• Journal of Mechanical Science and Technology
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• v.18 no.6
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• pp.961-971
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• 2004

Methods for determination of the crack opening stress intensity factor ($K_{op}$) and for estimation of the effective stress intensity factor range ($\Delta{K}_{eff}$) are evaluated for crack growth test data of aluminum alloys. Three methods of determining $K_{op}$, visual measurement, ASTM offset compliance method, and the neural network method proposed by Kang and Song, and three methods of estimating $\Delta{K}_{eff}$, conventional, the 2/PIO and 2/PI methods proposed by Donald and Paris, are compared in a quantitative manner by using evaluation criteria. For all $K_{op}$ determination methods discussed, the 2/PI method of estimating $\Delta{K}_{eff}$ provides good results. The neural network method of determining $K_{op}$ provides good correlation of crack growth data. It is recommended to use 2/PI estimation with the neural $K_{op}$ determination method. The ASTM offset method used in conjunction with 2/PI estimation shows a possibility of successful application. It is desired to improve the ASTM method.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.40-45
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• 2015

Online social networks(OSN) are very popular nowadays. As OSNs grows, the commercial markets are expanding their social commerce by applying Influence Maximization. However, in reality, there exist more than two players(e.g., commercial companies or service providers) in this same market sector. To address the Influence Maximization problem between adversaries, we first introduced Influence Maximization against the social adversaries' problem. Then, we proposed an algorithm that could efficiently solve the problem efficiently by utilizing social network properties such as Betweenness Centrality, Clustering Coefficient, Local Bridge and Ties and Triadic Closure. Moreover, our algorithm performed orders of magnitudes better than the existing Greedy hill climbing algorithm.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.35-40
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• 2021

The study aimed to realize one of the basic requirements for designing and building the integrated automated system for scientific research at Northern Border University, which includes the establishment of an automated interconnected system to manage all academic and financial operations of scientific research. From receiving the budget of the funded research courses, then the regular financial regulation of all the research team's rewards, the cost of publishing, translation and equipment, then receiving the research plans and linking them financially, preparing the total and detailed financial value for all stages, then financial disbursement operations, financial closure of research when published, and preparing financial reports The research team used the analytical approach to build the main and subsidiary requirements for designing the financial system, and the study concluded that all the elements required for the stages of financial management for scientific research at Northern Border University can be met based on sufficient by sequencing these processes and how they are sequenced as e It is designed in the research study.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.208-213
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• 2004

Methods for estimation of the effective stress intensity factor range (${\Delta}K_{eff}$) are evaluated for narrow and wide band random loading crack growth test data of 2024-T351 aluminum alloy. Three methods of determining $K_{op}$, visual measurement, ASTM offset compliance method, and the neural network method proposed by Kang and Song, and three methods of estimating ${\Delta}K_{eff}$, conventional, the 2/PI0 and 2/PI methods proposed by Donald and Paris, are compared in a quantitative manner by using the results of fatigue crack growth life prediction under random loading. For all $K_{op}$ determination methods discussed, the 2/PI0 and 2/PI methods of estimating ${\Delta}K_{eff}$ provide better results than conventional method for narrow and wide band random loading data.

• Korean Journal of Audiology
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• v.23 no.4
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• pp.210-213
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• 2019

The auricle is a three-dimensional cartilaginous frame covered with thin overlying skin. Due to its complex features, reconstructing helical rim defects after the excision of an auricular mass is challenging. Shortage of subcutaneous tissue and the presence of a tightly bound epithelium further hamper the primary closure of lateral (anterior) auricular skin defects. We present herein a case in which we used a helical rim advancement flap along with an additional postauricular skin flap. We achieved a satisfactory esthetic result with minimal loss of helical diameter and a low risk of flap necrosis by preserving the vascular network of the flap. This technique is less traumatic and will facilitate faster healing as well as improved patient recovery.

• Journal of Audiology & Otology
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• v.23 no.4
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• pp.210-213
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• 2019

The auricle is a three-dimensional cartilaginous frame covered with thin overlying skin. Due to its complex features, reconstructing helical rim defects after the excision of an auricular mass is challenging. Shortage of subcutaneous tissue and the presence of a tightly bound epithelium further hamper the primary closure of lateral (anterior) auricular skin defects. We present herein a case in which we used a helical rim advancement flap along with an additional postauricular skin flap. We achieved a satisfactory esthetic result with minimal loss of helical diameter and a low risk of flap necrosis by preserving the vascular network of the flap. This technique is less traumatic and will facilitate faster healing as well as improved patient recovery.

• Advances in aircraft and spacecraft science
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• v.10 no.6
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• pp.521-543
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• 2023

Reynolds-averaged Navier-Stokes (RANS) models are extensively employed in industrial settings for the purpose of simulating intricate fluid flows. However, these models are subject to certain limitations. Notably, disparities persist in the Reynolds stresses when comparing the RANS model with high-fidelity data obtained from Direct Numerical Simulation (DNS) or experimental measurements. In this work we propose an approach to mitigate these discrepancies while retaining the favorable attributes of the Menter Shear Stress Transport (SST) model, such as its significantly lower computational expense compared to DNS simulations. This strategy entails incorporating an explicit algebraic model and employing a neural network to correct the turbulent characteristic time. The imposition of realizability constraints is investigated through the introduction of penalization terms. The assimilated Reynolds stress model demonstrates good predictive performance in both in-sample and out-of-sample flow configurations. This suggests that the model can effectively capture the turbulent characteristics of the flow and produce physically realistic predictions.

• Tunnel and Underground Space
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• v.21 no.2
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• pp.117-127
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• 2011

The purpose of this study is to demonstrate the effect of in-situ rock stresses on the deformability and permeability of fractured rocks. Geological data were taken from the site investigation at Forsmark, Sweden, conducted by Swedish Nuclear Fuel and Waste Man-agement Company (SKB). A set of numerical experiments was conducted to determine the equivalent mechanical properties (essentially, elastic moduli and Poisson's ratio) and permeability, using a Discrete Fracture Network-Discrete Element Method (DFN-DEM) approach. The results show that both mechanical properties and permeability are highly dependent on stress because of the hyperbolic nature of the stiffness of fractures, different closure behavior of fractures, and change of fluid pathways caused by deformation. This study shows that proper characterization and consideration of in-situ stress are important not only for boundary conditions of a selected site but also for the understanding of the mechanical and hydraulic behavior of fractured rocks.

• Tunnel and Underground Space
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• v.24 no.4
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• pp.282-288
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• 2014

Stoping method has been acknowledged as one of the typical metalliferous underground mining methods. Notwithstanding with the popularity of the method, the majority of stoping mines are suffering from excessive unplanned dilution which often becomes as the main cause of mine closure. Thus a reliable unplanned dilution management system is imperatively needed. In this study, reliable unplanned dilution prediction system is introduced by adopting artificial neural network (ANN) based on data investigated from one underground stoping mine in Western Australia. In addition, contributions of input parameters were analysed by connection weight algorithm (CWA). To validate the reliability of the proposed ANN, correlation coefficient (R) was calculated in the training and test stage which shown relatively high correlation of 0.9641 in training and 0.7933 in test stage. As results of CWA application, BHL (Length of blast hole) and SFJ (Safety factor of Joint orientation) show comparatively high contribution of 18.78% and 19.77% which imply that these are somewhat critical influential parameter of unplanned dilution.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.771-775
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• 2008

Concerns related to protecting, identifying, and isolating of subsystems of a water distribution network have led to the realization of the increased importance of valves in the system. The most important purpose of valves in water distribution systems is to isolate subsystems due to breakage, maintenance activities, or contamination. A subsystem called segment is isolated by the closure of adjacent valves and an efficient algorithm should identify the adjacent valves to minimize the pipe failure impact. In this paper, an algorithm to identify adjacent valves to be closed to isolate a subsystem from the remainder of a network in case of a pipe failure is presented. An application to the water distribution system in Ottawa, Canada demonstrates the developed algorithm efficiently locates the adjacent valves for the isolation of a broken pipe.