• Steel and Composite Structures
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• v.27 no.1
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• pp.13-25
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• 2018

The main objective of this study is to develop a dual approach for geometrically nonlinear finite element analysis of plane truss structures. The geometric nonlinearity is considered using the Total Lagrangian formulation. The nonlinear solution is obtained by introducing and minimizing an objective function subjected to displacement-type constraints. The proposed method can fully trace the whole equilibrium path of geometrically nonlinear plane truss structures not only before the limit point but also after it. No stiffness matrix is used in the main approach and the solution is acquired only based on the direct classical stress-strain formulations. As a result, produced errors caused by linearization and approximation of the main equilibrium equation will be eliminated. The suggested algorithm can predict both pre- and post-buckling behavior of the steel plane truss structures as well as any arbitrary point of equilibrium path. In addition, an equilibrium path with multiple limit points and snap-back phenomenon can be followed in this approach. To demonstrate the accuracy, efficiency and robustness of the proposed procedure, numerical results of the suggested approach are compared with theoretical solution, modified arc-length method, and those of reported in the literature.

• Bulletin of the Korean Mathematical Society
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• v.54 no.4
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• pp.1195-1219
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• 2017

In this paper, the limit behavior of solution for the $Schr{\ddot{o}}dinger$ equation with random dispersion and time-dependent nonlinear loss/gain: $idu+{\frac{1}{{\varepsilon}}}m({\frac{t}{{\varepsilon}^2}}){\partial}_{xx}udt+{\mid}u{\mid}^{2{\sigma}}udt+i{\varepsilon}a(t){\mid}u{\mid}^{2{\sigma}_0}udt=0$ is studied. Combining stochastic Strichartz-type estimates with $L^2$ norm estimates, we first derive the global existence for $L^2$ and $H^1$ solution of the stochastic $Schr{\ddot{o}}dinger$ equation with white noise dispersion and time-dependent loss/gain: $idu+{\Delta}u{\circ}d{\beta}+{\mid}u{\mid}^{2{\sigma}}udt+ia(t){\mid}u{\mid}^{2{\sigma}_0}udt=0$. Secondly, we prove rigorously the global diffusion-approximation limit of the solution for the former as ${\varepsilon}{\rightarrow}0$ in one-dimensional $L^2$ subcritical and critical cases.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.7 no.2
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• pp.83-94
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• 2003

Let K be a nonempty closed convex subset of a real Hilbert space H. Approximation solvability of a system of nonlinear variational inequality (SNVI) problems, based on the convergence of projection methods, is given as follows: find elements $x^*,\;y^*{\in}H$ such that $g(x^*),\;g(y^*){\in}K$ and $$<\;{\rho}T(y^*)+g(x^*)-g(y^*),\;g(x)-g(x^*)\;{\geq}\;0\;{\forall}\;g(x){\in}K\;and\;for\;{\rho}>0$$ $$<\;{\eta}T(x^*)+g(y^*)-g(x^*),\;g(x)-g(y^*)\;{\geq}\;0\;{\forall}g(x){\in}K\;and\;for\;{\eta}>0,$$ where T: $H\;{\rightarrow}\;H$ is a relaxed $g-{\gamma}-r-cocoercive$ and $g-{\mu}-Lipschitz$ continuous nonlinear mapping on H and g: $H{\rightarrow}\;H$ is any mapping on H. In recent years general variational inequalities and their algorithmic have assumed a central role in the theory of variational methods. This two-step system for nonlinear variational inequalities offers a great promise and more new challenges to the existing theory of general variational inequalities in terms of applications to problems arising from other closely related fields, such as complementarity problems, control and optimizations, and mathematical programming.

• Journal of applied mathematics & informatics
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• v.41 no.4
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2187-2195
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• 2017

In order to solve the AC optimal power flow (OPF) problem considering the generators' on/off status, it is necessary to model the problem as mixed-integer nonlinear programming (MINLP). Because the computation time to find the optimal solution to the mixed-integer AC OPF problem increases significantly as the system becomes larger, most of the existing solutions simplify the problem either by deciding the on/off status of generators using a separate unit commitment algorithm or by ignoring the minimum output of the generators. Even though this kind of simplification may make the overall computation time tractable, the results can be significantly erroneous. This paper proposes a novel algorithm for the mixed-integer AC OPF problem, which can provide a near-optimal solution quickly and efficiently. The proposed method is based on a combination of the outer approximation method and the relaxed AC OPF theory. The method is applied to a real-scale power system that has 457 generators and 2132 buses, and the result is compared to the branch-and-bound (B&B) method and the genetic algorithm. The results of the proposed method are almost identical to those of the compared methods, but computation time is significantly shorter.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.9
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• pp.1314-1319
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• 2004

In this study, parameter optimization of micro-static mixer with a cantilever beam was accomplished for maximizing the mixing efficiency by using successive response surface approximations. Variables were chosen as the length of cantilever beam and the angle between horizontal and the cantilever beam. Sequential approximate optimization method was used to deal with both highly nonlinear and non-smooth characteristics of flow field in a micro-static mixer. Shape optimization problem of a micro-static mixer can be divided into a series of simple subproblems. Approximation to solve the subproblems was performed by response surface approximation, which does not require the sensitivity analysis. To verify the reliability of approximated objective function and the accuracy of it, ANOVA analysis and variables selection method were implemented, respectively. It was verified that successive response surface approximation worked very well and the mixing efficiency was improved very much comparing with the initial shape of a micro-static mixer.

• Transactions of Materials Processing
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• v.4 no.3
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• pp.214-221
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• 1995

In the paper, we have proposed a new method to determine the initial billet for the forged products using a function approximation in the neural network. The architecture of neural network is a three-layer neural network and the back propagation algorithm is employed to train the network. By utilizing the ability of function approximation of a neural network, an optimal billet is determined by applying the nonlinear mathematical relationship between the aspect ratios in the initial billet and the final products. The amount of incomplete filling in the die is measured by the rigid-plastic finite element method. The neural network is trained with the initial billet aspect ratios and those of the unfilled volumes. After learning, the system is able to predict the filling regions which are exactly the same or slightly different to the results of finite element simulation. This new method is applied to find the optimal billet size for the plane strain rib-web product in cold forging. This would reduce the number of finite element simulation for determining the optimal billet size of forging product, further it is usefully adapted to physical modeling for the forging design.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.139-150
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• 2005

A robust control design procedure for a nuclear reactor has been developed and experimentally validated on the Penn State TRIGA research reactor. The utilization of the robust controller as a component of an autonomous control system is also demonstrated. Two methods of specifying a low order (fourth-order) nominal-plant model for a robust control design were evaluated: 1) by approximation based on the 'physics' of the process and 2) by an optimal Hankel approximation of a higher order plant model. The uncertainty between the nominal plant models and the higher order plant model is supplied as a specification to the ,u-synthesis robust control design procedure. Two methods of quantifying uncertainty were evaluated: 1) a combination of additive and multiplicative uncertainty and 2) multiplicative uncertainty alone. The conclusions are that the optimal Hankel approximation and a combination of additive and multiplicative uncertainty are the best approach to design robust control for this application. The results from nonlinear simulation testing and the physical experiments are consistent and thus help to confirm the correctness of the robust control design procedures and conclusions.

• Interaction and multiscale mechanics
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• v.6 no.2
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• pp.137-156
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• 2013

In this paper, a meshfree shell adaptive procedure is developed for the applications in the sheet metal forming simulation. The meshfree shell formulation is based on the first-order shear deformable shell theory and utilizes the degenerated continuum and updated Lagrangian approach for the nonlinear analysis. For the sheet metal forming simulation, an h-type adaptivity based on the meshfree background cells is considered and a geometric error indicator is adopted. The enriched nodes in adaptivity are added to the centroids of the adaptive cells and their shape functions are computed using a first-order generalized meshfree (GMF) convex approximation. The GMF convex approximation provides a smooth and non-negative shape function that vanishes at the boundary, thus the enriched nodes have no influence outside the adapted cells and only the shape functions within the adaptive cells need to be re-computed. Based on this concept, a multi-level refinement procedure is developed which does not require the constraint equations to enforce the compatibility. With this approach the adaptive solution maintains the order of meshfree approximation with least computational cost. Two numerical examples are presented to demonstrate the performance of the proposed method in the adaptive shell analysis.

• Structural Engineering and Mechanics
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• v.7 no.6
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• pp.533-550
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• 1999

Optimal design of raft-pile foundations is examined by combining finite element technique and the optimization approach. The piles and soil medium are modeled by three dimensional solid elements while the raft is modelled by shell elements. Drucker-Prager criterion is adopted for the soil medium while the raft and the piles are assumed to be linear elastic. For the optimization process, the approximate semi-analytical method is used for calculating constraint sensitivities and a constraint approximation method which is a combination of the extended Bi-point approximation and Lagrangian polynomial approximation is used for predicting the behaviour of the constraints. The objective function of the problem is the volume of materials of the foundation while the design variables are raft thickness, pile length and pile spacing. The generalized reduced gradient algorithm is chosen for solving the optimization process. It is demonstrated that the method proposed in this study is promising for obtaining optimal design of raft-pile foundations without carrying out a large number of analyses. The results are also compared with those obtained from the previous study in which linear analysis was carried out.