• International Journal of High-Rise Buildings
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• v.7 no.2
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• pp.161-170
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• 2018

Rapid urbanization, resource depletion, and limited land are further increasing the need for skyscrapers in city centers; therefore, it is imperative to enhance tall building performance efficiency and energy-generative capability. Potential performance improvements can be explored using parametric multi-objective optimization, aided by evaluation tools, such as computational fluid dynamics and energy analysis software, to visualize and explore skyscrapers' multi-resource, multi-system generative potential. An optimization-centered, software-based design platform can potentially enable the simultaneous exploration of multiple strategies for the decreased consumption and large-scale production of multiple resources. Resource Generative Skyscrapers (RGS) are proposed as a possible solution to further explore and optimize the generative potentials of skyscrapers. RGS can be optimized with waste-energy-harvesting capabilities by capitalizing on passive features of integrated renewable systems. This paper describes various resource-generation technologies suitable for a synergetic integration within the RGS typology, and the software tools that can facilitate exploration of their optimal use.

• Ocean Systems Engineering
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• v.5 no.2
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• pp.91-107
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• 2015

Ship hull optimization is categorized as a bound, multi variable, multi objective problem with nonlinear constraints. In such analysis, where the objective function representing the performance of the ship generally requires computationally involved hydrodynamic interaction evaluation methods, the objective functions are not smooth. Hence, the evolutionary techniques to attain the optimum hull forms is considered as the most practical strategy. In this study, a parametric ship hull form represented by B-Spline curves is optimized for multiple performance criteria using Genetic Algorithm. The methodology applied to automate the hull form generation, selection of optimization solvers and hydrodynamic parameter calculation for objective function and constraint definition are discussed here.

• Structural Engineering and Mechanics
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• v.59 no.2
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• pp.277-290
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• 2016

This paper investigates the ground vibration induced by high-speed trains moving on multi-span continuous bridges. The dynamic impact factor of multi-span continuous bridges under trainloads was first determined in the parametric study, which shows that the dynamic impact factor will be large when the first bridge vertical natural frequency is equal to the trainload dominant frequencies, nV/D, where n is a positive integer, V is the train speed, and D is the train carriage interval. In addition, more continuous spans will produce smaller dynamic impact factors at this resonance condition. Based on the results of three-dimensional finite element analyses using the soil-structure interaction for realistic high-speed railway bridges, we suggest that the bridge span be set at 1.4 to 1.5 times the carriage interval for simply supported bridges. If not, the use of four or more-than-four-span continuous bridges is suggested to reduce the train-induced vibration. This study also indicates that the vibration in the train is major generated from the rail irregularities and that from the bridge deformation is not dominant.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.211-219
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• 2006

A random forests classifier is applied to multi-sensor data fusion for supervised land-cover classification in order to account for the importance of variable. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. The distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Two different multi-sensor data sets for supervised classification were used to illustrate the applicability of random forests: one with optical and polarimetric SAR data and the other with multi-temporal Radarsat-l and ENVISAT ASAR data sets. From the experimental results, the random forests approach could extract important variables or bands for land-cover discrimination and showed reasonably good performance in terms of classification accuracy.

• Geomechanics and Engineering
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• v.22 no.6
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• pp.509-518
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• 2020

Multi-layered primary linings have been proved to be highly effective for tunneling in severe squeezing grounds. But there still has not existed well-established design method for it. Basically, there are two main critical problems in this method, including determinations of allowable deformation and distribution of support stiffness. In order to address such problems, an attempt to investigate the mechanical response of a circular tunnel with double primary linings is performed in this paper. Analytical solutions in closed form for stresses and displacements around tunnels are derived. In addition, the effectiveness and reliability of theoretical formulas provided are well validated by using the numerical method. Finally, based on the analytical solutions, a parametric investigation on the effects of allowable deformation and distribution of support stiffness on tunnel performance is conducted. Results show that the rock pressure and displacement are significantly affected by these two design parameters. It can be found that rock pressure decreases as either allowable deformation increases or stiffness of the first primary lining decreases, but rock displacement shows an opposite trend. This paper can provide a useful guidance for the design of multi-layered primary linings.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.780-785
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• 2010

This paper introduces GP(Genetic Programming) based color detection model for an object detection and tracking. Existing color detection methods have used linear/nonlinear transformatin of RGB color-model and improved color model for illumination variation by optimization or learning techniques. However, most of cases have difficulties to classify various of colors because of interference of among color channels and are not robust for illumination variation. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various colors and images with different lighting conditions.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.3-9
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• 2012

In this paper, we present novel analysis results of sonar communication using parametric array. We consider transducer diameter, primary frequency, difference frequency and acoustic power as analysis parameters of communication performance. We calculate theoretical BER(Bit Error Rate) and channel capacity of MIMO(Multi Input and Multi Output) communication system. By considering practical parameters, we obtain optimum difference frequency generation condition. The obtained primary frequency is 560 kHz, difference frequency 45kHz and acoustic power is 28.05Watt. For BER of $10^{-4}$, the range gain of parametric array communication is 3.35km compared to primary frequency communication. For channel capacity of 10bps/Hz, the SISO and $2{\times}2$ MIMO communication range of parametric array communication are 3.8km and 3.98km respectively, while primary frequency communication range is 0.83km.

• Wind and Structures
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• v.31 no.3
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• pp.241-253
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• 2020

The inerter-based vibration absorber (IVA) is an enhanced variation of Tuned Mass Damper (TMD). The parametric optimization of absorbers in the previous research mainly considered only two decision variables, namely frequency ratio and damping ratio, and aimed to minimize peak displacement and acceleration individually under the excitation of the across-wind load. This paper extends these efforts by minimizing two conflicting objectives simultaneously, i.e., the extreme displacement and acceleration at the top floor, under the constraint of the physical mass. Six decision variables are optimized by adopting a constrained multi-objective evolutionary algorithm (CMOEA), i.e., NSGA-II, under fluctuating across- and along-wind loads, respectively. After obtaining a set of optimal individuals, a decision-making approach is employed to select one solution which corresponds to a Tuned Mass Damper Inerter/Tuned Inerter Damper (TMDI/TID). The optimization procedure is applied to parametric optimization of TMDI/TID installed in a 340-meter-high building under wind loads. The case study indicates that the optimally-designed TID outperforms TMDI and TMD in terms of wind-induced vibration mitigation under different wind directions, and the better results are obtained by the CMOEA than those optimized by other formulae. The optimal TID is proven to be robust against variations in the mass and damping of the host structure, and mitigation effects on acceleration responses are observed to be better than displacement control under different wind directions.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.439-449
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• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.

• Korean Journal of Computational Design and Engineering
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• v.4 no.3
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• pp.173-179
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• 1999

In reverse engineering, when a shape containing multi-patched surfaces is digitized, the boundaries of these surfaces should be detected. The objective of this paper is to introduce a computationally efficient segmentation technique for extracting edges, ad partitioning the 3D measuring point data based on the location of the boundaries. The procedure begins with the identification of the edge points. An automatic edge-based approach is developed on the basis of local geometry. A parametric quadric surface approximation method is used to estimate the local surface curvature properties. the least-square approximation scheme minimizes the sum of the squares of the actual euclidean distance between the neighborhood data points and the parametric quadric surface. The surface curvatures and the principal directions are computed from the locally approximated surfaces. Edge points are identified as the curvature extremes, and zero-crossing, which are found from the estimated surface curvatures. After edge points are identified, edge-neighborhood chain-coding algorithm is used for forming boundary curves. The original point set is then broke down into subsets, which meet along the boundaries, by scan line algorithm. All point data are applied to each boundary loops to partition the points to different regions. Experimental results are presented to verify the developed method.