Evaluation of primary water stress corrosion cracking growth rates by using the extended finite element method

AbstractBackgroundMitigation of primary water stress corrosion cracking (PWSCC) is a significant issue in the nuclear industry. Advanced nickel-based alloys with lower susceptibility have been adopted, although they do not seem to be entirely immune from PWSCC during normal operation. With regard to structural integrity assessments of the relevant components, an accurate evaluation of crack growth rate (CGR) is important.MethodsFor the present study, the extended finite element method was adopted from among diverse meshless methods because of its advantages in arbitrary crack analysis. A user-subroutine based on the strain rate damage model was developed and incorporated into the crack growth evaluation.ResultsThe proposed method was verified by using the well-known Alloy 600 material with a reference CGR curve. The analyzed CGR curve of the alternative Alloy 690 material was then newly estimated by applying the proven method over a practical range of stress intensity factors.ConclusionReliable CGR curves were obtained without complex environmental facilities or a high degree of experimental effort. The proposed method may be used to assess the PWSCC resistance of nuclear components subjected to high residual stresses such as those resulting from dissimilar metal welding parts

Information-Theoretic Text Hallucination Reduction for Video-grounded Dialogue

Video-grounded Dialogue (VGD) aims to decode an answer sentence to a question regarding a given video and dialogue context. Despite the recent success of multi-modal reasoning to generate answer sentences, existing dialogue systems still suffer from a text hallucination problem, which denotes indiscriminate text-copying from input texts without an understanding of the question. This is due to learning spurious correlations from the fact that answer sentences in the dataset usually include the words of input texts, thus the VGD system excessively relies on copying words from input texts by hoping those words to overlap with ground-truth texts. Hence, we design Text Hallucination Mitigating (THAM) framework, which incorporates Text Hallucination Regularization (THR) loss derived from the proposed information-theoretic text hallucination measurement approach. Applying THAM with current dialogue systems validates the effectiveness on VGD benchmarks (i.e., AVSD@DSTC7 and AVSD@DSTC8) and shows enhanced interpretability.Comment: 12 pages, Accepted in EMNLP 202

Round Robin Analyses on Stress Intensity Factors of Inner Surface Cracks in Welded Stainless Steel Pipes

AbstractAustenitic stainless steels (ASSs) are widely used for nuclear pipes as they exhibit a good combination of mechanical properties and corrosion resistance. However, high tensile residual stresses may occur in ASS welds because postweld heat treatment is not generally conducted in order to avoid sensitization, which causes a stress corrosion crack. In this study, round robin analyses on stress intensity factors (SIFs) were carried out to examine the appropriateness of structural integrity assessment methods for ASS pipe welds with two types of circumferential cracks. Typical stress profiles were generated from finite element analyses by considering residual stresses and normal operating conditions. Then, SIFs of cracked ASS pipes were determined by analytical equations represented in fitness-for-service assessment codes as well as reference finite element analyses. The discrepancies of estimated SIFs among round robin participants were confirmed due to different assessment procedures and relevant considerations, as well as the mistakes of participants. The effects of uncertainty factors on SIFs were deducted from sensitivity analyses and, based on the similarity and conservatism compared with detailed finite element analysis results, the R6 code, taking into account the applied internal pressure and combination of stress components, was recommended as the optimum procedure for SIF estimation

Large-scale filamentary structures around the Virgo cluster revisited

We revisit the filamentary structures of galaxies around the Virgo cluster, exploiting a larger dataset based on the HyperLeda database than previous studies. In particular, this includes a large number of low-luminosity galaxies, resulting in better sampled individual structures. We confirm seven known structures in the distance range 4~$h^{-1}$~Mpc~$<$ SGY~$<$ 16~$h^{-1}$ Mpc, now identified as filaments, where SGY is the axis of the supergalactic coordinate system roughly along the line of sight. The Hubble diagram of the filament galaxies suggests they are infalling toward the main-body of the Virgo cluster. We propose that the collinear distribution of giant elliptical galaxies along the fundamental axis of the Virgo cluster is smoothly connected to two of these filaments (Leo~II~A and B). Behind the Virgo cluster (16~$h^{-1}$~Mpc~$<$ SGY~$<$ 27~$h^{-1}$~Mpc), we also identify a new filament elongated toward the NGC 5353/4 group ("NGC 5353/4 filament") and confirm a sheet that includes galaxies from the W and M clouds of the Virgo cluster ("W-M sheet"). In the Hubble diagram, the NGC 5353/4 filament galaxies show infall toward the NGC 5353/4 group, whereas the W-M sheet galaxies do not show hints of gravitational influence from the Virgo cluster. The filamentary structures identified can now be used to better understand the generic role of filaments in the build-up of galaxy clusters at z~$\approx$~0.Comment: 8 pages, 4 figures, accepted for publication in Ap

CCD Photometry of the Classic Second-Parameter Globular Clusters M3 and M13

We present high-precision V, B-V color-magnitude diagrams (CMDs) for the classic second-parameter globular clusters M3 and M13 from wide-field, deep CCD photometry. The data for the two clusters were obtained during the same photometric nights with the same instrument, allowing us to determine accurate relative ages. Based on a differential comparison of the CMDs using the Δ(B-V) method, an age difference of 1.7 ± 0.7 Gyr is obtained between these two clusters. We compare this result with our updated horizontal-branch (HB) population models, which confirm that the observed age difference can produce the difference in HB morphology between the clusters. This provides further evidence that age is the dominant second parameter that influences HB morphology

A hybrid decision support model to discover informative knowledge in diagnosing acute appendicitis

BACKGROUND: The aim of this study is to develop a simple and reliable hybrid decision support model by combining statistical analysis and decision tree algorithms to ensure high accuracy of early diagnosis in patients with suspected acute appendicitis and to identify useful decision rules. METHODS: We enrolled 326 patients who attended an emergency medical center complaining mainly of acute abdominal pain. Statistical analysis approaches were used as a feature selection process in the design of decision support models, including the Chi-square test, Fisher's exact test, the Mann-Whitney U-test (p < 0.01), and Wald forward logistic regression (entry and removal criteria of 0.01 and 0.05, or 0.05 and 0.10, respectively). The final decision support models were constructed using the C5.0 decision tree algorithm of Clementine 12.0 after pre-processing. RESULTS: Of 55 variables, two subsets were found to be indispensable for early diagnostic knowledge discovery in acute appendicitis. The two subsets were as follows: (1) lymphocytes, urine glucose, total bilirubin, total amylase, chloride, red blood cell, neutrophils, eosinophils, white blood cell, complaints, basophils, glucose, monocytes, activated partial thromboplastin time, urine ketone, and direct bilirubin in the univariate analysis-based model; and (2) neutrophils, complaints, total bilirubin, urine glucose, and lipase in the multivariate analysis-based model. The experimental results showed that the model with univariate analysis (80.2%, 82.4%, 78.3%, 76.8%, 83.5%, and 80.3%) outperformed models using multivariate analysis (71.6%, 69.3%, 73.7%, 69.7%, 73.3%, and 71.5% with entry and removal criteria of 0.01 and 0.05; 73.5%, 66.0%, 80.0%, 74.3%, 72.9%, and 73.0% with entry and removal criteria of 0.05 and 0.10) in terms of accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under ROC curve, during a 10-fold cross validation. A statistically significant difference was detected in the pairwise comparison of ROC curves (p < 0.01, 95% CI, 3.13-14.5; p < 0.05, 95% CI, 1.54-13.1). The larger induced decision model was more effective for identifying acute appendicitis in patients with acute abdominal pain, whereas the smaller induced decision tree was less accurate with the test data. CONCLUSIONS: The decision model developed in this study can be applied as an aid in the initial decision making of clinicians to increase vigilance in cases of suspected acute appendicitis