.13 0.15 0.004 0.005 0.025 <1

CM2 0.01 0.01 1.65 0.04 0.56 0.041 <50 0.14 0.16 0.004 0.005 0.022 <1

CM3 0.02 0.85 1.60 0.00 0.49 0.006 <50 0.13 0.16 0.000 0.005 0.002 <1

CM4 0.02 0.86 1.53 0.05 055 0.031 <50 0.16 0.16 0.003 0.005 0.006 <1

CMS 0.02 0.86 1.61 0.04 0.53 0.050 dO 0.15 0.16 0.000 0.005 0.005 <1

CM6 0.02 1.68 1.50 0.05 0.54 0.007 <50 0.15 0.17 0.003 0.005 0.006 <1

CM7 0.00 1.70 1.55 0.05 0.56 0.047 <50 0.16 0.17 0.003 0.005 0.003 <1

CM8 0.01 0.86 0.01 0.04 0.55 0.004 <50 0.13 0.14 0.002 0.005 0.026 <1

CM9 0.01 0.86 0.85 0.04 0.55 0.003 <50 0.15 0.15 0.003 0.005 0.013 <1

CMIO 0.02 0.88 1.66 0.05 0.53 0.008 <50 0.16 0.17 0.004 0.005 0.003 <1

CMI1 0.34 0.85 1.64 0.02 0.53 0.006 <50 0.15 0.18 0.003 0.005 0.003 <1

CM12 0.86 0.84 1.65 0.02 0.51 0.006 <50 0.15 0.17 0.003 0.005 0.002 <1

CM13 0.11 0.83 1.61 0.00 0.51 0.004 <50 0.15 0.16 0.000 0.005 0.002 <1

CM14 0.11 0.83 1.62 0.00 0.52 0.040 <5O 0.16 0.17 0.000 0.005 0.003 <1

CM15 0.22 0.02 1.59 0.02 058 0.002 <50 0.14 0.15 0.003 0.005 0.019 <1

CM16 0.22 0.82 1.58 0.00 0.51 0.004 <50 0.16 0.25 0.000 0.005 0.003 <1

CM17 0.22 1.59 1.54 0.00 0.50 0.004 <50 0.16 0.25 0.000 0.005 0.003 <1

CMI8 OA3 0.02 1.70 0.02 0.56 0.002 <50 0.14 0.15 0.003 0.005 0.017 <1

CM19 0.42 0.85 1.63 0.01 0.51 0.005 <50 0.16 0.16 0.003 0.005 0.003 <1

CM20 0.43 1.69 1.63 0.02 0.50 0.006 <50 0.16 0.16 0.003 0.005 0.003 <1

CM21 0.42 0.84 0.01 0.02 058 0.002 <50 0.14 0.14 0.003 0.005 0.015 <1

CM22 0.42 0.84 0.84 0.02 0.56 0.002 <50 0.14 0.14 0.003 0.005 0.010 <1

CM23 0.02 0.83 1.62 0.04 0.55 0.002 <50 0.03 0.15 0.003 0.005 0.015 <1

CM24 0.02 0.87 1.65 0.05 0.52 0.010 <50 0.34 0.15 0.003 0.005 0.004 <1

CM25 0.01 0.87 1.53 0.05 0.52 0.003 200 0.14 0.17 0.002 0.005 0.018 <1

CM26 0.01 0.87 1.66 0.05 0.52 0.006 <50 0.16 0.17 0.003 0.020 0.003 <1

CM27 0.02 0.84 1.60 0.05 0.51 0.002 <50 0.16 0.16 0.003 0.005 0.002 10

CM28 0.42 0.84 1.60 0.02 0.51 0.002 <50 0.16 0.17 0.003 0.005 0.002 10

.CM29 0.21 0.02 1.68 0.02 0.02 0.002 <50 0.14 0.14 0.003 0.005 0.015 <1

CM30 0.22 0.86 1.64 0.42 0.50 0.006 <50 0.16 0.16 0.003 0.005 0.003 <1

CM31 0.01 0.80 1.65 0.05 0.51 0.006 <50 0.16 0.17 0.003 0.005 0.034 <1

8
Table 3-2. Stress Relief Anneal Matrix

Alloys: CM3, CM 5, CMI 1, CM12, CM13, CM16,

CM18, CMI9, CM20

Slow Cool Matrix: Stress relieved at the following

times and temperatures followed by a program cool at

8'C/h to 300'C followed by an air cool

Temperatures (C) Times (h)

590

607

624

641

as-tempered

24,48, 96

12,24,48,96

12,24,48

6,12,24

Variable Cool Matrix: Stress relieve at 607'C for 24h,

air cool

Table 3-3. LV-Series Alloy Compositions and Heat Treatments

Composition (weight percent)tt

Code C Cu Ni Mn Si

LA 0.14 0.40 0.00 1.37 0.22

LB 0.14 0.40 0.18 1.35 0.22

LC 0.14 0.41 0.86 1.44 0.23

LD 0.19 0.38 1.25 1.38 0.23

LG 0.16 0.00 0.74 1.37 0.22

LH 0.16 0.11 0.74 1.39 0.24

LI 0.16 0.20 0.74 1.37 0.24

Li 0.16 OA2 0.81 1.34 0.13

L( 0.13 0.80 0.81 1.13 0.13

LO 0.14 0.41 0.86 1.44 0.23

tt Alloys contained P <0.005, S 5 0.015, Cr 5 0.085, Mo - 0.55; they were austenitized

900°C/lh; air cooled; tempered 664°C/4h; air cooled; stress relieved 600°C/40h; furnace

cooled to 300°C; air cooled. With the exception of LO, which was not stress relieved after

tempering

9
Table 3-4. Commercial Steels

COMPOSITION (weight per cent)

Code C Mn P S Si Cr Ni Mo Cu V HT*

A 0.08 1.69 0.014 0.013 0.45 0.14 0.63 0.40 0.21 - I

B 0.09 1.63 0.018 0.009 0.54 0.10 0.69 0.40 0.28 - 2

C 0.08 1.30 0.009 0.010 0.37 0.08 0.62 0.31 0.06 -- 3

62W 0.08 1.61 0.020 0.007 0.59 0.12 0.60 0.39 0.23 0.01 4

63W 0.10 1.65 0.016 0.011 0.63 0.10 0.69 0.43 0.30 0.01 5

65W 0.08 1.45 0.015 0.015 0.48 0.09 0.60 0.39 0.22 0.006 6

67W 0.08 1.44 0.011 0.012 0.50 0.09 0.69 0.39 0.27 0.007 7

73W 0.10 1.56 0.005 0.005 0.45 0.25 0.60 0.58 0.31 - 8

Midland 0.08 1.61 0.017 0.007 0.62 0.10 0.57 0.41 0.27 0.004 9

EPRI C 0.16 1.55 0.005 0.009 0.17 0.04 0.60 0.44 0.35 10

A302B 0.21 1.20 0.015 0.017 0.28 0.24 0.20 0.60 0.14 0.004 11

HSST02 0.23 1.55 0.009 0.014 0.20 0.04 0.67 0.53 0.14 0.003 12

JRQ 0.18 1.40 0.019 0.004 0.25 0.12 0.82 0.50 0.14 0.003 13

*Heat Treatments

1. Post weld heat treatment (PWHT) 607'C for 15 h, furnace cool

2. PWHT, 607'C for 23 h, furnace cool

3. PWHT, 607C for 13.5 h, furnace cool

4. Submerged arc wild (SAW): stress relieved (SR) 8 cycles of 6 h at 593-621 C

5. SAW, SR 48 h at 593-621 C

6. SAW, SR 80 h at 593-621 C

7. Not available

8. PWHT 607'C, 40h

9. PWHT 607*C, 22.5h

10. SAW, PWHT 620C, 50h

11. Normalized and tempered; tempered for 6.5 h at each of 926-C, 885-C, 648'C, and 607-C, WQ

12. Austenitized 871 C, water quench; tempered 663C, 4 h; FC; stress relieved 607C, 40h, FC

13. Normalized @ 900T, quenched at 880-C, tempered at 665C for 12 h, SR at 620C 40h

10
Table 3-5 VM-Series Alloy Compositions

Composition (Weight per cent)*

Alloy Cu Mn N C Ti

(appm)

VA 0.000 0.00 5 0.00 0.000

VB 0.020 1.01 40 0.01 0.002

VC 0.020 1.03 30 0.17 0.004

VD 0.875 1.03 10 0.00 0.000

VE 0.910 1.08 20 0.16 0.010

VG 0.510 0.06 20 0.01 0.002

VH 0.910 0.01 20 0.01 0.010

VI 0.510 0.05 10 0.17 0.003

VJ 0.890 0.02 10 0.17 0.005

VK 0.020 0.02 100 0.01 0.001

VL 0.010 0.01 100 0.00 0.300

VM 0.510 0.01 120 0.01 0.010

VN 0.875 0.00 110 0.00 0.000

VO 0.910 0.00 110 0.16 0.000

VP 0.900 0.01 110 0.00 0.300

VR 0.010 1.06 100 0.01 0.010

VS 0.920 1.00 110 0.00 0.002

VT 0.880 1.00 90 0.00 0.260

*Solution treat 775C, 17h; quench in salt bath at 450*C, 3 minutes, air cool

11
variable stress relief series described above.

The PB capsule contained specimens for the

LV-series and CM-series. As described

previously, for this irradiation the CM alloys

were primarily in the as-tempered condition;

however, selected alloys were also irradiated in

several alternative heat treatment conditions.

For the T4, T14 and VSR irradiations,

specimens were loaded into aluminum boxes

2.54cm x 2.54cm x lcm deep. Once loaded,

the specimens were shimmed with aluminum

foil, and an aluminum cover plate was screwed

on. These capsules were machined to final

tolerance and shipped to the University of

Michigan for irradiation in the IVAR

(Irradiation VARiables) facility.

IVAR was collaboratively designed by UCSB

and ORNL, and it was fabricated and is

operated by ORNL. It consists of a sealed

container incorporating 50 electrical heaters

and has 49 thermocouples to monitor

temperatures. The entire facility is enclosed in

a boral shield to reduce activation from

thermal neutrons. Two removable specimen

baskets contain the irradiation capsules

described above. The facility has two separate

sections referred to as the high flux (HF) and

the intermediate flux/low flux (IFILF) sections.

The HF portion of the facility consists of a

removable specimen basket, which can contain

2 capsules at each of 2 different temperatures

(nominally 270 and 310'C) and 14 capsules at

a third temperature (nominally 290'C). The

IF/LF section consists of a removable basket

which can contain 9 capsules and one half

capsule at each of 2 different temperatures

(nominally 270 and 310'C) and 18 capsules

and 2 half capsules at a third temperature

(nominally 2900C). The specimen baskets

with their sliding cover plate are shown in

Figure 3-1 and a schematic diagram of the

irradiation facility is shown in Figure 3-2.

The Ford Nuclear Reactor (FNR) is a 2 MW

pool-type reactor located on the campus of the

University of Michigan in Ann Arbor,

Michigan. The reactor nominally operates on

a fixed cycle consisting of 10 days of

operation at full power, followed by a 4-day

maintenance shutdown. Experimental

facilities are located in a grid assembly located

on the south and east faces of the reactor. The

IVAR facility, and two companion ORNL

facilities, are located on a movable carriage at

the southeast corner of the reactor. The fully

loaded IVAR facility, including dummy

blocks, is brought to temperature in a retracted

position. The facility is then moved up against

the reactor face at full power. The HF zone

sits closest to and the LF zone furthest from

the reactor face. At the end of an irradiation

cycle, the facility is moved to the retracted

position, away from the reactor face. When a

capsule(s) reaches its target fluence, the basket

containing it is loaded into a shielded transfer

cask. The HF and IF/LF baskets can be

removed independently. The basket(s) is

transferred to a hot cell in the transfer cask

where the capsule(s) is removed and replaced.

The basket(s) is then returned to the IVAR

facility using the transfer cask. Hence, the

desired irradiation temperature, flux and

fluence is achieved by locating a capsule at the

appropriate site in the facility and exposing it

for the requisite time. Estimated uncertainties

in the irradiation temperature are 5'C.

Prior to its installation, the flux in the IVAR

location was mapped by a multiple foil

activation experiment [Remec, 19981. During

the first cycle of IVAR operation 16 additional

sets of Fe and Ni wires and 7 multiple foil sets

were located throughout the IVAR baskets and

subsequently removed and counted after the

first cycle. The fluxes reported [Remec, 1997]

were in reasonable agreement with the initial

map, although there appeared to be a slight

reduction in the higb flux positions. In

addition, every capsule that has been irradiated

in IVAR has included an Fe and Ni wire pair.

Nine of these have been counted from 6

locations. The activity measurements were

carried out by J. Adams of the Neutron

Interactions and Dosimetry Group at NIST in

Gaithersburg, MD. Analysis of these data

12
IF/LF Basket

-Specimen

Packets

Figure 3-1 Specimen Baskets in the IVAR Facility

13

'HF Basket

Cover
,Top Plug

1My/

Instrumentation

"on

Singl-Wall

Containment

-Transition

29

Zo

Double-Wall

Containment

High-Flux (HF)

- Region

DOC.

no

310C,

Zone

2700C

Zone

Intermediate-Flux (F) I -

Low-Ftux LF) Region

"o ;20 n.

0.5 In,

Hall Subcapsule

(4 Used)

Mounting

Block

Covers Removed to

Show Subcapsules

iadiation Facility

Figure 3-2 Schematic Design of the IVAR Irradiation Facility

14
Table 3-6. Specimen Loadings for Capsules T4 and T14

material T4 T14

tensile SANS wafer tensile SANS

ORNL Midland Weld

ORNL 73 Weld

ORNL A302b

ORNL HSST02 plate

B.W. A508 plate

B.W. A weld

B.W. B weld

B.W. C weld

B.W. 62 weld

B.W. 63 weld

B.W. 65 weld

B.W. 67 weld

Rolls Royce WV

Rolls Royce WG

Rolls Royce WP

EPRI C weld

JRQ

CMI

CM2

CM3

CM4

CM5

CM6

CM7

CM8

CM9

CMIO

CMII

CM12

CM13

CM14

CM15

CM16

CM17

CMi

CM19

CM2o

CM21

CM22

CM23

CM24

CM25

CM26

CM27

CM2S

CM29

CM30

CM31

LA

LB

LC

LD

LG

LH

U

Ll

LK

LO

3 2

3 1

3 2

I

3 1

3 1

3 1

3 1

3 2

3 1

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

4 1 1

4 1

4 1

3

3

4

3

4

4

4

4

4

3

3

3

3

3

3

3

3

3

3

15

I

I

I

I

I

I

I

I
Table 3-7. Capsule loading for VSR

Stress Relief time - - Alloy - - - -

And temperature CM3 CM5 CMII CM12 CM13 CM16 CM18 CM19 CM20

590'C 24h 2t* 2t 2t, Is 2t 2t 2t 2t 2t 2t

1w 1w Iw 1w 1w 1w 1w 1w 1w

590C 48h 2t 2t 2t 2t 2t 2t 2t 2t 2t

5900C 96h 2t 2t 2t 2t 2t 2t 2t 2t, Is 2t

1w Iw 1w 1w Iw 1w Iw 1w 1w

607'C 12h 2t 2t 2t 2t 2t 2t 2t 2t, Is 2t

Iw Iw Iw Iw Iw Iw Iw Iw Iw

6070C 24h 2t 2t 2t, Is 2t 2t 2t 2t, Is 2t, Is 2t, Is

607C 48h 2t 2t 2t 2t 2t 2t 2t 2t 2t

607'C 96h 2t 2t 2t, Is 2t 2t 2t 2t 2t, Is 2t

1w 1w 1w 1w 1w 1w 1w 1w 1w

624 C 12h 2t 2t 2t 2t 2t 2t 2t 2t 2t

624 C 24h 2t 2t 2t, Is 2t 2t 2t 2t 2t, Is 2t

624 C 48h 2t 2t 2t 2t 2t 2t 2t 2t 2t

1w 1w lw Iw 1w 1w 1w 1w 1w

641'C 6h 2t 2t 2t 2t 2t 2t 2t 2t 2t

1w 1w 1w 1w 1w 1w 1w 1w lw

641 C 12h 2t 2t 2t 2t 2t 2t 2t 2t, Is 2t

641 C 24h 2t 2t 2t, Is 2t 2t 2t 2t 2t 2t

1w 1w 1w 1w 1w 1w 1w 1w 1w

As-tempered 2t 2t 2t, Is 2t 2t 2t 2t 2t, Is 2t

1w 1w 1w 1w 1w 1w 1w 1w 1w

607;C 24h, air 2t 2t 2 21 2t 21 2t 2t, s 2t

cool

* t = tensile, w= wafer, s=SANS specimen

16
Table 3-8. Capsule loading for PB

Material

CMI as tempered

CM2 as tempered

CM3 as tempered

CM4 as tempered

CM5 as tempered

CM6 as tempered

CM7 as tempered

CMS as tempered

CM9 as tempered

CMIO as tempered

CMII as tempered

CM12 as tempered

CM13 as tempered

CM14 as temperd

CMI5 as tempered

CM16 as tempered

CM17 as tempered

CMI8 as tempered

CMI9 as tempered

CM20 as tempered

CM21 as tepered

CM22 as tempered

CM23 as tempered

CM24 as tempered

CM25 as tempered

CM26 as tempered

CM27 as tempered

CM28 as tempered

CM29 as tempered

CM30 as tempered

CM31 as tempered

CM5 aged 480-C 10h

CM8 salt quenched 400C

CM12 SR 600C 8h

CMI8 SR 600C 40h

CM19SR600CSh

CM19 SR600C40h

CM19SR600C80h

CM19 salt quenched 500C

CM20 SR 600'C 40

CM20 it quenched 500C

CM23 st quenched 400-C

CM26 aged 480C OOh

LA

LB

LC

LD

La

LH

Li

u

LK

tensile

2

2

2

3

3

2

2

3

3

2

2

2

2

2

2

2

2

3

11

3

3

3

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

SANS wafer

2 3

3

8

2 5

2 5

2 3

3

3

3

3

3

2 3

2 3

3

3

2 3

2

2 3

2 11

2 3

2 3

2 3

3

3

3

3

3

3

3

3

3

3

3

2 3

2 3

2 3

2 3

2 3

3

2 3

3

3

3

1 2

2

1

1 2

1 2

1 2

1 2

1 2

1 2

17
using cross sections from the preliminary ORNL

report indicated good agreement with the

previous estimate of flux levels. More recently,

ORNL remapped the flux distribution in and

around the IVAR facility based on new cross

sections and neutron transport calculations. The

estimated flux levels were generally slightly

lower, but in most cases only by a few percent.

However, several locations showed flux

reductions as large as 7%. The fluence estimates

presented in this report (in units of 10'3 n/M2 E >

I MeV) are based upon the most updated flux

levels at each position in the IVAR facility. The

fluence estimates for the T4, T14, and VSR

capsules are shown in Table 3-9. Final fluences

will be based on any further updates of the

activation cross sections and activity

measurements on the dosimetry wires from

individual capsules.

In the case of the PB irradiation, specimens were

loaded into a pair of aluminum sub-capsules

specifically designed to fill the space between

the clevis tabs in a row of large crack arrest

specimens. These specimens were included in a

large instrumented irradiation capsule built by

ORNL as part of the HSSI program. This

capsule was irradiated at FNR during the latter

part of 1993. Temperature was measured by

internal thermocouples and dosimetry was

performed by ORNL [Remec, 1998]. The

irradiation conditions for the PB irradiation are

also given in Table 3-9.

3.3 Tensile Testing

Following irradiation, the IVAR capsules were

returned to UCSB where specimens were

removed, sorted and cleaned to remove any

minor surface contamination . Following

careful measurements of the gauge dimensions

to about ± 5pm, the tensile specimens were

loaded into a linear carriage for automated

testing. The automated tensile tester consists of

a screw driven load frame, a linear drive, a

pneumatically actuated hydraulic upper grip and

a computer control and data logging system.

The linear carriage holds 29 tensile specimens

and serves as the lower grip. It mounts on the

linear drive. During a testing sequence, the drive

precisely locates a specimen under the upper

grip. The upper grip closes, and motion of the

is crosshead initiated. Loads are measured with

a precision calibrated load cell aligned with the

upper grip. Displacements between the bottom

of the upper grip and the lower carriage are

measured by an LVDT. The load-displacement

signals are digitized and continuously recorded

and monitored on a desktop computer during a

test. The crosshead is stopped when the load has

decreased 10% below it's maximum value. The

upper grips are opened and another specimen is

positioned for the next test. Yield strength,

ultimate tensile strength, and uniform elongation

are immediately calculated from the loaddisplacement data and specimen dimensions, and

loaded into a data base. However, each test

record is also examined to verify the results

generated by the computer. Three calibrated

standard specimens are included in every

carriage to ensure data reproducibility.

A minimum of two tensile tests were conducted

for each irradiation and unirradiated control

condition. Additional tests were typically caried

out on unirradiated specimens, as well as the

irradiated specimens in a number of cases. Yield

stress changes (o,) were determined by

subtracting the average unirradiated (baseline)

from the average irradiated yield stress. As

noted previously, both microhardness

measurements and billet location tracking were

used to reduce scatter in Aa, due to variability in

the baseline properties. This included both

matching irradiated and control specimens and

screening the data for cases where the accuracy

of Aa was in some question. In a very few cases

this reduced the number of test points below the

nornal minimum of two.

The estimated uncertainties in individual cy,

values were based on the root of the sum of the

squares of the standard errors (or the ay range

in the case of only two tests) of the unirradiated

and irradiated data. The estimated uncertainties

in Ac, averaged about ±11 MPa, but where

significantly higher in some cases. The largest

uncertainties were experienced in the VSR study.

18
Table 3-9. Irradiation Conditions

Capsule Irradiation Conditions

Flux Fluence Temperature

(10 r nLrm-s) (10 n/rn) (C)

T4 0.97 0.75 290

T14 0.32 0.48 290

VSR 0.97 0.85 290

PB 0.7 1.0 288

This led to a data screening procedure, described

in Section 6. 1, for the A5, used to estimate

matrix copper levels.

3A Small Angle Neutron Scattering

The Small Angle Neutron Scattering (SANS)

measurements were performed at the National

Institute of Standards and Technology (NIST).

Details of the experiments and data analysis are

present elsewhere [Mader, 1995; Wirth, 1998].

The approach can be briefly sunmarized as

follows. All measurements were made in a

strong (1.8±0.IT) magnetic field oriented in the

* = 0 horizontal direction. The scattering at

small angles, e : 8°, from a well collimated beam

of cold neutrons with a wavelength of - 0.5

nm, was measured on a 64x64 cm position

sensitive detector located about 2 meters from

the sample and rotated off the beam axis by 5°

to increase the scattering vector. The detector

records the number of scattered neutrons

detected in each 0.5xO.5 cm pixel element. The

irradiation-induced feature scattering crosssections are obtained by subtracting off the

corresponding, properly normalized

(measurement time, sample volume and

attenuation) counts from: a) background

radiation; b) parasitic scattering not associated

with the sample itself; and c) scattering from an

unirradiated control. The corrected defect

scattering data are then converted to an absolute

differential defect scattering cross-section

d3IdCl(q, ) by a normalization to

corresponding measurements on a water

reference sample with a 'known' isotropic

scattering cross section. ( 0.88 /cm-ster) [Wirth,

19981.

The differential coherent small angle cross

section, £/dQ for a dilute distribution of single

type scattering feature is given by [Kostorz;

Guinier and Foumet, 1955]

d.VdQ(q,) = NV2 Ap2 F(qr) (3-1)

where:

19
a) N, r and V are the number density,

characteristic size (e.g., radius) and volume of

the feature, respectively. b) F is the scattering

function which depends on feature size (r) and

shape, and the scattering vector, q = Usin(9)/X,

where O is half the scattering angle (26), and is

the neutron wavelength; for spherical features,

F(qr) = 31 [sin(qr) - qrcos(qr)y(qr) 3)

2 (3-2)

c) Ap is the difference (or contrast) between the

scattering length density of the feature (f) and

the matrix (m) or (Ap = pf Pm); here p is the

scattering length density defined as p = bl

where b is the average scattering length (nuclear

or magnetic in the feature or matrix) and is

the corresponding average atomic volume.

Coherent small angle scattering is produced by

both nuclear APN and magnetic APM contrast,

and the total scattering contrast (p 2) is given

by

Ap2 = APN2 + ApM2 sin2 (%s) (3-3)

where ¢, is the angle with respect to the applied

magnetic field.

As noted above, the dlYd[(q,,) data include

contributions from both nuclear (N) and

magnetic scattering (M), thus

d/d(qks)=dcdn N(q) +

dJdflm(q) sin2 ) (3-4)

The d£1dS2 increases from purely nuclear

scattering at = O' 00 to nuclear plus magnetic

scattering at +, = 900. The dVdl data at each

detector pixel were averaged over a set of

specified magnetic angle sectors, 0i+,, for a set

of discrete q,Aq . The corresponding standard

deviations were calculated for each averaged

defect cross section.

The nuclear scattering, Ap2. depends on the

feature composition. It is assumed that the

features are magnetic holes in a saturated

ferromagnetic iron matrix; hence, that the

magnetic scattering, AP 2, is independent of

composition [Fint, 1990; Mader, 1995; Wirth,

1998]. This is useful in two ways. First, the

magnetic to nuclear scattering ratio (MIN)

provides information about the composition of

the scattering feature (see below). Second, good

absolute estimates of the number density and

volume fraction of the scattering features can be

obtained from dl:(qydg, since APM2 is precisely

known. Single, and in some cases multiple,

feature fits are made to the dX/dIWq,O) data

based on the M/N ratio determined from dl,VdQ

vs. <sin2()> fits typically over a q-range where

irradiation-induced feature scattering is

dominant.

The d£/dQ data was analyzed assuming the size

distribution of the features can be approximately

described by a log-normal distribution

characterized by a mode radius r, and radius

distribution parameter, P. Non-linear least

squares fits to the data were carried out to

determine r,, P and dZ/dQ,(o = 0). These fit

parameters can be related to the average of the

radius cubed (<r?>P3 = <r>), number density (N)

and volume fraction (f) of the features as [int,

1990; Mader, 1995; Wirth, 1998]

r> = r,.exp(O.75f 2 ) (3-Sa)

N = (3/4x) 2

fexp(-9VY[rm6Ap2] dJdtam(O)

(3-5b)

fv = (314x){exp(-6.75yrm3Ap2

]) dYIdClM(O)

(3-5c)

Note the 3 and r. parameters have a large

covariance coefficient, hence, cannot be

independently determined with good precision.

This has relatively little effect on the estimates of

a> and f, but results in larger uncertainties in N.

A fixed 0 of 0.4 was used for most single defect

fits to provide a more self-consistent basis to

assess trends in <r>, f and, particularly, N.

As noted previously the M/N ratio provides

information on the composition of the scattering

feature. It is useful to characterize the relative

strengths of nuclear and magnetic scattering as R

= 4N/M (= Ap/APN), rather than MIN, since it is

approximately a simple linear function of the

20
composition, R = CcXc. + C.A. where the C's

are known coefficients and X's are the atom

fractions [Mader, 1995; Wirth, 1998]. For

example, the nominal R for a spherical void and

a pure copper precipitate in an iron matrix are

about 1.58 and 0.36, respectively [Wirth, 1998].

If the copper-rich precipitates (CRPs) contain

more than two elements (e.g. Cu, Mn and Ni),

the R is not a unique quantity. However, R

constrains and can be used along with other

information to estimate CRP composition. The

other information includes: a) the CRP volume

fraction; b) the amount of copper (and other

elements) in the CRPs based on independent

measurements of changes in the matrix levels; c)

use of isotopically modified constituents; d) data

from atom probe and other microanalytical

techniques such as positron annihilation

spectroscopy; e) thermodynamic calculations;

and f) hardening measurements [Wirth 1998].

3.5 Field Emission Gun Scanning Transmission Electron Microscopy

Field Emission Gun Scanning Transmission

Electron Microscopy (FEGSTEM) was

performed on a number of alloys in the

unirradiated condition to evaluate the amount of

copper in solution as a function of heat

treatment. The FEGSTEM studies were

performed at AEA Technology in a

collaborative program with UCSB. Standard

0.5x3mm transmission electron microscopy

(TEM) specimens were examined in a VG

HB501 STEM and a Philips EM430

conventional TEM. The STEM is fitted with a

parallel electron energy loss spectrometer

(PEELS) and an energy-dispersive X-ray (EDX)

detector. The relative concentration of copper

interacting with the electron beam is determined

from the ratio of the counts under the copper

peak to the counts under the peak of a reference

element, typically taken as iron [KenwayJackson, 1993].

The measurement of matrix copper with the

STEM EDX was determined as follows

[Kenway-Jackson, 19931. The foil precisely

positioned in the STEM in a specially-modified

holder of copper-free construction. X-ray

spectra were recorded from regions free of any

visible precipitates using the so-called spot mode

or small area mode, where the small areas were

fitted between dislocations. Precipitates with

diameters larger than about Snm were also

generally avoided by the small area

measurements. The small area measurements in

the STEM determine the average copper content

between dislocations and large precipitates, while

the spot analyses measure the copper content

between dislocations and all visible precipitates.

The visibility limit of the HB501 STEM is a

precipitate diameter of around 2nm. The

relationship of these two types of measurement

to the bulk copper content and to each other,

and the variation within a series of measurements

of a given type, changes with the type and extent

of precipitation, as explained below:

1. When no precipitation has occurred and the

dissolved copper is evenly distributed, both

spot and small area measurements are the

same as the bulk measurement and the

distribution about the mean will be relatively

narrow.

2. When heterogeneous precipitation occurs on

dislocations and grain boundaries, then the

small area and spot measurements will again

be tightly distributed about a mean, but the

mean will be less than the bulk copper level.

The difference between the bulk and the

mean represents the amount of copper

beterogeneously precipitated.

3. When some homogeneous matrix

precipitation occurs and the precipitates are

extremely fine (diameter, d < 2nm), the

precipitates are not easily visible in the STEM

images and are included in both the spot and

the small area measurements. In this case the

small area measurements overestimate the

dissolved copper content. Since the spot

measurements, randomly sample both matrix

and precipitates, the average spot

measurement will be equal to the average

small area measurement. However, the

distribution of individual spot measurements

21
becomes skewed and/or broadened, and the

lower end of the distribution corresponds

more closely to the true matrix level of

copper.

4. When homogeneous precipitation has

occurred and the precipitates have grown to

more than 2nm, the precipitates are visible in

the STEM images and can be avoided during

spot analysis. Under these conditions, the

spot measurement distribution will once

again become tight about a mean that

represents the best estimate of the matrix

copper level.

5. When further growth of matrix precipitates

results in diameters well over Snm, the

precipitates can be avoided by the small area

measurements as well as the spot

measurements; and the spot and small area

measurements will again be equivalent. Their

means will provide a best estimate of the

matrix solute content. The difference

between the bulk and small area

measurements will then include a

contribution from the large matrix

precipitates as well as the precipitates on

dislocations and grain boundaries.

Hence, the differences between bulk (or large

area), small area, and spot measurements as well

as the distribution of spot and small area

measurements provide a method of estimating

both the copper in solution as well as the size

and spatial distribution of copper precipitates.

When both heterogeneous and homogeneous

precipitation occur concurrently (the most

typical situation), the bulk measurement will be

greater than the STEM small area measurement,

and the STEM small area measurement will be

greater than the spot measurement. The

difference between the bulk and STEM small

area measurements will then show the extent of

heterogeneous precipitation, the difference

between the STEM small area and spot

measurements indicates the extent of

homogeneous precipitation producing

precipitates with diameters greater than 2nm.

The distribution of the spot measurements will

give information on the precipitates of diameter

less than 2nm. Once again, in this case the best

estimate of the dissolved copper level is given by

the spot measurements. Depending on the

situation, the best estimate of copper in solution

in the presence of small precipitates can be

obtained by either the mean of the lower peak in

a spot distribution or the mean of the lowest four

measurements. Summarizing, the amounts of

copper tied up in the various precipitate size

categories can be taken as:

1. The dislocation precipitate content is the bulk

copper level minus the mean of the small

area

2. The homogeneous precipitate content

(diameters above 2nm) is the mean small area

level minus the mean spot level

3. The homogeneous precipitate content

(diameters below 2nm) is the mean spot level

minus the matrix level

4. The matrix copper level taken as the mean of

the four lowest spot measurements, or the

mean of lowest peak in spot distribution

where relevant.

These working rules to establish the matrix

copper level from FEGSTEM data were

developed based on extensive Monte Carlo

studies of STEM electron beam interactions with

a range of precipitate structures. However, the

overall accuracy is limited and in general is of

order ±0.05% copper. The limitations of even

these highly sophisticated measurements and

analysis methods demonstrate the challenges to

precisely characterizing the effects of preprecipitation during stress relief on matrix

copper levels.

3.6 Electrical Resistivity

Measurements

Electrical resistivity (expressed in pil-cm in this

study) is a function of the solute content of the

matrix, and it can be precisely measured

[Rossiter, 1991; ASTM, 1987]. Tests were

22
performed on tensile specimens used in the

irradiation experiments. The width and

thickness of the guage section of the specimens

were carefully measured to 51pm. The specimen

was mounted and aligned on a Teflon support

block containing two copper electrodes that

contacted the tab ends of the specimen. These

electrodes were attached to a DC constant

current power supply. An upper block

containing two copper knife edge electrodes was

lowered onto the specimen, guided by alignment

pins. The knife edges were located at a precisely

known distance apart along the specimen gauge

section. They were loaded on the specimen with

a fixed weight. A current was applied and

measured with a precision ammeter. The

corresponding voltage drop across the knife

edge electrodes was measured with a high

precision DC nanovoltmeter. The current and

voltage was read by a desktop computer, and

along with the specimen dimensions and knife

edge spacing were used to compute the

resistivity. The entire apparatus was maintained

in an electrically and thermally insulated

container The sample temperature was

measured with a thermocouple attached to the

support block adjacent to the specimen. Tests

were performed at ambient temperature, in the

range of about 20-25-C. In this range, the

resistivity was linear with temperature with a

coefficient of about 0.08 tfl-ciC. The

resistivities was normalized to a reference

temperature of 23°C for data intercomparisons.

Resistivities of the alloys examined in this study

ranged from about 10-27 p5cm. Typical

uncertainties were on the order of ±0.05 pfl2cm

for a single specimen, and up to about 0.5 I.0-

cm between specimens of the same material. The

average uncertainty was about ±0.2 pf-cm.

3.7 Seebeck Coefficient

Measurements

Similar to resistivity, the Seebeck coefficient of a

metal or alloys is very sensitive to the

concentration of dissolved solutes [Pollock,

1991; Miloudi et. al, 1999, 2000]. The Seebeck

effect relates to the electric potential difference

established between junctions of dissimilar

conductors in a temperature gradient.

Thermoelectric power derives from three

interrelated effects: the Peltier effect, the

Thomson effect, and the Seebeck effect. These

form the basis for both thermocouples and

thermoelectric power generators [Pollock,

1991]. As noted above, the Seebeck effect

occurs when dissimilar conductors in contact

form a circuit that produces an electric potential

when the two junctions are held at different

temperatures. The Seebeck coefficient, S (in

units of pV 0K) is the open circuit potential

divided by the temperature difference.

The Seebeck coefficient is determined by

measuring the potential difference of an open

circuit composed of a pure copper reference

material and the samples, typically in the form

of tensile specimens. Thus the potential is for

the sample relative to copper and is not an

absolute value. The absolute value is found by

correcting for the absolute potential of the

reference material, in this case copper. The

sample was aligned in a fixture and held against

the copper electrodes with a fixed weight. One

of the electrodes was at ambient temperature

while the other was heated with a resistance tape

to about 100 higher. The temperatures in the

knife edges just below the sample were measured

with thermocouples to within ±0.1°C. The

potential difference was measured with a

precision nanovoltmeterto within :tl.5pV. Care

was taken to avoid noise or spurious electronic

signals, and copper leads of equal length were

used to minimize any extra potential not

associated with the specimen itself. The

instrument was calibrated with copper and

aluminum reference materials with known

absolute values of S. A nominal temperature

coefficient for S of 0.022 pVrK' was used to

correct the data to a nominal average sample

temperature of 31°C. Typical uncertainties were

j0.05 pVrK for a single specimen, and up to

about O.5 pVrK between specimens of the

same material. The average uncertainty is about

±0.25pV/K

23
4 EFFECTS OF COMPOSITION ON IR*ADIATION

HARDENING AND EMBRITTLEMENT

The empirical trends of A;Y variations with alloy

composition are described in this section. The

data are derived from the T4, T14, VSR and PB

capsules. Except for the PB capsule, which

contained specimens in the as-tempered heat

treatment condition, or as otherwise noted, all the

alloys are in a tempered plus standard stress

relief condition. The heat treatment schedules

are described in Section 3.

4.1 Summary of the Data Trends

4.1.1 Copper Bearing Alloys

Figure 41 plots the A;, of the intermediate

nickel (0.74 to 0.88%) CM and LV alloys versus

bulk copper content (Cub,). The data are from

the T4, T14 and VSR capsules. Figure 4-la

presents results for the CM-series (CM3, 10,

11,12, 13,16 and 19) and 4-lb for the LV-series

(LG, LH, LI, LC, LJ, LK), respectively. In both

cases Aa, (Cub,) has a typical sigmoidal shape,

with a low copper threshold region and a high

copper saturation, followed by a decrease at very

high copper levels. In between Au. increases

rapidly with increasing Cu,,.

Figure 4-2 shows the corresponding effects of

nickel variations on A(oY for intermediate and

high copper steels. The data are from the T14

and PB capsules. Figure 4-2a shows data for the

high copper (0.43%) CM-series (CM 18, 19, 20).

In all three cases, A; increases approximately

linearly with nickel, as Aa,(Ni) = A + BNi. The

average zero-nickel intercept is A = 63 6 MPa

and the average slope is B = 117±8 MPal%Ni.

Figure 4-2b shows a similar plot for the

intermediate copper (0.22%) CM alloys

(CM15,16,17). In this case, the data for the astempered heat treatment condition from the PB

capsule is included, since pre-precipitation is not

expected to occur at these bulk copper levels

(see Section 6). The Ay,(Ni) intercept is A =

45±3 MPa and the slope B = 106±:10 MPaf%Ni.

Figure 4-2c compares the Ay,(Ni) data for

intermediate and high copper steels from the

T14 capsule. Notably, nearly doubling Cubk,

results in only relatively small increases in the

Aur from about 18 MPa at low (0.0%) nickel to

32 MPa at the high (1.7%) nickel. Figure 4-2d

plots Aay, versus nickel for the high copper

(0.40%) LV series. The corresponding data for

the high copper CM-series is shown as small

filled symbols. The AG,(Ni) is very similar for

the CM and LV steels, with the exception of the

LV data from the T4 capsule, which falls well

below the other data trends. The LV steels also

have a slightly higher average intercept of A =

71.8 5 MPa than the CM alloys (A = 63 MPa

for the CM alloys), and a lower nickel sensitivity

with an average slope of B = 101± 15 MPaJ%Ni

(B = 117 MPal%Ni for the CM alloys).

However, in spite of these modest differences,

overall the behavior of Ao,(Ni) for the LV and

CM alloys are very similar. These results clearly

show that for intermediate-to-high copper steels,

nickel is the dominant compositional factor

controlling embrittlement.

Figure 4-3 plots Ay, versus manganese content

(0.0 to 1.65%) for the internediate nickel

(0.85%), high copper (0.42%) CM alloys

(CM19,21,22), as well as the LV steel (l) from

the T4 and T14 capsules. The AG,(Mn) is

approximately linear, AG,(Mn) = A + BMn, with

an average slope of B = 31±5 MPa/%Mn. The

AG, for the CM21 alloy with intermediate

manganese (0.84%) falls somewhat above the

linear trend line in both cases. Hence a AG,(Mn)

= A + BMn + CMn2 type dependence may

actually be more appropriate. The effect of

manganese is larger for the intermediate flux,

lower fluence T14 irradiation compared to the

high flux T4 capsule. This difference is

consistent with enhancement of a flux effect by

manganese (and nickel) that is discussed in

Appendix A.

Figure 4-4 plots A, from the a) PB and b) T14

capsules for other compositional variations in

intermediate and high copper CM alloys,

including: i) a 10 wt.ppm boron addition to the

24
cl

200

150

100

50

0

0 0.25 0.5 0.75

Cu (wt. %)

200

150

eS

1,

100

50

4

0

0 0.2 0.4 0.6

Cu ( %)

1

0.8 1

Figure 4-1 Variation of Acy with bulk copper in intermediate nickel alloys for the

a) CM and b) LV series

25

I I 

a CM-0.8%Ni

* t

4 s

0 * T14

A A T4

* * VSR

& I -. I 

* I U I

LV-0.8%Ni b

** A

a A

T14

A * PBC

A T4

. y y y

. . .

r r | . r
Ia

CM - 0.4% Cu a

* T14

a T4

* VSR

0.5 1 1.5 2

Ni (wL %)

a I

C x

CM - OA% Cu, T14 *

CM -0.2% u,TI

t CM - 0.2% CU, T4

I 

--L- .-- - - - -J

0 0.5

300

250

9

200

150

100

50

0

300

250

200

150

100

50

0

1 1.5 2

b X

CM - 0.4% Cu, T14 $

x

0 T14

) T4

CM - 0.2% Cu * PB

I ia, . i VSR

0 0.5 1 13 2

Ni (wt. %)

. ,

0.4% Cu CM (filled), * d

LV unfilled)

0

d . @ * T14

X t .~~ T4

* VSR

0 0.5

Ni (Wt. %)

1 1.5 2

Ni (wL %)

Figure 4-2 Variation of Acriwith nickel for a) 0.4 copper and b) 0.2 copper CM alloys;

c) comparison of Aay versus nickel for intermediate and high copper steels for T14;

d) variation of Acty with nickel for high copper LV series steels

(corresponding CM alloys shown for comparison as small filled symbols).

26

300

250

200

150

100

50

0

300

250

200

150

100

50

0
225

200

175

150

125

4

100

0 0.5 1 1.5

Mn (wt. %)

Figure 4-3 Variation of ac,y with manganese for intermediate nickel,

high copper CM and LV steels.

250

200

-3 150

10

50

a

250

200

I9150

100

50

n

e w h o ,e an c m o ) 1

Figure 4-4 Variation of Acry with boron, molybdenum and chromium for a) PB and b) T14.

27

I . I a

0.4 Cu CM, LV

& LV

A CM

0O 

0 &

I I I

2

b

T14

-

n . , . .

1|

I
high copper (0.42%) and intermediate nickel

(0.84%) alloy (CM27); ii) an intermediate

copper (0.22%) low nickel (0.02%) alloy

(CM29) with no molybdenum (0.02% versus a

nominal value of 0.5%); and iii) an intermediate

copper (0.22%) and nickel (0.85%) alloy

(CM30) with a 0.42% chromium addition. The

Aa, for the modified alloys are compared to the

corresponding base steels (CM27 vs. CM19,

CM29 vs. CM15 and CM30 vs. CM 16). The

alloys in the PB and T14 capsule are in the astempered and standard stress relief conditions

respectively. The boron and chromium

additions have a small to negligible effect.

However, the Aa, in steels without molybdenum

is larger in both cases.

While the overall effect of deledng molybdenum

is modest (a difference of about 30±6 MPa), this

trend is consistent with a lower dispersed

obstacle contribution to the unirradiated yield

strength in this alloy, that lacks fine scale Mo2C

carbides. As discussed in Section 6, this

behavior arises from the fact that the individual

strengthening contributions from the

unirradiated (aj and irradiation induced (a,)

dispersed dislocation obstacles must be

combined or superposed. For strong

unirradiated obstacles and weaker irradiation

induced obstacles, the superposition law falls

between linear and root sum square limits. Thus

for a given a, the net Ao, decreases with

increasing cr,. (see Equation 6-4 below). As a

simple example, taking a. as 200 and 35 MPa

for CM5 and CM29 respectively and assuming

a normal CRP superposition parameter of e =

0.4, a common , = 95 MPa results in a ao, of

51 (CM15) vs. 78 MPa (CM29), respectively.

These are close to the observed values.

Table 4-1 summarizes the trends discussed in the

previous paragraphs. Note the magnitudes given

are illustrative for 290°C, 0.5xIl2 n/m2 low-tointermediate flux irradiations of intermediate-tohigh copper alloys in the standard stress relief

condition. The specific values must be viewed as

representative, since detailed behavior depends

on the entire combination of variables.

4.1.2 Low Copper Alloys

Figures 4-5a, b and c plot Aa, from the T14 and

PB capsules versus phosphorous content (0.002

to 0.047%) for low copper (0.02%) CM alloys

with low (0.01%), intermediate (0.86%) and

high (1.53%) nickel. The effects of increasing

nickel are shown in Figures 4-5a (low, CM1, 2),

5b (intermediate, CM3, 4, 5) and Sc (high, CM6,

7), respectively. The Aa, increases

approximately linearly with phosphorous in all

cases, hay(P) = A + BP. The slopes of Ay(P)

range from B = 550 to 1450 MPa/%P. Plots of

the B versus nickel shown Figure 4-5d do not

seem to show any systematic trend. However, the

data from the T14 capsule are more scattered,

and the high nickel point seems to be

anomalously low. The slopes average 1165

MPa/%P with the T14 point included, and 1285

MPal%P if it is deleted. Figure 4-5e compares

the A,(P) for alloys with two copper levels

(0.02% and 0.11%). The effect of phosphorous

on A&Y for the PB capsule (filled symbols) is

very similar in both cases. However, the apparent

phosphorous sensitivity of the T14 capsule data

is higher for the alloy with 0.02% copper and

much lower for the alloy with 0.1 1% copper,

with B = 1931MPa/%P and 0 MPaJ%P,

respectively. Again, these differences may be

simply a consequence of the larger scatter in the

steels in the T14 capsule. Alternately it may

indicate that higher copper decreases the effect

of phosphorous for steels in the standard stress

relief (T14) versus as-tempered (PB) condition.

The effect of nickel on low (0.02%) copper

steels was shown in Figure 4-5a to 4-5c. Cross

plots of the CM data are shown in Figure 4-6 for

low (Figure 4-6a) and high (Figure 4-6b)

phosphorous. In three out of the four cases the

AcS, shows a clear linear trend, Aa(Ni) = A +

BNi, with an average slope of B = 20*4

MPal%Ni. The slope for the high phosphorous

T4 capsule data is much less (5.4 MPa/%Ni) and

the individual AoY are more scattered. Given the

general scatter of the Ao, values, such

differences are not unexpected. If this data point

is included the nickel sensitivity slope decreases

to 16 MPa/%Ni.

28
Table 4-1. Summary of Compositional Dependence of Hardening in High Copper Steels

Variable Dependence Interactions Magnitude

copper threshold- nickel, manganese, - 50 MPa (0.0%Ni)*

saturation HT't (S - 150 MPa (0.8%Ni)*

sigmoidal section ) - 240 MPa (0.8%Ni)*

*@ 0.3% Cu

nickel - A + BNi copper, managnese, B - 110 MPa%Ni

HT (see section 5)

manganese - A + BMn copper, managnese, B - 30 MPa/%Mn

HT (see section 5)

molydebdnum not established superposition of the - -30 MPa with vs.

irradiated/unirradiated without molydebdnum

obstacle strengths

boron, not established probably minor

chromium

tHT=heat treatment

Figure 4-7 plots Au. of low (0.02%) copper

CM alloys (CM8, 3, 9) from the T14 and PB

capsules versus the manganese content. The

As, data scatter around a linear trend,

Ayy(Mn) = A + BMn, with a slope of B = 10±1

MPa/%Mn.

Figure 4-8 shows histogram plots of Aa from

the T14 and PB capsules for alloys with single

element compositional variations. These

include: low (0.02%) copper CM alloys

(CM23 to 27) with a) low (0.05%),

intermediate (0.15%) and high (0.3%) carbon

(CM23, CM3, CM24), b) high nitrogen

(CM25), c) doping with a mix of tramp

elements (CM26) and d) a boron addition

(CM27). There is no systematic trend with

carbon. The intermediate carbon base alloy

(0.15%, CM3) has the highest As;, in one case

(PB) and lowest in the other (T14). A slight

increase in Aay at the higher nitrogen level

(CM25) is observed in data from both

capsules. The alloy with the boron addition

(CM27) has a lower Acr in both cases. The

Ay of the alloy with tramp element additions

is the same as the base alloy in one case (T14)

and slightly less in the other (PB). However, all

these A;o are small and the differences

between them are even smaller. Thus the

effects of these composition variations, with

the possible exception of boron, can be

considered to be well within the data scatter.

Since boron additions both-reduce the

magnitude and increase the scatter in the

unirradiated cr, no firm conclusion can be

drawn regarding the effect of this element

either. Therefore, it is concluded that the

effects of these other composition variations

are minor and, if they exist at all, will emerge

only at higher fluence, where the matrix defect

contribution to A,is larger.

Table 4-2 summarizes the trends discussed in

the previous paragraphs for low copper (-

0.02%) steels. Again, the magnitudes given are

illustrative for 290°C, 0.5-lx102 n/m2

irradiations (assuming there is no flux effect in

this case) of low copper alloys. The effects of

heat treatment have not been determined. The

specific values again must be viewed as

representative.

29
125

100

.0

75

50 1

25

0 0.01 0.02 0.03 0.04 0.05

P (wL %)

It

0 0.01 0.02 0.03 0.04 0.05

P(wt. %)

0 0.01 0.02 0.03 0.04 0.05

P (WL %)

0 0.5 1 1.5 2

Ni (%)

12

10

7

2

4

0

PB - 0.0% Cu

PB-0.1%Cu

T14 - 0.0% Cu

T14 - 0.1% Cu

5 a 

e

0.

5 .

o @

4

CM -O .8%Ni

A A, . . .

0 0.01 0.02 0.03 0.04 0.05

P(wL%)

Figure 4-5 Variation of Aoy with P for a) low copper, low nickel; b) low copper, intermediate

nickel; and c) low copper, high nickel steels. d) Variation of phosphorous sensitivity (B)

with nickel. e) Comparison of Acy (P) for alloys with 0.02 and 0.1 1% copper.

30

125

100

75

50

25

0

-25

125

100

ft

* T14 b

9 PB

*~

CM-0.8%Ni

0 2 -- - I __ I 

S
* T14 a

* PB 9 .

.~S

CM - 0.005%P

0 0.5 1 1.5 2 0 0.5 1 1.5

Ni (wL %) Ni (wt. %)

Figure 4-6 Variation of Aay with nickel for a) low and b) high phosphorous steels.

0 0.5 I

Mn (wt. %)

Figure 4-7 Variation of ATy with manganese for low copper CM alloys.

31

75

50- I-

.3 25

7% - - -A.

2

75

50

254

01

* T14

* PB

CM - 0.8%Ni

I II -25

1.5 2

_ _ _ _ _ _ _ .
50

40

iY3

C4

30

20

10

- L .. L... I 1. * Ii.1 1 O1 I I[ I I[ I 

U U z X P

Figure 4-8 Variation of Acy with carbon, nitrogen, boron and tramp elements (TE) for

low copper CM steels.

Table 42. Summary of Compositional Dependence of Hardening in Low Copper Steels

Variable Dependence Interactions Magnitude

phosphorus - A + BP possibly copper and B - 1200 MPa/%P _ _ _ _ _ H TT _ _ _ _ __H 

nickel - A + BNi B - 20 MPa/%Ni

manganese - A + BMn B - 10 MPal%Mn

C, N, B, tramp not established probably minor

elements

32
5 ANALYSIS OF THE COMPOSITIONAL TRENDS

5.1 Comparison of the IVAR

Results With Predictions of the

NUREG/CR-6551 Model

The NUREG/CR-6551 AT model (referred to

here as the NUREG model) derived from

statistical fits of physically motivated

embrittlement equations to the PREDB, provides

a good basis to analyze and evaluate the data

trends described in the previous section. The

NUREG-AT model was first converted to a

corresponding NUREG-&a, model using an

analytical AT-Aca, relation. Details are given in

Appendix A. Figure 5-1 shows the predicted

versus measured h,o for data from the Tl4

capsule. The predictions are based on the

NUREG-AT model parameters for welds. Good

agreement is found for all the LV and CM

model steels as well as the welds and plates

obtained from various sources. The overall bias

and standard error between the predicted and

measured values are about -1.9 and ±18 MPa,

respectively. A least squares fit has a slope of

1.06 and an intercept -6.1 MPa. Thus the mean

NUREG-&F, model predictions are within about

6 MPa of a perfect 1: correlation with

measured values up to 200 MPa.

Figure 5-2 compares the NUREG-&AG model

predictions of copper dependence of A, with

the T14 data that has been adjusted to a

common nickel (0.8%) and phosphorous

(0.005) content. The adjustments are based on

the differences predicted by the NUREG-A;7

model for the common versus actual alloy

composition. These adjustments are small

except in cases where the nickel level is much

different than about 0.8%. No correction is

made for manganese differences. The CM and,-

LV model steels, with nominal nickel and

manganese contents of about 0.8% and about

IA to 1.6%, respectively, are shown as the filled

circles. The CM and LV steels with higher or

lower nickel and manganese are shown as the

unfilled circles. The other welds and plates are

shown as unfilled diamonds and triangles,

respectively. The agreement is generally good.

However the Aa3, of the intermediate nickel, high

manganese CM and LV alloys fall a little higher

than the NUREG model predictions in the range

of 0.2 to 0.4% copper. As might be expected,

the hs, for the low manganese CM alloys fall

below the NUREG model predictions.

Figure 5-3 compares the NUREG model

predictions of the effect of nickel on Acy with

LV and CM data from the T14 capsule. Both

the magnitude and predicted variation of Ay

with nickel are in good agreement with the high

copper (0.42%) data (CM18-20) shown in

Figure 5-3a. The agreement is not as good for

the intermediate copper (0.22%) CM alloys

(CM1 5-17) where the Ar, are underpredicted at

both intermediate (0.85%) and high (1.6%)

nickel levels (CM 16 and 17).

Figure 5-4 compares the NUREG model

predictions of &F. as a function of fluence to

data for low copper (0.02%) intermediate nickel

(0.85%) CM alloys (CM3,5) for low and high

phosphorous levels. In this case Acr, data from

lower fluence2 capsules have been added to T4,

T14 and PB results. The data are scattered

around the NUREG predictions, but overall

agreement is good. Thus, the IVAR AGy data

suggests that the effect of phosphorous is well

represented by the NUREG model.

Given various sources of uncertainties in the data

and application the Acrmodification of the

NUREG AT correlation model statistically fit to

the completely independent surveillance PREDB,

the overall agreement is remarkable. Thus the

ACF, database generated in this study provide a

powerful and independent confirmation of the

general form of the NUREG model.

2 These capsules are designated TI, T2. TI I-T13, and T21

33
300 1 1 5

T14

-~~~~ ~0

200

40

0

0 100 200 300

Acy (pred, MPa)

Figure 5-1 Comparison of the NUREG- Acy model predictions with the data from the capsule T14.

200

150

100 P4

b

cX

50

0

- NUREG

0 CM/LV Base

O Weld

a Plate

0 CM/LV Other

0.00 0.20 0.40 0.60 0.80 1.00

Cubk (%)

Figure 5-2 Comparison of the NUREG- Aay model predictions with the data from capsule T14

adjusted to 0.8 nickel and 0.005% phosphorous.

34
400

0 0.5 1 1.5 2

250

200

150

100

50

0

Ni (wiL %)

0 0.5 1 1.5 2

Ni (wt. %)

Figure 5-3 Comparison of the NUREG-Acy model predictions of nickel dependence of

embrittlement with the T14 data for a) 0.4% copper and b) 0.2% copper steels.

0 0.5 1 1.5

*t (1023 n/n 2 )

Figure 5-4 Comparison of NUREG-Ahy model predictions with Acry data as a function of fluence

for low copper (0.02%) intermediate nickel (0.85%) CM alloys for both low (0.005%,

CM3) and high (0.04%, CM5) phosphorous levels.

35

125

100

75

50

es

tr

a4

25

0

2

300
52 The Microstructural Basis,

Mechanisms and Models for the

Composition Dependence of

Hardening and Embrittlement

The primary cause of AT is irradiation

hardening, A, [Odette et al, 1985; Fisher and

Buswell, 1987]. Hardening is in turn caused by

the irradiation induced formation of a large

population of nanoscale features that act as

obstacles to dislocation slip.[Odette, 1983;

Odette and Lucas, 1998; Fisher and Buswell,

1987]. The irradiation-induced nanofeatures

are significantly weaker than strong, pre-existing

obstacles to dislocation slip, such as fine scale

Mo2C carbides, that are largely unaltered by

irradiation. The latter require dislocations to

bow around them, while dislocations can

penetrate the irradiation nanofeatures. The

individual strength contribution of the

nanofeatures (,) is a function of their specific

character, size [rJ, number density (Ni) and

volume fraction (f1) as [Odette and Lucas, 1998]

Oi - Ai(r1y4f1 (5-1)

where the f, = [47tr, 3 3]N,, and the Ai describes

the strength of the feature that depends on r.

Peak strength occurs at roughly r = I to 1.5

nm. The Ai(r;) decreases rapidly below this peak

hardening size (r1,), and roughly proportionately

to (rtrj), where n c 1 at larger sizes. As

discussed elsewhere in this report, the net AY, is

less since, a, must combine with the contribution

of pre-existing strong obstacles ((Y.) [Odette and

Lucas, 1998].

Current understanding of the embrittlement

nanofeatures is based on combinations of

sophisticated microstructural and microchemical

characterization studies and physical models.

Characterization methods include: small angle

neutron and x-ray scattering that provide size,

volume fraction and compositional

information [Odette, 1995; Odette and Lucas,

1998; Phythian and English, 1993; Solt et a],

1990, 1993; Mader, 1995; Williams and

Phythian, 1996; Wirth, 1998; Wirth et. aL 1999;

Alexander et. al, 19991, various types of electron

microscopy that provide both high resolution

structural images and compositional information

[Phythian and English, 1993; Jenkins 1994;

Williams and Phythian, 1996] and 3-dimensional

atom probe-field ion microscopy that measures

the configuration of the elements within a small

sampling volume to near atomic resolution

[Miller et al, 1993; Miller et al, 2000]. Thermodynamic-kinetic models are used to track the

transport and fate of irradiation defects and

solutes and to predict the number, size

distribution and composition of the nanofeatures

[Odette and Wirth, 1997; Odette and Lucas,

1998; Odette 1998; Wirth, 19981. For pressure

vessel and surveillance conditions and the

irradiations in this study, the nanofeatures can be

divided into two broad categories [Odette and

Wirth, 1997; Odette and Lucas, 1998; Odette,

1998; Fisher and Buswell, 1987; Mader, 1995;

Wirth 1998; Liu et al, 1997]:

- copper-rich or catalyzed Mn-Ni rich

precipitates (CRPsl?Ps)

- matrix features primarily in steels with low or

no copper The matrix features are defect

(vacancies and possibly interstitials)-solute

cluster complexes that are probably formed

directly in displacement cascades. Other

precipitate phases, such as phosphides, may

also contribute to matrix feature hardening.

5.2.1 Copper Rich Precipitates

Following typical heat treatments, copper can

remain dissolved in the in the iron matrix up to

about 0.3% [Odette, 1995; Odette and Lucas,

1986, 1988, 1997, 1998; Buswell and Jones,

1993; Williams and Phythian, 1996; McElroy

and Lowe, 1996; English et al, 1997]. However,

the solubility of copper decreases at lower

temperatures, to <0.01% at around 290°C. The

supersaturated copper diffuses and precipitates

into a separate phase. Enhanced diffusion,

caused by excess vacancies produced by

irradiation, enormously accelerates processes

that are normally thermally sluggish, resulting in

the rapid formation of a high number (1023

m 3 ) of small (-1.5-3 nm diameter) CRPs with a

36
BCC crystal structure that is coherent with the

iron matrix.

The CRPs are the dominant hardening feature in

sensitive steels that have copper contents greater

than about 0.05-0.1%, which is the minimum

needed for rapid nucleation. The CRP volume

increases with copper up to an effective upper

limit around 0.3%, imposed by copper preprecipitation at the final stress relief temperature

(typically about 610°C). The CRP contribution

has a relatively weak irradiation temperature

dependence and saturates at high fluence, due to

copper depletion from the matrix. The CRP

evolution is delayed at higher fluxes by

interstitial recombination with vacancies that are

trapped at solutes and in small transient clusters

[Odette et al., 1993; Odette and Lucas, 1998;

Odette, 1998]. The amount of recombination

increases with increasing flux. At very low flux,

CRP evolutions may be accelerated due to a

contribution of thermal diffusion to copper

precipitation [Odette et al, 1999].

The precipitates are not pure copper, but are

enriched in manganese and nickel as well as

smaller amounts of phosphorous and silicon

[Mader, 1995; Liu et al, 1997; Odette and Lucas,

1998; Odette, 1998; Wirth, 1998; Wirth and

Odette, 1997]. The thermodynamics of the

copper-manganese system is such that at low

temperatures around 290°C manganese

partitions from the matrix and is enriched in

copper precipitates. Nickel itself does not

interact as strongly as manganese. However, if

nickel and manganese are both present, they

interact strongly with each other, and

synergistically increase the concentration of

both elements in the precipitates. In some cases

this can result in the replacement of CRPs with

manganese-nickel rich precipitates (MNPs) with

a small copper rich core [Wirth and Odette,

1999; Liu et al, 19971. Manganese-nickel

enrichment of the precipitates is promoted by

higher alloy contents of these elements, lower

copper (beyond the amount needed for

nucleation) and low irradiation temperature.

The increase in the volume fraction of CRPs (or

MNPs) with manganese and nickel explains the

strong effect of these elements on increasing AA,

and AT.

Typical values for the A, for CRPs at peak

strengthening size are about 3750 MPa. Thus, a

f,= 3xl0 3 produces a , - 240 MPa. Taking

.= 200 MPa and a superposition parameter of

e = 0.4 (see Equation 6-4 below) typical of

CRPs, gives a net A, - 135 MPa.

Figure 5-5 plots the estimated volume fraction

of CRPs from SANS measurements on CM and

LV alloys from the PB capsule as a function of

the alloy nickel and manganese contents. The

corresponding estimated precipitate volume

fractions of copper, nickel, manganese and

vacancies (lumped together for clarity) are also

shown. The composition evaluations are

consistent with the magnetic to nuclear scattering

ratios measured in the SANS studies.

Thermodynamic model predictions of the CRP

(MNP) composition are used to guide this

assessment [Wirth, 1998]. The thermodynamic

model generally predicts higher nickel and

manganese levels in the precipitates than is

consistent with the experimental scattering ratio.

Thus the amounts and relative proportion of

these elements are minimally adjusted to provide

consistency. The resulting estimates of the

composition of the precipitates are not unique

and are subject to considerable uncertainty.

However, these estimates are reasonable and

certainly provide insight into the general trends.

Further details are given elsewhere [Wirth, 1998;

Wirth et al, 19991.

Figure 5-5a shows differences in the precipitate

parameters as a function of nickel from 0.02 to

1.69% for the CM alloys (CM 18, 19, 20). The

f, increases linearly with nickel. Higher alloy

nickel levels increases the CRP manganese and

nickel contents, with a big jump between 0.84

and 1.69%. Indeed, at highest nickel the

precipitates are actually manganese-nickel rich

(MNP). Figure 5-5b shows similar but more

modest increases that are observed for the LV

alloys with 0.85 to 1.25% nickel (LC, LD).

Similar effects of increases in the CM alloy

manganese content from 0 to 1.6% (CM21, 19,

37
1.

* CRP

Ni

v Cu

* Mn + Vac.

I .v

0.81

a 0.6

0.4

0.21

0. -

0.5 1.0 1.5 2.0 0.0

Ni (%)

0.5 1.0 1.5

Mn(%)

* CRP

Ni

Cu

A Mn + Vac.

I

2.0

0.5 1.0

Ni (%)

1.5 2.0

0 100 200 300

A% (pred., MPa)

Figure 5-5 Volume fraction of CRP's estimated from SANS measurements on CM and LV alloys for

the PB capsule as a function of a) nickel for CM alloys, b) nickel for LV alloys, and c)

manganese for CM alloys; d) comparison of measured Acy with values predicted from

SANS microstructural parameters.

38

1.0 r

0.8

a

CM 0.4% Cu 0

. i. A

.(a. -

0.6r

0.4

0.2

0. 0

0.0

LV - 0.4%Cu b

* 0 OV

V

A

A

I1.n,.

0.8 1

0.5 -

0.C0-

0.0

CM 0.4% Cu c

v Y

A

A , 9

v

0.2t
22) are shown in Figure 5-5c. ligher nickel

and manganese alloy contents also increase

N,p [Wirth, 1998]. In this study, the increase

in N,p is more than a factor of 7 between 0

and 1.69% nickel, with a corresponding

reduction in r, from - 2 to 1.4 nm. Figure 5-

Sd compares the Aay predicted by a hardening

model based on the SANS measurements of

f, and r,, to experimental values. Details of

the procedure are described elsewhere [Wirth,

1998; Wirth et. al, 1999]. The agreement is

good, demonstrating that the effects of

manganese and nickel on the CRP

contribution to hardening and embrittlement,

as summarized in Table 4.1, can be

understood on the basis of the corresponding

effects of these elements on the f, and r,.

52 Matrix Features

The matrix features are generally not as well

understood as CRPs. Atom probe studies have

shown regions enriched in solutes like

manganese, nickel and silicon [Pariege, 1994;

Miller et. al, 2000]. These features are

probably formed directly in cascades, where

the solutes are complexed with defect clusters

[Wirth, 1998; Wirth and Odette, 1999].

Vacancy cluster solute complexes are the most

likely candidate, although small interstitial

cluster-solute complexes are also a possibility.

Even if the defect clusters dissolve, or migrate

to sinks, the solute enriched regions are left in

their wake. The atom probe studies suggest

that about 2.5x IO' matrix features form per

1023 n/M2 (roughly I for every 10 cascades).

Assuming an effective r, - 0.7 nm and f,, -

5x 04 per 1023 n/M2 , as suggested by SANS

studies [Wirth, 1998] (although the size of the

actual enriched region may be larger) results

in an estimate of A. 1 - 1350 MPa. Since the

matrix features are significantly weaker than

CRPs, it is generally assumed that their entire

G, contributes (adds) to Sar Thus the matrix

features are expected to produce about 30

MPa hardening at 102 ntn 2. Since the number

of matrix features increases in rough

proportion to fluence (t), at a roughly

constant size, their contribution to M is

predicted to increase with 'Jt. Note that given

their typical concentration and composition,

depletion of matrix manganese and nickel

does not lead to a saturation of the matrix

features in the fluence range of interest.

However, a slow decrease in the fluence

exponent in the NUREG model can be

understood based on depletion and overlap

effects, as well as some thermal recovery of the

strengthening contributions of the matrix

features over long periods of time.

At low concentrations phosphorous may also

segregate to the matrix feature complexes.

However, phosphorous has a very low

equilibrium solubility in steels that can form

alloy phosphides like Mo3P, which are much

more stable than the Fe3P phase in binary

alloys [Odette, 1998]. Thus alloy phosphides

are expected to form and contribute to Acr

Fine scale features containing phosphorous,

nitrogen and carbon have been observed in

atom probe studies [Pareige, 1994, Miller

2000]. Phosphorous also interacts strongly

with copper, and segregates to CRPs.

Phosphorous gettered by CRPs is not available

to form phosphides. This rationalizes an

interaction that reduces the effect of

phosphorous at higher copper levels. A

phosphorous-copper interaction of this sort

can also be produced by the strength

superposition mechanism noted previously.

That is the individual strength contribution of

phosphides to the net Acs, is reduced in the

presence of CRPs.

As noted above both SANS and atom probe

studies have detected matrix features, either

directly (atom probe) or through scattering

responses (SANS), that indicates a role of

manganese, nickel and phosphorous. Further,

atom probe studies of samples from the

decommissioned CHOOZ reactor vessel have

beautifully quantified the number and general

dilute solute enrichment characteristics of

matrix features over a wide range of fluence

[Pariege, 1994, Auger et al, 1994]. While

efforts to better quantify the matrix features

are continuing, these observations, and others

[Wirth and Odette, 1999], clearly rationalize

39
the Aa, trends with these elements as

summarized in Table 4-2. That is, higher

alloy nickel, manganese and phosphorous

contents increase some combination of the

solute content, volume fraction and strength of

the matrix features, leading to increased Aay.

It should be noted that the role of

phosphorous is somewhat special, since wellformed phosphide precipitates may be

responsible for the hardening caused by this

element. Further, depletion of matrix

phosphorous would be expected to lead to an

eventual saturation of the phosphide matrix

feature contribution. However, the evolution

of the phosphides appears to be much slower

than characteristic of CRPs, consistent with

their narrow range of chemistry and the low

phosphorous concentration. Thus for

practical purposes, it is a reasonable

engineering expedient to lump them with the

other matrix features.

More detailed discussions of the experimental

and modeling that underpins the preceding

discussion can be found elsewhere [Odette and

Lucas, 1998, 1999; Odette, 1998; Eason et al,

19981 and will be elaborated on in future

reports. For the present purposes, however, it

is sufficient to conclude this section by noting

that all the major trends in both the NUREG

model and observed in the IVAR database are

consistent with current understanding of

embrittlement mechanisms. However, a

number of open questions and unresolved

issues remain, providing further opportunities

for improvements in the NUREG

embritlement correlation models. These are

briefly described in the following section.

5.3 Discussion of Improvements in

the NUREG Embrittlement

Correlation Model Treatment of

Composition Effects

It must be stated at the outset that it is not

possible to separate compositional effects on

embrittlement from other metallurgical

variables, such as product form and heat

treatment, and irradiation variables, including

flux, fluence and temperature. Some of the

effects of heat treatment are presented in the

following section. Thus, a comprehensive

reassessment of the NUREG models and

progeny correlation models will be based on

the on the entire IVAR database in the future.

Nevertheless, the information presented in this

report provides some insight into what such

improvements may entail.

First, the overall treatment of copper-nickel

interactions in the NUREG model seems fairly

robust. However, IVAR data indicate that

manganese is also a key element in the CRP

contribution to embrittlement. This may at

least 2artlv explain why the forging CRP

coefficient (700C) is lower by about 22%

compared to that of plates (95 0C). Assuming

typical copper, nickel, and phosphorous

contents of 0.15%, 0.6% and 0.01%,

respectively, and an irradiation fluence of

5x1022nrn2 at 2880C, the NUREG plate model

predicts a Acy1, of about 70 MPa. However,

forgings have about half the manganese

content (- 0.7%) as plates (-1.4%). Based on

coefficients in Table 4-1 this translates to a

reduction in Aayby about 20 MPa, or a 29%

reduction.

There are even larger differences between the

NUREG CRP coefficients for forgings and

welds; and manganese differences do not

explain differences between the NUREG plate

and weld CRP coefficients. However, the

IVAR AF data for the CMILV steels and the

welds and forgings do not indicate such large

differences. Other factors that may influence

the apparent product form sensitivity include

the variations in both the average and range of

copper content in the PREDB, which are

significantly higher for welds. Effects that are

not accounted for in the NUREG model, such

as an influence of copper and nickel on the

fluence dependence of &T, and the effects of

start-of-life Charpy properties on the ,Ac/AT

relation, may also play a role in apparent

product form sensitivity. Further, a number of

other variables are known to influence both

CRP microstructures and W, at an otherwise

40
specified set of conditions. These variables

include: a) a range of heat treatment effects

(see below); b) phosphorous and silicon, which

are enriched in CRPs and increase their

number densities; and c) coarser scale

dislocation sink microstructures which

influence the radiation enhanced diffusion rate

- hence, the fluence dependence - of the

CRP contribution [Odette and Lucas, 1998;

Odette, 1998]. Finally, the current IVAR

database shows that flux and composition

interact to influence CRP contributions to Ar

Data on such interactions will be extended to

irradiation temperature in the future.

In summary, the part of the IVAR database

presented here provides a partial basis to

narrow differences in the CRP contribution

now empirically attributed to a product form

arising from mechanisms that are not

understood. More importantly, these results

lead to the anticipation that, in the future, such

differences can be further reduced and

explicitly modeled to reflect the responsible

variables.

Similar arguments pertain to the matrix feature

contributions to Ao. Clearly some of the

product form variability in the NUREG model

can be attributed to variables that are not

explicitly treated. Manganese and nickel

enhance hardening but are not accounted for

in the matrix feature contribution in the

NUREG model. Figure 5-6 plots the low

copper LV and CM A;, data (LG, CMltolO)

from the T14 and PB capsules versus a matrix

feature solute chemistry factor (CF.,) simply

defined by scaling the results as shown in

Table 4-1 by dividing by 10, where

CFf = 120P + 2Ni +IMn (5-2)

The PB data correlate very well with CF,

(filled circles) while the T14 data (open

circles) follow a similar trend, but are more

scattered. In both cases the least squares fit to

the Aa,(CF,,) have a negative value at the CF.,

= 0 intercept, suggesting that there is a

threshold solute concentration for hardening

in low copper steels. However, it is not clear

that this is actually the case, as illustrated by

VM-series data from the PB capsule shown as

the open diamonds at CF., = 0. These VM

alloys do not contain manganese and nickel

but do include small concentrations of

nitrogen and in one case a 0.25% titanium

addition.

The A;y data from the PB capsules for other

simple VM-series alloys shown in Figure 5-7

also illustrate the role of solutes and solute

interactions on matrix hardening. The

unalloyed iron (VA) with low (10 ppm)

nitrogen has a Acy of 42 MPa. Increasing the

nitrogen to 100 in unalloyed iron (VK, W,

VW) has little effect on hardening with an

average A;, of 36 MPa. However, the a; for

the VB alloy with 40 ppm nitrogen and 1%

manganese increases to 102 MPa. The VR

alloy with 120 ppm nitrogen and 1%

manganese has an even larger Ay of 152 MPa,

suggesting a strong interaction between these

elements. In contrast the VC alloy with 0.15%

carbon, 30 ppm nitrogen and 1% manganese

has an intermediate A; of 70 MPa. Most of

this reduction (- 24 MPa) can be attributed to

the precipitation of manganese in

Fe(0.2Mn)3C phases, and a lesser amount (- 8

MPa) is estimated be due to the lower nitrogen

in this steel (VC) compared to the 1% Mn

alloy without carbon (VB). Without nitrogen

present the effect of manganese is estimated to

be small (_10 MPaJ%Mn), but similar to that

found for RPV steels in Table 4-2. The VB

alloy with 40 ppm nitrogen and 1%

manganese showed a strong SANS signal

similar to scattering from matrix features in

complex steels [Wirth, 1998]: a radius of about

0.76 nm, a volume fraction of 0.052%, and a

low magnetic-to-nuclear scattering ratio

(0.57). This scattering ratio is characteristic of

manganese-vacancy clusters.

Such subtle interactive effects rationalize the

very large relative scatter in matrix features,

A;, and AT that are observed in low copper

steels. The scatter in AT is illustrated in Figure

5-8a, comparing the NUREG matrix feature

41
predictions with the data from the French

power reactor surveillance program [Brillaud

and Hedin, 1992]. Figure 5-8b shows the

large scatter also observed in Ac, in the low

copper steels irradiated in the IVAR capsules,

including an apparent difference between the

LV and CM alloys of unknown origin. The

significance of this scatter has been discussed

elsewhere [Odette and Lucas, 1999]. Briefly, it

is not of much practical significance in low

copper steels which experience only small to

modest AT. However, since the matrix features

add to the CRP contribution, presumably

along with its attendant scatter, this variability

may be much more serious in sensitive high

copper and high nickel steels. This is of

particular concern at high fluence, where the

125

100

75

50

25A

0

- 0

0.

I I 

0

0 1

-25

0 2.5 5 7.5 10

CFmf

matrix feature contribution becomes more

significant. Indeed, based on these

considerations it has been shown that AT in

excess of upper bound estimates from the

NUREG model based estimates might be

anticipated in some cases [Odette and Lucas,

1999]. However, this potential nonconservatism may be mitigated by the

simplified treatment of phosphorous in the

NUREG model. In particular both synergistic

interactions with copper and phosphorous

depletion at high fluence would reduce actual

AT compared to the NUREG model

predictions. Additional data generated in the

IVAR program will help to resolve these

issues.

* CM-T14

O0 CM-PB

A VM-PB

12.5

Figure 5-6 Variation of Aay with a matrix feature chemistry factor given in Equation 5-2

for low copper CM and LV steels for capsules T14 and PB. The unalloyed VM steels are shown as

filed triangles.

42
200

150

100

50

0 z 

.2 .2

':4

z

Z Z

:4

._I. >

Figure 5-7 Acy for various V-series alloys with no copper irradiated in PB.

'-- Plate MF i

'-Weld MF !

0 plate

a weld

CM

LV

0 0.25 0.5 0.75 1 1.25

4 t (1o23 n 2)

Figure 5-8 a) Comparison of NUREG matrix feature predictions with low copper French power

reactor surveillance data; b) plot showing scatter in Aay in low copper steel irradiations

in this study and unexplained differences between CM and LV alloys.

43

V-PB 0.0%Cu

HinF]

100

7S

0

I.- 50

25

18.0 18.5 19.0 19.5 20.0

Log t(lO1 9IrdCM2 )

- - l
6 EVALUATION OF THE MATRIX COPPER CONTENT

A key issue in developing embrittlement models

is determining the amount of copper in solution,

thus available for precipitation under irradiation.

Bulk copper (Cu.) that is tied up in coarse

precipitates, or other phases (e.g., copper sulfide

inclusions [Fisher et. al, 1985; Fisher and

Buswell, 1987]), at the start-of-life does not

contribute to subsequent hardening and

embrittlement. The difference between Cu, (in

wt%) and effective dissolved, or matrix, copper

content (Cu.) is deternined by both the alloy

composition and heat treatment history. Preprecipitation of large E-phase copper particles,

primarily on dislocations, during tempering and

stress relief (SR), is a primary mechanism

controlling Cu. below bulk levels. The Cu.,

approaches thermodynamic solubility limits

after long times at around 600°C. However,

thermal precipitation is a complex process. As

well as time-temperature kinetics, alloy

chemistry (thermodynamics) and microstructure

likely influence pre-precipitation behavior. In

NUREG/CR-6551 a statistical fit to the overall

PREDB gave the maximum Cu., (Cu.) of 0.3%.

This result is broadly consistent with data trends

and various estimates in the literature, although

both higher and lower values have been reported

[Odette, 1995; Odette and Lucas, 1986, 1988,

1997; Buswell et al, 1993, Williams and

Phythian, 1996; McElroy and Lowe, 1996;

Williams and Phythian, 1996; Kenway-Jackson

et. al, 1993; English et al, 19971. Indeed, both

information in the literature, and more recent

analysis of the PREDB, have suggested that the

actual value varies, depending on the alloy

nickel content [McElroy and Lowe, 1996;

Odette and Lucas, 1990, 1998; Williams and

Phythian, 1996].

Accurate direct estimates of Cu. require detailed

and costly measurements that push, or even

exceed, the capabilities of state-of-the-art

modern microanalytical characterization

methods. While some of these studies have been

carried out, much more work will be required to

provide a useful microanalytical database

necessary to develop models for Cu.. However,

mechanical property changes are the issue of

prime concern and can provide indirect

estimates of matrix copper. Thus, the variable

stress relief (VSR) study was primarily intended

to conveniently assess the effects of the heat

treatment and nickel content on Cu. by simply

assessing the corresponding effects on Ay.

While this objective was largely achieved, the

results of the VSR study also showed that heat

treatment effects extend well beyond matrix

copper levels, and influence both the start-oflife properties and microstructures of RPV steels.

The start-of-life condition, in turn, affects the

irradiation-induced changes in mechanical

properties.

The use of a large set of small split-melt model

steels with a wide range of compositions and

heat treatments in the VSR study resulted in

confounding effects that complicated assessment

of Cu. in a fraction of cases. The complications

included large o variations and variability

(scatter) for some heat treatments. These t,

variations also reflect underlying microstructural

differences. These problems were exacerbated

by the effects of banding and ghost lines found

in a number of the CM forgings, coupled with

the use of a slow cooling schedule of about

8°C/h. The as-tempered alloys and the CM

alloys that were furnace cooled following stress

relief were more stable and less variable.

Thus for purposes of assessing the matrix

copper, the VSR Au, data were carefully

screened to avoid or minimize the confounding

effects noted above. The screened VSR data

were used to assess the Cu, based on the

NUREG model. The NUREG-AT model was

first converted to corresponding Au, predictions

using analytical &T-ME, relations (see Appendix

A). The NUREG-Aa. model was then used to

calculate values of Cu. for the VSR data set as

well as alloys subject to different heat treatments

in the PB experiment, consistent with the

measured Acr, for the specific alloy and

irradiation condition (phosphorous, nickel

content, flux, fluence and temperature). Other

44
modifications of the NUREG-&i. model to

account for flux-composition and product form

effects are discussed below.

A second approach to estimating Cu. from the

As, data was based on examining deviations

from the NUREG model form

AaF= A + BX (6-1)

where X is the NUREG copper factor, X = 0 for

Cu, 0.072% and X = (Cu.-0.072)h 7s for Cu.

> 0.072%. In this case, no assumptions were

made about A and B, or their dependence on

embrittlement variables. The A and B were

found by fitting the A;y data from sets of alloys

with different copper levels, but nominally

similar compositions and heat treatment. Minor

corrections were made for nickel differences in

the LV alloys (LG, Li at 0.74% vs. LI with

0.85%). The fits to Equation 6-1 were restricted

to alloys with copper levels below the maximum

precipitation limit L. 0.22% for the standard

stress relief condition and S 0.33% for the astempered condition). The A and B fits were then

used with the measured A; for higher copper

steels (not used in the fitting) to calculate Cu. as,

Cu. = [(A - A)IBl]'5+ 0.072 (6-2)

The second method was applied to A, from the

T4, T14 and PB capsules as well as some

averaged data from the VSR study.

The A&-based estimates of Cu, were

complemented by several other sources of

microanalytical information including field

emission scanning transmission electron

microscopy (EGSTEM), Seebeck coefficient,

electrical resistivity and small angle neutron

scattering (SANS) measurements. The

FEGSTEM provides direct evaluation of the Cu.

subject to uncertainties and assumpfions used in

the analysis. The Seebeck coefficient (S) and

electrical resistivity (p) evalutions were also

based on deviations from low copper linear

trends in S and p plotted against Cub, indicating

pre-precipitation. The limited SANS data

provided direct evidence of the effect of stress

relief on the volume fraction of CRP's from the

PB experiment.

6.1 General Effects of Heat

Treatment on cy and Ay

To provide a proper framework for assessing

Cu., it is necessary to begin with a description of

the general effects of heat treatment on a, as

well as possible effects of ;, on Ac;y. This

provides a basis to identify the subsets of data

that can be used most reliably to estimate Cu.

As is a general characteristic of quenched and

tempered low alloy steels, the ;. in RPV steels

decreases with increasing stress relief time (tr)

and temperature (T.). This trend is shown in

Figure 6-1 where the a, data from the VSR

study are plotted as a function of a temperature

compensated time parameter Pn defined as

Pn = iexp(-260,000RT.(i))t.(i) (6-3)

Here T. is in °K, t,, is in h and i represents Tk-t

increments of 8°C-lh at the various stages of the

heat treatment, including the 660°C-4h temper,

the actual isothermal ,-T,,stress relief and

subsequent slow cooling that was truncated at

450°C. For most stress relief conditions, the ;,

is well behaved; but substantial softening

generally occurs at high PT,. However, in some

cases a large decrease in a, is observed

indicating instability in the alloy microstructure.

Such instability is indicated by the data below

the horizontal lines in Figures 6-la to 6-1c. The

reasons for such large reductions in c are not

known.

Thus the following question must be addressed.

Does the lower cr affect Ay due to mechanisms

that are not related to copper pre-precipitation

and Cu.? Figure 6-2a illustrates the general

trend to lower A:, with increasing c, for the set

of high copper (- 0.42%) CM alloys with

varying nickel content. The effect is minimal

for the low nickel (0.0%) CM18 alloy and only

apparent for the lowest (,data in the case of the

intermediate nickel (0.85%) CMl9 alloy.

However, the trend appears to be more

systematic for the high nickel (1.69%) CM20

45
alloy. Since all these alloys contain more than

0.4% copper, pre-precipitation probably

contributes to the a,-aG trend in this case.

Figure 6-2b shows similar plots for intermediate

nickel (-0.85%) alloys with 0.22% (CM16) and

0.33% (CMI 1) copper levels. Both alloys show

a trend of lower Aa, with increasing a, at least

for the highest and lowest a,. However, little or

no pre-precipitation is expected in CM 16, with

only 0.22% copper. Thus other explanations of

the a,-Aa, trend must be sought in this case.

Possible reasons include:

1. Random variations in the ay of the specimens

used for both the unirradiated baseline and

irradiated testing produce random scatter in

boy. However, corresponding plots of aY,

versus Aa, will show an apparent bias of the

type observed in Figure 6-2. The apparent

bias increases with the scatter in aY,. Since the

number of redundant tests in the VSR study

were limited, and in some cases the scatter

was rather large, such apparent bias is to be

expected. The scatter in ay adds to the scatter

in Ar, and the Cu. derived from AO.

However, the apparent bias does not directly

confound assessment of trends in heat

treatment effects of Cu,.

2. The individual contribution of the irradiation

induced features (ai) is less than Aa,, since a

must combine with other pre-existing

dispersed barrier contributions (a.). The a.

strength component is due to fine scale

carbides and dislocation intersections that are

strong obstacles dislocation slip. The

carbides coarsen and the dislocations recover

with increasing Pn, thus decreasing the

number of pinning points and a,. The

superposition of the cs. and a strength

contributions falls between linear and root

sum squares laws as [Odette and Lucas, 1998;

Foreman and Makin 1967]

Aa, = Oa,, + (I-O)("2 + a,,2)"- aXE (6-4)

Here 0 (= 0 to 1) is a superposition parameter

that depends on the strength of the weaker

irradiation induced barriers, as discussed

elsewhere Odette and Lucas, 1998]. For

example if a,= a,= 150 MPa, and B = 0.4 (a

typical value for CRPs), then As, is only 97

MPa. However, if a,, is decreased to 50 MPa,

Aa,, increases to 125 MPa. That is, while a

does not change, the net Aa, increases by

about 25% because of the lower cr,. The

solid line in Figure 6.2b shows the predicted

effect on Aay, of variations in a. from 40 to

210 MPa for a,= 185 MPa and 0 = 0.4.

Note the (, scale assumes that there are 300

MPa of contributions to the total yield stress

other than a.. Thus, at least part of the

variation in A, with c,can be understood in

terms of the strength superposition

mechanism. An increase in AG, with a

decrease in a. due to stress relief, potentially

confounds estimates of Cu,. based on the

irradiation hardening data.

3. The recovery of dislocation structures during

heat treatment can also influence the a, itself.

A lower dislocation sink density (pd)

increases the radiation enhanced diffusion

coefficient, thus accelerating CRP growth,

shifting the Ma, versus fluence curve down to

lower fluence (t). In the simplest case ay -

a+ pPd and the ~t at a specified Aa, is

roughly proportional to Pd. Thus there an

indirect physical relation between Aa, and a,,

mediated by p. The dashed line in Figure 6-

2b is a crude estimate of this effect for CMI I

in the VSR study. Thus, dislocation recovery

during heat treatment also potentially

confounds estimates of Cu, based on Aa,

data.

It must be emphasized that the increases in Aa,

due to both superposition effects of reduced (Y.

and dislocation recovery leading to faster copper

diffusion are real consequences of longer t and

higher T, Hence, these mechanisms should be

considered in future research, including their

influence on the start-of-life Charpy properties

and the corresponding relation between AT and

Aay.

46
IE-14 IE-14 2E-14 2E-14

F1t(h)

IE-14 2E-14 2E-14 3E-14

P ()

3E

a CMi8

* CM16

* CM5

E-14

MI9

* M1II

* CM3

3E-14

600

500

i 400

2 300

20D

1001

* CM20

CM12

* CM13

5E-15 IE-14 IE-14 2E-14 2E-14 3E-14

PTt (h)

Figure 6-1 Variation of a; with PT for a) CM5, 11, 18 b) CM3, 11, 19 c) CM12, 13, 20

47

500

450

400 

350

300

250-

SE-1

a a

16.18

*OA

t * & 

S o

.9 . 9 -

S

500

450

400

e' 350

b

* * ik 6

* *4 * n8

0 9

0 A 0

300

250

SE-15

c

a

* 9v0 * *o

0 0

0 0 4

9 0

-

. . . .
* CM 18 a

* CM19

* CM20

: r 0 o .t 

4. *s S

** . S

EU O

a U---- ~

50 150 250

a 425

350 325

75 125

Aay (MPa) Aa. (MPa)

Figure 6-2 Variation of Ay with Y (unirradiated) for a) high (.42%) copper CM alloys, b)

intermediate (0.8%) nickel, 0.22% copper alloys.

250 - VSR & PB

200 

0

150 

'100 

50

0 0 0.--p 

0 0.25 0.5 0.75

* AT

o 590

O 607

1

x

Figure 6-3 Variation of Ay with X for irradiated intermediate nickel alloys.

500

450

400

350

175 225

-a

50 525
However, it is not possible to completely

disentangle . reductions and dislocation

recovery from the effects of copper preprecipitation at this time. Indeed, this may not be

necessary if the viewpoint is adopted that Cu.

derived from A:y data is a practical surrogate for

all three of these real mechanisms. Nevertheless,

the following procedure was used to screen the

data for use in assessing matrix copper levels.

1. In order to mininize the effects of scatter,

preliminary hardness measurements were

made on the end tabs of most of the VSR

specimens. Large variations in the

unirradiated yield a, and/or differences in

end-tab hardness between the specimens used

for baseline and irradiated testing were used

to screen the quality of the Ac, data, and to

eliminate the points of suspicious accuracy.

2. The Ac;y data for alloys showing significant

mechanical instability during heat treatment,

shown as the open symbols below the dashed

lines in Figures 6-la to 6-lc were not used to

estimate Cu,.

3. The Ac;, data for alloys that were stable, but

that showed a significant reduction in 0y

relative to the other stress relief conditions

for a particular steel, were also not used to

estimate Cu.. These are shown as the other

open symbol in Figures 6-la to 6-lc.

The remaining filled symbols in Figures 6-la to

6-ic fall within cy and Ac;y quality limits judged

to be useful for estimating the effects of heat

treatment on matrix copper. It should be noted

that this is scientifically and practically a

conservative approach. Beyond the issue of

scatter, if the other mechanisms contribute some

residual fraction to reducing Acy due to stress

relief treatments, the corresponding estimates of

Cu. will be biased towards higher levels of

matrix copper.

6.2 Estimates of Matrix Copper

Levels

62.1 Estimates of Cu. Based on Au

Deviations From the Low Copper X irend Line

Results of the evaluation of Cu. based on the

method represented by Equations 6-1 and 6-2

are presented first. Figure 6-3 plots the Aay for

intermediate nickel (- 0.84%) alloys versus X =

(Cu.-0.072)°"", for both the as-tempered

condition and averages for selected points for

the 590 and 607°C stress relieved conditions. In

order to increase the reliability of the key

baseline comparison data, the as-tempered A6y

data for the VSR study were averaged with the

corresponding data from the PB irradiation at a

similar flux, fluence and temperature. These

averages include a small adjustment, based on

the NUREG-AC;, model, to account for minor

differences in fluence (0.85 versus lxl 2 n/in2)

and irradiation temperature (288 versus 290°C)

for PB and VSR, respectively. The average

values for VSR data are for the t, of 48 and 96h

at the Tuof 5901C and the t of 24 and 48 h at

the T., of 607°C. The Pn at these two T, span a

similar range. The data points at X = 0 are for

the CM3 and CMIO alloys with CuLi = 0.02%.

The as-tempered PB and averaged VSR data

overlap at lower Cub. The as-tempered PB data

follow a linear trend with X up to approximately

Cubk = 0.42% (CM 19) but the 0.33% copper

alloy (CM I ) in the stress relieved condition

deviates from this trend. The least square fit to

the 'low' copper data (filled symbols and solid

line) is Ac,= 20 + 365X MPa. The 'high'

copper Ac;y data (open symbols) for CMl2 in

both as-tempered and standard stress relief

conditions and CM 1 I and 19 in the standard

stress relief condition fall below the trend line,

indicating that Cum < Cubk in these cases.

Table 6-1 summarizes the Cu. found by solving

Equation 6-2, which in this case is X., -

[(Ac,(meas.) - 20)/365 and Cu, - X- 25 + 0.072.

A similar analysis was carried out for the

intermediate nickel CM and LV Aa, data from

the T14, T4 and PB capsules. The results are

shown in Figure 6-4a to 6-4f and the

49
Table 6-1. Estimated Cumfor Intermediate Nickel High Copper CM Alloys in VSR Study

Alloy CUbk Cum- AT Cum-590'C Cu,-607°C

CM I 0.33 0.33 0.28 0.28 CMI9 0.42 0.41 0.29 O.8

CM12 0.43 0.23 0.23

Table 6-2. Estimated Cum for Intermediate Nickel High Copper CM Alloys in Various Capsules

Alloy Capsule Bulk Cu Matrix Cu - SSR Matrix Copper

as-tempered CMIr TT4 F 0.26

CMIg TI4 0 : 0.27

CM 12 T14 0.86 0.21

CM18 T14 0.43 0.22

CM20 14 0.42 0.27

LC T14 0.41 0.34_ _

Wr T~1 4 04 0.30_ L T1 F _T__1 0.36

LK T0.80 0.24

Ll1T PB 0.42 0.25_ _

LK PBW- 0.80 0.20

LOT= PB 0.42 0.41

1MI PB 0.42 0.43

CM 12 PB 0.86 0.44

CM18 PB _ 0.35

CM20 PB ~ _______OA 0.35

CM4I T0 33 0.28_ _

CMI9 T4 0.42 0.29

LC T4 0.41 0.25 _

Ll T4 0.42 0.26

LK T4 0.80 0.18 _

LO T4 0.41_ 0.34

50
200

150 150 

2 100 /i10

50 IN Low C/ 0 Low Cu cOr.

50 ir E3 Low Cu - 50 0 High Cu

0 High Cu I! LowCu

0 0.25 0.5 0.75 0 0.25 0.5 0.75 1

x x

200 200

CM-T4 c d LV-T4

50 Lo a / Low Cu cor.

150 00 * Low0Cu50 0 O igh Cu

! Z O~~ High Cu . Low Cu

0 0 .25 0.5 0.75 1 0 0.25 0.5 0.75 1

X 0

CM-PB ;/e 20LV-PB 1 f

. 0 . 0 ' 200/

0~~~O

150 tsr U \ /50 ' ISOh/ o 

I 0~~~~~~~~

dF F 100 / gr=r40h 6 e100 /

<1 / tsr 8 h O Low Cu

fal O [/ AT 5C j/ES O H figh Cu AT

0 . ,O SR a .o3 Low Cll cor.

0 0.25 0.5 0.75 1 0 0.25 0.5 0.75 1

x x

Figure 64 Variation of Acy with X for intermediate Ni LV and CM alloys in capsules T14 (a and b),

T4 (c and d) and PB (e and f)

51

200
corresponding estimates of Cu, are given in

Table 6-2 for the SSR condition.

6.2.2 Estimates of Cum Based on the VSR Ay

Trends and the Modified NUREGICR-6551

Aay Model

Figure 6-5a to 6-Si summarizes the hay results

for the screened data set for the various heat

treatment conditions. The dashed line is the

measured Aa for the as-tempered condition to

help guide the eye to Aa, differences for

various T, and t. The general trends can be

summarized as follows.

1. In the steels with Cu* 0.3%, stress relief

following tempering systematically reduces

Aa.. The strongest effect is seen in high

copper (0.86%), intermediate nickel (0.8%)

CMI 2 alloy and the intermediate copper

(0.43%), low nickel (0.0%) CM18 alloy.

Similar but much weaker trends are observed

in the intermediate copper (0.42%), high

nickel (1.69%) CM20 alloy. The intermediate

nickel (0.8%) alloys, CMI I with Cut, = 0.33%

and CMI9 with Cu,,= OA2%, fall in between.

There is also a general trend towards larger

AoYat higher T. in CM12, CMl9 and CM 20.

In the cases of CMI9 and CM20, the A, for

the T, = 641 °C stress relief are similar to the

AC. for the as-tempered condition. The effect

of t is clearest for the CM 19 alloy for T.

from 590 to 6240C. This trend is also seen in

some other cases (CMI I at 607 and 624°C,

CMI 8 at 590°C), but is reversed, or within the

scatter, for the other high copper alloys and

heat treatments.

2. For the intermediate nickel (-0.85%) low

copper alloys with Cubk = 0.02% (CM3) and

Cu,; = 0.1 1% (CM13) the a,for the stress

relieved and as-tempered conditions are

similar, and suggest no general trend. The AY,

are lower for the stress relieved conditions for

the intermediate nickel (0.85%) low copper

Cu,, = 0.02% (CM5) steel containing high

phosphorous (0.035%). This may indicate

some phosphorous removal from the matrix

during stress relief, but the magnitudes of the

differences are small and probably within the

data scatter. Contrary to the general trend, Aa,

are generally higher for the stress relieved

conditions of the intermediate nickel (0.85%)

steel with intermediate Cubk = 0.22% (CM 16).

This may be a partial consequence of the

mechanisms associated with reductions in c,

and dislocation recovery discussed previously.

However there is no overall trend in the CM 16

data, and this deviation from the norm is also

probably primarily associated with scatter.

The trends in the VSR Aca, data are certainly

consistent with significant pre-precipitation in

high copper steels. The behavior of the CMI I

alloys with 0.33% Cu suggests that the

effective maximum copper following typical

T,-t,, schedules is 0.3% or less. Further, the

results are qualitatively consistent with more

efficient pre-precipitation at very high copper

contents (e.g., CM1 2) and decreasing preprecipitation with increasing nickel content

(e.g., CM 18,19, 20).

Further quantification of these results was

carried out by using the modified NUREGA, model to calculate the Cu, required to

produce the measured a, for the various

alloys and heat treatment conditions. The

basis for the modified NUREG-Aa, model and

Cu, predictions are described in more detail in

Appendix A. Briefly, however, as shown in

Section 5, the NUREG-Ao, model predictions

are generally very consistent with the data

from the intermediate flux T14 capsule. This

consistency was found using the NUREG CRP

term for welds for all of the steels irradiated in

this program, irrespective of their specific

product form. Similar comparisons show that

the NUREG-Aa, model overpredicts the

measured Acy, from the high flux T4 capsule.

The difference between the T4 (high flux) and

T14 (intermediate flux) data suggests a flux

effect on AGr A strong and systematic effect

of flux has also been observed in several other

IVAR data sets. Low flux accelerates the CRP

evolutdon and shifts Aa, to lower fluence.

The discrepancy between the NUREG-Aay

model predictions and T4 observations (or

52
In N .

CM3 a

Q MLrp_

607 624

T (°C) - t(h)

-lN

590 641

1u

75

50

25

U

AT

n

CM5 b

........ ....... .. r

r

F L A AT

590 607 624

T(°C) - t(h)

607 624

T(°C) - t(h)

185t

160

135

CMII c

.. _. . ...............

I . -1 11 - I

' AT

641

I rnr 

...... .............. ... ... ...............

CM12

L.... le i h . ].. . .

590 607 624

T(°C) - t(h)

r.

-'N AT

641

590 607 624

T(°C) - t(h)

641 590 607 624

rC-t(h)

Figure 6-5 Variation of Aay with SR condition for a) CM3, b) CM5, c) CMI I, d) CM12, e)

CM13, f) CM16

53

751

b 50

25

A

dU.&W

1951

1701

145

120

590

100

641

I Afk 

A' ' _ _i ' . . i - - ' .

1%I n%

-

*W

v

ui
i

590 607 624 641

225

CM19 h

20 .

1 7

150

125 * R AT

590 607 624 641

T(Q-XQv

oilI

a

tp

44

AT

590 607 624 641

rQ-tm

Figure 6-5 (cont.). Variation of cTy with SR condition for g) CM18, h) CMI9, i) CM 20

54
between the T14 and T4 results) increases with

increasing alloy nickel and manganese

content. The interactive effect of composition

and flux is consistent with defect trapping by

these elements. Trapping increases defect

recombination, hence, slows radiationenhanced diffusion. Slower diffusion shifts the

A;-curves to higher fluence. Details of the

ongoing investigations of the effects of flux

will be presented in the future. For the present

purposes, however, the NUREG-A,& model was

further modified to account for composition

dependent flux effects by including a nickel

dependent flux-factor f,(Ni) = I(l+yNi, y -

1.3) that decreases the effective fluence as Ot,

= ft, in the CRP term of the NUREG-ca,

model. This flux-dependent version of

NUREG-A&ay model fitted the high flux T4

data was used to estimate Cu. for the high flux

VSR data.

Figures 6-6a to 6-6e show the Cu. estimates

for the VSR study plotted against t The

corresponding T. is indicated by the various

filled symbols and Cub, by the unfilled circle.

The Cu. in all the high copper (> 0.3%) alloys

are substantially less than bulk levels. For

intermediate nickel (0.84% Ni) alloys, Cu.

falls below 0.25% Cu. The Cu. renerallv

decreases with increasing t,,, and more weakly

with decreasing T, although individual data

points scatter around these broad trends. The

low nickel CM 18 alloy (0.02% Ni) shows a

rapid drop, approaching 0.2% Cu at 40 h for

T,= 590'C. In contrast, the high nickel

(1.68% Ni) CM20 decreases less, with Cu. -

0.29 after the longest t at the lowest T,

Figure 6-6f compares the Cu, trend in CM 19

with those for low copper alloys with Cu, =

0.22% (CM16) and 0.11% (CM 13). For

clarity no distinction is made between the

various T,, in this case. The data for the low

copper steels scatter around Cu.

Table 6-3 summarizes the Cu. estimates from

the VSR study for the as-tempered condition

and the average values for the stress relieved

conditions for 48 and 96h at 590°C and 24

and 48 h at 6070. A similar analysis was

carried out for as-tempered and limited stress

relief data from the PB experiment. The

results are shown in Figure 6-7 and the

corresponding Cu, estimates are given in

Table 6-4.

Averaged results of the various estimates of

Cu, for high copper, intermediate nickel steels

following typical stress relief treatments from

about 590 to 610°C are summarized in Table

6-5. The overall average for the intermediate

nickel steels (CMI 1, 19, LC and LJ) with

nominal levels of Cu,: from 0.3 to 0.4% is Cu.,

- 0.28%. In alloys with a high Cuk of 0.8%,

the matrix copper is lower, with Cu. - 0.21%.

This can be understood based on higher preprecipitation nucleation and growth rates in

steels that start with higher copper in solution.

The matrix copper in the high nickel alloy

(CM20) is larger with Cu, - 0.31%. The Cu., -

0.27% in the low nickel steel (CM1 8), is

similar to that for the intermediate nickel

alloys; however, this limited data may be

biased by the high estimate of Cu, from the

PB capsule.

These estimates of Cu., based on Au,

measurements are subject to considerable

uncertainty, but reflect relative trends and the

'practical' effects of stress relief. They

support the following general conclusions:

1. Typical heat treatments in the range of

590-6101C for periods between 20 and 80

h of intermediate nickel, high copper (Cu,

5 0.3%) steels result in a reduction of Cu,

to below 0.3% Cu, with even lower values

frequently observed.

2. General trends towards decreasing Cu. with

decreasing nickel, very bigh copper, lower

T. and longer t,, are observed. However, the

data do not allow precise quantification of

these effects.

3. The best maximum copper fit value of

0.25%Cu for intermediate nickel welds in

the PREDB is credible and consistent with

these result of this study. The observation

55
O..

0.1

0.1

0.

;F0.

0.:

0.'

0.

5 a 45 CMI I

40 

35

30 2 -

25' *

2'

11CI ' ' 

' jO

AT

* 5900C

* 6070C

* 6240C

o Bulk

25 50 75 100

th,(h)

O.50L 

0.40 . CM18 c

0.40

0.35 a

0.30 * 0

0.25 A

0.20 0

0.15o 25 50 75 1(

AT

* 590°C

* 607 C

A 6240C

v 641 C

° BULK

0.

0.

0.

ae 0.

3 0.

0.

0.

0.

U

5. 

4 5 CM12 b

35'

30 

25t Y v

20 * *

147 I A JO 25 50

th,(h)

75 100

0.5 d'

0.45 CMI9

0.4

0.35 

0.3 A 3 

0.25 * S

0.2

0.15o o% o U 

tNt(h)

t a

tbg(h)

0.51

0.4

OX

e CM20

.4

.

0.21

0 25 50

tt,(h)

75

AT

* 5900C

' 607 C

A 624 C

' 641°C

° BULK

Ue

100 N o

tb(h)

Figure 6-6 Aoy-based NUREG model prediction of the variation in Cuin with SR time

for the VSR data for a) CMI 1, b) CM12, c) CMI 8, d) CM 19, e) CM20;

f) Comparison of high Cu CMI19 to two lower copper steels

56

s

0

A

-

0

AT

590 0C

6070C

6240C

641°C

BULK

AT

* 5900C

* 607 C

A 624°C

Y 641 C

o BULK

0. I

1 . .

)O b

r
0 CM 19

CM20

A CM18

4: CM12

In~~~~~~~~~~~~~~~~~~

tht (h)

Figure 6-7 Acry-based NUREG model prediction of the variation in Cum with stress relief time for the

PB data for CM12, CM18, CM19, CM20

Table 6-3. Estimated Cum for High Copper CM Alloys in VSR Study

Alloy CUbk AT-CUm 590°CCum 6070C-Cu

CM 1 0.33 0.29 0.26 0.25

CM19 0.42 0.34 0.25 0.29

CM12 0.86 0.38 0.21 0.21

CM18 0.43 0.48 0.21 0.28

CM20 0.43 0.34 0.30 0.31

Table 6-4. Estimated Cum for High Copper CM Alloys in the PB Study

Alloy Cubk AT-Cum 607'C/8h-Cum 6O7 0C40h-Cum 607'C-80h-Cum

CM12 0.86 0.37 0.32

CM18 0.43 0.47 - 0.35

CMIg19 0.42 0.36 0.33 0.33 0.29

CM20 0.43 0.33 - 0.35

57

0.20
Table 6-5. Averaged Cum Following Heat Treatment at -590-610'C

Cubk/Ni T14 T4 PB PBSR VSR-1 VSR-2 AVG

CMI 1 0.26 0.28 0.25 0.28 0.27

CM19 0.27 0.29 0.31 0.27 0.28 0.28

LC 0.34 0.25 0.30

Li 0.30 0.26 0.25 0.27

CM12 0.21 0.32 0.22 0.23 0.24

LK 0.24 0.18 0.20 0.21

CM20 0.27 0.35 0.32 0.31

CM18 _ 0.22 0.35 0.27

that this maximum is lower in low nickel steels

and higher in high nickel steels is also broadly

consistent with the present results. However,

these statistical fit results do not preclude a

slightly higher actual maximum copper or a

heat-to-heat variability in this value depending

on many details of the alloy and its processing

history.

6.3 Microanalytical Assessments of

Cum

The Cu. estimates based on Aa, data have been

complemented by limited microanalytical

studies that are summarized below. These

include field emission scanning transmission

microscopy (EGSTEM) carried out at AEA

Harwell, electrical resistivity and Seebeck

coefficient measurements and small angle

neutron scattering (SANS).

63.1 Field Emission Gun Scanning

Transmission Electron MiScroscopy

Table 6-6 summarizes the FEGSTEM results on

Cu. for CM 19, CM 20 and CM 12. Most of

these measurements were made after a so-called

UK quench and temper (Q&T) which differed

somewhat from the UCSB base Q&T. However,

the alternative Q&T are not expected to make a

substantial difference to the Cu. results.

An intercomparison of these and other results is

given below. However, overall they are very

consistent with results of the Cu. assessment

based on the Aa, data trends.

63.2 Electrical Resistivity

As discussed in Section 3, electrical resistivity, p,

of metals and alloys can be precisely measured.

While there are many contributions to resistivity,

in dilute alloys the total is usually dominated by

the resistance of the pure solvent (e.g., Prj plus

dissolved solutes (e.g., Cu, Ni, Mn,...). with lesser

contributions from microstructural defects, trace

impurities and precipitates, p (Rossiter, 1987].

In RPV steels, these 'other' factors typically

contribute about 3 f-cm, out of a total of more

than 20 pacm. The p of simple dilute binary

alloys can be precisely related to the solute

distribution. Alloying and impurity elements

located in large precipitates contribute little to p

and to first order can be neglected [Rossiter,

58
Table 6-6. FEGSTEM Estimates of Cum for CM12, CMI9 and CM20

Alloy Tht(0

C) Cum Cum

(As Quenched)t (thi short -h) tht = int. (h) tht long (h)

CM 19 550 0.35 *0.05

CMI9 600 0.35 ±0.05 0.34 ±0.04 (8) 0.32±0.05 (40) 0.25±0.05 (80)

CMI9 630 0.35 ±0.05 0.29 ±0.05 (8) 0.30±0.03 (40) 0.24±0.05 (200)

CMI9 660 0.35 ±0.05 0.36 ±0.03 (4) 0.31±0.03 (40) _

CMI9* 0.42 :O.03 (8) 0.28±0.03 (40) 0.27±0.07 (80)

CM12 660 - 0.49 ±0.05 (4)

CM12 600 0.28±0.05 (40)

* Tempered at 660°C for different times; stress relieved at 600°C

t UK base was as quenched

1987]. The resistivity coefficients (ks) of

common elements (i) dissolved in iron are

known or can be established. For example, in

the case of copper, k,, - 3.5pG-cm/wt%

[Mathon, 1995]. In the dilute solution range,

the resistivity coefficients are approximately

independent of composition (p. = kjC,),

although deviations from such linearity occur

for some elements like manganese (perhaps

due to clustering). Further, to first order, the

net contribution of different solutes in more

complex dilute solutions is simply the linear

sum of the individual contributions.

P - Pie +pm+ £kjCjk (6-5)

Consider an idealized case of a set of complex

alloys that are identical except for the amount

of one element x illustrated in Figure 6-8. In

this example, the p of the alloy with C, = 0 is

Po = Pi +P. = 2 2 p l2-cm and k = pcml%x. Based on the assumptions listed above

the p of the alloys would increase with the

bulk solute content C,, up to the point where

precipitation occurs at p. For equilibrium

conditions the p would remain constant at

higher C,1 (filled circles). The break point at p

= 23.5pfl-cm defines the solubility limit of C^,

= 0.3%. Thus alloys with C2b> C,, and

measured p., > p, (e.g., the open circle with

Cb = 0.6% and p.,= 24 pfl-cm) reflects nonequilibrium levels C.,, in solution. le C,b,

can be determined by the fit to the alloys with

C,b less than the solubility limit (dashed line)

as

C.1 = (p, - Po)/k = (24 - 22)/5 = 0.4%.

(6-6)

Precipitation following additional stress relief

or irradiation would be reflected in p.2 (=

23.75) < p,,, hence, lower dissolved Cx ,2

(=0.35%).

Such idealized conditions cannot be met in

practice, except in the simplest cases.

Complications include alloy-to-alloy variations

in solutes other than x, including the effects of

precipitation during processing and

confounding variations due to other

uncontrolled contributions from

microstructure. However, the approach

illustrated in Figure 6-8 can be facilitated by

calibrating the k,. Plus a general alloy category

term, pj, accounting for all other factors for a

particular alloy class j, including contributions

from tnicrostructure and precipitates. Further

a term can be added to account for any second

order nonlinearities in the composition

dependence of p, = k,C, +k1' C,2. Thus

Equation 6-5 is modified as

p - pj + 1(k,C1 +k'C 2) (6-7)

59
Fitting Equation 6-7 requires a set of alloys

with a range of known compositions. The k,

can be found only where there is a significant

variation in C,. Further, the qC must be

corrected for the fraction that is not in

solution, thus not contributing to p. For the

present purposes this means that alloys with

'high' copper cannot be used in the fit, since

the corresponding Cu,,. are not known.

However, since the corrections are generally

small, other elements were considered to be in

solution at bulk levels (e.g., Mn) or completely

precipitated (e.g., C), hence lumped in with p,.

Finally, it is assumed that the p accounts for all

other factors in alloys in category j.

Equation 6-7 was fit to alloys in four classes:

a) the VM series of simple ferritic alloys with

variations in Cu, Mn, C and N and heat treated

24.5

0~

23.5

22.5

I

21.5

0 0.2

to retain copper in solution; b) the LV alloy

series in its standard stress relief condition and

one high copper alloy in the as-tempered

condition (LO); c) the CM alloys series in the

standard stress relief condition; and d) the CM

alloys series in the as-tempered condition.

The ki terms included Cu, Ni, Mn, Si and P.

Only Mn benefited from a nonlinear k,. term.

The effects of other compositional variables

(C, N, Mo,..) were generally too small to be

established and were lumped into the p, term.

As noted above, all alloys were assumed to

have dissolved solute levels equal to the bulk

chemistry with the exception of copper.This

clearly is an approximation, particularly for

the manganese which is incorporated into M3C

phases in carbon containing alloys, as well as

for low solubility elements like phosphorous.

0.4 0.6 0.8

CX

Figure 6-8 Idealized variation of resistivity with content C1 of solute x.

60

a I * Ik

p = CX +22 - kx

0~~

wS

Cxe

p 
The resistivity data trend themselves were used to

guide the assumptions concerning the definition

of low copper alloys fit to Equation 6-7: VM

Cu, = Cub; LV and CM-standard stress relief

Cu., up to 0.22 % copper; CM-as-tempered Cu,

up to 0.33% copper.

The k1 and p, were used to normalize the

measured p to a common composition and

alloy condition: Mn = 1.6%, Ni = 0.8%, Si =

0.15% P = 0.005%, Ti = 0.0 and VM. Figure 6-

9 shows the resulting variation in a normalized

resistivity, p., with copper. The overall standard

error in the fit is :t0.25 pfl-cm, or only about I

to 3% of the measured values. The individual fit

parameters are given in Table 6-7. The k; are

also generally in agreement with published

values. The low copper data used in the fitting

are shown as the filled symbols. A least squares

14

13

0-,

Q

12

11

10

9 -- -

0.00 0.25 0.50 0.75

fit line to all this data gives a k, = 3.54 pflcm/% Cu in excellent agreement with results in

the literature [Mathon, 1995]. The standard

error for this fit to the p. data was ±0.2 pfl-cm.

The open symbols are for the high copper alloys

not used in the fitting, since their Cu. were

unknown.

The high copper p. data for the CM alloys fall

below the low copper fit line, indicating preprecipitation. This is also the case for the

intermediate nickel (0.85%), high copper

(0.42%) LC alloy. However the other high

copper LV alloys with lower (LA and LB) and

higher (LD) nickel contents fall on or above the

low copper fit line. This suggests that in addition

to this contribution to p1, nickel may also

influence the microstructure term, pj.

* CM SSR < 0.3 Cu

* * VMa

a LV- SSR < 0.3 Cu

A CM-AT < 0.3 Cu

119

0 CM-SSR > 0.3 Cu

0

/ O LV- SSR > 0.3 Cu

1.00

Cubk (%)

Figure 6-9 Variation of resistivity with copper content for a range of alloys

61
In order to further minimize possible effects

of heat-to-heat variability in estimating Cu.,

analysis of the norrnalized resistivity data was

restricted to the intermediate nickel alloys. The

low copper data were fit both with (solid lines)

and without (dashed lines) an imposed k, =

3.5 fl-cm/% Cu. Figure 6-lOa shows the

results for the CM series with about 0.85%

nickel in the standard stress relief condition.

The estimated Cu, for alloys with Cu,, =

0.33% (CM1) and 0.42% (CMI9) are Cu,=

0.20±0.01 and

0.24±0.02 respectively. Note, somewhat

higher values are found if the data point for

CMIO with 0.02% copper is included in the

analysis. However, since this data point is

inconsistent with the trend for other low

copper alloys (CM3, CM13 and CM16), it was

not used in the analysis. The corresponding

Cu, estimate for the CM12 alloy with Cub =

0.86% copper is also unrealistically low (<

0.1% Cu), perhaps also indicating an effect of

very high copper on p. Since this value is well

below the solubility limit at 607°C, it is not

shown. Figure 6-lOb shows the corresponding

result for the LV alloys. The p of alloy LC

with Cubk = 0.42% deviates from the lower

copper trends (LG, LH and LI), with an

estimated Cu, = 0.3±0.01. Figure 6-lOc

shows the results for the CM series in the as -

tempered condition. In this case, as expected,

both the CMl9 and CM12 show higher

estimated values of Cu. - 0.32 and 0.48%Cu,

compared to the standard stress relief

condition. Unfortunately there is not

sufficient data to carry out a similar analysis

on the high and low nickel CM series.

In summary the p-based Cu, estimates for the

high copper steels are consistent with

significant pre-precipitation of copper during

both tempering and stress relief and stress

relief heat treatments. For the standard stress

relief condition Cu, - 0.2-0.3%. The lowest

Cu. was found for the alloy with the highest

copper (CM 12). This Cu. is quantitatively

unreliable, but the indicated trend is

qualitatively consistent with the previous

analysis.

6.3.3 Seebeck Coefricient

As described in Section 3, the Seebeck

coefficient (S, V/OC) can be measured

precisely and is also sensitive to the

concentration of dissolved solutes in alloys

and to a lesser extent microstructure [Pollock,

1991; Miloudi et al, 1999, 2000]. The effect

of solutes can be described by elementspecific factors in forms roughly analogous

to Equation 6-7. Most, but not all, solutes

have negative , hence, S usually decreases

with increasing C,. Thus an analysis similar to

that used to estimate Cu, from the p data was

carried out based on measurements of S in the

VM, CM and LV series alloys. However, there

are some possible differences between the S

and p behavior that require some

modifications of the approach. First, the

dependence of S on C, is generally not well

established. Further, both theoretical

considerations and experimental observations

suggest that the S-dependence may be nonlinear and sensitive to the total alloy solute

content [Pollock, 1991]. Thus the effects of C,

on S are represented by linear (), non-linear

(K,' ) and a solute-total solute interactive

(icj,C) terns as

S = S + 1i(K,C, + K,' C,2

) xo,EC' (68)

Fitting Equation 6-8 to the VM, CM and LV

series database showed that good results could

be obtained without the r.,C, terms, and that

nonlinear terms were (moderately) significant

only for nickel and copper. The fitting results

are also given in Table 6-7. Note, not only do

the K,, have different values than p but they

also vary in sign (e.g., K. > 0). The standard

error of the fit was about 0.22 pV/°C or

roughly 2 to 3% of the measured S. The

normalized S. versus Cu,, is shown in Figure 6-

11. The normalization procedure and symbol

designation showing low copper (fitted -

filled) versus high copper (not fitted-unfilled)

are the same as those used in the p plots. The

62
0 0.1 0.2 0.3 0.4 0.5

Cubk (%)

*12.0 a I

LV

11.5-

211.0 

10.5 _ b

K ~~~b

10.0 , . .

0 0.1 0.2 0.3 0.4

CUbk (%)

14

13

12 o

11

CM-AT

10 , 0.00 0.25 0.50 0.75 1.00

Cubk (%)

Figure 6-10 Variation of resistivity with copper content for a) CM, b) LV and c) as-tempered CM

alloys.

63

12.0

11.5

11.0

a

10.5

10.0
Table 6-7 Least square fit calibration of Equations 6-7 and 6-8

Technique, Fe + 'Microstructure" Elements - ki (pW-cm/%i, k j(iV/0

KI%i)

Parameter r, (p-cm) S(iVPK)

LV. VM CM. CM. Si* Ti* P* Mn Mn2 Ni Ni' Cu Cu2

p, k 15.1 105 14.8 13.9 2.5 1.78 12.2 6.56 1.05 2A2 3.52

S

S, xij 8.0 13.7 10.3 10.1 3.56 0.49 16.1 0.24 1.62 0.31 5.94 u.5

1

1

1-

0

Ct

I

4

* CM Cu < 0.3

2 £ * LV Cu < 0.3

V 0* VM a Cu

0 0 LVCu>0,3

O CMCu>0.3

8

6

0.00 0.25 0.50 0.75 1.00

Cubk(%)

Figure 6-11 Variation of Seebeck coefficient with copper content

64
normalized S decreases with increasing Cu,

with a linear slope of -5.98 iVrC/%Cu. This

is about 16% less than the value reported for

iron-copper binary alloys reported in the

literature [Miloudi et. al, 2000] and may

reflect the interactions and non-linearities

noted above. The S. data for high copper

alloys fall above this line, again indicating preprecipitation.

The overall standaTd error to the simple linear

trend line of 0.2 pVPC indicates that a simpler

expression in the form

S= Sj +lC,,,X (6-9)

can be used to estimate Cu. for the high

copper steels. In order to minimize the effects

of alloy-specific confounding factors not

accounted for, Equation 6-9 was again fitted to

the various individual subsets of the

normalized (e.g., corrected for composition

and alloy category) intermediate (-0.85%)

nickel CM and LV S. data. However, in this

case no effort is made to fix c,,, at a nominal

value.

The results are shown in Figure 6-12. The

data for the model VM alloys are included but

are not used in the fitting. Figure 6-12a shows

the results for the CM standard stress relief

condition. The fitted ,,, is 5.61 pVrCI%Cu,

reasonably close to the overall fit to the data.

For the alloys with Cub, = 0.33% (CM 11),

0.42% (CM19) and 0.86% (CM12) the

estimates are Cu, = 0.25, 0.19 and 0.35%,

respectively. Figure 6-12b shows the

corresponding results for the CM series in the

as-tempered condition. In this case , = 5.57

pVPCI%Cu is essentially the same as for the

standard stress relief case. As expected,

however, the corresponding Cu., are generally

higher for the as-tempered relative to the

standard stress relief condition with values of

Cu., = 0.25, 0.26 and 0.42% respectively, for

CMll, CMI9 and CM12. Figure 6-12c shows

the results for the LV series. The estimated

Cu., for the intermediate nickel (0.86%) high

copper alloy (LC ) is 0.24% Cu.

In summary the S-based Cu. estimates for the

high copper steels are also consistent with

significant pre-precipitation of during both

tempering and stress relief heat treatments. For

the standard stress relief condition Cu. for

high copper alloys ranged from - 0.19-

0.25%. The estimated Cum for the alloy with

very high copper (CM12) gave the highest

Cu. = 0.35, which is qualitatively inconsistent

with the other data trends and may be due to

an effect of very high copper on S,.

6A Summary and Discussion of

the Aay and Microanalytical Based

Estimates of Cu.

Table 6-8 summarizes the microanalytical

estimates of Cu. for intermediate nickel, high

copper steels for typical as-tempered and stress

relieved conditions. Note however, the specific

heat treatments in these broad categories vary

slightly. For example, most of the FEGSTEM

CM data involve a so-called UK austenitizetemper treatment and air/furnace cooling

following isothermal stress relief. This differs

somewhat from heat treatment schedules used

in this program. The p and S data are for the

CM and LV alloys are in their specified astempered (CM) and standard stress relieved

conditions (LV and CM). The Aa,/VSR

entries are averages for both a range of typical

T. = 590-610°C and t = 24-96 h, as well as

for different Cu., assessment methods. Overall

there is reasonable agreement. These results

are summarized in Figure 6-13.3

3Recent results have been obtained that provide further

support for the conclusion reached in this section

regarding copper in solution following stess relief heat

treatment for intermediatc nickel steels. These new

results include the following items. I) Changes in both

Seebeck coefficient (AS) and resistivity (Ap)

measurements on CM, LV alloys and sevcral welds

following irradiation show a similar pattern to the trends

for the absolute values of these parameters (S and p) in

the unirradiated condition as shown in Figures 6-9 and 6-

12. That is, the low copper steels follow a linear trend

but at higher copper levels the AS and Ap fall below the

linear trend line indicating pre-precipitation. For alloys

with Cubk > 0.30% a preliminary analysis indicates an

65
6.5 Small Angle Neutron Scattering

Studies from the PB Experiment

Figure 6-14 shows data from Small Angle

Neutron Scattering studies on the effect of t.,

from 0 to 80 h for T., = 607°C on the CRP

features for the high copper (0.42%)

intermediate nickel (0.85%) alloy (CMI9)

irradiated in the PB capsule [Wirth, 1998].

Figure 6-14 shows both the total CRP volume

fractions (f., filled circles) and the

corresponding estimates of the copper volume

fraction (f 3, unfilled circles), based on the

magnetic to nuclear scattering ratio. Figure 6-

14 also shows the SANS volume fraction data

for the CM19 with t, = 24h at T, = 600°C,

irradiated in the T4 capsule (open triangle).

The x symbol is an adjustment to

approximately account for the lower fluence

of T4 (0.75x103 n/m2) versus the PB (x1023

n/zn 2) capsule based on the corresponding ratio

of the NUREG CRP fluence functions (see

Appendix A). The f,, decreases with

increasing t,, to values of fc. - 0.25%,

consistent with the corresponding evaluations

of Cu. described above. Clearly the effects of

t, on Cu. in the unirradiated condition are

reflected in the f. following irradiation.

However, the f, cannot be used to directly

evaluate Cu., since precipitation is presumably

not complete at this fluence. However, the

relative values are certainly meaningful and

also correlate well with the Acy changes.

Further, since the as-tempered alloy has a

nominal f,. - Cut, - 0.42%, it is not

completely unreasonable to assume that f,, -

Cu.,. The open diamonds are adjustments to

estimate the saturadon f based on dividing

the experimentally derived f values by the

NUREG CRP fluence function for the PB and

T4 capsules. These estimates of the saturation

f,. also fall below 0.3% at long t,,

average Cum - 0.26 0.03%. 2) Recent AP data reported

by Miller show Cu. in the range of 0.19 o 0.27% for a

weld with Cubk 0.3% depending on the stress relief

temperature and cooling rate. Note the effect of air

versus slow cooling following a stress relief at 607°C for

24h was also explored in this study. No systematic

pattem was observed in the My for the high copper CM

alloys (I, 12. 19 and 20) for these two cases. he

average difference in y was approximately zero. Thus

while slow cooling is expected to lead to lower Cu. the

effect does not appear to be large at least in this case.

66
Table 6-8. Microanalytical and A6y Based Estimates of Cu. for Typical As-tempered and

stress-relieved conditions

Alloy/HT FEGSTEM p TEP Aay(av) Av.

CMI9/AT 0.36 0.32 0.26 0.38 0.34

CMIIAT 0.33 0.25 0.33 0.30

CM12/AT 0.49 0.48 0.42 0.39 0.43

CM19SR 0.28 0.23 0.19 0.28 0.25

CMI I/SR 0.19 0.25 0.26 0.23

CM12/SR 0.28 0.34 0.24 0.23

LC/SR 0.28 0.30 0.24 0.27 0.27

CM18/SR 0.27 0.27

CM20/SR 0.31 0.31

67
14 -w1

12 X

2.

> 10

8

6

0.00 0.25 0.50 0.75 1.00

14 -- r

12 

a 10 

8 

6

0.00 0.25

CUbk (%)

0.50 0.75

Cubk (%)

14

12

12

2-

> 10

En

8I

6 0.25 . . Q.00 0.25 O.S0 0.75 1.00

Figure 6-12 Variation of Seebeck coefficient with copper content for a) stress-relieved CM,

b) as-tempered CM and c) LV-series alloys.

68

1.00

I, LV

* VM
0.5 0.5

0.5

0.4

0.3

:f 0.2

0.1

0.0 -

0.4

0.3

:f 0.2

u

0.1

0.0

1Z. 4

Figure 6-13 Cum measurements from various techniques for a) CMI I, b) CMI9, c) LC

69

a CMIl O AT

O SSR 0.4 

0.3

f 0.2

U

0.1 

0.0

:J

1Z

.

0.5 0.5
I

T4-CM19, LC

0 0

x

0

0

0

0 25 50

0

0

75

o Cu

Q Cu-sat

x LC-adj

* CRP

100

tsr Qb)

Figure 6-14 Effects of tr on CRP features as measured by SANS on CM19 from the PB capsule.

70

0.6

4

0.51

0.4

-

he

Wb.

$4

g

0.3

0.2 I
7 A PRE-PRECIPITATION MODEL FOR Cum

As noted above the data developed in this

study are not sufficiently accurate to derive a

detailed time-temperature-precipitation Ccurve model relating Cu. to the Cub,, T, t,, as

well as metallurgical factors such as nickel and

bulk copper content. However, it is useful to

evaluate general trends in the data to provide

additional guidance on Cu. limits within the

framework of such a model. The most robust

physical consideration is that Cu. must remain

at or above the equilibrium solubility limit of

copper (Cue) in ferrite. The solubility limit

has been examined with a number of

techniques and is given by [Kenway-Jackson

et al, 1993]

Cu,(wt%) = 120expl-5560/T (°K)1 (7- 1)

Figure 7-1 compares Cue to Cu. estimates for

high copper CM alloys (CMI 1,12,18,19,20)

from the VSR study based on the NUREG

assessment method. The available data for 48

and 96h at 590°C, 24 and 48 h at 607°C, 12

and 24h at 624°C and 6 h at 641°C have been

averaged in this plot (note data were not

available for all materials for all these

conditions). The general trend is for Cu to

increase with T, at a small increment above

Cue. The divergence between Cu,, and Cu,

increases with decreasing T, The high nickel

CM20 data fall above the others, while the

intermediate nickel and alloys with 0.33 and

0.86% copper (CM1 1,12) copper fall near or

slightly below Cue. The low and intermediate

nickel alloys with Cub, - 0.42% lie in between.

The dashed line, in the form of Equation 7-1,

is a fit to the average (large plus symbols) of

the high copper, intermediate nickel CMI I

and CM19 data and is given by

Cu, - I .lexp(-3282T,) (7-2)

Equation 7-2 represents a reasonable basis to

estimate Cu, for 'typical' high copper

intermediate nickel RPV steels as a function of

T, assuming reasonably long t,, The stress

relief time dependence of pre-precipitation

can be crudely modeled in terms of standard

equations for diffusion-controlled growth of

precipitates [Porter and Easterling, 1987] as

Cu,(t ,T.) =

Cu.(AT)-[Cu,.(AT)-C,(T.)][ I -exp(k,.Y2 )]

(7-3)

Here Cu,(AT) is the Cu, in the as-tempered

(AT) condition and k, is a transformation rate

coefficient that depends on the Cu,(AT), the

copper thermal diffusion coefficient and the

number density of the pre-precipitates. Thus,

k1, is also expected to depend on T,, and

CuJ(AT). The transformation rate coefficient

is physically complex but is crudely modeled

as

k, = y,Cu,.(AT) Cubkexp(-E.J1) (7-4)

where ,, is a numerical constant, and the Cu,,

term represents the effect of the bulk copper

on the pre-precipitate number density (or

nucleation rate) and E, is an activation energy

term that accounts for the combined effect of

T.r on copper diffusion and pre-precipitate

number density.

Figure 7-2 compares the results for the high

copper intermediate nickel CM alloys

(CI 1,12,19) from the VSR study, using the

NUREG-Acry model to assess Cu,, to

predictions using Equations. 7-1 through 7-4,

with Y.= 1.33 x 10' and E, =20,000°K. The

resulting predicted Cu. values for CM 19 are in

good agreement with the VSR estimates, while

the CMI 2 results are more scattered and the

CMI I values are lower by an average of about

0.05%. Figure 7-3 compares the

corresponding predictions of Cu, as a

function of t, for CM19. The effects of the

variation of k. with T,, are small and less than

the uncertainties in the data. Thus it is

reasonable to use a constant value of k, equal

to that predicted for 5900C to model the

average t,, behavior of a typical high copper,

intermediate nickel steel as

71
Cu(t .T.)=Cum(AT)-

[Cu.(AT)-Cu.(T,)][ 1-exp(-0.0 17t,3)]

(7-5)

Here Cu,(AT) = 0.35% for Cubk,> 0.35% and

Cum(AT) = Cub, for Cu,(T,) < Cub,< 0.35%.

At best Equation 7-5 can be used as a rule of

thumb for assessing the effects of stress relief

conditions on Cu. in low to intermediate

nickel steels. The Cu, accounts for T, and the

constant k. crudely accounts for the t,.

0.35

0.30

Ug

JU

0.25

0.20

dependence. However, Equation 7-5 should

not be extrapolated below about 590°C,

because of slower diffusion rates, or above

640°C because reduced rates of pre-precipitate

nucleation. Equation 7-5 is also not applicable

to high nickel steels, where higher Cu. are

anticipated.

Verification and further refinement of the Cu,.

model will require additional data and more

detailed modeling.

* CM19

O CM18

* CMll

O CM20

+ Av. CM1l, 19

0.15 L- -a CUmcrsr)

575

T (°C)

Figure 7-1 Comparison of Cu, to Cum for high copper CM alloys from VSR

72

600 625 650 675
0.20 0.25 0.30 0.35

Cum (pred., %)

* CM19

A CM12

* CMil

0.40

Figure 7-2 Comparison of Cum from VSR data to predictions of Equations 7-2 through 7-4.

-4

K AT

* 5900C

* 607°C

A 6240C

v 641°C

O BULK

d- 5900C

._-.- 6070C

..em--m. 6248C

"m"llgn 641

Figure 7-3 Comparison of Cum for CM19 as a function of tsr.

73

0.40

0.35

UP

A

=F

0.30

0.25

0.20

0.15 

0.15

0.45

0.4

0.35

0.3

0.25

0.2

M

Lh

tht (h)

.i
8 SUMMARY AND CONCLUSIONS

This study is part of an overall effort to

provide guidance and insight for supporting a

technical basis for proposed changes to Reg

Guide 1.99/Rev 2. The overall effort involves

developing an independent embrittlement

database from controlled, single-variable

experiments. High-resolution experimental

maps of the individual and interactive effects

of metallurgical and environmental variables

on embrittlement are derived from irradiation

and post-irradiation testing of very large

experimental matrices. These experiments

take advantage of the relationship between AT

and increases in yields stress (Aa,), which can

be measured using small tensile specimens.

These experiments achieve precise control and

characterization of the embrittlement variables.

Irradiations are carried out in the Irradiation

Variable Facility (IVAR) at the University of

Michigan Ford Research Reactor. The large

experimental Aa, database under development,

will ultimately be complemented by an

extensive effort to characterize the

microstructural changes responsible for Acy,

and AT. The collective results will be analyzed

and used to develop quantitative, mechanismbased embrittlement models. These in turn

can be used to support the development and

justification of statistical fits to the power

reactor embrittlement database (PREDB), such

as the Eason-Wright-Odette Model

(NUREGICR-655 1) as a part of the technical

basis for proposed changes to Reg Guide

1.99/2.

This report has focused on a subset of

important questions that must be answered in

establishing this technical basis. The effort

involved analyzing irradiation hardening data

from three irradiation experiments (T4, T14

and VSR) performed in the IVAR facility, and

one irradiation experiment (PB) performed in

a piggy back experiment.

Collectively, the T4, T14 and PB data

permitted the systematic investigation of

compositional effects. The sigmoidal

dependence of hardening on copper was seen,

as expected. The data also showed systematic

increases of hardening with nickel,

phosporous, and manganese. The sensitivity

to copper was enhanced by nickel and the

sensitivity to phosphorous was decreased by

copper. The sensitivity to other chemical

elements - boron, carbon, nitrogen, tramp

elements - was small or negligible. The

observed small sensitivity to molybdenum is

consistent with a superposition of irradiation

hardening to pre-existing hardening from

strong obstacles like Mo2C.

Data from these irradiations were compared to

predictions of a Ao1 modification of a

NUREG-AT correlation model. The overall

agreement was quite remarkable. Thus the

Ao, database generated in this study provides a

powerful and independent confirmation of the

general form of the NUREG model treatment

of copper, nickel and phosphorous and their

interactions. All the major trends in both the

NUREG model and in the IVAR database are

consistent with current understanding of

embrittlement mechanisms. Specifically, the

data validate the general two-component form

of the NUREG-AT model comprised of a

copper-independent (matrix feature, matrix

features) and copper-dependent (copper rich

precipitate, CRP) terms, and corroborate the

very strong interaction between copper and

nickel in the NUREG model CRP contribution

to AT. The data also validate the inclusion of

phosphorous in the NUREG model, and

support its approximate treatment in the

matrix feature contribution to AT.

The VSR experiment permitted the

investigation of the effect of systematic

variations in stress relief time and temperature

following the final tempering of several sets of

A533B-type split melt alloys. These data

demonstrated the systematic reduction of

matrix copper, Cu., prior to irradiation by preprecipitation. The pre-precipitation occurred

to a greater extent with increasing stress relief

time and with decreasing stress relief

temperature. The irradiation hardening data

74
were complemented by FEGSTEM, resistivity

and Seebeck coefficient measurements on

unirradiated alloys subject to a range of stress

relief anneals. In addition to verifying the

effect of heat treatment on matrix copper, the

emergence of resistivity and Seebeck

coefficient measurements as useful

nondestructive tools for assessing

embrittlement potential were demonstrated.

Together the data were used to develop a

simple transformation model to estimate Cu,

as a function of stress relief time and

temperature. In addition the data validate a

maximum in Cu. of around 0.3% following

tempering and stress relief heat treatments

found in the NUREG model. Strong support

was also found for even lower Cu, levels of

about 0.25% in low-to-intermediate nickel

steels, as well as evidence for corresponding

levels in excess of 0.3% in high nickel steels.

unirradiated microstructure and properties,

hence, also A;r, and AT.

4. Possible sources of product form variability

and data scatter in the matrix features term,

including an increase in A; with

manganese and nickel.

5. A possible interaction reducing the effect

of phosphorus at higher copper.

These will be addressed in ongoing research in

the UCSB program.

The database and analysis provided in this

report also provides additional insight into

several other issues, which are further from

closure. Resolution of these issues could lead

to signif-icant improvements in embrittlement

forecasting. They include:

l. Possible sources of product form variability

and data scatter in the CRP term. These

include embrittlement contribu-tions from

elements not explicitly accounted for in the

NUREG-DT model, like manganese

(interacting with nickel and copper), and

effects of microstructural variations on the

fluence dependence of Ay and AT.

2. An unanticipated effect of flux and fluxcomposition interactions on the fluence

dependence of the CRP contribution to A,

and AT.

3. Effects of the unirradiated constitutive and

Charpy properties on: a) the Ac; -produced

by a specified embrittlement

microstructure; and b) the relationship

between Ay and AT. This work has also

identified new mechanisms that influence

the effects the heat treatment on the

75
9 REFERENCES

Arajs, S., F. C. Schwerer, R. M Fisher, "Residual

Resistivities of Binary Iron Alloy," Phys. Stat.

Sol, 33, 1969, pp.73 1 -

7 40 .

Alexander, D. E., B. J. Kestel, P. R. Jemian, G. R.

Odette, D. Klingensmith, D. Gragg, "Anomalous

Small Angle X-ray Scattering Characterization

of Model Pressure Vessel Alloy

Microstructures," MRS Soc. Symp. Proc., 540,

1999, p.4 15 .

ASTM Standard Test Method for Resistivity of

Electrical Conductor Materials, ASTM B193-87,

Annual Book of ASTM Standards, American

Society for Testing and Materials, Philadelphia,

PA, 1987.

ASTM Standard Test Method for Determination

of Reference Temperature T. for Ferritic Steels

in the Transition Range, ASTM 1921-97 Annual

Book of ASTM Standards 03.01, American

Society for Testing and Materials, West

Conshohocken, PA, 1998, pp. 1068-1084.

Auger, P., P Parieje, M. Alcamatsu, J. C. Van

Duysen, "Microstructural Characterization of

Atom Clusters in Irradiated Pressure Vessel

Steels and Model Alloys," J. NucL Mater., 211,

1994, pp. 194-201.

Bolton, C., J. T. Buswell, R. B. Jones, R.

Moskovic, R. H. Priest, "The Modeling of

Irradiation Embrittlement in Submerged-Arc

Welds," ASTM STP 1270, American Society for

Testing and Materials, Philadelphia, PA, 1996,

pp. 103-118.

Brillaud, C. and F. Hedin, "In Service

Evaluation of French Pressurized Water Reactor

Vessel Steel, ASTM-STP-1 125, American

Society for Testing and Materials, Philadelphia,

PA, 1992.

Buswell, J. T. and R. B. Jones, "The Modeling

of Radiation Hardening and Embrittlement in

Magnox Mild Steel Submerged-Arc Welds,

ASTM STP 1175, American Society for Testing

and Materials, Philadelphia, PA, 1993, pp. 424-

443.

Eason, E. D., J. E., Wright and G. R. Odette,

"Improved Embrittlement Correlations for

Reactor Pressure Vessel Steels," NUREG/CR6551, U. S. Nuclear Regulatory Commission,

Washington D.C., 1998.

English, C.A., W. J. Phythian and R. J. McElroy,

"Microstructure and Modelling of RPV,

Embrittlement," Microstructure Evolution

During Irradiation, MRS Symp. 439, I. M.

Robertson et al., eds., MRS, 1997, p. 471.

Fint, J., "A Study of the Evolution of

Precipitates in Pressure Vessel Steels Using Small

Angle Neutron Scattering," MS Thesis, UC

Santa Barbara, 1990.

Fisher, S. B.,1. E. Harbottle, N. Aldridge, PhiL

Trans. Roy. Soc. Lond, A315, 1985, 301.

Fisher, S. B, and J. T. Buswell, "A Model for

PWR Pressure Vessel Embrittlement," Int.

Journal of Pressure Vessels and Piping, 27-2.

1987, pp. 91-135.

Foreman, A.J. E., and M. J. Makin, Can. J. Phys.

45, 1967,p.511.

Guinier, A. and G. Foumet, Small Angle

Scattering of X-rays, translated by C. B. Walker,

John Wiley and Sons, New.York, 1955.

Jenkins, M. L., "Characterization of Radiation

Damage Microstructures by TEM," J. Nuclear

Materials, 216, 1994, pp. 125-156.

Kenway-Jackson, A. J., J. Mace, R. N Thomas,.

W. Phythian, Technical Report AEA-RS 4411,

AEA Technology, Harwell, UK, 1993.

Kostorz, G., Small Angle Scattering and Its

Applications to Materials Science," Treatise on

Materials Science and Technology, 15.

76
Liu, C. L., G. R. Odette, B. D. Wirth, G. E. Lucas,

"A Lattice Monte Carlo Simulation of

Nanophase Compositions and Structures in

Irradiated Pressure Vessel Fe-Cu-Ni-Mn-Si

Steels," Matls Sci and Eng., A238, 1997, pp.

202-209.

Lott, R. and P. D. Freyer, "Modeling of

Irradiation Embrittlement and

Annealing/Recovery in Pressure Vessel Steels,"

ASTM STP 1270, American Society for Testing

and Materials, Philadelphia, PA, 1996, pp. 86-

102.

Mader, E., "Kinetics of Irradiation

Embrittlement and the Post-Irradiation

Annealing of Nuclear Reactor Pressure Vessel

Steels, Ph.D. Thesis, UC Santa Barbara, 1995.

Mathon, M-H., "Etude De La Precipitation Et

Des Mechnismes Microscopiques De

Durcissement Sous Irradiation Dans Des Alliages

Ferritiques Dilues, Report CEA-R-5701,

Commissariat A L'Engerie Atomique, Saclay,

France, 1995

McElroy, R. . and A. L. Lowe, "Irradiation

Embrittlement Modeling of Linde 80 Welds,"

ASTM STP 1270, American Society for Testing

and Materials, Philadelphia, PA, 1996, pp. 68-

85.

Miller, M. K., and M. G. Burke, "An APPIM

Survey of Grain Boundary Segregation and

Precipitation in Iradiated Pressure Vessel

Steels," ASTM STP 1175, American Society for

Testing and Materials, Philadelphia, PA, 1993,

pp. 492-502.

Miller, M. K., P. Pareige, M. G. Burke,

"Understanding Pressure Vessel Steels: An

Atom Probe Perspective," Materials

Characterization, 44, 2000, pp. 235-254.

Miloudi, S., S. Jumel, J.-F. Coste, J.-C. van

Duysen, "Thermoelectric Power: NonDestructive Method for Monitoring the

Irradiation Effects in Ferritic Steels," in: NDT

Methodsfor Monitoring Degradation, U. von

Estorff, L. M. Davies, P. Trampus, eds, European

Commission, Petten, The Netherlands, 1999, pp.

114-121.

Miloudi, S., S. Jumel, P. Pareige, J.-F. Coste, J.-C.

Van Duysen, Thermoelectric Power: A NonDestructive Method for Monitoring the

Irradiation Effects in Ferritic Steels," ASTMSTP-1366, American Society for Testing and

Materials, West Conshohocken, PA, 2000,

pp.1029-1042.

Odette, G. R., "On the Dominant Mechanism of

Irradiation Embrittlement in Pressure Vessel

Steels," Scripta Met., 11, 1983, p. 1183.

Odette, G. R., P. M. Lombrozo, R. A. Wullaert,

"The relationship Between Irradiation

Hardening and Embrittlement of Pressure Vessel

Steels," ASTM STP 870, American Society for

Testing and Materials, Philadelphia, PA, 1985,

pp. 840-860.

Odette, G. R. and G. E. Lucas, "Recent

Advances in Predicting Embrittlement of

Reactor Pressure Vessel Steels," Proceeding of

the 2"d International Symposium on

Environmental Degradation in Nuclear Reactors

- Water Reactors, J. T. A. Roberts, J. R. Weeks,

G. J Theus, eds., American Nuclear Society, La

Grange Park, IL, 1986, p. 345.

Odette, G. R. and G. E. Lucas "The Effect of

Heat Treatment on radiation Harding of

Pressure Vessel Steels," Proceeding of the 3rd

International Symposium on Environnental

Degradation in Nuclear Reactors - Water

Reactors, J. R. Weeks, G. J Theus, eds, The

Metallurgical Society, Warrendale, PA, 1988, p.

95.

Odette G. R and G. E. Lucas, "Irradiation

Embrittlement of LWR Pressure Vessel Steels,"

EPRI NP-6114 (1989).

Odette, G. R. and G. E. Lucas The Effect of

Nickel on Radiation Hardening of Pressure

Vessel Steels," ASTM-STP-1046, Vol. ,

77
American Society for Testing and Materials,

1990, p.323.

Odette, G. R., Mader, E., Lucas, G. E., Phythian,

W. J., English, C. A., "The Effect of Flux on

Irradiation Hardening of Pressure Vessel Steels,"

Proceedings of the 16th Symposium on the

Effects of Irradiation on Materials, ASTM-STPII 75, American Society for Testing and

Mateials, Philadelphia, PA (1993) 373-393.

Odette, G. R., "Radiation Induced

Microstructural Evolution in Reactor Pressure

Vessel Steels," MRS Soc. Symposium

Proceedings, 373, 1995, p.137.

Odene, G. R. and G. E. Lucas, "An Integrated

Approach to Evaluating the Fracture Toughness

of Irradiated Nuclear Reactor Pressure Vessels,"

. Non-Destrucive Eval., 14, 3/4 (1996) 137-

150.

Odette, G. R. and G. E. Lucas, "Current

Understanding of the Effects of Environmental

and Irradiation Variables on RPV

Embrittlement", Proceedings of the 24th Water

Reactor Safety Meeting, 2, NUREG/CR-0157-2,

1997, p. 1.

Odette, G. R. and B. D. Wirth, "A

Computational Microscopy Study of

Nanostructural Evolution in Irradiated Pressure

Vessel Steels, . NucL Mater., 251, 1997, pp.

157-171.

Odette, G. R. and G. E. Lucas, "Recent Progress

in Understanding Reactor Pressure Vessel Steel

Embrittlement," Radiation Effects and Defects in

Solids, 144, 1998, pp. 189-231.

Odette, G. R., "Modeling Irradiation

Embrittlement in Reactor Pressure Vessel

Steels," Neutron Irradiation Effects in Reactor

Pressure Vessel Steels and Weidnents, IAEAIWG-LMNPP-98/3, M. Davies, ed., LAEA,

Vienna, 1998.

Odette, G. R. and G. E. Lucas, "Reactor Pressure

Vessel Embrittlement: The Road Ahead," Proc.

Water Reactor Safety Meeting, October, 1999,

U.S. NRC.

Odette, G. R., 0. E. Lucas, D. Klingensmith,

"Anomalous Hardening in Model Alloys and

Steels Thermally Aged at 2900C and 350°C:

Implications to Low Flux Irradiation

Embrittlement," Effects of Radiation on

Materials: 18th International Symposium,

ASTM-STP-1325, American Society for Testing

and Materials, 1999, pp.88-101.

Odette, G. R. and M. He, "Physical Model for the

Master Curve Shape," Applications of Fracture

Mechanics in Failure Assessment, PVP-412, D.

Lidbury et al., eds. PVP-ASME, 2000, p. 93.

Odette, G. R. and M. He, "A Cleavage Toughness

Master Curve Model," J. Mucl. Mater., 283-287,

2000, pp. 120-127.

Pareige, P., "Etude A La Sonde Atomique De

L'Evolution Microstructurale Sous Irradiation

D'Alliages Ferritiques FeCu Et D'Aciers De

Cuve De Reacteurs Nuclearies," Ph.D. Thesis,

LeUniversite de Rouen, 1994.

Phythian, W. and C. A. English,

"Microstructural Evolution in Reactor Pressure

Vessel Steels," J. Nucl. Mater., 205, 1993,

p.162.

Pollock, D. D., Thermocouples, Theory and

Propertes, CRC Press, Ann Arbor, 1991.

Porter, D. A., and K E. Easterling, Phase

Transformations in Metals and Alloys, Van

Nostrand Reinhold, Berkshire, UK, 1987.

Remec, I, "Preliminary Fast Neutron Flux

Results for the UCSB Irradiation Facility

Characterization Experiment," ORNL Internal

Report, July 24, 1997.

Remec, I., C. A. Baldwin, F.B.K Kam, "Neutron

Exposure Parameters fof Capsule 10.05 in the

Heavy-Section Steel Irradiation Program Tenth

Irradiation Series," NUREGICR-6600, U. S.

Nuclear Regulatory Commission, 1998.

78
Rossiter, P. L., The Electrical Resistivity of Metals

and Alloys, Cambridge University Press,

Cambridge, UK, 1991.

Sokolov, M. A, S. Spooner, G. R. Odette, B. D.

Wirth, G. E. Lucas, "SANS Study of High

Copper RPV Welds in Irradiated and Annealed

Conditions," Effects of Radiation on Materials:

18th Int'l Symp., ASTM STP 1325, American

Society for Testing and Materials, 1999, pp.

333-345.

Solt, G., F. Frisius, W. B. Waeber, P. Tipping,

Proceedings of the 5th Inteanational Symposium

on Environmental Degradation of Materials in

Nuclear Power Systems - Water Reactors, D.

Cubicciott, E. Simonen, R. Gold (eds), American

Nuclear Society, La Grange Park, IL, 1990, p.

444.

Solt, G., F. Frisius, W.B. Waeber, P. Tipping,

ASTM STP 1175, American Society for Testing

and Materials, West Conshohocken, PA, 1993,

pp. 444-462.

Stallmann, F. W., J. A. Wang, F. B. K. Kam, B. J

Taylor, "PR-EDB: Power Reactor Embrittlement

Data Base, Version 2," NUREG/CR-4816, U. S.

Nuclear Regulatory Commission, 1994.

Stoller, R., 'Pressure Vessel Embrittlement

Predictions Based on a Composite Model of

Copper Precipitation and Point Defect

Clustering, ASTM STP 1270, American Society

for Testing and Materials, West Conshohocken,

PA, 1996, pp. 25-58.

Williams, T. J., and W. J. Phythian, "Electron

Microscopy and Small Angle Neutron Scattering

Study of Precipitates in Low-Alloy Submerged

Arc Welds:' ASTM STP 1270, American Society

for Testing and Materials, Philadelphia, PA,

1996, p. 191.

Wirth, B. D., "On the Character of Nano-Scale

Features in Reactor Pressure Vessel Steels Under

Neutron Irradiation," Ph.D. Thesis, University

of California, Santa Barbara, 1998.

Wirth, B. D., G. R. Odette, W. Pavinich, G. E.

Lucas, S. Spooner, Small Angle Neutron

Scattering Study of Linde 80 RPV Welds," ASTM

STP 1325, American Society for Testing and

Materials, 1999, pp.102-124.

Wirth, B. D., and G. R. Odette, "Kinetic Lattice

Monte Carlo Simulations of Cascade Aging in

Dilute Iron-Copper Alloys, MRS Symp. Proc.,

540, 1999, pp. 637-642.

USNRC, Rules and Regulations Title 10 Code of

Federal Regulations Part 50 Fracture

Toughness Requirement, United States Nuclear

Regulatory Commission, U. S. Government

Printing Office, Washington, 1986.

USNRC, Regulatory Guide 1.99: Radiation

Embrittlement to Reactor Vessel Materials,

United States Nuclear Regulatory Commission,

U. S. Government Printing Office, Washington,

D.C., 1988.

Williams, T. J., P. R. Burch, C. A. English, and P.

H. N de la Cour Ray, "The Effects of Dose Rate

and Temperature and Copper and Nickel

Content on the Irradiation Shift of Low Ally

Submerged-Arc Welds," Proceedings of the 3rd

International Symposium on Environmental

Degradation of Materials in Nuclear Power

Systems - Water Reactors, J. R. Weeks, G. J

Theus, eds, The Metallurgical Society,

Warrendale, PA, 1988, p. 121.

79
Appendix A The NUREG Acy Model

A comprehensive effort to develop improved

embrittlement prediction models was reported

in NUREG/CR-6551 published in 1998 [Eason

et al, 1998]. Statistical equations were least

squares fit to the scrubbed Charpy V-notch

test energy-temperature data extracted from

power reactor embrittlement (surveillance)

data base (PREDB). Embrittlement equations

were developed for both reductions in upper

shelf energy and increases in the 41J transition

temperature (AT). The latter were based on

609 AT points in the PREDB. The NUREGAT models contain two terms. The first is

attributed to what is called in this report the

matrix feature contribution, which occurs in

steels independent of their copper (and nickel)

content. The matrix features term depends on

phosphorous, irradiation temperature (Ti) and

fluence (t). The second term derives from

what is called the CRP contribution in this

report. The NUREG CRP term depends on

copper, nickel, Ot and flux () or irradiation

time (t/0).

The most salient features of the NUREG AT

models were that: a) the correlation equations

were based on an understanding of key

embrittlement mechanisms; b) selection from

among a large number of statistically similar

calibrated correlation equations was based on

both mechanistic considerations and

consistency with independent sources of data,

largely derived from UCSB test reactor studies

preceding the IVAR program, including data

from the PB capsule; c) unless there was a

combination of mechanistic and statistical

significance dictating otherwise, the correlation

equations were kept as simple and with as few

degrees of freedom as possible.

Improvements in the NUREG model have

continued and currently focus on the

following questions and issues:

a. The treatment of phosphorous in the matrix

feature term.

b. The effective maximum copper content as

influenced by variables such as product form

and nickel.

c. Variability in the embrittlement model

coefficients associated with product form,

including subclasses representing a vendor

effect.

d. The effects of flux-time in the CRP term

associated with possible thermal diffusion

contributions to precipitation kinetics,

primarily impacting very low flux service

conditions characteristic of BWRs.

e. An additional possible non-conservative bias

in AT at times in excess of about 1 O'h that

cannot be attributed to a particular mechanism

or combination of other variables (although

this effect increases slighdy with increasing

T.)

While not a major issue of contention, it

remains important to evaluate the general

forms and variable dependence of both the

matrix features and CRP, since some details of

the correlation depend on all others. Thus a

major objective of this study has been to

compare the IVAR data trends with predictions

of the NUREG model.

Such comparisons require conversion of the

AT predictions to corresponding values of

Ao,. A strong empirical relation between AT

and Ay has been observed in almost all cases

where both types of data are available in cases

where non-hardening temper embrittlement,

associated with intergranular fracture does not

play a role [Odette et al, 1985]. However, the

empirical hardening Charpy shift factor, Cc =

ATIA,Y, vares in a typical range of about

0.65±0.15 C/MPa. The AT-Ay relation

should also be consistent with the

micromechanics of cleavage fracture.

80
A quantitative micromechanics model of C,

has been developed [Odette et al, 1985]. The

model includes treatment of both: a) Acy

induced shifts in the maximum temperature

(T,) for cleavage preceding general yield

(which occurs at a Charpy energy of about

I OJ); and b) the layover in the Charpy energytemperature curve in the transition that is be

related to the decrease in the upper shelf

energy (AUSE) that can also be related

empirically to Aa,. As a consequence of the

temperature-dependence of a and the

contribution of the USE drop to the 41 J AT,

Cc depends on the unirradiated Charpy

properties (T,U and USE,) and Acy. Thus this

model explains part of the observed variability

of C.

The NUREG-AT model does not explicitly

account for the variations in Cc due to

differences in unirradiated T,. and USE".

However, it does implicitly account for Acr

Thus the average of values in the T, and USE.

in the NUREG PREDB were used in the model

to determine an average relation between

AT(0C) and A;, (MPa). The results can be fit

to a convenient analytical form

C.(AT) = AT/AY (A-l)

WhereA; - 6.59x104 T

3-

4.67xl o *AT2+1 .78*AT+3.432

Figure A- I shows that Cc increases

significantly with increasing AT (and A,).

However, while such tends have been observed,

the quantitative relationship has not been fully

verified by experiment, particularly at high

A;. and C, > 0.8. Further, within data scatter

an average value of C, = 0.7 is a reasonable

approximation to relate to A; - AT/C: Thus

three options were used to convert the

NUREG-AT to AG,r including: a) Equation A1; b) Equation A-I up to a maximum C.=

0.8; c) an average constant Cv= 0.7.

The NUREG-AT model is given by

AT = AT,r +ATp (A-2a)

where

AT 1, = Aexp{ 1.9lx104(Ti.

+460)1(1 +57.7P)¢t' 0 " '*'"

AT., = B(1l+2.56Ni'35')h(Cu)g(t)

and

h = 0, for Cu _ 0.072%,

h = (Cu - 0.072)f'

for 0.072 < Cu <0.3%

b = 0.367 for Cu2 0.3%

(A-2b)

(A-2c)

g(ot)=0.5 +0.5tanh[(ogt-l8.29)/0.6]

(A-2d)

The T,' is in °F and the g(ot) ignores a small

contribution from irradiation time that is not

pertinent to assessing the test reactor data in

this report. The corresponding bA were

determined as Aa,= AT K,, based on one of

the three options listed above.

The NUREG-Aa, model was used in analyzing

the IVAR data. In all cases the A and B

parameters for welds from the NUREG model

were used since this choice provided the best

results and welds cover the widest range of

copper and nickel in the PREDB. The analysis

involved:

1. Adjusting Acty for the LH and LI (- 0.74%)

alloys to account for small differences in

nickel compared to the high copper LV and

CM alloys ( - 0.83:0.03%). This was done by

adding the NUREG predictions of AaANi for

LV or CM) - a,(Ni = 0.74%) to the

experimental AC, 1 using the set of other

pertinent variables. This small adjustment, of

order 10-15 MPa, was based on the basic

NUREG model and use of option b above for

C.

2. Comparison of the Ay predicted by the

NUREG model for the specified alloy

81
chemistry, irradiation temperature and fluence

to the corresponding experimental data from

the T14 capsule. Flux was not explicitly

considered in this comparison, and option b

above for C, provided the best results.

3. Comparing the a, predictions of the

NUREG model (the matrix feature term) to the

corresponding data for low copper CM steels

from a number of IVAR capsules for low

(0.005%) and high (0.040%) nominal

phosphorous contents. This used the base

model and option b for C,.

4. Evaluating Cu, from the ha, data from the

VSR study. The VSR data are from a high flux

capsule. Although not the focus of this report,

other IVAR data show that higher flux shifts

the Aa:(Ot) CRP contribution for a particular

alloy to higher fluence. Thus the NUREG

model was modified to account for the effect

of flux. The approach was based on analysis

of the data from the high flux T4 capsule. A

number of modified NUREG models were

tried to find a plausible treatment of flux that

provided a good fit to these data. It was found

that a very good fit could be achieved by

using option c for Cc above, and a flux factor

(f, 5 1) to reduce the actual fluence to an

effective fluence at high flux. Further, it was

found that fitting required a f4 that decreased

with increasing alloy nickel content. This

behavior is consistent with higher rates of

interstidal recombination with vacancies

trapped on nickel solutes. The fit provided by

f,= 1/(1+1.3Ni) is shown as the filled circles in

Figure A-2 comparing the A,predicted by

the modified NUREG model with the data

from the T4 capsule. The unfilled circles are

the corresponding results for f = 1. The need

to account for nickel is illustrated in Figure A3. Here the differences between the predicted

and measured a, are plotted against nickel

for the T4 capsule steels with more than

0.072% copper. Data for the low manganese

and highest copper alloys and one weld (67W)

with a large inexplicable discrepancy are not

included in this plot, since they are not

representative of the other IVAR or the

PREDB data trends (note the low manganese

result is consistent with the lower sensitivity of

forgings in the PREDB). The discrepancy

between the Acy, predictions of a flux

independent NUREG model and experiment

increases with increasing nickel. This trend

demonstrates the need for a nickel-dependent

f in the modified NUREG model. However, it

should be emphasized that the f,(Ni)

modification does not represent a quantitative

flux model. Rather, it represents an attempt to

calibrate the modified NUREG model to

estimate relative values of Cu. using data from

the VSR study.

Application of the modified NUREG-model is

straightforward. The specific nickel and

phosphorous contents along with the VSR

irradiation temperature and fluence are used to

compute Aci, using the modified NUREG

model as a function of copper. The copper

that gives the predicted Acy equal to the

measured value is taken as Cu,.

82
IW

U

0

U

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0 50 100 150 200 250

AT (°C)

Figure A-I Variation of Cc with AT. The dashed line shows the average.

400 . I I

T4-alI data

300 f = 1(1+1.3Ni)

s 0 ° f¢= 

Z 200

.0

t o

0

0 100 200 300 400

AcFy (pred., MPa)

Figure A-2 Comparison measured ,ay with values predicted from NUREG model for T4.

83

6

a

ft-
100

75/

X 50 -/

d 25 - 0

e o 

-25i. 

0.0 0.5 1.0 1.5 2.0

Ni (%)

Figure A-3 Variation of the difference between predicted and measured Aay with Ni.

84
APPENDIX B TENSILE DATA FOR T4, T14, VSR AND PB

Table T4. Data for Capsule T4

Alloy

CM3

CMIO

CMIl

CM13

CM15

CM16

CM17

CM18

CMl9

CM20

CM21

CM22 (series a)

CM22 (series b)

LA

LB

LC

LD

LG

LH

Li

Li

LK

LO

Baseline kradiated Baseline Irdiated

Cry *aGy Ca, :toy aC, tACF, uts tUts Uts tuts auts ±LAuts

MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa

428

429

438

424

433

434

451

433

450

464

398

406

446

469

483

491

501

493

507

512

530

551

527

12 433

11 452

6 587

11 464

5 478

14 558

9 650

8 492

4 602

11 716

8 505

7 545

6 575

6 549

9 563

4 636

3 671

7 526

4 544

6 617

12 671

8 663

9 712

ORNL73 weld 507 13 639

EPRI C weld 536 5 656

B.W. weld 62 526 8 620

B.W. weld 63 497 7 632

B.W. weld 65 473 7 573

B.W. wld 67 514 16 581

ORNL A302b 557 18 580

ORNL HSST02 plate 473 4 570

JRQ plate 484 8 543

14 5 18 531

10 23 15 520

12 149 13 527

4 40 12 512

7 45 9 516

9 124 17 523

3 199 10 548

7 59 11 521

7 152 8 545

7 252 13 561

9 107 12 464

6 139 9 482

129 6 515

13 80 15 583

11 80 14 590

3 145 5 609

5 170 6 633

6 33 9 609

1 37 4 616

11 105 12 628

1 141 12 641

3 112 8 644

2 185 9 638

6 132 14 610

3 120 6 626

4 94 9 627

0 135 7 598

8 100 11 575

6 67 17 606

4 23 18 690

10 97 11 619

1 59 8 601

16 523 12 -8 20

15 537 13 17 20

11 658 10 131 15

17 540 8 28 19

8 549 13 33 16

16 635 8 112 18

14 718 8 170 16

15 564 5 43 16

11 666 10 121 15

19 784 11 223 22

11 550 7 86 13

6 598 3 116 7

7 622 107 7

6 656 10 73 12

7 667 4 77 8

4 745 6 136 7

3 791 1 0 3

6 637 6 28 9

2 650 1 34 2

7 719 11 91 13

4 758 1 117 4

6 746 5 102 8

8 808 1 170 8

12 726 6 116 13

8 731 5 105 9

8 700 1 73 8

5 716 3 118 6

6 661 6 86 8

15 663 4 57 15

19 714 0 24 19

4 700 4 81 6

10 657 1 55 10

u = undereniined

85
Data for Capsule T14

Baseline lradiaed Baseline hmdiated

a ±0 Ci, ±O AO ±Aa7 uts ±uts uts ±uts Auts ±AUtS Na MI MPa Miia Ma MPa MPa MPa MPa MPa MPa MPa

419 8 416

436 9 472

428 12 434

458 13 490

394 21 453

453 9 476

457 17 502

400 6 393

416 5 427

429 11 455

438 6 610

496 9 634

421 2 483

429 14 492

434 13 476

434 13 582

451 9 676

433 8 496

450 4 621

464 11 736

398 8 513

406 7 562

446 6 591

404 3 416

463 13 481

443 6 462

444 6 456

445 5 447

438 14 435

448 10 634

265 7 343

481 9 619

444 6 442

469 6 549

483 9 577

491 4 660

501 3 701

493 7 528

507 4 553

512 10 619

530 12 684

551 8 680

527 9 709

8 -3 12 497

4 36 10 527

10 6 16 531

5 32 14 559

9 62 24 488

21 23 22 552

16 45 24 566

11 -8 12 478

0 11 5 499

1 26 11 520

4 172 7 527

6 138 11 590

10 62 10 507

11 63 18 526

6 42 14 523

4 148 14 523

5 225 10 548

3 63 9 521

1 171 4 545

6 272 12 561

6 113 10 464

5 156 9 482

u 145 6 515

6 12 7 479

1 18 13 599

2 19 6 532

19 12 20 529

u 2 5 537

u -3 14 529

1 186 10 538

2 78 7 379

5 138 10 579

1 -3 6 514

8 80 10 583

8 94 12 590

4 169 6 609

1 200 3 633

3 35 7 609

1 46 4 616

8 107 13 628

4 154 13 641

8 129 11 644

1 182 9 638

9 480

15 552

16 575

13 575

18 566

8 559

20 606

9 472

15 505

15 538

11 718

12 711

17 534

15 585

16 549

16 651

14 739

15 568

11 690

19 799

11 564

6 617

7 649

4 486

23 611

13 545

9 537

8 529

18 523

8 696

12 434

11 698

8 512

6 657

7 677

4 764

3 810

6 636

2 658

6 721

4 773

6 763

8 811

17 -17

1 25

13 -10

3 16

8 0

27 7

12 40

i -7

10 6

4 18

5 152

8 121

27 27

13 59

9 26

6 128

4 191

7 47

5 145

8 238

7 97

5 135

u 134

5 7

8 12

25 13

18 8

u -8

u -12

0 158

4 55

6 119

8 1

6 74

7 87

2 155

2 177

2 27

1 42

5 93

4 132

12 119

1 173

19

15

21

13

20

28

12

14

18

15

12

15

17

20

18

17

15

16

12

21

13

8

7

6

25

28

20

8

18

8

13

13

8

9

10

5

3

6

2

8

6

13

8

86

Alloy

CMI

CM2

CM3

CM4

CM5

CM6

CM7

CM8

CM9

CM1O

CM]I

CM12

CM13

CMI4

CM15

CM16

CM17

CMI8

CMl9

CM20

CM21

CM22(setl)

CM22(set2)

CM 23

CM24

CM25

CM26

CM27(setl)

CM27(set2)

CM28

CM29

CM30

CM31

LA

LB

LC

LD

LG

LH

U

Li

LK

LO
T14 - cont'd

Baseline lndiated Baseline hadiated

cry :t, Gy ,Au, tAy UtS ±uts utS *uts tuts *Auts

MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa

ORNL 73 Weld

EPRI C weld

B.W. A weld

B.W. B weld

B.W. C weld

B.W. weld 62

B.W. weld 63

B.W. weld 65

B.W. weld 67

Rolls Royce Weld WV

Rolls Royce Weld WG

Rolls Royce Weld WP

ORNL Midland Weld

ORNL A302b

ORNL HSST02 plate

B.W. A508 plate

507 13 654

537 6 674

514 15 620

510 11 625

470 6 509

526 8 624

497 7 642

473 7 568

514 16 593

462 8 761

422 6 583

472 3 514

522 8 641

557 18 599

473 4 586

418 8 447

7 147

2 137

1 106

6 115

7 39

2 98

4 145

7 95

21 79

2 299

12 161

3 42

4 119

6 42

10 113

5 29

15 610 12 737

6 631 6 749

15 610 10 702

12 611 6 711

9 572 6 603

8 627 8 705

8 598 5 722

10 575 6 631

26 606 .15 675

8 559 8 829

14 533 8 675

4 571 3 608

9 623 9 723

19 690 19 723

11 619 4 714

9 573 9 591

u = underternined

87

5 127

2 118

1 92

5 100

1 31

4 78

1 124

4 56

15 69

6 270

13 142

2 37

5 99

8 33

8 95

3 18

13

6

10

8

6

9

5

7

21

10

15

3

10

21

9

9
Data for Capsule PB

Baseline hIadiated Baseline 1riated

ay :osy 0, : ay ±A* Bauts ±Uts uts ±uts Auts ±Auts

MPa MPa MPa MPa MPa MPa MPa MP MPa MPa MPa MPa

CM I-as tempered

CM2-as tempered

CM3-as tempered

CM4-as tempered

CM5-as tempered

CM6-as tempered

CM7-as tempered

CM8-as tempered

CM9-as tempered

CM1O-as tempered

CMI 1-as tempered

CM12-as tempered

CM 13-as tempered

CM 14-as tempered

CM15-as tempered

CM16-as tempered

CMI 7-as tempered

CMI8-as tempered

CM19-as tempered

CM20-as tempered

CM21-as tempered

CM22-as tempered

CM23-as tempered

CM24-as tempered

CM25-as tempered

CM26-as tempered

CM27-as tempered

CM28-as tempered

CM29-as tempered

CM30-as tempered

CM31-as tempered

alternate heat treatments

CM5* aged 480°100hrac

CM8* 400°C s.q.(not 4500)

CM12* s.r. 600° Shr/ ac.

CM18* s.r 600° 40hr/ ac.

CMI 9* s.r. 600° 8hr/ ac.

CMI 9* s.r. 6000 40hr/ ac.

CMl9* s.r. 600° 80hrl a.c.

CM19* 500°C s.q.(not 4500)

CM20* sr. 600° 40hr/ a.c.

CM20*500°C s.q.(not 450)

CM23* 400°C s.q.(not 450°)

CM26* aged 480°lOOhr/ac.

451

477

447

533

493

541

486

434

450

460

480

505

474

476

477

477

497

464

490

478

454

480

412

496

475

471

488

498

315

498

472

519

422

499

437

476

463

464

495

467

507

425

490

8 464

8 540

7 481

8 600

27 573

14 590

16 587

14 450

1 462

6 499

4 667

5 714

3 515

18 561

8 530

4 613

8 726

4 566

16 698

11 769

6 563

4 651

13 410

12 525

5 513

16 498

17 499

12 701

7 394

18 636

11 505

17 539

33 439

8 682

20 522

6 667

12 653

21 637

12 694

5 773

25 823

12 448

3 487

a

2 13 8 521 4 538 1

6 63 10 558 11 632 0

20 34 21 535 8 569 26

4 67 9 635 15 686 4

8 80 28 585 32 671 10

4 49 15 632 19 681 2

9 101 18 589 9 693 6

21 16 25 521 15 532 18

9 12 9 530 6 536 7

8 40 10 545 6 582 4

2 187 5 580 4 749 6

32 208 14 589 4 802 10

5 41 6 560 5 591 5

8 86 20 566 28 653 8

4 52 9 546 10 601 2

1 136 4 561 5 685 1

5 228 10 591 7 808 1

5 102 6 542 4 638 11

10 205 19 590 24 787 15

6 291 12 588 10 866 1

3 109 7 516 6 620 1

1 171 4 543 7 704 1

3 -2 13 492 12 490 6

u 29 u 619 23 664 u

5 38 7 563 19 594 8

4 27 17 572 21 585 5

34 11 38 571 19 581 28

16 203 20 587 18 776 19

25 79 26 430 5 486 26

20 138 27 591 28 696 10

10 33 15 556 15 586 15

35 20 39 639 20 640 46

15 18 36 504 18 510 15

5 183 9 591 17 749 10

3 85 20 518 6 583 1

15 191 16 572 10 741 6

4 190 13 554 25 727 0

5 173 22 566 25 713 10

6 200 14 601 11 775 11

9 306 11 550 4 842 16

3 316 25 609 33 908 11

37 23 39 503 14 522 35

26 -3 26 592 9 581 42

17

75

35

51

86

49

103

12

6

37

169

213

31

87

54

125

217

96

197

277

104

161

-2

45

32

12

10

189

56

105

30

I

6

158

65

169

173

147

174

292

299

19

-12

4

11

27

15.5

33.5

19.1

10.8

24

9

7

7

11

7

29

10

5

7

11

29

10

6

7

14

u

21

22

34

26

27

30

21

* 50

23

20

6

12

25

27

16

17

35

38

43

88

Alloy
Baselne Eradiaed

°Y ±C01 CaY tGy AcOy ACoy

MPa MPa MPa MPa MPa MPa

462

484

513

493

498

497

527

537

497

154

158

152

216

220

174

175

176

179

226

154

207

214

240

196

169

218

223

181

209

10 534 0 71

6 569 5 86

2 729 0 216

10 529 29 36

8 558 2 59

8 623 4 125

12 683 3 156

13 667 u 130

10 719 3 223

15 196 20 42

17 260 17 102

2 222 43 70

6 522 3 306

3 428 3 208

7 348 6 175

12 393 4 218

15 351 2 175

8 397 17 218

5 259 4 33

11 178 19 24

7 356 5 149

17 430 4 217

10 464 11 225

14 443 14 247

3 321 1 152

6 536 8 318

7 443 3 219

13 220 1 39

7 245 1 36

Baselne Iffadiad

uts tuts uts tuts Auts t-Auts

MPa MPa MPa MPa MPa MPa

579 8 643 1 64 8

600 4 689 4 90 6

649 7 840 0 191 7

613 16 654 19 41 25

620 13 665 0 45 13

615 5 723 4 108 6

641 14 775 2 134 14

644 8 762 u 118 8

613 10 827 3 214 11

25 217 13 230 26 14

24 215 12 325 16 110

43 204 16 257 38 54

7 310 7 579 2 268

4 322 5 489 1 167

9 257 10 390 1 134

13 252 14 444 4 192

15 261 22 412 1 151

18 257 10 447 10 190

6 289 8 299 4 10

22 269 2 283 9 14

9 277 19 400 1 123

18 312 9 493 1 181

15 332 11 523 3 192

20 327 21 515 7 187

3 272 5 376 7 104

10 304 5 582 14 278

8 343 14 520 2 176

13 240 7 258 3 18

7 271 9 287 9 16

29

20

41

7

5

10

15

22

14

9

9

19

9

12

22

9

15

14

8

13

U = undeternined

89

PB cont'd

Alloy

LA

LB

LD

LG

LH

LI

Li

LK

LO

VA

VB

Vc

VD

VE

VG

VH

VI

VJ

VK

VL

VM

VN

Vo

VP

VR

Vs

VT

W

VW
Data for VSR Capsule

Baseline lradiated

Alloy SR

CM3 5900C/24h

CM3 590°C/48h

CM3 590°C/96h

CM3 607°C/12h

CM3 607°C124h

CM3 607°C/48h

CM3 607°C/96h

CM3 607°C/24h-air cool

CM3 6240C/12h

CM3 624°C/24h

CM3 624°C/48h

CM3 641°C16h

CM3 641°C/12h

CM3 641°C/24h

CM3 AT

590°C24h

590°C148h

590°C/96h

607°C/12h

607°C/24h

607°C/48h

607°C/96h

607°C124h-air cool

624°C/12h

624°C/24h

624°C148h

641°C/6h

641 C/12h

641 °C/24h

CMII 590 0

C/24h

CMII 590°C/48h

CMI I 590°C/96h

CMI I 607°C/12h

CMI I 6070C/24h

CMI I 607°C/48h

CMI I 607°C196h

CMI I 607°C/24h-air cool

CMI I 624°C112h

CMII 624°C124h

CMI I 624°C/48h

CMI I 641 C/6h

CMI I 641C112h

CM I 641°C124h

CMIl AT

Baseline hmiated

a, ±ay cy C,1 Aay ±Aq, uts ±uts uts ±uts Auts ±Auts

MPa MPa MPa MPa MPa MP MP MPa MPa MPa MPa MPa

447

414

369

431

428

410

302

448

421

417

397

409

392

306

479

359

337

267

388

No

371

257

411

375

365

364

363

355

293

4 457

23 445

7 394

21 456

12 459

13 438

16 285

1 455

26 449

4 440

1 413

3 432

1 410

u 334

7 507

47 426

35 410

5 358

u 440

da

5 419

8 320

u 447

u 430

8 426

31 412

6 407

u 412

21 360

471 14 612

450 6 600

421 23 591

466 21 633

446 15 582

445 18 596

365 34 573

486 1 588

452 12 612

453 2 582

425 0 571

432 2 600

432 9 590

393 0 585

490 5 636

1 10

21 31

8 25

15 25

0 31

5 27

u -17

3 18

6 28

4 23

8 16

4 23

4 18

30 28

1 28

4 537

31 495

11 450

25 523

12 531

14 497

16 422

3 520

27 513

6 508

9 491

5 506

4 488

30 434

7 566

33 67 57 468

29 73 46 448

54 92 54 410

22 52 22 494

1 49 5 473

11 63 14 399

8 36 8 494

23 55 23 482

17 61 19 471

12 48 33 457

2 44 6 480

10 57 10 465

41 68 46 428

6 141

7 151

5 170

4 167

8 136

13 151

6 208

16 102

17 161

11 130

8 146

24 169

25 158

2 192

8 146

15 566

10 538

24 499

21 570

17 539

22 545

34 463

16 574

21 557

12 557

8 523

24 534

26 536

2 500

9 577

8 540

24 517

4 467

21 539

16 548

22 524

6 411

6 527

25 538

7 529

0 501

4 523

1 500

u 443

4 596

44 522

24 505

4 468

u 541

8 507

13 444

u 541

u 526

9 529

u 507

11 512

u 520

14 478

23 689

9 677

27 656

20 714

22 650

23 673

19 635

1 654

15 693

1 659

0 652

3 686

10 674

0 670

19 722

6

29

9

21

0

6

u

9

10

6

6

8

4

17

2

3

22

16

16

17

27

-11

19

25

21

10

18

12

9

10

38

10

29

16

23

6

11

27

9

6

9

4

17

33 54 55

24 57 34

32 58 32

25 47 25

7 34 11

4 45 13

6 47 6

12 44 12

12 58 15

5 50 5

1 32 11

11 55 11

33 50 35

8 123

4 139

4 157

3 144

6 Ill

16 128

4 173

16 80

18 136

11 103

11 129

28 152

24 138

0 170

13 145

24

10

27

20

23

28

20

16

23

11

11

28

26

0

23

90

CM5

CM5

CM5

CMS

CM5

CM5

CM5

CMS

CMS

CMS

CM5

CM5

CM5

CM5

I
VSR - cont'd

Alloy SR

CM12 590°C/24h

CM12 590°C/48h

CM12 590°C/96h

CM12 607°C112h

CM12 607°C124h

CM12 607°C148h

CM12 607°C/96h

CM12 607°C/24h-air cool

CM12 624°C112h

CM12 624°C124h

CM12 624°C148h

CM12 641°C/6h

CM12 641 C/I2h

CM12 641°C/24h

CM12 AT

CM13 590°C/24h

CM13 590°C/48h

CM13 5900C196h

CM13 607°C/12h

CM13 607°C/24h

CM13 607°C148h

CM13 6O7°C196h

CM13 624°C/l2h

CM13 624°C124h

CM13 624°C148h

CM13 641°C16h

CM13 641°C112h

CM13 641°C124h

CM13 AT

CM16 590°C/24hrs

CM16 590°C148hrs

CM16 590°C/96hrs

CM16 607°C/12hrs

CM16 6070C/24hrs

CM16 607°C148hrs

CM16 607°C/96hrs

Baseline riadiaed

CG toy cy ±UY

MPa MPa MPa MPa

494

486

482

488

499

475

461

495

487

479

464

478

466

452

515

438

416

407

439

419

368

327

408

294

192

304

197

190

479

469

438

450

452

450

448

374

CM16 607°CT24hrs-air cool 459

CM16 624°C112hrs 427

CM16 624°C/24hrs 418

CM16 624°C/48hrs 410

CM16 641°C/6hrs 451

CM16 641°C112hrs 395

CM16 641°C/24hrs 354

CM16 AT 503

u 621

u 617

u 600

u 633

u 619

1 607

u 594

27 650

u 624

u 613

u 610

1 627

4 612

2 610

4 708

23 482

24 464

8 449

21 473

5 475

17 424

0 423

u 456

u 380

1 293

62 410

1 293

2 286

13 537

15 600

6 574

1 554

21 578

14 584

11 557

20 533

16 581

12 566

4 562

17 554

4 561

24 564

1 515

6 602

Baseline Imdialed

Aa, ±bao uts ±uts uts tuts Auts ±A^uts

MPa MPa MPa MPa MPa MPa MPa MPa

4 127

5 131

3 118

8 145

1 120

14 133

8 133

u 155

9 137

1 134

2 146

1 149

13 146

6 159

u 193

4 580

5 577

3 563

8 571

1 589

14 562

8 533

27 572

9 583

1 557

2 546

1 566

13 554

6 531

4 601

23 45 32 522

16 48 29 493

4 42 9 486

1 34 21 530

6 56 8 504

18 56 25 452

13 96 13 430

11 48 11 '496

u 86 u 412

4 101 4 348

31 106 70 417

4 96 4 355

5 96 5 353

8 52 15 566

1 131

5 136

6 104

1 126

17 134

4 109

8 159

11 122

2 139

3 144

1 143

6 110

1 168

4 162

3 99

15 569

8 525

7 534

21 544

22 546

12 542

22 465

19 540

12 521

5 510

17 507

8 550

24 497

4 466

7 588

u 688 7

u 680 0

u 660 10

u 707 3

u 695 2

8 679

u 644

33 719

u 685

u 675

u 674

6 705

2 683

1 672

10 795

30 559

30 530

11 513

31 548

4 561

11 493

0 495

u 530

u 467

0 397

29 495

2 400

3 405

25 631

9 679

9 651

4 620

21 658

23 666

12 633

11 599

3 653

15 644

8 641

16 636

0 640

17 646

3 597

3 691

108

103

97

136

106

13 117

6 111

u 147

8 102

1 118

11 128

1 139

9 129

1 142

u 194

7

0

10

3

2

16

6

33

8

1

11

6

9

2

10

30 37 43

16 37 34

7 28 13

6 18 32

8 57 9

15 41 19

11 65 11

20 34 20

u 55 u

5 49 5

33 78 44

2 45 3

6 52 6

4 62 25

1 110

13 126

6 86

11 114

13 120

6 91

6 134

19 113

12 123

11 131

4 128

6 90

6 149

7 131

13 103

9

15

7

24

26

13

12

19

19

14

17

6

18

8

13

91
VSR - cont'd

Baselire 1zmae Baseline ITadiated

(Ty toy ay :toy a, tAo uts ±uts uts tuts Auts t:uts

Alloy SR MPa MPa MP MPa MPa MPa M a MPa MPa MPa MPa MPa

CMI8 5900C/24hrs 451 16 523 2 72 16 539 12 601 4 62 12

CM18 590°C/48hrs 446 10 505 6 58 12 537 4 574 6 37 7

CM18 590°C/96hrs 418 13 480 8 62 16 497 19 545 20 48 27

CM18 607°lC2hrs 451 9 522 9 71 13 541 10 593 8 52 13

CM18 6070C/24hrs 433 8 510 9 77 12 521 15 587 4 66 15

CM18 607°C148hrs 435 6 499 3 64 7 521 3 572 1 51 3

CM18 6070C/96hrs 394 7 460 2 66 7 471 4 522 1 51 4

CM18 607°C/24hrs-aircool 452 4 532 6 81 7 529 1 598 7 69 7

CM18 624°C112hrs 439 3 506 13 67 13 528 4 579 11 51 12

CM18 6240C/24hrs 431 15 498 0 67 15 517 6 576 3 59 6

CM18 624°C/48hrs 413 6 486 6 73 8 502 7 564 9 62 12

CM18 641C/6hs 421 2 498 4 77 4 519 6 581 3 62 7

CM18 641°C112hrs 420 5 490 8 70 9 505 9 564 8 59 12

CM18 641°C/24hrs 402 5 481 1 79 5 491 2 554 3 63 4

CM18 AT 478 5 579 5 101 7 569 10 659 6 90 12

CM19 590°C/24h 449 12 626 4 177 13 543 19 705 2 162 19

CM19 590°C148h 448 6 595 1 147 6 545 10 663 10 118 14

CM19 590°C/96h 440 12 582 2 142 12 528 25 637 1 109 25

CMI9 607°C12h 446 8 636 8 190 11 541 17 718 11 176 20

CM19 607°C24h 447 5 615 11 168 12 538 11 690 12 152 16

CMI9 607°C148h 435 12 597 3 162 12 528 21 679 2 150 21

CM19 6070

C/96h 404 17 582 9 178 20 483 17 644 8 161 19

CMI9 607°C/24h-air cool 459 16 612 4 153 17 533 21 681 14 148 25

CM19 624°C/12h 437 14 618 11 181 18 536 22 697 18 161 28

CM9 624°C24h 430 5 601 5 170 7 531 9 681 6 149 11

CM9 624°C148h 419 23 588 14 169 27 516 28 669 16 152 32

CM19 641°C16h 432 1 609 1 177 1 542 11 692 2 150 11

CM19 641°C112h 420 16 595 6 190 17 528 16 671 8 160 18

CMI9 641°C24h 369 3 575 4 206 5 482 3 656 4 174 5

CM19 AT 495 4 671 3 176 5 568 19 756 3 188 19

92

I
VSR - cont'd

Baseline Indiated

Alloy SR

CM20 590°C124h

CM20 590°C/48h

CM20 590OC/96h

CM2O 607°C1l2h

CM20 607°C/24h

CM20 607°C/48h

CM20 607°C/96h

CM20 607°C/24h-air cool

CM20 624°C/12h

CM20 624°C124h

CM20 624°CJ48h

CM20 641°C/6h

CM20 641°C/12h

CM20 641°C/24h

CM20 AT

gy ±, ;y , ±0 y , Ac, uts

MPa MPa MPa MPa MPa MPa MPa

473

461

459

453

468

466

449

409

450

449

406

439

417

384

490

15 722

8 722

15 704

3 722

14 722

11 719

11 712

15 696

7 726

11 721

20 711

11 726

24 710

10 707

2 759

10 249

8 261

1 245

4 269

4 254

2 253

12 263

6 287

6 276

0 272

9 305

1 287

1 293

4 323

1 269

Baseline hrAdiated

18 566

12 556

15 547

5 530

14 561

11 563

17 543

16 496

10 553

11 552

22 513

11 546

24 528

11 510

2 574

±uts uts tuts Auts tAUts

MPa MPa MPa MPa MPa

24 789

9 792

22 757

1 780

19 794

13 787

10 779

12 754

23 799

18 790

18 774

19 804

21 780

12 776

1 837

9 223

11 236

1 210

1 250

8 233

4 224

23 236

4 258

8 246

0 238

5 261

13 258

12 252

3 266

2 263

26

14

22

2

20

13

25

12

24

18

19

23

24

12

2

93
NRC FORM 13! US. NUCLEAR REGULATORY COMMISSION 1. REPORT NUMBER

(2-M (Aned by NRC, Add VaL. Supp., Rev..

32oM 2. BIBUOGRAPHIC DATA SHEET dMumNumb%VSfly

2. T_LE AN SUBTrTLE NUREG/CR-6778

The Effects of Composition and Heat Treatment on 3. DATE REPORT PUUSHE

Hardening and Embrittlement of Reactor Pressure Vessel Steels T 2 2 Orz 

May

4. FIN OR GRANT NULBER

Y6396

5. AUrHOR(S) 6. TYPE OF REPORT

G. R. Odette, .E. Lucas, D. Klingensmith, B. D.Wirth and D. Gragg

7. PERIOD OOVERED fnciu Dow)

S. PERFORMING ORGANATION - NAME AND ADDRESS (Yr poveOA'axw% earRegmn U& vr.gufbyCamss and mukdg addius: r-&Wbr.

pwide mud ame mei addres)

Department of Mechanical and Environmental Engineering

University of California Santa Barbara

Santa Barbara, CA 93106

S. SPUORMN ORGANIZATION- NAM AN AnOESS PF#, a s &twtcc*cr m pr,d9=kW Cfflwbg Ooia U..s NRWd9f9fbuffL an weft ad*frSs)

Division of Engineering Technology

Office of Nuclear Regulatory Research

U.S. Nuclear Regulatory Commission

Washington, DC 20555-0001

10. SUPPLEMETARY NOTES

C. Santos, NRC Project Manaaer

11. ABSTRACT MM *vds brss)

This report addresses several important issues regarding possible revisions of RG 1.99 Rev. 2 to predict irradiation

induced hardening (y) and hence embrittlement manifested as shifts (AT) in the 41 J Charpy test transition

temperature. We are developing a Acy database from controlled, single-variable experiments to map the individual

and interactive effects of metallurgical and environmental variables.The data are generated from a large matrix of

composition-controlled alloys Irradiated in the Irradiation Variables Fadlity (IVAR) at the University of Michigan Ford

Research Reactor.The results provide quantitative and Independent validation of the two component form of the

NUREG/CR-6551 model, comprised of matrix feature (MF) and copper rich precipitate (CRP) terms. The IVAR database

also quantitatively supports: 1) the model treatments of a strong copper-nickel interaction in the CRP term; 2) the

treatment of phosphorous in the MF term; 3) an independent validation of a maximum effective matrix copper level

(Cumax) of around 03% following heat treatment and 4) a sensitivity of Cumax to nickel content.The IAR database

also shows: 1) manganese interaction with copper and nickel in the CRP contribution; 2) manganese and nickel

Increase the MF term; 3) a somewhat unanticipated effect of flux and flux-composition interactions on the fluence

dependence of AMy and AT; and 4) a possible reduction in the effect of phosphorus at higher copper.

12. KEY WOD SAE S .d. "rs -RO rs w,ss l w in . iH r) 1& AVALABLnrY STAEMENr

Reactor Pressure Vessel, Embrittlement, unEmfe

Embrittlement Mechanisms

(This Ave)

unclassified

(Ihrs Rep"~

unclassified

15. NLLIBER OF PAGES

16. PRICE

NRC FORM 33 ) Thi b m wsoe1bvk pd by M Ftm Fnm. Whc
JPrinted

on recycleds

Fe a Rpaper P

Federal Recycling Program

I
NUREG/CR-6778 THE EFFECTS 0F COMPOSITION AN!) H1EAT.REATMENT' N HARDEINING AND

EMBRITTLEMENT OF REACTOR PRESSURE VESSEL STEELS

UNITED STATES

NUCLEAR REGULATORY COMMISSION

WASHINGTON, DC 20555-0001

OFFICIAL BUSINESS

MAY 2003

-------