• Title/Summary/Keyword: parameters back analysis

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Uncertainty Cases in Economic Evaluation of Back-End Nuclear Fuel Cycle (후행 핵연료주기 경제성 평가의 불확실성 사례)

  • Kim, Hyung-Joon;Cho, Chun-Hyung;Lee, Kyung-Ku
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.6 no.2
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    • pp.141-145
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    • 2008
  • Due to the uncertainties resulting from cost projection, evaluation over long term period, and adequacy of applied discount rate, the economic assessment for back-end fuel cycle is different from each organizations or individuals. In this paper, the features and limitations of some noticeable economic evaluations were investigated and analysed to contribute for the public participation and back-end fuel cycle policy related researches. As a result of analysis, we found that the reprocess and recycling is more economical than direct disposal option, but the result includes high uncertainty that depends on the input parameters.

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Determination of Optimal Welding Parameter for an Automatic Welding in the Shipbuilding

  • Park, J.Y.;Hwang, S.H.
    • International Journal of Korean Welding Society
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    • v.1 no.1
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    • pp.17-22
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    • 2001
  • Because the quantitative relationships between welding parameters and welding result are not yet blown, optimal values of welding parameters for $CO_2$ robotic arc welding is a difficult task. Using the various artificial data processing methods may solve this difficulty. This research aims to develop an expert system for $CO_2$ robotic arc welding to recommend the optimal values of welding parameters. This system has three main functions. First is the recommendation of reasonable values of welding parameters. For such work, the relationships in between the welding parameters are investigated by the use of regression analysis and fuzzy system. The second is the estimation of bead shape by a neural network system. In this study the welding current voltage, speed, weaving width, and root gap are considered as the main parameters influencing a bead shape. The neural network system uses the 3-layer back-propagation model and a generalized delta rule as teaming algorithm. The last is the optimization of the parameters for the correction of undesirable weld bead. The causalities of undesirable weld bead are represented in the form of rules. The inference engine derives conclusions from these rules. The conclusions give the corrected values of the welding parameters. This expert system was developed as a PC-based system of which can be used for the automatic or semi-automatic $CO_2$ fillet welding with 1.2, 1.4, and 1.6mm diameter the solid wires or flux-cored wires.

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Stability Evaluation of failed Slope in Gohan, Korea using Numerical Analysis (강원도 정선군 고한 지역 붕괴사면의 수치해석을 이용한 사면안정성 평가)

  • Jang, Hyun-Sic;Lee, Ju-Young;Seo, Yong-Seok;Jang, Bo-An
    • The Journal of Engineering Geology
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    • v.24 no.4
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    • pp.511-523
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    • 2014
  • Limit equilibrium analysis and finite difference analysis were used to evaluate slope stability in the in Gohan, Korea, which is affected by large-scale tensile cracks and uplift. There is a thick colluvial layer in the study area and predicting ground behavior is problematic because the presence of clay makes it difficult to determine the strength parameters of the soil. Consequently, a numerical model able to reflect the collapse properties of the site was required that applied the modified boundary layer model and calculated the strength parameters using back analysis. The numerical simulation results that consider the strength parameter one does with the present situation the establishment of the pile is completed, and the simulation is able to asses ground stability in complex terrain in a reliable manner. Also the somewhat it judges with the fact that it will be able to provide the fundamental data which secures the stability of the segment where it is unstable.

The profile of musculoskeletal pain and its associations with sleep quality and depression during the COVID-19 in Turkey

  • Karatel, Merve;Bulut, Zeynep Irem;Sari, Erkin Oguz;Pelin, Zerrin;Yakut, Yavuz
    • The Korean Journal of Pain
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    • v.35 no.1
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    • pp.78-85
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    • 2022
  • Background: The current pandemic has affected people's health multidimensionally. This study aims to investigate musculoskeletal pain, sleep quality, depression levels, and their relationships in individuals belonging to different age groups during COVID-19 in Turkey. Methods: A web-based self-administered survey that consisted of demographic questions, The Beck Depression Inventory (BDI), Pittsburgh Sleep Quality Index (PSQI), and scores of musculoskeletal pain was sent to participants. Pearson correlation analysis was used for determining the statistical relationship between variables. Results: The study includes 1,778 participants. The highest percentage for mild, moderate, and severe pain was in the head (49.8%), back (15.5%), and head (11.5%), respectively. The PSQI-total had shown a weak correlation with pain levels in all body parts. The highest correlation for sleep quality and pain levels was between the PSQI-5 and lower back pain. There was a weak correlation between PSQI-2 and the BDI score, and a moderate correlation between the PSQI-1, PSQI-5, PSQI-7, PSQI-total, and BDI score. Pain in all body parts showed a weak correlation with depression level. Conclusions: This study showed that musculoskeletal pain was varied in body parts with different intensities according to age groups in Turkey during the pandemic. The most common pain was in the head, back, and lower back. Headache was found correlated with the parameters of sleep quality. Pain of the head, neck, back, lower back, and shoulder were correlated with sleep latency. Sleep quality was associated with depression and musculoskeletal pain, while musculoskeletal pain was correlated with depression.

Statistical Qualitative Analysis on Chemical Mechanical Polishing Process and Equipment Characterization

  • Hong, Sang-Jeen;Hwang, Jong-Ha;Seo, Dong-Sun
    • Transactions on Electrical and Electronic Materials
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    • v.12 no.2
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    • pp.56-59
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    • 2011
  • The characterization of the chemical mechanical polishing (CMP) process for undensified phophosilicate glass (PSG) film is reported using design of experiments (DOE). DOE has been used by experimenters to understand the relationship between the input variables and responses of interest in a simple and efficient way, and it typically is beneficial for determining the appropriatesize of experiments with multiple process variables and making statistical inferences for the responses of interest. The equipment controllable parameters used to operate the machine consist of the down force of the wafer carrier, pressure on the back side wafer, table and spindle speeds (SS), slurry flow (SF) rate, pad condition, etc. None of these are independent ofeach other and, thus, the interaction between the parameters also needs to be understoodfor improved process characterization in CMP. In this study, we selected the five controllable equipment parameters the most recommendedby process engineers, viz. the down force (DF), back pressure (BP), table speed (TS), SS, and SF, for the characterization of the CMP process with respect to the material removal rate and film uniformity in percentage terms. The polished material is undensified PSG which is widely used for the plananization of multi-layered metal interconnects. By statistical modeling and the analysis of the metrology data acquired from a series of $2^{5-1}$ fractional factorial designs with two center points, we showed that the DF, BP and TS have the greatest effect on both the removal rate and film uniformity, as expected. It is revealed that the film uniformity of the polished PSG film contains two and three-way interactions. Therefore, one can easily infer that process control based on a better understanding of the process is the key to success in current semiconductor manufacturing, in which the size of the wafer is approaching 300 mm and is scheduled to continuously increase up to 450 mm in or slightly after 2012.

Back-Analysis for Estimating Transmissivity in Riverbank Filtration (강변여과 대수층의 투수량계수 추정을 위한 역해석)

  • Park Seo-Hwa;Lee Sang-Il;Lee Sang-Sin
    • Journal of Korea Water Resources Association
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    • v.39 no.6 s.167
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    • pp.503-510
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    • 2006
  • Riverbank filtration is a natural process, using alluvial aquifers to remove contaminants and pathogens in river water for the production of drinking water. Back analysis which minimizes the objective function that is typically the sum of squares of the differences between the calculated and measured quantities is used for the estimation of aquifer parameters. In this study, transmissivity is back-analysed using the BFGS (Broyden-Fletcher-Goldfarb-Shanno) scheme for optimization. MOC is used to obtain calculated groundwater level. The developed inverse model was applied to Dae-san, Chang-won city where riverbank filtration is being undertaken. The model showed good convergence behavior for different groundwater conditions. The performance of the model was better than a widely-used commercial software package in terms of error between calculated and observed groundwater level.

Tunnel-lining Back Analysis Based on Artificial Neural Network for Characterizing Seepage and Rock Mass Load (투수 및 이완하중 파악을 위한 터널 라이닝의 인공신경망 역해석)

  • Kong, Jung-Sik;Choi, Joon-Woo;Park, Hyun-Il;Nam, Seok-Woo;Lee, In-Mo
    • Journal of the Korean Geotechnical Society
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    • v.22 no.8
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    • pp.107-118
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    • 2006
  • Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

Analysis of Permanent Magnet Synchronous Generator for Vortex Induced Vibration Hydrokinetic Energy Applications Based on Analytical Magnetic Field Calculations

  • Choi, Jang-Young;Shin, Hyun-Jae;Choi, Jong-Su;Hong, Sup;Yeu, Tae-Kyeong;Kim, Hyung-Woo
    • Journal of Magnetics
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    • v.17 no.1
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    • pp.19-26
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    • 2012
  • This paper deals with the performance analysis and estimation of the electrical parameters of a permanent magnet synchronous generator (PMSG) for hydrokinetic energy conversion applications using vortex induced vibration (VIV). The analytical solutions for the magnetic fields produced by permanent magnets (PMs) and stator winding currents are obtained using a 2D polar coordinate system and a magnetic vector potential. An analytical expression for the 2D permeance is also derived, which takes into account stator skew effects. Based on these magnetic field solutions and the 2D permeance function, electrical circuit parameters such as the backemf constant and the air-gap inductance are obtained analytically. The performances of the PMSG are investigated using the estimated electrical circuit parameters and an equivalent circuit (EC). All analytical results are validated extensively using 2D finite element (FE) analyses. Experimental measurements for parameters such as the back-emf and inductance are also presented to confirm the analyses.

Time-frequency Analysis of Vibroarthrographic Signals for Non-invasive Diagnosis of Articular Pathology (비침습적 관절질환 진단을 위한 관절음의 시주파수 분석)

  • Kim, Keo-Sik;Song, Chul-Gyu;Seo, Jeong-Hwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.4
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    • pp.729-734
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    • 2008
  • Vibroarthrographic(VAG) signals, emitted by human knee joints, are non-stationary and multi-component in nature and time-frequency distributions(TFD) provide powerful means to analyze such signals. The objective of this paper is to classify VAG signals, generated during joint movement, into two groups(normal and patient group) using the characteristic parameters extracted by time-frequency transform, and to evaluate the classification accuracy. Noise within TFD was reduced by singular value decomposition and back-propagation neural network(BPNN) was used for classifying VAG signals. The characteristic parameters consist of the energy parameter, energy spread parameter, frequency parameter, frequency spread parameter by Wigner-Ville distribution and the amplitude of frequency distribution, the mean and the median frequency by fast Fourier transform. Totally 1408 segments(normal 1031, patient 377) were used for training and evaluating BPNN. As a result, the average value of the classification accuracy was 92.3(standard deviation ${\pm}0.9$)%. The proposed method was independent of clinical information, and showed good potential for non-invasive diagnosis and monitoring of joint disorders such as osteoarthritis and chondromalacia patella.

An Analysis of the Physiological and Psychological Responses Elicited When Wearing an Aerogel Cold Protective Jacket in Airflow (에어로젤 방한 재킷 착용시의 기류 유무에 따른 생리·심리학적 특성 분석)

  • Seong-Suk Kim;Su-Young Son;Hee-Eun Kim
    • Human Ecology Research
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    • v.62 no.2
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    • pp.317-326
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    • 2024
  • This study evaluated the thermal physiological and psychological responses elicited when wearing cold protective jackets with aerogel fillings in two cold environments, one without air velocities and one with air velocities (2.3 m·s-1), at an air temperature of 10℃. The participants were five healthy young males. Measures were taken of physiological parameters, blood pressure (BP), heart rate (HR), core temperature, oxygen uptake (Vo2), and microclimate (temperature and humidity). The psychological parameters evaluated were thermal and wetness sensation. No differences were observed in systolic blood pressure, heart rate, and oxygen intake between the conditions. At tympanic temperature, a significant difference was observed between the conditions during exercise (p<.05); . A significant difference was observed in the microclimate temperature of the clothing according to the airflow, and temperature changes in the chest and back revealed different patterns. Significant differences were observed in thermal sensation (whole body (p<.05), chest (p<.05), back (p<.01)) between airflow conditions. The results therefore indicate that cold protective jackets with an aerogel filling are suitable for people operating in low-temperature and airflow environments.