# International Course to Support Nuclear Licensing by  User Training in the Areas of Scaling, Uncertainty, and  3D Thermal-Hydraulics/Neutron-Kinetics Coupled Codes: 3D S.UN.COP Seminars

Authors: Alessandro Petruzzi; Francesco D'Auria; Tomislav Bajs; Francesc Reventos; Yassin Hassan
Journal: Science and Technology of Nuclear Installations
 (2008)

---

## Abstract

Thermal-hydraulic system computer codes are extensively used worldwide for analysis of nuclear facilities by utilities, regulatory bodies, nuclear power plant designers, vendors, and research organizations.
The computer code user represents a source of uncertainty that can influence the results of system code calculations. This influence is commonly known as the “user effect" and stems from the limitations embedded in the codes as well as from the limited capability of the analysts to use the codes. Code user training and qualification represent an effective means for reducing the variation of results caused by the application of the codes by different users. This paper describes a systematic approach to training code users who, upon completion of the training, should be able to perform calculations making the best possible use of the capabilities of best estimate codes. In other words, the program aims at contributing towards solving the problem of user effect.
In addition, this paper presents the organization and the main features of the 3D S.UN.COP (scaling, uncertainty, and 3D coupled code calculations) seminars during which particular emphasis is given to the areas of the scaling, uncertainty, and 3D coupled code analysis.


---

## Body

## 1. Introduction

A wide range of activities has recently been
completed in the area of system thermal-hydraulics as a follow-up to
considerable research efforts. Problems have been addressed, solutions to which
have been at least partly agreed upon on international ground. These include the
need for best-estimate system codes [1, 2], the general code qualification
process [3, 4], the proposal for nodalization qualification, and attempts
aiming at qualitative and quantitative accuracy evaluations [5]. Complex
uncertainty methods have been proposed, following a pioneering study at USNRC [6].
This study attempted,
among other things, to account for user effects (see Section 2 for definition) on code results. An international
study aiming at the comparison of assumptions and results of code uncertainty methodologies
has been completed [7].More recently (during the period 1997–1999),  the IAEA (International Atomic Energy Agency) developed
a document consistent with its revised Nuclear Safety Standards Series [8] that
provides guidance on accident analysis of nuclear power plants (NPPs). The
report includes a number of practical suggestions on the manner in which to
perform accident analysis of NPPs. These cover the selection of initiating
events, acceptance criteria, computer codes, modeling assumptions, the
preparation of input, qualification of users, presentation of results, and
quality assurance. The suggestions are both conceptual as well as formal and
are based on present practice worldwide for performing
accident analysis. The report covers all major steps in performing analyses and
is intended primarily for code users.Within the framework of the “Nuclear Safety Standard
Series” the important role of the user’s effects on the analysis has been
addressed. The need for user qualification and training has been clearly
recognized and the systematic training of analysts was emphasized as being
crucial for the quality of the analysis results. Three areas of training, in
particular, have been specified in the following:(i)
practical training on the design and operation of the
plant;
(ii)
software specific training;
(iii)
application specific training.
Training on the phenomena and methodologies is typically
provided at the university level, but cannot always be considered sufficient.
Furthermore, training on the specific application of system codes is not usually
provided at this level, whereas practical training on the design and operation
of the plant is essential for the development of the plant models. Software
specific training is important for the effective use of the individual code.
Application specific training requires the involvement of a strong support
group that shares its experience with the trainees and provides careful
supervision and review. Training at all three levels ending with examination is
encouraged for a better effectiveness of the training. Such a procedure is
considered a step in the direction of establishing a standard approach that
could be applicable to an international basis.Based on the above
considerations and facts, the paper outlines the role of the code user, addresses
the problem of the user’s effect in Section2, provides a proposal for a
permanent training course for system codes in Section 3, and gives a tangible example of user-training-course
(i.e., 3D S.UN.COP), mostly focused on the
development and application of best-estimate codes emphasizing scaling,
best-estimate, uncertainty, and 3D coupled code calculations analyses, in
Section 4.


## 2. Thermal-Hydraulic Codes and Code Users

### 2.1. Role and Relevance of Code User

The best estimate thermal-hydraulic codes used in the
area of nuclear reactor safety have reached a marked level of sophistication.
Their capabilities to predict accidents and transients at existing plants have
substantially improved over the past years as a result of large research
efforts and can be considered satisfactory for practical needs provided that
they are used by competent analysts.Best estimate system
codes (RELAP, TRAC, CATHARE, or ATHLET) are currently used by
design-er/vendors of NPPs, by utilities, licensing authorities, research
organizations including universities, nuclear fuel companies, and by technical
support organizations. The objectives of using the codes may be quite
different, ranging from design or safety assessment to simply understanding the
transient behavior of a simple system. However, the ap-plication of a selected
code must be proven to be adequate to the performed analysis. Many aspects from
the design data necessary to create input to the selection of the noding solutions
and the code itself are the user’s responsibility [9–11].The role of the code user is extremely
relevant: experience with large number of International Standard Problems (ISPs)
has shown the dominant influence of the code user on the final results and the
goal of reduction of user effects has not been achieved. It has been observed
previously that(i)
the user gives a contribution to the overall uncertainty that
unavoidably characterizes system code calculation results;
(ii)
in the majority of cases, it is impossible to distinguish among
uncertainty sources like “user effect,” “nodalization inadequacy,” “physical
model deficiencies,” “uncertainty in boundary or initial conditions,” and “computer/compiler
effect;”
(iii)
“reducing the user effect” or “finding the optimum nodalization” should
not be regarded as a process that removes the need to assess the uncertainty.
Performing an adequate code analysis or
assessment involves two main aspects.(1)
Code adequacy. The adequacy demonstration process must be
undertaken by a code user when a code is used outside its assessment range,
when changes are made to the code, and when a code is used for new applications
where different phenomena are expected. The impact of these changes must be
analyzed and the analyses must be thoroughly reviewed to ensure that the code
models are still adequate to represent the phenomena that are being observed.
(2)
Quality of results. Historically the results of code predictions,
specifically when compared with experimental data gathered from applicable
scaled test facilities, have revealed inadequacies raising concerns about code
reliability and their practical usefulness. Discrepancies between measured and
calculated values were typically attributed to model deficiencies, approximation
in the numeric solutions, computer, and compiler
effects, nodalization inadequacies, imperfect knowledge of boundary and initial
conditions, unrevealed mistakes in the input deck, and to “user
effect." In several ISPs sponsored by OECD (Organisation for Economic Cooperation and
Development), several users modeled
the same experiment using the same code, and the code-calculated results varied
widely, regardless of the code used. Some of the discrepancies can be
attributed to the code user approach as well as to a general lack of
understanding of both the facility and the test.
The two items are the main aspects, both
related to the code user. The first aspect is included in the qualification framework
of the code and nodalization. The second aspect is directly related to the user
choices generally referred to as User Effect.


### 2.2. User Effect

Complex systems codes
such as RELAP5, CATHARE, TRAC, and ATHLET have many degrees of freedom that
allow misapplication (e.g., not using the countercurrent flow-limiting model at
a junction where it is required) and errors by users (e.g., inputting the
incorrect length of a system component). In addition, even two competent users
will not approach the analysis of a problem in the same way and consequently,
will likely take different paths to obtain a problem solution. The cumulative
effect of user community members to produce a range of answers using the same
code for a well-defined problem with rigorously specified boundary and initial
conditions is the user effect (see Figure1).Figure 1
User effect: different results for the cladding temperature in the ISP25 test from different users adopting the same code and BIC.The following are some of the reasons for the
user effects.(i)
Code use guidelines are
not fully detailed or comprehensive.
(ii)
Based on the current state
of the art, the actual 3D plant geometries are usually modeled using several 1D
zones; these complex 3D geometries are suitable for different modeling
alternatives; as a consequence an assigned reactor vessel part is modeled
differently by different users of the same code. Beside the major 1dimensional
code modules, a number of empirical models for system components, such as
pumps, valves, and separators, are specified by the users, sometimes based on
extrapolation from scaled devices, thereby introducing additional inaccuracies.
(iii)
Experienced users may
overcome known code limitations by adding engineering knowledge to the input
deck.
(iv)
Problems inherent to a
given code or a particular facility have been dealt with over the years by the
consideration and modeling of local pressure drop coefficients, critical flow
rate multipliers, or other bias to obtain improved solutions. This has been
traditionally done to compensate for code limitation (e.g., application of
steady-state qualified models to transient conditions, and lack of validity of
the fully developed flow concept in typical nuclear reactor conditions).
Furthermore, specific effects such as small bypass flows or distribution of
heat losses might exacerbate the user effect.
(v)
The increasing number
of users performing analysis with insufficient training.  As such, their lack of
understanding of the code capabilities and limitations leads to incorrect
interpretation of results. The failure to obtain a stable steady state by the
user prior to the initiation of the transient is included in this item.
(vi)
A nonnegligible effect on
code results comes from the compiler and the computer used to run an assigned
code selected by the user; this remains true for very recent code versions.
(vii)
Error bands and the values
of initial and boundary conditions which are needed as code inputs are not well
defined; this ambiguity is used to justify inappropriate model modifications or
interpretation of results.
(viii)
Analysts lack complete
information about facilities before developing input and hence filling the gaps
with unqualified data.
(ix)
Although the number of
user options is thought to be reduced in the advanced codes, for some codes
there are several models and correlations for the user to choose. The user is
also required to specify parameters such as pressure loss coefficients, manometric
characteristics, efficiencies, and correlation factors which may not be well
defined.
(x)
Most codes have algorithms
to adjust the time step control (e.g., Courant limit) to maximum efficiency and
minimize run time. However, users are allowed to change the time step to
overcome code difficulties and impose smaller time steps for a given period of
the transient. If the particular code uses an explicit numerical scheme, the
result will vary significantly with the time step size.
(xi)
Quality assurance guidelines
should be followed to check the correctness of the values introduced in the
input despite the automatic consistency checks provided by the code.
Typical examples of user and other
related effects on code calculations of selected experiments are presented in
several CSNI reports (e.g., ISP-25, ACHILLES reflooding test; LOBI natural
circulation test; ISP-22 on SPES Loss-Of-Feed-Water test; ISP-26 on LSTF 5%
cold-leg-break loss-of-coolant-accident (LOCA); ISP-27 on BETHSY 2"
cold-leg LOCA) and based on these outcomes different organizations have defined in what follows some general
principles in order to reduce the user effects.(i)
The misapplication of the
system code should be eliminated (or reduced at least) by means of
sufficiently detailed code description and by relevant code user
guidelines.
(ii)
Errors should be
minimized: any analysis of merit should include quality assurance
procedures designed to minimize or eliminate errors. In a sense, the
mis-application of the system code is itself a certain class of error.
(iii)
The user community should
preferably use the same computing platform (i.e., the machine round-off
er-rors and treatment of arithmetic operations are as-sumed the same).
(iv)
The system code should
preferably be used by a relatively large user community (a large sample
size).
(v)
The problem to be
analyzed should be rigorously specified (i.e., all geometrical dimensions,
initial conditions, and boundary conditions should be clearly specified). Within the defined
framework, the user effect can be quantified and be a function of(i)
the flexibility of the system code. An example is the flexibility associated with modeling a system
compo-nent such as the steam generator: for instance, the TRAC code has a
specific component designed to model steam generators whereas a steam generator
model created using RELAP5 is constructed of basic model components such as PIPE and BRANCH; consequently, there are more degrees of
freedom available to the user, each requiring a decision, when a RELAP5 steam
generator model is being constructed than when a TRAC-generated model of the
same component is being defined;
(ii)
the practices used to define the nodalization and to ensure that a
convergent solution is achieved.
In this context, the code validation process, the nodalization qualification,
and the qualitative or quantitative accuracy evaluation are necessary steps to
reduce the possibility of producing poor code predictions [12, 13].


## 2.1. Role and Relevance of Code User

The best estimate thermal-hydraulic codes used in the
area of nuclear reactor safety have reached a marked level of sophistication.
Their capabilities to predict accidents and transients at existing plants have
substantially improved over the past years as a result of large research
efforts and can be considered satisfactory for practical needs provided that
they are used by competent analysts.Best estimate system
codes (RELAP, TRAC, CATHARE, or ATHLET) are currently used by
design-er/vendors of NPPs, by utilities, licensing authorities, research
organizations including universities, nuclear fuel companies, and by technical
support organizations. The objectives of using the codes may be quite
different, ranging from design or safety assessment to simply understanding the
transient behavior of a simple system. However, the ap-plication of a selected
code must be proven to be adequate to the performed analysis. Many aspects from
the design data necessary to create input to the selection of the noding solutions
and the code itself are the user’s responsibility [9–11].The role of the code user is extremely
relevant: experience with large number of International Standard Problems (ISPs)
has shown the dominant influence of the code user on the final results and the
goal of reduction of user effects has not been achieved. It has been observed
previously that(i)
the user gives a contribution to the overall uncertainty that
unavoidably characterizes system code calculation results;
(ii)
in the majority of cases, it is impossible to distinguish among
uncertainty sources like “user effect,” “nodalization inadequacy,” “physical
model deficiencies,” “uncertainty in boundary or initial conditions,” and “computer/compiler
effect;”
(iii)
“reducing the user effect” or “finding the optimum nodalization” should
not be regarded as a process that removes the need to assess the uncertainty.
Performing an adequate code analysis or
assessment involves two main aspects.(1)
Code adequacy. The adequacy demonstration process must be
undertaken by a code user when a code is used outside its assessment range,
when changes are made to the code, and when a code is used for new applications
where different phenomena are expected. The impact of these changes must be
analyzed and the analyses must be thoroughly reviewed to ensure that the code
models are still adequate to represent the phenomena that are being observed.
(2)
Quality of results. Historically the results of code predictions,
specifically when compared with experimental data gathered from applicable
scaled test facilities, have revealed inadequacies raising concerns about code
reliability and their practical usefulness. Discrepancies between measured and
calculated values were typically attributed to model deficiencies, approximation
in the numeric solutions, computer, and compiler
effects, nodalization inadequacies, imperfect knowledge of boundary and initial
conditions, unrevealed mistakes in the input deck, and to “user
effect." In several ISPs sponsored by OECD (Organisation for Economic Cooperation and
Development), several users modeled
the same experiment using the same code, and the code-calculated results varied
widely, regardless of the code used. Some of the discrepancies can be
attributed to the code user approach as well as to a general lack of
understanding of both the facility and the test.
The two items are the main aspects, both
related to the code user. The first aspect is included in the qualification framework
of the code and nodalization. The second aspect is directly related to the user
choices generally referred to as User Effect.


## 2.2. User Effect

Complex systems codes
such as RELAP5, CATHARE, TRAC, and ATHLET have many degrees of freedom that
allow misapplication (e.g., not using the countercurrent flow-limiting model at
a junction where it is required) and errors by users (e.g., inputting the
incorrect length of a system component). In addition, even two competent users
will not approach the analysis of a problem in the same way and consequently,
will likely take different paths to obtain a problem solution. The cumulative
effect of user community members to produce a range of answers using the same
code for a well-defined problem with rigorously specified boundary and initial
conditions is the user effect (see Figure1).Figure 1
User effect: different results for the cladding temperature in the ISP25 test from different users adopting the same code and BIC.The following are some of the reasons for the
user effects.(i)
Code use guidelines are
not fully detailed or comprehensive.
(ii)
Based on the current state
of the art, the actual 3D plant geometries are usually modeled using several 1D
zones; these complex 3D geometries are suitable for different modeling
alternatives; as a consequence an assigned reactor vessel part is modeled
differently by different users of the same code. Beside the major 1dimensional
code modules, a number of empirical models for system components, such as
pumps, valves, and separators, are specified by the users, sometimes based on
extrapolation from scaled devices, thereby introducing additional inaccuracies.
(iii)
Experienced users may
overcome known code limitations by adding engineering knowledge to the input
deck.
(iv)
Problems inherent to a
given code or a particular facility have been dealt with over the years by the
consideration and modeling of local pressure drop coefficients, critical flow
rate multipliers, or other bias to obtain improved solutions. This has been
traditionally done to compensate for code limitation (e.g., application of
steady-state qualified models to transient conditions, and lack of validity of
the fully developed flow concept in typical nuclear reactor conditions).
Furthermore, specific effects such as small bypass flows or distribution of
heat losses might exacerbate the user effect.
(v)
The increasing number
of users performing analysis with insufficient training.  As such, their lack of
understanding of the code capabilities and limitations leads to incorrect
interpretation of results. The failure to obtain a stable steady state by the
user prior to the initiation of the transient is included in this item.
(vi)
A nonnegligible effect on
code results comes from the compiler and the computer used to run an assigned
code selected by the user; this remains true for very recent code versions.
(vii)
Error bands and the values
of initial and boundary conditions which are needed as code inputs are not well
defined; this ambiguity is used to justify inappropriate model modifications or
interpretation of results.
(viii)
Analysts lack complete
information about facilities before developing input and hence filling the gaps
with unqualified data.
(ix)
Although the number of
user options is thought to be reduced in the advanced codes, for some codes
there are several models and correlations for the user to choose. The user is
also required to specify parameters such as pressure loss coefficients, manometric
characteristics, efficiencies, and correlation factors which may not be well
defined.
(x)
Most codes have algorithms
to adjust the time step control (e.g., Courant limit) to maximum efficiency and
minimize run time. However, users are allowed to change the time step to
overcome code difficulties and impose smaller time steps for a given period of
the transient. If the particular code uses an explicit numerical scheme, the
result will vary significantly with the time step size.
(xi)
Quality assurance guidelines
should be followed to check the correctness of the values introduced in the
input despite the automatic consistency checks provided by the code.
Typical examples of user and other
related effects on code calculations of selected experiments are presented in
several CSNI reports (e.g., ISP-25, ACHILLES reflooding test; LOBI natural
circulation test; ISP-22 on SPES Loss-Of-Feed-Water test; ISP-26 on LSTF 5%
cold-leg-break loss-of-coolant-accident (LOCA); ISP-27 on BETHSY 2"
cold-leg LOCA) and based on these outcomes different organizations have defined in what follows some general
principles in order to reduce the user effects.(i)
The misapplication of the
system code should be eliminated (or reduced at least) by means of
sufficiently detailed code description and by relevant code user
guidelines.
(ii)
Errors should be
minimized: any analysis of merit should include quality assurance
procedures designed to minimize or eliminate errors. In a sense, the
mis-application of the system code is itself a certain class of error.
(iii)
The user community should
preferably use the same computing platform (i.e., the machine round-off
er-rors and treatment of arithmetic operations are as-sumed the same).
(iv)
The system code should
preferably be used by a relatively large user community (a large sample
size).
(v)
The problem to be
analyzed should be rigorously specified (i.e., all geometrical dimensions,
initial conditions, and boundary conditions should be clearly specified). Within the defined
framework, the user effect can be quantified and be a function of(i)
the flexibility of the system code. An example is the flexibility associated with modeling a system
compo-nent such as the steam generator: for instance, the TRAC code has a
specific component designed to model steam generators whereas a steam generator
model created using RELAP5 is constructed of basic model components such as PIPE and BRANCH; consequently, there are more degrees of
freedom available to the user, each requiring a decision, when a RELAP5 steam
generator model is being constructed than when a TRAC-generated model of the
same component is being defined;
(ii)
the practices used to define the nodalization and to ensure that a
convergent solution is achieved.
In this context, the code validation process, the nodalization qualification,
and the qualitative or quantitative accuracy evaluation are necessary steps to
reduce the possibility of producing poor code predictions [12, 13].


## 3. Permanent User Training Course for System Code: The Proposal

As a follow-up to the
specialists meeting held at the IAEA in September 1998, the Universities of Pisa
and Zagreb
and
the Jožef Stefan
Institute, Ljubljana,
jointly presented a Proposal to IAEA for the Permanent Training Course for
System Code Users [14]. It was recognized that such a course would represent
both a source of continuing education for current code users and a means for
current code users to enter the formal training structure of a proposed
“permanent” stepwise approach to user training.As a follow-up to the
massive work conducted in different organizations, the need was felt to fix
criteria for training the code user. As a first step, the kind of code user and
the level of responsibility of a calculation result should be discussed.


### 3.1. Levels of User Qualification

Two main levels for code user
qualification are distinguished in the following:(i)
code user, level “A" (LA);
(ii)
responsible for the calculation results, level
“B" (LB).
Two levels should be considered among LB code users to distinguish
seniority (i.e., Level B, Senior (LBS)). Requisites are detailed hereafter for
the LA grade only; these must be intended as a necessary step (in the future)
to achieve the LB and the LBS grades. The main difference between LA and LB
lies in the documented experience with the use of a system code; for the LB and
the LBS grades, this can be fixed in 5 and 10 years, respectively, after
achieving the LA grade. In such a context, any calculation having an impact in
the sense previously defined must be approved by a LB (or LBS) code user and
performed by a different LA or LB (or LBS) code user.


### 3.2. Requisites for Code User Qualification

#### 3.2.1. LA Code User Grade

The identification of the requisites for a qualified code
user derives from the areas and the steps concerned with a qualified system
code calculation: a system code is one of the codes previously defined and a
qualified calculation in principle includes the uncertainty analysis. The
starting condition for LA code user is a scientist with generic knowledge of
nuclear power plants and reactor thermal hydraulics (e.g., in possession of the
master degree in US, of the “Laurea” in Italy, etc.).The requisites competencies for the LA grade code user are in
the following areas.(A)
Generic code development and assessment processes:
Subarea (A1):
conservation (or balance) equations in thermal hydraulics including definitions like HEM/EVET, UVUT(UP),
Drift Flux, 1D, 3D, 1-field, Multifield, [2], conduction and radiation heat
transfer, Neutron Transport Theory and Neutron Kinetics approximation, constitutive
(closure) equations including convection heat transfer, special components
(e.g., pump, separator), material properties, simulation of nuclear plant and
BoP related control systems, numerical methods, general structure of a system
code;
Subarea (A2):
developmental assessment, independent assessment including Separate
Effect Tests (SETF) Code Validation Matrix [3], and Integral Test (ITF) Code
Validation Matrix [4]. Examples of specific Code validation Matrices.
(B)
Specific code structure:
Subarea (B1):
structure of the system code selected
by the LA code user: thermal hydraulics, neutronics, control system, special
components, material properties, numerical solution;
Subarea (B2):
structure of the input; examples of
user choices.
(C)
Code use-Fundamental Problems (FP):
Subarea (C1):
definition of Fundamental Problem
(FP): simple problems for which analytical solution may be available or less.
Examples of code results from applications to FP; different areas of the code
must be concerned (e.g., neutronics, thermal hydraulics, and numerics);
Subarea (C2):
the LA code user must deeply analyze at least three
specified FPs, searching for and characterizing the effects of nodalization
details, time step selection and other code-specific features (to develop a nodalization starting from a supplied data base or problem
specifications; to run a reference test case; to compare the results of the reference test case with data (experimental
data, results of other codes, analytical solution), if available; to run
sensitivity calculations; and to produce
a comprehensive calculation report (having an assigned format).
(D)
Basic Experiments and Test Facilities (BETF):
Subarea (D1):
definition of Basic Experiments and test
facilities (BETF): research aiming at the characterization of an individual
phenomenon or of an individual quantity appearing in the code implemented
equations, not necessarily connected with the NPP. Examples of code results
from applications to BETF;
Subarea (D2):
the LA code user must deeply analyze
at least two selected BETF, searching for and characterizing the effects of
nodalization details, time step selection, error in boundary and initial
conditions, and other code-specific features.
(E)
Code use-Separate Effect Test Facilities (SETF):
Subarea (E1):
Definition of Separate Effect Test
Facility (SETF): test facility where a component (or an ensemble of components)
or a phenomenon (or an ensemble of phenomena) of the reference NPP is
simulated. Details about scaling laws and design criteria. Examples of code
results from applications to SETF;
Subarea (E2):
The LA code user must deeply analyze at least one specified SETF experiment,
searching for and characterizing the effects of nodalization details, time step
selection, errors in boundary and initial conditions, and other code-specific
features.
(F)
Code use-Integral Test Facilities (ITF):
Subarea (F1):
definition of Integral Test
Facility (ITF): test facility where the transient behavior of the entire NPP is
addressed. Details about scaling laws and design criteria. Details about
existing (or dismantled) ITF and related experimental programs. ISPs activity.
Examples of code results from applications to ITF;
Subarea (F2):
the LA code user must deeply
analyze at least two specified ITF
experiments, searching for and characterizing the effects of nodalization
details, time step selection, errors in boundary and initial conditions and
other code-specific features.
(G)
Code use-Nuclear Power Plant transient Data:
Subarea (G1):
description of the concerned NPP
and of the relevant (to the concerned NPP and calculation) BoP and ECC systems.
Examples of code results from applications to NPP;
Subarea (G2):
the LA code user must deeply
analyze at least two specified NPP transients, searching for and characterizing
the effects of nodalization details, time step selection, errors in boundary
and initial conditions and other code-specific features.
(H)
Uncertainty Methods including concepts like nodalization, accuracy
quantification, and user effects.Description of the available
uncertainty methodologies. The LA code user must be aware of the state of the
art in this field.


#### 3.2.2. LB Code User Grade

A qualified user at the LB grade must be in possession of the same
expertise as the LA grade and(I)
he
must have a documented experience in the use of system codes of at least 5
additional years;
(J)
he must
know the fundamentals of Reactor Safety and Operation- and Design having
generic expertise in the area of application of the concerned calculation;
(K)
he must be
aware of the use and of the consequences of the calculation results; this may
imply the knowledge of the licensing process.


#### 3.2.3. LBS Code User Grade

A qualified user at the LBS grade must be in possession of the same
expertise as the LB grade and(L)
he must have
an additional documented experience in the use of system codes of at least 5
additional years. Moreover, the LBS code user is responsible for documenting
user guidelines, methodology descriptions, and for providing technical
leadership in R&D activities.


### 3.3. Course Conduct and Modalities for the Achievements of Code User Grades

The training of the code user
requires the conduct of lectures, practical on-site exercises, homework, and
examination, while for the senior code user, only a review of documented
experience and on-site examination is foreseen. The code user training,
including practical exercises which represent an essential part of the course,
lasts two years and covers the areas from (A) to (H).The modalities defined in Table1 are necessary to achieve the LA, LB
(5 years after the LA grade), and LBS (5 years after achieving the LB grade and
following the demonstration of performed activity in the 5-year period) grades.Table 1
Subjects and time schedule necessary for the LA Code user grade.
Code
user grade
Weeks
Lectures
Specific
for homework
Homework
On-site
test
LA
1-2
A1, A2
⋀, B1, B2
⋀, C1, D1
3
C2, D2
4–25
A, B, C2*, D2*
26
A1, B1, C, D, C2°, D2°
27
A2, E1
E2
28–50
E2*
51
A2, E, E2°
52
B2, F1
F2
53–76
F2*
77
B2, F, F2°
78
H, G1
G2*
79–102
G2*
103
G, H, G2*
LB (5 yrs after LA)
1
I*, J, K, K°
LBS
(5 yrs after LB)
1
L*
⋀ Fundamental
*Report necessary
°Solution of submitted problems and discussion.


### 3.4. Training Exercises

Practical exercises foreseen during the training include
development of the nodalization from the pre-prepared database with problem
specifications. To this end, educational material and presentations/lectures on
the exercise will be provided with a detailed explanation of the objectives of
the work that the trainee must perform. Extensive application of the code by
the trainee at his own institution following detailed recommendations and under
the supervision of the course lecturers is foreseen as “homework.” The use of
the code at the course venue is foreseen for the following applications:(i)
fundamental problems including nodalization
development;
(ii)
basic test facilities and related experiments
including nodalization development;
(iii)
SETFs and related experiments including nodalization
development;
(iv)
ITF experiments with nodalization modifications; and
(v)
NPP transients including nodalization modifications.
For each of the above cases, the trainee will be required to(1)
develop (or modify) a nodalization starting from the database or problem
specifications provided;
(2)
run the reference test case;
(3)
compare the results of the reference test case with data (experimental
data, results of other codes, and analytical solution);
(4)
run sensitivity calculations;
(5)
produce a comprehensive calculation report following a prescribed format
whereby the report should include, for example,
(a)
the description of a particular facility;
(b)
the description of an experiment (including relevance to scaling and
relevance to safety);
(c)
modalities for developing (or modifying) the nodalization;
(d)
the description and use of nodalization qualification criteria for
steady-state and transient calculations;
(e)
qualitative and quantitative accuracy evaluation;
(f)
use of thresholds for the acceptability of results for the reference
case;
(g)
planning and analysis of the sensitivity runs; and
(h)
an overall
evaluation of the activity (code capabilities, nodalization adequacy, scaling,
impact of the results on the safety
and the design of NPP, etc.).


### 3.5. Examination

On-site examination at different stages during the
course is considered a condition for the successful completion of the code user
training. The homework that the candidate must complete before attempting the
on-site examination includes(A)
studying the
material/documents supplied by the course organizers and
(B)
solving the problems
assigned by the course organizers. This also involves the preparation of
suitable reports that must be approved by the course organizers.
The on-site tests
consist of four main steps that include the evaluation of the reports prepared
by the candidate, answering questions on the reports and course subjects, and
demonstrating the capability to work with the selected code. Each step must be
accomplished before proceeding to the subsequent one.


## 3.1. Levels of User Qualification

Two main levels for code user
qualification are distinguished in the following:(i)
code user, level “A" (LA);
(ii)
responsible for the calculation results, level
“B" (LB).
Two levels should be considered among LB code users to distinguish
seniority (i.e., Level B, Senior (LBS)). Requisites are detailed hereafter for
the LA grade only; these must be intended as a necessary step (in the future)
to achieve the LB and the LBS grades. The main difference between LA and LB
lies in the documented experience with the use of a system code; for the LB and
the LBS grades, this can be fixed in 5 and 10 years, respectively, after
achieving the LA grade. In such a context, any calculation having an impact in
the sense previously defined must be approved by a LB (or LBS) code user and
performed by a different LA or LB (or LBS) code user.


## 3.2. Requisites for Code User Qualification

### 3.2.1. LA Code User Grade

The identification of the requisites for a qualified code
user derives from the areas and the steps concerned with a qualified system
code calculation: a system code is one of the codes previously defined and a
qualified calculation in principle includes the uncertainty analysis. The
starting condition for LA code user is a scientist with generic knowledge of
nuclear power plants and reactor thermal hydraulics (e.g., in possession of the
master degree in US, of the “Laurea” in Italy, etc.).The requisites competencies for the LA grade code user are in
the following areas.(A)
Generic code development and assessment processes:
Subarea (A1):
conservation (or balance) equations in thermal hydraulics including definitions like HEM/EVET, UVUT(UP),
Drift Flux, 1D, 3D, 1-field, Multifield, [2], conduction and radiation heat
transfer, Neutron Transport Theory and Neutron Kinetics approximation, constitutive
(closure) equations including convection heat transfer, special components
(e.g., pump, separator), material properties, simulation of nuclear plant and
BoP related control systems, numerical methods, general structure of a system
code;
Subarea (A2):
developmental assessment, independent assessment including Separate
Effect Tests (SETF) Code Validation Matrix [3], and Integral Test (ITF) Code
Validation Matrix [4]. Examples of specific Code validation Matrices.
(B)
Specific code structure:
Subarea (B1):
structure of the system code selected
by the LA code user: thermal hydraulics, neutronics, control system, special
components, material properties, numerical solution;
Subarea (B2):
structure of the input; examples of
user choices.
(C)
Code use-Fundamental Problems (FP):
Subarea (C1):
definition of Fundamental Problem
(FP): simple problems for which analytical solution may be available or less.
Examples of code results from applications to FP; different areas of the code
must be concerned (e.g., neutronics, thermal hydraulics, and numerics);
Subarea (C2):
the LA code user must deeply analyze at least three
specified FPs, searching for and characterizing the effects of nodalization
details, time step selection and other code-specific features (to develop a nodalization starting from a supplied data base or problem
specifications; to run a reference test case; to compare the results of the reference test case with data (experimental
data, results of other codes, analytical solution), if available; to run
sensitivity calculations; and to produce
a comprehensive calculation report (having an assigned format).
(D)
Basic Experiments and Test Facilities (BETF):
Subarea (D1):
definition of Basic Experiments and test
facilities (BETF): research aiming at the characterization of an individual
phenomenon or of an individual quantity appearing in the code implemented
equations, not necessarily connected with the NPP. Examples of code results
from applications to BETF;
Subarea (D2):
the LA code user must deeply analyze
at least two selected BETF, searching for and characterizing the effects of
nodalization details, time step selection, error in boundary and initial
conditions, and other code-specific features.
(E)
Code use-Separate Effect Test Facilities (SETF):
Subarea (E1):
Definition of Separate Effect Test
Facility (SETF): test facility where a component (or an ensemble of components)
or a phenomenon (or an ensemble of phenomena) of the reference NPP is
simulated. Details about scaling laws and design criteria. Examples of code
results from applications to SETF;
Subarea (E2):
The LA code user must deeply analyze at least one specified SETF experiment,
searching for and characterizing the effects of nodalization details, time step
selection, errors in boundary and initial conditions, and other code-specific
features.
(F)
Code use-Integral Test Facilities (ITF):
Subarea (F1):
definition of Integral Test
Facility (ITF): test facility where the transient behavior of the entire NPP is
addressed. Details about scaling laws and design criteria. Details about
existing (or dismantled) ITF and related experimental programs. ISPs activity.
Examples of code results from applications to ITF;
Subarea (F2):
the LA code user must deeply
analyze at least two specified ITF
experiments, searching for and characterizing the effects of nodalization
details, time step selection, errors in boundary and initial conditions and
other code-specific features.
(G)
Code use-Nuclear Power Plant transient Data:
Subarea (G1):
description of the concerned NPP
and of the relevant (to the concerned NPP and calculation) BoP and ECC systems.
Examples of code results from applications to NPP;
Subarea (G2):
the LA code user must deeply
analyze at least two specified NPP transients, searching for and characterizing
the effects of nodalization details, time step selection, errors in boundary
and initial conditions and other code-specific features.
(H)
Uncertainty Methods including concepts like nodalization, accuracy
quantification, and user effects.Description of the available
uncertainty methodologies. The LA code user must be aware of the state of the
art in this field.


### 3.2.2. LB Code User Grade

A qualified user at the LB grade must be in possession of the same
expertise as the LA grade and(I)
he
must have a documented experience in the use of system codes of at least 5
additional years;
(J)
he must
know the fundamentals of Reactor Safety and Operation- and Design having
generic expertise in the area of application of the concerned calculation;
(K)
he must be
aware of the use and of the consequences of the calculation results; this may
imply the knowledge of the licensing process.


### 3.2.3. LBS Code User Grade

A qualified user at the LBS grade must be in possession of the same
expertise as the LB grade and(L)
he must have
an additional documented experience in the use of system codes of at least 5
additional years. Moreover, the LBS code user is responsible for documenting
user guidelines, methodology descriptions, and for providing technical
leadership in R&D activities.


## 3.2.1. LA Code User Grade

The identification of the requisites for a qualified code
user derives from the areas and the steps concerned with a qualified system
code calculation: a system code is one of the codes previously defined and a
qualified calculation in principle includes the uncertainty analysis. The
starting condition for LA code user is a scientist with generic knowledge of
nuclear power plants and reactor thermal hydraulics (e.g., in possession of the
master degree in US, of the “Laurea” in Italy, etc.).The requisites competencies for the LA grade code user are in
the following areas.(A)
Generic code development and assessment processes:
Subarea (A1):
conservation (or balance) equations in thermal hydraulics including definitions like HEM/EVET, UVUT(UP),
Drift Flux, 1D, 3D, 1-field, Multifield, [2], conduction and radiation heat
transfer, Neutron Transport Theory and Neutron Kinetics approximation, constitutive
(closure) equations including convection heat transfer, special components
(e.g., pump, separator), material properties, simulation of nuclear plant and
BoP related control systems, numerical methods, general structure of a system
code;
Subarea (A2):
developmental assessment, independent assessment including Separate
Effect Tests (SETF) Code Validation Matrix [3], and Integral Test (ITF) Code
Validation Matrix [4]. Examples of specific Code validation Matrices.
(B)
Specific code structure:
Subarea (B1):
structure of the system code selected
by the LA code user: thermal hydraulics, neutronics, control system, special
components, material properties, numerical solution;
Subarea (B2):
structure of the input; examples of
user choices.
(C)
Code use-Fundamental Problems (FP):
Subarea (C1):
definition of Fundamental Problem
(FP): simple problems for which analytical solution may be available or less.
Examples of code results from applications to FP; different areas of the code
must be concerned (e.g., neutronics, thermal hydraulics, and numerics);
Subarea (C2):
the LA code user must deeply analyze at least three
specified FPs, searching for and characterizing the effects of nodalization
details, time step selection and other code-specific features (to develop a nodalization starting from a supplied data base or problem
specifications; to run a reference test case; to compare the results of the reference test case with data (experimental
data, results of other codes, analytical solution), if available; to run
sensitivity calculations; and to produce
a comprehensive calculation report (having an assigned format).
(D)
Basic Experiments and Test Facilities (BETF):
Subarea (D1):
definition of Basic Experiments and test
facilities (BETF): research aiming at the characterization of an individual
phenomenon or of an individual quantity appearing in the code implemented
equations, not necessarily connected with the NPP. Examples of code results
from applications to BETF;
Subarea (D2):
the LA code user must deeply analyze
at least two selected BETF, searching for and characterizing the effects of
nodalization details, time step selection, error in boundary and initial
conditions, and other code-specific features.
(E)
Code use-Separate Effect Test Facilities (SETF):
Subarea (E1):
Definition of Separate Effect Test
Facility (SETF): test facility where a component (or an ensemble of components)
or a phenomenon (or an ensemble of phenomena) of the reference NPP is
simulated. Details about scaling laws and design criteria. Examples of code
results from applications to SETF;
Subarea (E2):
The LA code user must deeply analyze at least one specified SETF experiment,
searching for and characterizing the effects of nodalization details, time step
selection, errors in boundary and initial conditions, and other code-specific
features.
(F)
Code use-Integral Test Facilities (ITF):
Subarea (F1):
definition of Integral Test
Facility (ITF): test facility where the transient behavior of the entire NPP is
addressed. Details about scaling laws and design criteria. Details about
existing (or dismantled) ITF and related experimental programs. ISPs activity.
Examples of code results from applications to ITF;
Subarea (F2):
the LA code user must deeply
analyze at least two specified ITF
experiments, searching for and characterizing the effects of nodalization
details, time step selection, errors in boundary and initial conditions and
other code-specific features.
(G)
Code use-Nuclear Power Plant transient Data:
Subarea (G1):
description of the concerned NPP
and of the relevant (to the concerned NPP and calculation) BoP and ECC systems.
Examples of code results from applications to NPP;
Subarea (G2):
the LA code user must deeply
analyze at least two specified NPP transients, searching for and characterizing
the effects of nodalization details, time step selection, errors in boundary
and initial conditions and other code-specific features.
(H)
Uncertainty Methods including concepts like nodalization, accuracy
quantification, and user effects.Description of the available
uncertainty methodologies. The LA code user must be aware of the state of the
art in this field.


## 3.2.2. LB Code User Grade

A qualified user at the LB grade must be in possession of the same
expertise as the LA grade and(I)
he
must have a documented experience in the use of system codes of at least 5
additional years;
(J)
he must
know the fundamentals of Reactor Safety and Operation- and Design having
generic expertise in the area of application of the concerned calculation;
(K)
he must be
aware of the use and of the consequences of the calculation results; this may
imply the knowledge of the licensing process.


## 3.2.3. LBS Code User Grade

A qualified user at the LBS grade must be in possession of the same
expertise as the LB grade and(L)
he must have
an additional documented experience in the use of system codes of at least 5
additional years. Moreover, the LBS code user is responsible for documenting
user guidelines, methodology descriptions, and for providing technical
leadership in R&D activities.


## 3.3. Course Conduct and Modalities for the Achievements of Code User Grades

The training of the code user
requires the conduct of lectures, practical on-site exercises, homework, and
examination, while for the senior code user, only a review of documented
experience and on-site examination is foreseen. The code user training,
including practical exercises which represent an essential part of the course,
lasts two years and covers the areas from (A) to (H).The modalities defined in Table1 are necessary to achieve the LA, LB
(5 years after the LA grade), and LBS (5 years after achieving the LB grade and
following the demonstration of performed activity in the 5-year period) grades.Table 1
Subjects and time schedule necessary for the LA Code user grade.
Code
user grade
Weeks
Lectures
Specific
for homework
Homework
On-site
test
LA
1-2
A1, A2
⋀, B1, B2
⋀, C1, D1
3
C2, D2
4–25
A, B, C2*, D2*
26
A1, B1, C, D, C2°, D2°
27
A2, E1
E2
28–50
E2*
51
A2, E, E2°
52
B2, F1
F2
53–76
F2*
77
B2, F, F2°
78
H, G1
G2*
79–102
G2*
103
G, H, G2*
LB (5 yrs after LA)
1
I*, J, K, K°
LBS
(5 yrs after LB)
1
L*
⋀ Fundamental
*Report necessary
°Solution of submitted problems and discussion.


## 3.4. Training Exercises

Practical exercises foreseen during the training include
development of the nodalization from the pre-prepared database with problem
specifications. To this end, educational material and presentations/lectures on
the exercise will be provided with a detailed explanation of the objectives of
the work that the trainee must perform. Extensive application of the code by
the trainee at his own institution following detailed recommendations and under
the supervision of the course lecturers is foreseen as “homework.” The use of
the code at the course venue is foreseen for the following applications:(i)
fundamental problems including nodalization
development;
(ii)
basic test facilities and related experiments
including nodalization development;
(iii)
SETFs and related experiments including nodalization
development;
(iv)
ITF experiments with nodalization modifications; and
(v)
NPP transients including nodalization modifications.
For each of the above cases, the trainee will be required to(1)
develop (or modify) a nodalization starting from the database or problem
specifications provided;
(2)
run the reference test case;
(3)
compare the results of the reference test case with data (experimental
data, results of other codes, and analytical solution);
(4)
run sensitivity calculations;
(5)
produce a comprehensive calculation report following a prescribed format
whereby the report should include, for example,
(a)
the description of a particular facility;
(b)
the description of an experiment (including relevance to scaling and
relevance to safety);
(c)
modalities for developing (or modifying) the nodalization;
(d)
the description and use of nodalization qualification criteria for
steady-state and transient calculations;
(e)
qualitative and quantitative accuracy evaluation;
(f)
use of thresholds for the acceptability of results for the reference
case;
(g)
planning and analysis of the sensitivity runs; and
(h)
an overall
evaluation of the activity (code capabilities, nodalization adequacy, scaling,
impact of the results on the safety
and the design of NPP, etc.).


## 3.5. Examination

On-site examination at different stages during the
course is considered a condition for the successful completion of the code user
training. The homework that the candidate must complete before attempting the
on-site examination includes(A)
studying the
material/documents supplied by the course organizers and
(B)
solving the problems
assigned by the course organizers. This also involves the preparation of
suitable reports that must be approved by the course organizers.
The on-site tests
consist of four main steps that include the evaluation of the reports prepared
by the candidate, answering questions on the reports and course subjects, and
demonstrating the capability to work with the selected code. Each step must be
accomplished before proceeding to the subsequent one.


## 4. 3D S.UN.COP Seminars: Follow-up of the Proposal

### 4.1. Background Information about 3D S.UN.COP Trainings

The 3D
S.UN.COP (Scaling, Uncertainty, and 3D coupled code calculations) training aims
to transfer competence, knowledge, and experience from recognized international
experts in the area of scaling, uncertainty, and 3D coupled code calculations
in nuclear reactor safety technology to analysts with a suitable background in
nuclear technology.The training
(http://dimnp.ing.unipi.it/3dsuncop) is open to research organizations,
companies, vendors, industry, academic institutions, regulatory authorities,
national laboratories, and so on. The seminar is in general subdivided into
three parts and participants may choose to attend a one-, two-, or three-week
course. The first week is dedicated to the background information including the
theoretical bases for the proposed methodologies; the second week is devoted to
the practical application of the methodologies and to the hands-on training on
numerical codes; the third week is dedicated to the user qualification problem
through the hands-on training for advanced user and includes a final exam. From
the point of view of the conduct of the training, the weeks are characterized
by lectures, code-expert teaching, and by hands-on-application. More than
thirty scientists are in general involved in the organization of the seminars,
presenting theoretical aspects of the proposed methodologies and holding the
training and the final examination. A certificate of qualified code user is
released to participants that successfully solve the assigned problems during
the exams.The
framework in which the 3D S.UN.COP seminars have been designed may be derived
from
Figure2, where the roles of two main international institutions (OECD and
IAEA) and of the US NRC (here playing the role of any other regulatory body of
other countries) to address the problem of user effect are outlined together
with the proposed programs and produced documents. Figure 3 depicts how the 3D
S.UN.COP ensures the nuclear technology maintenance and advancements through the qualification of personnel in
regulatory bodies, research activities, and industries by means of teaching by very well-known
scientists belonging to the same type of institutions.Figure 2
3D S.UN.COP framework to address the user effect problem.Figure 3
3D S.UN.COP Loop of benefits.Seven training courses
have been organized up to now and were successfully held at(i)
The University of Pisa (Pisa, Italy), 5–9 January 2004 (6
participants);
(ii)
The Pennsylvania State University (University
Park, PA, USA), 24–28 May 2004 (15
participants);
(iii)
The University of Pisa (Pisa, Italy), 14–18 June 2004 (11
participants);
(iv)
The University of Zagreb
(Zagreb, Croatia), 20 June–8 July 2005 (19
participants);
(v)
The Technical University of
Catalonia (Barcelona, Spain), 23 January–10 February 2006
(33 participants);
(vi)
The “Autoridad
Regulatoria Nuclear (ARN),” the “Comisión Nacional de Energía
Atómica (CNEA),” the “Nucleoelectrica Argentina S.A (NA-SA),”
and the “Universidad Argentina De la Empresa” (Buenos Aires,
Argentina), 2 October–14 October 2006
(37 participants); and
(vii)
The Texas A&M University
(College Station, Texas, USA), 22 January–9 February 2007
(26 participants).


### 4.2. Objectives and Features of the 3D S.UN.COP Seminar Trainings

The main objective of the seminar activity is the
training in safety analysis of analysts with a suitable background in nuclear
technology. The training is devoted to the promotion and use of international
guidance and to homogenize the approach to the use of computer codes for
accident analysis. The main objectives are(i)
to transfer knowledge and expertise in Uncertainty Methodologies,
Thermal-Hydraulics System Code, and 3D Coupled Code Applications;
(ii)
to diffuse the use of international guidance;
(iii)
to homogenize
the approach in the use of computer codes (like RELAP, TRACE, CATHARE, ATHLET,
CATHENA, PARC, RELAP/SCDAP, MELCOR, and IMPACT) for accident analysis;
(iv)
to disseminate
the use of standard procedures for qualifying thermal-hydraulic system code
calculation (e.g., through the application of the UMAE “uncertainty methodology
based on accuracy extrapolation" [15]);
(v)
to promote best estimate plus uncertainty
(BEPU) methodologies in thermal-hydraulic accident analysis through the
presentation of the current industrial applications [16–20] and
the description of the theoretical aspects of the deterministic and statistical
uncertainty methods as well as the method based upon the propagation of output
errors (called CIAU “code with the capability of internal assessment of uncertainty"
[21, 22]);
(vi)
to spread available
robust approaches based on BEPU methodology in licensing process;
(vii)
to address and reduce user effects;
and
(viii)
to realize a
meeting point for exchanges of ideas among the worlds of Academy, Research
Laboratories, Industry, Regulatory Authorities, and International Institutions.
The main
features of the seminar course are identified as follows.(i)
The practical use of a mix of different codes. The use of different code is
worthwhile to establish a common basis for code assessment and for the
acceptability of code results.
(ii)
The exam.
Exams were in the past courses (very) well accepted by code users. The
exam gives them the possibility to show their expertise and to demonstrate
the effort done during the course.
(iii)
The practical use of procedures for nodalization qualification. Standardized techniques for
developing and qualifying nodalization (i.e., input) can be directly
applied in the participants institutions.
(iv)
The practical use of procedures for accuracy quantification. The availability of
methodologies and tools for quantifying qualitatively and quantitatively
the accuracy (i.e., the discrepancy between experimental and calculated
data) constitutes a key point for the acceptability of the code results.
(v)
The “joining” between BE codes and uncertainty evaluation. The use of BEPU methodology
within the licensing process is worthwhile for predicting more “realistic”
results and for demonstrating the existence of larger safety margins.
(vi)
The large participation of very well-known international experts. The establishment, integrity,
and use of international guidance are promoted through lectures presented
by top-level scientists coming from different institutions and countries.


### 4.3. Scientific and Technological Areas Presented  at the 3D S.UN.COP

As the acronym 3D
S.UN.COP implies, the following three scientifically relevant areas for the
nuclear technology are addressed during the course.(1)
Scaling analysis.
(2)
Best estimate plus uncertainty
analysis.
(3)
Three-dimensional coupled
code analysis.
Brief descriptions of
each topic are given hereafter.


#### 4.3.1. Scaling Analysis

Scaling is a broad term used in nuclear reactor
technology, as well as in basic fluid dynamics, and in thermal hydraulics. In
general terms, scaling indicates the need for the process of transferring
information from a model to a prototype. The model and the prototype are
typically characterized by different geometric dimensions as well as adopted
materials, including working fluids, and different ranges of variation for thermal-hydraulic
quantities.Therefore, the word “scaling” may have different
meanings in different contexts. In system thermal hydraulics, a scaling
process, based upon suitable physical principles, aims at establishing a
correlation between (a) phenomena expected in a NPP transient scenario and
phenomena measured in smaller scale facilities or (b) phenomena predicted by numerical
tools qualified against experiments performed
in small scale facilities (in connection with this point, owing to limitations
of the fundamental equations at the basis of system codes, the scaling issue
may constitute an important source of uncertainties in code applications and
may envelop various “individual” uncertainties).Three main objectives can be associated to the
scaling analysis:(i)
the design
of a test facility,
(ii)
the code
validation, that is, the demonstration that the code accuracy is scale
independent,
(iii)
the
extrapolation of experimental data (obtained into an ITF) to predict the
NPP behavior. In order to address the scaling issue,
different approaches have been historically followed:(i)
fluid
balance equation, deriving nondimensional parameters adopting the
Buckingham theorem,
(ii)
semi-empirical
mechanistic equations, deriving non-dimensional parameters,
(iii)
to perform
experiments at different scales (very expensive way and could not be
totally exhaustive),
(iv)
to
develop, to qualify, and to apply codes showing their capabilities at
different scales. The first item recalls a typical approach based
on a theorem (applied also to solve heat transfer problems) for determining the
number of independent nondimensional groups needed to describe a phenomenon. It
stated that a physical relationship among n variables, which can be
expressed in a minimum of m dimensions, can be rearranged into a
relationship among (
n
−
m
) independent dimensionless groups of the
original variables. Buckingham called the dimensionless groups pi-groups and
identified them as Π
1
,
Π
2
,
Π
3
,
…
,
Π
n
−
m.
Thus a dimensional functional equation reduces to a dimensionless functional
equation of the form
(1)
Π
1
=
f
(
Π
2
,
Π
3
,
…
,
Π
n
−
m
)
. The second item implies the definition of
non-dimensional parameters derived from relationships that link in an empirical
way some dependency, for example, from consideration of experimental evidence.
Again dimensionless groups are defined similar to the pi-groups. It should be
reminded that the relationships defined in this approach are valid for a
restricted range thus also the dimensionless parameters are affected by this
limitation.Performing experiment at different scale (third
item) might be a way to solve the scaling problem but firstly a lot of
experiments should be conducted to cope with the wide range of the scaling
factor, secondly the experimental results are affected by peculiarity related
to the typical dimension of a test rig at a certain scale.The last proposal to solve the scaling problem
(fourth item) is to accept all the limitation remarked above, to develop a
system code, to qualify it against experimental data, to prove that its
accuracy is scale independent, and to apply such code to predict the same
relevant phenomena that are expected to find in a same experiment (or
transient) performed at different scale.


#### 4.3.2. Best-Estimate Plus Uncertainty Analysis

In the past, large
uncertainties in the computer models used for nuclear power system design and
licensing have been compensated using highly conservative assumptions. The loss-of-coolant-accident
(LOCA) evaluation model is one of the main examples about this approach. Conservative analysis was introduced to cover
uncertainties at the level of knowledge in the 1970s and it is based on the variation of key components of the safety
analysis (computer code, availability
of components and systems, and initial and boundary conditions) in a way leading to pessimistic results relative to
specified acceptance criteria. However, the results obtained by this
approach may be misleading (e.g., unrealistic behavior may be predicted or
order of events may be changed) and this typically leads to unphysical
results. In addition, significant
economic penalties, not necessarily commensurate to the safety benefits, may
result as consequence of the unknown level of used conservatism.
As a conclusion, the use
of this approach is not longer recommended
(e.g., in [23], however it is still mandatory in the USA for methodologies referencing
the Appendix K of US NRC 10 Code of Federal Regulations 50 (10 CFR 50) [24]) and
today the application of “realistic” code methods rather than “conservative”
approaches can be identified.By definition, a best estimate (BE) analysis (the
term “best estimate” is usually used as a substitute
for “realistic”) is an accident analysis which is free of deliberate
pessimism regarding selected acceptance criteria, and is characterized by
applying best estimate codes along with nominal plant data and with best estimate
initial and boundary conditions. However, notwithstanding the important
achievements and progress made in recent years, the predictions of the best
estimate system codes are not exact but remain uncertain because [7] of the
following.(i)
The assessment process depends upon data almost
always measured in small scale facilities and not in the full power reactors.
(ii)
The models and the solution methods in the
codes are approximate: in some cases, fundamental laws of the physics are not
considered.
Consequently, the
results of the code calculations may not be applicable to give exact
information on the behavior of a NPP during postulated accident scenarios.
Therefore, best estimate predictions of NPP scenarios must be supplemented by
proper uncertainty evaluations in order to be meaningful. The term “best estimate plus uncertainty” (BEPU) was
coined for indicating an accident analysis which(1)
is free of deliberate pessimism regarding
selected acceptance criteria,
(2)
uses a BE code, and
(3)
includes uncertainty analysis.
Thus the word “uncertainty” and
the need for uncertainty evaluation are strictly connected with the use of BE
codes and, at least, the following three main reasons for the use
of uncertainty analysis can be identified.(i)
Licensing and safety: if calculations are performed in best
estimate fashion with quantification of uncertainties, a “relaxation” of
licensing rules is possible and a more realistic estimates of NPPs’ safety
margins can be obtained.
(ii)
Accident management: the estimate of code uncertainties may also
have potential for improvements in emergency response guidelines.
(iii)
Research prioritization: the uncertainty analysis can help to identify
correlation and code models that need the most improvement (code development
and validation become more cost effective); it also shows what kind of
experimental tests are most needed.
Development of the BEPU approach has spanned
nearly the last three decades. The international project on the evaluation of
various BEPU methods—uncertainty
methods study (UMS)—conducted under
the administration of the OECD/NEA [7] during 1995–1998 already
concluded that the methods are suitable for use under different circumstances
and uncertainty analysis is needed if useful conclusions are to be obtained
from best estimate codes. Similar international projects are in progress under
the administration of OECD/NEA (BEMUSE—best estimate methods uncertainty and sensitivity
evaluation [25]) and IAEA (Coordinated Research Project on investigation of uncertainties
in best estimate accident analyses) to evaluate the practicability, quality,
and reliability of BEPU methods.Notwithstanding the above
considerations, it is necessary to note that the selection of a BEPU analysis
in place of a conservative one depends upon a number of conditions that are
away from the analysis itself. These include the available computational tools,
the expertise inside the organization, the availability of suitable NPP data
(e.g., the amount of data and the related details can be much different in the
cases of best estimate or conservative analyses), or the requests from the
national regulatory body (e.g., in US licensing process, the BEPU approach was formulated as an
alternative to Appendix K conservative approach defined in [24] to reflect the
improved understanding of Emergency Core Cooling System (ECCS) performance obtained
through the extensive research [1, 26]).
In addition, conservative analyses are still widely used to avoid the need of
developing realistic models based on experimental data or simply to avoid the
burden to change approved code and/or the approaches or procedures to get the
licensing.


#### 4.3.3. Three-Dimensional Coupled Code Analysis

The advent of increased computing power with the present
available computer systems is making possible the coupling of large codes that
have been developed to meet specific needs such as three-dimensional neutronics
calculations for partial anticipated transients without scram (ATWS), with
computational fluid dynamics codes, and to study mixing in three-dimensions (particularly
for passive emergency core cooling systems) and with other computational tools.
The range of software packages that are desirable to couple with advanced
thermal-hydraulics systems analysis codes includes(i)
multidimensional neutronics,
(ii)
multidimensional computational fluid dynamics (CFD),
(iii)
containment,
(iv)
structural mechanics,
(v)
fuel behavior, and
(vi)
radioactivity  transport.
There are many
techniques for coupling advanced codes. In essence, the coupling may be either
loose (meaning the two or more codes only communicate after a number of time
steps) or tight such that the codes update one another time step to time step. Whether a loose coupling or a tight coupling is required is dependent on the phenomena that are being modeled and analyzed. For example, the need to consider heat transferred between the
primary fluid and the secondary fluid during a relatively slow transient does
not require close coupling and thus the codes of interest do not have to
communicate time step by time step. In contrast, the behavior of fluid moving
through the core region, where a portion of the core is modeled in great detail
using a CFD code while the remainder of the core is modeled using a system
analysis code would require tight coupling if the two codes were linked—since dramatic
changes may occur during a NPP transient. Indeed, since CFD codes generally do
not have the capability to model general system behavior due to the exceedingly
large computer resource requirements, the only means to update a CFD analysis
of a somewhat rapid transient in an NPP core region is via close coupling with
a system analysis code used to model the NPP system. Thus the system analysis
code provides boundary conditions to the CFD code if such an analysis need is
identified.


### 4.4. The Structure of the 3D S.UN.COP

The
seminar is subdivided into three main parts, each one with a
program to be developed in one week. The changes between lectures, computer
work, and model discussion have shown to be useful at maintaining participant
interest at a high level. The duration of the individual sessions varied substantially
according to the complexity of the subjects and the training needs of the
participants.(i) The first week (titled “fundamental theoretical
aspects”) is fully dedicated to lectures describing the concepts of the
proposed methodologies. The following technical sessions (with more than 40
lectures) are presented covering the main topics hereafter listed.(a)
Session I: System codes: evaluation,
application, modeling, and scaling
(1)
Models and capabilities of system code models,
(2)
Development process of generic codes and developmental assessment,
(3)
Scaling of thermal-hydraulic phenomena,
(4)
Separate and integral test facility
matrices.
(5)
Session II: International standard problems
(1)
Lesson learned from OECD/CSNI ISP,
(2)
Characterization and Results from some ISP.
(c)
Session III: Best estimate in system code
applications and uncertainty evaluation
(1)
IAEA safety standards,
(2)
Origins of uncertainty,
(3)
Approaches to calculate uncertainty,
(4)
User effect,
(5)
Evaluation of safety margins using BEPU
methodologies,
(6)
International programs on uncertainty (UMS
[7] and BEMUSE [25]).
(d)
Session IV:
Qualification procedures
(1)
Qualifying, validating, and documenting
input,
(2)
The feature of UMAE methodology,
(3)
Description and use of nodalization qualification criteria for steady-state
and transient calculations,
(4)
Use of thresholds for the acceptability
of results for the reference case,
(5)
Qualitative
accuracy evaluation,
(6)
Quantitative accuracy evaluation by fast
Fourier transform based method (FFTBM).
(e)
Session V: Methods for sensitivity and uncertainty analysis
(1)
GRS statistical uncertainty methodology [27],
(2)
CIAU
method for uncertainty evaluation,
(3)
Adjoint
sensitivity analysis procedure (ASAP) and global adjoint sensitivity analysis procedure
(GASAP), procedures for sensitivity analysis [28, 29],
(4)
Comparison
of uncertainty methods with code scaling, applicability, and uncertainty (CSAU) evaluation methodology
[6].
(f)
Session VI: Relevant
topics in best estimate licensing approach
(1)
Best
estimate approach in the licensing process in several countries (e.g., Brazil,
Germany, US, etc.).
(g)
Session VII:
Industrial application of the best estimate plus uncertainty methodology
(1)
Westinghouse realistic large break LOCA
methodology [16],
(2)
AREVA realistic accident analysis methodology
[17],
(3)
GE technology for establishing and confirming uncertainties
[18],
(4)
Best estimate and uncertainty (BEAU) for CANDU
reactors [19],
(5)
UMAE/CIAU application to Angra-2
licensing calculation [20].(ii) The second week (titled “Practical
Applications and Hands-on Training”) is devoted to lectures on the practical
aspects of the proposed methodologies and to the hands-on training on numerical
codes like ATHLET, CATHARE, CATHENA, RELAP5 USNRC, RELAP5-3D, TRACE, PARCS,
RELAP/SCDAP, and IMPACT. The following technical sessions are presented
covering the main topics hereafter listed.(a)
Session I: Coupling methodologies
(1)
Cross-section generation: models and applications,
(2)
Coupling 3D neutron-kinetics/thermal-hydraulic codes (3D NK-TH),
(3)
Uncertainties in basic cross-section,
(4)
CIAU extension to 3D NK-TH.
(b)
Session II: Coupling code applications
(1)
PWR-BWR-WWER analysis,
(2)
BWR stability issue,
(3)
WWER containment modeling,
(4)
System boron transport, boron mixing and validation.
(c)
Session III: CIAU/UMAE applications
(1)
Key applications of CIAU methodology,
(2)
Example
of code results from application to ITF (LOFT, LOBI, BETHSY) and to a NPP (PWR-Type and WWER-Type),
(3)
“PSB Facility” counterpart test,
(4)
Bifurcation study with CIAU,
(5)
CIAU software.
(d)
Session IV: Computational Fluid Dynamics Codes
(1)
The role and the structure of the CFD
codes,
(2)
CFD simulation in nuclear application: needs
and applications.
Each
of the parallel hands-on trainings on
numerical codes consists of about 20 hours and covers the following main
topics:(3)
structure of specific codes,
(4)
numerical
methods,
(5)
description
of input decks,
(6)
description
of fundamental analytical problems,
(7)
analysis
and code hands-on training on fundamental problems (e.g., for RELAP5, fundamental
proposed problems deal with boiling channel, blow-down of a pressurized vessel,
and pressurizer behavior),
(8)
Example of code results from applications to
ITFs (LOFT, LOBI, BETHSY).
(iii)The third week (titled “Hands-on Training for Advanced Users
and Final Examination”) is
designed for advanced users addressing the user effect problem. The
participants are divided into groups of three and each group receives the
training from one teacher. The applications of the proposed methodologies
(UMAE, CIAU, etc.) are illustrated through the BETHSY ISP 27 (small break LOCA)
and LOFT L2–5 (large break LOCA) tests. Applications and exercises using
several tools (RELAP5, WinGraf, FFTBM, UBEP, CIAU, etc.) are considered. The
following main topics are covered:(1)
modalities
for developing (or modifying) the nodalization,
(2)
plant
accident and transient analyses,
(3)
examples
of code results from application to a NPP (PWR-Type and VVER-Type), and
(4)
Code
hands-on training through the application of system codes to ITFs (LOFT and
BETHSY).
A final examination on the lessons learned
during the seminar is designed and consists of three parts.(i)
Written
Part: questions
about the topics discussed during the seminar are proposed and assigned both to
each participant and to each group.
(ii)
Application Part: two
types of problems are proposed to the single participant and to the group,
respectively.
(1)
Detection of Simple Input Error:
Each participant
receives the experimental data of the selected transient, the correct RELAP5 nodalization
input deck, and the restart file of the wrong input deck containing one simple
input error. Each participant will identify the error.
(2)
Detection of Complex Input Error:
Each group receives
the experimental data of the selected transient, the correct RELAP5 nodalization
input deck, and the restart file of the wrong input deck containing one complex
input error. Each group will identify the error.
Evaluation
reports are submitted in a written form containing short notes about the reasons
for the differences between results of the reference calculation and results
from the “modified” nodalization. At least, one problem over two will be correctly
solved to obtain the certificate.
(iii)
Final
Discussion: each participant takes an oral examination discussing own
results (or results obtained by own group) with the examiners. General
questions related to lectures presented during the three-week seminar are asked
to the participants.
A
certificate of type “LA Code User Grade” (see Table 1) like the one depicted in
Figure 4 is released to participants that successfully solved the assigned
problems.Figure 4
3D S.UN.COP “LA Code User Grade” Certificate.


### 4.5. 3D S.UN.COP 2007 at Texas A&M University (Texas, USA)

The 3D
S.UN.COP 2007 was successfully held at the Texas A&M University (Texas,
USA) from January 22nd to February 9th with the attendance of 26 participants
coming from 12 countries and 17 different institutions (universities, vendors,
national laboratories, and regulatory bodies). About 30 scientists (from 11
countries and 19 different institutions) were involved in the organization of
the seminar, presenting theoretical
aspects of the proposed methodologies and holding the training and the final
examination. More details may be found in Table2.Table 2
3D S.UN.COP 2007.
Structure of 3D S.UN.COP 2007
Week
Content
# Part.
I-Fundamental
Theoretical Aspects
7 Technical Session—35 Lectures
19
II-Practical Applications and Hands-on Training—(lectures sessions)
3 Technical Session—15 Lectures
20
III-Practical Applications and Hands-on Training—(parallel code sessions of 20 hours)
RELAP5 USNRC and RELAP5-3D
5
TRACE
5
PARCS
5
CATHARE
3
CATHENA
2
IV-Hands-on Training for Advanced Users and Final Examination
24 hours hand-on trainings–2 days exam
4
Participants,
lectures, and code developers
Participants
Lectures and code developers
Institutions
Country
Names
Institutions, Country
COMENA
Algeria
N. Aksan
PSI, Switzerland
AECL
Canada
W. Ambrosini
UNIPI, Italy
Nuclear Safety Solution
T.
Bajs
FER, Croatia
NPIC
China
F.
D’Auria
UNIPI, Italy
University of Zagreb
Croatia
C.
Delfino
ISL, USA
EDF
France
I.
Dor
CEA France
FZK
Germany
T.
Downar
PURDUE, USA
ENEA
Italy
M.
Dzodzo
Westinghouse, USA
University of Pisa
A.
Del Nevo
UNIPI, Italy
PBMR
South Africa
C.
Frepoli
Westinghouse, USA
ESKOM
R.
Galetti
CNEN, Brazil
KEPRI
South Korea
J.
Gary
INL, USA
Technical University of Catalonia
Spain
H.
Glaeser
GRS, Germany
D.
Grgic
FER, Croatia
IBERINCO
Y.
Hassan
Texas A&M, USA
ROLLS-ROYCE
UK
C.
Heck
GE, USA
AREVA NP
USA
H.
Ikeda
TEPSYS, Japan
Texas A&M
R.
Landry
US NRC, USA
R.
Martin
AREVA, USA
J.
Mahaffy
PSU, USA
J. Misak
NRI, Czech Republic
A.
Petruzzi
UNIPI, Italy
D.
Pialla
CEA, France
N.
Popov
AECL, Canada
C.
Pretel
ETSEIB, Spain
F.
Reventos
ETSEIB, Spain
J.
Vedovi
GE, USA
S.
Volkan
PURDUE, USAAll the participants
achieved a basic capability to set up, run, and evaluate the results of a
thermal-hydraulic system code (e.g., RELAP5) through the application of the proposed qualitative and
quantitative accuracy evaluation procedures.At the end
of the seminar a questionnaire for the evaluation of the course was distributed
to the participants. All of them very positively evaluated the conduct of the
training as can be derived from Figure5.Design and conduct of the seminar training.
(a)
(b)
(c)
(d)


## 4.1. Background Information about 3D S.UN.COP Trainings

The 3D
S.UN.COP (Scaling, Uncertainty, and 3D coupled code calculations) training aims
to transfer competence, knowledge, and experience from recognized international
experts in the area of scaling, uncertainty, and 3D coupled code calculations
in nuclear reactor safety technology to analysts with a suitable background in
nuclear technology.The training
(http://dimnp.ing.unipi.it/3dsuncop) is open to research organizations,
companies, vendors, industry, academic institutions, regulatory authorities,
national laboratories, and so on. The seminar is in general subdivided into
three parts and participants may choose to attend a one-, two-, or three-week
course. The first week is dedicated to the background information including the
theoretical bases for the proposed methodologies; the second week is devoted to
the practical application of the methodologies and to the hands-on training on
numerical codes; the third week is dedicated to the user qualification problem
through the hands-on training for advanced user and includes a final exam. From
the point of view of the conduct of the training, the weeks are characterized
by lectures, code-expert teaching, and by hands-on-application. More than
thirty scientists are in general involved in the organization of the seminars,
presenting theoretical aspects of the proposed methodologies and holding the
training and the final examination. A certificate of qualified code user is
released to participants that successfully solve the assigned problems during
the exams.The
framework in which the 3D S.UN.COP seminars have been designed may be derived
from
Figure2, where the roles of two main international institutions (OECD and
IAEA) and of the US NRC (here playing the role of any other regulatory body of
other countries) to address the problem of user effect are outlined together
with the proposed programs and produced documents. Figure 3 depicts how the 3D
S.UN.COP ensures the nuclear technology maintenance and advancements through the qualification of personnel in
regulatory bodies, research activities, and industries by means of teaching by very well-known
scientists belonging to the same type of institutions.Figure 2
3D S.UN.COP framework to address the user effect problem.Figure 3
3D S.UN.COP Loop of benefits.Seven training courses
have been organized up to now and were successfully held at(i)
The University of Pisa (Pisa, Italy), 5–9 January 2004 (6
participants);
(ii)
The Pennsylvania State University (University
Park, PA, USA), 24–28 May 2004 (15
participants);
(iii)
The University of Pisa (Pisa, Italy), 14–18 June 2004 (11
participants);
(iv)
The University of Zagreb
(Zagreb, Croatia), 20 June–8 July 2005 (19
participants);
(v)
The Technical University of
Catalonia (Barcelona, Spain), 23 January–10 February 2006
(33 participants);
(vi)
The “Autoridad
Regulatoria Nuclear (ARN),” the “Comisión Nacional de Energía
Atómica (CNEA),” the “Nucleoelectrica Argentina S.A (NA-SA),”
and the “Universidad Argentina De la Empresa” (Buenos Aires,
Argentina), 2 October–14 October 2006
(37 participants); and
(vii)
The Texas A&M University
(College Station, Texas, USA), 22 January–9 February 2007
(26 participants).


## 4.2. Objectives and Features of the 3D S.UN.COP Seminar Trainings

The main objective of the seminar activity is the
training in safety analysis of analysts with a suitable background in nuclear
technology. The training is devoted to the promotion and use of international
guidance and to homogenize the approach to the use of computer codes for
accident analysis. The main objectives are(i)
to transfer knowledge and expertise in Uncertainty Methodologies,
Thermal-Hydraulics System Code, and 3D Coupled Code Applications;
(ii)
to diffuse the use of international guidance;
(iii)
to homogenize
the approach in the use of computer codes (like RELAP, TRACE, CATHARE, ATHLET,
CATHENA, PARC, RELAP/SCDAP, MELCOR, and IMPACT) for accident analysis;
(iv)
to disseminate
the use of standard procedures for qualifying thermal-hydraulic system code
calculation (e.g., through the application of the UMAE “uncertainty methodology
based on accuracy extrapolation" [15]);
(v)
to promote best estimate plus uncertainty
(BEPU) methodologies in thermal-hydraulic accident analysis through the
presentation of the current industrial applications [16–20] and
the description of the theoretical aspects of the deterministic and statistical
uncertainty methods as well as the method based upon the propagation of output
errors (called CIAU “code with the capability of internal assessment of uncertainty"
[21, 22]);
(vi)
to spread available
robust approaches based on BEPU methodology in licensing process;
(vii)
to address and reduce user effects;
and
(viii)
to realize a
meeting point for exchanges of ideas among the worlds of Academy, Research
Laboratories, Industry, Regulatory Authorities, and International Institutions.
The main
features of the seminar course are identified as follows.(i)
The practical use of a mix of different codes. The use of different code is
worthwhile to establish a common basis for code assessment and for the
acceptability of code results.
(ii)
The exam.
Exams were in the past courses (very) well accepted by code users. The
exam gives them the possibility to show their expertise and to demonstrate
the effort done during the course.
(iii)
The practical use of procedures for nodalization qualification. Standardized techniques for
developing and qualifying nodalization (i.e., input) can be directly
applied in the participants institutions.
(iv)
The practical use of procedures for accuracy quantification. The availability of
methodologies and tools for quantifying qualitatively and quantitatively
the accuracy (i.e., the discrepancy between experimental and calculated
data) constitutes a key point for the acceptability of the code results.
(v)
The “joining” between BE codes and uncertainty evaluation. The use of BEPU methodology
within the licensing process is worthwhile for predicting more “realistic”
results and for demonstrating the existence of larger safety margins.
(vi)
The large participation of very well-known international experts. The establishment, integrity,
and use of international guidance are promoted through lectures presented
by top-level scientists coming from different institutions and countries.


## 4.3. Scientific and Technological Areas Presented  at the 3D S.UN.COP

As the acronym 3D
S.UN.COP implies, the following three scientifically relevant areas for the
nuclear technology are addressed during the course.(1)
Scaling analysis.
(2)
Best estimate plus uncertainty
analysis.
(3)
Three-dimensional coupled
code analysis.
Brief descriptions of
each topic are given hereafter.


### 4.3.1. Scaling Analysis

Scaling is a broad term used in nuclear reactor
technology, as well as in basic fluid dynamics, and in thermal hydraulics. In
general terms, scaling indicates the need for the process of transferring
information from a model to a prototype. The model and the prototype are
typically characterized by different geometric dimensions as well as adopted
materials, including working fluids, and different ranges of variation for thermal-hydraulic
quantities.Therefore, the word “scaling” may have different
meanings in different contexts. In system thermal hydraulics, a scaling
process, based upon suitable physical principles, aims at establishing a
correlation between (a) phenomena expected in a NPP transient scenario and
phenomena measured in smaller scale facilities or (b) phenomena predicted by numerical
tools qualified against experiments performed
in small scale facilities (in connection with this point, owing to limitations
of the fundamental equations at the basis of system codes, the scaling issue
may constitute an important source of uncertainties in code applications and
may envelop various “individual” uncertainties).Three main objectives can be associated to the
scaling analysis:(i)
the design
of a test facility,
(ii)
the code
validation, that is, the demonstration that the code accuracy is scale
independent,
(iii)
the
extrapolation of experimental data (obtained into an ITF) to predict the
NPP behavior. In order to address the scaling issue,
different approaches have been historically followed:(i)
fluid
balance equation, deriving nondimensional parameters adopting the
Buckingham theorem,
(ii)
semi-empirical
mechanistic equations, deriving non-dimensional parameters,
(iii)
to perform
experiments at different scales (very expensive way and could not be
totally exhaustive),
(iv)
to
develop, to qualify, and to apply codes showing their capabilities at
different scales. The first item recalls a typical approach based
on a theorem (applied also to solve heat transfer problems) for determining the
number of independent nondimensional groups needed to describe a phenomenon. It
stated that a physical relationship among n variables, which can be
expressed in a minimum of m dimensions, can be rearranged into a
relationship among (
n
−
m
) independent dimensionless groups of the
original variables. Buckingham called the dimensionless groups pi-groups and
identified them as Π
1
,
Π
2
,
Π
3
,
…
,
Π
n
−
m.
Thus a dimensional functional equation reduces to a dimensionless functional
equation of the form
(1)
Π
1
=
f
(
Π
2
,
Π
3
,
…
,
Π
n
−
m
)
. The second item implies the definition of
non-dimensional parameters derived from relationships that link in an empirical
way some dependency, for example, from consideration of experimental evidence.
Again dimensionless groups are defined similar to the pi-groups. It should be
reminded that the relationships defined in this approach are valid for a
restricted range thus also the dimensionless parameters are affected by this
limitation.Performing experiment at different scale (third
item) might be a way to solve the scaling problem but firstly a lot of
experiments should be conducted to cope with the wide range of the scaling
factor, secondly the experimental results are affected by peculiarity related
to the typical dimension of a test rig at a certain scale.The last proposal to solve the scaling problem
(fourth item) is to accept all the limitation remarked above, to develop a
system code, to qualify it against experimental data, to prove that its
accuracy is scale independent, and to apply such code to predict the same
relevant phenomena that are expected to find in a same experiment (or
transient) performed at different scale.


### 4.3.2. Best-Estimate Plus Uncertainty Analysis

In the past, large
uncertainties in the computer models used for nuclear power system design and
licensing have been compensated using highly conservative assumptions. The loss-of-coolant-accident
(LOCA) evaluation model is one of the main examples about this approach. Conservative analysis was introduced to cover
uncertainties at the level of knowledge in the 1970s and it is based on the variation of key components of the safety
analysis (computer code, availability
of components and systems, and initial and boundary conditions) in a way leading to pessimistic results relative to
specified acceptance criteria. However, the results obtained by this
approach may be misleading (e.g., unrealistic behavior may be predicted or
order of events may be changed) and this typically leads to unphysical
results. In addition, significant
economic penalties, not necessarily commensurate to the safety benefits, may
result as consequence of the unknown level of used conservatism.
As a conclusion, the use
of this approach is not longer recommended
(e.g., in [23], however it is still mandatory in the USA for methodologies referencing
the Appendix K of US NRC 10 Code of Federal Regulations 50 (10 CFR 50) [24]) and
today the application of “realistic” code methods rather than “conservative”
approaches can be identified.By definition, a best estimate (BE) analysis (the
term “best estimate” is usually used as a substitute
for “realistic”) is an accident analysis which is free of deliberate
pessimism regarding selected acceptance criteria, and is characterized by
applying best estimate codes along with nominal plant data and with best estimate
initial and boundary conditions. However, notwithstanding the important
achievements and progress made in recent years, the predictions of the best
estimate system codes are not exact but remain uncertain because [7] of the
following.(i)
The assessment process depends upon data almost
always measured in small scale facilities and not in the full power reactors.
(ii)
The models and the solution methods in the
codes are approximate: in some cases, fundamental laws of the physics are not
considered.
Consequently, the
results of the code calculations may not be applicable to give exact
information on the behavior of a NPP during postulated accident scenarios.
Therefore, best estimate predictions of NPP scenarios must be supplemented by
proper uncertainty evaluations in order to be meaningful. The term “best estimate plus uncertainty” (BEPU) was
coined for indicating an accident analysis which(1)
is free of deliberate pessimism regarding
selected acceptance criteria,
(2)
uses a BE code, and
(3)
includes uncertainty analysis.
Thus the word “uncertainty” and
the need for uncertainty evaluation are strictly connected with the use of BE
codes and, at least, the following three main reasons for the use
of uncertainty analysis can be identified.(i)
Licensing and safety: if calculations are performed in best
estimate fashion with quantification of uncertainties, a “relaxation” of
licensing rules is possible and a more realistic estimates of NPPs’ safety
margins can be obtained.
(ii)
Accident management: the estimate of code uncertainties may also
have potential for improvements in emergency response guidelines.
(iii)
Research prioritization: the uncertainty analysis can help to identify
correlation and code models that need the most improvement (code development
and validation become more cost effective); it also shows what kind of
experimental tests are most needed.
Development of the BEPU approach has spanned
nearly the last three decades. The international project on the evaluation of
various BEPU methods—uncertainty
methods study (UMS)—conducted under
the administration of the OECD/NEA [7] during 1995–1998 already
concluded that the methods are suitable for use under different circumstances
and uncertainty analysis is needed if useful conclusions are to be obtained
from best estimate codes. Similar international projects are in progress under
the administration of OECD/NEA (BEMUSE—best estimate methods uncertainty and sensitivity
evaluation [25]) and IAEA (Coordinated Research Project on investigation of uncertainties
in best estimate accident analyses) to evaluate the practicability, quality,
and reliability of BEPU methods.Notwithstanding the above
considerations, it is necessary to note that the selection of a BEPU analysis
in place of a conservative one depends upon a number of conditions that are
away from the analysis itself. These include the available computational tools,
the expertise inside the organization, the availability of suitable NPP data
(e.g., the amount of data and the related details can be much different in the
cases of best estimate or conservative analyses), or the requests from the
national regulatory body (e.g., in US licensing process, the BEPU approach was formulated as an
alternative to Appendix K conservative approach defined in [24] to reflect the
improved understanding of Emergency Core Cooling System (ECCS) performance obtained
through the extensive research [1, 26]).
In addition, conservative analyses are still widely used to avoid the need of
developing realistic models based on experimental data or simply to avoid the
burden to change approved code and/or the approaches or procedures to get the
licensing.


### 4.3.3. Three-Dimensional Coupled Code Analysis

The advent of increased computing power with the present
available computer systems is making possible the coupling of large codes that
have been developed to meet specific needs such as three-dimensional neutronics
calculations for partial anticipated transients without scram (ATWS), with
computational fluid dynamics codes, and to study mixing in three-dimensions (particularly
for passive emergency core cooling systems) and with other computational tools.
The range of software packages that are desirable to couple with advanced
thermal-hydraulics systems analysis codes includes(i)
multidimensional neutronics,
(ii)
multidimensional computational fluid dynamics (CFD),
(iii)
containment,
(iv)
structural mechanics,
(v)
fuel behavior, and
(vi)
radioactivity  transport.
There are many
techniques for coupling advanced codes. In essence, the coupling may be either
loose (meaning the two or more codes only communicate after a number of time
steps) or tight such that the codes update one another time step to time step. Whether a loose coupling or a tight coupling is required is dependent on the phenomena that are being modeled and analyzed. For example, the need to consider heat transferred between the
primary fluid and the secondary fluid during a relatively slow transient does
not require close coupling and thus the codes of interest do not have to
communicate time step by time step. In contrast, the behavior of fluid moving
through the core region, where a portion of the core is modeled in great detail
using a CFD code while the remainder of the core is modeled using a system
analysis code would require tight coupling if the two codes were linked—since dramatic
changes may occur during a NPP transient. Indeed, since CFD codes generally do
not have the capability to model general system behavior due to the exceedingly
large computer resource requirements, the only means to update a CFD analysis
of a somewhat rapid transient in an NPP core region is via close coupling with
a system analysis code used to model the NPP system. Thus the system analysis
code provides boundary conditions to the CFD code if such an analysis need is
identified.


## 4.3.1. Scaling Analysis

Scaling is a broad term used in nuclear reactor
technology, as well as in basic fluid dynamics, and in thermal hydraulics. In
general terms, scaling indicates the need for the process of transferring
information from a model to a prototype. The model and the prototype are
typically characterized by different geometric dimensions as well as adopted
materials, including working fluids, and different ranges of variation for thermal-hydraulic
quantities.Therefore, the word “scaling” may have different
meanings in different contexts. In system thermal hydraulics, a scaling
process, based upon suitable physical principles, aims at establishing a
correlation between (a) phenomena expected in a NPP transient scenario and
phenomena measured in smaller scale facilities or (b) phenomena predicted by numerical
tools qualified against experiments performed
in small scale facilities (in connection with this point, owing to limitations
of the fundamental equations at the basis of system codes, the scaling issue
may constitute an important source of uncertainties in code applications and
may envelop various “individual” uncertainties).Three main objectives can be associated to the
scaling analysis:(i)
the design
of a test facility,
(ii)
the code
validation, that is, the demonstration that the code accuracy is scale
independent,
(iii)
the
extrapolation of experimental data (obtained into an ITF) to predict the
NPP behavior. In order to address the scaling issue,
different approaches have been historically followed:(i)
fluid
balance equation, deriving nondimensional parameters adopting the
Buckingham theorem,
(ii)
semi-empirical
mechanistic equations, deriving non-dimensional parameters,
(iii)
to perform
experiments at different scales (very expensive way and could not be
totally exhaustive),
(iv)
to
develop, to qualify, and to apply codes showing their capabilities at
different scales. The first item recalls a typical approach based
on a theorem (applied also to solve heat transfer problems) for determining the
number of independent nondimensional groups needed to describe a phenomenon. It
stated that a physical relationship among n variables, which can be
expressed in a minimum of m dimensions, can be rearranged into a
relationship among (
n
−
m
) independent dimensionless groups of the
original variables. Buckingham called the dimensionless groups pi-groups and
identified them as Π
1
,
Π
2
,
Π
3
,
…
,
Π
n
−
m.
Thus a dimensional functional equation reduces to a dimensionless functional
equation of the form
(1)
Π
1
=
f
(
Π
2
,
Π
3
,
…
,
Π
n
−
m
)
. The second item implies the definition of
non-dimensional parameters derived from relationships that link in an empirical
way some dependency, for example, from consideration of experimental evidence.
Again dimensionless groups are defined similar to the pi-groups. It should be
reminded that the relationships defined in this approach are valid for a
restricted range thus also the dimensionless parameters are affected by this
limitation.Performing experiment at different scale (third
item) might be a way to solve the scaling problem but firstly a lot of
experiments should be conducted to cope with the wide range of the scaling
factor, secondly the experimental results are affected by peculiarity related
to the typical dimension of a test rig at a certain scale.The last proposal to solve the scaling problem
(fourth item) is to accept all the limitation remarked above, to develop a
system code, to qualify it against experimental data, to prove that its
accuracy is scale independent, and to apply such code to predict the same
relevant phenomena that are expected to find in a same experiment (or
transient) performed at different scale.


## 4.3.2. Best-Estimate Plus Uncertainty Analysis

In the past, large
uncertainties in the computer models used for nuclear power system design and
licensing have been compensated using highly conservative assumptions. The loss-of-coolant-accident
(LOCA) evaluation model is one of the main examples about this approach. Conservative analysis was introduced to cover
uncertainties at the level of knowledge in the 1970s and it is based on the variation of key components of the safety
analysis (computer code, availability
of components and systems, and initial and boundary conditions) in a way leading to pessimistic results relative to
specified acceptance criteria. However, the results obtained by this
approach may be misleading (e.g., unrealistic behavior may be predicted or
order of events may be changed) and this typically leads to unphysical
results. In addition, significant
economic penalties, not necessarily commensurate to the safety benefits, may
result as consequence of the unknown level of used conservatism.
As a conclusion, the use
of this approach is not longer recommended
(e.g., in [23], however it is still mandatory in the USA for methodologies referencing
the Appendix K of US NRC 10 Code of Federal Regulations 50 (10 CFR 50) [24]) and
today the application of “realistic” code methods rather than “conservative”
approaches can be identified.By definition, a best estimate (BE) analysis (the
term “best estimate” is usually used as a substitute
for “realistic”) is an accident analysis which is free of deliberate
pessimism regarding selected acceptance criteria, and is characterized by
applying best estimate codes along with nominal plant data and with best estimate
initial and boundary conditions. However, notwithstanding the important
achievements and progress made in recent years, the predictions of the best
estimate system codes are not exact but remain uncertain because [7] of the
following.(i)
The assessment process depends upon data almost
always measured in small scale facilities and not in the full power reactors.
(ii)
The models and the solution methods in the
codes are approximate: in some cases, fundamental laws of the physics are not
considered.
Consequently, the
results of the code calculations may not be applicable to give exact
information on the behavior of a NPP during postulated accident scenarios.
Therefore, best estimate predictions of NPP scenarios must be supplemented by
proper uncertainty evaluations in order to be meaningful. The term “best estimate plus uncertainty” (BEPU) was
coined for indicating an accident analysis which(1)
is free of deliberate pessimism regarding
selected acceptance criteria,
(2)
uses a BE code, and
(3)
includes uncertainty analysis.
Thus the word “uncertainty” and
the need for uncertainty evaluation are strictly connected with the use of BE
codes and, at least, the following three main reasons for the use
of uncertainty analysis can be identified.(i)
Licensing and safety: if calculations are performed in best
estimate fashion with quantification of uncertainties, a “relaxation” of
licensing rules is possible and a more realistic estimates of NPPs’ safety
margins can be obtained.
(ii)
Accident management: the estimate of code uncertainties may also
have potential for improvements in emergency response guidelines.
(iii)
Research prioritization: the uncertainty analysis can help to identify
correlation and code models that need the most improvement (code development
and validation become more cost effective); it also shows what kind of
experimental tests are most needed.
Development of the BEPU approach has spanned
nearly the last three decades. The international project on the evaluation of
various BEPU methods—uncertainty
methods study (UMS)—conducted under
the administration of the OECD/NEA [7] during 1995–1998 already
concluded that the methods are suitable for use under different circumstances
and uncertainty analysis is needed if useful conclusions are to be obtained
from best estimate codes. Similar international projects are in progress under
the administration of OECD/NEA (BEMUSE—best estimate methods uncertainty and sensitivity
evaluation [25]) and IAEA (Coordinated Research Project on investigation of uncertainties
in best estimate accident analyses) to evaluate the practicability, quality,
and reliability of BEPU methods.Notwithstanding the above
considerations, it is necessary to note that the selection of a BEPU analysis
in place of a conservative one depends upon a number of conditions that are
away from the analysis itself. These include the available computational tools,
the expertise inside the organization, the availability of suitable NPP data
(e.g., the amount of data and the related details can be much different in the
cases of best estimate or conservative analyses), or the requests from the
national regulatory body (e.g., in US licensing process, the BEPU approach was formulated as an
alternative to Appendix K conservative approach defined in [24] to reflect the
improved understanding of Emergency Core Cooling System (ECCS) performance obtained
through the extensive research [1, 26]).
In addition, conservative analyses are still widely used to avoid the need of
developing realistic models based on experimental data or simply to avoid the
burden to change approved code and/or the approaches or procedures to get the
licensing.


## 4.3.3. Three-Dimensional Coupled Code Analysis

The advent of increased computing power with the present
available computer systems is making possible the coupling of large codes that
have been developed to meet specific needs such as three-dimensional neutronics
calculations for partial anticipated transients without scram (ATWS), with
computational fluid dynamics codes, and to study mixing in three-dimensions (particularly
for passive emergency core cooling systems) and with other computational tools.
The range of software packages that are desirable to couple with advanced
thermal-hydraulics systems analysis codes includes(i)
multidimensional neutronics,
(ii)
multidimensional computational fluid dynamics (CFD),
(iii)
containment,
(iv)
structural mechanics,
(v)
fuel behavior, and
(vi)
radioactivity  transport.
There are many
techniques for coupling advanced codes. In essence, the coupling may be either
loose (meaning the two or more codes only communicate after a number of time
steps) or tight such that the codes update one another time step to time step. Whether a loose coupling or a tight coupling is required is dependent on the phenomena that are being modeled and analyzed. For example, the need to consider heat transferred between the
primary fluid and the secondary fluid during a relatively slow transient does
not require close coupling and thus the codes of interest do not have to
communicate time step by time step. In contrast, the behavior of fluid moving
through the core region, where a portion of the core is modeled in great detail
using a CFD code while the remainder of the core is modeled using a system
analysis code would require tight coupling if the two codes were linked—since dramatic
changes may occur during a NPP transient. Indeed, since CFD codes generally do
not have the capability to model general system behavior due to the exceedingly
large computer resource requirements, the only means to update a CFD analysis
of a somewhat rapid transient in an NPP core region is via close coupling with
a system analysis code used to model the NPP system. Thus the system analysis
code provides boundary conditions to the CFD code if such an analysis need is
identified.


## 4.4. The Structure of the 3D S.UN.COP

The
seminar is subdivided into three main parts, each one with a
program to be developed in one week. The changes between lectures, computer
work, and model discussion have shown to be useful at maintaining participant
interest at a high level. The duration of the individual sessions varied substantially
according to the complexity of the subjects and the training needs of the
participants.(i) The first week (titled “fundamental theoretical
aspects”) is fully dedicated to lectures describing the concepts of the
proposed methodologies. The following technical sessions (with more than 40
lectures) are presented covering the main topics hereafter listed.(a)
Session I: System codes: evaluation,
application, modeling, and scaling
(1)
Models and capabilities of system code models,
(2)
Development process of generic codes and developmental assessment,
(3)
Scaling of thermal-hydraulic phenomena,
(4)
Separate and integral test facility
matrices.
(5)
Session II: International standard problems
(1)
Lesson learned from OECD/CSNI ISP,
(2)
Characterization and Results from some ISP.
(c)
Session III: Best estimate in system code
applications and uncertainty evaluation
(1)
IAEA safety standards,
(2)
Origins of uncertainty,
(3)
Approaches to calculate uncertainty,
(4)
User effect,
(5)
Evaluation of safety margins using BEPU
methodologies,
(6)
International programs on uncertainty (UMS
[7] and BEMUSE [25]).
(d)
Session IV:
Qualification procedures
(1)
Qualifying, validating, and documenting
input,
(2)
The feature of UMAE methodology,
(3)
Description and use of nodalization qualification criteria for steady-state
and transient calculations,
(4)
Use of thresholds for the acceptability
of results for the reference case,
(5)
Qualitative
accuracy evaluation,
(6)
Quantitative accuracy evaluation by fast
Fourier transform based method (FFTBM).
(e)
Session V: Methods for sensitivity and uncertainty analysis
(1)
GRS statistical uncertainty methodology [27],
(2)
CIAU
method for uncertainty evaluation,
(3)
Adjoint
sensitivity analysis procedure (ASAP) and global adjoint sensitivity analysis procedure
(GASAP), procedures for sensitivity analysis [28, 29],
(4)
Comparison
of uncertainty methods with code scaling, applicability, and uncertainty (CSAU) evaluation methodology
[6].
(f)
Session VI: Relevant
topics in best estimate licensing approach
(1)
Best
estimate approach in the licensing process in several countries (e.g., Brazil,
Germany, US, etc.).
(g)
Session VII:
Industrial application of the best estimate plus uncertainty methodology
(1)
Westinghouse realistic large break LOCA
methodology [16],
(2)
AREVA realistic accident analysis methodology
[17],
(3)
GE technology for establishing and confirming uncertainties
[18],
(4)
Best estimate and uncertainty (BEAU) for CANDU
reactors [19],
(5)
UMAE/CIAU application to Angra-2
licensing calculation [20].(ii) The second week (titled “Practical
Applications and Hands-on Training”) is devoted to lectures on the practical
aspects of the proposed methodologies and to the hands-on training on numerical
codes like ATHLET, CATHARE, CATHENA, RELAP5 USNRC, RELAP5-3D, TRACE, PARCS,
RELAP/SCDAP, and IMPACT. The following technical sessions are presented
covering the main topics hereafter listed.(a)
Session I: Coupling methodologies
(1)
Cross-section generation: models and applications,
(2)
Coupling 3D neutron-kinetics/thermal-hydraulic codes (3D NK-TH),
(3)
Uncertainties in basic cross-section,
(4)
CIAU extension to 3D NK-TH.
(b)
Session II: Coupling code applications
(1)
PWR-BWR-WWER analysis,
(2)
BWR stability issue,
(3)
WWER containment modeling,
(4)
System boron transport, boron mixing and validation.
(c)
Session III: CIAU/UMAE applications
(1)
Key applications of CIAU methodology,
(2)
Example
of code results from application to ITF (LOFT, LOBI, BETHSY) and to a NPP (PWR-Type and WWER-Type),
(3)
“PSB Facility” counterpart test,
(4)
Bifurcation study with CIAU,
(5)
CIAU software.
(d)
Session IV: Computational Fluid Dynamics Codes
(1)
The role and the structure of the CFD
codes,
(2)
CFD simulation in nuclear application: needs
and applications.
Each
of the parallel hands-on trainings on
numerical codes consists of about 20 hours and covers the following main
topics:(3)
structure of specific codes,
(4)
numerical
methods,
(5)
description
of input decks,
(6)
description
of fundamental analytical problems,
(7)
analysis
and code hands-on training on fundamental problems (e.g., for RELAP5, fundamental
proposed problems deal with boiling channel, blow-down of a pressurized vessel,
and pressurizer behavior),
(8)
Example of code results from applications to
ITFs (LOFT, LOBI, BETHSY).
(iii)The third week (titled “Hands-on Training for Advanced Users
and Final Examination”) is
designed for advanced users addressing the user effect problem. The
participants are divided into groups of three and each group receives the
training from one teacher. The applications of the proposed methodologies
(UMAE, CIAU, etc.) are illustrated through the BETHSY ISP 27 (small break LOCA)
and LOFT L2–5 (large break LOCA) tests. Applications and exercises using
several tools (RELAP5, WinGraf, FFTBM, UBEP, CIAU, etc.) are considered. The
following main topics are covered:(1)
modalities
for developing (or modifying) the nodalization,
(2)
plant
accident and transient analyses,
(3)
examples
of code results from application to a NPP (PWR-Type and VVER-Type), and
(4)
Code
hands-on training through the application of system codes to ITFs (LOFT and
BETHSY).
A final examination on the lessons learned
during the seminar is designed and consists of three parts.(i)
Written
Part: questions
about the topics discussed during the seminar are proposed and assigned both to
each participant and to each group.
(ii)
Application Part: two
types of problems are proposed to the single participant and to the group,
respectively.
(1)
Detection of Simple Input Error:
Each participant
receives the experimental data of the selected transient, the correct RELAP5 nodalization
input deck, and the restart file of the wrong input deck containing one simple
input error. Each participant will identify the error.
(2)
Detection of Complex Input Error:
Each group receives
the experimental data of the selected transient, the correct RELAP5 nodalization
input deck, and the restart file of the wrong input deck containing one complex
input error. Each group will identify the error.
Evaluation
reports are submitted in a written form containing short notes about the reasons
for the differences between results of the reference calculation and results
from the “modified” nodalization. At least, one problem over two will be correctly
solved to obtain the certificate.
(iii)
Final
Discussion: each participant takes an oral examination discussing own
results (or results obtained by own group) with the examiners. General
questions related to lectures presented during the three-week seminar are asked
to the participants.
A
certificate of type “LA Code User Grade” (see Table 1) like the one depicted in
Figure 4 is released to participants that successfully solved the assigned
problems.Figure 4
3D S.UN.COP “LA Code User Grade” Certificate.


## 4.5. 3D S.UN.COP 2007 at Texas A&M University (Texas, USA)

The 3D
S.UN.COP 2007 was successfully held at the Texas A&M University (Texas,
USA) from January 22nd to February 9th with the attendance of 26 participants
coming from 12 countries and 17 different institutions (universities, vendors,
national laboratories, and regulatory bodies). About 30 scientists (from 11
countries and 19 different institutions) were involved in the organization of
the seminar, presenting theoretical
aspects of the proposed methodologies and holding the training and the final
examination. More details may be found in Table2.Table 2
3D S.UN.COP 2007.
Structure of 3D S.UN.COP 2007
Week
Content
# Part.
I-Fundamental
Theoretical Aspects
7 Technical Session—35 Lectures
19
II-Practical Applications and Hands-on Training—(lectures sessions)
3 Technical Session—15 Lectures
20
III-Practical Applications and Hands-on Training—(parallel code sessions of 20 hours)
RELAP5 USNRC and RELAP5-3D
5
TRACE
5
PARCS
5
CATHARE
3
CATHENA
2
IV-Hands-on Training for Advanced Users and Final Examination
24 hours hand-on trainings–2 days exam
4
Participants,
lectures, and code developers
Participants
Lectures and code developers
Institutions
Country
Names
Institutions, Country
COMENA
Algeria
N. Aksan
PSI, Switzerland
AECL
Canada
W. Ambrosini
UNIPI, Italy
Nuclear Safety Solution
T.
Bajs
FER, Croatia
NPIC
China
F.
D’Auria
UNIPI, Italy
University of Zagreb
Croatia
C.
Delfino
ISL, USA
EDF
France
I.
Dor
CEA France
FZK
Germany
T.
Downar
PURDUE, USA
ENEA
Italy
M.
Dzodzo
Westinghouse, USA
University of Pisa
A.
Del Nevo
UNIPI, Italy
PBMR
South Africa
C.
Frepoli
Westinghouse, USA
ESKOM
R.
Galetti
CNEN, Brazil
KEPRI
South Korea
J.
Gary
INL, USA
Technical University of Catalonia
Spain
H.
Glaeser
GRS, Germany
D.
Grgic
FER, Croatia
IBERINCO
Y.
Hassan
Texas A&M, USA
ROLLS-ROYCE
UK
C.
Heck
GE, USA
AREVA NP
USA
H.
Ikeda
TEPSYS, Japan
Texas A&M
R.
Landry
US NRC, USA
R.
Martin
AREVA, USA
J.
Mahaffy
PSU, USA
J. Misak
NRI, Czech Republic
A.
Petruzzi
UNIPI, Italy
D.
Pialla
CEA, France
N.
Popov
AECL, Canada
C.
Pretel
ETSEIB, Spain
F.
Reventos
ETSEIB, Spain
J.
Vedovi
GE, USA
S.
Volkan
PURDUE, USAAll the participants
achieved a basic capability to set up, run, and evaluate the results of a
thermal-hydraulic system code (e.g., RELAP5) through the application of the proposed qualitative and
quantitative accuracy evaluation procedures.At the end
of the seminar a questionnaire for the evaluation of the course was distributed
to the participants. All of them very positively evaluated the conduct of the
training as can be derived from Figure5.Design and conduct of the seminar training.
(a)
(b)
(c)
(d)


## 5. Conclusions

An effort is being made
to develop a proposal for a systematic approach to user training. The estimated
duration of training at the course venue, including a set of training seminars,
workshops, and practical exercises, is approximately two years. In addition,
the specification and assignment of tasks to be performed by the participants at
their home institutions, with continuous supervision from the training center, have
been foreseen.The 3D S.UN.COP seminars
training courses constitute the follow-up of the presented proposal. The
problem of the code-user effect along with the methodologies for performing the
scaling-, the BEPU-, and the 3D coupled-code-calculation-analyses are the main
topics discussed during the course. The responses of the participants during
the training demonstrated an increase in their capabilities to develop and/or
modify the nodalizations and to perform a qualitative and quantitative accuracy
evaluation. It is expected that the participants will be able to set up more
accurate, reliable, and efficient simulation models applying the procedures for
qualifying the thermal-hydraulic system code calculations and for the
evaluation of the uncertainty.



---

*Source: 874023-2008-04-13.xml*