| 1. |
- Sjöstrand, Henrik, 1978-, et al.
(författare)
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Propagation Of Nuclear Data Uncertainties For Fusion Power Measurements
- 2016
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Konferensbidrag (refereegranskat)abstract
- Fusion plasmas produce neutrons and by measuring the neutron emission the fusion power can be inferred. Accurate neutron yield measurements are paramount for the safe and efficient operation of fusion experiments and, eventually, fusion power plants.Neutron measurements are an essential part of the diagnostic system at large fusion machines such as JET and ITER. At JET, a system of activation foils provides the absolute calibration for the neutron yield determination. The activation system uses the property of certain nuclei to emit radiation after being excited by neutron reactions. A sample of suitable nuclei is placed in the neutron flux close to the plasma and after irradiation the induced radiation is measured. Knowing the neutron activation cross section one can calculate the time-integrated neutron flux at the sample position. To relate the local flux to the total neutron yield, the spatial flux response has to be identified. This describes how the local neutron emission affects the flux at the detector. The required spatial flux response is commonly determined using neutron transport codes, e.g., MCNP.Nuclear data is used as input both in the calculation of the spatial flux response and when the flux at the irradiation site is inferred. Consequently, high quality nuclear data is essential for the proper determination of the neutron yield and fusion power. However, uncertainties due to nuclear data are generally not fully taken into account in today’s uncertainty analysis for neutron yield calibrations using activation foils. In this paper, the neutron yield uncertainty due to nuclear data is investigated using the so-called Total Monte Carlo Method. The work is performed using a detailed MCNP model of JET fusion machine. In this work the uncertainties due to the cross sections and angular distributions in JET structural materials, as well as the activation cross sections, are analyzed. It is shown that a significant contribution to the neutron yield uncertainty can come from uncertainties in the nuclear data.
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| 2. |
- Birgersson, Evert, et al.
(författare)
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Binary fission-fragment yields from the reaction 251Cf(nth, f)
- 2005
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Ingår i: Nuclear fission and fission-product spectroscopy. - : American Institute of Physics. - 0735402884 ; , s. 349-352
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Konferensbidrag (refereegranskat)abstract
- The recoil mass spectrometer LOHENGRIN of the Laue-Langevin Institute, Grenoble has been used to measure the light fission-fragment mass yield and kinetic energy distributions from neutron-induced 252Cf*, using 251Cf as target material. ©2005 American Institute of Physics
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| 3. |
- Birgersson, Evert, et al.
(författare)
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Light fission-fragment mass distribution from the reaction 251Cf(nth, f)
- 2007
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Ingår i: Nuclear Physics A. - Amsterdam : Elsevier. - 0375-9474 .- 1873-1554. ; 791:1-2, s. 1-23
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Tidskriftsartikel (refereegranskat)abstract
- For mass numbers A = 80 to 124 the recoil mass spectrometer LOHENGRIN of the Institute Laue-Langevin in Grenoble was used to measure with high resolution the light fission-fragment mass yields and kinetic energy distributions from thermal-neutron induced fission of 252Cf* for the first time, using 251Cf as target material. The obtained mean light fragment mass AL = (107 ± 2) and the corresponding mean kinetic energy Ek,L = (103±2) MeV are within the expected trend. Emission yields around A = 115 are enhanced and the corresponding mean kinetic energy is higher compared to spontaneous fission of 252Cf. This could be explained by the existence of an additional super-deformed fission mode.
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| 4. |
- Fischer, Ulrich, et al.
(författare)
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Nuclear data activities of the EUROfusion consortium
- 2020
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Ingår i: ND 2019. - : EDP Sciences. - 9782759891061
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Konferensbidrag (refereegranskat)abstract
- The activities of the EUROfusion consortiums on the development of high quality nuclear data for fusion applications are presented. The activities, implemented in the Power Plant Physics and Technology (PPPT) programme of EUROfusion, include nuclear data evaluations for neutron and deuteron induced reactions and the production of related data libraries which satisfy the needs for nuclear analyses of the DEMO fusion power plant and the IFMIF-DONES neutron source. The activities are closely linked to the JEFF initiative of the NEA Data Bank. The evaluation work is complemented by extensive benchmark, sensitivity and uncertainty analyses to check the performance of the evaluated cross-section data and libraries against integral experiments.
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| 5. |
- Helgesson, Petter, 1986-
(författare)
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Experimental data and Total Monte Carlo : Towards justified, transparent and complete nuclear data uncertainties
- 2015
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The applications of nuclear physics are many with one important being nuclear power, which can help decelerating the climate change. In any of these applications, so-called nuclear data (ND, numerical representations of nuclear physics) is used in computations and simulations which are necessary for, e.g., design and maintenance. The ND is not perfectly known - there are uncertainties associated with it - and this thesis concerns the quantification and propagation of these uncertainties. In particular, methods are developed to include experimental data in the Total Monte Carlo methodology (TMC). The work goes in two directions. One is to include the experimental data by giving weights to the different "random files" used in TMC. This methodology is applied to practical cases using an automatic interpretation of an experimental database, including uncertainties and correlations. The weights are shown to give a consistent implementation of Bayes' theorem, such that the obtained uncertainty estimates in theory can be correct, given the experimental data. In the practical implementation, it is more complicated. This is much due to the interpretation of experimental data, but also because of model defects - the methodology assumes that there are parameter choices such that the model of the physics reproduces reality perfectly. This assumption is not valid, and in future work, model defects should be taken into account. Experimental data should also be used to give feedback to the distribution of the parameters, and not only to provide weights at a later stage.The other direction is based on the simulation of the experimental setup as a means to analyze the experiments in a structured way, and to obtain the full joint distribution of several different data points. In practice, this methodology has been applied to the thermal (n,α), (n,p), (n,γ) and (n,tot) cross sections of 59Ni. For example, the estimated expected value and standard deviation for the (n,α) cross section is (12.87 ± 0.72) b, which can be compared to the established value of (12.3 ± 0.6) b given in the work of Mughabghab. Note that also the correlations to the other thermal cross sections as well as other aspects of the distribution are obtained in this work - and this can be important when propagating the uncertainties. The careful evaluation of the thermal cross sections is complemented by a coarse analysis of the cross sections of 59Ni at other energies. The resulting nuclear data is used to study the propagation of the uncertainties through a model describing stainless steel in the spectrum of a thermal reactor. In particular, the helium production is studied. The distribution has a large uncertainty (a standard deviation of (17 ± 3) \%), and it shows a strong asymmetry. Much of the uncertainty and its shape can be attributed to the more coarse part of the uncertainty analysis, which, therefore, shall be refined in the future.
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| 6. |
- Helgesson, Petter, 1986-, et al.
(författare)
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Including experimental information in TMC using file weights from automatically generated experimental covariance matrices
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The Total Monte Carlo methodology (TMC) for nuclear data (ND) uncertainty propagation has been subject to some critique because the nuclear reaction parameters are sampled from distributions which have not been rigorously determined from experimental data. In this study, it is thoroughly explained how random ND files are weighted with likelihood function values computed by comparing the ND files to experimental data, using experimental covariance matrices generated from information in the experimental database EXFOR and a set of simple rules. A proof that such weights give a consistent implementation of Bayes' theorem is provided. The impact of the weights is mainly studied for a set of integral systems/applications, e.g., a set of shielding fuel assemblies which shall prevent aging of the pressure vessels of the Swedish nuclear reactors Ringhals 3 and 4.For many applications, the weighting does not have much impact, something which can be explained by too narrow prior distributions. Another possible explanation is that the integral systems are highly sensitive to resonance parameters, which effectively are not treated in this work. In other cases, only a very small number of files get significantly large weights, which can be due to the prior parameter distributions or model defects.Further, some parameters used in the rules for the EXFOR interpretation have been varied. The observed impact from varying one parameter at a time is not very strong. This can partially be due to the general insensitivity to the weights seen for many applications, and there can be strong interaction effects. The automatic treatment of outliers has a quite large impact, however. To approach more justified ND uncertainties, the rules for the EXFOR interpretation shall be further discussed and developed, in particular the rules for rejecting outliers, and random ND files that are intended to describe prior distributions shall be generated. Further, model defects need to be treated.
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| 7. |
- Helgesson, Petter, 1986-, et al.
(författare)
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Incorporating Experimental Information in the Total Monte Carlo Methodology Using File Weights
- 2015
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Ingår i: Nuclear Data Sheets. - : Elsevier BV. - 0090-3752 .- 1095-9904. ; 123:SI, s. 214-219
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Tidskriftsartikel (refereegranskat)abstract
- Some criticism has been directed towards the Total Monte Carlo method because experimental information has not been taken into account in a statistically well-founded manner. In this work, a Bayesian calibration method is implemented by assigning weights to the random nuclear data files and the method is illustratively applied to a few applications. In some considered cases, the estimated nuclear data uncertainties are significantly reduced and the central values are significantly shifted. The study suggests that the method can be applied both to estimate uncertainties in a more justified way and in the search for better central values. Some improvements are however necessary; for example, the treatment of outliers and cross-experimental correlations should be more rigorous and random files that are intended to be prior files should be generated.
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| 8. |
- Helgesson, Petter, 1986-, et al.
(författare)
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Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation
- 2016
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Ingår i: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier. - 0168-9002 .- 1872-9576. ; 807, s. 137-149
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Tidskriftsartikel (refereegranskat)abstract
- In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also be used in cases where the experimental uncertainties are not Gaussian, and for other purposes than to compute the likelihood, e.g., to produce random experimental data sets for a more direct use in ND evaluation.
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| 9. |
- Helgesson, Petter, 1986-, et al.
(författare)
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UO-2 Versus MOX: Propagated Nuclear Data Uncertainty for k-eff, with Burnup
- 2014
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Ingår i: Nuclear science and engineering. - 0029-5639 .- 1943-748X. ; 177:3, s. 321-336
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Tidskriftsartikel (refereegranskat)abstract
- Precise assessment of propagated nuclear data uncertainties in integral reactor quantities is necessary for the development of new reactors as well as for modified use, e.g. when replacing UO-2 fuel by MOX fuel in conventional thermal reactors.This paper compares UO-2 fuel to two types of MOX fuel with respect to propagated nuclear data uncertainty, primarily in k-eff, by applying the Fast Total Monte Carlo method (Fast TMC) to a typical PWR pin cell model in Serpent, including burnup. An extensive amount of nuclear data is taken into account, including transport and activation data for 105 isotopes, fission yields for 13 actinides and thermal scattering data for H in H2O.There is indeed a significant difference in propagated nuclear data uncertainty in k-eff; at 0 burnup the uncertainty is 0.6 % for UO-2 and about 1 % for the MOX fuels. The difference decreases with burnup. Uncertainties in fissile fuel isotopes and thermal scattering are the most important for the difference and the reasons for this are understood and explained.This work thus suggests that there can be an important difference between UO-2 and MOX for the determination of uncertainty margins. However, the effects of the simplified model are difficult to overview; uncertainties should be propagated in more complicated models of any considered system. Fast TMC however allows for this without adding much computational time.
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| 10. |
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