• Title/Summary/Keyword: Volume Factor Model

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Effects of Elastic Modulus Ratio on Internal Stresses in Short Fiber Composites (단섬유 복합체에서 탄성계수비가 내부응력에 미치는 영향)

  • 김홍건;노홍길
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.4
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    • pp.73-78
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    • 2004
  • The conventional SLT(Shear Lag Theory) which has been proven that it can not provide sufficiently accurate strengthening predictions in elastic regime when the fiber aspect ratio is small. This paper is an extented work to improve it by modifying the load transfer mechanism called NSLT(New Shear Lag Theory), which takes into account the stress transfer across the fiber ends and the SCF(Stress Concentration Factor) that exists in the matrix regions near the fiber ends. The key point of the model development is to determine the major controlling factor among the material and geometrical coefficients. It is found that the most affecting factor is the fiber/matrix elastic modulus ratio. It is also found that the proposed model gives a good result that has the capability to correctly predict the elastic properties such as interfacial shear stresses and local stress variations in the small fiber aspect ratio regime.

Gasification reactivity of Chinese Shinwha Coal Chars with Steam (스팀을 이용한 중국산 신화 석탄 촤 가스화 반응에 관한 연구)

  • Kang, Min-Woong;Seo, Dong-Kyun;Kim, Yong-Tak;Hwang, Jung-Ho
    • Journal of the Korean Society of Combustion
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    • v.15 no.1
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    • pp.22-29
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    • 2010
  • In this study, carbon conversion was measured using an electronic mass balance. In a lab scale furnace, each coal sample was pyrolyzed in a nitrogen environment and became coal char, which was then gasified with steam under isothermal conditions. The reactivity of coal char was investigated at various temperatures and steam concentrations. The VRM(volume reaction model), SCM(shrinking core model), and RPM(random pore model) were used to interpret experimental data. For each model the activation energy(Ea), pre-exponential factor (A), and reaction order(n) of the coal char-steam reaction were determined by applying the Arrhenius equation into the data obtained with thermo-gravimetric analysis(TGA). According to this study, it was found that experimental data agreed better with the VRM and SCM for 1,000 and $1,100^{\circ}C$, and the RPM for 1,200 and $1,300^{\circ}C$. The reactivity of chars increased with the increase of gasification temperature. The structure parameter(${\psi}$) of the surface area for the RPM was obtained.

Accuracy Evaluation of Earthwork Volume Calculation According to Terrain Model Generation Method (지형모델 구축 방법에 따른 토공물량 산정의 정확도 평가)

  • Park, Joon Kyu;Jung, Kap Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.1
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    • pp.47-54
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    • 2021
  • Calculation of quantity at construction sites is a factor that has a great influence on construction costs, and it is important to calculate accurate values. In this study, topographic model was created by using drone photogrammetry and drone LiDAR to estimate earthwork volume. ortho image and DSM (Digital Surface Model) were constructed for the study area by drone photogrammetry, and DEM (Digital Elevation Model) of the target area was established using drone LiDAR. And through accuracy evaluation, accuracy of each method are 0.034m, 0.35m in horizontal direction, 0.054m, 0.25m in vertical direction. Through the research, the usability of drone photogrammetry and drone LiDAR for constructing geospatial information was presented. As a result of calculating the volume of the study site, the UAV photogrammetry showed a difference of 1528.1㎥ from the GNSS (Global Navigation Satellite System) survey performance, and the 3D Laser Scanner showed difference of 160.28㎥. The difference in the volume of earthwork is due to the difference in the topographic model, and the efficiency of volume calculation by drone LiDAR could be suggested. In the future, if additional research is conducted using GNSS surveying and drone LiDAR to establish topographic model in the forest area and evaluate its usability, the efficiency of terrain model construction using drone LiDAR can be suggested.

Reliability analysis-based conjugate map of beams reinforced by ZnO nanoparticles using sinusoidal shear deformation theory

  • Keshtegar, Behrooz;Kolahchi, Reza
    • Steel and Composite Structures
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    • v.28 no.2
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    • pp.195-207
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    • 2018
  • First-order reliability method (FORM) is enhanced based on the search direction using relaxed conjugate reliability (RCR) approach for the embedded nanocomposite beam under buckling failure mode. The RCR method is formulated using discrete conjugate map with a limited scalar factor. A dynamical relaxed factor is proposed to control instability of proposed RCR, which is adjusted using sufficient descent condition. The characteristic of equivalent materials for nanocomposite beam are obtained by micro-electro-mechanical model. The probabilistic model of nanocomposite beam is simulated using the sinusoidal shear deformation theory (SSDT). The beam is subjected to external applied voltage in thickness direction and the surrounding elastic medium is modeled by Pasternak foundation. The governing equations are derived in terms of energy method and Hamilton's principal. Using exact solution, the implicit buckling limit state function of nanocomposite beam is proposed, which is involved various random variables including thickness of beam, length of beam, spring constant of foundation, shear constant of foundation, applied voltage, and volume fraction of ZnO nanoparticles in polymer. The robustness, accuracy and efficiency of proposed RCR method are evaluated for this engineering structural reliability problem. The results demonstrate that proposed RCR method is more accurate and robust than the excising reliability methods-based FORM. The volume fraction of ZnO nanoparticles and the applied voltage are the sensitive variables on the reliable levels of the nanocomposite beams.

Analysis on Factors Affecting Traffic Accident Severity - Case Study : Arterial Included Curve Section - (교통사고심각도 영향요인 분석에 관한 연구 - 곡선부가 포함된 국도를 중심으로 -)

  • Park, Jae Hong;Yun, Duk Geun;Sung, Jung Gon
    • Journal of the Korean Society of Safety
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    • v.28 no.6
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    • pp.84-89
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    • 2013
  • The main causes of traffic accidents can be classified by 3 factors - human error, vehicle deficiency and road environmental problem and most accidents occurs not only 1 factor but combination of 2 or 3-factors. Among these factors, road environmental factor is the most important factor due to influence the behavior of cars and road users and road environmental factor affects 30% of total accidents approximately. The 5 years traffic accidents data analyzed to verify the accidents severity on Korea National Highways. In order to analyze the severity, Ordered Probit Model was used. As a independent variables of this model the number of lane, neighbor road environments, sight distance, vertical grade, lane width, shoulder width and traffic volume were used and as a dependent variables the minor injuries, serious injuries and fatalities were used. Research results shows that sight distance and lane width are identified as significant factors for the traffic accident severity and lesser sight distance and lane width shows greater traffic accident severity.

Effects of Physical Characteristics on a Nutrient-Chlorophyll Relationship in Korean Reservoirs

  • Hwang, Soon-Jin;Jeon, Ji-Hong;Ham, Jong-Hwa;Kim, Ho-Sub
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.7
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    • pp.64-73
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    • 2002
  • This study was performed to evaluate effects of physical characteristics of both watershed and reservoir on nutrient-chlorophyll relationship in Korean reservoirs. Simple linear models were developed with published data in Korea including 415 reservoirs and 11 multi-purpose dams, and physico-chemical parameters of reservoirs and characteristics relationship of models were analyzed. Theoretical residence time in Korean reservoirs was strongly correlated with the ratio of TA/ST (drainage area + surface area / storage volume) in the logarithmic function. As a result of monthly nutrients-chlorophyll-a regression analysis, significant Chl-a-TP relationship appeared during May~July. The high Chl-a yields per total phosphorus appeared during this time (R$\^$2/=0.51, p<0.001, N= 1088). Chlorophyll-a demonstrated much stronger relationship with TP. than TN. Seasonal algal-nutrient coupling were closely related with N:P ratio in the reservoir water, and it was, in turn, dependent on the monsoon climatic condition (precipitation). Based on the results of regression analysis and high N:P ratio, a major limiting factor of algal growth appeared to be phosphorus during this time. Unlikely TA/ST ratio, DA/SA ratio (drainage area f surface area) was likely to influence directly on the nutrient-Chl-a relationship, indicating that if storage volume and inflowing water volume were the same, algal biomass could be developed more in reservoirs with large surface area. Thus, DA/SA ratio seemed to be an important factor to affect the development of algal biomass in Korean reservoirs. With low determination coefficient of TP-Chl-a relationship, our findings indicated not only nutrient (phosphorus) but also other physical factors, such as DA/SA ratio, may affect algal biomass development in Korean reservoirs, where actual residence time appears to be more closely related to reservoir surface area rather than storage volume.

An Empirical Analysis on the Long-term Balance of Bunker Oil Prices Using the Co-integration Model and Vector Error Correction Model (공적분·벡터오차수정모형을 활용한 벙커유 가격의 장기균형 수렴에 관한 실증분석)

  • Ahn, Young-Gyun;Lee, Min-Kyu
    • Korea Trade Review
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    • v.44 no.1
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    • pp.75-86
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    • 2019
  • This study performs a factor analysis that affects the bunker oil price using the Co-integration model and Vector Error Correction Model (VECM). For this purpose, we use data from Clarkson and the analysis results show 17.6% decrease in bunker oil price when the amount of crude oil production increases at 1.0%, 10.3% increase in bunker oil price when the seaborne trade volume increases at 1.0%, 1.0% decrease in bunker oil price when total volume of vessels increases at 1.0%, and 0.003% increase in bunker oil price when 1.0% increase in world GDP, respectively. This study is meaningful in that this study estimates the speed of convergence to long-term equilibrium and identifies the price adjust mechanism which naturally exists in bunker oil market. And it is expected that the future study can provide statistically more meaningful econometric results if it can obtain data during more long-periods and use more various kinds of explanatory variables.

Numerical Analysis of Heat Transfer Characteristics in Corrugated Plate Type Heat Exchanger Channel (주름형상 판형열교환기 채녈에서의 열전달 특성 수치해석적 연구)

  • 김태용;이재용;김남진;김종보
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.13 no.7
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    • pp.588-594
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    • 2001
  • The purpose of this study is to investigate the thermal and hydrodynamic characteristics of the channel in corrugated plate type heat exchangers numerically. Numerical work has been conducted using the Reynolds Stress Model(RSM) by utilizing the commercial finite-volume code, FLUENT. Based on this model, the dependence of heat transfer and friction factor on geometrical parameters have been investigated. It is found that larger corrugation angle give higher values of heat transfer coefficients and friction factors. As the reynolds number increases, the heat transfer coefficient also increases. It is also observed that the heat transfer coefficient reaches maximum while the friction factor stays relatively low at same corrugation angle. Through the analysis, it is found that the optimum corrugation angle for the heat exchanger performance exists. It is noted that the flow repulsions at the contact point of the two fluid streams make the low mixing more active for larger corrugation angle and high reynolds number.

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Material distribution optimization of 2D heterogeneous cylinder under thermo-mechanical loading

  • Asgari, Masoud
    • Structural Engineering and Mechanics
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    • v.53 no.4
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    • pp.703-723
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    • 2015
  • In this paper optimization of volume fraction distribution in a thick hollow cylinder with finite length made of two-dimensional functionally graded material (2D-FGM) and subjected to steady state thermal and mechanical loadings is considered. The finite element method with graded material properties within each element (graded finite elements) is used to model the structure. Volume fractions of constituent materials on a finite number of design points are taken as design variables and the volume fractions at any arbitrary point in the cylinder are obtained via cubic spline interpolation functions. The objective function selected as having the normalized effective stress equal to one at all points that leads to a uniform stress distribution in the structure. Genetic Algorithm jointed with interior penalty-function method for implementing constraints is effectively employed to find the global solution of the optimization problem. Obtained results indicates that by using the uniform distribution of normalized effective stress as objective function, considerably more efficient usage of materials can be achieved compared with the power law volume fraction distribution. Also considering uniform distribution of safety factor as design criteria instead of minimizing peak effective stress affects remarkably the optimum volume fractions.

Forecasting the Busan Container Volume Using XGBoost Approach based on Machine Learning Model (기계 학습 모델을 통해 XGBoost 기법을 활용한 부산 컨테이너 물동량 예측)

  • Nguyen Thi Phuong Thanh;Gyu Sung Cho
    • Journal of Internet of Things and Convergence
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    • v.10 no.1
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    • pp.39-45
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    • 2024
  • Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.