**ENERGY RESEARCH-LABORATORY\
TECHNOLOGY RESEARCH PROGRAM**

**PROPOSAL FOR FY 1999 ER-LTR MULTIYEAR CRADA PROJECT**

**A Novel Methodology for Welding\
Consumable Design and Optimization**

[Technical Focus Area]{.underline}: Advanced Materials & Intelligent
Processes and Controls

**[Participants]{.underline}**

*Oak Ridge National Laboratory*

*Lincoln Electric Company*

**[ORNL Principal Investigator]{.underline}**

S. S. Babu

J. M. Vitek

Metals and Ceramics Division

Tel: (423) 574-4806

Fax: (423) 574-4928

Email: <Babuss@ornl.gov>

Email: <Vitekjm@ornl.gov>

Internet: http://engm01.ms.ornl.gov

September 15, 1998

**Agreement**

The signatures of the industry principal investigator and the ORNL
principal investigator indicate agreement and concurrence with all
aspects of this proposal.

M. Quintana S. S. Babu

Senior Project Engineer Development Staff

Welding Consumable Division Metals and Ceramic Division

Lincoln Electric Company Oak Ridge National Laboratory

Cleveland, OH 44117 Oak Ridge, TN 37831

> J. M. Vitek
>
> Senior Research Staff
>
> Metals and Ceramics Division
>
> Oak Ridge National Laboratory
>
> Oak Ridge, TN 37831

Table of Contents

Technical Abstract [1](#technical-abstract)

Project Objective: [2](#project-objective)

Technical Background [2](#technical-background)

Scientific and Technical Approach
[4](#scientific-and-technical-approach)

Description of Operational Characteristics
[5](#description-of-operational-characteristics)

Description of Weld Thermal Cycles and Weld Pool Geometry
[5](#description-of-weld-thermal-cycles-and-weld-pool-geometry)

Development of Microstructure-Property Correlation
[7](#development-of-microstructure-property-correlation)

Development of an Integrated Computer Aided Design and Optimization Tool
[8](#development-of-an-integrated-computer-aided-design-and-optimization-tool)

Work Plan and Division of Responsibilities
[8](#work-plan-and-division-of-responsibilities)

Work Plan [8](#work-plan)

Year 1 [9](#year-1)

Year 2 [10](#year-2)

Year 3 [10](#year-3)

Division of responsibilities [11](#division-of-responsibilities)

Relevance to DOE Programs [11](#relevance-to-doe-programs)

Anticipated Commercial Potential [11](#anticipated-commercial-potential)

Appendices [i](#appendices)

1\. Key Personnel and Facilities [i](#key-personnel-and-facilities)

2\. Selected Relevant Publications [i](#selected-relevant-publications)

3\. Curriculum Vitae of Key Team Members
[ii](#curriculum-vitae-of-key-team-members)

S. S. Babu [iii](#s.-s.-babu)

J. M. Vitek [v](#j.-m.-vitek)

M. Quintana [vii](#m.-quintana)

GENERAL DYNAMICS, ELECTRIC BOAT DIVISION, GROTON, CT
[vii](#general-dynamics-electric-boat-division-groton-ct)

EDUCATION [viii](#education)

PROFESSIONAL ACTIVITIES [viii](#professional-activities)

4\. Previous Research Demonstration
[x](#previous-research-demonstration)

5\. Budget and Explanation [xii](#budget-and-explanation)

Letter of Interest from Industrial Partner
[xiii](#letter-of-interest-from-industrial-partner)

**ENERGY RESEARCH-LABORATORY TECHNOLOGY RESEARCH PROGRAM**

**PROPOSAL FOR FY 1999 ER-LTR MULTIYEAR CRADA PROJECT**

+-------------+--------------------------------------------------------+
| **Proposal  | ORNL 99 - 7                                            |
| No**.:      |                                                        |
+-------------+--------------------------------------------------------+
| **Project   | A Novel Methodology for Welding Consumable Design and  |
| Title**:    | Optimization                                           |
+-------------+--------------------------------------------------------+
| *           | [Advanced Materials and Intelligent Processes and      |
| *Technical\ | Controls]{.underline}                                  |
| Di          |                                                        |
| scipline:** | Welding consumables are used to join a wide range of   |
|             | materials and, therefore, play a critically important  |
|             | role in the welding industry. The ability to optimize  |
|             | welding consumables in a reliable and efficient manner |
|             | is crucial to ensure that the US welding industry      |
|             | remains competitive in a global marketplace.           |
|             | Traditional welding consumable design involves         |
|             | expensive and time intensive experimental trials,      |
|             | characterizations and optimizations based on trial and |
|             | error. In this research proposal we propose to develop |
|             | an alternative and novel design and optimization       |
|             | methodology that will lead to efficient and flexible   |
|             | welding consumables that can enhance the capability    |
|             | and performance.                                       |
+-------------+--------------------------------------------------------+
| *           | S. S. Babu , Metals and Ceramics Division, ORNL, (423) |
| *Laboratory | 574-4806                                               |
| PIs**:      |                                                        |
|             | J. M. Vitek, Metals and Ceramics Division, ORNL, (423) |
|             | 574-5061                                               |
+-------------+--------------------------------------------------------+
| *           | Lincoln Electric Company, Cleveland, OH 44117          |
| *Industrial |                                                        |
| Partner**:  |                                                        |
+-------------+--------------------------------------------------------+
| **Industry  | Lincoln Electric, headquartered in Cleveland, Ohio, is |
| Partner     | a worldwide manufacturer of arc welding consumable     |
| Profile**:  | products and a major producer of premium quality       |
|             | industrial electric motors, robotic welding systems,   |
|             | environmental systems, and plasma and oxy-fuel cutting |
|             | equipment.                                             |
+-------------+--------------------------------------------------------+
| **Partner   | M. Quintana, Consumable Research and Development,      |
| PI**:       |                                                        |
|             | Lincoln Electric Company, Cleveland, OH 44117.         |
+-------------+--------------------------------------------------------+
| **Project   | 36 months                                              |
| Duration**: |                                                        |
+-------------+--------------------------------------------------------+

Budget Information (details in Appendix 5)

  ------------------- ----------------------- --------------------------- ------------------------
  [Fiscal             [DOE                    [Industry Partner           
  Year]{.underline}   Funding]{.underline}    Contribution]{.underline}   

                                              [In-Kind]{.underline}       [Funds-In]{.underline}

  FY 1999 (\~0.5 yr.) \$ 100,000              \$ 100,000                  \$ 10,000

  FY 2000             \$ 200,000              \$ 200,000                  \$ 15,000

  FY 2001             \$ 200,000              \$ 200,000                  \$ 15,000

  FY 2002 (\~0.5 yr.) \$ 100,000              \$ 100,000                  \$ 10,000

  Total               \$ 600,000              \$ 600,000                  \$ 50,000
  ------------------- ----------------------- --------------------------- ------------------------

# Technical Abstract

Welding consumables are used to join a wide range of materials from
steels to advanced nickel base superalloys and, therefore, play a
critically important role in the welding industry. The ability to
optimize welding consumables in a reliable and efficient manner is
crucial to ensure that the US welding industry remains competitive in a
global marketplace. Welding consumables must be designed to provide the
required operational characteristics (such as arc stability over a wide
range of parameters, deposition rate appropriate to the application,
minimal spatter and fume, etc.) and weldment properties (such as
cracking resistance, strength, toughness, etc.) The operational
characteristics and weldment properties are not independent of each
other. Moreover, the nature of the interdependency of these two
characteristics is a function of the type of material being joined and
the welding arc atmosphere. Traditional welding consumable design
involves expensive and time-intensive experimental trials,
characterization and optimization based on trial and error. In this
research, we propose to develop an alternative and novel welding design
and optimization methodology that should result in greater efficiency
and improved performance.

This alternative methodology will rely on fundamental laws of physical
processes that determine the operational characteristics and weldment
properties. Some of these physical processes include arc-plasma
interactions, gas-metal reactions, slag-metal reactions, solidification
and solid-state phase transformation \[1\]. Over the past three decades,
significant progress has been made in the fundamental understanding of
individual physical process. Many theoretical and computational models
have been developed to describe individual process \[2\] as well as some
of the complex interaction \[3\]. However, there is nearly a total
absence of applied research to extend this knowledge to the design and
optimization of welding consumables. Recent collaborative research
between ORNL and Lincoln Electric Company has shown the potential of
such applied research by successfully understanding microstructure
development in self-shielded flux cored arc welds \[4\]. This was made
possible by coupling the laws of gas-metal reactions, thermodynamic
phase stability, and atomic diffusion models of phase transformations.
Our research proposal aims to develop a generalized methodology based on
coupling and extending applicable models for individual processes, in
order to improve the efficiency and potential of weld consumable design
and optimization.

This research proposal addresses goals and issues in two DOE ER-LTR
technical focus areas, namely advanced materials and intelligent
processes and controls. The successful completion of this project will
provide for an efficient and reliable methodology for welding consumable
development for advanced structural alloys. Moreover, the project will
use both advanced thermodynamic-kinetic models of phase transformations
as well as semi-empirical techniques, such as artificial neural
networks, to develop improved design of welding consumables for better
properties. The research will also leverage ongoing BES-sponsored
welding science programs at ORNL. It will also utilize, and strengthen
the ORNL core competency in materials science, and contribute to US
competitiveness in the welding industry, which is considered to be
critical for both energy and defense related projects.

This research will have significant impact on the shipbuilding,
construction, heavy machine, power generation, and oil and gas
industries. Previous collaborative research efforts \[4-7\] with
industry and governmental agencies have indicated the commercial
potential of the proposed research methodology.

# Project Objective:

The research proposal aims to develop a generalized methodology to
describe operational characteristics and mechanical property development
as a function of alloy composition in an integrated fashion. However, to
achieve this we need to overcome technical issues in the five categories
listed below. In this research, all of these issues will be addressed
and relevant existing models will be identified and modified to meet the
current needs.

1.  Description of operational characteristics as a function of welding
    process (FCAW-S and FCAW-G), process parameters (voltage, current,
    velocity and plate thickness) and consumable variables (composition,
    flux, shielding gas, and consumable wire size),

2.  Description of weld thermal cycles and weld pool geometry as a
    function of welding process parameters,

3.  Description of microstructure development as a function of
    composition, dissimilar filler wire combinations, and thermal
    history

4.  Development of microstructure-property correlation, and

5.  Integration of the above to develop a computer aided design and
    optimization tool.

The research on the above five issues will be discussed in detail later.
The research will involve extensive microstructural characterization,
computer model development based on fundamental thermodynamic and atomic
diffusion theories supplemented by semi-empirical techniques such as
artificial neural networks, production of experimental welds, as well as
measurement and analysis of welding operational characteristics. The
final outcome of this research will be an integrated computational tool
by which welding consumable design can be performed efficiently and
reliably for both existing and new materials. In this program, the
research will focus on Fe-C-Mn-Al-Ti-O-N low-alloy steel materials and
gas shielded (FCAW-G) and self-shielded flux-cored (FCAW-S) arc welding
processes. However, the methodology will be in a general form so that it
can be extended to other advanced materials and processes.

# Technical Background

The design of welding consumables that meet both operational
requirements and weldment property needs is far from trivial.
Operational characteristics that must be considered include arc
stability, deposition rate, and extent of spatter and fumes. The
operational characteristics control the welding productivity, and
therefore the cost effectiveness of welding operations. Weldment
properties include yield strength, tensile strength, ductility and
toughness. The desired weldment properties are controlled by the service
requirements for the final fabricated structure. Both operating
characteristics and weldment properties are affected by welding process
parameters such as voltage, current, speed, and consumable parameters
such as composition, shielding gases, and fluxes \[8\]. Previous work
has shown that these two considerations are not independent of each
other. For example, the operational conditions control the weld thermal
cycle and final weld metal composition. In-turn, thermal cycles and weld
metal composition control the final microstructure. Finally, the
microstructure controls the final properties. Therefore, it is critical
to consider all of these interactions when designing weld consumables in
order to get optimum results.

In some cases, the optimum conditions for operational characteristics
may not overlap with optimum conditions for superior weldment
properties. However, these inter-relations between operational
characteristics and properties are specific to particular alloy classes
and welding processes. Therefore, they can not be generalized.
Consequently, traditional welding consumable design has involved
extensive, expensive experimentation by trial and error. This trial and
error methodology severely limits the potential for optimization of
existing consumables and also the development of new consumables for new
classes of structural alloys. The above constraint is mainly due to the
absence of predictive tools that can consider the interactive effects of
welding consumable and welding process parameters on operational
characteristics and weldment properties.

Over the past three decades much of the research has focussed on
developing an understanding of each of the above physical processes
\[1\]. Research at the Pennsylvania State University (PSU) has focused
on the arc plasma - liquid metal interaction \[1\]. Their work has shown
the effect of plasma on reducing the vaporization of elements from
metals. In addition, models have been developed to understand the
vaporization of alloying elements and dissolution of gases in the weld
pool. Research at PSU and Oak Ridge National Laboratory (ORNL) has led
to the development of computational heat transfer and fluid flow models
to describe the weld pool development \[2, 9\]. This research has shown
the importance of the rate of change of surface tension with temperature
on the weld pool flow behavior and resulting weld pool shapes \[10\]. In
addition, the heat transfer and fluid flow models can be used to
describe complex thermal excursions of inclusions in a steel weld metal.
Research at Colorado School of Mines (CSM) has considered slag-metal
reactions, solidification partitioning and its effect on microstructure
of low-alloy steel weld \[11\]. Fundamental aspects of inclusion
formation in liquid steel are being studied at ORNL and have led to
major breakthrough in understanding of inclusion formation in steel weld
\[3\]. This study has shown that inclusion formation in steel welds can
be described by overall transformation kinetic theories. Based on these
theories a model has been developed to describe inclusion formation as a
function of weld metal composition and cooling curve. This work has
shown that the sequential oxidation of various elements in liquid steel
will vary depending upon the weld metal composition as well as cooling
rate, contrary to the fixed oxidation sequence assumed before. In
addition, experimental investigations showed \[see Fig. 1\] fluid
velocity gradient lead to rapid inclusion coarsening \[12\]. Recently,
the effects of fluid flow on the inclusion formation have also been
considered \[9\] using computational heat transfer and fluid flow
models.

![](media/image1.png){width="2.984027777777778in"
height="2.122916666666667in"}
![](media/image2.wmf){width="2.9583333333333335in"
height="2.125in"}(*b*)

Figure 1: Comparison of inclusion size distribution from submerged arc
weld in the (*a*) as-welded condition and (*b*) after holding at 1480 °C
for 60 seconds with fluid flow velocity gradients.

The relationship between crystallographic conditions and weld
solidification characteristics is being modeled at ORNL. \[13\].
Bhadeshia et al. devoted extensive efforts to describe the
microstructure development with theories of phase transformation \[14,
15\]. Preliminary studies are underway to relate the weld microstructure
to properties \[16, 17\]. Currently, there are no physical models that
describe some simple welding characteristics such as spatter and fumes
as a function of consumable and process parameters in a quantitative
manner. [Although the above work addresses each of the physical process
and some limited interactions among them, there is no comprehensive
predictive tool that considers all of the interactions in an integrated
and quantitative way.]{.underline}

# Scientific and Technical Approach

Many of the individual process models are developed \[1\]. However, some
are not available and need to be generated and also existing models need
to be enhanced. By combining five modular research tasks as described in
detail in the following sections, an integrated computer aided design
and optimization tool will be developed. A general overview of the
approach is shown in Fig. 2. The two sets of variables, i.e., process
parameters and consumable parameters need to be considered for each of
the modules that consider the different physical process.

![](media/image3.wmf)

Figure 2. Schematic illustration of overview of the project. The
connecting lines between each task indicate that their results may
interact with each other.

The overall integrated predictive tool will consider the interactions
among these sets of physical process. This modular approach is preferred
for the following reasons. At present, available fundamental models
cannot consider all the physical processes and, therefore, there is a
need to use semi-empirical and empirical models such as artificial
neural networks. However, as new and improved fundamental models for
physical processes are developed \[18\], the modular approach proposed
in this project allows for flexible and efficient incorporation of new
developments. Each module listed in Fig. 2 is discussed in detail, in
terms of challenges, technical details and approaches to development.

[As mentioned earlier, the research will focus on low-alloy steel
materials and gas-shielded flux cored arc (FCAW-G) and self-shielded
flux cored (FCAW-S) arc welding processes.]{.underline}

## Description of Operational Characteristics 

Although much experimental information exists on operation
characteristics of welding process such as arc stability, deposition
rate, spatter formation and fumes with different welding consumables,
there is no established quantitative method to predict them.

Previous works in this area have shown that these characteristics may
not be independent of each other. Arc stability in gas metal arc welding
is related to the ratio of arc-period to short-period \[19\], the type
of shielding gas \[8\] and the melt-back distance. The melt-back
distance is related to Joule-heating that will depend on the welding
consumable composition. The deposition rate is related to the type of
metal-transfer for a given welding process parameter. These can be
related to the arc-voltage condition \[20\]. There are fundamental
models that exist to describe molten droplet formation at the consumable
and are related to welding current by considering electromagnetic pinch
effect, surface tension, gravitation, and momentum transfer due to
motion of the consumable \[21\]. Weld spatter formation is also related
to the type of metal transfer \[8\]. Most of the welding consumables
produce fumes containing chromium, manganese, and other gases. These
pose serious health hazards and will be impacted by anticipated
reductions of exposure limits \[22\]. The particle size distribution,
and specific surface area of these particles in fumes are known to
change with different welding processes \[23\]. However, there are no
models to describe them. The elemental evaporation models and
thermodynamic stability of various species in gases can be used as a
guideline to estimate the welding fume composition \[24\].

Coupling all of the above research in the form a fundamental numerical
model to predict the arc stability, maximum deposition rate, propensity
for spatter formation, and welding fume characteristics as a function of
welding consumable composition and process parameter range is an
extremely difficult problem. However, it is indeed possible to develop
semi-empirical models and neural networks based on the above work for
use as a predictive tool. However, the challenge will be to design these
predictive tools to capture the physical process effects in a
generalized fashion without being specific to the experimental
conditions involved.

In this task, published experimental techniques will be used to measure
the operational characteristics quantitatively. Based on the new
experimental and existing industrial data provided by Lincoln Electric
Company, critical operation characteristics will be identified and
analyzed. This information will be used to develop appropriate
artificial neural networks and semi-empirical models for this task. The
model will be evaluated with new experimental data and independent data
sets and also with extensive sensitivity analysis. This model will be
available as a computer tool at the end of first phase of the
project.[^1]

## Description of Weld Thermal Cycles and Weld Pool Geometry

Descriptions of thermal cycle and weld pool shape as a function of
welding process parameters has been studied extensively in the past and
continue to be investigated by many researchers \[2,9,10\]. Due to the
enormous literature on this subject, only salient features are outlined.
The models can be classified into two categories. The first category is
the analytical modes, which uses modified forms of solutions to heat
transfer equations developed by Rosenthal to predict weld pool shape and
thermal cycle \[1\]. Analytical and computer models are available to
describe the thermal history at various locations of a weldment.
However, these models are not easily extended to a wide range of welding
processes. The second category is the numerical heat transfer models
with or without consideration of fluid flow conditions \[2\]. These
models are based on the numerical solution of the equations of
conservation of mass, momentum and energy in two or three dimensions.
Although, these models are powerful and can describe fine details of the
weld pool development, they are computationally intensive and require
considerable expertise in the computer systems. The complications of the
numerical models increase if the consumable effect is considered \[9\].
Numerical models are often cumbersome, computationally intensive, and
often not suited for process optimization. Recent work has shown that by
calibrating analytical models or coupling neural network models with
experimental parameters such as weld pool width and depth \[5\], one can
obtain sufficiently accurate results that eliminate the above-cited
limitations \[see Appendix 4 for example\]. However, the challenge would
be to describe the effects of shielding gases in the FCAW-G process and
that of metal powder additions to both FCAW-G and FCAW-S process.

In this project, we propose to extend the above work and develop a
generalized methodology to relate the welding process, consumable
parameters, and joint design to weld pool geometry and thermal cycles.
This research will be developed in such a way that it can be integrated
with the previous module for operational characteristics. Thermal
experienced by weld metal will be measured experimentally to evaluate
the computer model. This effort will be applicable for FCAW-G and FCAW-S
welding processes. However, the methodology will be designed for simple
extension to other shielded metal arc welding (SMAW) and submerged arc
welding (SAW) processes.

***Description of Microstructure Development***

Similar to weld thermal cycle and pool shape prediction, extensive
knowledge exists on relating weld thermal history to microstructure
development in steel welds \[14, 17, 25, 26\]. Models have been
developed that are essentially based on relating thermal history to weld
metal hardenability. Bhadeshia et al. used quasi-chemical models relate
the driving force for formation of ferrite from austenite to the
hardenability of steel \[14\]. These driving force values were used to
calculate paraequilibrium conditions between austenite and ferrite.
Diffusivity data were used to calculate growth rates of ferrite in
austenite. With these calculations and the weld thermal cooling curve,
they were able to describe the microstructure development in Fe-C-Mn-Si
low-alloy steel welds \[14\]. In other methods, the cooling time between
800 to 500 °C and carbon equivalence was used to estimate the volume
fractions of ferrite, bainite and martensite \[26\]. However, these
models are not suitable for a wide range of consumable compositions and
thermal histories. For example, if we apply these models to some of the
FCAW-S weld metal compositions, they do not predict the formation of
residual delta ferrite \[see Fig. 3\]. This is because these models do
not consider the solidification to delta ferrite and subsequent
transformation to austenite. The challenges to modify and expand
existing models would be describe the following phenomena

(1) The change from oxide formation to nitride formation in the liquid
    steel;

(2) The effects of varying electrode compositions on the evolution of
    microstructure;

(3) The change of solidification mode from delta ferrite to austenite;

(4) The change in rate of austenite nucleation on the delta
    ferrite/austenite interface and its effect on the austenite grain
    size;

(5) The change in growth conditions at low temperatures due to residual
    delta ferrite.

![](media/image4.png){width="3.00625in"
height="2.3159722222222223in"}(*a*) ![](media/image5.png){width="3.00625in"
height="2.292361111111111in"}(*b*)

Figure 3. (*a*) Optical micrograph of Fe - 0.2C - 0.6 Mn - 1.8 Al (wt.%)
low-alloy steel weld metal microstructure produced by FCAW-S process.
The skeletal ferrite microstructure was due to incomplete austenite
formation from δ ferrite. (*b*) For similar welding process the
reduction of aluminum concentration leads to complete austenite
formation and typical low-alloy steel weld metal microstructure.

To address these concerns, we propose to use fundamental thermodynamic
and kinetic theories to describe microstructure development as a
function of welding consumable parameters and thermal cycle. The
resultant model will describe the formation of inclusions,
solidification to δ ferrite or austenite, nucleation and growth of
austenite in the solid state, and finally decomposition of austenite to
ferrite and martensite. This model will use diffusion controlled growth
calculations \[see Appendix 4 for examples\] with local equilibrium
conditions for solidification, δ ferrite formation and austenite
formation \[27, 28\]. For low temperature solid-state transformation of
austenite, the concepts developed by Bhadeshia et al. \[14\] will be
utilized.

This model will utilize the thermal history data predicted by the
previous module and will estimate the volume fractions of
microstructural phases. This model will be developed in a modular
fashion in order to be able to couple it with the modules for
operational characteristics and thermal cycle. As mentioned earlier, the
model will be applied to low alloy steels and FCAW-G and FCAW-G process
conditions. Model development will involve significant experimental
characterization using optical microscopy, scanning electron microscopy,
and transmission electron microscopy.

## Development of Microstructure-Property Correlation 

A quantitative description of microstructure-property correlations is
one of the crucial links to the design and optimization tool. Past work
on relating microstructure to properties can be classified into three
categories. The first is based on developing analytical equations
describing strength parameters and using work hardening and dislocation
pileup theory \[29\]. The second is based on developing semi-empirical
relationships between microstructure and flow properties \[16\]. The
third approach is based on developing artificial neural networks to
describe complex relationships between microstructure and all properties
such as yield, tensile, and toughness \[30\]. The first two methods are
based, to a large extent, on fundamental relations. However, the
application of these methods to the complex, multiphase microstructure
of low-alloy steel weld metal is complicated and necessitates further
detailed research. Recent Basic Energy Science - Partnership for New
Generation Vehicles welding science research has shown that it is indeed
possible to quantitatively relate the local microstructural changes to
strength properties of the weldment \[7, 31\]. However, the above
research is in its infancy and further research is necessary before it
can be used as an optimization tool. Therefore, in this research
project, we propose to develop semi-empirical models, such as artificial
neural networks, to relate microstructure and properties. The challenge
would be to relate the effects of microstructure morphology on
properties. For example, the model would need to distinguish between the
effects of acicular ferrite and bainite on the properties
quantitatively, although both types of ferrite form by similar
transformation mechanism \[32\].

Based on the experimental information to be generated at Lincoln
Electric, published literature \[33\], and the above-mentioned research,
a generalized quantitative methodology will be developed to relate the
microstructure to properties such as strength, ductility and toughness.
This methodology can be extended in the future to consider the effect of
microstructure on other properties such as creep properties.

## Development of an Integrated Computer Aided Design and Optimization Tool

All the above four modules will be integrated into one single
computerized optimization tool by which one can relate the desired
behavior to welding consumable and process parameters. This optimization
tool can be used to facilitate the design of new welding consumables and
optimize existing welding consumables for specific applications.
Moreover, the approach will be general enough that this optimization
tool may be applied to new materials development. Several optimization
schemes will be evaluated, including a new nonlinear optimization
algorithm, developed at ORNL, which offers potential advantages over
traditional methods for solving large-scale nonlinear problem \[34\].

The significance of this research can be illustrated with an example. In
FCAW-S arc-welding consumables, a high concentration of (1.7 wt.%)
aluminum is utilized to improve operational characteristics such as arc
stability and to avoid porosity. However, a large concentration of
aluminum is known to induce residual ferrite, which deteriorates the
weldment properties such as ductility and toughness. The optimization
tool that is to be developed in this research could be used to evaluate
the effect of compositional changes (such as aluminum and carbon
concentrations) on improving weldment properties while maintaining the
same control on arc stability and porosity.

# Work Plan and Division of Responsibilities

## Work Plan

The project duration will be 36 months, with an anticipated start in
February 1999. The subtasks to achieve the overall goal are given below.
To achieve the final goal, many tasks will be performed simultaneously
as shown in Table 1. This work plan necessitates extensive collaborative
effort between ORNL and Lincoln Electric Company for successful
completion of the project. The research tasks are divided into
categories so that strength of each participant can be used efficiently
to achieve the project goal.

Table 1. Overview of the work plan.

  ------------------------------------------ ------ -- -- -- ------ -- -- -- ------ -- -- --
  **Description**                            Year 1          Year 2          Year 3       

  Model development for operational                                                       
  characteristics                                                                         

  Evaluation of operational characteristics                                               
  model                                                                                   

  Production of experimental welds                                                        

  Measurement of weld pool geometry &                                                     
  thermal history                                                                         

  Coupled semi-empirical and analytical                                                   
  model for weld pool geometry and thermal                                                
  cycle                                                                                   

  Evaluation of weld pool geometry & thermal                                              
  cycle model                                                                             

  Macro and micro-structure characterization                                              

  Microstructure model development                                                        

  Evaluation of microstructure model                                                      

  Semi-empirical model for microstructure -                                               
  property correlation                                                                    

  Evaluation of microstructure property                                                   
  correlation                                                                             

  Integrated Model                                                                        

  Evaluation of integrated model                                                          
  ------------------------------------------ ------ -- -- -- ------ -- -- -- ------ -- -- --

## Year 1

Critical operational parameters will be identified and experimental
measurement will be performed in FCAW-G and FCAW-S welding processes. In
addition, techniques like through the arc-sensing methods will be used.
The parameters to be considered are arc stability criteria, deposition
rate ranges, spatter characteristics, and fume generation. These
parameters will be measured as a function of welding process and
consumable parameters at Lincoln Electric. The new and already available
data in Lincoln Electric Company will be compiled and analyzed. These
data will be provided to ORNL for the start up of neural network model
development. [In this research, the consumable composition will be
limited to Fe-C-Mn-Al-Ti-O-N low alloy steel system and FCAW-S and
FCAW-G processes.]{.underline}

By the end of this year, the model for operational characteristics will
be available as a computer tool. Semi-empirical models for fume
generation will be investigated at ORNL with thermodynamic information.
In addition, models for microstructure and property development will be
started. Available thermodynamic-kinetic models will be identified and
modified to describe the microstructure development, starting form
inclusion formation, solidification, and solid state transformation at
ORNL. In this year, inclusion formation and solidification will be
considered.

Experimental welds will be made in Lincoln Electric Company with new
consumable compositions based on prior experience. Some of the
macrostructure and properties will be characterized at Lincoln Electric
Company. Extensive microstructural characterization will be started at
ORNL. The weld pool shapes for various conditions will be measured using
optical microscopy. The inclusion characteristics (inclusion size,
number density, and composition), prior austenite grain size, presence
of residual delta ferrite, volume fraction of microstructure (fraction
of martensite, acicular ferrite, bainite, Widmanstätten ferrite,
allotriomorphic ferrite, and pearlite) and size and morphology of
ferrite phases will be characterized. In addition, thermal cycles in the
weld metal region will be measured at Lincoln Electric and ORNL.

## Year 2

The model developed for operation characteristics will be evaluated and
possible modifications will be made. New experimental welds will be made
based on the results of first year\'s research. Characterization of
these welds will continue on in the second year. The properties such as
tensile strength and toughness of various welds will be measured at
Lincoln Electric. These characterizations will be used for evaluation of
models.

Thermal cycles experienced by weld metal as a function process and
consumable parameters will be measured. Coupled analytical and neural
network development for weld pool geometry and thermal cycles will be
initiated and. The weld pool, thermal cycle, and microstructure models
are expected to be completed by the end of this year. For this task, the
data generated during characterization in the last year and measured
thermal cycles in this year will be used.

The microstructure model development will be continued and solid state
transformations will be considered this year. This module will be
designed to use predicted thermal cycles with analytical and neural
network models.

In this year, development of a model to describe the microstructure and
property correlations will be initiated. For this task artificial neural
network model or semi-empirical model or combination of the both will be
considered. These models will be developed based on the experimental
data in the last two years.

## Year 3

The weld pool, thermal cycle, and microstructure model will be evaluated
based on existing data available at ORNL and Lincoln Electric Company,
published literature, and newly generated data in the last two years.
The microstructure-property correlation will be completed and the
evaluation of the same will be started.

After the evaluation, all the models will be integrated for use as a
design and optimization tool. This will involve computational issues for
efficient coupling of various models. Computational tools such as
problem-solving environment (PSE) will be used \[18\]. In addition, the
optimization tools developed at ORNL will be incorporated \[34\]. This
tool will be available by the second half of third year. This tool will
be evaluated at ORNL and Lincoln Electric Company for totally
independent conditions. This may involve production of new experimental
welds designed by this tool for a specific application.

## Division of responsibilities

Lincoln Electric will develop the database on operational
characteristics, conducting all measurements and analyses required.
During the course of this research many experimental welds will be
produced and their properties will be measured at Lincoln Electric
Company. This involves extensive planning of consumable composition,
flux composition, shielding gas ratio, filler wire production, welding
process parameters, machining, property evaluation. This is a
significant commitment from Lincoln Electric Company.

The experimental welds will be characterized with optical microscopy and
transmission electron microscopy at ORNL. This involves extensive and
time-intensive data generation and analysis. In addition, ORNL
researchers will identify already existing models and also develop new
models to describe the operational characteristics, weld thermal cycle,
weld pool geometry, microstructure and correlation between
microstructure and properties. This involves use of expertise in the
development of artificial neural net models, thermodynamic models,
kinetic models and also computational programs.

# Relevance to DOE Programs

The proposed research project will allow for a method by which various
research findings from other basic energy sciences programs on welding
science \[3,17\] can be evaluated in an industrial setting. The above
research will also utilize the on-going BES-welding science research
program on steel weld microstructure development in the development of
models for microstructure. Therefore, this industry partner
collaboration provides a unique coupling of both fundamental and applied
research efforts for the successful completion of this project. This
integrated design and optimization tool will also provide for
development of new research programs related to other advanced alloys
such as nickel base superalloys. For example, there is a need to develop
welding consumables for repair welding of nickel-based superalloy blade
materials for land based turbines \[35\] and is of interest to advanced
turbine systems (ATS) program of Office of Industrial Technologies, US
Department of Energy. Since the optimization tool to be developed in
this research project is general it can be extended to these issues in
the future.

# Anticipated Commercial Potential

The commercial potential of this research is significant. Many new
materials that are developed often encounter complications during
various applications because they are not designed with weldability in
mind, even though good welding performance is critical for their
application. The proposed tool will provide an efficient means for
developing consumables with good weldability. In addition, besides
improving weldability, the proposed tool will enable the user to improve
the weldment properties as well. Specifically, this research will have
significant impact on the shipbuilding, construction, heavy machine,
power generation, and oil and gas industries. Previous collaborative
industrial research efforts have indicated the commercial potential of
the proposed research methodology \[see Appendix 4\].

**References**

1\. T. DebRoy and S. A. David: *Rev. of Mod. Physics*., 1995, 67,85-112.

2.  T. Zacharia and S. A. David: Mathematical Modeling of Weld
    Phenomena, Eds. H. Cerjak and K. E. Easterling, The Institute of
    Materials, London, 1993, 1-23.

3.  S. S. Babu, S. A. David, J. M. Vitek, K. Mundra, and T. DebRoy:
    *Mater. Sci. Technol*., 1995, 11, 186-199.

4.  M. Quintana, J. McLane, S. S. Babu, and S. A. David: to be presented
    at AWS Annual Convention, 1999 (This work is based on an MPLUS
    collaborative research effort between ORNL and Lincoln Electric).

5.  S. S. Babu, J. M. Vitek, and S. A. David: Multi-laboratory
    Director's Research Development project on laser assisted arc
    welding of aluminum alloys, Oak Ridge National Laboratory,
    1997-1998.

6.  S. S. Babu, G. M. Goodwin, R, J, Rohde, and B. Sielen: *Welding
    Journal*, 1998, 77, 249s-253s.

7.  S. S. Babu, S. A. David and G. R. Edwards, High-strength steel
    welding research, Report on research sponsored by Office of Naval
    Research, submitted to Office of Naval Research, 800 N. Quincy
    Street, Arlington, VA 22217-5000, May 1997.

8.  ASM Metals Handbook, Vol. 6, ASM International, 1993.

9.  T. Hong, T. DebRoy, S. S. Babu and S. A. David, unpublished
    research, The Pennsylvania State University, PA 16802.

10. T. Zacharia, S. A. David, J. M. Vitek, and T. DebRoy, *Welding
    Journal*, 1989, 68, 499s.

11. D. L. Olson, S. Liu, and G. R. Edwards, Mathematical Modeling of
    Weld Phenomena, Eds. H. Cerjak and K. E. Easterling, The Institute
    of Materials, London, 89-108.

12. S. S. Babu, S. A. David and T. DebRoy, *Sci. Tech. Weld. Join.,*
    1996, 1, 17-27.

13. S. A. David and J. M. Vitek, Mathematical Modeling of Weld
    Phenomena, Eds. H. Cerjak and K. E. Easterling, The Institute of
    Materials, London, 41-59.

14. H. K. D H. Bhadeshia, L.--E. Svensson, and B. Gretoft, *Acta
    Metallurgica*, 1985, 33, 1271-1283.

15. Internet location on modeling microstructure development:
    [http://engm01.ms.ornl.gov](http://engm01.ms.ornl.gov/)

16. Y. Tomota et al. *ISIJ International*, 1992, 32, 343-349.

17. M. L. Santella, S. S. Babu, B. W. Riemer, and Z. Feng: to be
    published in Proc. of Intl. Conference on Trends in Welding
    Research, Pine Mountain, Georgia, 1-5 June 1998.

18. Oak Ridge National Laboratory Review, \"High Performance
    Computing,\" Vol. 30, Nos., 3 and 4, 1997.

19. G. E. Cook *et al.,* in Proc. of Intl. Conference on Trends in
    Welding Research, Gatlingburg, Tennessee, 5-8 June, 1995.

20. W. Wang, S. Liu, and J. E. Jones, *Welding Journal*, 1995, 74,
    S369-377.

21. S. W. Simpson, P. Y. Zhu, *J. of Applied Physics*, 1995, 28,
    1594-1600.

22. H. R. Castner and C. L. Null, *Welding Journal*, 1998, 77,
    223s-231s.

23. P. Hewett, *American Industrial Hygiene Association Journal*, 1995,
    56, 128-135.

24. P. Hewitt, and A. A. Hirst, *Anals of Occupational Hygiene*, 1991,
    35, 223-232.

25. H. K. D. H. Bhadeshia, and L.--E.Svensson, Mathematical Modeling of
    Weld Phenomena, Eds. H. Cerjak and K. E. Easterling, The Institute
    of Materials, London, 1993, 109-178.

26. K. E. Easterling, Mathematical Modeling of Weld Phenomena, Eds. H.
    Cerjak and K. E. Easterling, The Institute of Materials, London,
    1993, 183-200.

27. Zi-Kui Liu, *et. al*., *Metallurgical Transactions A,* 1991, 22A,
    1745-1752.

28. J. M. Vitek, S. A. Vitek, and S. A. David: *Metallurgical and
    Materials Transactions A*, 1995, 26A, 1995-2007.

29. Z. Jiang, J. Liu, and J. Lian, *Acta Metall. Mater.*1992, 40,
    1587-1597.

30. H. K. D. H. Bhadeshia, D. J. C. Mackay and L.--E. Svensson:
    *Materials Science and Technology*, 1995, 11, 1046-1051.

31. J. W. Cohron, et al., Unpublished research , BES-PNGV research, Oak
    Ridge National Laboratory, Oak Ridge, TN 37831-6096.

32. S. S. Babu and H. K. D. H. Bhadeshia, *Materials Science and
    Technology*, 1990, 6, 1005-1020.

33. G. M. Evans and N. Bailey, Metallurgy of Basic Weld Metals
    (Cambridge, England: Abington Publishing, 1997), 391-420.

34. J. Barhen, V. Protopopescu and D. Reiseter, *Science*, 1997, 276,
    1094-1097.

35. EPRI Report on weld repair for nickel based superalloy blading,
    TR-108272, April 1998.

# Appendices

## 1. Key Personnel and Facilities

Personnel at ORNL have exceptional capabilities in modeling
microstructure development in welds. These models have been applied to
stainless steel, low alloy steel, and nickel base superalloy welds. Both
principal investigators at ORNL are internationally known in this
subject and have been recognized by professional societies with various
awards. In addition, these researchers made a breakthrough by designing
internet calculations based on models developed at ORNL (see
[http://engm01.ms.ornl.gov)](). This allowed industrial and academic
users to use the model as well as evaluate them for various purposes.
ORNL also has excellent characterization tools that will be used in this
project. ORNL has extensive experience in the neural network development
for welding applications. In addition, expertise in optimization
algorithms is available at ORNL.

ORNL is a multi-program science and technology laboratory managed for
the U.S. Department of Energy by Lockheed Martin Energy Research
Corporation. Scientists and engineers at ORNL conduct basic and applied
research and development to create scientific knowledge and
technological solutions that strengthen the nation\'s leadership in key
areas of science; increase the availability of clean, abundant energy;
restore and protect the environment; and contribute to national
security. The Laboratory shares its unique facilities and capabilities
with partners from industry, universities, and other research
institutions. Further information on ORNL can be obtained from following
Internet site: http://www.ornl.gov.

Personnel at Lincoln Electric Company have state-of-the art welding
consumable development facilities. Lincoln Electric is a world leader in
welding consumables, welding power sources and cutting products, and a
premier manufacturer of electric motors. The personnel at Lincoln
Electric Company have industry proven track record of new developments
in welding consumables and also welding power sources. The Company is
known around the globe for creating the highest quality products and
services. Lincoln Company considers that several factor set it apart
from other manufacturers and that these factors contribute to its status
as a \"leader and innovator\" in the welding industry. They are
dedicated and talented workforce which is highly trained and motivated,
an ongoing series of technical achievements that continues to raise
industry standard for performance, worldwide manufacturing to serve the
expanding customer base cost effectively, commitment to quality, strong
distribution and customer service, and its unique incentive performance
system. The Company also adds value by providing customers with \"total
solutions\" which \"improve productivity, enhance performance, heighten
quality and lower costs.\" Further information on Lincoln Electric
Company can be obtained from the following Internet site:
http://www.lincolnelectric.com

Therefore, the proposed research proposal will utilize the best
capabilities from both industry and national laboratory.

## 2. Selected Relevant Publications

Babu, S. S., David, S. A., Vitek, J. M., Mundra, K., and DebRoy, T.,
Development of macro -- and microstructures of C--Mn low alloy steel
welds -- Inclusion Formation, *Materials Science and Technology*, 11,
1995, pp. 186-199.

Babu, S. S., David, S. A., Vitek, J. M., and Miller, M. K, Phase
stability and atom probe field ion microscopy of Type 308 CRE stainless
steel weld metal, *Metall. & Mater. Trans. A*., 27A, 1996, 763-774.

Babu, S. S., David, S. A., and Miller, M. K., Microstructural
development in PWA1480 electron beam welds - An atom probe field ion
microscopy study, *Applied Surface Science*, 94/95, 1996, 280-287.

Babu, S. S., and David, S. A., Coarsening of oxide inclusions in low
alloy steel welds, *Science and Technology of Welding and Joining*,
1996, 1, 17-27.

Mundra, K., DebRoy, T., Babu, S. S., and David, S. A.[^2] Weld metal
microstructure calculations from fundamentals of transport phenomena in
the arc welding of low alloy steels, *Welding Journal*, 1997, 76,
163s-171s.

Babu, S. S., Vitek, J. M., Iskander, Y. S., and David, S. A., A new
model for prediction of ferrite number of stainless steel welds,
*Science and Technology of Welding and Joining,* 1997*,* 2, 279-285.

Babu, S. S., Goodwin, G. M., Rohde, R. J., and Sielen, B., Effect of
residual boron on the microstructure of low-carbon steel resistance-seam
welds, *Welding Journal*, 1998, 77, 249s-253s.

Vitek, J.M., Vitek, S. A., David, S. A., Numerical modeling of
diffusion-controlled phase transformations in ternary-systems and
application to the ferrite austenite transformation in the Fe-Cr-Ni
system, *Metallurgical and Materials Transactions A*, 1995, 26A,
1995-2007.

Vitek, J. M., Iskander, Y. S., Oblow, E. M., Babu, S.S., and David, S.
A., Neural network modeling of pulsed-laser weld pool shapes in aluminum
alloy welds, Proc. of Intl. Conference on Trends in Welding Research,
June 1-5, 1998, Pine Mountain, GA, in press.

Vitek, J. M., Iskander, Y. S., Oblow, E. M., Babu, S.S., and David, S.
A., Neural network model for predicting ferrite number in stainless
steel welds, Proc. of Intl. Conference on Trends in Welding Research,
June 1-5, 1998, Pine Mountain, GA, in press.

## 3. Curriculum Vitae of Key Team Members

(see next page)

### S. S. Babu

[EDUCATION]{.underline}

1988 -- 1991 Ph.D. from University of Cambridge, U. K.

1986 -- 1988 Master of Technology in Industrial Metallurgy, specializing
in Welding Technology from Indian Institute of Technology, Madras, INDIA

1982 -- 1986 Bachelor of Engineering in Metallurgy from P. S. G. College
of Technology, Bharathiar University, Coimbatore, INDIA

[WORK EXPERIENCE]{.underline}

1997- Development Staff Member, Oak Ridge National Laboratory, Lockheed
Martin Energy Research Corporation, Oak Ridge, TN 37831-6096. The
research focuses on basic and applied welding metallurgy, phase
transformation issues in steel, aluminum alloy, and nickel-base
superalloy welds.

1996 --1997 Research Assistant Professor, a joint appointment by Oak
Ridge National Laboratory and The University of Tennessee, Knoxville, TN
37996.

1993--1996 Postdoctoral Scholar Oak Ridge National Laboratory, Oak
Ridge, TN 37831 / The Pennsylvania State University, University Park
joint appointment.

1992--1993 Research associate at the Institute for Materials Research,
Tohoku University, JAPAN.

[ACHIEVEMENTS, HONORS, and AWARDS]{.underline}

1998 Professor Koichi Masubuchi Award from American Welding Society for
significant contributions in the advancement of science and technology
of materials joining through research and development activities

1998 Co-recipient of Warren F. Savage Memorial Award for the paper which
was judged the greatest contribution to the understanding of welding
metallurgy published in the welding journal during the year 1997

1997 ASM-IIM India Visiting Lecturer Award

1991 Pfeil Medal for the research paper of particular merit in the field
of physical metallurgy for the previous two years, published by the
Institute of Metals, London, UK.

1988 Cambridge Commonwealth Trust--India Scholarship for doctoral study
and Overseas Research Student award (ORS) for the doctoral study in the
United Kingdom by the Council of Vice Chancellors and Principals of the
Universities in the UK.

1987 Sudarsan Bhat Memorial award for the best academic record during
the Master of Technology degree at IIT Madras, INDIA.

1987 Special scholarship by KCP Industries for the best academic
achievement

1986 Government of India scholarship for the postgraduate study through
a country wide competitive examination.

1986 Best project award (1986--87) during Bachelor of Engineering
degree, sanctioned by the Director of Technical Education, Madras,
INDIA.

1986 Academic proficiency award during the Bachelor of Engineering
degree

[OTHER ACADEMIC ACTIVITIES]{.underline}

Board of review in Metallurgical and Materials Transactions, A from
1996. Serving as reviewer of technical articles in reputed international
journals such as *Metallurgical and Materials Transactions*, *Welding
Journal*, *Scripta Metallurgica et Materialia* and *Science and
Technology of Welding and Joining.* Served as chairman of Weldability II
and Properties of Weldments II sessions in the 4th International
Conference on Trends in Welding Research, 5-8 June 1995.

[RESEARCH INTERESTS]{.underline}

Phase transformations during welding of materials especially in steels,
aluminum alloys and Ni-base super alloys. Microstructure development
with consideration of externally applied and internally generated
stresses during welding and processing of metals. Fundamental issues in
non--equilibrium phase transformations that occur in welding and use of
tools like atom probe field ion microscope, and electron microscopy to
investigate these phenomena. Phase transformations in nanostructured
materials.

Process modeling of structural materials based on fundamental
thermodynamics and kinetic theories. Application of the computer aided
models to solve the industrial related problems.

Welding process and weldability issues in structural materials

[COMPUTATIONAL SKILLS]{.underline}

Experience in developing WWW based scientific/engineering applications
and WWW publishing of research results. Experience in C and FORTRAN
programming for modeling the phase transformations in welds and analysis
of atom probe data.

[Number of publications]{.underline}: 49

### J. M. Vitek

[EDUCATION]{.underline}

1969-1973 PhD in Materials Science from Massachusetts Institute of
Technology

1968-1969 MS in Materials Science from California Institute of
Technology

1964-1968 BS in Materials Science from Massachusetts Institute of
Technology

[WORK EXPERIENCE]{.underline}

1980 Research Staff Member, Oak Ridge National Laboratory,
Lockheed-Martin Energy Research Corporation, Oak Ridge, TN 37831-6376

1992 Guest Scientist at Nippon Research Laboratories, Nippon Steel
Corporation, Futtsu, Japan

1984-1984 Guest Scientist at Max Planck Institut für Metallforschung,
Stuttgart, Germany

1976-1980 Research Scientist at Metals Research Laboratories, Olin
Corporation, New Haven, CT

1973-1976 Post-doctoral researcher at Max Planck Institut für
Metallforschung, Stuttgart, Germany

[ACHIEVEMENTS, HONORS, and AWARDS]{.underline}

1998 Elected Fellow of the American WeldingSociety

1997 Elegant Work Prize, The Institute of Materials

1994 Co-author Citation for the Champion H. Mathewson Award, TMS

1991 Selected to participate in the Japan Key Technology Program as a
visiting scientist at Nippon Steel Corporation

1990 Jacquet-Lucas Grand Prize, ASM-International and International
Metallographic Society

1988 Martin Marietta Publications Award

1988 Jacquet-Lucas Grand Prize, ASM-International and International
Metallographic Society

1987 Jacquet-Lucas Grand Prize, ASM-International and International
Metallographic Society

1987 Outstanding Paper Award, Acta Metallurgica

[OTHER PROFESSIONAL ACTIVITIES]{.underline}

1998 Co-chairman, 5^th^ International Conference on Trends in Welding
Research, Pine Mountain, Georgia

1997 - Alloy Phase Diagram Committee, ASM-International

1997 - Board of Review, Metallurgical Transactions A

1996 - Editorial Board, Science and Technology of Welding and Joining

1993 Co-chairman, Modeling for Welding Science Workshop, Cocoa Beach,
Florida

1992-1993 Chairman, Board of Review, Metallurgical Transactions A

1992 Co-chairman, 3^rd^ International Conference on Trends in Welding
Research, Gatlinburg, Tennessee

1989-1993 Publications Council, ASM-International

1989 Co-chairman, 2^nd^ International Conference on Trends in Welding
Research, Gatlinburg, Tennessee

1988-1994 Board of Review, Metallurgical Transactions A

[COMPUTATIONAL SKILLS]{.underline}

Experience in developing artificial neural networks for applications in
welding science, including neural networks on weld pool shape
development and ferrite prediction in stainless steels. Experience in
developing a finite element model from diffusion controlled
transformation in multi-component alloy systems.

[RESEARCH INTERESTS]{.underline}

Phase transformation behavior in metal alloys, particularly in steels,
aluminum alloys, and nickel-base superalloys.

Welding of single crystals, both stainless steels and nickel-base
superalloys, and the effect of welding conditions on microstructural
development in single crystals.

Microstructure analysis, and the relationship between microstructure and
properties.

Modeling of phase stability in multicomponent systems by means of
modeling thermodynamic properties and behavior.

Modeling of diffusion controlled phase transformation behavior.

Development of neural network models for applications in welding
science.

Effects of rapid solidification on microstructural development,
including, most recently, the effect of high energy density welding
processes on solidification and phase transformation behavior.

[Number of publications]{.underline}: 145

[Number of patents]{.underline}: 9

### M. Quintana

PROFESSIONAL EXPERIENCE

***SENIOR PROJECT ENGINEER,*** 1995 to present

***Consumable Research & Development***

[THE LINCOLN ELECTRIC COMPANY, CLEVELAND, OHIO]{.underline}

-   Developed relational database for integration of weldment properties
    with welding process variables

-   Investigated artificial neural networks for correlation of weldment
    properties with welding process and consumable variables

-   Introduced statistics based "design of experiments" techniques for
    mixture designs

-   Characterized microstructure/properties relationships with regard to
    chemical composition and welding process effects

-   Developed cored electrodes for welding CMn steels

-   Performed failure investigations for customers with weld cracking
    problems

-   Continued efforts to optimize diffusible hydrogen test procedures
    and develop new moisture test procedures

***ENGINEERING SPECIALIST,*** 1989 to 1995

***Welding Process Development Laboratory***

[GENERAL DYNAMICS, ELECTRIC BOAT DIVISION, GROTON, CT]{.underline}

***SENIOR ENGINEER*** 1981 to 1988\
***Welding Process Development Laboratory***

# GENERAL DYNAMICS, ELECTRIC BOAT DIVISION, GROTON, CT

-   Formulated technical and business goals, budgets and research plans
    for Industrial Research and Development/Manufacturing & Production
    Engineering Technology projects

-   Coordinated efforts of several departments for effective project
    execution

-   Projects focus on metallurgical aspects of welding and involve the
    study of hydrogen damage/cracking in high strength steel weldments
    and the influence of weld process variables on weld properties and
    performance

-   Developed test methods for diffusible hydrogen measurement
    implemented throughout the welding industry

-   Developed and qualified procedures for HY-80/100 steels and
    bimetallic welding

-   Performed extensive evaluation of new products and suppliers prior
    to purchase

-   Evaluated military specifications for impact on shipyard
    construction and cost

***ENGINEER, Nuclear Construction*** 1978 to 1981

[GENERAL DYNAMICS, ELECTRIC BOAT DIVISION, GROTON, CT]{.underline}

-   Provided technical review, direction and assistance to shipyard
    trades to solve production problems associated with shielded
    structures

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-   Reviewed fabrication and installation procedures for shielding
    installation

-   Conducted radiation shield surveys in support of ship's testing and
    construction schedules, including training and supervision of a data
    reduction crew and evaluation of radiation data

***ENGINEERING AIDE*** 1973 to 1978

[BUREAU OF ELECTRICITY, ALAMEDA, CA]{.underline}

-   Prepared working drawings for overhead and underground power
    distribution system

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```
-   Maintained electrical distribution maps and records

-   Processed documents and layouts for rights of way

-   Supervised entry level employees

## EDUCATION

M.S. Metallurgy, University of Connecticut, Storrs 1980 to 1983

B.S. Materials Science, University of California, Berkeley 1972 to 1978

## PROFESSIONAL ACTIVITIES

Chair, 1996 to present\
Society of Women Engineers Scholarship Committee

Chair, American Welding Society A5W Subcommittee 1993 to present

Moisture and Weld Metal Diffusible Hydrogen

Chair, American Welding Society A5A Task Group 1989 to 1992\
Moisture Test Development

American Welding Society A5A Committee, Filler Metals 1988 to present

American Welding Society A5A Subcommittee, 1987 to present

Carbon and Low Alloy Steel Electrodes for Shielded Metal Arc

and Oxy-Fuel Gas Welding

President, Society of Women Engineers, Connecticut Section 1984 to 1988

American Welding Society A5A Task Group, 1984 to 1985

Diffusible Hydrogen Testing of Ferritic Weld Metal

American Society for Testing and Materials, F7.04 Subcommittee on 1985
to present

Hydrogen Embrittlement

**PUBLICATIONS**

Quintana, Cote and Kvidahl, "Hydrogen Measurement Techniques", \[Conf.
Proc.\] [International Workshop on Hydrogen Management for Welding
Applications]{.underline}, CANMET, October 1998, Ottawa, Canada

Quintana and Johnson, "The Effects of Intermixed Weld Metal on
Mechanical Properties-Part 3", \[Conf. Proc.\] [International Conference
on Welded Constructions in Seismic Areas]{.underline}, AWS/JWS, October
1998, Maui, HI

Johnson and Quintana, "The Effects of Intermixed Weld Metal on
Mechanical Properties", \[Conf. Proc.\] [Third US-Japan Workshop on
Steel Fracture Issues]{.underline}, NSF, April 1998, Tokyo, Japan

Quintana and Johnson, "The Effects of Intermixed Weld Metal on
Mechanical Properties-Part 2", 79^th^ Annual American Welding Society
Convention, April 1998, Detroit, MI (to be submitted to the [Welding
Journal]{.underline})

Quintana and Johnson, "The Effects of Intermixed Weld Metal on
Mechanical Properties-Part 1", 78^th^ Annual American Welding Society
Convention, April 1997, Los Angeles, CA (to be published in the [Welding
Journal]{.underline})

Quintana, "*AWS Task Group Findings on Moisture Testing of Welding
Consumables: Progress Report*", [Welding Journal]{.underline}, Vol. 72,
No. 8, pp. 409s-415s, August 1993

Quintana, "*Development of Electrode Coating Moisture and Weld Metal
Diffusible Hydrogen Analytical Practices*", [Ferrous Alloy
Weldments]{.underline}, ed. D. L. Olson and T. A. North, Trans Tech
Publications Ltd., Zurich, Switzerland, March 1992

Quintana and Fichtelberg, "*Influence of Process and Material Variables
on Hydrogen Related Effects in Submerged Arc Welding of Alloy Steel*",
\[Conf. Proc.\] [2nd Int'l Conference on Trends in Welding
Research]{.underline}, Gatlinburg, TN, May 17, 1989, ASM International,
1990

Quintana and Dannecker, "*Diffusible Hydrogen Testing by Gas
Chromatography*", [Hydrogen Embrittlement: Prevention and
Control]{.underline}, ASTM Special Technical Publication 962, 1988

Quintana, "*A Critical Evaluation of the Glycerin Test*", [Welding
Journal]{.underline}, Vol. 63, No. 5, pp. 141s-149s, May 1984

## 4. Previous Research Demonstration

A demonstration of previous research related to this proposal can be
accessed directly over the Internet (http://engm01.ms.ornl.gov). These
examples show the capability of the principal investigators to complete
the proposed research task successfully.

[Weld pool prediction]{.underline}: An internet based computer tool has
been developed to predict the weld pool shape of laser assisted plasma
arc welds made on 6111 type and 5754 type aluminum alloys used for
automotive industries.

![](media/image6.wmf){width="2.9972222222222222in"
height="2.220138888888889in"} −\>
![](media/image7.wmf){width="3.0034722222222223in"
height="2.220138888888889in"}

[Ferrite Number prediction]{.underline}: A semi-empirical model based on
thermodynamic information and artificial neural network has been
developed and is being currently used extensively for evaluating ferrite
content in stainless steel welds.

![](media/image8.wmf){width="3.001388888888889in"
height="2.6118055555555557in"}−\>
![](media/image9.wmf){width="3.0027777777777778in"
height="2.6083333333333334in"}

[Time-Temperature-Transformation diagram]{.underline}: Calculation of
TTT diagram and CCT diagram as a function of low-alloy steel composition
and cooling rate has been developed as a computer tool.

![](media/image10.wmf){width="3.002083333333333in"
height="2.4145833333333333in"}−\>
![](media/image11.wmf){width="3.001388888888889in"
height="2.4229166666666666in"}

[Growth and dissolution of ferrite in stainless steel
welds]{.underline}: A detailed finite element method has been developed
to predict ferrite growth and dissolution in stainless steel welds which
combines both thermodynamic information and kinetic model. Example plot
shown below illustrates the phase-diagram, tie line, diffusion profile
of Cr and Ni, and variation of ferrite fraction at two time instances
for a given isothermal transformation temperature.

  ------------------------------------------ -- -----------------------------------------------------
  Diffusion in ferrite controls ferrite         Diffusion in austenite controls ferrite growth
  growth                                        

  ![](media/image12.wmf){width="2.94375in"      ![](media/image13.wmf){width="2.9493055555555556in"
  height="2.0541666666666667in"}                height="2.0652777777777778in"}
  ------------------------------------------ -- -----------------------------------------------------

## 5. Budget and Explanation

  -------------- -------------- -------------- -------------- --------------
                 FY 1999        FY 2000        FY 2001        FY 2002

  From DOE-LTR   \$ 100,000     \$ 200, 000    \$ 200,000     \$ 100,000

  From Funds-in  \$ 10,000      \$ 15,000      \$ 15,000      \$ 15,000

  Total          \$ 110,000     \$ 215,000     \$ 215,000     \$ 110,000
  Allocation                                                  

  ORNL Expense                                                

  Staff (S. S.   44, 662        89,648         88,868         43,452
  Babu and J. M.                                              
  Vitek)                                                      

  Post-doc       35,000         75,000         75,000         35,000

  Travel         5,000          5,000          5,000          5,000

  Materials      5,000          5,000          5,000          5,000

  Indirect Cost  20,338         40,352         41,132         21,548

  Total          \$ 110,000     \$ 215,000     \$ 215,000     \$ 110,000
  -------------- -------------- -------------- -------------- --------------

# Letter of Interest from Industrial Partner

[^1]: ^†^ See some examples of computer tools developed by the principal
    investigators in Appendix 4.

[^2]: ^†^ This paper was awarded with Warren F. Savage memorial award
    from American Welding Society.