We found that the time interval analyzer ͑TIA, EG&G 914P͒ used in our experiment reported in our paper is flawed. When the time bin width is set to 100 ns ͑which is the one used in that experiment͒, this device adds some additional electric counts ͑for reasons we do not understand͒ at the beginning part of the spectrum right after the start signal. This leads to an incorrect larger number of counts for the first peak in our coincidence measurement of both the autocorrelation and the cross-correlation ͑Fig. 2a in our paper͒. During the process of improvement, we did that experiment with a new TIA device ͑FAST ComTec P7888͒, and under otherwise the same experimental condition, the first peak of the coincidence measurement gets smaller while the following peaks remain almost the same ͑see the new data in Fig. 1͒. When we changed the TIA back to EG&G 914P, we obtained the same signal as reported in our work. We then tested these two different TIA devices directly with known electric signals, and found that the problem was due to the EG&G 914P TIA device ͑we have two EG&G 914P devices in our lab, and we find both of them have the same problem when the time bin width is set to 100 ns͒. With the new recorded data as shown in Fig. 1, we do not find violation of the Cauchy-Schwarz inequality under the same experimental condition. So we conclude that the violation of the Cauchy-Schwarz inequality reported in our paper is due to the experimental flaw as described above.We thank J. Pan for helpful discussion.FIG. 1. ͑Color online͒ Experimental condition is the same as that described in Fig. 2 of our paper except for a larger repetition rate.PHYSICAL REVIEW A 73, 069907͑E͒ ͑2006͒
In this study, the relationship between impact toughness and microstructure in Cr-Mo-V multi-pass weld metals has been systematically investigated. The Charpy impact energy of two weld metals with various alloy elements increased remarkably. The primary cause of the change of impact toughness was attributed to the difference of acicular ferrite (AF) content and prior-austenite grain size, and the size and distribution of necklace martensite-austenite (M-A) constituents. With increasing Ti content, Ti-containing inclusions were increased, which resulted in an increased number of nucleation sites for AF, a change in the microstructure from allotriomorphic ferrite to AF, and refined ferrite grain size. In addition, smaller and more dispersive M-A constituents were observed in the weld metal with higher impact toughness.
The potential-driving model is used to describe the driving potential distribution and to calculate the pre-neutron emission mass distributions for different incident energies in the
reaction. The potential-driving model is implemented in Geant4 and used to calculate the fission-fragment yield distributions, kinetic energy distributions, fission neutron spectrum and the total nubar for the
reaction. Compared with the built-in G4ParaFissionModel, the calculated results from the potential-driving model are in better agreement with the experimental data and evaluated data. Given the good agreement with the experimental data, the potential-driving model in Geant4 can describe well the neutron-induced fission of actinide nuclei, which is very important for the study of neutron transmutation physics and the design of a transmutation system.
Abstract:The flow behavior of . %Si alloys during hot compression was investigated at temperatures 650-950 • C and strain rates 0.01-10 s −1 . The results showed that the flow stress depended distinctly on the deformation temperatures and strain rates. The flow stress and work hardening rate increased with the decrease of temperature and the increase of strain rate. The activation energy under all the deformation conditions was calculated to be 410 kJ/mol. The constitutive equation with hyperbolic sine function and Zener-Hollomon parameter was developed. The peak stress, critical stress, and steady-state stress could be represented as σ = A + Bln(Z/A). Dynamic recrystallization occurred under the deformation conditions where the values of Z were lower than 10 20 . Processing maps were established to optimize the processing parameters. The power dissipation efficiency decreased in the high temperature and low strain rate region, increased in the high temperature and high strain rate region, and remained unchanged in other regions with the increase of true strain. Furthermore, the unstable area expanded. The true strain of 0.7 was the optimum reduction according to the processing map. Based on the analysis of surface quality, microstructures, and ordered structures, the optimized processing parameters for the Fe-6.5wt. %Si alloys were the temperature and strain rate of higher than 900 • C and 0.01-10 s −1 , respectively, or 800-900 • C and lower than 0.4 s −1 , respectively.
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