• Advances in nano research
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• v.14 no.2
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• pp.141-154
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• 2023

Effects of viscoelastic foundation on vibration of curved-beam structure with clamped and simply-supported boundary conditions is investigated in this study. In doing so, a micro-scale laminate composite beam with two piezoelectric face layer with a carbon nanotube reinforces composite core is considered. The whole beam structure is laid on a viscoelastic substrate which normally occurred in actual conditions. Due to small scale of the structure non-classical elasticity theory provided more accurate results. Therefore, nonlocal strain gradient theory is employed here to capture both nano-scale effects on carbon nanotubes and microscale effects because of overall scale of the structure. Equivalent homogenous properties of the composite core is obtained using Halpin-Tsai equation. The equations of motion is derived considering energy terms of the beam and variational principle in minimizing total energy. The boundary condition is assumed to be clamped at one end and simply supported at the other end. Due to nonlinear terms in the equations of motion, semi-analytical method of general differential quadrature method is engaged to solve the equations. In addition, due to complexity in developing and solving equations of motion of arches, an artificial neural network is design and implemented to capture effects of different parameters on the inplane vibration of sandwich arches. At the end, effects of several parameters including nonlocal and gradient parameters, geometrical aspect ratios and substrate constants of the structure on the natural frequency and amplitude is derived. It is observed that increasing nonlocal and gradient parameters have contradictory effects of the amplitude and frequency of vibration of the laminate beam.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.615-621
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• 2018

To enhance the energy saving and comfort of indoors, this study performed a stimulation of sound fluctuation, color temperature, and aroma. The experiment with EEG, HRV, and Vibra images was conducted in an environmental test room with a temperature of $25[^{\circ}C]$, relative humidity of 50[RH%], air current speed of 0.002[m/s], and illuminance of 1000[lux]. The stimulation experiment set up different sensory stimulation conditions, such as before exposure, single-sensory stimulation of fluctuation a=1.106 jazz music, single-sensory stimulation of RED color lighting, single-sensory stimulation of scent aroma, and multi-sensory stimulation of fluctuation a=1.106 jazz music, RED color lighting, and scent aroma. After the multi-sensory stimulation of fluctuation a=1.106 jazz music, RED color lighting and scent aroma, the capacity for work and attention were increased, and the stress index and fatigue degree were decreased. In addition, multi-sensory stimulation of fluctuation a=1.106 jazz music, RED color lighting, and scent aroma were effective in maintaining a stable heart and health. In addition, the Vibra image appeared to decrease tension/anxiety and stress. The multi-sensory stimulation of fluctuation a=1.106 jazz music, RED color lighting, and scent aroma help increase the Neuro-energy more than that by no exposure and single-sensory stimulation.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.608-616
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• 2022

Power peaking factors (PPF) is an important parameter for safe and efficient reactor operation. There are several methods to calculate the PPF at TRIGA research reactors such as MCNP and TRIGLAV codes. However, these methods are time-consuming and required high specifications of a computer system. To overcome these limitations, artificial intelligence was introduced for parameter prediction. Previous studies applied the neural network method to predict the PPF, but the publications using the ANFIS method are not well developed yet. In this paper, the prediction of PPF using the ANFIS was conducted. Two input variables, control rod position, and neutron flux were collected while the PPF was calculated using TRIGLAV code as the data output. These input-output datasets were used for ANFIS model generation, training, and testing. In this study, four ANFIS model with two types of input space partitioning methods shows good predictive performances with R² values in the range of 96%-97%, reveals the strong relationship between the predicted and actual PPF values. The RMSE calculated also near zero. From this statistical analysis, it is proven that the ANFIS could predict the PPF accurately and can be used as an alternative method to develop a real-time monitoring system at TRIGA research reactors.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.5
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• pp.77-85
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• 2001

The purpose of this study is to suggest Vergence Information Extracting Algorithm(VIEA) which enables quick and accurate vergence information achievement for automation of vergence and focus control of horizontal moving stereoscopic camera. Firstly, for this purpose, the geometric structure of horizontal moving stereoscopic camera device was analyzed and linear relation between the vergence and the focus control. Then stereoscopic camera was designed and produced with the application of vergence and focus relation formula. Finally, VIEA that uses Cepstrum filter was employed to implement Automatic Vergence and Focus Controlling Stereoscopic Camera System(AVFCSCS). VIEA showed lower vergence achievement time and error ratio in comparison with existing algorithms. The suggested system in this study substantially reduced the controlling time and error-ratio as to make it possible to achieve natural and clear images. It also simplified the handling of stereoscopic camera for the convenience of end-users.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.1
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• pp.78-84
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• 1998

The fluid system such as, the quantity control of raw water, chemicals control in the purification, the waste water system as well as in the feed water or circulation system of the power plant and the ventilation system is controlled with the valve and moter pump. The system's performance and the energy saving of the fluid systems depend on control of method and delicacy. Until, PI controller use in these system but it cannot control delicately because of the coupling in the system loop. In this paper we configure a single flow system to the multi variable system and suggest the application of 2-DOF PID controller and the tuning methods by the neural network to the electrical power of the flow control system. the 2-DOF controller follows to a setpoint has a robustness against the disturbance in the results of simulation. Keywords Title, Intelligent control, Neuro control, Flow control, 2 - DOF control., 2 - DOF control.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1587-1599
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• 2017

This paper proposes a real-time implementation of an optimal operation of a double stage grid connected wind power system incorporating an active power filter (APF). The system is used to supply the nonlinear loads with harmonics and reactive power compensation. On the generator side, a new adaptive neuro fuzzy inference system (ANFIS) based maximum power point tracking (MPPT) control is proposed to track the maximum wind power point regardless of wind speed fluctuations. Whereas on the grid side, a modified predictive current control (PCC) algorithm is used to control the APF, and allow to ensure both compensating harmonic currents and injecting the generated power into the grid. Also a type 2 fuzzy logic controller is used to control the DC-link capacitor in order to improve the dynamic response of the APF, and to ensure a well-smoothed DC-Link capacitor voltage. The gained benefits from these proposed control algorithms are the main contribution in this work. The proposed control scheme is implemented on a small-scale wind energy conversion system (WECS) controlled by a dSPACE 1104 card. Experimental results show that the proposed T2FLC maintains the DC-Link capacitor voltage within the limit for injecting the power into the grid. In addition, the PCC of the APF guarantees a flexible settlement of real power exchanges from the WECS to the grid with a high power factor operation.

• Advances in nano research
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• v.12 no.5
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• pp.515-527
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• 2022

The application of fibers in concrete obviously enhances the properties of concrete, also the application of natural fibers in concrete is raising due to the availability, low cost and environmentally friendly. Besides, predicting the mechanical properties of concrete in general and shear strength in particular is highly significant in concrete mixture with fiber nanocomposite reinforced concrete (FRC) in construction projects. Despite numerous studies in shear strength, determining this strength still needs more investigations. In this research, Adaptive Neuro-Fuzzy Inference System (ANFIS) have been employed to determine the strength of reinforced concrete with fiber. 180 empirical data were gathered from reliable literature to develop the methods. Models were developed, validated and their statistical results were compared through the root mean squared error (RMSE), determination coefficient (R²), mean absolute error (MAE) and Pearson correlation coefficient (r). Comparing the RMSE of PSO (0.8859) and ANFIS (0.6047) have emphasized the significant role of structural parameters on the shear strength of concrete, also effective depth, web width, and a clear depth rate are essential parameters in modeling the shear capacity of FRC. Considering the accuracy of our models in determining the shear strength of FRC, the outcomes have shown that the R² values of PSO (0.7487) was better than ANFIS (2.4048). Thus, in this research, PSO has demonstrated better performance than ANFIS in predicting the shear strength of FRC in case of accuracy and the least error ratio. Thus, PSO could be applied as a proper tool to maximum accuracy predict the shear strength of FRC.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.1
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• pp.1-8
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• 2022

With the spread of COVID-19 worldwide, non-face-to-face services have grown rapidly, but at the same time, the problem of plastic waste is getting worse. Accordingly, eco-friendly policies such as carbon neutrality and sustainable circular economy are being promoted worldwide. Due to the high demand for eco-friendly products, the packaging industry is trying to develop eco-friendly packaging materials using PLA and PBAT and create new business models. On the other hand, Ulva australis occurs in large quantities in the southern seas of Korea and off the coast of Jeju Island, causing marine environmental problems. In this study, lactic acid was produced through dilute acid pretreatment, enzymatic saccharification, and fermentation processes to utilize Ulva australis as a new alternative energy raw material. In general, seaweeds vary in carbohydrate content and sugar composition depending on the species, harvest location, and time. Seaweed is mainly composed of polysaccharides such as cellulose, alginate, mannan, and xylan, but does not contain lignin. It is difficult to expect high extraction yield of the complex polysaccharide constituting Ulva australis with only one process. However, the fusion process of dilute acid and enzymatic saccharification presented in this study can extract most of the sugars contained in Ulva australis. Therefore, the fusion process is considered to be able to expect high lactic acid production yield when a commercial-scale production process is established.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.166-174
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• 1999

On-line efficiency optimization control of an induction motor drive using neural network is important from the v viewpoints of energy saving and controlling a nonlinear system whose charact81istics are not fully known. This paper p presents a neural networklongleftarrowbased on-line efficiency optimization control for an induction motor drive, which adopts an optimal slip an밍J.lar frequency control. In the proposed scheme, a neuro-controller provides minimal loss operating point i in the whole range of the measured input power. Both simulation and experimental results show that a considerable e energy saving is achieved compared with the conventional constant vlf ratio operation.