• The Journal of Korean Academy of Prosthodontics
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• v.55 no.4
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• pp.394-402
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• 2017

Purpose: The purpose of this study is to evaluate the displacement of artificial tooth of monolithic complete denture manufactured by milling and 3D printing method in which the denture base and the artificial teeth are simultaneously made. Materials and methods: Twelve upper and lower complete dentures for each were made by milling and 3D printing method. Group Up and Group Lp are a group of upper and lower dentures made by printing, and Group Um and Group Lm are denture groups made by milling. Group Uc and Group Lc are is a group of finally designed upper and lower dentures respectively. Measurements were performed between both central incisors (AB, ab), both canines (CD, cd), both first molars (EF, ef), between an incisor and a first molar (AE, ae), and between incisor and lingual point (AG, ag) for each upper and lower denture. Results: AG and ag value between printed dentures and original ones as well as between milled dentures and original ones showed a statistically significant difference (One-way ANOVA, P<.05) in both lower and upper monolithic dentures. In the lower monolithic ones, ab, cd and ef value revealed a significant difference between Group Lp and Group Lm (One-way ANOVA, P<.05). Conclusion: Dentures made using milling or 3D printers revealed statistically significant difference compared with those of original data. However, it showed clinically very accurate reproducibility.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.59-70
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• 2008

도심지 터널의 설계, 시공 그리고 유지관리에 있어서 지반 변위 억제와 변형거동 예측은 중요하다. 국내 외 연구자들은 다양한 수치해석적인 기법과 현장 계측 결과를 이용하여 터널 시공과 관련된 변형거동 예측을 시도하였다. 하지만, 설계물성치의 산정과 지반 모델링 그리고 수치해석기법과 관련된 사용상의 어려움에 의해 아직까지 만족스러운 결과를 얻지는 못하였다. 본 논문은 수치해석적인 기법과 인공신경망을 이용하여 도심지 NATM 터널의 설계 물성치 산정과 변형거동 예측에 관한 방법을 제안하였다. 인공신경망 모델 개발을 위한 학습과 테스트과정은 데이터베이스된 수치해석결과를 이용하였다. 개발된 인공신경망 모델은 입력변수인 지반변위와 결과변수인 설계 물성치 간의 상호관계를 적절히 인식할 수 있다. 수치해석은 지반의 연화거동을 모사할 수 있는 변형률 연화모델을 적용하였다. 사례분석에 있어서 굴착 초기단계의 계측 값을 개발된 인공신경망 모델에 입력하여 설계 물성치를 계산하였으며, 수정된 설계 물성치는 수치해석을 통하여 다음 굴착단계에서의 터널 주변의 지반 변형거동을 예측하였다. 본 논문에서 제안된 방법을 토대로 시공조건이 엄밀한 도심지 터널의 설계물성치의 정량적인 평가 및 변형거동 예측이 계측이 입수된 초기 굴착단계에서 가능할 것으로 기대된다.

• Journal of the Korean GEO-environmental Society
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• v.13 no.8
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• pp.25-33
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• 2012

Although it is important to reflect the accurate information of the ground condition in the tunnel design, the analysis and design are conducted by limited information because it is very difficult to consider various geographies and geotechnical conditions. When the tunnel is under construction, examination of accurate safety and prediction of behavior are overcome the limits of predicting behavior by Artificial Neural Network in this study. First, construct the suitable structure after the data of field was made sure by the multi-layer back propagation, then apply with algorithm. Employ the result of measured data from database, and consider the influence factor of tunnel, like supporting pattern, RMR, Q, the types of rock, excavation length, excavation shape, excavation over, to carry out the reliable analysis through field applicability of Artificial Neural Network. After studying, using the ANN model to predict the shearing displacement, convergence displacement, underground displacement, Rock bolt output follow the excavation over of tunnel construction field, then determine the field applicability with ANN through field measured value and comparison analysis when tunnel is being constructed.

• Journal of the Korean Geotechnical Society
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• v.16 no.1
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• pp.83-97
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• 2000

In the present study, artificial neural network based on the multi-layer perceptron is used and an optimum model is chosen through the process of efficiency evaluation in order to develop a system predicting maximum displacements of the earth retaining walls at various excavation stages. By analyzing the measured field data collected at various urban excavation sites in Korea, factors influencing on the behaviors of the excavation wall are examined. Among the measured data collected, reliable data are further selected on the basis of the performance ratio and are used as a data base. Data-based measurements are also utilized for both teaming and verifying the artificial neural network model. The learning is carried out by using the back-propagation algorithm based on the steepest descent method. Finally, to verify a validity of the formulated artificial neural network system, both the magnitude and the occurring position of the maximum horizontal displacement are predicted and compared with measured data at real excavation sites not included in the teaming process.

• Journal of Dental Rehabilitation and Applied Science
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• v.31 no.3
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• pp.186-194
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• 2015

Purpose: To evaluate the effects of implant location and length on stress distribution and displacement in osseointegrated-implants that were associated with mandibular distal extension removable partial dentures (DERPD). Materials and Methods: A sagittally cut model with the #33, #34 teeth and a removable partial denture of the left mandible was used. Seven models were designed with NX 9.0. Models A, B, C had implants with lengths of 11, 6, 4 mm, respectively, under the denture base of the #37 artificial tooth. Models D, E, F had implants with lengths of 11, 6, 4 mm, respectively, under the denture base of the #36 artificial tooth. Model G did not have any implants. Axial force (250 N) was loaded on #36 central fossa. The finite element analysis was performed with MSC Nastran. Von Mises stress maps were plotted to visualize the results. Results: The models of #37 implant placement showed much lower stress concentration on the surrounding bone of the implant compared with #36. The #36 implant position tended to reduce displacement more than #37. Conclusion: When an IARPD is designed, the distal positioning of implant placement has more advantages in the edentulous bone of DERPD on the prognosis of short implants and the stress distribution of edentulous alveolar bone. Using implants with longer lengths are important for stress distribution. However, Additional studies are necessary of the effects of length on implant survival.

• Journal of Biomedical Engineering Research
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• v.17 no.1
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• pp.85-92
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• 1996

A monoleaflet polymer artificial heart valve which showed the remarkable improvement in pressure drop compared with other types of artificial valve was designed to minimize the deflection in vertical direction and the displacement of the valve tip in horizontal direction obtained by using finite element method as the location of the supporting members of the valve frame changed stress distribution change was also studied on each model generated by changing the distance between the frame and supporting members. It was found that by using the valve tip horizontal displacement the minimum valve thickness could be obtained in order to prevent the gap between the valve tip and the frame wall.

• The korean journal of orthodontics
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• v.36 no.6
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• pp.412-421
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• 2006

Objective: The result of finite element analysis depends on material properties, structural expression, density of element, and boundar or loading conditions. To represent proper elastic behavior, a finite element model was made using Hounsfield unit (HU) values in CT images. Methods: A 13 year 6 month old male was used as the subject. A 3 dimensional visualizing program, Mimics, was used to build a 3D object from the DICOM file which was acquired from the CT images. Model 1 was established by giving 24 material properties according to HU. Model 2 was constructed by the conventional method which provides 2 material properties. Protraction force of 500g was applied at a 45 degree downward angle from Frankfort horizontal (FH) plane. Results: Model 1 showed a more flexible response on the first premolar region which had more forward and downward movement of the maxillary anterior segment. Maxilla was bent on the sagittal plane and frontal plane. Model 2 revealed less movement in all directions. It moved downward on the anterior part and upward on the posterior part, which is clockwise rotation of the maxilla. Conclusion: These results signify that different outcomes of finite element analysis can occur according to the given material properties and it is recommended to use HU values for more accurate results.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.1
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• pp.37-53
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• 2012

There is considerable uncertainty in ground properties used in tunnel designs. In this study, a back analysis was performed to find optimal ground properties based on the artificial neural network facility of MATLAB program of using tunnel monitoring data. Total 81 data were constructed by changing elastic modulus and coefficient of lateral pressure which have great influence on tunnel convergence. A sensitivity analysis was conducted to establish an optimal training model by varying the number of hidden layers, the number of nodes, learning rate, and momentum. Meanwhile, the optimal training model was selected by comparing MSE (Mean Squared Error) and coefficient of determination ($R^2$) and was used to find the correct elastic moduli of layers and the coefficient of lateral pressure. In future, it is expected that the suggested method of this study can be applied to determine the optimum tunnel support pattern under given ground conditions.

• Journal of the Korean Geotechnical Society
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• v.20 no.7
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• pp.69-78
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• 2004

In this study, the back analysis program was developed by applying the genetic algorithm, one of artificial intelligence fields, to the direct method. The optimization process which has influence on the efficiency of the direct method was modulated with genetic algorithm. On conditions that the displacement computed by forward analysis for a certain rock mass model was the same as the displacement measured at the tunnel section, back analysis was executed to verify the validity of the program. Usefulness of the program was confirmed by comparing relative errors calculated by back analysis, which is carried out under the same rock mass conditions as analysis model of Gens et at (1987), one of back analysis case in the past. We estimated the total displacement occurring by tunnelling with the crown settlement and convergence measured at the working faces in three tunnel sites of Kyungbu Express railway. Those data measured at the working face are used for back analysis as the input data after confidence test. As the results of the back analysis, we comprehended the tendency of tunnel behaviors with comparing the respective deformation characteristics obtained by the measurement at the working face and by back analysis. Also the usefulness and applicability of the back analysis program developed in this study were verified.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.2
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• pp.76-82
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• 2018

In this present study, in order to update the finite element model considering the boundary conditions, a method has been proposed. The conventional finite element model updating method, updates the finite element model by using the dynamic characteristics (natural frequency, mode shape) which can be estimated from the ambient vibration test. Therefore, prediction of the static response of an actual structure is difficult. Furthermore, accurate estimation of the physical properties is relatively hard. A novel method has been proposed to overcome the limitations of conventional method. Initially, the proposed method estimates the rotational spring constant of a finite element model using the deflection of structure and the rotational displacement of support measurements. The final updated finite element model is constructed by estimating the material properties of the structure using the finite element model with updated rotational spring constant and the dynamic characteristics of the structure. The proposed finite element model updating method is validated through numerical simulation and compared with the conventional finite element model updating method.