Leak-tightness characteristics concerning the containment structures of the HTTR

The containment structures of the HTTR consist of the reactor containment vessel, the service area, and the emergency air purification system, which minimise the release of fission products in postulated accidents, which lead to fission product release from the reactor facilities. The reactor containment vessel is designed to withstand the temperature and pressure transients and to be leak-tight in the case of a rupture of the primary concentric hot-gas duct, etc. The pressure inside the service area is maintained at a negative pressure by the emergency air purification system. The emergency air purification system will also remove airborne radioactivity and will maintain a correct pressure in the service area.The leak-tightness characteristics of the containment structures are described in this paper. The measured leakage rates of the reactor containment vessel were enough less than the specified leakage limit of 0.1%/d confirmed during the commissioning tests and annual inspections. The service area was kept in a way that the design pressure becomes well below its allowable limitation by the emergency air purification system, which filters efficiency of particle removal and iodine removal well over the limited values.The obtained data demonstrate that the reactor containment structures were fabricated to minimise the release of fission products in the postulated accidents with fission product release from the reactor facilities.     

Adaptive Learning with Large Variability of Teaching Signals for Neural Networks and Its Application to Motion Control of an Industrial Robot

Recently, various control methods represented by proportional-integral-derivative (PID) control are used for robotic control.To cope with the requirements for high response and precision, advanced feedforward controllers such as gravity compensator,Coriolis/centrifugal force compensator and friction compensators have been built in the controller.Generally, it causes heavy computational load when calculating the compensating value within a short sampling period.In this paper, integrated recurrent neural networks are applied as a feedforward controller for PUMA560 manipulator.The feedforward controller works instead of gravity and Coriolis/centrifugal force compcusators.In the learning process of the neural network by using back propagation algorithm, the learning coefficient and gain of sigmoid function are tuned intuitively and empirically according to teaching signals.The tuning is complicated because it is being conducted by trial and error.Especially, when the scale of teaching signal is large, the problem becomes crucial.To cope with the problcm which concerns the learning performance, a simple and adaptive learning technique for large scale teaching signals is proposed.The learning techniques and control effectiveness are evaluated through simulations using the dynamic model of PUMA560 manipulator.     

Martensitic stabilization and defects induced by deformation in TiNi shape memory alloys

Martensitic stabilization caused by deformation in a TiNi shape memory alloy was studied.Special attention was paid to the deformed microstructures to identify the cause of martensitic stabilization.Martensitic stabilization was demonstrated by differential scanning calorimetry for the tensioned TiNi shape memory alloy.Transmission electron microscopy revealed that antiphase boundaries were formed because of the fourfold dissociation of[110]B19'super lattice dislocations and were preserved after reverse transformation due to the lattice correspondence.Martensitic stabilization was attributed to dislocations induced by deformation,which reduced the ordering degree of the microstructure,spoiled the reverse path from martensite to parent phase compared with thermoelastic transformation,and imposed resistance on phase transformation through the stress field.     

Clinically applicable bulk isolation of blood CD34+ cells for autografting in children

The quality of population-based cancer registries has been measured by the indices of the proportion of total incident cases (DCO%) registered by death certificate only (DCO), and the ratio of incidence to mortality (I/D ratio). Recently it has been recommended that DCO% should be used as an index for the reliability of diagnosing cancers and that the proportion of cases first notified via death certificate (DCN, DCN%) be used as an index for the completeness of registration. Parkin introduced a method to estimate the registration rate, the estimated proportion of the "true incidence" that are registered in population-based registries. We recommend a modified method for estimating the registration rate for cancer registries where DCN% is relatively high, as it is in Japan, as Parkin's method may overestimate the registration rate. The method is as follows: the registration rate = (1-DCN% x 1/D ratio)/(1-DCN%). The registration rates at the Osaka Cancer Registry between 1966 and 1992 were estimated using our method. During this period, the yearly registration rate was 74.6-78.4% for males and 69.1-73.3% for females. When the cancer cases were looked at according to site, the yearly registration rate was 74.2-81.6% for stomach cancer, 81.2-89.3% for lung cancer, and 71.3-76.9% for uterine cancer. These results show that the registration rate is high for cancers that have an unfavorable prognosis and low for cancers that have a favorable prognosis. We recommend that all cancer registries in Japan calculate the completeness of registration by utilizing DCN defined as the sum of DCO plus cases not reported as cancer but with supportive clinical information of such obtained through survey of the registry for DCN.     

Investigations on welding residual stresses in penetration nozzles by means of 3D thermal elastic plastic FEM and experiment

Recent discoveries of stress corrosion cracking (SCC) in weldments including penetration nozzles at pressurized water reactors (PWRs) and boiling water reactors (BWRs) have raised concerns about safety and integrity of plant components. It is well known that welding residual stress is an important factor resulting in SCC in weldments. In the present work, both experimental method and numerical simulation technology are used to investigate the characteristics of welding residual stress distribution in penetration nozzles welded by multi-pass J-groove joint. An experimental mock-up is fabricated to measure welding residual stress at first. In the experiment, each weld pass is performed using a semi-circle balanced welding procedure. Then, a corresponding finite element models with considering moving heat source, deposition sequence, inter-pass temperature, temperature-dependent thermal and mechanical properties, strain hardening and annealing effect is developed to simulate welding temperature and residual stress fields. The simulation results predicted by the 3D model are generally in good agreement with the measurements. Meanwhile, to clarify the influence of deposition sequence on the welding residual stress, the welding residual stress field in the same geometrical model induced by a continuous welding procedure is also calculated. Finally, the influence of a joint oblique angle on welding residual stress is investigated numerically. The numerical results suggest that both deposition sequence and oblique angles have effect on welding residual stress distribution.     

Uniform temperature cooling power of the superfluid Stirling refrigerator

Uniform temperature cooling power measurements of a superfluid Stirling refrigerator are presented for³He-⁴He molar concentrations of 5.9%, 17% and 36% and for temperatures between 0.37 K and 1.4 K. The results are compared to an ideal Fermi gas model and to a more general thermodynamic model. The Fermi model agrees well with the 5.9% concentration data; however, the more elaborate model is needed for higher concentration mixtures.     

Experimental and numerical investigation of effects of particle shape and size distribution on particles’ dispersion in a coaxial jet flow

In this study, an experimental and a numerical investigations are performed to investigate the effect of particle’s shape and size distribution on its dispersion behavior. Firstly, particle dispersion of pulverized coal and spherical polymer particles is observed by Particle Image Velocimetry (PIV) technique in the experiment. Secondly, a simulation is performed to analyze the particle dispersion in detail. Spherical and spheroidal motion models are applied to particle’s movement to investigate the shape effect. Furthermore, monodisperse and polydisperse for particles are applied to investigate the size distribution effect on the dispersion. Experimental results show that in the jet turbulence flow, pulverized coal particles, which have complex shapes and various sizes, have quite different dispersion behavior compared to spherical particles. In terms of the results of the simulation, this difference is mainly caused by the size distribution effect. Although particle’s shape affects the dispersity, it is weakened by the size distribution effect.     

Development of correlation-based clustering method and its application to software sensing

The individuality of production devices should be taken into account when soft-sensors are designed for parallelized devices. Since it is expressed as differences of the correlation among measured variables, it is useful to cluster samples on the basis of the correlation among variables for adopting a multi-model approach. In addition, changes in process characteristics can be coped with in the same way. In the present work, a new clustering method, referred to as NC-spectral clustering, is proposed by integrating the nearest correlation (NC) method and spectral clustering. Spectral clustering is a graph partitioning method that can be used for sample classification when an affinity matrix of a weighted graph is given. The NC method can detect samples that are similar to the query from the viewpoint of the correlation without a teacher signal. In the proposed method, the NC method is used for constructing the weighted graph that expresses the correlation-based similarities between samples and the constructed graph is partitioned by using spectral clustering. In addition, a new soft-sensor design method is proposed on the basis of the proposed NC-spectral clustering. The usefulness of the proposed methods is demonstrated through a numerical example and a case study of parallelized batch processes. The performance of the proposed correlation-based method is better than that of the conventional distance-based methods.     

Psychological Stress Exacerbates Inflammation of the Ileum via the Corticotropin-Releasing Hormone-Mast Cell Axis in a Mouse Model of Eosinophilic Enteritis

The effects of psychological stress on eosinophilic gastrointestinal disorders have not been elucidated. This study investigated the effects of psychological stress in a mouse model of eosinophilic enteritis (EoN). BALB/c mice were treated with ovalbumin (OVA) to create an EoN model and subjected to either water avoidance stress (WAS) or sham stress (SS). Microscopic inflammation, eosinophil and mast cell counts, mRNA expression, and protein levels of type 2 helper T cell (Th2) cytokines in the ileum were compared between groups. We evaluated ex vivo intestinal permeability using an Ussing chamber. A corticotropin-releasing hormone type 1 receptor (CRH-R1) antagonist was administered before WAS, and its effects were analyzed. WAS significantly increased diarrhea occurrence and, eosinophil and mast cell counts, and decreased the villus/crypt ratio compared to those in the SS group. The mRNA expression of CRH, interleukin IL-4, IL-5, IL-13, eotaxin-1, and mast cell tryptase β2 significantly increased, and the protein levels of IL-5, IL-13, and OVA-specific immunoglobulin E (IgE) also significantly increased in the WAS group. Moreover, WAS significantly increased the intestinal permeability. The CRH-R1 antagonist significantly inhibited all changes induced by WAS. Psychological stress exacerbated ileal inflammation via the CRH-mast cell axis in an EoN mouse model.