• Korea-Australia Rheology Journal
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• 제12권1호
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• pp.83-92
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• 2000

In resin transfer molding (RTM) process, preplaced fiber mat is set up in a mold and thermoset resin is injected into the mold. An important interest in RTM process is to minimize cycle time without sacrificing part quality or increasing cost. In this study, the numerical simulation and optimization process in filling stage were conducted in order to determine the optimum gate locations. Control volume finite element method (CVFEM) was used in this numerical analysis with the coordinate transformation method to analyze the complex 3-dimensional structure. Experiments were performed to monitor the flow front to validate simulation results. The results of numerical simulation predicted well the experimental results with every single, simultaneous and sequential injection procedure. We performed the optimization analysis for the sequential injection procedure to minimize fill time. The complex geometry of an automobile bumper core was chosen. Genetic algorithm was used in order to determine the optimum gate locations with regard to 3-step sequential injection case. These results could provide the information of the optimum gate locations in each injection step and could predict fill time and flow front.

• Steel and Composite Structures
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• 제49권1호
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• pp.1-17
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• 2023

Based on Ahmadzadeh-Varvani hardening rule (A-V model), multiaxial ratcheting effect of Z2CND18.12N austenitic stainless steel is simulated by ABAQUS with user subroutine UMAT. The results show that the predicted results of the origin multiaxial A-V model are lower than the experimental data, and it is difficult to control ratcheting strain rate. In order to improve the predicted capability of A-V model, the A-V model is modified. In this study. Moreover, under the assumption of the von Mises yield criterion and normal plasticity flow rule, we develop a numerical algorithm of plastic strain with the improved model to implement the finite element calculation of the model. Internal iteration in the numerical algorithm was implemented with the Euler backward method, which calculated the trial strain for each equilibrium iteration using the consistent tangent matrix. With a user subroutine, the proposed model is programmed into ABAQUS for a user - executable version. By simulating the uniaxial ratcheting of a round bar made of Z2CND18.12N austenitic stainless steel, we observe that the predicted results simulated by ABAQUS with UMAT are compared with the experimental data. The predicted results of the improved multiaxial A-V model are consistent well with the experimental data.

• Structural Engineering and Mechanics
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• 제32권5호
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

• Journal of applied mathematics & informatics
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• 제26권1_2호
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• pp.213-222
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• 2008

Iterative methods are often suitable for solving least squares problems min$||Ax-b||_2$, where A $\epsilon\;\mathbb{R}^{m{\times}n}$ is large and sparse. The well known LSQR algorithm is among the iterative methods for solving these problems. A good preconditioner is often needed to speedup the LSQR convergence. In this paper we present the numerical experiments of applying a well known preconditioner for the LSQR algorithm. The preconditioner is based on the $A^T$ A-orthogonalization process which furnishes an incomplete upper-lower factorization of the inverse of the normal matrix $A^T$ A. The main advantage of this preconditioner is that we apply only one of the factors as a right preconditioner for the LSQR algorithm applied to the least squares problem min$||Ax-b||_2$. The preconditioner needs only the sparse matrix-vector product operations and significantly reduces the solution time compared to the unpreconditioned iteration. Finally, some numerical experiments on test matrices from Harwell-Boeing collection are presented to show the robustness and efficiency of this preconditioner.

• 대한기계학회논문집
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• 제16권2호
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• pp.236-247
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• 1992

Optimization has been developed to minimize the cost function while satisfying constraints. Nonlinear Programming method is used as a tool for the optimization. Usually, cost and constraint function calculations are required in the engineering applications, but those calculations are extremely expensive. Especially, the function and sensitivity analyses cause a bottleneck in structural optimization which utilizes the Finite Element Method. Also, when the functions are quite noisy, the informations do not carry out proper role in the optimization process. An algorithm called "Second-order Approximation Method" has been proposed to overcome the difficulties recently. The cost and constraint functions are approximated by the second-order Taylor series expansion on a nominal points in the algorithm. An optimal design problem is defined with the approximated functions and the approximated problem is solved by a nonlinear programming numerical algorithm. The solution is included in a candidate point set which is evaluated for a new nominal point. Since the functions are approximated only by the function values, sensitivity informations are not needed. One-dimensional line search is unnecessary due to the fact that the nonlinear algorithm handles the approximated functions. In this research, the method is analyzed and the performance is evaluated. Several mathematical problems are created and some standard engineering problems are selected for the evaluation. Through numerical results, applicabilities of the algorithm to large scale and complex problems are presented.presented.

• 한국공간구조학회논문집
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• 제22권2호
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• pp.39-46
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• 2022

Recently, machine learning is widely used to solve optimization problems in various engineering fields. In this study, machine learning is applied to development of a control algorithm for a smart control device for reduction of seismic responses. For this purpose, Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm. A single degree of freedom (SDOF) structure with a smart tuned mass damper (TMD) was used as an example structure. A smart TMD system was composed of MR (magnetorheological) damper instead of passive damper. Reward design of reinforcement learning mainly affects the control performance of the smart TMD. Various hyper-parameters were investigated to optimize the control performance of DQN-based control algorithm. Usually, decrease of the time step for numerical simulation is desirable to increase the accuracy of simulation results. However, the numerical simulation results presented that decrease of the time step for reward calculation might decrease the control performance of DQN-based control algorithm. Therefore, a proper time step for reward calculation should be selected in a DQN training process.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.756-768
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• 2023

Neutron transport calculations are extremely challenging due to the high computational cost of large and complex problems. A multilevel octree grid algorithm (MLTG) of discrete ordinates method was developed to improve the modeling accuracy and simulation efficiency on 3-D Cartesian grids. The Balakovo-3 VVER-1000 neutron dosimetry benchmark is calculated to verify and validate this numerical technique. A simplified S₂ synthetic acceleration is used in the MLTG calculation method to improve the convergence of the source iterations. For the triangularly arranged fuel pins, we adopt a source projection algorithm to generate pin-by-pin source distributions of hexagonal assemblies. MLTG provides accurate geometric modeling and flexible fixed source description at a lower cost than traditional Cartesian grids. The total number of meshes is reduced to 1.9 million from the initial 9.5 million for the Balakovo-3 model. The numerical comparisons show that the MLTG results are in satisfactory agreement with the conventional S_N method and experimental data, within the root-mean-square errors of about 4% and 10%, respectively. Compared to uniform fine meshing, approximately 70% of the computational cost can be saved using the MLTG algorithm for the Balakovo-3 computational model.

• Advances in Computational Design
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• 제9권1호
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• pp.1-23
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• 2024

Present paper deals with the cost effective design of reinforced concrete building frame employing unified particle swarm optimization (UPSO). A building frame with G+8 stories have been adopted to demonstrate the effectiveness of the present algorithm. Effect of seismic loads and wind load have been considered as per Indian Standard (IS) 1893 (Part-I) and IS 875 (Part-III) respectively. Analysis of the frame has been carried out in STAAD Pro software.The design loads for all the beams and columns obtained from STAAD Pro have been given as input of the optimization algorithm. Next, cost optimization of all beams and columns have been carried out in MATLAB environment using UPSO, considering the safety and serviceability criteria mentioned in IS 456. Cost of formwork, concrete and reinforcement have been considered to calculate the total cost. Reinforcement of beams and columns has been calculated with consideration for curtailment and feasibility of laying the reinforcement bars during actual construction. The numerical analysis ensures the accuracy of the developed algorithm in providing the cost optimized design of RC building frame considering safety, serviceability and constructional feasibilities. Further, Monte Carlo simulations performed on the numerical results, proved the consistency and robustness of the developed algorithm. Thus, the present algorithm is capable of giving a cost effective design of RC building frame, which can be adopted directly in construction site without making any changes.

• ETRI Journal
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• 제24권1호
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• pp.43-55
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• 2002

This paper proposes a flow-based admission control algorithm through an Asynchronous Transfer Mode (ATM) based Multi-Protocol Label Switching (MPLS) network for multiple service class environments of Integrated Service (IntServ) and Differentiated Service (DiffServ). We propose the Integrated Packet Scheduler to accommodate IntServ and Best Effort traffic through the DiffServ-aware MPLS core network. The numerical results of the proposed algorithm achieve reliable delay-bounded Quality of Service (QoS) performance and reduce the blocking probability of high priority service in the DiffServ model. We show the performance behaviors of IntServ traffic negotiated by end users when their packets are delivered through the DiffServ-aware MPLS core network. We also show that ATM shortcut connections are well tuned with guaranteed QoS service. We validate the proposed method by numerical analysis of its performance in such areas as throughput, end-to-end delay and path utilization.

• Journal of applied mathematics & informatics
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• 제32권1_2호
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• pp.211-225
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• 2014

A new class of smoothing functions is introduced in this paper, which includes some important smoothing complementarity functions as its special cases. Based on this new smoothing function, we proposed a smoothing Newton method. Our algorithm needs only to solve one linear system of equations. Without requiring the nonemptyness and boundedness of the solution set, the proposed algorithm is proved to be globally convergent. Numerical results indicate that the smoothing Newton method based on the new proposed class of smoothing functions with ${\theta}{\in}(0,1)$ seems to have better numerical performance than those based on some other important smoothing functions, which also demonstrate that our algorithm is promising.