Benoit Geslot
email: benoit.geslot@cea.fr

Adrien Gruel

Paul Ros

Patrick Blaise

Pierre Leconte

Gilles Noguere

Ludovic Matthieu

David Villamarin

Vicente Becares

Arjan Plompen

Stefan Kopecky

Peter Schillebeeckx

Americium-241 integral radiative capture cross section in overmoderated neutron spectrum from pile oscillator measurements in the Minerve reactor

An experimental program, called AMSTRAMGRAM, was recently conducted in the Minerve low power reactor operated by CEA Cadarache. Its aim was to measure the integral capture cross section of 241 Am in the thermal domain. Motivation of this work is driven by large differences in this actinide thermal point reported by major nuclear data libraries. The AMSTRAMGRAM experiment, that made use of well characterized JRC-IMM americium samples, was based on the oscillation technique commonly implemented in the Minerve reactor. First results are presented and discussed in this article. A preliminary calculation scheme was used to compare measurements to calculated values. It is shown that this work confirms a bias previously observed with JEFF3.1.1 (C/E-1 = -10.5 ± 4 %). On the opposite, the experiment is in close agreement with 241 Am thermal point reported by JEFF3.2 (C/E-1 = -0.5 ± 4 %).

Introduction

For nearly 10 years, several experiments have been conducted to improve 241 Am radiative capture cross section. Indeed, evaluated cross sections from major libraries differ from 10 % to 15 %, especially in the thermal domain [1][2]. For instance, a difference of 9 % on the thermal point can be observed between JEFF3.2 and ENDF-B.VII.1 nuclear data libraries. An international collaborative working group organized by NEA-OECD started in 2015 with the aim of explaining such discrepancies [3].

In this framework, an experimental program was recently conducted by CEA Cadarache in the Minerve reactor. Its main objective was to measure 241 Am integral capture cross section in a very thermal neutron spectrum, providing valuable information on the 241 Am thermal point, with a target accuracy of 3 % (1σ).

This experiment made use of 7 americium samples manufactured by ITE Karlsruhe in the framework of a previous collaboration between JRC-IRMM and CEA [4]. Measurements setup was based on the reactivity oscillator technique commonly implemented in Minerve [5]. Gold and lithium samples with the same geometry as americium samples were used for calibration.

Experimental setup

Reactor configuration

Minerve is a pool type reactor operated at low power (100 W maximum). Its core is made of two parts: -a driver zone (DZ) with highly enriched uranium/aluminum assemblies and surrounded by graphite reflector blocks ; -an experimental zone (EZ) in which 3% enriched UO2 fuel rods are loaded in a square lattice with a pitch of 1.26 cm. At the center of the experimental zone, an irradiation channel makes it possible to introduce various material samples in the core. Samples are held in an oscillator that is used to perform pile oscillator experiments. Samples reactivity worth (in the range of a few pcm) are obtained and compared against reference materials.

In the AMSTRAMGRAM configuration, a water hole is arranged at the center of the experimental zone. Its dimensions (roughly 4.4 cm in radius) were chosen so as to maximize the moderation ratio at the oscillation location.

The neutron spectrum in the oscillation channel exhibits a strong thermal component, as shown on Fig. 1. The reactivity sensitivity to the americium cross section is also plotted (dotted curve). It shows that the thermal domain (below the first resonance at 0.3 eV) accounts for around 80 % of the reactivity.

Americium samples

Americium samples used in this work were manufactured by ITE Karlsruhe from on raw material given by CEA Marcoule. They were previously irradiated at JRC-IRMM for the measurement of the 241 Am(n,2n) cross section [4].

Samples are made of 241 AmO2 and Al2O3 powders mixed and pressed into pellets or 12 mm in diameter and 2 mm thickness and then encapsulated in aluminum containers (see drawing on Fig. 3).

Americium mass is around 40 mg diluted in roughly 400 mg of alumina.

Additional samples

Calibration of the measurement process is obtained by using disks of reference material in dummy containers. Gold disks (Ø10 mm, 0.125 mm thick) and lithium disks (Ø10 mm, 0.2 mm thick) of high purity for purchased.

Additional samples loaded with 400 mg alumina pellets were also measured in order to obtain the reactivity per gram of alumina matrix.

Data processing

The reactivity oscillator technique

Oscillation techniques are based on creating a weak and localized perturbation in a characterized neutron flux. Its characteristics (amplitude, neutron spectrum) can be connected to physical parameters of the perturbation source (i.e. isotopic cross sections).

Oscillation techniques can be classified in function of 3 main parameters: use of a power compensation system, the oscillator frequency, the detector location. Detailed information can be found in the literature [START_REF] Foell | Small-sample reactivity measurements in nuclear reactors[END_REF].

The technique performed in Minerve is called « reactivity oscillator ». It is based on the compensation of the reactivity perturbation induced by the sample motion in the core. The reactor is kept critical using a rotating cadmium rod, which is driven by a monitor boron chamber, located in the reflector, through a retro-active loop.

The measured signal is given by the cadmium rod rotation angle. It is proportional to the small sample reactivity worth. This can be expressed using the exact perturbation theory (EPT).

Let 1 be a reactor state perturbed by a small reactivity sample and 0 be the reference state. P and L refer to operators of production and absorption, λ = 1/k where k is the multiplication factor and Ψ and Ψ + are direct and adjoint fluxes. Then, the reactivity difference between the two reactor states can be expressed as:

0 0 1 0 1 1 | ( ) | P L P λ δ δ δρ + + Ψ - Ψ = Ψ ⋅ Ψ (1)
Making the assumption that the test sample is a pure absorber, a first order approximation gives:

0 0 0 0 0 | | L P δ δρ + + Ψ -Ψ ≈ Ψ ⋅ Ψ (2)
In the reference state, which is the same for every sample, the irradiation channel is filled with an aluminum rod. It is then possible to calculate ratios of δρ against a reference material, like gold or lithium:

( ) ( ) 0 0 0 0 ref ref E drdE E drdE σ δρ δρ σ + + Ψ Ψ = Ψ Ψ ∫ ∫ ∫ ∫ (3)
Introducing a correction factor f(σ): ( ) ( )

( ) ( ) 0 0 0 ( ) E drdE f E drdE σ σ σ + Ψ Ψ = Ψ ∫ ∫ ∫ ∫ , (4)
0 0 ( ) ( ) ref ref ref E drdE f f E drdE σ δρ σ δρ σ σ Ψ = Ψ ∫ ∫ ∫ ∫ (5)
In the previous equation, the left hand side term is directly obtained from the experiment. The right hand side term is divided into two factors. The first one can be calculated using a deterministic code like APOLLO2 in a 2D geometry and the second one can be precisely calculated from a TRIPOLI4.10 simulation.

Measurement setup

One americium sample is worth about -0.2 pcm in reactivity, which is quite low compared to the measurement range (~10 pcm).

In order to increase the signal to noise ratio of the measurement, several samples were oscillated at the same time. For that purpose, up to 5 americium samples (and up 7 gold samples) were loaded column-wise in a sample container. The container was made of aluminum alloy 5754 and sealed by screw-in plugs. It was placed in an oscillator tube along with aluminum rods (alu 5754 as well) so that its mid-plane was aligned with the core mid-plane when the oscillator was in its lower position.

Measurements were composed of sets of 5 oscillation cycles with 120 s period. Acquisition was trigged by the oscillator control system and recorded data included 3 analog signals: oscillator position, current of the boron chamber and angle of the cadmium rod versus time.

Every measurement gave 5 values of the rod angle difference between upper and lower position of the sample in the core. For each oscillator loading, measurements were reproduced at least 5 times. If results were consistent (based on a χ² test), measurements were averaged to obtain a mean value.

To extract the reactivity worth of an isotope of interest, it is necessary to subtract any signal coming from the matrix (alumina) and the container (clad and aluminum wedges). Indeed, at first order, the overall reactivity can be linearly divided into a sum of individual components:

sample Am alu clad δρ δρ δρ δρ = + + (3)
Last terms in eq. ( 3) can be obtained by oscillating dedicated samples (empty clads or samples loaded with alumina only). Corrections should take into account any significant mass differences between samples.

Uncertainties management

Sources of uncertainties that affect the measurement are numerous and difficult to model. They come from mechanical fluctuation in the oscillator, electronic perturbation in signal recording, core evolution during the program, etc.

An empirical approach is used to estimate two overall sources of uncertainties: one responsible for variation amongst oscillation cycles, referred to as "repeatability", and another one responsible for any fluctuation from one measurement to the other, called "reproducibility". Those uncertainty sources are supposed to be independent from signal level. Measurements are also assumed to be uncorrelated.

Under those assumptions, the repeatability can be estimated as the intra-class variance of oscillation cycles Sij(ε) and the reproducibility can be viewed as the interclass variance of the whole measurements Si(ε).

( ) ( ) ( ) 2 2 , , 1 ˆ1 e ij i i j S S p N ε σ ε ε = - ⋅ -∑ (6)
( ) ( ) ( )

2 2 1 ˆ1 c i i S S N ε σ ε ε = - -∑∑ (7) ( ) ( ) ( ) , 1 1
ij i i j i S S S n p n ε ε ε ε ε = = × ∑ ∑ (8)
The final uncertainty affecting the reactivity worth of sample ε from n measurements of p cycles is expressed as:

2 2 ˆê c n p n ε σ σ σ = + ⋅ (9)

Experimental results

Raw signals (in angular unit) are converted in reactivity unit (cent) using a calibration coefficient. It is obtained by measuring the core reactivity (by reactor doubling time) at various cadmium rod angular positions. This coefficient may be somehow imprecise but note that is has no impact on reactivity ratios. Results are given in the Table 1. The value given for 241 Am is obtained by subtracting the reactivity from the alumina matrix, which amplitude is about 2 % (positive) of the overall signal (negative). When several samples were piled in a sample container, a small shadow effect between samples was observed in the case of lithium and gold. This effect was corrected by extrapolating the reactivity per mass unit measured for different sample loadings down to the average sample mass.

Final mass reactivity ratios is 6.27 in the case of americium / gold and 2.85 in the case of americium / lithium.

4 Preliminary feedback on nuclear data 4.1 Calculation scheme A two-step preliminary calculation scheme was built to calculate the right hand side terms of equation (5).

In a first step, deterministic code APOLLO2 is used to calculate direct and adjoint fluxes and reaction rate of samples in a simplified 2D reactor model of the experimental zone. Factors defined in equation ( 4) are obtained for each oscillated sample.

In a second step, a simplified calculation based on TRIPOLI4.10 Monte Carlo code is used to calculate reaction rates in 3D realistic sample models. A neutron spectrum previously obtained from a 3D core Monte Carlo calculation is used as an input of that simplified calculation.

Preliminary calculated values

In a more evolved interpretation scheme, several correction factors should be applied in order to get rid of modelling biases and obtain more precise results.

A clear trend can still be derived from this preliminary scheme. Indeed a 10 % difference is obtained in the C/E-1 value when comparing calculation using libraries JEFF3.1.1 and JEFF3.2. This confirms a similar trend observed in UOx-PWR and MOx-PWR spectra obtained from the OSMOSE program performed in Minerve [START_REF] Antony | Proceedings of 1 st Int. Conf. on Advancements in Nuclear Instrumentation, Measurement Methods and their Applications[END_REF][START_REF] Bernard | [END_REF].

Moreover, it is observed that the preliminary JEFF3.2 comparison with experiment is very close to 0. Since reactivity sensitivity to 241 Am capture cross section is around 0.8 for the thermal domain, this result support very closely 241 Am thermal point as reported by JEFF3.2.

Conclusions

This paper presents preliminary experimental results from the AMSTRAMGRAM program conducted by CEA in the Minerve reactor. A very thermal neutron spectrum was designed for the experiment that aimed at providing a new integral measurement of 241 Am radiative capture cross section with target uncertainty of less than 3 %. The experiment, based on the pile oscillation technique, was only possible thanks to JRC-IRMM that provided several well characterized americium samples. Analysis shows that a clear trend when comparing measurements to calculations associated to JEFF3.1.1 and JEFF3.2 libraries. First results are in very good agreement with JEFF 3.2 thermal point (662.5 b). This work was conducted in the framework of the CHANDA international collaboration that regroups CIEMAT, JRC-IRMM, CNRS and CEA.

Fig. 1 .

 1 Fig. 1. Drawing of the AMSTRAMGRAM experimental zone.

Fig. 2 .

 2 Fig. 2. Neutron spectrum in the oscillation channel (solid curve) and cumulative sensitivity of core reactivity to 241 Am capture cross section (dotted line).

Fig. 3 .

 3 Fig. 3. Drawing of JRC-IRMM americium samples

  -8 1E-7 1E-6 1E-5 1E-4 1E-3 1E-2 1E-1 1E+0 1E+1Cumulative sensitivity (a.u.) Neutron flux (a.u.) can be rewritten as follows:

Table 1 .

 1 Reactivity per mass unit for test materials.

	Material	Mass (mg)	Mass reactivity (cent/g)
	Al2O3	396	0.009
	197 Au	185.4	-0.707
	nat Li	83.8	-12.54
	241 Am	41.5	-4.442

Table 2 .

 2 Calculation over experiment for JEFF3.1.1 and JEFF3.2.

	Library	Thermal point (b)	Resonance Integral (b)	C/E -1 (%)
	JEFF3.1.1	662.549	1689,17	-10.5 ± 4
	JEFF3.2	764.397	1995,96	-0.5 ± 4


Mireille Lefèvre

Isabelle Blanc

Benoît Gschwind

Thierry Ranchin

Kamila M Drebszok

Artur Wyrwa

Loss of Life Expectancy related to temporal evolution of PM2.5 considered within energy scenarios in Europe

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Contact:

Web Site: Loss of Life Expectancy related to temporal evolution of PM 2.5 considered within energy scenarios in Europe  United Nations [2] for the 5-years cohorts size and mortality rates per country, from 1950 to 2100. The population under concern is people older than 30 years in year 2005.  SEDAC [3] for density maps of population in years 2005, 2010 and 2015.  Pope (2002) [4] for the relative risk value for a population older than 30 years exposed to PM 2.5 .

 Algorithm based on the approach recommended by the « Task Force on Health » [5] and IIASA [1] : loss of life expectancy is the difference between life expectancy calculated with PM 2.5 concentrations observed along the population lifetime, and life expectancy without exposure.  Temporal interpolations of PM 2.5 concentrations performed in the scenarios (from 2005 to 2050) along the population lifetime.



  Significant difference in results of about 20% with lower impacts for the dynamic model which takes into account the temporal evolution of the pollutant concentrations.  More realistic approach in the framework of scenarios comparison. Baseline scenario : current European legislation with the objective to reduce some pollutants and more specifically PM 2.5 , fine particulates of 2.5 µm size.  Evaluation of different electricity energy scenarios compared to the baseline, studying their impacts on life expectancy.  Static standard evaluation: PM 2.5 concentration is considered constant during the exposed lifetime of the population. Energy scenarios horizon : 2050.  Important variation of PM 2.5 exposure during the population whole lifetime.  Proposal of a dynamic method to compare scenarios accounting for their temporal dimension.Loss of life expectancy for the population older than 30 years in 2005, in the static approach (top) and dynamic one (bottom) for the baseline energy scenario.Resolution 20 km x 20 km.

Fine

  particulates: a major pollutant for human health Conclusions mireille.lefevre@mines-paristech.fr www.oie.mines-paristech.fr Necessity to integrate the temporal dimension of scenarios Loss of Life Expectancy: a key indicator to compare impacts from energy scenarios  IIASA [1] for PM 2.5 concentration maps derived from GAINS model for the baseline scenario in years 2005, 2030, 2040 and 2050.

Data sources

[1] International Institute for Applied Systems Analysis, Austria. [2] United Nations, Department of Economic and Social Affairs, Population Division. The 2010 Revision of the World Population Prospects. [3] SEDAC : Socio Economic Data and Applications Center, center for International Earth Science Information Network (CIESIN), Columbia University. Gridded Population of the World (v3). [4] Pope, C. et al. 2002. Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. Jama-Journal of the American Medical Association, 287: 1132-1141. [5] TFH. 2003. Modelling and assessment of the health impact of particulate matter and ozone. EB.AIR/WG.1/2003/11, United Nations Economic Commission for Europe, Task Force on Health, Geneva. The research leading to these results receives funding from European Community's Seventh Framework Programme (FP7, 2007-2013) under Grant Agreement Number 226364.

Accounting for the dynamic of the scenario

Maps of impacts on human health