Residual stress characterization of single and triple-pass autogenously welded stainless steel pipes

Using neutron diffraction the components of the residual stress field have been determined in the region near a mid-length groove in two identical austenitic stainless pipes in which weld beads had been laid down. One pipe sample had a single pass, and the second a triple pass, autogenous weld deposited around the groove circumference. The results show the effect on the stress field of the additional weld deposited and are compared to the results of Finite Element Modelling. The hoop stress component is found to be generally tensile, and greater in the triple pass weldment than in the single pass weldment. The hoop stresses reach peak values of around 400 MPa in tension. X-ray measurements of the residual stress components on the near inner surface of the pipe weldments are also presented, and show tensile stresses in both pipes, with a higher magnitude in the three-pass weldment

Heterogeneous Batch Distillation Processes: Real System Optimisation

In this paper, optimisation of batch distillation processes is considered. It deals with real systems with rigorous simulation of the processes through the resolution full MESH differential algebraic equations. Specific software architecture is developed, based on the BatchColumn® simulator and on both SQP and GA numerical algorithms, and is able to optimise sequential batch columns as long as the column transitions are set. The efficiency of the proposed optimisation tool is illustrated by two case studies. The first one concerns heterogeneous batch solvent recovery in a single distillation column and shows that significant economical gains are obtained along with improved process conditions. Case two concerns the optimisation of two sequential homogeneous batch distillation columns and demonstrates the capacity to optimize several sequential dynamic different processes. For such multiobjective complex problems, GA is preferred to SQP that is able to improve specific GA solutions

Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks

Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training

Gamow-Teller Strength in the Region of 100^{100}Sn

New calculations are presented for Gamow-Teller beta decay of nuclei near $^{100}$Sn. Essentially all of the $^{100}$Sn Gamow-Teller decay strength is predicted to go to a single state at an excitation energy of 1.8 MeV in $^{100}$In. The first calculations are presented for the decays of neighboring odd-even and odd-odd nuclei which show, in contrast to $^{100}$Sn, surprisingly complex and broad Gamow-Teller strength distributions. The results are compared to existing experimental data and the resulting hindrance factors are discussed.Comment: 12 pages (latex) and 2 figures available on reques

Overconstrained estimates of neutrinoless double beta decay within the QRPA

Estimates of nuclear matrix elements for neutrinoless double beta decay (0nu2beta) based on the quasiparticle random phase approximations (QRPA) are affected by theoretical uncertainties, which can be substantially reduced by fixing the unknown strength parameter g_pp of the residual particle-particle interaction through one experimental constraint - most notably through the two-neutrino double beta decay (2nu2beta) lifetime. However, it has been noted that the g_pp adjustment via 2\nu2\beta data may bring QRPA models in disagreement with independent data on electron capture (EC) and single beta decay (beta^-) lifetimes. Actually, in two nuclei of interest for 0nu2beta decay (Mo-100 and Cd-116), for which all such data are available, we show that the disagreement vanishes, provided that the axial vector coupling g_A is treated as a free parameter, with allowance for g_A<1 (``strong quenching''). Three independent lifetime data (2nu2beta, EC, \beta^-) are then accurately reproduced by means of two free parameters (g_pp, g_A), resulting in an overconstrained parameter space. In addition, the sign of the 2nu2beta matrix element M^2nu is unambiguously selected (M^2nu>0) by the combination of all data. We discuss quantitatively, in each of the two nuclei, these phenomenological constraints and their consequences for QRPA estimates of the 0nu2beta matrix elements and of their uncertainties.Comment: Revised version (27 pages, including 10 figures), focussed on Mo-100 and Cd-116. To appear in J. Phys. G: Nucl. Phys. (2008

Minimizing material consumption of 3d printing with stress-guided optimization

3D printing has been widely used in daily life, industry, architecture, aerospace, crafts, art, etc. Minimizing 3D printing material consumption can greatly reduce the costs. Therefore, how to design 3D printed objects with less materials while maintain structural soundness is an important problem. The current treatment is to use thin shells. However, thin shells have low strength. In this paper, we use stiffeners to stiffen 3D thin-shell objects for increasing the strength of the objects and propose a stress guided optimization framework to achieve minimum material consumption. First, we carry out finite element calculations to determine stress distribution in 3D objects and use the stress distribution to guide random generation of some points called seeds. Then we map the 3D objects and seeds to a 2D space and create a Voronoi Diagram from the seeds. The stiffeners are taken to be the edges of the Voronoi Diagram whose intersections with the edges of each of the triangles used to represent the polygon models of the 3D objects are used to define stiffeners. The obtained intersections are mapped back to 3D polygon models and the cross-section size of stiffeners is minimized under the constraint of the required strength. Monte-Carlo simulation is finally introduced to repeat the process from random seed generation to cross-section size optimization of stiffeners. Many experiments are presented to demonstrate the proposed framework and its advantages

Large-space shell-model calculations for light nuclei

An effective two-body interaction is constructed from a new Reid-like $NN$ potential for a large no-core space consisting of six major shells and is used to generate the shell-model properties for light nuclei from $A$=2 to 6. (For practical reasons, the model space is partially truncated for $A$=6.) Binding energies and other physical observables are calculated and compare favorably with experiment.Comment: prepared using LaTex, 21 manuscript pages, no figure

Neutrinoless Double Beta Decay in Gauge Theories

Neutrinoless double beta decay is a very important process both from the particle and nuclear physics point of view. Its observation will severely constrain the existing models and signal that the neutrinos are massive Majorana particles. From the elementary particle point of view it pops up in almost every model. In addition to the traditional mechanisms, like the neutrino mass, the admixture of right handed currents etc, it may occur due to the R-parity violating supersymmetric (SUSY) interactions. From the nuclear physics point of view it is challenging, because: 1) The relevant nuclei have complicated nuclear structure. 2) The energetically allowed transitions are exhaust a small part of all the strength. 3) One must cope with the short distance behavior of the transition operators, especially when the intermediate particles are heavy (eg in SUSY models). Thus novel effects, like the double beta decay of pions in flight between nucleons, have to be considered. 4) The intermediate momenta involved are about 100 MeV. Thus one has to take into account possible momentum dependent terms in the nucleon current. We find that, for the mass mechanism, such modifications of the nucleon current for light neutrinos reduce the nuclear matrix elements by about 25 per cent, almost regardless of the nuclear model. In the case of heavy neutrinos the effect is much larger and model dependent. Taking the above effects into account, the available nuclear matrix elements for the experimentally interesting nuclei A = 76, 82, 96, 100, 116, 128, 130, 136 and 150 and the experimental limits on the life times we have extracted new stringent limits on the average neutrino mass and on the R-parity violating coupling for various SUSY models.Comment: Latex, 24 pages, 1 postscript figure, uses iopconf.st

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning