• 한국공간구조학회논문집
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• 제23권3호
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.

• Structural Engineering and Mechanics
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• 제87권6호
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• pp.541-554
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• 2023

An unbraced cantilever beam subjected to loads which cause bending about the major axis may buckle in a flexuraltorsional mode by deflecting laterally and twisting. For the efficient design of these structures, design engineers require a simple accurate equation for the elastic flexural-torsional buckling load. Existing solutions for the flexural-torsional buckling of cantilever beams have mainly been derived by numerical methods which are tedious to implement. In this research, an attempt is made to derive a theoretical equation by the energy method using different buckled shapes. However, the results of a finite element flexural-torsional buckling analysis reveal that the buckled shapes for the lateral deflection and twist rotation are different for cantilever beams. In particular, the buckled shape for the twist rotation also varies with the section size. In light of these findings, the finite element flexural-torsional buckling analysis was then used to derive simple accurate equations for the elastic buckling load and moment for cantilever beams subjected to end point load, uniformly distributed load and end moment. The results are compared with previous research and it was found that the equations derived in this study are accurate and simple to use.

• International journal of advanced smart convergence
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• 제12권1호
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• pp.92-100
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• 2023

Wireless communication technology is becoming increasingly prevalent in smart factories, but the rise in the number of wireless devices can lead to interference in the ISM band and obstacles like metal blocks within the factory can weaken communication signals, creating radio shadow areas that impede information exchange. Consequently, accurately determining the radio communication coverage range is crucial. To address this issue, a Radio Environment Map (REM) can be used to provide information about the radio environment in a specific area. In this paper, a technique for estimating an indoor REM usinga mobile robot and machine learning methods is introduced. The mobile robot first collects and processes data, including the Received Signal Strength Indicator (RSSI) and location estimation. This data is then used to implement the REM through machine learning regression algorithms such as Extra Tree Regressor, Random Forest Regressor, and Decision Tree Regressor. Furthermore, the numerical and visual performance of REM for each model can be assessed in terms of R2 and Root Mean Square Error (RMSE).

• 대한한방내과학회지
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• 제43권6호
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• pp.1247-1254
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• 2022

Objectives: The purpose of this study was to report the clinical effects of pharmacopuncture, acupuncture, and ohrimsan on prostatitis that was not improved by antibiotics. Methods: The patient underwent So-Yeom pharmacopuncture injection, acupuncture, and ohrimsan. A numerical rating scale (NRS) was used to obtain a sense of residual urine and the National Institute of Health Chronic Prostatitis Symptom Index (NIH-CPSI) was used to evaluate the treatment effects. Results: NRS for the sense of residual urine decreased from 70 before treatment to 0 after treatment. The NIH-CPSI was 19 on the first day of admission and decreased to 8 on the day of discharge. No side effects were observed after treatment. Conclusions: The traditional Korean medicine of pharmacopuncture, acupuncture, and ohrimsan is effective for treating prostatitis that is not improved by antibiotics.

• Structural Engineering and Mechanics
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• 제86권1호
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• pp.29-48
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• 2023

Pounding happens when contiguous structures with differing heights vibrate out of line caused by a seismic activity. The situation is aggravated due to the insufficient separation gap between the structures which can lead to the crashing of the buildings or total collapse of an edifice. Countries around the world have compiled building standards to address the pounding issue. One of the strategies recommended is the introduction of the separation gap between structures. AS1170.4-2007 is an Australian standard that requires 1% of the building height as a minimum separation gap between buildings to preclude pounding. This article presents experimental and numerical tests to determine the adequacy of this specification to prevent the occurrence of seismic pounding between steel frame structures under near-field and far-field earthquakes. The results indicated that the recommended minimum separation gap based on the Australian Standard is inaccurate if low-rise structure in a coupled case is utilised under both near and far field earthquakes. The standard is adequate if a tall building is involved but only when a far-field earthquake happens. The research likewise presents results derived by using the ABS and SRSS methods.

• 한국전자통신학회논문지
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• 제18권3호
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• pp.535-544
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• 2023

본 논문에서는 희망하는 빔포밍을 실현하기 위하여 LMS 알고리즘(반복법)을 이용하는 경우에 반복 계산과정에서 무게 분포를 조절하기 위한 기울기 벡터의 계산법(해석적인 방법, 중앙유한차분법)이 적응 빔포밍에 미치는 영향을 연구하였다. 이를 위하여 임의로 설정한 빔폭을 갖는 준이상 빔과 회전 빔, 그리고 멀티 빔을 예로 하여 검토하였다. 수치 실험은 적응 빔포밍 시스템에 임의의 초기치와 시행착오를 거쳐서 설정한 적절한 값의 스텝 파라미터를 두 계산법에 동일하게 적용하고, 기울기 벡터의 계산을 위한 두 가지 방법을 이용하여 적응성과 오차를 평가하는 목적 함수의 수렴 특성 등을 비교하였다.

• 한국지반공학회논문집
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• 제23권10호
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• pp.85-96
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• 2007

쏘일 네일 공법은 기존의 지보공법에 비해 시공의 편리성과 경제성, 안정성이 우수하여 최근 현장에 적용되는 사례가 증가하고 있다. 하지만, 쏘일 네일 공법에 대한 공학적인 접근은 미흡하여 우리나라에서는 지금까지 체계적인 설계 공법이 확립되지 못한 실정이다. 기존의 쏘일 네일 공법 설계에는 네일에 작용하는 전단 저항 및 휨 저항을 고려하지 않았으나, 철근과 시멘트로 구성된 쏘일 네일은 전단 및 휨에 대한 저항을 가지고 있다. 따라서, 본 논문에서는 네일의 전단 및 휨 저항을 고려한 쏘일 네일 보강시 수치해석 프로그램인 $FLAC^{2D}$를 이용해 사면의 안정성을 분석하였다.

• Structural Engineering and Mechanics
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• 제81권1호
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• pp.93-102
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• 2022

The optimum design of reinforced concrete cantilever retaining walls subjected to seismic loads is an extremely important challenge in structural and geotechnical engineering, especially in seismic zones. This study proposes an adaptive sperm swarm optimization algorithm (ASSO) for economic design of retaining structure under static and seismic loading. The proposed ASSO algorithm utilizes a time-varying velocity damping factor to provide a fine balance between the explorative and exploitative behavior of the original method. In addition, the new method considers a reasonable velocity limitation to avoid the divergence of the sperm movement. The proposed algorithm is benchmarked with a set of test functions and the results are compared with the standard sperm swarm optimization (SSO) and some other robust metaheuristic from the literature. For seismic optimization of retaining structures, Mononobe-Okabe method is employed for dynamic loading conditions and total construction cost of the structure is considered as the single objective function. The optimization constraints include both geotechnical and structural restrictions and the design variables are the geometrical dimensions of the wall and the amount of steel reinforcement. Finally, optimization of two benchmark retaining structures under static and seismic loads using the ASSO algorithm is presented. According to the numerical results, the ASSO may provide better optimal solutions, and the designs obtained by ASSO have a lower cost by up to 20% compared with some other methods from the literature.

• Steel and Composite Structures
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• 제42권1호
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• pp.23-32
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• 2022

In this paper, a nonlinear numerical method to solve the large deflection problem is introduced. And the non-dimensional load-deflection behavior of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) plates is parametrically investigated. The large deflection problem is formulated according to the von Kármán nonlinear theory and the (1,1,0)^* hierarchical model, and it is approximated by 2-D natural element method (NEM). The shear locking phenomenon is suppressed by the selectively reduced integration method. The nonlinear matrix equations are solved by combining the incremental loading scheme and the Newton-Raphson iteration method. The proposed method is validated from the benchmark experiments, where the propose method shows an excellent agreement with the reference methods. The nonlinear behavior of FG-CNTRC plates is evaluated in terms of the non-dimensional load-deflection curve, and it is parametrically investigated with respect to the existence/non-existence and gradient pattern of CNTs, the width-to-thickness and aspect ratios of plates and the type of boundary conditions. The non-dimensional central deflection is significantly reduced when CNTs and added, and it decreases with the volume fraction of CNTs. But, it shows a uniform increase in proportion to the width-to-thickness and aspect ratios. Both the gradient pattern of CNTs and the type of boundary conditions do also show the remarkable effects.

• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1428-1438
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• 2023

A novel Fission Diffusion Synthetic Acceleration (FDSA) method is developed and implemented as a part of a hybrid neutronics method for source convergence acceleration and variance reduction in Monte Carlo (MC) criticality calculations. The acceleration of the MC calculation stems from constructing a synthetic operator and solving a low-order problem using information obtained from previous MC calculations. By applying the P₁ approximation, two correction terms, one for the scalar flux and the other for the current, can be solved in the low-order problem and applied to the transport solution. A variety of one-dimensional (1-D) and two-dimensional (2-D) numerical tests are constructed to demonstrate the performance of FDSA in comparison with the standalone MC method and the coupled MC and Coarse Mesh Finite Difference (MC-CMFD) method on both intended purposes. The comparison results show that the acceleration by a factor of 3-10 can be expected for source convergence and the reduction in MC variance is comparable to CMFD in both slab and full core geometries, although the effectiveness of such hybrid methods is limited to systems with small dominance ratios.