Nuclear Instruments and Methods in Physics Research A 712 (2013) 157–161

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Nuclear Instruments and Methods inPhysics Research A

0168-90

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journal homepage: www.elsevier.com/locate/nima

Development of a stochastic detection efficiency calibration procedure forstudying collimation effects on a broad energy germanium detector

Massimo Altavilla a, Romolo Remetti b,n

a High Institute for Environmental Protection and Research (ISPRA)—Department for Nuclear, Technological and Industrial Risk. Via Vitaliano Brancati 48, 00144 Rome, Italyb ‘‘Sapienza’’—University of Rome, Department BASE—Basic and Applied Sciences for Engineering. Via Antonio Scarpa 14, 00161 Rome, Italy

a r t i c l e i n f o

Article history:

Received 5 September 2012

Received in revised form

31 January 2013

Accepted 7 February 2013Available online 27 February 2013

Keywords:

Broad energy germanium detector

Gamma-ray spectrometry

MCNPX

ISOCS

Collimator algorithms

02/$ - see front matter & 2013 Elsevier B.V. A

x.doi.org/10.1016/j.nima.2013.02.019

esponding author. Tel.: þ390649766538; fax

ail address: romolo.remetti@uniroma1.it (R. R

a b s t r a c t

ISPRA, the Italian nuclear safety regulatory body, has started a measurement campaign for validating

the performances of in situ gamma-ray spectrometry based on BEGe detectors and ISOCS software. The

goal of the validation program is to verify if the mathematical algorithms used by Canberra to account

for collimation effects of HpGe detectors continue to work well also for BEGe detectors. This has

required the development of a calibration methodology, based on MCNPX code, which, by avoiding any

mathematical algorithm utilization, is purely stochastic.Experimental results obtained by such a new

procedure, were generally found to be 5% of the reference values. While, in the case of gamma-ray

energies greater than 400 keV and small angles collimation, results given by ISOCS software produced

larger deviations, around 20%. This work presents a detailed description of the simulation procedure

and of the first experimental results.

& 2013 Elsevier B.V. All rights reserved.

1. Introduction

In many operative situations that require immediateradiometric characterization, in situ gamma-ray spectrometryrepresents an ideal technique for providing, directly on site,radionuclide concentrations and other related quantities, suchas activities per unit area and exposure rates. The potentialities ofsuch a technique have been strongly enhanced by the introduc-tion of BEGe detectors, which allow an extended assay energyrange from 3 keV to 3 MeV in the same measurement, bycombining the spectral advantages of low energy and coaxialdetectors. Furthermore, software tools based on mathematicalmodels aimed at simulating a wide variety of sample shapeseliminate the need of radionuclide standards for detector’sefficiency calibration. Summing up, it is expected that a portablesystem composed of a broad energy germanium detector, adetector holder, a nuclear electronics workstation, and a laptopPC implementing spectrum analysis and calibration software,should be able to face almost every in situ situation, mostly indecommissioning operations of nuclear installations. For thiswork, a portable gamma-ray spectrometry system provided witha BE3825 Canberra detector [1] and with ISOCSTM software [2]was considered.

ll rights reserved.

: þ390644240183.

emetti).

As described by Venkataraman et al. [3,4] the ISOCS calibrationmethod is based on a detailed Monte Carlo model of a specificgermanium detector created using the nominal dimensions pro-vided by the production facility. The detector model is validatedby comparing Monte Carlo detection efficiencies to measuredefficiencies for several source geometries and at a range ofenergies. These two efficiency data sets are then meshed togetherinto a single characterization file, which contains a series ofequations defining the detector response which are then imple-mented in the ISOCS software.

When operating with portable systems in in situ conditions,the typical scenario is characterized by the contemporaneouspresence of many spatially distributed radioactive sources; adirect consequence of such a situation is the need to reduce thedetector’s field of view by proper collimation. Obviously, theconsequent detection efficiency modifications introduced bychanging detector collimation should be taken into account bythe ISOCS software. Introducing corrections for collimation effectson detection efficiency may be a not easy solution task. Forinstance, Venkataraman and Bronson [5] point out that in earlierversion of ISOCS (up to Version 1.2b) the uncertainty in theefficiency calibration for collimated geometries was larger thanthat for non-collimated geometries. This defect was then cor-rected, and for more recent ISOCS versions Canberra has designedand tested for accuracy improvements, and minimal computa-tional speed degradation, a series of collimator algorithms to beused with germanium detectors. Venkataraman and Bronson [5]reports that accuracies of both collimated and uncollimated

M. Altavilla, R. Remetti / Nuclear Instruments and Methods in Physics Research A 712 (2013) 157–161158

detector efficiencies are about 4–5% (1s) at photon energies4150 keV, and 8–10% at energies o150 keV. Anyway, the ISOCS(Version 4.0) validation manual [6], reports that, in some cases,when small aperture collimators are involved, deviations as muchas 22% from reference values may appear.

A nuclear safety regulatory body may judge such a magnitudeuncertainties unacceptable. Such an assessment can be under-stood just on the basis of the peculiar advantages of in situgamma-ray spectrometry respect to laboratory gamma-ray spec-trometry, that can be summarized by the words of Benke andKearfott [7]: ‘‘The possibility to characterize larger volume ofmaterials, of requiring less time to determine accurate radio-nuclide concentrations, and of minimizing worker doses and therisk of radioactive contamination’’. Further, making errors around20% can be harmful not only for wrong estimations of workers’doses and radioactive contaminations, but also when discriminat-ing between radioactive wastes and clearable materials.

Starting from these assumptions, ISPRA, the Italian HighInstitute for Environmental Protection and Research, has initiateda task to validate the performances of recently acquired ISOCSsystem with a BEGe detector; in particular, the target is to verify ifcollimator algorithms of ISOCS Version 4.0 software, originallydeveloped for HpGe detectors, remain still valid for BEGe detec-tors within the whole energy range that this kind of detectors canassay. Such a validation task is based on experimental measure-ments of reference sources carried out by the ISOCS hardware,ISOCS software, and by an original stochastic calibration proce-dure based on MCNPXTM [8].

The MCNPX calibration procedure developed for this workincludes stochastic models for both detector and collimator,hence it represents a novel contribution respect to ISOCS char-acterization software, because it does not use algorithms fortaking into account the additional attenuation due to the colli-mator. Making use of such a pure stochastic calibration procedureallows to obtain measured results that, without and with collima-tion, are generally within 5% from reference values.

Fig. 1. Schematic view of the detector assembly, Carbon epoxy window (1), gap

between crystal and crystal holder filled with thick plastic insulator all around the

crystal (2), aluminum end-cap (3), and copper crystal holder (4).

2. Monte Carlo simulation of the detector

Monte Carlo simulation of gamma-ray radiation detectors is apowerful tool for determining detection efficiency in manymeasurement configurations, even if, as focused by many authors,it requires a thorough knowledge of structural characteristics ofthe detectors. As pointed out by Decombaz and Laedermann [9]such a requirement may be simply accomplished for NaI detec-tors, for which only dimensions and materials of the crystal andhousing must be accurately known. On the other hand, forgermanium detectors the determination of geometrical para-meters can be extremely complicated as a larger number ofdimensions are involved. For instance, Vargas et al. [10], dealingwith a coaxial n-type HpGe detector, describe seven main para-meters: diameter and height of the crystal, diameter and height ofthe internal core, thickness of the beryllium window, distancebetween the crystal top and the Be window, and the thickness ofthe dead layer of Ge. Bochud et al. [11] consider that notwith-standing manufacturers usually document geometrical dimen-sions, the associated uncertainties, that may play a fundamentalrole in the quality of the simulation, are not very well known.Rodenas et al. [12] emphasize how the dead layer thickness [13]plays a non-negligible role in accurate Monte Carlo simulations.Due to the impossibility of performing physical measurements ofthe extension of the dead layer, in Monte Carlo detector simula-tions this value is tuned from experimental measurements; anaccurate description of such a sensitivity analysis is given by Luiset al. [14]. Having described accurately the detector’s internal

structure and the experimental set-up, it is possible to obtaincalculated detection efficiencies that generate measured activityvalues from net peak areas of gamma-ray spectra [11,12].

For this work a Broad Energy Germanium detector has beenutilized and for this kind of detectors simulation is even morecomplicated due to the presence of two dead layers: the top deadlayer and the lateral one. It is a planar p-type High Purity Germaniumdetector, [13], with the Li-drifted nþ contact covering the wholeouter surface, and a small pþ contact on the back side. The top nþ

contact is very thin to reduce absorption of low energy gamma rays.Accurate descriptions of this kind of detector are given by Luis et al.[14], Mueller et al. [15], Budjas et al. [16], and Barrientos et al. [17]. Inparticular, we used the BE3825 Canberra model, characterized by 28%relative efficiency, and values of full width at half maximum (FWHM)of about 0.72% at 122 keV and 1.978% at 1333 keV [1].

Structural characteristics of the detector were derived frommanufacturer’s data sheets and from Gonzalez et al. [18]. As deadlayer values are concerned, the usual operation of preliminarytuning vs. experimental data was carried out, which allowed toobtain practically the same results reported in [18]. Figs. 1 and 2give an idea of the degree of detail of the simulation. Obtained bymeans of MCNPX Visual Editor [19], Fig. 3 gives a three-dimensional view and highlights the germanium crystal as wellas the carbon epoxy window, the copper crystal holder, and thealuminum end cap assembly.

Simulation of the detector was carried out using MCNPXversion 2.7.0 [8], by trying to account for those composingsections that influence the detection efficiency.

2.1. Simulation technique

With the aim to obtain a simulated gamma-ray spectrum, theoutput of the simulation was given in terms of the Pulse HeightTally F8 [8], i.e. the tally reproducing the energy distribution ofpulses created inside the detector by radiation. Tally F8 has manyoptions. The standard F8 tally is a pulse-height tally and theenergy bins are no longer the energies of scoring events, butrather the energy balance of all events in a history. When flaggedwith an asterisk, nF8 becomes an energy deposition tally.

To improve simulation of the gamma-ray spectrum, theGaussian Energy Broadening (GEB) option was adopted. GEB is aspecial feature, activated by entering the FT card [8] in the inputfile, which reproduces the Gaussian fluctuation that a single

Fig. 2. Particular of the germanium crystal, Germanium entrance window (1),

litium diffused nþ contact (2), and boron implanted pþ contact (3).

Fig. 3. Side views of detector’s assembly, Obtained by means of MCNPX Visual

Editor. Germanium crystal (1), carbon epoxy window (2), copper crystal holder

(3), and aluminum end cap assembly (4).

Fig. 4. Experimental FWHM values of BE3825 detector, Energy range of

0.05–1.84 MeV; least squares best fit (correlation coefficient R2¼0.9931).

Table 1NPL ARAME source [20], Aref represents the reference source activity with its

associated error DAref.

Radionuclide Energy [MeV] FWHM [MeV] Aref [Bq] DAref [%]

Pb-210 0.0465 6.28E-04 1603.32 2.99

Am-241 0.0595 6.02E-04 245.00 2.04

Cd-109 0.0880 6.64E-04 1261.50 2.68

Co-57 0.1221 6.74E-04 52.33 2.64

Ce-139 0.1659 7.39E-04 53.24 2.56

Cr-51 0.3201 8.91E-04 878.87 2.41

Sn-113 0.3917 9.49E-04 155.83 2.37

Sr-85 0.5140 1.06E-03 179.07 2.44

Cs-137 0.6617 1.20E-03 238.00 2.52

Mn-54 0.8348 1.33E-03 242.30 2.45

Y-88 0.8980 1.33E-03 390.10 2.48

Zn-65 1.1155 1.54E-03 502.80 2.35

Co-60 1.1732 1.48E-03 277.00 2.17

Co-60 1.3325 1.46E-03 277.00 2.17

Y-88 1.8360 1.76E-03 390.10 2.48

M. Altavilla, R. Remetti / Nuclear Instruments and Methods in Physics Research A 712 (2013) 157–161 159

gamma-ray emission exhibits when detected in a real detector.The tallied energy is broadened by sampling from the Gaussiancentered on the energy of the tally. As in the real situation, theGaussian width is expressed in terms of FWHM. In the MCNPXsimulation, the FWHM is specified by the user by means of theconstants a, b, and c, through the relation

FWHM¼ aþbðEþcE2Þ1=2

ð1Þ

where E represents the incident gamma ray energy, [8].For determining the constants a–c it was necessary to perform

a real measurement with the real detector, measuring the multi-energy radionuclide standard source, emitting in the energy rangeof 46.5–1836.1 keV, described in detail in the next section. Asuccessive least-square interpolation of the experimental datagave the numerical values of the three parameters, which weresubsequently utilized for the GEB option of the Tally F8. Experi-mental data with the interpolating function (1) are showed inFig. 4 (correlation coefficient R2

¼0.9931). The values obtained forthe three constants, that were maintained unmodified for all thesuccessive simulation runs, are the following:

a¼0.0004 MeVb¼0.0010 MeV1/2

c¼0.0436 MeV�1

As statistical precision is concerned, the simulation runs carriedout were completely analogous, no variance reduction method hasbeen applied, and the number of histories has been chosen in orderto obtain an error comprised between 0.2% and 0.7%.

3. Validation of the simulation

The validation of the simulation was carried out by means of acertified filter type NPL ARAME source [20], with the radionuclidecomposition described in Table 1.

As geometry and materials are concerned, the filter has beenmodeled in the input code with an internal diameter of 7.6 cm, aninternal height of 0.8 cm, and a 0.35 cm thick wall envelope madeof fiber glass. For the fiber glass (0.13 g/cm3 density) a composi-tion of 58.00% SiO2, 8.00% Al2O3, 5.00% B2O3, 1.00% Na2O, 25.00%CaO, and 3.00% MgO has been assumed. The top and bottomlayers of the source, 0.078 cm thick, were modeled as PVC(H3C2Cl) with 1.4 g/cm3 density. For the experimental set-up,the source was positioned at 12 cm away from the BEGe detectorcrystal surface. A graphical description of the experimental set-upis given in Fig. 5, obtained through MCNPX Visual Editor.

For the described source and experimental set-up, the sto-chastic detection efficiencies given by the MCNPX simulationwere applied to a real gamma-ray spectrum measured with theBE3825 detector in order to determine radionuclide activitieswithin the source. These activities were then compared toreference values from the source standard and to results obtainedby applying the ISOCS [2] software to the same spectrum. TheISOCS template [2] was built with the same data utilized for theMCNPX input file.

3.1. Comparison vs. experimental data

For the experimental set-up in Fig. 5, Fig. 6 shows the resultsobtained with no collimation of the detector and a live time of3600 s. In particular, Fig. 6 shows the errors respect to referencevalues of the activities obtained with MCNPX, AMCNPX, and those

Fig. 5. Experimental set-up, ARAME source (1) with PVC encapsulation (2) is

positioned at 12 cm from the detector crystal surface (3).

Fig. 6. Percentage error vs. reference values—no collimation, Errors respect to

reference values of activities measured by MCNPX and ISOCS calibrations for the

experimental set-up shown in Fig. 5.

Fig. 7. Simulated and real spectra, Particular of experimental (discrete points)

and simulated (continuous line) spectra in the energy region of the two peaks of60Co.

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ones obtained with ISOCS, AISOCS. These two data sets, obtainedwith the detection efficiencies given by MCNPX and ISOCSseparately, are compared with the reference activities Aref interms of percentage errors, [(Ai–Aref)/Aref]%, with i¼MCNPX, ISOCS.

Simulated data were obtained performing a different run foreach gamma-ray energy of the source with between 100 and 600million particle histories. Taking into account the variation ofdetection efficiency vs. gamma-ray energy, a highest number ofhistories was utilized for higher energies, in order to accomplishstatistical errors comprised between 0.2% and 0.7% for the wholeenergy range. Statistical errors were multiplied by the efficiencyvalue obtained for each gamma-ray energy to yield the error oneach efficiency data point in Fig. 6, which also represents the errorfor simulated activities DAMCNPX. For the experimental data, theerror on each peak is generated directly by ISOCS GeometryComposer. For instance, the software generates a 15% maximumerror for the 210Pb peak. Such an error is then multiplied by thecorresponding ISOCS value of detection efficiency, giving the erroron the efficiency point at 0.0465 MeV, which is subsequentlyassumed as the error on measured activity, DAISOCS. By consider-ing the relative error, error bars of Fig. 6 are then calculated as(DAi/Ai)%, with i¼MCNPCX, ISOCS.

As may be noted from Fig. 6, MCNPX data show a goodagreement with ISOCS results and even better performances vs.certified data.

3.2. Comparison vs. experimental spectrum

Fig. 7 shows simulated and experimental spectra in the energyrange of 1.17–1.35 MeV. Simulated peaks of 60Co are in closeagreement with real ones. The real spectrum is represented as‘‘raw data’’, i.e. without application of algorithms for smoothingor area subtraction. MCNPX spectrum was obtained from histories

of photons only (tally F8 in ‘‘mode p’’ [8]), as a consequence,Compton continuum of each peak is not generated. The ‘‘mode p,e’’ would have allowed instead to follow the histories of electronsas well, but it would require much more running time. Anyway,full energy peaks are well reproduced and it is even possibleto note the germanium x-ray escape peak in the region of1.32–1.33 MeV.

To generate a simulated spectrum with the tally F8 forcomparison to the experimental measurement, the FWHM para-meters a–c of the GEB option were applied with a WGT card [8]defined as

WGT ¼ ðSiAiIgiÞt ð2Þ

where Ai is activity of each radionuclide, i present in the ARAMEsource; Igi is branching ratio of each emission and t is live time(3600 s).

4. Collimation effects

Further tests have been carried out with the same experi-mental set-up shown in Fig. 5 but with various detector collima-tions. For large collimation angles (opening apertures on thecollimator’s end between 901 and 1801), MCNPX and ISOCScalibrations produced similar detection efficiencies that tendedto be within 5–10% of each other. However, larger difference ofnearly 19% arose with small collimation angles, i.e. with openingapertures on the collimator’s end between 01 and 301.

Fig. 8 shows the same situation of Fig. 5 but with detectorendowed with an old 5 cm thick lead collimator with 301 apertureangle. Fig. 9 indicates detection efficiencies calculated by MCNPXand ISOCS for energies greater than about 0.4 MeV differ by anamount that is greater than the range of their respective errorbars. Fig. 10 shows how these differences influence the percen-tage error against reference values of the source.

5. Conclusions

Broad energy detectors, together with appropriate in situcalibration software, provide extraordinary capabilities for detect-ing 241Am and low gamma-ray energies associated with actinidealpha-emitters that greatly exceed the potentialities of traditionalgermanium coaxial detectors. Without and with collimation,differences between the MCNPX calibrated results and referencesource activities were generally within 5%. Without collimationthe ISOCS calibration exhibited slightly larger deviations for a fewgamma-ray emissions. With a small angled collimator, the ISOCScalibration produced differences of approximately 19% for gammarays with energies greater than 0.4 MeV. From ISPRA’s point ofview, collimated systems for in situ measurements should never

Fig. 8. Side view of collimated detector’s assembly, Obtained by means of

MCNPX Visual Editor. Lead collimator (1), 301 aperture (2), source (3), and

detector (4).

Fig. 9. Absolute detection efficiencies �301 collimation.

Fig. 10. Percentage error vs. reference values �301 collimation, Errors respect

to reference values of activities measured by MCNPX and ISOCS calibrations for

the experimental set-up shown in Fig. 8.

M. Altavilla, R. Remetti / Nuclear Instruments and Methods in Physics Research A 712 (2013) 157–161 161

make errors exceeding the ones declared in instrumentation’svalidation documents. That could lead to not bounded values forworkers’ doses estimations and radioactive contamination assess-ments, and could produce mistakes in discriminating betweenradioactive wastes and potentially clearable materials. The largerdeviations for ISOCS calibration approach, produced by collimatoralgorithms originally developed for HpGe detectors, might be dueto the different crystal configuration of broad energy detectorscompared to coaxial detectors; i.e. to a different importance of the

active area portion obscured by the collimator. Anyway, whendealing with measurement systems designed to operate in situ,mathematical collimator algorithms constitute an irreplaceabletool, both for the immediateness of response and for beingimplemented in software with user’s friendly input procedures.It is desirable that the MCNPX stochastic calibration proceduredeveloped in this work may constitute a useful tool for furtherimprovement of collimator algorithms.

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