• Structural Engineering and Mechanics
• /
• v.85 no.1
• /
• pp.89-104
• /
• 2023

This work presents a proposal for employing reduced numerical integration in the formulation of the 4-node quadrilateral solid finite element. The use of these low-order integration rules leads to numerical instabilities such as those producing the hourglass effect. The proposed procedure allows evaluating a given constitutive model only in one integration point, achieving an attractive computational cost reduction and, also, successfully controls the hourglass effect. A validation of the proposal is included and discussed throughout the paper. To show the efficiency of the proposal, several application examples of masonry structures are studied and discussed. To represent the non-linear mechanical behaviour of masonry a plastic-damage model is implemented within the application of this sub-integration scheme. Also, in order to have a full and computationally efficient strategy to determine the behaviour of masonry structures, involving its evolution to collapse, a homogenization technique with a macro-modeling approach is used. The methodology discussed throughout this paper demonstrates a substantial computational cost reduction and an improved approximation of the non-linear problem evidenced by a reduction of up to 85% of the computational time for some cases.

• Nuclear Engineering and Technology
• /
• v.54 no.1
• /
• pp.36-48
• /
• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Nuclear Engineering and Technology
• /
• v.54 no.5
• /
• pp.1825-1834
• /
• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.2
• /
• pp.21-32
• /
• 1997

This paper proposes an elliptical world-modeling mehtrod in order to secure the safety of the mobile robot from the unreliability of ultrasonic sensors and to estimate the lateral orientation of the detected objects. This method is advnatageous because the total amount of data that the robot utilizes is reduced when historical and new data are clusterd during each sensing period and also because the objects in the environment can be almost exactly recognized. This paper also proposes a new local path planning algorithm which is divided into four different situations and gudies the robot through the safe local path using dat acollected in elliptical form. This algorithm can help the AMR navigate by allowing it to sum up the virtual vector forces made form the ellipses in order to select a safe subgoal. This local path plannin gmehtod using the elliptical world model has been proved by several navigation experiments.

• Journal of the korean Society of Automotive Engineers
• /
• v.10 no.2
• /
• pp.54-60
• /
• 1988

This paper presents a study of tool-life equation on cut-off test by the statistical approach, referred to as response surface methodology instead of a conventional one-variable at a time method. It is the merit of response surface methodology that the test time is reduced to minimize the size and accurate analysis can be done. The reliability of such an equation can also be estimated. Two independent variables, cutting speed and feed rate, were investigated. A first order modeling equation is presented in this project. The results of this study are as follows that tool-life in cut-off operation is affected by cutting speed more than feed, and first order tool-life predicting equations are in good agreement with experimental results.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.664-669
• /
• 2003

This paper proposes a swing-arm type dual-stage actuator, which consists of a PZT actuator for fine motion and a VCM(Voice Coil Motor) for coarse motion, for SFF ODD(Small Form Factor Optical Disk Drive), in order to achieve fast access speed and precise track following control. We focus our attention on the design and control of the PZT actuator, because there have been a lot of previous researches related to the VCM and dual-stage actuators. Due to the dual cantilever structure, the PZT actuator can generate precise translational tracking motion at its tip where optical pickup is attached at, and the effect of hysteric behavior of the PZT element is reduced. The dynamic model of the PZT actuator is derived by using the Hamilton's principle, and verified by comparing with the experimental frequency response. The sliding mode control is designed in order to be robust against modeling uncertainties. Simulations and experimental results confirm the effectiveness of the suggested control scheme.

• Journal of Mechanical Science and Technology
• /
• v.14 no.5
• /
• pp.508-517
• /
• 2000

For shift quality improvement, torque sensors are currently too expensive to be used on production vehicles. To achieve smooth acceleration shift, the reference trajectory of the clutch slip speed for accomplishing the shift process within a designated shift completion time and its relationship with the clutch actuating torque were suggested by Jeong and Lee (1999). In order to facilitate the proposed algorithm, nonlinear estimators for necessary information such as the axle shaft torque, clutch friction and turbine torque were designed using only speed sensors. Accounting for the modeling error, a control law for this indirect smooth shift was proposed based on the above mentioned suggestions. Simulation results of the proposed estimators and shift controller were presented and further considerations for practical applications are discussed.

• KIISE Transactions on Computing Practices
• /
• v.20 no.10
• /
• pp.534-542
• /
• 2014

Multiscale modeling is a new simulation approach which can manage different spatial and temporal scales of system. In this study, as part of multiscale modeling research, we propose the way of combining two different simulation methods, molecular dynamics(MD) and stochastic rotation dynamics(SRD). Our conceptual implementations are based on LAMMPS, one of the well-known molecular dynamics programs. Our prototype of multiscale modeling follows the form of the third party implementation of LAMMPS. It added MD to SRD in order to simulate the boundary area of the simulation box. Because it is important to guarantee the seamless simulation, we also designed the overlap zones and communication zones. The preliminary experimental results showed that our proposed scheme is properly worked out and the execution time is also reduced.

• Journal of the Korean Geotechnical Society
• /
• v.15 no.4
• /
• pp.221-234
• /
• 1999

This paper deals with the application of joint element in the finite element modeling of discontinuities encountered during rock tunneling. A nodal displacement joint element was implemented in a two dimensional finite element program GEOFE2D. The applicability of the joint element for modeling of discontinuities and the numerical stability of the implemented algorithm were examined by comparing the results of reduced small scale model tests as well as commercially available FEM program. The GEOFE2D was then used to analyze a tunnel crossed by a major discontinuity for the purpose of understanding the effect of discontinuity on the tunnel behavior. In addition, a modeling technique for the junction of discontinuity and shotcrete lining was presented. The results of analysis indicated that the stress-strain field around the tunnel is significantly altered by the presence of discontinuity, and that the stresses in the shotcrete lining considerably increase at the junction of the shotcrete lining and the discontinuity. It is therefore concluded that the major discontinuities must be carefully modeled in the finite element analysis of a tunneling problem in order to obtain more reliable results close to actual tunnel behavior.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2005.11a
• /
• pp.190-200
• /
• 2005

In this paper, the image modelling of road's lane markings is established using view frustum(VF) modeling. This algorithm also involve the real time processing of the 3D position coordinate and the distance data from the camera to the points on the 3D world coordinate by the camera calibration. In order to reduce their measurement error, an useful algorithm for which analyze the geometric variations clue to traveling vehicle's fluctuation using VF model is proposed. In experiments, without correction, for instance, the $0.4^{\circ}$ of pitching rotation gives the error of $0.4^{\sim}0.6m$ at the distance of 10m, but the more far distance cause exponentially the more error. We confirmed that this algorithm can be reduced less than 0.1m of error at the same condition.