• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.29 no.1
• /
• pp.47-53
• /
• 2005

This paper presents the method for developing an optimum hull form with minimum wave resistance using SQP(sequential quadratic programming) as an optimization technique. The wave resistance is evaluated by a Rankine source panel method with non-linear free surface conditions and the ITTC 1957 friction line is used to predict the frictional resistance coefficient. The geometry of the hull surface is represented and modified using NURBS(Non-Uniform Rational B-Spline) surface patches. To verity the validity of the developed program the numerical calculations for Wigley hull and Series 60(C${_B}$=0.6) hull had been performed and the results obtained after the numerical calculations had been compared with the original hulls.

• Journal of Korean Society on Water Environment
• /
• v.23 no.1
• /
• pp.111-121
• /
• 2007

The experimental design and response surface methodologies haven been applied to the investigation of the chemical coagulation of livestock wastewater. The chemical coagulation reactions were mathematically described as a function of parameters raping mixing (rpm) of chemical coagulation ($X_1$), slow mixing (rpm) of chemical coagulation ($X_2$), $FeCl_3 $ concentration (mg/L) ($X_3$) and pH ($X_4$) being modeled by use of the central composite design. Empirical models were developed to describe relationship between the experimental variables and response. Statistical analysis indicates that three factors ($X_1$: raping mixing (rpm), $X_2$: slow mixing (rpm), $X_3$: $FeCl_3 $ concentration (mg/L) on the linear term (main effect), slow mixing (rpm) (${X_2}^2$) on the non-linear term (quadratic), and two factors ($X_1-X_3$, $X_2-X_3$) on the non-linear term (cross-product) had significant effects, respectively. The estimated ridge of maximum responses and optimal conditions for CODcr using canonical analysis was 87.44% ($X_1$: 229 rpm, $X_2$: 51 rpm, $X_3$: 877 mg/L, $X_4$: 4.3). To confirm this optimum condition, three additional experiments were performed and the mean CODcr removal (%) and concentration (mg/L) with a standard deviation of $87{\pm}1.2%$ ($576{\pm}34ppm$) were obtained.

• Proceeding of EDISON Challenge
• /
• 2016.03a
• /
• pp.246-255
• /
• 2016

When spring of the suspension is exerted by an external load, a car should be designed to prevent predictable damages and designed for a ride comfort. We used experiments design to design VON-MISES STRESS and K, a constant, of spring of suspension which is installed in a car as a goal level. We analyzed the result from Edison's Elastic - Plastic Analysis SW(CSD_EPLAST) by setting D, d, n as external diameter of coil, internal diameter of coil, the number of total coil respectively. The experiment design let the outcome be as Full-second order by using Box-Behnken which is one of response surface methods. Experimented and analyzed results based on the established experiments design, We found out design parameter which has desired VON-MISES STRESS and the constant K. Additionally, we predicted life time of when the external load was exerted by repeated load by using fatigue equation, and verification of plastic deformation has also been made. Additionally we interpreted a model, which is formed by optimized design parameter, with linear analysis and non-linear analysis, at the same time we also analyzed plastic deformation with the values from the both models. Finally, we predicted fatigue life of optimized model by using fatigue estimation theory and also evaluated a ride comfort with oscillation analysis.

• Smart Structures and Systems
• /
• v.14 no.1
• /
• pp.17-37
• /
• 2014

In this study, four widely accepted and used variants of Evolution Strategies (ES) are adapted and applied to the output-error state-space identification problem. The selection of ES is justified by prior strong indication of superior performance to similar problems, over alternatives like Genetic Algorithms (GA) or Evolutionary Programming (EP). The ES variants that are being tested are (i) the (1+1)-ES, (ii) the $({\mu}/{\rho}+{\lambda})-{\sigma}$-SA-ES, (iii) the $({\mu}_I,{\lambda})-{\sigma}$-SA-ES, and (iv) the (${\mu}_w,{\lambda}$)-CMA-ES. The study is based on a six-degree-of-freedom (DOF) structural model of a shear building that is characterized by light damping (up to 5%). The envisaged analysis is taking place through Monte Carlo experiments under two different excitation types (stationary / non-stationary) and the applied ES are assessed in terms of (i) accurate modal parameters extraction, (ii) statistical consistency, (iii) performance under noise-corrupted data, and (iv) performance under non-stationary data. The results of this suggest that ES are indeed competitive alternatives in the non-linear state-space estimation problem and deserve further attention.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.12
• /
• pp.209-218
• /
• 2012

Recently, the Field Programmable Stateful Logic Array (FPSLA) was proposed as one of the most promising system integration technologies which will extend the life of the Moore's law. This work is the first proposal of the FPSLA design automation flow, and the approaches to logic synthesis, synchronization, physical mapping, and automatic placement of the FPSLA designs. The synchronization at each gate for pipelining determines the x-coordinates of cells, and reduces the placement to 1-dimensional problems. The objective function and its gradients for the non-linear optimization of the net length and placement density have been remodeled for the reduced global placement problem. Also, a recursive algorithm has been proposed to legalize the placement by relaxing the density overflow of bipartite bin groups in a top-down hierarchical fashion. The proposed model and algorithm are implemented, and validated by applying them to the ACM/SIGDA benchmark designs. The output state of a gate in an FPSLA needs to be duplicated so that each fanout gate can be connected to a dedicated copy. This property has been taken into account by merging the duplicated nets into a hyperedge, and then, splitting the hyperedge into edges as the optimization progresses. This yields additional 18.4% of the cell count reduction in the most dense logic stage. The practicality of the FPSLA can be further enhanced primarily by incorporating into the logic synthesis the constraint to avoid the concentrated fains of gates on some logic stages. In addition, an efficient algorithm needs to be devised for the routing problem which is based on a complicated graph. The graph models the nanowire crossbar which is trimmed to be embedded into the FPSLA fabric, and therefore, asymmetric. These CAD tools can be used to evaluate the fabric efficiency during the architecture enhancement as well as automate the design.

• Steel and Composite Structures
• /
• v.24 no.2
• /
• pp.227-237
• /
• 2017

This paper presents optimization of a long-span portal steel frame under dynamic wind loads using a surrogate-assisted evolutionary algorithm. Long-span portal steel frames are often used in low-rise industrial and commercial buildings. The structure needs be able to resist the wind loads, and at the same time it should be as light as possible in order to be cost-effective. In this work, numerical model of a portal steel frame is constructed using structural analysis program (SAP2000), with the web-heights at five locations of I-sections of the columns and rafters as the decision variables. In order to evaluate the performance of a given design under dynamic wind loading, the equivalent static wind load (ESWL) is obtained from a database of wind pressures measured in wind tunnel tests. A modified formulation of the problem compared to the one available in the literature is also presented, considering additional design constraints for practicality. Evolutionary algorithms (EA) are often used to solve such non-linear, black-box problems, but when each design evaluation is computationally expensive (e.g., in this case a SAP2000 simulation), the time taken for optimization using EAs becomes untenable. To overcome this challenge, we employ a surrogate-assisted evolutionary algorithm (SAEA) to expedite the convergence towards the optimum design. The presented SAEA uses multiple spatially distributed surrogate models to approximate the simulations more accurately in lieu of commonly used single global surrogate models. Through rigorous numerical experiments, improvements in results and time savings obtained using SAEA over EA are demonstrated.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.2
• /
• pp.99-104
• /
• 2008

This study performed robust design optimization of fighter wing planform, considering uncertainty based on neural network model. To construct uncertainty model, aerodynamic performance and their sensitivity were evaluated by 3-dimensional Euler equations and adjoint variable method at experimental points selected from central composite design. In addition, because a neural network model has the advantage of capturing non-linear characteristic, it was possible to predict sensitivity of the aerodynamic performance efficiently and accurately . From the results of robust design optimization, it could be confirmed that the robustness of the objective function and constraints were improved if the variation of uncertainty and sigma level were increased.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.31 no.6
• /
• pp.258-263
• /
• 2021

ZnO varistor is a semiconductor device which can serve to protect the circuit from surge voltage because its non-linear I-V characteristics by controlling the microstructure of grain and grain boundaries. In order to obtain desired electrical properties, it is important to control microstructure evolution during the sintering process. In this research, we defined a dataset composed of process conditions of sintering and relative permittivity of sintered body, and collected experimental dataset with DOE. Meta-models can predict permittivity were developed by learning the collected experimental dataset on various machine learning algorithms. By utilizing the meta-model, we can derive optimized sintering conditions that could show the maximum permittivity from the numerical-based HMA (Hybrid Metaheuristic Algorithm) optimization algorithm. It is possible to search the optimal process conditions with minimum number of experiments if meta-model-based optimization is applied to ceramic processing.

• 유체기계공업학회:학술대회논문집
• /
• 2002.12a
• /
• pp.47-53
• /
• 2002

The hydraulic design optimization and performance analysis of mixed-flow pumps for waterjet marine vehicle propulsion has been carried out using mean streamline analysis and three-dimensional computational fluid dynamics (CFD) code. In the present study the conceptual design optimization has been formulated with a non-linear objective function to minimize the fluid dynamic losses and then the commercial CFD code was incorporated to allow for detailed flow dynamic phenomena in the pump system. New designed mixed-flow model pump has been tested in the laboratory. Predicted performance curves by the CFD code agree very well with experimental data for a newly designed mixed-flow pump over the normal operating conditions. The design and prediction methods presented herein can be used efficiently as a unified hydraulic design process of mixed-flow pumps for waterjet marine vehicle propulsion.

• Journal of Biomedical Engineering Research
• /
• v.36 no.5
• /
• pp.211-220
• /
• 2015

Recently, model-based iterative reconstruction (MBIR) has played an important role in transmission tomography by significantly improving the quality of reconstructed images for low-dose scans. MBIR is based on the penalized-likelihood (PL) approach, where the penalty term (also known as the regularizer) stabilizes the unstable likelihood term, thereby suppressing the noise. In this work we further improve MBIR by using a more expressive regularizer which can restore the underlying image more accurately. Here we used a spline regularizer derived from a linear combination of the two-dimensional splines with first- and second-order spatial derivatives and applied it to a non-quadratic convex penalty function. To derive a PL algorithm with the spline regularizer, we used a separable paraboloidal surrogates algorithm for convex optimization. The experimental results demonstrate that our regularization method improves reconstruction accuracy in terms of both regional percentage error and contrast recovery coefficient by restoring smooth edges as well as sharp edges more accurately.