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\section{ERRORR}
\label{sERRORR}
\index{ERRORR|textbf}
\hypertarget{sERRORRhy}{The}
ERRORR module is used to produce cross section and distribution
covariances from error files in ENDF format.
This chapter describes the ERRORR module in NJOY2016.0.
\subsection{Introduction}
\label{ssERRORR_Intro}
After evaluators have completed their review of the available
measurements of various nuclear data (having true values $\sigma_{1},
\sigma_{2}, \sigma_{3},\cdots$) and the theoretical analysis, they will
have formed at least a subjective opinion of the joint probability
distribution of the data examined; that is, the probability
\[ P(\sigma_{1},\sigma_{2},\cdots) \, d\sigma_{1}\, d\sigma_{2}\cdots\]
that the true value of $\sigma_1$ lies in the range $(\sigma_1,
\sigma_1 {+} d\sigma_1)$, and that $\sigma_2$ lies in the range
$(\sigma_2, \sigma_2 {+} d\sigma_2)$, etc. In the early versions
of the ENDF format, only the first moments (expectation values) of this
probability distribution could be included in the numerical data
files. However, beginning with ENDF/B-IV and expanding significantly
in ENDF/B-V and later, the second moments of the data
probability distributions have been included in many of the files.
As discussed in Section~\ref{ssERRORR_Defs}, these second moments
(or ``data covariances'')
contain information on the uncertainty of individual data, as well as
correlations that may exist. Fig.~\ref{b10cov} shows an example of
this for $^{10}$B from ENDF/B-VII.0. The top plot shows the first
moment (the percent standard deviation) of the uncertainty in the
(n,$\alpha$) cross section. The right-hand plot shows the cross
section. The center plot shows the correlations between the
(n,$\alpha$) cross section at one energy to itself at other energies.
\index{covariances}
\begin{figure}[thb]\centering
\includegraphics[keepaspectratio, width=5.0in,angle=0]{figs/b10covack}
\caption[ENDF/B-VII.0 $^{10}$B(n,$\alpha$) covariance data]{Covariance
plot for $^{10}$B(n,$\alpha$) from ENDF/B-VII.0. This reaction is used as
a standard in the ENDF system.}
\label{b10cov}
\end{figure}
Data covariances have many applications. For example, they can be
combined with sensitivity coefficients to obtain the uncertainty, due
to the data, in calculated quantities of applied interest\cite{Gerstl}.
This information can be used in turn to judge the adequacy of the data
for that application.
\index{sensitivity analysis}
The availability of data covariances also makes it possible to use the
generalized method of least squares to improve the data evaluation
after new integral or differential measurements have been
performed\cite{Reupke}. The least-squares method requires only data
covariances (not the full probability distribution), and the improved,
or adjusted, data are guaranteed\cite{Hamilton} to have the smallest
possible uncertainties, regardless of the actual shape of the underlying
probability distribution function, $P(\sigma_1, \sigma_2,\cdots)$.
\index{data adjustment}
Thus, the ENDF-formatted covariance files contain, in about as compact
a form as possible, a statement about the quality of the data, as well
as sufficient information (in principle) to carry out future
improvements on an objective basis.
In many of these applications, it is necessary to begin by converting
energy-dependent covariance information in ENDF format\cite{ENDF102}
into multigroup form. This task can be performed conveniently in the
NJOY environment, using the ERRORR module. In particular,
ERRORR calculates the uncertainty in infinitely dilute multigroup cross
sections (or multigroup $\bar{\nu}$ values), as well as the associated
correlation coefficients. These data are obtained by combining
absolute or relative covariances from ENDF Files 31, 32, 33, 34, 35 and 40
with multigroup $\bar{\nu}$ data, cross section data, angular disbribution
data, fission spectra data or radionuclide production data. These
multigroup data are obtained from \hyperlink{sGROUPRhy}{GROUPR}
processing, or in some instances are calculated
within ERRORR. ERRORR is coded to treat all approved ENDF-4, -5, and -6
covariance formats for these files. ERRORR can also treat
resolved-resonance covariances given in File 32 using the old
Breit-Wigner resolved-resonance parameter uncertainties (\cword{LRF}=1
and \cword{2}) in Version-5 format, the ``Version-5 compatible''
option of Version 6 (\cword{LCOMP}=0) using the new formats
that include resonance-resonance covariances, and the newest
format based on Reich-Moore-Limited parameters that include
resonance-resonance correlations between different reactions.
The methodology of ERRORR assumes that the weighting flux
\index{weighting flux} used to convert energy-dependent cross sections
into multigroup averages is free of uncertainty. In cases in which
the cross-section information is obtained from an existing multigroup
library, it is usually necessary to make assumptions about the shape
of the cross section and the weight function within certain input
energy groups.
\subsection{Definitions of Covariance-Related Quantities}
\label{ssERRORR_Defs}
For convenient reference in discussing the methodology and input
requirements of the ERRORR module, we next review the basic definitions
of covariance-related quantities. Let $x_{0}$ and $y_{0}$ be the
evaluated values of $x$ and $y$, respectively:
\begin{equation}
x_{0} \equiv {\rm E}[x] \; ,
\end{equation}
\noindent
and
\begin{equation}
y_0 \equiv {\rm E}[y] \; .
\end{equation}
\noindent
Here E is the expectation operator, which performs an average over the
joint probability distribution of $x$ and $y$. The second moment of
this distribution is called the covariance of $x $ with $y$:
\begin{equation}
{\rm cov} (x,y) \equiv {\rm E}[(x\;-\;x_0)\;(y\;-\;y_0)]\;.
\label{cov}
\end{equation}
\noindent
Covariance is a measure of the degree to which $x$ and $y$ are both
affected by the same sources of error. The covariance of $x$ with
itself is called the variance of $x$:
\begin{equation}
{\rm var}(x) \equiv {\rm cov}(x,x) = {\rm E}[(x\;-\;x_0)^2]\;.
\end{equation}
\noindent
The more familiar standard deviation $\Delta x$ (also called the
``uncertainty'') is simply
\begin{equation}
\Delta x \equiv [{\rm var} (x)]^{1/2} = [{\rm cov}(x,x)]^{1/2} \; .
\label{deltax}
\end{equation}
\noindent
The correlation between $x$ and $y$ (also called the correlation
coefficient) is defined as
\begin{equation}
{\rm corr}(x,y) \equiv \frac{{\rm cov}(x,y)}{\Delta x\;\Delta y} \;.
\label{corr}
\end{equation}
\noindent
The absolute value of a correlation coefficient is guaranteed to be
less than or equal to unity. Another useful quantity is the relative
covariance of $x$ with $y$,
\begin{equation}
{\rm rcov}(x,y) \equiv \frac {{\rm cov}(x,y)}{x_0 \; y_0} \;.
\label{rcov}
\end{equation}
\noindent
Unlike ${\rm cov}(x,y)$, the relative
{\rm cov}ariance ${\rm rcov}(x,y)$ is a dimensionless quantity.
Closely related to the relative covariance is the relative standard
deviation,
\begin{equation}
\frac {\Delta x}{x_0} \;=\; \frac {[{\rm cov}(x,x)]^{1/2}}{x_0} \;,
\end{equation}
\noindent
which, from Eq.~\ref{rcov}, can be written as
\begin{equation}
\frac {\Delta x}{x_0}\; =\; [{\rm rcov}(x,x)]^{1/2} \; .
\label{deltax0}
\end{equation}
\noindent
Combining Eqs.~\ref{corr} and \ref{rcov}, we have another useful result,
\begin{equation}
{\rm corr}(x,y) = \frac{{\rm rcov}(x,y)}{(\Delta x/x_0) (\Delta y/y_0)}\;.
\label{corr2}
\end{equation}
While it is customary to speak of uncertainties\index{uncertainties}
and correlations\index{correlations} as separate entities, these
are actually just two different aspects of the covariance. If one
has a set of absolute covariances for various reactions, including
the self-covariance, then Eqs.~\ref{deltax} and \ref{corr} can be used
to calculate $\Delta x$ and corr$(x,y)$. Similarly, if one has a set
of relative covariances, one can use Eqs.~\ref{deltax0} and
\ref{corr2} to calculate $\Delta x/x_0$ and corr$(x,y)$.
Consider now a set of nuclear data $\sigma_i$ with uncertainties
characterized by the covariances {\rm cov}$(\sigma_i,\sigma_j)$. Let
$A$ and $B$ be two linear functions of the $\sigma_i$,
\begin{equation}
A =\sum_{i} \; a_i \; \sigma_i
\end{equation}
\noindent
and
\begin{equation}
B =\sum_{j} \; b_j \; \sigma_j \; ,
\end{equation}
\noindent
where the $a_i$ and $b_j$ are sets of known constants. The above
definitions can be used to calculate the covariances of the functions
$A$ and $B$ induced by the covariances of the data.
From Eq.~\ref{cov},
\begin{eqnarray} {\rm cov}(A,B) & = & {\rm E} \left\{ {\vphantom{\sum_j}}\left
({\vphantom{\sum_j}}\sum_{i} \; a_i \; \sigma_i \; - \;\sum_{i}\; a_i {\rm E}
(\sigma_i)\right)\;{\vphantom{\sum_j}}\left(\sum_{j} \;b_j \;\sigma_j - \sum_{j}
(\sigma_j )\right )\right \} \nonumber \\
& = & \sum_{i,\; j} \; a_i \; b_j \; {\rm E} \left \{ {\vphantom{\sum}}\left
({\vphantom{\sum}}\sigma_i
{-} {\rm E} (\sigma_i) \right ) \;
\left ({\vphantom{\sum}} \sigma_j{-}{\rm E} (\sigma_j) \right) \right \} \;,
\end{eqnarray}
\noindent
so that
\begin{equation}
{\rm cov}(A,B) = \sum_{i,\,j} \; a_i \; b_j \; {\rm cov}(\sigma_i , \sigma_j ) \
\label{e11}
\end{equation}
\noindent
This result, called the ``propagation of errors'' formula, is
fundamental to the subject of multigroup processing of ENDF covariance
data and will be referenced frequently in later sections of this
chapter.
\subsection{Structure of ENDF Files 31, 33, and 40: Energy-Dependent Data}
\label{ssERRORR_Str}
Data in ENDF format are stored in various numbered ``files,'' where the
file number depends on the type of information contained. For example,
the covariances of $\bar{\nu}(E)$ (the average number of neutrons per
fission, which is a function of the incident neutron energy) are stored
in File 31, where the possible ``reaction'' types are prompt
$\bar{\nu}$, delayed $\bar{\nu}$, and total $\bar{\nu}$. File 33
contains the covariances of energy-dependent cross sections. In
general, for data given in File N, covariance data are given in
File (N+30). The structures of Files 31, 33, and 40 are identical
and will be described first.
Files 31, 33, and 40 describe the covariances of energy-dependent data. To
expand on this point, we recall that the full energy dependence of a
cross section $\sigma (E)$, for example, is described in the ENDF File
3 by specifying the cross-section values at a relatively small number
of energy points and then providing a set of interpolation laws to be
used in reconstructing the actual cross section at any intermediate
energy. Somewhat the same philosophy is used to describe the
two-dimensional energy dependence of data covariances in Files 31, 33, and
40. That is, one specifies a set of numerical data and a set of
formulae, which together can be used to compute ${\rm cov}(x,y)$ for
any desired pair of energies, $E_x$ and $E_y$. Although
the interpolation laws are presently restricted to the simple forms
described below, it is not true (as sometimes stated) that ENDF
contains multigroup covariances. The expression ``multigroup
covariance'' refers to the covariance of one multigroup-averaged
quantity with another averaged quantity, whereas ENDF contains the
covariances between point-energy data. It is precisely the task of
ERRORR to compute multigroup covariances, starting from point
covariances.
Files 31, 33, and 40 of an evaluation for material \cword{MAT} are divided
into ``sections,'' indexed by the reaction type \cword{MT}. A section
\cword{(MAT,MT)} is further subdivided into ``subsections.'' As
described in the ENDF formats manual, a subsection is the repository
for all explicit statements of the two-dimensional energy dependence
of the covariances of reaction \cword{(MAT,MT)} with another reaction
\cword{(MAT1,MT1)}. Because covariances are symmetric, a subsection
with \cword{MAT1}=\cword{MAT} and \cword{MT1}$<$\cword{MT} would be
redundant with a subsection in an earlier section, and such data are,
by convention, omitted from the ENDF files.
Subsections are further divided into ``sub-subsections.'' Two different
types of sub-subsections are used in the ENDF-5 and ENDF-6 formats. ERRORR
also treats data covariances in the earlier
ENDF-4 format, but this is of little practical interest since only three
covariance evaluations were released in the Version-4 format. ``NI-type''
sub-subsections are used to express covariances explicitly, while
``NC-type'' sub-subsections are used to indicate the existence of
connections between various data that result in ``implicit'' covariance
contributions for various reaction pairs. We shall return to this
point when discussing NC-Type Sub-Subsections.
\paragraph{NI-Type Sub-Subsections.} Multiple NI-type sub-subsections
are used to describe multiple, statistically independent sources of
uncertainty for a given reaction pair. If $ {\rm cov}(x,y)_n$ is the
covariance computed from the data in one sub-subsection, then, because
the uncertainties in different sub-subsections are uncorrelated,
$$
{\rm cov}(x,y) \;= \; \sum^{{\rm NI}}_{n=1} \; {\rm cov}(x,y)_n \; ,
$$
\vspace{2 pt}
where NI is the number of NI-type sub-subsections in the current
subsection.\ The numerical content of one NI-type sub-subsection
consists of either one or two energy grids, a collection of constants,
and a parameter \cword{LB}. The parameter \cword{LB} governs how the
energies and constants are to be used in constructing the covariance in
various rectangular regions of $E_x {-}E_y$ space. For \cword{LB}=0, 1,
2 and 8, a single table containing pairs $(E_i,F_i)$ is
given. For \cword{LB}=3 and \cword{LB}=4, two such tables are given. For
\cword{LB}=5, a single set of energies $E_i$ is given, along with an
associated square matrix of constants $G_{ij}$. Finally, for
\cword{LB}=6, two energy grids are given, along with an associated
rectangular matrix of constants $G'_{ij}$.
The first of these tables $(E_i,F_i)$ defines a function $f(E)$
that is constant except for
discrete steps at energies $E_i$,
\begin{equation}
f(E) = F_i ,\;{\rm if}\; E_i{\leq} E{<}E_{i+1} \;.
\label{e12}
\end{equation}
\vspace{0.5 pt}
\noindent
Similarly, if there is a second table,
\begin{equation}
f'(E) = F'_j , \; {\rm if}\; E'_j{\leq}E{<}E'_{j+1} \;.
\end{equation}
\vspace{0.5 pt}
\noindent
The \cword{LB}=5 matrix data $G_{ij}$ also define a function,
\begin{equation}
g(E_x,E_y) = G_{ij},\, {\rm{if}}\; E_i {\leq} E_x{<}E_{i+1} \;{\rm {and}}\; E_j
\; , \end{equation}
\noindent
and similarly for \cword{LB}=6
\begin{equation}
g'(E_x,E_y) = G'_{ij}, \, {\rm {if}}\; E_i {\leq} E_x {<} E_{i+1}\;{\rm {and}}
{\leq} E_y{<}E'_{j+1} \;.
\end{equation}
\vspace{1 pt}
\noindent
These functions are simply histograms in either one or two dimensions.
Using the functions $f$, $f'$, $g$, and $g'$ thus defined, we can list
the formulae in Eq.~\ref{lbopts}, which are used to specify energy-dependent
covariances for the different allowed values of \cword{LB}. Thus, if
$x$ is the value of the cross section or of the $\bar{\nu}$ value for the
reaction \cword{(MAT,MT)} that determines the ENDF/B
\underline{section}, and if $y$ is the value for the reaction
\cword{(MAT1,MT1)} that determines the \underline{subsection}, then for
\begin{equation}
\begin{array} {rrrll}
{\rm {LB}} & = & 0, & {\rm {{\rm cov}}} (x,y)_n & = \; f (E_x) \,
\delta (E_x,E_y) \\
{\rm {LB}} & = & 1, & {\rm {r{\rm cov}}} (x,y)_n & = \; f (E_x) \,
\delta (E_x,E_y) \\
{\rm {LB}} & = & 2, & {\rm {r{\rm cov}}} (x,y)_n & = \; f (E_x)\,f(E_y) \\
{\rm {LB}} & = & 3, & {\rm {r{\rm cov}}} (x,y)_n & = \;f (E_x)\,f'(E_y) \\
{\rm {LB}} & = & 4, & {\rm {r{\rm cov}}} (x,y)_n & = \; f (E_x) \,
\delta (E_x,E_y)\;f'(E_x)\,f'(E_y)
\\ {\rm {LB}} & = & 5, & {\rm {r{\rm cov}}} (x,y)_n & = \;g (E_x,E_y) \\
{\rm {LB}} & = & 6, & {\rm {r{\rm cov}}} (x,y)_n & = \; g'(E_x,E_y)\,\,.
\end{array}
\label{lbopts}
\end{equation}
\noindent
The symbol $\delta (E_x,E_y)$ has the following meaning: $\delta
(E_x,E_y){ =} 1$ if $E_x$ and $E_y$ fall in the same energy interval of
the first table $(E_i$, $F_i$), and $\delta(E_x,E_y){ =} 0$ otherwise.
The final covariance law, \cword{LB}=8, is an exceptional case that
cannot be expressed in terms of point covariances. \cword{LB}=8 is
used primarily to represent uncertainty effects due to suspected, but
unresolved, energy-dependent structure in a given cross section. If
$\Delta E_j$ is the energy width of the $j$-th ``union'' energy group
(see the discussion of union groups in Section~\ref{ssERRORR_UnionGrid}),
and if this group
lies within the $k$-th range ($E_k, E_{k+1}$) of an ENDF \cword{LB}=8
energy grid, then the effect of the \cword{LB}=8 subsection is to
trigger the addition of an uncorrelated contribution of
$F_k\,(E_{k+1} - E_k )/\Delta E_j$ to the (absolute) variance
of the $j$-th union-group cross section. No contributions to
off-diagonal elements of the multigroup covariance matrix are
generated by an \cword{LB}=8 sub-subsection.
\paragraph{NC-Type Sub-Subsections.} NC-type sub-subsections, which
describe covariances indirectly, are used in several evaluation
situations, which are flagged by different values of the parameter
\cword{LTY}. The first situation, \cword{LTY}=0, occurs when the
following two conditions are met: (a) the covariances of a given
reaction \cword{MT}, both with itself and with other reactions, can be
deduced in an energy range \cword{(E1, E2)} solely from the application
of a cross-section ``derivation relation,''
\begin{equation}
x({\mathtt{MAT,MT}};E) = \sum_{i} \; C_i \; x({\mathtt{MAT,MT}}_i; E),\;
\label{e17}
\end{equation}
\noindent
and (b) the covariances of all of the reaction cross sections on the
right-hand side of Eq.~\ref{e17} have been given directly (that is, using
only NI-type sub-subsections) throughout the range (\cword{E1, E2}).
The energy boundaries \cword{E1} and \cword{E2}, the constants $C_i$,
and the reaction identifiers \cword{MT}$_i$ are specified in an NC-type
sub-subsection with \cword{LTY}=0. This format is widely used in the
ENDF/B library, and it makes possible the elimination of large volumes
of otherwise redundant data. It also introduces considerable
complexity in the multigroup processing, as discussed in
Section~\ref{ssERRORR_UnionGrid}, and
adds to the computer running times. The presence of this one short
sub-subsection affects the calculation of the covariances for many
different reaction pairs, such as $x$\cword{(MAT,MT)} with
$x$\cword{(MAT,MT}$_i$\cword{)}. Less widely used are NC-type
sub-subsections with \cword{LTY}=1. These are employed when a reaction
\cword{MT} in material \cword{MAT} is evaluated in some energy range
\cword{(E1, E2)} as a ratio to a standard reaction \cword{MTS} in some
other material \cword{MATS}. That is,
\begin{equation}
x({\mathtt{MAT,MT}};E) = R(E)\, x ({\mathtt{MATS,MTS}};E).
\label{e18}
\end{equation}
In practical evaluation situations, the uncertainty of $R$ is almost
never correlated with that of $x$\cword{(MATS,MTS)}. Because of this,
the relative uncertainty in $R$ is treated simply as one independent
component of the relative uncertainty in $x$\cword{(MAT,MT)}, and it is
described using normal NI-type sub-subsections. On the other hand, the
contribution from uncertainty in $x$\cword{(MATS,MTS)} is represented
with an NC-type sub-subsection with \cword{LTY}=1, which contains,
in ENDF/B-V, only \cword{E1}, \cword{E2}, \cword{MATS}, and \cword{MTS}.
The actual numerical covariance information must be read from the
evaluation for the standard material \cword{MATS}, which usually resides
on an entirely different ENDF tape. An NC-type sub-subsection with
\cword{LTY}=1, which occurs in a given subsection
\cword{(MAT,MT; MAT,MT)}, affects the calculation of the covariances
only for the current reaction pair (reaction \cword{MT} with itself)
and, in this respect, is more like an NI-type sub-subsection than, for
example, an NC-type sub-subsection with \cword{LTY}=0. This similarity
is exploited in the processing of ratio covariances, as discussed in
Section~\ref{ssERRORR_Ratio}.
An NC-type sub-subsection with \cword{LTY}=2 is used, in a similar way,
to describe the covariances of $x$\cword{(MAT,MT)} with
$x$\cword{(MATS,MTS)}. As in the \cword{LTY}=1 case, an \cword{LTY}=2
sub-subsection contains only \cword{E1}, \cword{E2}, \cword{MATS}, and
\cword{MTS}.
An NC-type sub-subsection with \cword{LTY}=3 is included in material
\cword{MATS} to describe the (redundant) covariances of
$x$\cword{(MATS,MTS)} with $x$\cword{(MAT,MT)}. The numerical
information contained here is the same as for \cword{LTY}=1 and
\cword{LTY}=2. As discussed in Section~\ref{ssERRORR_Ratio},
an important function of
\cword{LTY}=3 data is to help locate reactions other than
\cword{(MAT,MT)} that have been measured relative to the same standard
\cword{(MATS,MTS)}.
\subsection{Resonance-Parameter Formats---File 32}
\label{ssERRORR_RR32}
File 32 contains covariances of resonance parameters
\index{resonance parameters} from File 2. Older versions of ERRORR
could only handle the ENDF-5 format (now called the
``Version-5 compatible'' format. Current versions can handle the
newer ENDF-6 formats that include resonance-resonance correlations.
\paragraph{ENDF-5 Type Resonance Formats.} With these formats
(\cword{LCOMP}=0), ERRORR processes File 32 in the following
limited sense: when infinite-dilution cross-section covariances
are processed (see previous section) from File 33, the diagonal
elements of the resulting (self-reaction) multigroup covariance
matrices are augmented by contributions based on the parameter
covariances in File 32. These methods were sufficient for
processing the covariance files in ENDF/B-VI.
For either of the permitted resolved resonance formalisms
(\cword{LRF}=1 or \cword{LRF}=2), the parameters considered in File 32 are
the resonance energy $E_r$, the neutron width $\Gamma_n$, the radiative
capture width $\Gamma_{\gamma}$, the fission width $\Gamma_f$, and (in
Version 5 only) the total angular momentum $J$. All cross-parameter
relative covariances, such as r{\rm cov}($\Gamma_n$,$\Gamma_{\gamma}$),
are included, with the exception of the covariances of $E_r$ with the
remaining parameters, which are assumed to be negligible.
Cross-resonance covariances, such as {\rm cov}($E_r^i,\;E_r^j$), where
$i$ and $j$ refer to different resonances, are omitted in the
\cword{LCOMP}=0 option.
\paragraph{ENDF/B-VII Resonance Covariances.} For ENDF/B-VII, a
number of evaluations include covariance formats that represent
the correlations between resonance parameters for a given
resonance and between different resonances. In later versions
of NJOY99, these cases are handled by the ERRORJ\cite{ERRORJ}\index{ERRORJ}
module, which was developed in Japan and contributed to the
NJOY project. The ERRORJ coding was integrated into NJOY2012's
ERRORR module, and it remains in NJOY2016. The ERRORJ approach
is based on computing the sensitivity of a cross section to a
given resonance by numerical differencing and then combining
these sensitivities with parameter covariances from the evaluation.
There are three basic covariance format options, governed by the
\cword{LCOMP} and/or \cword{LRU} flags. The \cword{LRU} flag
distinguishes between resolved resonance (\cword{LRU}=1) and
unresolved resonance (\cword{LRU}=2) data. For \cword{LCOMP}=1/\cword{LRU}=1,
there may be two classes of data, designated as \cword{NSRS} or
\cword{NLRS} sub-subsections. \cword{NSRS} sub-subsections provide covariance
data among parameters of specified resolved resonances. Covariances
may be given for all ENDF recognized resolved resonance formats (as
specified via the \cword{LRF} flag). \cword{NLRS} sub-subsections provide
long-range parameter covariances. These data are allowed for
all resolved resonance formats. At present there are no \cword{NLRS}
sub-subsection data in ENDF/B-VII, and NJOY does not process
these data.
The \cword{LCOMP}=2/\cword{LRU}=1 format provides a combination of resolved
resonance parameters and their uncertainties plus a correlation matrix.
The correlation matrix is given in a special packed form using the
ENDF INTG record format with matrix elements consisting of as few
as 2 to as many as 6 digits. Covariance matrix elements,
$V_{ij}$ can be reconstructed as
\begin{equation}
V_{ij} = D_iC_{ij}D_j
\end{equation}
\noindent
where $D_i$ is the uncertainty on parameter $i$ and $C_{ij}$ is the
correlation matrix element relating parameters $i$ and $j$. Since
the correlation matrix is symmetric, and its diagonal terms are unity,
only the upper triangle of matrix elements is given in the ENDF file.
This more compact representation of the covariances helps for materials
with large numbers of resonances.
Finally, the \cword{LRU}=2 (\cword{LCOMP} is not defined and its
location in the ENDF file is typically set to zero) format is used
to define covariances for unresolved resonance parameters. The
data represent an energy independent relative covariance matrix
even if the underlying unresolved resonance parameters are energy
dependent. This is a symmetric matrix and so only the upper
triangular portion of the matrix is provided in the ENDF file.
The original covariance data formats did not allow the evaluator to
define an uncertainty in the scattering radius (only for resonance
energy and the total or partial resonance widths). This deficiency
was eliminated in 2009, but until new evaluations are released there
are no scattering radius uncertainty data in current evaluated
library files. NJOY can include scattering radius uncertainty
effects if such data are given in the evaluated file. In addition,
users can specify an uncertainty in the ERRORR input so that this
important component to the cross section uncertainty is considered
when processing existing files that lack these data (see the
description for \cword{dap} on Card 7 in Section~\ref{ssERRORR_inp} below).
\paragraph{Reich-Moore-Limited Covariance Representations.}
The current ENDF-6 format also allows resonances using the \cword{LRF}=7
Reich-Moore-Limited (RML)\index{Reich-Moore-Limited!RML}
representation. In addition to the covariances described above, the
RML approach can define channel-channel covariances properly. There
are two experimental evaluations currently available that use this
approach. A sample $^{19}$F evaluation from the ORNL
\index{Oak Ridge National Laboratory!ORNL} represents the
four reactions elastic, capture, (n,n$_1$), and (n,n$_2$).
Fig.~\ref{covyy} shows that ERRORR can generate the covariances
between elastic and (n,n$_1$). The ENDF/B-VII.1 $^{35}$Cl
evaluation from ORNL uses the \cword{LRF}=7 formalism to
represent the elastic, capture, and (n,p) reactions. The
coding in NJOY2016 to handle these cases uses analytic calculations
for the parameter sensitivities borrowed from SAMMY\cite{SAMMY}.
\begin{figure}[t]\centering
\includegraphics[keepaspectratio, width=5in,angle=0]{figs/covyyack}
\caption[Example of elastic scattering and (n,n$_1$) covariance data]
{Covariance plot for the elastic and (n,n$_1$) reactions from a
sample ORNL evaluation for $^{19}$F, demonstrating the channel-channel
covariances possible when using the Reich-Moore-Limited resonance
representation.}
\label{covyy}
\end{figure}
\subsection{Secondary Particle Angular Distribution Covariances---File 34}
\label{ssERRORR_34}
File 34 contains covariances for angular distributions of secondary
particles. While the underlying angular distribution data in File 4
may be given as tabulated distributions or as Legendre polynomial
coefficients, File 34's covariance data are only given for Legendre
coefficients. At present there is no provision to specify covariances
between cross sections from File 3 and angular distributions from
File 4, nor to specify angular distribution covariances between
different materials. The data format is governed by the \cword{LB}
flag discussed above in Section~\ref{ssERRORR_Str} with LB values
of 0, 1, 2, 5 and 6 allowed.
File 34 in the ENDF file may include covariance data for any MT
reaction defined in File 4, but currently NJOY only processes
the $P_1$ component of MT=2 (elastic scattering).
Fig.~\ref{mf34cov} shows an example of the covariances computed from File 34
for $^{238}$U from JENDL-3.3. As usual, there are three components to this
plot. On the right side, we illustrate $\bar{\mu}$ {\it vs} energy, which
dislays the expected forward-peaked characteristic with increasing energy;
on the top is
the uncertainty in $\bar{\mu}$ {\it vs} energy; and in the center is the
correlation matrix. The ERRORR input for this case will be presented
below.
\begin{figure}[thb]\centering
\includegraphics[keepaspectratio, width=5in, angle=0]{figs/mf34covack}
\caption[Example of angular distribution covariance data]{Example of angular
distribution covariance data.}
\label{mf34cov}
\end{figure}
\subsection{Secondary Particle Energy Distribution Covariances---File 35}
\label{ssERRORR_35}
File 35 contains covariance matrices for the energy distributions
of secondary particles given in File 5. If the spectral distributions
are correlated with angular distributions and given in File 6, the
covariance information still appears in File 35 (the MT section
identifier is the common datum relating these data) and refers
to the angle-integrated distributions only. The secondary energy
distribution is usually defined on a relatively fine energy grid,
and multiple distributions are given as a function of increasing
incident particle energy. Since the uncertainties in secondary
distributions are usually highly correlated as a function of incident
particle energy, it is generally sufficient to only define a few
covariance matrices over relatively broad incident energy groups.
There is no provision to specify covariances between these groups
nor with data from other files such as File 3 cross sections or
File 1 prompt, delayed or total $\bar{\nu}$.
File 35 covariance data are given in a series of \cword{NK} subsections,
with each subsection covering a unique incident particle energy range.
The lowest energy of the first subsection and the highest energy of
the last subsection must cover the entire incident particle energy
range from File 5 (or File 6). When processing MF35 data, the user
can specify the incident particle energy of interest (\cword{efmean}
on Card 7). NJOY will process the \cword{NK}$^{\rm th}$ subsection whose
energy is closest to, but less than, \cword{efmean}. The data
tabulated in the ENDF file are normalized probabilities of absolute
covariances identified as an \cword{LB}=7 subsection. \cword{LB}=7
is identical to \cword{LB}=5 defined in Section~\ref{ssERRORR_Str}
except that these data are now absolute rather than relative covariances.
The ENDF format manual notes these matrices are probability distributions
that must remain normalized to unity and therefore the elements in these
symmetric matrices are constrained such that the sum of the elements
in any row (or column) must be zero. This is sometimes referred to as
the ``zero sum" rule. Of course, when dealing with real
numbers of finite precision whose values can vary by orders of magnitude
it is virtually impossible to rigorously conform to this rule.
Therefore, if the sum is sufficiently small, the rule is judged to be
satisfied. If not, the ENDF manual provides a correction formula
to apply to all matrix elements. When processing File 35 data NJOY,
checks this summation requirement and, if necessary, applies the
required correction. NJOY uses the ``sufficiently small" criteria
specified in the Format manual for this check.
At present there are no File 35 data in ENDF/B-VII.0 neutron files,
but the $^{252}$Cf decay file does contain such data. Also, these data
are becoming available in preliminary ENDF/B-VII.1 files available from
the National Nuclear Data Center (NNDC) at Brookhaven
National Laboratory (BNL). These files follow
the ``zero sum' rule discussed above, but users are cautioned that
other internationally distributed files, particularly those from
JENDL-3.3, may provide File 35 data in an alternate format. The
matrix elements in the JENDL-3.3 files have been divided by the
group energy width to yield energy-group averaged probability
distributions, as this is the data representation expected by the
Japanese ERRORJ code\cite{ERRORJ}\index{ERRORJ}. A conversion code,
chmf35, has been developed and is available from the Nuclear Energy Agency
\footnote{chmf35 may be downloaded from
\href{http://www.nea.fr/dbprog/Njoy/chmf35.for}
{http://www.nea.fr/dbprog/Njoy/chmf35.for}}
to reformat these files
so that they are suitable for processing by NJOY.
Fig.~\ref{mf35cov}
shows the results of processing the ficticious $^{252}$Cf evaluation. The
ERRORR input for this job will be presented below.
\begin{figure}[thb]\centering
\includegraphics[keepaspectratio, width=5in, angle=0]{figs/mf35covack}
\caption[$^{252}$Cf(n,f) spontaneous fission spectrum covariance data]{Example
of energy distribution covariances. The appearance of negative correlations
results from the requirement for preserving normalization.}
\label{mf35cov}
\end{figure}
\subsection{Radioactive Nuclide Production Covariances--File 40}
\label{ssERRORR_40}
There is only one file in ENDF/B-VII.0 that includes File 40 covariance
data -- $^{93}$Nb. The input for calculating the $^{93m}$Nb production
uncertainty will be shown below, but the resulting covariances are shown
here in Fig.~\ref{mf40cov}. The form of the graphical output
obtained when processing File 40 is identical to that produced when
processing File 33; with the cross section shown to the right, the
uncertainty shown to the top and the correlation matrix shown in the
center. That these are File 40 data can be determined from the label
on the uncertainty portion of the plot. In 2009, the File 40 format
was modified to include the \cword{IZAP} parameter that identifies the daughter
product. We include this \cword{IZAP} value in the plot label so that the user
can more fully identify these data. If an older File 40 file is processed
that does not define \cword{IZAP}, then the text string ``\cword{MF40}'' will
appear in the title. In the example shown here we have modified the original
ENDF/B-VII.0 $^{93}$Nb file to include the proper \cword{IZAP} value in
File 40, which then appears in the plot title.
\begin{figure}[t]\centering
\includegraphics[keepaspectratio, width=5in, angle=0]{figs/mf40covack}
\caption[Radioactive nuclide production covariance example]{Example of
radioactive nuclide production covariances.}
\label{mf40cov}
\end{figure}
\subsection{Calculation of Multigroup Fluxes, Cross Sections, and
Covariances on the Union Grid}
\label{ssERRORR_UnionGrid}
As mentioned before, the main function of the ERRORR module is to
calculate the uncertainty in group-averaged cross sections at infinite
dilution due to uncertainty in the ENDF point data. In this and the
following sections, we describe the procedures used in performing this
task.
In order to proceed, it is necessary to introduce into the discussion
three different energy grids, namely, the user grid, the ENDF grid, and
the union grid. The relationship of these three grids is shown in
Fig.~\ref{grel}. The user grid is the multigroup structure in which
the output multigroup covariances are to be produced. The ENDF grid
is the collection of energies obtained (in subroutines
\cword{gridd}\index{gridd@{\ty gridd}} and
\cword{grist}\index{grist@{\ty grist}}) by forming
the union of (a) all energy ``lists'' appearing in any NI-type
sub-subsection of any subsection to be processed in the current ENDF
material, and (b) all energy pairs used to define the range of
effectiveness of any NC-type sub-subsection of any subsection to be
processed. The union grid, on the other hand, is simply the union of
the user grid and ENDF grid. The utility of the union grid is that (a)
the covariances are particularly simple to calculate in this grid, as
discussed below, and (b) the multigroup covariances needed by the user
are then easily obtained by a straightforward collapse from this to
the user grid. In fact, the design of the current ENDF covariance
format was strongly influenced by the desire to employ this particular
procedure for multigroup processing\cite{Weisbin,Smith}.
\begin{figure}[b]\centering
$\begin{array}{lccccccccr}
{\rm User\; Grid} \; \; &|&& \phi_1 , X_1 & &|& & \phi_2 , X_2 & &| \\
{\rm ENDF\; Grid} \; \; &|& F_1 \; &|& & F_2 & & |& F_3 &| \\
{\rm Union \;Grid} \; \; &|&\phi_1 , x_1 &|& \phi_2 , x_1 &|&\phi_3 ,
x_3 & | &\phi_4, x_4 &|\\
\end{array}$
\vspace{.25 in}
\caption{Illustration of energy grid relations.}
\label{grel}
\end{figure}
After the union grid is formed in subroutine
\cword{uniong}\index{uniong@{\ty uniong}}, the cross
sections $x(E)$ and weighting flux $\phi (E)$ are integrated to produce
$x_I$ and $\phi_I$, multigrouped on this grid. If point cross sections
are supplied, an exact integration is done in subroutine
\cword{grpav}\index{grpav@{\ty grpav}}. If, on the other hand, a
multigroup cross-section library is supplied, then subroutine
\cword{colaps}\index{colaps@{\ty colaps}} is used. If a library group
is subdivided by a union-group boundary, then over the span of that
library group, the unknown energy dependencies of $x(E)$ and $\phi
(E)$, which are needed to calculate $x_I$ and $\phi_I $, are
approximated in subroutine \cword{colaps} by constants. Normally, the
effect of this approximation is not large and, in any case, can be
reduced or eliminated by increasing the number of groups in the input
library.
We next consider the theoretical basis for the calculation of
union-grid multigroup covariances, as performed in subroutine
\cword{covcal}\index{covcal@{\ty covcal}}. By definition, $x_I$
is just the average of $x(E)$ over union group I,
\begin{equation}
x_I \; \equiv \;\frac {\displaystyle\int_I \; \phi (E) \; x(E) \;
dE}{\displaystyle\int_I \; \phi (E) \; dE} \,\,,
\label{e19}
\end{equation}
\noindent
where $\phi (E)$ is the flux ``model'' assumed for the multigroup
calculations. Let $y_J$ denote similarly the average of $y(E)$ over
union group $J$.
Let us imagine that these groups are subdivided into many subintervals
of infinitesimal width, so that in the i$^{\rm{th}}$ subinterval of group I,
for example, $x(E)$ can be well approximated by the constant $x_i$. By
this device, the integrals that define $x_I$ and $y_J$ can be converted
to discrete sums:
\begin{equation}
x_I \; = \frac{{\displaystyle \sum_{i\in I}} \; \phi_i \; x_i}{\phi_I } \; = \;
\sum_{i\in I} \; \alpha_{Ii} \; x_i\,\,,
\label{e20}
\end{equation}
\noindent
where
\begin{eqnarray}
\phi_i & = & \int_{i} \; \phi (E) \; dE \;,\\
\nonumber \\
\phi_I & = & \sum_{i\in I} \; \phi_{i} \; = \; \int_{I} \; \phi (E) \; dE\;,
\end{eqnarray}
\noindent
and
\begin{equation}
\alpha_{Ii} \equiv \frac{\phi_i}{\phi_I} \; .
\end{equation}
\noindent
From these definitions, clearly
\begin {equation}
\sum_{i\in I}\; \alpha_{Ii} \; = \; 1 \; .
\label{e24}
\end{equation}
\noindent
Similarly for $y$,
\begin{equation}
y_J = \sum_{j\in J} \; \alpha_{Jj} \; y_j\;,
\label{e25}
\end{equation}
\noindent
and
\begin{equation}
\sum_{j \in J} \; \alpha_{Jj} = 1 \;.
\label{e26}
\end{equation}
The methodology of ERRORR assumes that $\phi(E)$ in Eq.~\ref{e19} is
free of uncertainty. Under this assumption, the terms $\alpha_{Ii}$
and $\alpha_{Jj}$ are simply known constants. The covariance of $x_I$
with $y_J$ can then be calculated using the propagation-of-errors
formula, Eq.~\ref{e11}, together with Eqs.~\ref{e20} and \ref{e25}.
\begin{eqnarray}
{\rm {\rm cov}} (x_I,y_J) & = & \sum_{i\in I\atop{j\in J}}\;
\alpha_{Ii} \; \alpha_{Jj} \; {\rm cov}
(x_i ,y_j) \nonumber \\
\nonumber \\
& = & \sum_{i\in I\atop{j\in J}}\; \alpha_{Ii} \; \alpha_{Jj} \; \sum_{n}{\rm
cov} (x_i ,y_j)_n \; ,
\end{eqnarray}
\noindent
where the summation over $n$ results from the different independent
contributions to the ENDF point covariances coming from the different
NI-type sub-subsections. Changing the order of summation, we obtain
\begin{equation}
{\rm cov} (x_I,y_J) \; = \; \sum_{n} \; {\rm cov} (x_I,y_J)_n \; ,
\label{e28}
\end{equation}
\noindent
where
\begin{equation}
{\rm cov} (x_I,y_J)_n \;=\; \sum_{i\in I\atop{j\in J}} \; \alpha_{Ii}\;
\alpha_{Jj}\;\; {\rm {\rm cov}} (x_i,y_j)_n \; .
\label{e29}
\end{equation}
To evaluate the sum in Eq.~\ref{e29}, we make use of the fact that union
groups {\it I} and {\it J} do not cross any ENDF grid boundaries.
Recalling the discussion of NI-type sub-subsections (and
excluding for the moment the case where sub-subsections with
\cword{LB}=8 are present), there are only two possibilities for the
energy dependence of the covariance between ENDF grid points; thus,
over the limits of the sum, either cov$(x_i,y_j)_n$ is independent of
$i$ and $j$ (if \cword{LB}=0) or rcov$(x_i,y_j)_n$ is independent of
$i$ and $j$ (if $1\leq$ \cword{LB} $\leq 6$). We consider first the
constant-absolute-covariance case, \cword{LB}=0. Eq.~\ref{e29} can then be
rewritten as follows:
\begin{equation} {\rm {\rm cov}} (x_I,y_J)_n\; = \; {\rm {\rm cov}} (x,y)_n
\; \sum_{i\in I\atop{j\in J}} \; \alpha_{Ii} \; \alpha_{Jj} \; = \;
{\rm {\rm cov}} (x,y)_n
\left(\sum_{i\in I} \; \alpha_{Ii} \right) \left(\sum_{j\in J} \;
\alpha_{Jj}\right) \; .
\end{equation}
\noindent
Invoking Eqs.~\ref{e24} and \ref{e26}, we obtain
\begin{equation}
{\rm cov}(x_I , y_J)_n \;=\; {\rm cov}(x,y)_n \; \;\;\;\;\;
(\hbox{\cword{LB}} = 0) \;.
\label{e31}
\end{equation}
\noindent
For \cword{LB}-values ranging from 1 to 6, the relative covariance is
constant over each union group, so we rewrite Eq.~\ref{e29} in the form
\begin{eqnarray}
{\rm {\rm cov}} (x_I,y_J)_n & = & \sum_{i\in I\atop{j\in J}}\; \alpha_{Ii}\;
\alpha_{Jj} \; x_i \; x_j \;
{\rm r{\rm cov}} (x_i , x_j)_n \nonumber \\
& = &{\rm r{\rm cov}} (x,y)_n \sum_{i\in I\atop{j\in J}}\;
(\alpha_{Ii}\; x_i ) \; (\alpha_{Jj} \; y_j) \nonumber \\
& = & {\rm rcov} (x,y)_n \; \left(\sum_{i\in I} \; \alpha_{Ii} \;
x_i \right) \left(\sum_{j\in J}\; \alpha_{Jj} \; y_j \right) \; .
\label{e32}
\end{eqnarray}
\noindent
Substituting here from Eqs.~\ref{e20} and \ref{e25}, we obtain
\begin{equation}
{\rm {\rm cov}} (x_I , y_J)_n = x_I\; y_J \; {\rm r{\rm cov}} (x,y)_n
\;\;\;\;\;\; (1
\leq\hbox{\cword{LB}}\leq 6)\; .
\label{e33}
\end{equation}
\noindent
The final union-group multigroup covariance is obtained by inserting
these results, Eqs.~\ref{e31} and \ref{e33}, back into Eq.~\ref{e28}
\begin{equation} {\rm cov} (x_I,y_J) = \; \sum_{\rm n(LB=0)} \;
{\rm cov} (x,y)_n \;+\; \sum_{\rm n(LB=1,6)} \;x_I\;y_J
\; {\rm r{\rm cov}} (x,y)_n\;,
\label{e34}
\end{equation}
\vspace{1 pt}
\noindent
where the first sum runs over all sub-subsections with \cword{LB}=0 and
the second runs over all sub-subsections with \cword{LB}=1 through 6. The
quantities cov$(x,y)_n$ and r{\rm cov}$(x,y)_n$ here
are simply the point-energy covariances from the ENDF covariance file,
as described in Eqs.~\ref{e12} through \ref{lbopts}. Equation \ref{e34}
then is the basic equation used in subroutine \cword{covcal} to
calculate the desired union-group covariances.
The final step, if sub-subsections with \cword{LB}=8 are present, is to
increment the diagonal elements (variances) as follows:
\begin{equation}
{\rm cov} (x_I, x_I) = {\rm cov} (x_I, x_I) +
F_k\,(E_{k+1} - E_k)/\Delta E_I \;,
\label{e35}
\end{equation}
\noindent
where k indexes the range of the \cword{LB}=8 energy grid that includes
union group {\it I}.
\subsection{Basic Strategy for Collapse to the User Grid}
\label{ssERRORR_GridStrategy}
The union-group fluxes $\phi_I$ are used, in subroutine
\cword{sigc}\index{sigc@{\ty sigc}}, to collapse the union-group
cross sections to the coarser user grid. Changing notation slightly,
let us denote by $x_I(a)$ the cross section in union group {\it I}
for reaction $a$, and similarly let $X_K (a)$ be the cross section
in user group {\it K} for the same reaction. In complete analogy
with Eq.~\ref{e20},
\begin{equation}
X_K(a) = \frac {\displaystyle{\sum_{I\in K}\; \phi_I\;x_I(a)}}{\phi_K}
\;=\; \sum_{I\in K} \; A_{KI} \; x_I(a)\;,
\end{equation}
\noindent
where