• Journal of Power Electronics
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• v.11 no.6
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• pp.904-913
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• 2011

Previous publications regarding the design and specifications of input filters for STATCOMs usually deal with the input filter only, and seldom pay any attention to the influence of the input filters on the performance of the STATCOM systems. A detailed analysis of the influences of input filters on the stability of STATCOM systems and the corresponding design considerations are presented in this paper. Three types of input filters, L filters, LC filters, and LCL filters, are examined separately. The influences of the parameters of input filters on system stability are investigated through frequency domain methods. With direct current control taken as the major control strategy for the STATCOMs, the different situations when adopting different current detection points are covered in this analysis. A comparison between LC filters and LCL filters is also presented with optimized filter parameters. Based on the analysis, the phase margin, as one of the design considerations for the different types of input filters under different current detection schemes, is discussed. This leads to filter parameters that are different than those of the traditional design. Hardware experimental results verify the validity of the above analysis and design.

• Journal of Environmental Science International
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• v.24 no.7
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• pp.939-946
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• 2015

Hydraulic conductivity is an important parameter in the analytical model of groundwater. This study analyzed the groundwater movement characteristics by estimating optimal parameters according to hydraulic conductivity input methods with the MODFLOW model which is widely used. It first estimated the optimal parameters by dividing hydraulic conductivity zones by attitude. Next, it estimated optimal parameters by geological characteristic. It analyzed the groundwater movement characteristics by applying the recharge quantity and amount of evapotranspiration of drought periods and flood years with the estimated parameters. As the result was analyzed that there are differences of observation water level values according to hydraulic conductivity input methods but there is no big differences of overall groundwater movement characteristics by hydraulic conductivity input method, the two methods have found to be applicability in analyses of groundwater. So, it is judged that studies on more exact application of hydraulic conductivity and the application methods are needed.

• Journal of Radiation Protection and Research
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• v.25 no.1
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• pp.11-19
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• 2000

The sensitivity analysis of input parameters for a dynamic food chain model DYNACON was conducted as a function of deposition date for the long-lived radionuclides $(^{137}Cs,\;^{90}Sr)$. Also, the influence of input parameters for the short and long-terms contamination of selected foodstuffs (cereals, leafy vegetables, milk) was investigated. The input parameters were sampled using the LHS technique, and their sensitivity indices represented as PRCC. The sensitivity index was strongly dependent on contamination period as well as deposition date. In case of deposition during the growing stages of plants, the input parameters associated with contamination by foliar absorption were relatively important in long-term contamination as well as short-term contamination. They were also important in short-term contamination in case of deposition during the non-growing stages. In long-term contamination, the influence of input parameters associated with foliar absorption decreased, while the influence of input parameters associated with root uptake increased. These phenomena were more remarkable in case of the deposition of non-growing stages than growing stages, and in case of $^{90}Sr$ deposition than $^{137}Cs$ deposition. In case of deposition during growing stages of pasture, the input parameters associated with the characteristics of cattle such as feed-milk transfer factor and daily intake rate of cattle were relatively important in contamination of milk.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.8
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• pp.1482-1488
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• 2010

Recently to increase the productivity and improve the quality in the industrial process, suppressing the residual vibration in motion control systems becomes the essential problem to solve. One of the methods to suppress the residual vibration is the input shaping technique. It is based on parameters of the system model; however, the parameters are usually difficult to obtain. This paper shows the effects of the residual vibration caused by the variation of the general velocity profile for the system with two vibration modes, and also shows the effects of the input shaping filter based on the parameters of system model. Finally, the simulation results show that the proposed input shaping filter using an artificial immune algorithm is more effective for suppressing residual vibrations than genetic algorithm.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.3
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• pp.358-367
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• 2019

Objectives: This study aimed to review model algorithms and input parameters applied to some exposure models and to compare the simulated estimates using an exposure scenario from each model. Methods: A total of five exposure models which can estimate inhalation exposure were selected; the Korea Ministry of Environment(KMOE) exposure model, European Centre for Ecotoxicology and Toxicology of Chemicals Targeted Risk Assessment(ECETOC TRA), SprayExpo, and ConsExpo model. Algorithms and input parameters for exposure estimation were reviewed and the exposure scenario was used for comparing the modeled estimates. Results: Algorithms in each model commonly consist of the function combining physicochemical properties, use characteristics, user exposure factors, and environmental factors. The outputs including air concentration ($mg/m^3$) and inhaled dose(mg/kg/day) are estimated applying input parameters with the common factors to the algorithm. In particular, the input parameters needed to estimate are complicated among the models and models need more individual input parameters in addition to common factors. In case of CEM, it can be obtained more detailed exposure estimates separating user's breathing zone(near-field) and those at influencing zone(far-field) by two-box model. The modeled exposure estimates using the exposure scenario were similar between the models; they were ranged from 0.82 to $1.38mg/m^3$ for concentration and from 0.015 to 0.180 mg/kg/day for inhaled dose, respectively. Conclusions: Modeling technique can be used for a useful tool in the process of exposure assessment if the exposure data are scarce, but it is necessary to consider proper input parameters and exposure scenario which can affect the real exposure conditions.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4195-4208
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• 2022

In this study, operator habitability was numerically evaluated in the event of a fire at the main control bench board (MCB) in a reference main control room (MCR). It was investigated if evacuation variables including hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD) at 1.8 m from the MCR floor exceed the reference evacuation criteria provided in NUREG/CR-6850. For a fire model validation, the simulation results of the reference MCR were compared with existing experimental results on the same reference MCR. In the simulation, various input parameters were applied to the MCB panel fire scenario: MCR height, peak heat release rate (HRR) of a panel, number of panels where fire propagation occurs, fire propagation time, door open/close conditions, and mechanical ventilation operation. A specialized-average HRR (SAHRR) concept was newly devised to comprehensively investigate how the various input parameters affect the operator's habitability. Peak values of the evacuation variables normalized by evacuation criteria of NUREG/CR-6850 were well-correlated as the power function of the SAHRR for the various input parameters. In addition, the evacuation time map was newly utilized to investigate how the evacuation time for different SAHRR was affected by changing the various input parameters. In the previous studies, it was found that the OD is the most dominant variable to determine the MCR evacuation time. In this study, however, the evacuation time map showed that the HF is the most dominant factor at the condition of without-mechanical ventilation for the MCR with a partially-open false ceiling, but the OD is the most dominant factor for all the other conditions. Therefore, the method using the SAHRR and the evacuation time map was very useful to effectively and comprehensively evaluate the operator habitability for the various input parameters in the event of MCB fires for the reference MCR.

• Fire Science and Engineering
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• v.26 no.2
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• pp.40-52
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• 2012

This paper presents the uncertainty analysis results of fire modeling input parameters for motor control center in switchgear room of nuclear power plants. FDS (Fire Dynamics simulator) 5.5 was used to simulate the fire scenario and Latin Hyper Cube Monte Carlo simulations were employed to generate random samples for FDS input parameters. The uncertainty analysis results of input parameters are compared with those of the model uncertainty analysis and sensitivity analysis approaches of NUREG-1934. The study results show that the input parameter uncertainty analysis approach may lead to more conservative results than the uncertainty analysis and sensitivity analysis methods of NUREG-1934.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.13-20
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• 2010

To evaluate the performance of safety apparatus without the full scale crash test, the computer simulation is inevitable. But, to improve the accuracy of computer simulation, it is important to reasonably determine the input parameters in which the interaction of vehicle-guardrail-soil should be accounted for. This study is focused on how to enhance the reliance of the dynamic performance of guardrail obtained by computer simulation. Analyses were done on the sensitivity of output variables to the change of input parameters by using BARRIER VII of which the usefulness was proved on the barrier-vehicle impact analysis. Through the analyses important input parameters, which give sensitive effects to output of computer simulation, are found out, and methods to determine such parameters are suggested to improve the accuracy of simulation.

• Structural Engineering and Mechanics
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• v.56 no.2
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• pp.257-273
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• 2015

Numerical value of correlation between effective parameters in the strength of a structure is as important as its stochastic properties in determining the safety of the structure. In this article investigation is made about the variation of coefficient of correlation between effective parameters in corrosion initiation time of reinforcement and the time of concrete cover cracking in reinforced concrete (RC) structures. Presence of many parameters and also error in measurement of these parameters results in uncertainty in determination of corrosion initiation and the time to crack initiation. In this paper, assuming diffusion process as chloride ingress mechanism in RC structures and considering random properties of effective parameters in this model, correlation between input parameters and predicted time to corrosion is calculated using the Monte Carlo (MC) random sampling. Results show the linear correlation between corrosion initiation time and effective input parameters increases with increasing uncertainty in the input parameters. Diffusion coefficient, concrete cover, surface chloride concentration and threshold chloride concentration have the highest correlation coefficient respectively. Also the uncertainty in the concrete cover has the greatest impact on the coefficient of correlation of corrosion initiation time and the time of crack initiation due to the corrosion phenomenon.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.208-217
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• 2021

3D-CNN is one of the deep learning techniques for learning time series data. However, these three-dimensional learning can generate many parameters, requiring high performance or having a significant impact on learning speed. We will use these 3D-CNNs to learn hand gesture and find the parameters that showed the highest accuracy, and then analyze how the accuracy of 3D-CNN varies through input data changes without any structural changes in 3D-CNN. First, choose the interval of the input data. This adjusts the ratio of the stop interval to the gesture interval. Secondly, the corresponding interframe mean value is obtained by measuring and normalizing the similarity of images through interclass 2D cross correlation analysis. This experiment demonstrates that changes in input data affect learning accuracy without structural changes in 3D-CNN. In this paper, we proposed two methods for changing input data. Experimental results show that input data can affect the accuracy of the model.