• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.323-329
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• 2023

In this study, Proline pentamer model was used to investigate change in the dihedral angle, intramolecular hydrogen bonding and formation energies during structural optimization. L-Proline (LP, as an imino acid residue) pentamers having four conformation types [β: φ/ψ=t−/t+, α: φ/ψ=g−/g−, PP_II: φ/ψ=g−/t+ and Plike: φ/ψ= g−/g+] were carried out by QCC [B3LYP/6-31G(d,p)]. The optimized structure and formation energy were examined for designated structure. In LP, P-like and PP_II types did not change by optimization, and β types were transformed into PP_II having no H-bond independently of the designated ψ values. PP_II was more stable than P-like by about 2.2 kcal/mol/mu. The hydrogen bond distances of d2(4-6) type H-bonds were 1.94 - 2.00Å. In order to understand the processes of the transformations, the changes of φ/ψ, distances of NH-OC (d_NH/CO) and formation energies (ΔE, kcal/mol/mu) were examined.

• Journal of Advanced Navigation Technology
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• v.24 no.4
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• pp.291-298
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• 2020

This study proposed a model that can track MPP faster than the existing MPPT algorithm using the particle swarm optimization algorithm (PSO). The proposed model highly sets the acceleration constants of gbest and pbest in the PSO algorithm to quickly track the MPP point and eliminates the power instability problem. In addition, this algorithm was re-executed by detecting the change in power of the solar panel according to the rapid change in solar radiation. As a result of the experiment, MPP time was 0.03 seconds and power was 131.65 for 691.5 W/m2, and MPP was tracked at higher power and speed than the existing P&O and INC algorithms. The proposed model can be applied when a change in the amount of power is detected by partial shading in a Photovoltaic power plant with Photovoltaic connected in parallel. In order to improve the MPPT algorithm, this study needs a comparative study on optimization algorithms such as moth flame optimization (MFO) and whale optimization algorithm (WOA).

• Journal of computational fluids engineering
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• v.17 no.4
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• pp.32-40
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• 2012

Efficient Global Optimization (EGO) method is a global optimization technique which can select the next sample point automatically by infill sampling criteria (ISC) and search for the global minimum with less samples than what the conventional global optimization method needs. ISC function consists of the predictor and mean square error (MSE) provided from the kriging model which is a stochastic metamodel. Also the constrained EGO method can minimize the objective function dealing with the constraints under EGO concept. In this study the constrained EGO method applied to the RAE2822 airfoil shape design formulated with the constraint. But the noisy CFD data caused the kriging model to fail to depict the true function. The distorted kriging model would make the EGO deviate from the correct search. This distortion of kriging model can be handled with the interpolation(p=free) kriging model. With the interpolation(p=free) kriging model, however, the search of EGO solution was stalled in the narrow feasible region without the chance to update the objective and constraint functions. Then the accuracy of EGO solution was not good enough. So the three-step search method was proposed to obtain the accurate global minimum as well as prevent from the distortion of kriging model for the noisy constrained CFD problem.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1485-1495
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• 2009

This paper presents a novel approach to economic dispatch (ED) with nonconvex fuel cost function as combinatorial optimization problems (COP) while most of the conventional researches have been developed as function optimization problems (FOP). One nonconvex fuel cost function can be divided into several convex fuel cost functions, and each convex function can be regarded as a generation type (G-type). In that case, ED with nonconvex fuel cost function can be considered as COP finding the best case among all feasible combinations of G-types. In this paper, a genetic algorithm is applied to solve the COP, and the ${\lambda}-P$ function method is used to calculate ED for the fitness function of GA. The ${\lambda}-P$ function method is reviewed briefly and the GA procedure for COP is explained in detail. This paper deals with two kinds of ED problems, namely ED with multiple fuel units (EDMF) and ED with prohibited operating zones (EDPOZ). The proposed method is tested for all the ED problems, and the test results show an improvement in solution cost compared to the results obtained from conventional algorithms.

• The Korean Journal of Food And Nutrition
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• v.29 no.4
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• pp.583-594
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• 2016

The purpose of this study was to determine the optimal mixing ratio of olive oil, parmesan cheese, and nuts for preparation of pesto with spinach. Based on a surface response methodology (RSM), the independent variables were olive oil (100~300 g), parmesan cheese (25~75 g) and nuts (12~36 g). The dependent variables were physico-chemical properties as pH, color values (L, a, and b values), viscosity and sensory evaluation. pH decreased with increasing parmesan cheese levels. The L value decreased and the a and b values increased with increasing olive oil levels. Viscosity was negatively correlated with olive oil levels but positively correlated with the amounts of parmesan cheese and nuts. The addition of oil exerted a positive effect on gloss, and oily taste. In the sensory evaluation, the values of appearance, color, flavor, taste and overall acceptance were in the range of 4.4~7.2, 3.7~7.4, 4.4~7.1, 3.9~7.3 and 3.5~7.6, respectively. The sensory evaluation results showed significant values in appearance (p<0.01), flavor (p<0.01), taste (p<0.01) and overall acceptance (p<0.05). The optimal amounts of spinach pesto with olive oil, parmesan cheese, and nuts were determined by numerical optimization of a canonical model and graphical optimization. The optimal amounts were 175.29 g of olive oil, 49.51 g parmesan cheese, and 27.37 g of nuts per 100 g of spinach.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.255-262
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• 2015

In the absence of a deterministic algorithm for economic load dispatch optimization problem (ELDOP), existing algorithms proposed as solutions are inevitably non-deterministic heuristic algorithms. This paper, therefore, proposes a balance-and-swap algorithm to solve an ELDOP. Firstly, it balances the initial value to ${\Sigma}P_i=P_d$ by subsequently reducing power generation for each adult-step and baby-step and selects the minimum cost-generating method. Subsequently, it selects afresh the minimum cost-generating method after an optimization of the previously selected value with adult-step baby-step swap and giant-step swap methods. Finally, we perform the $P_i{\pm}{\beta}$, (${\beta}=0.1,0.01,0.001,0.0001$) swap. When applied to the 3 most prevalently used economic load dispatch problem data, the proposed algorithm has obtained improved results for two and a result identical to the existing one for the rest. This algorithm thus could be applied to ELDOP for it has proven to consistently yield identical results and to be applicable to all types of data.

• Structural Engineering and Mechanics
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• v.5 no.5
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• pp.609-624
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• 1997

The optimization of cutouts in composite plates was investigated by implementing a procedure known as Evolutionary Structural Optimization. Perforations were introduced into a finite element mesh of the plate from which one or more cutouts of a predetermined size were evolved. In the examples presented, plates were rejected from around each evolving cutout based on a predefined rejection criterion. The limiting ply within each plate element around the cutout was determined based on the Tsai-Hill failure criterion. Finite element plates with values below the product of the average Tsai-Hill number and a rejection criterion were subsequently removed. This process was iterated until a steady state was reached and the rejection criterion was then incremented by an evolutionary rate and the above steps repeated until the desired cutout area was achieved. Various plates with differing lay-up and loading parameters were investigated to demonstrate the generality and robustness of this optimization procedure.

• Journal of the Korea Society of Computer and Information
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• v.17 no.5
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• pp.49-57
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• 2012

In P2P streaming management, peer's churning and finding efficient topology architecture optimization algorithm that reduces streaming delay is important. This paper studies a topology optimization algorithm based on the P2P streaming using peer's link information. The proposed algorithm is based on the estimation of peer's upload bandwidth using peer's link information on mesh-network. The existing algorithm that uses the information of connected links is efficient to reduce message overload in the point of resource management. But it has a risk of making unreliable topology not considering upload bandwidth. And when some network error occurs in a server-closer-peer, it may make the topology worse. In this paper we propose an algorithm that makes up for the weak point of the existing algorithm. We compare the existing algorithm with the proposed algorithm using test data and analyze each simulation result.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.4
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• pp.729-740
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• 1994

In the shape optimal design based on h-version of FEM, the ideal mesh for the initial geometry most probably will not be suitable for the final analysis. Thus, it is necessary to remesh the geometry of the model at each stage of optimization. However, the p-version of FEM appears to be a very attractive alternative for use in shape optimization. The main advantages are as follows; firstly, the elements are not sensitive to distortion for interpolation polynomials of order $p{\geq}3$; secondly, even singular problems can be solved more efficiently with p-version than with the h-version by proper mesh design; thirdly, the initial mesh design are identical. The 2-D p-version model for shape optimization is presented on the basis of Bezier's curve fitting, gradient projection method, and integrals of Legendre polynomials. The numerical results are performed by p-version software RASNA.

• Culinary science and hospitality research
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• v.18 no.1
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• pp.15-26
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• 2012

The objective of this study is to optimize enzymatic hydrolysis of cooked krill by using Alcalase. To optimize krill hydrolysis on such dependent variables as TCA, DPPH-scavenging, and Fe-chelating activities by using Alcalase, independent variables of hydrolysis pH and temperature were investigated Their formulas and three dimensional graphs were obtained by using SAS and Maple softwares, respectively. For comparison of general composition of raw krill, its contents of moisture, crude protein, crude fat, and ash were 17.48%, 53.74%, 15.66%, and 10.21%, respectively, and for cooked krill, its contents were 4.80%, 71.84%, 5.26%, and 15.09%, respectively. The composition of fatty acids for cooked krill was similar to that of raw krill. The most abundant fatty acid was palmitic acid(16:0) and the following order was oleic acid(18:1), eicosapentaenoic acid (20:5), palmitoleic acid(16:1), and docosahexaenoic acid(22:6). For DH optimization of hydrolysates from cooked krill, its result was pH 8.5 and $66.6^{\circ}C$ hydrolysis temperature for the maximum DH of 29.4% For DPPH-antioxidative optimization of hydrolysates from raw krill, its maximum result of 27.1% was obtained in the hydrolysis condition of pH 7.4 and $67.5^{\circ}C$. For Fe-chelating optimization of hydrolysates from cooked krill, its maximum result of 24.9% was in the condition of pH 8.7 and $65.5^{\circ}C$. These results can be used for basic data for using krill products and other fish products as bioactive ingredients.