• Structural Engineering and Mechanics
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• v.83 no.5
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• pp.671-680
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• 2022

The shear capacity of beams is an essential parameter in designing beams carrying shear loads. Precise estimation of the ultimate shear capacity typically requires comprehensive calculation methods. For steel fiber reinforced concrete (SFRC) beams, traditional design methods may not accurately predict the interaction between different parameters affecting ultimate shear capacity. In this study, artificial neural network (ANN) modeling was utilized to predict the ultimate shear capacity of SFRC beams using ten input parameters. The results demonstrated that the ANN with 30 neurons had the best performance based on the values of root mean square error (RMSE) and coefficient of determination (R²) compared to other ANN models with different neurons. Analysis of the ANN model has shown that the clear shear span to depth ratio significantly affects the predicted ultimate shear capacity, followed by the reinforcement steel tensile strength and steel fiber tensile strength. Moreover, a Genetic Algorithm (GA) was used to optimize the ANN model's input parameters, resulting in the least cost for the SFRC beams. Results have shown that SFRC beams' cost increased with the clear span to depth ratio. Increasing the clear span to depth ratio has increased the depth, height, steel, and fiber ratio needed to support the SFRC beams against shear failures. This study approach is considered among the earliest in the field of SFRC.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.53-61
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• 1994

An experimental study on heat pump cycle systematizing characteristics for non-azeotropic refrigerant mixtures of R-22+R-114 was reported. Data were obtained under steady state condition at the ranges of parameters, 550- 2, 170kcal/h, 670-2, 990kcal/h, 24-71kg/h, and 0-1, for as cooling capacity, heating capacity, mass 25, 50, 75, and 100 per cent of R-22 by weight fraction for R-22+R-114 mixtures. The results shown that the C.O.P of the 50wt% of R-22 mixture was considerably larger than for pure R-22 and other weight fraction of R-22 mixtures, but the compression power of the 25wt% of R-22 was lower than that of the pure R-22 and the other weight fraction of R-22 mixtures. The hightest value of cooling capacity was obtained at the conditions of evaporating temperature 5.deg.C and R-22 50wt% mixture. In general, with an increase in the R-22 weight fraction for fixed values of the other parameter, the cooling capacity increased at first, obtained a maximum, and then decreasd. This verified the importance of accurate weight fractions od refrigerant mixtures in the heat pump cycle.

• Geomechanics and Engineering
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• v.30 no.2
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• pp.123-138
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• 2022

Present study computes the ultimate bearing capacity of an embedded strip footing situated on the rock slope subjected to seismic loading. Influences of embedment depth of strip footing, horizontal seismic acceleration coefficient, rock slope angle, Geological Strength Index, normalized uniaxial compressive strength of rock mass, disturbance factor, and Hoek-Brown material constant are studied in detail. To perform the analysis, the lower bound finite element limit analysis method in combination with the semidefinite programming is utilized. From the results of the present study, it can be found that the magnitude of the bearing capacity factor reduces quite substantially with an increment in the seismic loading. In addition, with the increment in slope angle, further reduction in the value of the bearing capacity factor is observed. On the other hand, with an increment in the embedment depth, an increment in the value of the bearing capacity factor is found. Stress contours are presented to describe the combined failure mechanism of the footing-rock slope system in the presence of static as well as seismic loadings for the different embedment depths.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.95-104
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• 2013

This study set out to devise an optimized system to take into account life cycle cost(LCC) and ton of carbon dioxide($TCO_2$) by applying the weighted coefficient method(WCM) to "public-purpose" facility buildings according to the mandatory 5% and 11% of new renewable energy in total construction costs and anticipated energy consumption, respectively, based on the changes of the public obligation system. (1) System installation capacity is applied within the same new renewable energy facility investment according to the mandatory 5% of new renewable energy in total construction costs. Both LCC and $TCO_2$ recorded in the descending order of geothermal, solar, and photovoltaic energy. The geothermal energy systems tended to exhibit an excellent performance with the increasing installation capacity percentage. (2) Optimal systems include the geothermal energy(100%) system in the category of single systems, the solar energy(12%)+geothermal energy(88%) system in the category of 2-combined systems, and the photovoltaic energy(12%)+solar energy(12%)+geothermal energy(76%) system and the photovoltaic energy(12%)+solar energy(25%)+geothermal energy(63%) system in the category of 3-combined systems. (3) LCC was the highest in the descending order of photovoltaic, geothermal and solar energy due to the influences of each energy source's correction coefficient according to the mandatory 11% of new renewable energy in anticipated energy consumption. The greater installation capacity percentage photovoltaic energy had, the more excellent tendency was observed. $TCO_2$ recorded in the descending order of geothermal, photovoltaic and solar energy with the decreasing installation capacity of photovoltaic energy. The greater installation capacity percentage a geothermal energy system had, the more excellent tendency it demonstrated. (4) Optimal systems include the geothermal energy(100%) system in the category of single systems, the photovoltaic energy(62%)+geothermal energy(38%) system in the category of 2-combined systems, and the photovoltaic energy(50%)+solar energy(12%)+geothermal energy(38%) system and the photovoltaic energy(12%)+solar energy(12%)+geothermal energy(76%) system in the category of 3-combined systems.

• Food Science and Preservation
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• v.11 no.2
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• pp.250-256
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• 2004

The objectives of this study were to develop a new commercial grain cooler suited to domestic weather and post-harvesting conditions for paddy, and to evaluate the performance. A prototype grain cooler capable of cooling paddy of 200 tons within 24 hours was developed. The grain cooler was designed to control the refrigeration capacity from 0 to 100% by controlling the capacity of compressor with unloading solenoid valve and by changing the flow rates of hot refrigerant gas flowing into reheater and evaporator from compressor. And a controller with one chip microprocessor was developed to control temperature and relative humidity of cooling air. The maximum cooling capacity of the grain cooler was 35,284㎉/hr at condensing/evaporating pressure of 16.5/3.6 kgf/$\textrm{cm}^2$. Maximum flow rate of cooling air was 120 ㎥/min at static pressure of 279 mmAq. The total maximum required power was 22.8㎾, and total required energy was saved from 26.7 to 33.3% of maximum power depending on operating conditions. The coefficient of performance of refrigeration devices and total coefficient of performance of the grain cooler were 4.71 and 1.8, respectively.

• Steel and Composite Structures
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• v.51 no.4
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• pp.417-440
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• 2024

Artificial neural networks (ANN) have been the focus of several studies when it comes to evaluating the pile's bearing capacity. Nonetheless, the principal drawbacks of employing this method are the sluggish rate of convergence and the constraints of ANN in locating global minima. The current work aimed to build four ANN-based prediction models enhanced with methods from the black hole algorithm (BHA), league championship algorithm (LCA), shuffled complex evolution (SCE), and symbiotic organisms search (SOS) to estimate the carrying capacity of piles in cold climates. To provide the crucial dataset required to build the model, fifty-eight concrete pile experiments were conducted. The pile geometrical properties, internal friction angle 𝛗 shaft, internal friction angle 𝛗 tip, pile length, pile area, and vertical effective stress were established as the network inputs, and the BHA, LCA, SCE, and SOS-based ANN models were set up to provide the pile bearing capacity as the output. Following a sensitivity analysis to determine the optimal BHA, LCA, SCE, and SOS parameters and a train and test procedure to determine the optimal network architecture or the number of hidden nodes, the best prediction approach was selected. The outcomes show a good agreement between the measured bearing capabilities and the pile bearing capacities forecasted by SCE-MLP. The testing dataset's respective mean square error and coefficient of determination, which are 0.91846 and 391.1539, indicate that using the SCE-MLP approach as a practical, efficient, and highly reliable technique to forecast the pile's bearing capacity is advantageous.

• Korean Journal of Soil Science and Fertilizer
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• v.29 no.2
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• pp.92-106
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• 1996

Imaginary grass field was assumed suitable as the representative one for simplified estimation of local drought, and a moisture balance booking model computing drought was developed with the limited numbers of its determining factors, such as crop coefficient of the field, reservoir capacity of the soil, and the beginning point of drought as defined by soil moisture status. The maximum effective rainfall was assumed to be the same as the available free space of soil reservoir capacity. The model is similar to a definite depth evaporation pan, which stores rainfall as much as the available free space on the water in it and consumes the water by evaporation. When the pan keeps water less than a certain defined level, it is droughty. The model simulates soil moisture deficit on the assumed grass field for the drought estimation. The model can assess the water requirement, drought intensity, and the index of yield decrement due to drought. The influencing intensity indices of the selected factors were 100, 21, and 16 respectively for crop coefficient, reservoir capacity, and drought beginning point, determined by the annual water requirements as influenced by them in the model. The optimum values of the selected factors for the model were respectively 58% for crop coefficient defined on the energy indicator scale of the small copper pan evaporation, 50 mm for reservoir capacity on the basis of the average of experimentally determined values for sandy loam, loam, clay loam, and clay soils, and 65% of the reservoir capacity for the beginning point of drought.

• Computers and Concrete
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• v.31 no.5
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• pp.443-455
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• 2023

This is a research analyses on the bearing capacity at a pile tip embedded in rock. The aim is to propose a shape coefficient for an analytical solution and to investigate the influence of the plastic flow law on the problem. For this purpose, the finite difference method is used to analyze the bearing capacity of various types and states of rock masses, assuming the Hoek & Brown failure criterion, by considering both plane strain and an axisymmetric model. Different geometrical configurations were adopted for this analysis. First, the axisymmetric numerical results were compared with those obtained from the plane strain analytical solution. Then the pile shape influence on the bearing capacity was studied. A shape factor is now proposed. Furthermore, an evaluation was done on the influence of the plastic flow law on the pile tip bearing capacity. Associative flow and non-associative flow with null dilatancy were considered, resulting in a proposed correlation. A total of 324 cases were simulated, performing a sensitivity analysis on the results and using the graphic output of vertical displacement and maximum principal stress to understand how the failure mechanism occurs in the numerical model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.75-82
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• 2018

Recently, emerging countries have been paying attention to Korean economic development policy, trying to adopt the Korean regional innovation model. Korea is also interested in exporting its regional innovation model and enhancing economic cooperation with those countries. This paper aims to analyze the capacity-building programs of the Korean regional innovation model for emerging countries and suggests policies for it. For this purpose, the local innovators' participation patterns in the process of collaborative learning/networking/interaction are investigated with a focused group-interview method. From an analysis of the programs supported by Korean organizations, this study finds that the correlation coefficient between the training time of capacity building and the participation rate of local members' collaborative learning is very high (0.975). Since the correlation coefficient between the participation rates of collaborative learning and networking is relatively low (0.667), a policy to link local collaborative learning to networking should be provided. As the correlation coefficient between the participation rates of networking and interaction is high (0.950), networking is a key to regional innovation. This study recommends activity programs to promote networking among local innovators, rather than training and consulting programs. As introduced in the Chungnam Techno Park case, this study suggests that the capacity-building program should include programs to initiate a collaborative learning network, to create a local-demand, regional innovation model, and to operate the regional innovation platform, which should be done by local innovators in the emerging countries.

• International journal of steel structures
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• v.18 no.4
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• pp.1153-1166
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• 2018

This paper was concerned with the nonlinear analysis on the overall stability of H-type honeycombed composite column with rectangular concrete-filled steel tube flanges (STHCC). The nonlinear analysis was performed using ABAQUS, a commercially available finite element (FE) program. Nonlinear buckling analysis was carried out by inducing the first buckling mode shape of the hinged column to the model as the initial imperfection with imperfection amplitude value of L/1000 and importing the simplified constitutive model of steel and nonlinear constitutive model of concrete considering hoop effect. Close agreement was shown between the experimental results of 17 concrete-filled steel tube (CFST) specimens and 4 I-beams with top flanges of rectangular concrete-filled steel tube (CFSFB) specimens conducted by former researchers and the predicted results, verifying the correctness of the method of FE analysis. Then, the FE models of 30 STHCC columns were established to investigate the influences of the concrete strength grade, the nominal slenderness ratio, the hoop coefficient and the flange width on the nonlinear stability capacity of SHTCC column. It was found that the hoop coefficient and the nominal slenderness ratio affected the nonlinear stability capacity more significantly. Based on the results of parameter analysis, a formula was proposed to predict the nonlinear stability capacity of STHCC column which laid the foundation of the application of STHCC column in practical engineering.