• Geomechanics and Engineering
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• v.16 no.6
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• pp.577-588
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• 2018

A major concern in deep excavation project in soft clay deposits is the potential for adjacent buildings to be damaged as a result of the associated excessive ground movements. In order to accurately determine the wall deflections using a numerical procedure such as the finite element method, it is critical to use the correct soil parameters such as the stiffness/strength properties. This can be carried out by performing an inverse analysis using the measured wall deflections. This paper firstly presents the results of extensive plane strain finite element analyses of braced diaphragm walls to examine the influence of various parameters such as the excavation geometry, soil properties and wall stiffness on the wall deflections. Based on these results, a multivariate adaptive regression splines (MARS) model was developed for inverse parameter identification of the soil relative stiffness ratio. A second MARS model was also developed for inverse parameter estimation of the wall system stiffness, to enable designers to determine the appropriate wall size during the preliminary design phase. Soil relative stiffness ratios and system stiffness values derived via these two different MARS models were found to compare favourably with a number of field and published records.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.884-893
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• 2019

Spent fuel racks are steel structures used in the storage of the spent fuel removed from the nuclear power reactor. Rack units are submerged in the depths of the spent fuel pool to keep the fuel cool. Their free-standing design isolates their bases from the pool floor reducing structural stresses in case of seismic event. However, these singular features complicate their seismic analysis which involves a transient dynamic response with geometrical nonlinearities and fluid-structure interactions. An accurate estimation of the response is essential to achieve a safe pool layout and a reliable structural design. An analysis methodology based on the hydrodynamic mass concept and implicit integration algorithms was developed ad-hoc, but some dispersion of results still remains. In order to validate the analysis methodology, vibration tests are carried out on a reduced scale mock-up of a 2-rack system. The two rack mockups are submerged in free-standing conditions inside a rigid pool tank loaded with fake fuel assemblies and subjected to accelerations on a unidirectional shaking table. This article compares the experimental data with the numerical outputs of a finite element model built in ANSYS Mechanical. The in-phase motion of both units is highlighted and the water coupling effect is detailed. Results show a good agreement validating the methodology.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.2
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• pp.165-174
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• 2021

This study describes a method of measurement and verification of array manifold of uniform circular array antenna applicable to multistatic Passive Coherent Location(PCL) system using FM broadcasting. In an environment of outdoor test where FM broadcast signals are scattered, array manifold measurement methods using network analyzer and multi-channel digital receiver are introduced. Also, the descriptions and solutions for the test limits of each measurement method and the considerations affecting the measurement accuracy are presented. In addition, to verify the validity of the measured array manifold, the gain and phase difference were compared with the array manifold data obtained by EM simulation, and the effectiveness and accuracy of the measured array manifolds were compared and analyzed by estimating the direction of arrival of the FM broadcast signal received from the multistatic PCL system.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.24-37
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• 2021

China's "One Belt and One Road" initiative has brought multiple opportunities to the development of tourism in Guangdong, Guangxi and Hainan provinces and the implementation of the Beibu Gulf Urban Agglomeration Development Plan hasset clear goalsforfurther accelerating the coordinated development, in-depth cooperation of the three. This study takes the Beibu Gulf Urban Agglomeration as the research object and utilized the data envelopment analysis (DEA) procedure to estimate the technical efficiency, pure technical efficiency, and scale efficiency scores for each city and Malmquist index was subsequently used to analyze dynamically, then tries to offer an adequate inclusion of sustainable factors in overall tourism development efficiency results through the detection and estimation of potential sources of efficiency. In order to complete the task, data collection was focused on Guangdong, Guangxi and Hainan provinces of China over the period from 2016 to 2018. The results in the first phase show relatively high efficiency scores, particularly in the case of the Beibu Gulf Urban Agglomeration and with room for improvement in the case of other cities of Guangdong, Guangxi and Hainan provinces. The second stage results present several aspects that should be carefully considered in order to analysis tourism efficiency of the Beibu Gulf Urban Agglomerations vertically according to the changes of the frontier.

• Computers and Concrete
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• v.30 no.3
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• pp.225-236
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• 2022

In this article, Multi-Gene Genetic Programming (MGGP) is proposed for the estimation of the compressive strength of concrete. MGGP is known to be a powerful algorithm able to find a relationship between certain input space features and a desired output vector. With respect to most conventional machine learning algorithms, which are often used as "black boxes" that do not provide a mathematical formulation of the output-input relationship, MGGP is able to identify a closed-form formula for the input-output relationship. In the study presented in this article, MGPP was used to predict the compressive strength of plain concrete, concrete with fly ash, and concrete with furnace slag. A formula was extracted for each mixture and the performance and the accuracy of the predictions were compared to the results of Artificial Neural Network (ANN) and Extreme Learning Machine (ELM) algorithms, which are conventional and well-established machine learning techniques. The results of the study showed that MGGP can achieve a desirable performance, as the coefficients of determination for plain concrete, concrete with ash, and concrete with slag from the testing phase were equal to 0.928, 0.906, 0.890, respectively. In addition, it was found that MGGP outperforms ELM in all cases and its' accuracy is slightly less than ANN's accuracy. However, MGGP models are practical and easy-to-use since they extract closed-form formulas that may be implemented and used for the prediction of compressive strength.

• Geomechanics and Engineering
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• v.28 no.4
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• pp.359-374
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• 2022

Geology conditions are crucial in decision-making during the planning and design phase of a tunnel project. Estimation of the geology conditions of road tunnels is subject to significant uncertainties. In this work, the effectiveness of a novel regression method in estimating geological or geotechnical parameters of road tunnel projects was explored. This method, called Gaussian process regression (GPR), formulates the learning of the regressor within a Bayesian framework. The GPR model was trained with data of old tunnel projects. To verify its feasibility, the GPR technique was applied to a road tunnel to predict the state of three geological/geomechanical parameters of Rock Mass Rating (RMR), Rock Structure Rating (RSR) and Q-value. Finally, in order to validate the GPR approach, the forecasted results were compared to the field-observed results. From this comparison, it was concluded that, the GPR is presented very good predictions. The R-squared values between the predicted results of the GPR vs. field-observed results for the RMR, RSR and Q-value were obtained equal to 0.8581, 0.8148 and 0.8788, respectively.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.E3
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• pp.101-107
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• 2001

Source profiles were developed for a total of 45 volatile organic compounds (VOC) that can be emitted from gasoline evaporation. The gasoline samples of five major brands (for each season) were blended on the basis of the market share in Seoul area and analyzed by a GC-MS/FID system. In addition, we calculated gasoline evaporative compositions using the Raoult's law from the liquid gasoline compositions. The measured and estimated gasoline vapor compositions agree well each other. As a group, alkanes are the most abundant in the gasoline vapors profiles (77.4% on average), followed by alkenes (19.1%), and aromatics (1.7%). As a specie in gasoline vapor, i-pentane is the most abundant, followed by n-butane, n-pentane, i-butane, trans-and cis-2-butenes, 2-methyl-2-butene, and trans-and cis-2-pentenes . It was also seen that aromatic content was much lower in the vapor phase compositions. From the comparison between experimental and calculated compositions, we identified the fact that once the gasoline vapor composition is reliably constructed entirely from the measured gasoline composition and the Raoult's law calculations, the need for doing separate chemical analyses of the gasoline vapor can be reduced.

• Advances in nano research
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• v.13 no.5
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• pp.499-512
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• 2022

This study investigates the efficiency of ensemble machine learning for predicting the lightweight-aggregate concrete (LWC) characteristics. A stacking ensemble (STEN) approach was proposed to estimate the dry density (DD) and 28 days compressive strength (Fc-28) of LWC using two meta-models called random forest regressor (RFR) and extra tree regressor (ETR), and two novel ensemble models called STEN-RFR and STEN-ETR, were constructed. Four standalone machine learning models including artificial neural network, gradient boosting regression, K neighbor regression, and support vector regression were used to compare the performance of the proposed models. For this purpose, a sum of 140 LWC mixtures with 21 influencing parameters for producing LWC with a density less than 1000 kg/m³, were used. Based on the experimental results with multiple performance criteria, it can be concluded that the proposed STEN-ETR model can be used to estimate the DD and Fc-28 of LWC. Moreover, the STEN-ETR approach was found to be a significant technique in prediction DD and Fc-28 of LWC with minimal prediction error. In the validation phase, the accuracy of the proposed STEN-ETR model in predicting DD and Fc-28 was found to be 96.79% and 81.50%, respectively. In addition, the significance of cement, water-cement ratio, silica fume, and aggregate with expanded glass variables is efficient in modeling DD and Fc-28 of LWC.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.429-431
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• 2022

하지 웨어러블 로봇의 근력 보조 성능을 극대화하기 위해서는 착용자의 보행 상태를 인식하는 보행 위상 추정 기술이 필수적으로 요구된다. 본 논문에서는 착용자의 보행 속도 변화 및 착용자 간 보행 특성 차이에도 강인하게 보행 위상을 추정할 수 있는 LSTM 기반 보행 위상 강건 인식 기술을 개발하였다. 웨어러블 고관절 보조 로봇을 착용한 총 5명의 트레드밀 및 실외 overground의 보행 센서 정보를 바탕으로 학습을 수행하였다. 저속 및 고속 보행을 포함한 다양한 보행 속도에서 정밀한 보행 위상 추정이 가능한 웨어러블 센서 조합을 도출하였고, 보행 위상 인식 정밀성은 5-Fold Cross Validation 기준 RMSE 약 1.68% 수준의 결과를 얻을 수 있었다.

• Smart Structures and Systems
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• v.33 no.1
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• pp.41-53
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• 2024

Grouting sleeves are an essential connecting component of prefabricated components, and the quality of grouting has a significant influence on structural integrity and seismic performance. The embedded grouting sleeve (EGS)'s grouting defects are highly undetectable and random, and no effective monitoring method exists. This paper proposes an ultrasonic guided wave method and provides a set of guidelines for selecting the optimal frequency and suitable period for the EGS. The optimal frequency was determined by considering the group velocity, wave structure, and wave attenuation of the selected mode. Guided waves are prone to multi-modality, modal conversion, energy leakage, and dispersion in the EGS, which is a multi-layer structure. Therefore, a time-reversal (TR)-based multi-mode focusing and dispersion automatic compensation technology is introduced to eliminate the multi-mode phase difference in the EGS. First, the influence of defects on guided waves is analyzed according to the TR coefficient. Second, two major types of damage indicators, namely, the time domain and the wavelet packet energy, are constructed according to the influence method. The constructed wavelet packet energy indicator is more sensitive to the changes of defecting than the conventional time-domain similarity indicator. Both numerical and experimental results show that the proposed method is feasible and beneficial for the detection and quantitative estimation of the grouting defects of the EGS.