• Journal of the Korean Institute of Gas
• /
• v.14 no.5
• /
• pp.19-25
• /
• 2010

The flash points for the systems, o-xylene+n-pentanol and m-xylene+n-hexanol, were measured by using Tag open-cup tester(ASTM D1310-86). The experimental data were compared with the values calculated by the Raoult's law and the optimization method using van Laar and Wilson equations. The calculated values based on the optimization method were found to be better than those based on the Raoult's law. The predictive curve of the flash point prediction model based on the van Laar equation described the experimentally-derived data more effectively than was the case when the prediction model was based upon the Wilson equation.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.38 no.3
• /
• pp.347-354
• /
• 2014

The color appearance of a yarn-dyed woven fabric depends on the color of the yarn as well as on the weave structure. Predicting the final color appearance or formulating the recipe is a difficult task, considering the interference of colored yarns and structure variations. In a modern fabric design process, the intended color appearance is attained through a digital color methodology based on numerous color data and color mixing recipes (i.e., color prediction models, accumulated in CAD systems). For successful color reproduction, accurate color prediction models should be devised and equipped for the systems. In this study, the final colors of yarn-dyed woven fabrics were predicted using six geometric-color mixing models (i.e., simple K/S model, log K/S model, D-G model, S-N model, modified S-N model, and W-O model). The color differences between the measured and the predicted colors were calculated to evaluate the accuracy of various color models used for different weave structures. The log K/S model, D-G model, and W-O model were found to be more accurate in color prediction of the woven fabrics used. Among these three models, the W-O model was found to be the best one as it gave the least color difference between the measured and the predicted colors.

• Journal of Korean Society of Transportation
• /
• v.18 no.2
• /
• pp.41-52
• /
• 2000

In the developing country, the transportation situation is changed very quickly and the transportation environment is not stable. So the transportation planning should be frequently made in considering the limited cost and time. And the traditional large-scale survey(household survey, roadside interview, etc.) has many Problem like the difficulty for doing it and getting mood results. Therefore the study about the method of evaluation on the traffic count based O/D matrix is Processing actively recently. Though the many study for the network in the realistic size are enacted, the study for comparing with the advantage and disadvantage of each method are few. Therefore this study mainly deals with the static method among the existing models of evaluation on the traffic count based O/D matrix(in terms of the transportation plan). Bi-level(GU) and gradient method are selected as main alternative model and analyzed their capability and validity. For testing the reliability of the models, Bi-level(GLS) and gradient method are adapted to toy network. Then we analyze the result of testing, and study the way for large network.

• Journal of Magnetics
• /
• v.14 no.1
• /
• pp.11-14
• /
• 2009

We investigated the I-V curves and differential tunneling conductance of two, CoFeB/MgO/CoFeB-based, magnetic tunnel junctions (MTJs): one with a low tunneling magnetoresistance (TMR; 22%) and the other with a high TMR (352%). This huge TMR difference was achieved by different MgO sputter conditions rather than by different annealing or deposition temperature. In addition to the TMR difference, the junction resistances were much higher in the low-TMR MTJ than in the high-TMR MTJ. The low-TMR MTJ showed a clear parabolic behavior in the dI/dV-V curve. This high resistance and parabolic behavior were well explained by the Simmons' simple barrier model. However, the tunneling properties of the high-TMR MTJ could not be explained by this model. The characteristic tunneling properties of the high-TMR MTJ were a relatively low junction resistance, a linear relation in the I-V curve, and conduction dips in the differential tunneling conductance. We explained these features by applying the coherent tunneling model.

• Bulletin of the Korean Chemical Society
• /
• v.31 no.11
• /
• pp.3297-3300
• /
• 2010

In this study, the 3D-QSARs (three-dimensional quantitative structure-activity relationships: CoMFA and CoMSIA) between structural changes of N-phenyl-O-phenylthionocarbamate analogues (1-30) and their fungicidal activities against the capsicum phytophthora (Phyophthora capsici) fungi were analyzed, then considered quantitatively in terms of minimum structural requirements for fungicidal evaluation. The statistical qualities ($r^2_{cv.}$ = 0.510 and $r^2_{ncv.}$ = 0.948) of the optimal CoMFA 1 model are improved over the other models in the conditions of field combinations, and the two alignments. In the optimal CoMFA 1 model, relative contribution percentages of the CoMFA field were: steric field, 52.3%; electrostatic field, 37.8%; hydrophobic field, 9.9%. Results were similar for the CoMFA 2 model. Therefore, the steric field of the analogues had the highest contribution ratio for fungicidal activity. Specifically, with the contour map of steric fields, the fungicidal activity increased when bulky steric Y-substituents were introduced to the meta-position on the N-phenyl ring and small steric Y-subsituents were introduced to its para-position.

• The Bulletin of The Korean Astronomical Society
• /
• v.41 no.1
• /
• pp.40.2-41
• /
• 2016

To understand the observed kinematics in the narrow-line region (NLR) of type 2 AGNs, we construct a model of 3-D biconical outflow combined with a thin dust plane. The model consists of two identical cones whose apex is located at the nucleus, and the cones are axisymmetric with respect to the bicone axis. After we define the properties of the bicone and the dust plane, we calculate a spatially integrated velocity and velocity dispersion along the line-of-sight using various physical parameters. As we test the effect of model parameters, we find three key parameters determining the integrated kinematics: intrinsic outflow velocity, bicone inclination, and the amount of dust extinction. The velocity dispersion increases as the intrinsic outflow velocity or the bicone inclination increases, while the velocity shift increases as the amount of dust extinction increases. We confirm that the integrated velocity dispersion can be a good indicator of the intrinsic outflow velocity unless dust extinction is not very strong (>~80%), while the effect of dust extinction can be alleviated by combining the integrated velocity and the velocity dispersion. Based on the simulated velocity distributions using the 3-D models, the variety of the observed [O $_{III}$] line profiles of type 2 AGNs can be well reproduced. In addition, we perform Monte Carlo simulations based on the different sets of model parameters. By comparing the model results with the observed [O $_{III}$] kinematics of ~39,000 SDSS type 2 AGNs (Woo et al. 2016), we find that the observed [O $_{III}$] velocity-velocity dispersion distribution is well reproduced by the biconical outflow model, enabling us to constrain the intrinsic physical parameters of outflows.

• Journal of Korean Port Research
• /
• v.14 no.2
• /
• pp.175-185
• /
• 2000

Today freeway is experiencing a severe congestion with incoming or outgoing traffic through freeway ramps during the peak periods. Thus, the purpose of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the delay predictive models on the rap junctions of freeway with 70mph speed limit. From the traffic analyses, and model construction and verification for delay prediction on the ramp junctions of freeway, the following results were obtained : ⅰ) Traffic flow showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period. ⅱ) The occupancy also showed a big difference depending on the time periods, and the downstream occupancy(Od) was especially shown to have a higher explanatory power for the delay predictive model construction on the ramp junctions of freeway. ⅲ) The delay-occupancy curve showed a remarkable shift based on the occupancies observed : O$\_$d/〈9% and O$\_$d/$\geq$9%. Especially, volume and occupancy were shown to be highly explanatory for delay prediction on the ramp junctions of freeway under O$\_$d/$\geq$9%, but lowly for delay prediction on the ramp junctions of freeway under O$\_$d/〈9%. Rather, the driver characteristics or transportation conditions around the freeway were thought to be a little higher explanatory for the delay prediction under O$\_$d/〈9%. ⅳ) Integrated delay predictive models showed a higher explanatory power in the morning peak period, but a lower explanatory power in the non-peak periods.

• Journal of Korean Society on Water Environment
• /
• v.26 no.3
• /
• pp.460-467
• /
• 2010

For D-WTP's sedimentation basin and distribution reservoir, and water tap the predictive models proposed tentatively herein included the models for estimating TTHM concentration in precipitated water, for treated water and for tap water, and the estimated correlation formula between treated water's TTHM concentration and tap water. As for TTHM-concentration predictive model in sedimentation water, the coefficient of determination is 0.866 for best-fitted short-term $DOC{\times}UV_{254}$ based Model (TTHM). As for $HAA_5$-concentration predictive model in sedimentation water, the coefficient of determination is 0.947 for the suitable $UV_{254}$-based model ($HAA_5$). In case of the predictive model in treated water, the coefficient of determination is 0.980 for best-fitted $DOC{\times}UV_{254}$ based model (TTHM) using coagulated waters, while the coefficient of determination is 0.983 for best-fitted $DOC{\times}UV_{254}$ based model ($HAA_5$) using coagulated waters, which described the $HAA_5$ concentration well. However, the predictive model for tap water could not be compatible with the one for treated water, only except for possibility inducing correlation formula for prediction, [i.e., the correlation formula between TTHM concentration and tap water was verified as TTHM (tap water) = $1.162{\times}TTHM$ (treated water), while $HAA_5$ (tap water) = $0.965{\times}HAA_5$ (treated water).] The correlation analysis between DOC and $KMnO_4$ consumption by process resulted in higher relationship with filtrated water, showing that its regression is $DOC=0.669{\times}KMnO_4$ consumption - 0.166 with 0.689 of determination coefficient. By substituting it to the existing DOC-based model ($HAA_5$) for treated water, the consequential model formula was made as follows; $HAA_5=8.35(KMnO_4\;consumption{\times}0.669-0.166)^{0.701}(Cl_2)^{0.577}t^{0.150}0.9216^{(pH-7.5)}1.022^{(Temp-20^{\circ}C)}$

• Transactions of the Korean Society of Automotive Engineers
• /
• v.20 no.1
• /
• pp.95-105
• /
• 2012

The selective catalytic reduction (SCR) system is a highly-effective aftertreatment device for NOx reduction of diesel engines. Generally, the ammonia ($NH_3$) was generated from reaction mechanism of SCR in the SCR system using the liquid urea as the reluctant. Therefore, the precise urea dosing control is a very important key for NOx and $NH_3$ slip reduction in the SCR system. This paper investigated NOx and $NH_3$ emission characteristics of urea-SCR dosing system based on model-based control algorithm in order to reduce NOx. In the map-based control algorithm, target amount of urea solution was determined by mass flow rate of exhaust gas obtained from engine rpm, torque and $O_2$ for feed-back control NOx concentration should be measured by NOx sensor. Moreover, this algorithm can not estimate $NH_3$ absorbed on the catalyst. Hence, the urea injection can be too rich or too lean. In this study, the model-based control algorithm was developed and evaluated on the numerical model describing physical and chemical phenomena in SCR system. One channel thermo-fluid model coupled with finely tuned chemical reaction model was applied to this control algorithm. The vehicle test was carried out by using map-based and model-based control algorithms in the NEDC mode in order to evaluate the performance of the model based control algorithm.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.58-61
• /
• 2002

In this paper, we present a new generalized k-Tree-based (CU/PE) allocation model to perform dynamic resource (CU/PE) allocation/deallocation decision for the reconfigurable MSIMD/MIMD multi-dimensional (k-D) mesh-connected architectures. Those reconfigurable multi-SIMD/MIMD systems allow dynamic modes of executing tasks, which are SIMD and MIMD. The MIMD task requires only the free sub-system; however the SIMD task needs not only the free sub-system but also the corresponding free CU. In our new k-Tree-based (CU/PE) allocation model, we introduce two best-fit heuristics for the CU allocation decision: 1) the CU depth first search (CU-DFS) in O(kN$_{f}$ ) time and 2) the CU adjacent search (CU-AS) in O(k2$^{k}$ ) time. By the simulation study, the system performance of these two CU allocation strategies was also investigated. Our simulation results showed that the CU-AS and CU-DFS strategies performed the same system performance when applied for the reconfigurable MSIMD/MIMD 2-D and 3-D mesh-connected architectures.