• Title/Summary/Keyword: Hazard prediction

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FEM Analysis for the Prediction of Void Closure On the Open Die Forging Process (자유단조공정에서 기공폐쇄 예측을 위한 유한요소해석)

  • Min, K.Y.;Lim, S.J.;Choi, H.J.;Choi, S.;Park, Y.B.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2008.05a
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    • pp.71-74
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    • 2008
  • In order to resolve the problems which appear after the clean large ingot production process, the impurities which are involved in the steel smelting process should be removed by developing cleaner materials. Through the rationalization of cogging process that is the first forging process of large ingot the quality is to be improved. For the sake of the optimization of an open die forging process and the improvement of the subject matter frequency ratio, a hazard precise die forging process must be developed and a Near Net Shape Forming accomplished. As a result, energy can be reduced by minimizing an after control process. In order to produce large axes and other forming parts, processing techniques are to be developed. In this context, this paper is a study about a reduction ratio, dies width ratio and rotary angles, the amount of overlap, and intends to analysis cogging processes, utilizing Deform-3D cogging module

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Integrated Model for Assessment of Risks in Rail Tracks under Various Operating Conditions

  • G. Chattopadhyay;V. Reddy;Larsson, P-O
    • International Journal of Reliability and Applications
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    • v.4 no.4
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    • pp.183-190
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    • 2003
  • Rail breaks and derailments can cause a huge loss to rail players due to loss of service, revenue, property or even life. Maintenance has huge impact on reliability and safety of railroads. It is important to identify factors behind rail degradation and their risks associated with rail breaks and derailments. Development of mathematical models is essential for prediction and prevention of risks due to rail and wheel set damages, rail breaks and derailments. This paper addresses identification of hazard modes, estimation of probability of those hazards under operating, curve and environmental condition, probability of detection of potential hazards before happening and severity of those hazards for informed strategic decisions. Emphasis is put on optimal maintenance and operational decisions. Real life data is used for illustration.

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Prediction of the Intensity of Vibration Around the Crossing Part of Manganese Turnout (망간분기기 크로싱부 인근의 진동 발생수준 예측)

  • Eum, Ki-Young
    • Journal of the Korean Society of Hazard Mitigation
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    • v.8 no.6
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    • pp.61-66
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    • 2008
  • In railroad operation, turnout is the device designed to provide very critical functions of moving the train to the neighboring rail. It's the only movable section among the rail and track equipment, which has a complicated structure and as rapid movement between the wheel and rail during operation is unavoidable, the safety and the vibration caused by the impact load of the passing train becomes always the major concern. Response to rail vibration tends to vary depending on physical properties of the rail, rail base and the ground, making it difficult to estimate the quantitative outcome through the measurement. Thus, experimental or empirical approach, rather than an analytic method, has been more commonly employed to deal with the ground vibration. To predict the vibration of the turnout, an experimental value and the measured values are applied in parallel to the factors with a high degree of uncertainty. This study hence was intended to compare and analyze the vibration values measured at the crossing part of manganese turnout by type of train and turnout and distance, as well as predict the intensity of vibration generated at the crossing part of manganese turnout when tilting train accelerates.

A Study on Development of an Earthquake Ground-motion Database Based on the Korean National Seismic Network (국가지진관측망 기반 지진동 데이터베이스 개발 연구)

  • Choi, Sae-Woon;Rhie, Junkee;Lee, Sang-Hyun;Kang, Tae-Seob
    • Journal of the Earthquake Engineering Society of Korea
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    • v.24 no.6
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    • pp.277-283
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    • 2020
  • In order to improve the ground-motion prediction equation, which is an important factor in seismic hazard assessment, it is essential to obtain good quality seismic data for a region. The Korean Peninsula has an environment in which it is difficult to obtain strong ground motion data. However, because digital seismic observation networks have become denser since the mid-2000s and moderate earthquake events such as the Odaesan earthquake (Jan. 20, 2007, ML 4.8), the 9.12 Gyeongju earthquake (Sep. 12, 2016, ML 5.8), and the Pohang earthquake (Nov. 15, 2017, ML 5.4) have occurred, some good empirical data on ground motion could have been accumulated. In this study, we tried to build a ground motion database that can be used for the development of the ground motion attenuation equation by collecting seismic data accumulated since the 2000s. The database was constructed in the form of a flat file with RotD50 peak ground acceleration, 5% damped pseudo-spectral acceleration, and meta information related to hypocenter, path, site, and data processing. The seismic data used were the velocity and accelerogram data for events over ML 3.0 observed between 2003 and 2019 by the Korean National Seismic Network administered by the Korea Meteorological Administration. The final flat file contains 10,795 ground motion data items for 141 events. Although this study focuses mainly on organizing earthquake ground-motion waveforms and their data processing, it is thought that the study will contribute to reducing uncertainty in evaluating seismic hazard in the Korean Peninsula if detailed information about epicenters and stations is supplemented in the future.

Pull-out Behaviors of Headed Bars with Different Details of Head Plates (Head 플레이트 상세에 따른 Headed Bars의 인발거동에 관한 연구)

  • Park, Hyun-Gyoo;Yoon, Young-Soo;Ryoo, Young-Sup;Lee, Man-Seop
    • Journal of the Korean Society of Hazard Mitigation
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    • v.2 no.2 s.5
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    • pp.95-104
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    • 2002
  • This paper presents the pull-out failure mode on Headed Bars and prediction of tensile capacity, as governed by concrete cone failure. 17 different plate types, three different concrete strengths and three different welding types of specimens were simulated. Test variables are the reinforcing bar diameters connected to headed plate (e.g., 16mm, 19mm and 22mm), the head plate shapes (e.g., circular, square, rectangular), the dimensions of head plates (e.g., area and thickness), the types of welding scheme for connection of reinforcing bars and head plates (e.g., general welding and friction welding). Headed Bars were manufactured in different areas, which shape and thickness are based on ASTM 970-98. Calculation of Embedment length in concrete is based on CSA 23.3-94, and static tensile load was applied. Pullout capacities tested were compared to the values determined using current design methods such as ACI-349 and CCD method. If compare experiment results and existings, Headed bar expressed high strength and bigger breakdown radious than standard by wide plate area and anomaly reinforcing rod unlike anchor.

Parameter Estimation of Storage Function Method using Metamodel (메타모델을 이용한 저류함수법의 매개변수추정)

  • Chung, Gun-Hui;Oh, Jin-A;Kim, Tae-Gyun
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.6
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    • pp.81-87
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    • 2010
  • In order to calculate the accurate runoff from a basin, nonlinearity in the relationship between rainfall and runoff has to be considered. Many runoff calculation models assume the linearity in the relationship or are too complicated to be analyzed. Therefore, the storage function method has been used in the prediction of flood because of the simplicity of the model. The storage function method has five parameters with related to the basin and rainfall characteristics which can be estimated by the empirical trial and error method. To optimize these parameters, regression method or optimization techniques such as genetic algorithm have been used, however, it is not easy to optimize them because of the complexity of the method. In this study, the metamodel is proposed to estimate those model parameters. The metamodel is the combination of artificial neural network and genetic algorithm. The model is consisted of two stages. In the first stage, an artificial neural network is constructed using the given rainfall-runoff relationship. In the second stage, the parameters of the storage function method are estimated using genetic algorithm and the trained artificial neural network. The proposed metamodel is applied in the Peong Chang River basin and the results are presented.

A Study on Measuring and Calibration Method using Time Domain Reflectometry Sensor under Road Pavement (Time Domain Reflectometry 방식을 이용한 도로 하부의 함수비 계측 및 보정 방안에 관한 연구)

  • Cho, Myung-Hwan;Lee, Yoon-Han;Kim, Nak-Seok;Park, Joo-Young
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.2
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    • pp.23-30
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    • 2010
  • The research presents moisture content measuring and calibration method of road pavement, especially asphalt concrete pavement for performance evaluation or remaining life prediction using Time Domain Reflectometry(TDR) sensor, CS616 made by campbell INC. Before calibration test of CS616, accomplished a sensor verification tests. Verification test items were covering depth and interference effect of two CS616 sensors, temperature effects between $5^{\circ}C\sim25^{\circ}C$ and compaction ratio effects. Covering depth and interference effects between two CS616 sensors were just small and the effects of temperature and compaction ratio effected a Volumetric Moisture Contents at $\pm6%$ under disregard appeared with the fact that was possible. Also, obtained the calibration equation of the subgrade and subbase course, $R^2$ showed above of all 0.9.

Applications of Artificial Neural Networks for Using High Performance Concrete (고성능 콘크리트의 활용을 위한 신경망의 적용)

  • Yang, Seung-Il;Yoon, Young-Soo;Lee, Seung-Hoon;Kim, Gyu-Dong
    • Journal of the Korean Society of Hazard Mitigation
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    • v.3 no.4 s.11
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    • pp.119-129
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    • 2003
  • Concrete and steel are essential structural materials in the construction. But, concrete, different from steel, consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructors. Concrete have two kinds of properties, immediately knowing properties such as slump, air contents and time dependent one like strength. Therefore, concrete mixes depend on experiences of experts. However, at point of time using High Performance Concrete, new method is wanted because of more ingredients like mineral and chemical admixtures and lack of data. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network ate used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength, slump, and air contents are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.

A study on the factors affecting shelf-life for 60, 81mm mortar ammunition (60, 81mm 박격포탄의 저장수명 요인 연구)

  • Jang, SooHee;Chun, Heuiju;Cho, Inho;Yoon, KeunSig;Kang, MinJung;Park, DongSoo
    • The Korean Journal of Applied Statistics
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    • v.31 no.5
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    • pp.611-620
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    • 2018
  • Limitations on human and material resources make it is difficult to conduct Ammunition Stockpile Reliability Program (ASRP) tasks for the entire ammunition. Stockpile ammunition life prediction studies can contribute to efficient ASRP tasks. This study assess the shelf-life of ammunition, using survival analysis based on ASRP results for 60mm and 81mm mortar ammunition from 2003 to 2016. Traditional assessments often use solely storage duration as the only main independent variable; however, this assessment used other factors such as ammunition magazine shape and weather factors with the stockpile shelf-life as independent variables to conduct a Cox's proportional hazard model analysis. This was then followed by an assessment of ammunition magazine type, maximum temperature and rainfall factors influence on the shelf-life of 60mm and 81mm mortar ammunition. As a result, the type of ammunition magazine, maximum temperature and the rainfall influence the shelf-life of 60mm and 81mm mortar ammunition.

Prognostic Factors for Survival in Patients with Breast Cancer Referred to Omitted Cancer Research Center in Iran

  • Baghestani, Ahmad Reza;Shahmirzalou, Parviz;Zayeri, Farid;Akbari, Mohammad Esmaeil;Hadizadeh, Mohammad
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.12
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    • pp.5081-5084
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    • 2015
  • Background: Breast cancer is a malignant tumor that starts from cells of the breast and is seen mainly in women. It's the most common cancer in women worldwide and is a major threat to health. The purpose of this study was to fit a Cox proportional hazards model for prediction and determination of years of survival in Iranian patients. Materials and Methods: A total of 366 patients with breast cancer in the Cancer Research Center were included in the study. A Cox proportional hazard model was used with variables such as tumor grade, number of removed positive lymph nodes, human epidermal growth factor receptor 2 (HER2) expression and several other variables. Kaplan-Meier curves were plotted and multi-years of survival were evaluated. Results: The mean age of patients was 48.1 years. Consumption of fatty foods (p=0.033), recurrence (p<0.001), tumor grade (p=0.046) and age (p=0.017) were significant variables. The overall 1- year, 3-year and 5-year survival rates were found to be 93%, 75% and 52%. Conclusions: Use of covariates and the Cox proportional hazard model are effective in predicting the survival of individuals and this model distinguished 4 effective factors in the survival of patients.