• Structural Engineering and Mechanics
• /
• 제27권2호
• /
• pp.199-222
• /
• 2007

Composite laminated structures supported on elastic foundations are being increasingly used in a great variety of engineering applications. Composites exhibit larger dispersion in their material properties compared to the conventional materials due to large number of parameters associated with their manufacturing and fabrication processes. And also the dispersion in elastic foundation stiffness parameter is inherent due to inaccurate modeling and determination of elastic foundation properties in practice. For a better modeling of the material properties and foundation, these are treated as random variables. This paper deals with effects of randomness in material properties and foundation stiffness parameters on the free vibration response of laminated composite plate resting on an elastic foundation. A $C^0$ finite element method has been used for arriving at an eigen value problem. Higher order shear deformation theory has been used to model the displacement field. A mean centered first order perturbation technique has been employed to handle randomness in system properties for obtaining the stochastic characteristic of frequency response. It is observed that small amount of variations in random material properties and foundation stiffness parameters significantly affect the free vibration response of the laminated composite plate. The results have been compared with those available in the literature and an independent Monte Carlo simulation.

• 한국군사과학기술학회지
• /
• 제23권4호
• /
• pp.346-354
• /
• 2020

Nowadays, it is required to apply low observable technology to weapon systems in operation or under development. Radar Cross Section(RCS) is a measure of the scattered power in an given direction when a target is illuminated by an incident wave and used as a parameter to estimate the low observable performance of weapon system. RCS of a target can be calculated by various numerical methods. However, measurement is also needed to estimate RCS of a complex target because it is difficult to estimate theoretically. To acquire reliable measurement results, an analysis of measurement uncertainty is essential. In this paper, error components and uncertainties of near-field RCS measurement system which was constructed in ASTEC(Aerospace System Test & Evaluation Center) were analyzed based on the IEEE recommended practice for radar cross-section test procedures(IEEE Std. 1502-2007) which describes the uncertainty of RCS measurement and unique error components of this near-field measurement system were also identified.

• 품질경영학회지
• /
• 제49권4호
• /
• pp.467-482
• /
• 2021

Purpose: The main theme of this study is to determine the optimal control limit of conditional variance investigation by mathematical approach. According to the determination approach of control limit presented in this study, it is possible with only one parameter to calculate the control limit necessary for budgeting control system or standard costing system, in which the limit could not be set in advance, that's why it has the advantage of high practical application. Methods: This study followed the analytical methodology in terms of the decision model of information economics, Bayesian probability theory and Taguchi's quality loss function concept. Results: The function suggested by this study is as follows; ${\delta}{\leq}\frac{3}{2}(k+1)+\frac{2}{\frac{3}{2}(k+1)+\sqrt{\{\frac{3}{2}(k+1)\}^2}+4$ Conclusion: The results of this study will be able to contribute not only in practice of variance investigation requiring in the standard costing and budgeting system, but also in all fields dealing with variance investigation differences, for example, intangible services quality control that are difficult to specify tolerances (control limit) unlike tangible product, and internal information system audits where materiality standards cannot be specified unlike external accounting audits.

• Nuclear Engineering and Technology
• /
• 제53권9호
• /
• pp.3100-3111
• /
• 2021

Numerical modeling for the safety-related equipment used in a nuclear power plant (i.e., cabinet facilities) plays an essential role in seismic risk assessment. A full finite element model is often time-consuming for nonlinear time history analysis due to its computational modeling complexity. Thus, this study aims to generate a simplified model that can capture the nonlinear behavior of the electrical cabinet. Accordingly, the distributed plasticity approach was utilized to examine the stiffness-degradation effect caused by the local buckling of the structure. The inherent dynamic characteristics of the numerical model were validated against the experimental test. The outcomes indicate that the proposed model can adequately represent the significant behavior of the structure, and it is preferred in practice to perform the nonlinear analysis of the cabinet. Further investigations were carried out to evaluate the seismic behavior of the cabinet under the influence of the constitutive law of material models. Three available models in OpenSees (i.e., linear, bilinear, and Giuffre-Menegotto-Pinto (GMP) model) were considered to provide an enhanced understating of the seismic responses of the cabinet. It was found that the material nonlinearity, which is the function of its smoothness, is the most effective parameter for the structural analysis of the cabinet. Also, it showed that implementing nonlinear models reduces the seismic response of the cabinet considerably in comparison with the linear model.

• 한국지진공학회논문집
• /
• 제25권3호
• /
• pp.93-102
• /
• 2021

The dynamic characterization of a three-story auxiliary building in a nuclear power plant (NPP) constructed with a monolithic reinforced concrete shear wall is investigated in this study. The shear wall is subjected to a joint-research, round-robin analysis organized by the Korea Atomic Energy Research Institute, South Korea, to predict seismic responses of that auxiliary building in NPP through a shake table test. Five different intensity measures of the base excitation are applied to the shaking table test to get the acceleration responses from the different building locations for one horizontal direction (front-back). Simultaneously to understand the global damage scenario of the structure, a frequency search test is conducted after each excitation. The primary motivation of this study is to develop a nonlinear numerical model considering the multi-layered shell element and compare it with the test result to validate through the modal parameter identification and floor responses. In addition, the acceleration amplification factor is evaluated to judge the dynamic behavior of the shear wall with the existing standard, thus providing theoretical support for engineering practice.

• Earthquakes and Structures
• /
• 제16권1호
• /
• pp.119-127
• /
• 2019

When a structural wall is subjected to multi-directional ground motion, torsion-induced cracks degrade the stiffness of the wall. The effect of torsion should not be neglected. As a main lateral load resisting member, reinforced concrete (RC) structural wall has been widely studied under the combined action of bending and shear. Unfortunately, its seismic behavior under a combined action of torsion, bending and shear is rarely studied. In this study, torsional performances of the RC structural walls under the combined action is assessed from a comprehensive parametrical study. Finite element (FE) models are built and calibrated by comparing with the available experimental data. The study is then carried out to find out the critical design parameter affecting the torsional stiffness of RC structural walls, including the axial load ratio, aspect ratio, leg-thickness ratio, eccentricity of lateral force, longitudinal reinforcement ratio and transverse reinforcement ratio. Besides, to facilitate the application in practice, an empirical equation is developed to estimate the torsional stiffness of RC rectangular structural walls conveniently, which is found to agree well with the numerical results of the developed FE models.

• Smart Structures and Systems
• /
• 제29권4호
• /
• pp.599-616
• /
• 2022

Bridge displacement contains vital information for bridge condition and performance. Due to the limits of direct displacement measurement methods, the indirect displacement reconstruction methods based on the strain or acceleration data are also developed in engineering applications. There are still some deficiencies of the displacement reconstruction methods based on strain or acceleration in practice. This paper proposed a novel method based on long short-term memory (LSTM) networks to reconstruct the bridge dynamic displacements with the strain and acceleration data source. The LSTM networks with three hidden layers are utilized to map the relationships between the measured responses and the bridge displacement. To achieve the data fusion, the input strain and acceleration data need to be preprocessed by normalization and then the corresponding dynamic displacement responses can be reconstructed by the LSTM networks. In the numerical simulation, the errors of the displacement reconstruction are below 9% for different load cases, and the proposed method is robust when the input strain and acceleration data contains additive noise. The hyper-parameter effect is analyzed and the displacement reconstruction accuracies of different machine learning methods are compared. For experimental verification, the errors are below 6% for the simply supported beam and continuous beam cases. Both the numerical and experimental results indicate that the proposed data fusion method can accurately reconstruct the displacement.

• Geomechanics and Engineering
• /
• 제34권5호
• /
• pp.561-575
• /
• 2023

This study investigates to provide a fast solution to the problem of bearing capacity in layered soils with easily obtainable parameters that does not require the use of any charts or calculations of different parameters. Therefore, a hybrid approach including both the finite element (FE) method and machine learning technique have been applied. Firstly, a FE model has been generated which is validated by the results of in-situ loading tests. Then, a total of 192 three-dimensional FE analyses have been performed. A data set has been created utilizing the soil properties, footing sizes, layered conditions used in the FE analyses and the ultimate bearing capacity values obtained from the FE analyses to be used in multigene genetic programming (MGGP). Problem has been modeled with five input and one output parameter to propose a bearing capacity formula. Ultimate bearing capacity values estimated from the proposed formula using data set consisting of 20 data independent of total data set used in MGGP modelling have been compared to the bearing capacities calculated with semi-empirical methods. It was observed that the MGGP method yielded successful results for the problem considered. The proposed formula provides reasonable predictions and efficient enough to be used in practice.

• International Journal of Computer Science & Network Security
• /
• 제23권10호
• /
• pp.115-128
• /
• 2023

Deep learning has been incorporating various optimization techniques motivated by new pragmatic optimizing algorithm advancements and their usage has a central role in Machine learning. In recent past, new avatars of various optimizers are being put into practice and their suitability and applicability has been reported on various domains. The resurgence of novelty starts from Stochastic Gradient Descent to convex and non-convex and derivative-free approaches. In the contemporary of these horizons of optimizers, choosing a best-fit or appropriate optimizer is an important consideration in deep learning theme as these working-horse engines determines the final performance predicted by the model. Moreover with increasing number of deep layers tantamount higher complexity with hyper-parameter tuning and consequently need to delve for a befitting optimizer. We empirically examine most popular and widely used optimizers on various data sets and networks-like MNIST and GAN plus others. The pragmatic comparison focuses on their similarities, differences and possibilities of their suitability for a given application. Additionally, the recent optimizer variants are highlighted with their subtlety. The article emphasizes on their critical role and pinpoints buttress options while choosing among them.

• 한국철도학회논문집
• /
• 제12권1호
• /
• pp.31-38
• /
• 2009

국내에서 터널 설계시 암반의 물리적, 역학적 특성에 따라서 $5{\sim}6$개의 암반등급으로 분류한 후 터널의 용도 및 특성을 고려하여 지보시스템을 결정하게 된다. 그러나 이와 같은 방법은 암반의 특성이 균일하다는 가정을 하고 있으며 암반특성이 종 방향으로 변화될 경우 이에 대한 지보시스템의 친정이 달라져야 한다. 본 연구는 3차원 수치해석 프로그램(FLAC3D)을 이용하여 NATM 터널시공시 암반특성의 종방향 변화가 암반분류 및 지보시스템 결정에 미치는 영향을 파악하고자 총 14Case를 현장의 시공순서를 고려한 해석을 수행하였다. 암반특성의 종방향 변화시 전 후방 암반의 강성차이가 작은 경우에는 암반경계를 기준으로 0.5D내외, 강성차이가 큰 경우에는 1.0D 내외의 범위에서 유리한 암반등급의 거동과는 다르므로 암반특성에 따라서 암반경계층을 기준으로 $0.5D{\sim}1.0D$구간을 안전측(보수적)으로 평가하여 설계에 반영하거나, 지보패턴을 하향조정하는 것이 시공성, 작업효율성, 공사기간 등의 측면에서 효과적일 것으로 판단된다.