• Journal of the Korean Chemical Society
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• v.57 no.6
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• pp.761-768
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• 2013

Removal of COD and TSS from rice mill wastewater was investigated using continuous electrocoagulation method (CEC). The electrical energy consumption (EEC) of the process was also examined in order to evaluate the economic viability. The Box-Behnken statistical experiment design (BBD) and response surface methodology (RSM) were used to investigate the effects of major operating variables. Initial pH, current density, electrode distance and flow rate were selected as independent variables in BBD while COD removal, TSS removal and EEC were considered as the response functions. The predicted values of responses obtained using the response function was in good agreement with the experimental data. Optimum operating conditions were found to be pH of 7, current density of 15 mA $cm^{-2}$, electrode distance of 5 cm and flow rate of 70 ml/min. Under these conditions, greater than 89% removal of COD and TSS were obtained with EEC value of 7 KWh.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.12
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• pp.867-874
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• 2012

In the present study, three-dimensional transient numerical simulations were carried out to improve the performance of a vehicle paint drying process. In order to describe the movement of a vehicle, the techniques of moving boundary condition and multiple reference flames (MRF) were used. For the validation of the numerical analysis, the predicted temperature on the surface of a vehicle was compared to the experimental data, and a good agreement was achieved. With validated numerical procedure, various operating conditions of the temperature and the flow rate of the supply air were investigated to improve the drying performance of the facility. It is shown that the optimization of the operating condition can lead to energy savings and faster line speed of the production.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.38-40
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• 2009

In order to achieve a gearless construction of the wind energy conversion system(WECS), a low-speed generator should be used. Of the various candidate machine types, radial-field, multi-pole, permanent magnet, synchronous machines may be used for low-speed applications. So, this paper deals with the design of direct-coupled, multi-pole radial field machines with permanent magnet(PM) excitation for wind power applications for cogging torque reduction through the determination of optimum pole arc/pitch ratio. On the basis of an equivalent magnetic circuit method(EMCM) and a space harmonic method(SHM), an initial design is performed considering restricted conditions. And then, a detailed design is made using a non-linear finite element analyses(FEA). Finally, test results concerning generating characteristics are given to confirm the validation of the design.

• Nuclear Engineering and Technology
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• v.36 no.2
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• pp.142-152
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• 2004

The liquid entrainment and vapor pull-through offtake model of RELAP5/MOD3 had been developed for SBLOCA (Small Break Loss of Coolant Accident). The RELAP5/MOD3 model for horizontal volumes accounts for the phase separation phenomena and computes the flux of mass and energy through a branch when stratified conditions occur in the horizontal pipe. In the case of CANDU reactor, this model should be used in the coolant flow of 95 feeders connected to the reactor header component under the horizontal stratification in header. The current RELAP5 model can treat the only 3 directions junctions; vertical upward, downward, and side oriented junctions, and thus improvements for the liquid entrainment and vapor pull-through model were needed for considering the exact angles. The RELAP5 off-take model was modified and generalized by considering the geometric effect of branching angles. Based on the previous experimental results, the critical height correlation was reconstructed by use of the branch line connection angle and validation analyses were also performed using SET. The new model can be applied to vertical upward, downward and angled branch, and the accuracy of the new correlations is more improved than that of RELAP5.

• Earthquakes and Structures
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• v.13 no.6
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• pp.589-598
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• 2017

In this paper, dynamic response of the horizontal concrete beam subjected to seismic ground excitation is investigated. The structure is reinforced by $Fe_2O_3$ nanoparticles which have the magnetic properties. The hyperbolic shear deformation beam theory (HSDBT) is used for mathematical modeling of the structure. Based on the Mori-Tanaka model, the effective material properties of concrete beam is calculated considering the agglomeration of $Fe_2O_3$ nanoparticles. Applying energy method and Hamilton's principle, the motion equations are derived. Harmonic differential quadrature method (HDQM) along with Newmark method is utilized for numerical solution of the motion equations. The effects of different parameters such as volume fraction and agglomeration of $Fe_2O_3$ nanoparticles, magnetic field, boundary conditions and geometrical parameters of concrete beam are studied on the dynamic response of the structure. In order to validation of this work, an exact solution is used for comparing the numerical and analytical results. The results indicated that applying magnetic field decreases the of the structure up to 54 percent. In addition, increase too much the magnetic field (Hx>5e8 A/m) does not considerable effect on the reduction of the maximum dynamic displacement.

• Steel and Composite Structures
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• v.33 no.4
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• pp.583-594
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• 2019

In the areas highly exposed to earthquakes, concrete-filled steel tube columns (CFSTCs) are known to provide superior structural aspects such as (i) high strength for good seismic performance (ii) high ductility (iii) enhanced energy absorption (iv) confining pressure to concrete, (v) high section modulus, etc. Numerous studies were reported on behavior of CFSTCs under axial compression loadings. This paper presents an analytical model to predict ultimate load capacity of CFSTCs with circular sections under axial load by using multivariate adaptive regression splines (MARS). MARS is a nonlinear and non-parametric regression methodology. After careful study of literature, 150 comprehensive experimental data presented in the previous studies were examined to prepare a data set and the dependent variables such as geometrical and mechanical properties of circular CFST system have been identified. Basically, MARS model establishes a relation between predictors and dependent variables. Separate regression lines can be formed through the concept of divide and conquers strategy. About 70% of the consolidated data has been used for development of model and the rest of the data has been used for validation of the model. Proper care has been taken such that the input data consists of all ranges of variables. From the studies, it is noted that the predicted ultimate axial load capacity of CFSTCs is found to match with the corresponding experimental observations of literature.

• Smart Structures and Systems
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• v.24 no.6
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• Advances in Energy Research
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• v.4 no.3
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• pp.213-221
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• 2016

The main purpose of this work is to test the validation of use of a four step reaction mechanism to simulate the laminar speed of hydrogen enriched methane flame. The laminar velocities of hydrogen-methane-air mixtures are very important in designing and predicting the progress of combustion and performance of combustion systems where hydrogen is used as fuel. In this work, laminar flame velocities of different composition of hydrogen-methane-air mixtures (from 0% to 40% hydrogen) have been calculated for variable equivalence ratios (from 0.5 to 1.5) using the flame propagation module (FSC) of the chemical kinetics software Chemkin 4.02. Our results were tested against an extended database of laminar flame speed measurements from the literature and good agreements were obtained especially for fuel lean and stoichiometric mixtures for the whole range of hydrogen blends. However, in the case of fuel rich mixtures, a slight overprediction (about 10%) is observed. Note that this overprediction decreases significantly with increasing hydrogen content. This research demonstrates that reduced chemical kinetics mechanisms can well reproduce the laminar burning velocity of methane-hydrogen-air mixtures at lean and stoichiometric mixture flame for hydrogen content in the fuel up to 40%. The use of such reduced mechanisms in complex combustion device can reduce the available computational resources and cost because the number of species is reduced.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.896-904
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• 2017

Several Generation IV nuclear reactor concepts have goals for optimizing investment recovery through phased introduction of multiple units on a common site with shared facilities and/or reconfigurable energy conversion systems. Additionally, small modular reactors are suitable for remote deployment to support highly localized microgrids in isolated, underdeveloped regions. The long-term economic viability of these advanced reactor plants depends on significant reductions in plant operations and maintenance costs. To accomplish these goals, intelligent control and diagnostic capabilities are needed to provide nearly autonomous operations with anticipatory maintenance. A nearly autonomous control system should enable automatic operation of a nuclear power plant while adapting to equipment faults and other upsets. It needs to have many intelligent capabilities, such as diagnosis, simulation, analysis, planning, reconfigurability, self-validation, and decision. These capabilities have been the subject of research for many years, but an autonomous control system for nuclear power generation remains as-yet an unrealized goal. This article describes a functional framework for intelligent, autonomous control that can facilitate the integration of control, diagnostic, and decision-making capabilities to satisfy the operational and performance goals of power plants based on multimodular advanced reactors.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1479-1486
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• 2019

The purpose of the present study is to develop the 3D static and noise simulator based on Galerkin Finite Element Method (GFEM) using the unstructured hexahedral elements. The 3D, 2G neutron diffusion and noise equations are discretized using the unstructured hexahedral by considering the linear approximation of the shape function in each element. The validation of the static calculation is performed via comparison between calculated results and reported data for the VVER-1000 benchmark problem. A sensitivity analysis of the calculation to the element type (unstructured hexahedral or tetrahedron elements) is done. Finally, the neutron noise calculation is performed for the neutron noise source of type of variable strength using the Green function technique. It is shown that the error reduction in the static calculation is considerable when the unstructured tetrahedron elements are replaced with the hexahedral ones. Since the neutron flux distribution and neutron multiplication factor are appeared in the neutron noise equation, the more accurate calculation of these parameters leads to obtaining the neutron noise distribution with high accuracy. The investigation of the changes of the neutron noise distribution in axial direction of the reactor core shows that the 3D neutron noise analysis is required instead of 2D.