• Journal of the Korean Geotechnical Society
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• v.40 no.1
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• pp.5-14
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• 2024

PHC piles demonstrate superior resistance to compression and bending moments, and their factory-based production enhances quality assurance and management processes. Despite these advantages that have resulted in widespread use in civil engineering and construction projects, the design process frequently relies on empirical formulas or N-values to estimate the soil-pile friction, which is crucial for bearing capacity, and this reliance underscores a significant lack of experimental validation. In addition, environmental factors, e.g., the pH levels in groundwater and the effects of seawater, are commonly not considered. Thus, this study investigates the influence of vibrating machine foundations on PHC pile models in consideration of the effects of varying pH conditions. Concrete model piles were subjected to a one-month conditioning period in different pH environments (acidic, neutral, and alkaline) and under the influence of seawater. Subsequent repeated direct shear tests were performed on the pile-soil interface, and the disturbed state concept was employed to derive parameters that effectively quantify the dynamic behavior of this interface. The results revealed a descending order of shear stress in neutral, acidic, and alkaline conditions, with the pH-influenced samples exhibiting a more pronounced reduction in shear stress than those affected by seawater.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.4
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• pp.133-142
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• 2023

In this paper, we built a data-driven artificial intelligence model using RNN-LSTM (Recurrent Neural Networks-Long Short-Term Memory) to predict the Lorenz system, and examined the possibility of whether this model can replace chaotic dynamic models. We confirmed that the data-driven model reflects the chaotic nature of the Lorenz system, where a small error in the initial conditions produces fundamentally different results, and the system moves around two stable poles, repeating the transition process, the characteristic of "deterministic non-periodic flow", and simulates the bifurcation phenomenon. We also demonstrated the advantage of adjusting integration time intervals to reduce computational resources in data-driven models. Thus, we anticipate expanding the applicability of data-driven artificial intelligence models through future research on refining data-driven models and data assimilation techniques for data-driven models.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.391-398
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• 2023

In this paper, a penalized maximum likelihood estimation (PMLE) method that applies a penalty to increase the accuracy of a basis-screening-based Kriging model (BSKM) is introduced. The maximum order and set of basis functions used in the BSKM are determined according to their importance. In this regard, the cross-validation error (CVE) for the basis functions is employed as an indicator of importance. When constructing the Kriging model (KM), the maximum order of basis functions is determined, the importance of each basis function is evaluated according to the corresponding maximum order, and finally the optimal set of basis functions is determined. This optimal set is created by adding basis functions one by one in order of importance until the CVE of the KM is minimized. In this process, the KM must be generated repeatedly. Simultaneously, hyper-parameters representing correlations between datasets must be calculated through the maximum likelihood evaluation method. Given that the optimal set of basis functions depends on such hyper-parameters, it has a significant impact on the accuracy of the KM. The PMLE method is applied to accurately calculate hyper-parameters. It was confirmed that the accuracy of a BSKM can be improved by applying it to Branin-Hoo problem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.7071-7077
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• 2015

In recently, the demand of cover-glass is increased because smart phone, tablet pc, and electrical device has become widely used. The display of mobile device is enlarged, so it is necessary to have a high strength against the external force such as contact or falling. In fabrication process of cover-glass, a grinding process is very important process to obtain high strength of glass. Conventional grinding process using a grinding wheel is caused such as a scratch, chipping, notch, and micro-crack on a surface. In this paper, polishing system using a abrasive film was developed for a grinding of mobile cover-glass. To evaluate structural stability of the designed system, finite element model of the polishing system is generated, and multi-body dynamic analysis of abrasive film polishing machine is proposed. As a result of the analysis, stress and displacement analysis of abrasive film polishing system are performed, and using laser displacement sensor, structural stability of abrasive film polishing system is confirmed by measuring displacement.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.846-851
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• 2005

In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.

• Korean Journal of Construction Engineering and Management
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• v.9 no.1
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• pp.187-198
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• 2008

There are usually plenty of material inventories in a construction site. More inventories can meet unexpected demands, and also they may have an economical advantage by avoiding a probable escalation of raw material costs. On the other hand, these inventories also cause negative aspects to increase costs for storing redundant inventory as well as decreasing construction productivity. Therefore, a proper method of deciding an optimal level of material inventories while considering dynamic variations of resources under uncertainty is very crucial for the economical efficiency of construction projects. This research presents a stochastic modelling method for construction operations, particularly targeting a work process involving on-site fabrication of raw materials like iron-rebar process (delivery, cut and assembly, and placement). To develop the model, we apply the concept of factory physics to depict the overall components of a system. Then, an optimal inventory management model is devised to support purchase decisions where users can make timely actions on how much to order and when to buy raw materials. Also, optimal time lag, which minimizes the storage time for pre-assembled materials, is obtained. To verify this method, a real case is applied to elicit an optimal amount of inventory and time lag. It is found that average values as well as variability of inventory level decreased significantly so as to minimize economic costs related to inventory management under uncertain project condition.

• Clean Technology
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• v.26 no.3
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• pp.186-195
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• 2020

The isothermal adsorption, dynamic, and thermodynamic parameters of Acid black (AB) and Quinoline yellow (QY) adsorption by activated carbon were investigated using the initial concentration, contact time, temperature, and pH of the dyes as adsorption parameters. The adsorption equilibrium data fits the Freundlich isothermal adsorption model, and the calculated Freundlich separation factor values found that activated carbon can effectively remove AB and QY. Comparing the kinetic data showed that the pseudo second order model was within 10% error in the adsorption process. The intraparticle diffusion equation results were divided into two straight lines. Since the slope of the intraparticle diffusion line was smaller than the slope of the boundary layer diffusion line, it was confirmed that intraparticle diffusion was the rate-controlling step. The thermodynamic experiments indicated that the activation energies of AB and QY were 19.87 kJ mol^-1 and 14.17 kJ mol^-1, which corresponded with the physical adsorption process (5 ~ 40 kJ mol^-1). The adsorption reaction was spontaneous because the free energy change in the adsorption of AB and QY by activated carbon was negative from 298 to 318 K. As the temperature increased, the free energy value decreased resulting in higher spontaneity. Adsorption of AB and QY by activated carbon showed the highest adsorption removal rate at pH 3 due to the effect of anions generated by dissociation. The adsorption mechanism was electrostatic attraction.

• Journal of the Korea Concrete Institute
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• v.24 no.5
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• pp.559-566
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• 2012

In this study, fiber elements and a spring are used to build a reinforced concrete shear wall model. The fiber elements and the spring reflect flexural and shear behaviors of the shear wall, respectively. The fiber elements are built by inputting section data and material properties. The spring parameters representing strength and stiffness degradation, pinching, and slip were determined by comparing behaviors of fiber element and VecTor2 results. 'Pinching4' model in OpenSees is used for shear spring. The parameter selecting process for shear spring is a complicated and time consuming process. To study the applicability of the fiber element, reinforced concrete buildings containing a shear wall are evaluated using nonlinear dynamic analysis with various wall aspect ratio (H/L), various beam heights, and stiffness and flexural strength of beam and wall ratios. The aspect ratio of the wall showed distinct difference in IDR (interstory drift ratio) of the models with and without spring. On the other hand, the height of beam and ratio of stiffness and flexural strength of beam and wall did not show clear relation.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.103-113
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• 2003

This paper shows alternative route search and preference route search for the traffic route search, and proposes the use of the fuzzy non-additive controller by the application of AHP(analytic hierarchy process). It is different from classical route search and notices thinking method of human. Appraisal element, weight of route is extracted from basic of the opinion gathering for the driving expert and example of route model was used for the finding of practice utility. Model evaluation was performed attribute membership function making of estimate element, estimate value setting, weight define by the AHP, non additive presentation of weight according to $\lambda$-fuzzy measure and Choquet fuzzy integral. Finally, alternative route search was possible to real time traffic route search for the well variable traffic environment, and preference route search showed reflection of traffic route search disposition for the driver individual. This paper has five important meaning. (1)The approach is similar to the driver's route selection decision process. (2)The approach is able to control of route appraisal criteria for the multiple attribute. (3)The approach makes subjective judgement objective by a non additive. (4)The approach shows dynamic route search for the alternative route search. (5)The approach is able to consider characteristics of individual drivers attributed for the preference route search.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.209-221
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• 2009

Travel time estimation under given traffic conditions is important for providing drivers with travel time prediction information. But the present expressway travel time estimation process cannot calculate a reliable travel time. The objective of this study is to estimate the path travel time spent in a through lane between origin tollgates and destination tollgates on an expressway as a prerequisite result to offer reliable prediction information. Useful and abundant toll collection system (TCS) data were used. When estimating the path travel time, the path travel time is estimated combining the link travel time obtained through a preprocessing process. In the case of a lack of TCS data, the TCS travel time for previous intervals is referenced using the linear interpolation method after analyzing the increase pattern for the travel time. When the TCS data are absent over a long-term period, the dynamic travel time using the VDS time space diagram is estimated. The travel time estimated by the model proposed can be validated statistically when compared to the travel time obtained from vehicles traveling the path directly. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variaty of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.