Self-Contrastive Learning: Single-viewed Supervised Contrastive Framework using Sub-network

Contrastive loss has significantly improved performance in supervised classification tasks by using a multi-viewed framework that leverages augmentation and label information. The augmentation enables contrast with another view of a single image but enlarges training time and memory usage. To exploit the strength of multi-views while avoiding the high computation cost, we introduce a multi-exit architecture that outputs multiple features of a single image in a single-viewed framework. To this end, we propose Self-Contrastive (SelfCon) learning, which self-contrasts within multiple outputs from the different levels of a single network. The multi-exit architecture efficiently replaces multi-augmented images and leverages various information from different layers of a network. We demonstrate that SelfCon learning improves the classification performance of the encoder network, and empirically analyze its advantages in terms of the single-view and the sub-network. Furthermore, we provide theoretical evidence of the performance increase based on the mutual information bound. For ImageNet classification on ResNet-50, SelfCon improves accuracy by +0.6% with 59% memory and 48% time of Supervised Contrastive learning, and a simple ensemble of multi-exit outputs boosts performance up to +1.5%. Our code is available at https://github.com/raymin0223/self-contrastive-learning.Comment: AAAI 202

Fatigue Behavior of Additive Manufactured 304L Stainless Steel Including Surface Roughness Effects

The fatigue behavior of additive manufactured parts in the as-built surface condition is typically dominated by the surface roughness. However, the fatigue behavior of 304L stainless steel fabricated by laser beam powder bed fusion shows less sensitivity to surface roughness under strain-controlled loading conditions than other additive manufactured materials. Under force-controlled conditions, however, the high cycle fatigue resistance is much lower for the as-built surface condition than the machined one. This study investigates the underlying mechanisms responsible for fatigue failure for each condition (i.e. strain-controlled or force-controlled). The corresponding cyclic deformation behavior was characterized, and a thorough fractography analysis was performed to identify the features responsible for crack initiation. Results indicate that the crack initiation features in both loading conditions are similar, and that the reduced high cycle fatigue resistance for force-controlled fatigue loading compared to strain-controlled one is related to differences in the cyclic deformation behavior of the material.Mechanical Engineerin

Extended station blackout analyses of an APR1400 with MARS-KS

The Fukushima Daiichi nuclear power plant accident shows that natural disasters such as earthquakes and the subsequent tsunamis can cause station blackout for several days. The electric energy required for essential systems during a station blackout is provided from emergency backup batteries installed at the nuclear power plant. In South Korea, in the event of an extended station blackout, the life of these emergency backup batteries has recently been extended from 8 hours to 24 hours at Shin-Kori 5, 6, and APR1400 for design certification. For a battery life of 24 hours, available safety means system, equipment and procedures are studied and analyzed in their ability to cope with an extended station blackout. A sensitivity study of reactor coolant pump seal leakage is performed to verify how different seal leakages could affect the system. For simulating extended station blackout scenarios, the best estimate MARS-KS computer code was used. In this paper, an APR1400 RELAP5 input deck was developed for station blackout scenario to analyze operation strategy by manually depressurizing the reactor coolant system through the steam generator's secondary side. Additionally, a sensitivity study on reactor coolant pump seal leakage was carried out

Laser-Assisted Surface Defects and Pore Reduction of Additive Manufactured Titanium Parts

Laser surface treatment of additively manufactured parts has attracted considerable interest in the past few years due to its flexibility, operation speed, and capability for polishing complex surfaces as compared to conventional mechanical based methods. This study presents the role of laser surface processing in minimizing the surface roughness and pores that have detrimental effects on the fatigue behavior of additively manufactured specimens. This study is performed by a precise laser melting and recrystallization process to close the pores within 70 μm of the surface in order to enhance the fatigue life of these specimens. A continuous-wave fiber laser is employed to investigate the effect of various processing parameters for controlled laser surface treatments in this study.Mechanical Engineerin

Locational Dependency of Additively Manufactured Parts: Effects of Surface Roughness on Fatigue Behavior

Surface roughness (SR) can vary significantly among parts manufactured at different locations on the same build platform because of the gas flow and powder recoating process in current laser beam powder bed fusion (LB-PBF) technique. In this study, intra-build SR variation across locations was investigated for LB-PBF 316L stainless steel. The build platform was divided into 4 quadrants to assess the location-dependent variation of SR. Uniaxial stress-controlled fatigue tests were conducted using a servo-hydraulic system. The SR from the four quadrants was analyzed using the one-way Analysis of Variance (ANOVA) method and further verified SR's location dependency. Kruskal-Wallis test was also employed since Box-Cox transformed data failed to meet the requirements of the ANOVA test. Kruskal-Wallis test revealed that there are statistically significant differences in SR values across different locations. The results were validated using fatigue test results and gas flow simulation results reported in literature.Mechanical Engineerin

iSAVE: A Behavioral Emulator for in-System Algorithm Verification

Abstrac

Analysis of Drought Intensity and Trends Using the Modified SPEI in South Korea from 1981 to 2010

The aim of this study is to analyze the characteristics of drought, such as intensity and trends, based on SPEI (Standardized Precipitation Evapotranspiration Index) at 8 stations in South Korea from 1981 to 2010. The traditional SPEI is based on the Thornthwaite equation for estimating evapotranspiration; SPEI_th. However, a standard of agricultural water management in Korea suggests the FAO Penman-Monteith equation; SPEI_pm. Therefore, we analyzed the intensity, variability, and trends of drought using SPEI_th and SPEI_pm, respectively, and compared the results. SPEI_pm showed slightly more intensive drought rather than SPEI_th except for Chuncheon and Gwangju. In 5 stations—excluding Cheoncheon, Gwangju and Jinju—the cumulative probability that SPEI_pm was below −1.5 was significantly increased from 1981–1995 to 1996–2010. In addition, the northwest and southwest regions had higher intensity of 1-month droughts, and the central and southwest regions had a higher intensity of 3-month droughts. According to the Mann–Kendall test, there was a decreasing trend of 1-month SPEI during the fall season and 3-month SPEI during winter season