[en] The modelling of irradiation-induced damage of RPV steels from primary cascades up to the change of mechanical properties bridging length scales from the atomic level up to the macro-scale and time scales up to years contributes essentially to an improved understanding of the phenomenon of neutron embrittlement. In future modelling may become a constituent of the procedure to evaluate RPV safety. The selected two-step approach is based upon the coupling of a rate-theory module aimed at simulating the evolution of the size distribution of defect-solute clusters with a hardening module aimed at predicting the yield stress increase. The scope of the investigation consists in the development and validation of corresponding numerical tools. In order to validate these tools, the output of representative simulations is compared with results from small-angle neutron scattering experiments and tensile tests performed for neutron-irradiated RPV steels. Using the developed rate-theory module it is possible to simulate the evolution of size, concentration and composition of mixed Cu-vacancy clusters over the relevant ranges of size up to 10.000 atoms and time up to tens of years. The connection between the rate-theory model and hardening is based upon both the mean spacing and the strength of obstacles for dislocation glide. As a result of the validation procedure of the numerical tools, we have found that essential trends of the irradiation-induced yield stress increase of Cu-bearing and low-Cu RPV steels are displayed correctly. First ideas on how to take into account the effect of Ni on both cluster evolution and hardening are worked out.

[en] The BMWi project 1501393 aimed at contributing to the clarification of flux effects and late blooming effects in irradiated RPV steels by means of experimental techniques of sensitivity at the nm scale. The investigation of these effects was focussed on RPV steels, both base metal and weld of German reactors selected according to the objectives of the present project from two previous projects performed at AREVA GmbH. The complementary techniques of small-angle neutron scattering, atom probe tomography and positron annihilation spectroscopy were applied to detect and characterize the irradiation-induced nm-scale defect-solute clusters. A flux effect on the size of the irradiation-induced clusters but no flux effect on both cluster volume fraction and mechanical properties was found. For a low-Cu RPV weld, a late blooming effect was observed, which results in a steep slope of both cluster volume fraction and transition temperature shift after an initial stage of small or no change.

[en] Using blobs allows modeling the CT system's geometry more correctly within an iterative reconstruction framework. However their application comes with an increased computational demand. This led us to use blobs for image representation and a dedicated GPU hardware implementation to counteract their computational demand. Making extensive use of the texture interpolation capabilities of CUDA and implementing an asymmetric projector/backprojector pair we achieve reasonable processing times and good system modeling at the same time. (orig.)

[en] X-ray CT measures the attenuation of polychromatic x-rays through an object of interest. The CT data acquired are the negative logarithm of the relative x-ray intensity after absorption. These data must undergo water precorrection to linearize the measured data and convert them into line integrals through the patient that can be reconstructed to yield the final CT image. The function to linearize the measured projection data depends on the tube voltage U. In most circumstances, CT scans are carried out with a constant tube voltage. For those cases there are dozens of different techniques to carry out water precorrection. In our case the tube voltage is rather modulated as a function of the object. We propose an empirical cupping correction (ECCU) algorithm to correct for CT cupping artifacts that are induced by nonlinearities in the projection data. The method is rawdata based, empirical and requires neither knowledge of the x-ray spectrum nor of the attenuation coefficients. It aims at linearizing the attenuation data using a precorrection function of polynomial form in the polychromatic attenuation data q and in the tube voltage U. The coefficients of the polynomial are determined once using a calibration scan of a homogeneous phantom. The coefficients are computed in the image domain by fitting a series of basis images to a template image. The template image is obtained directly from the uncorrected phantom image and no assumptions on the phantom size or of its positioning are made. Rawdata are precorrected by passing them through the once-determined polynomial. Numerical examples are shown to demonstrate the quality of the precorrection. ECCU is achieved to remove the cupping artifacts and to obtain well-calibrated CT values. A combination of ECCU with analytical techniques yielding a hybrid cupping correction method is possible and allows for channel-dependent correction functions.

[en] In computed tomography there are different situations where reconstruction has to be performed with limited raw data. In the past few years it has been shown that algorithms which are based on compressed sensing theory are able to handle incomplete datasets quite well. As a cost function these algorithms use the l₁-norm of the image after it has been transformed by a sparsifying transformation. This yields to an inequality-constrained convex optimization problem. Due to the large size of the optimization problem some heuristic optimization algorithms have been proposed in the past few years. The most popular way is optimizing the raw data and sparsity cost functions separately in an alternating manner. In this paper we will follow this strategy and present a new method to adapt these optimization steps. Compared to existing methods which perform similarly, the proposed method needs no a priori knowledge about the raw data consistency. It is ensured that the algorithm converges to the lowest possible value of the raw data cost function, while holding the sparsity constraint at a low value. This is achieved by transferring the step-size determination of both optimization procedures into the raw data domain, where they are adapted to each other. To evaluate the algorithm, we process measured clinical datasets. To cover a wide field of possible applications, we focus on the problems of angular undersampling, data lost due to metal implants, limited view angle tomography and interior tomography. In all cases the presented method reaches convergence within less than 25 iteration steps, while using a constant set of algorithm control parameters. The image artifacts caused by incomplete raw data are mostly removed without introducing new effects like staircasing. All scenarios are compared to an existing implementation of the ASD-POCS algorithm, which realizes the step-size adaption in a different way. Additional prior information as proposed by the PICCS algorithm can be incorporated easily into the optimization process.

[en] Neutron irradiation of reactor pressure vessel steels leads to the formation of nano-sized defects which can deteriorate the material. An understanding of the microstructural evolution of the material is important for making reliable security assessments about possible future long-term operation of nuclear power plants. So-called late-blooming phases are formed after long-term irradiation and lead to considerable material ageing effects. Encouraging factors for the formation of these phases are a low Cu-content, moderate to high contents of Mn and Ni, low irradiation temperatures and different neutron fluxes. Positron annihilation lifetime spectroscopy which is ideally suited for the detection and characterization of these irradiation-induced defects was applied for different selected materials which fulfill these conditions in order to investigate the occurrence and behavior of these phases.

[en] The effects of lattice vibration on the thermodynamics of nanosized coherent clusters in bcc-Fe consisting of vacancies and/or copper are investigated within the harmonic approximation. A combination of on-lattice simulated annealing based on Metropolis Monte Carlo simulations and off-lattice relaxation by molecular dynamics is applied to obtain the most stable cluster configurations at T = 0 K. The most recent interatomic potential built within the framework of the embedded-atom method for the Fe-Cu system is used. The total free energy of pure bcc-Fe and fcc-Cu as well as the total formation free energy and the total binding free energy of the vacancy-copper clusters are determined for finite temperatures. Our results are compared with the available data from previous investigations performed using many-body interatomic potentials and first-principles methods. For further applications in rate theory and object kinetic Monte Carlo simulations, the vibrational effects evaluated in the present study are included in the previously developed analytical fitting formulae. (paper)

[en] Reactor pressure vessel (RPV) steel, when exposed to neutron irradiation, induces the formation of nano-sized features. Using small angle neutron scattering (SANS) we have studied the neutron fluence dependence of the precipitate volume fraction for high-Cu and low-Cu materials separately. Cu-rich precipitates have long been recognized to play the dominant role in embrittlement of Cu-bearing RPV steels. In contrast, Mn–Ni-rich precipitates seem to govern embrittlement in the case of low levels of impurity Cu. The objective is to work out the resulting differences from the microstructural point of view. For low-Cu materials, the volume fraction was found to be within the detection limit of SANS at fluences below an apparent threshold fluence, whereas the slope increases considerably beyond. The relationship between irradiation-induced yield stress increase and precipitate volume fraction was also considered. We have derived estimates of the obstacle strength for Cu-rich precipitates and for Mn–Ni-rich precipitates.

[en] Highlights: • JRQ steel was irradiated by Fe²⁺ ions in order to simulate neutron damage. • Hardening was investigated and observed by means of nanoindentation technique. • Defect profile was measured by slow-positron Doppler broadening spectroscopy. • Open volume defects were excluded from a responsibility for the damage arising. • Hardening features are the same in neutron and ion irradiated material. A model reactor pressure vessel (RPV) steel, known as JRQ, was manufactured in Japan for IAEA neutron embrittlement research studies in late 80 s. This model alloy belongs to the commercially used steel of A533B-1 type and shows relatively large changes in mechanical properties after a neutron irradiation due to considerable copper content (0.15 wt%). In order to simulate neutron irradiation and investigate the hardening effect, studied specimens of JRQ steel were exposed to Fe²⁺ ion irradiation in five different exposures calculated using the SRIM code. The ion energy of 5 MeV, temperature at 300 °C and the flux of 1.0 × 10¹¹ cm⁻² s⁻¹ were the same during the irradiations. The hardening was investigated and observed by means of nanoindentation technique and a defect profile of irradiated steels was measured by Slow-positron Doppler broadening spectroscopy (DBS). The observed increasing trend of nanohardness as a function of fluence is in good agreement with the trend observed on the basis of Vickers hardness measured for neutron-irradiated JRQ. This confirms that Cu precipitation is most likely responsible for the observed irradiation hardening and that neutron-irradiation-induced damage can be simulated using ion irradiation in the present case. We have also excluded open volume (vacancy type) defects in the crystal lattice of JRQ steel from a responsibility for the damage arising by the Fe²⁺ ion irradiation.

[en] Oxide dispersion strengthening of high-Cr steels is a well-recognized way to extend the application window including nuclear applications for this class of materials. The experimental investigation of model alloys of less complexity is important in order to separate individual influence factors and to understand the irradiation behaviour. The present work is devoted to the mechanical properties of ODS Fe-9wt%Cr alloys produced by means of spark plasma sintering. The range of material conditions covers contents of nanodispersed yttria of 0 (reference), 0.3 wt%, and 0.6 wt% as well as variations of the milling time. Results obtained for the density, elastic properties, hardness, tensile behaviour, and brittle-ductile transition are reported, and the effect of ODS content and PM process parameters is discussed. (orig.)