• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.180-184
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• 2007

For driving a sinusoidal type permanent magnet synchronous motor with a maximum continuous torque, a $120^0$ delayed three phase sinusoidal current input which matched with the absolute rotor position is needed at a stator coil. So, the detection of absolute rotor position is required inevitably. Thus the right angle relationship between stator magnetic field and rotor magnetic field has to be preserved at a stator by this commutation action. The detection of a absolute position for the commutation can be made generally by the output signal analysis of the encoder attached at a motor shaft. This study purposes to design signal processing logic circuits which can detect the absolute position of motor with a modem encoder system and generate the three reference wave for making sinusoidal current input at a stator coil.

• Steel and Composite Structures
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• v.17 no.6
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• pp.891-906
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• 2014

This study aims to present a three dimensional finite element model to investigate the wave propagation in a concrete filled steel tubular column (CFSC) due to transient impact load. Both the concrete and steel are regarded as linear elastic material. The impact load is simulated by a semi sinusoidal impulse. Besides the CFSC models, a concrete column (CC) model is established for comparing under the same loading condition. The propagation characteristics of the transient waves in CFSC are analyzed in detail. The results show that at the intial stage of the wave propagation, the velocity waves in CFSC are almost the same as those in CC before they arrive at the steel tube. When the waves reach the column side, the velocity responses of CFSC are different from those of CC and the difference is more and more obvious as the waves travel down along the column shaft. The travel distance of the wave front in CFSC is farther than that in CC at the same time. For different wave speeds in steel and concrete material, the wave front in CFSC presents an arch shape, the apex of which locates at the center of the column. Differently, the wave front in CC presents a plane surface. Three dimensional effects on top of CFSC are obvious, therefore, the peak value and arrival time of incident wave crests have great difference at different locations in the radial direction. High-frequency waves on the waveforms are observed. The time difference between incident and reflected wave peaks decreases significantly with r/R when r/R < 0.6, however, it almost keeps constant when $r/R{\geq}0.6$. The time duration between incident and reflected waves calculated by 3D FEM is approximately equal to that calculated by 1D wave theory when r/R is about 2/3.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1018-1024
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• 2011

For the driving of the sinusoidal type permanent magnet synchronous motor with a maximum continuous torque, the 1200 delayed three phase sinusoidal current inputs which matched with the absolute rotor position are needed at the stator coil. Therefore, the detection of a absolute rotor position is required inevitably. And the right angle relationship between stator magnetic field and rotor magnetic field has to be preserved at a stator by this commutation action. The detection of a absolute position for the commutation can be made generally by the output signal analysis of the encoder attached at a motor shaft. The purposes of this study are to design signal processing logic circuits which could detect the absolute position of motor with a modern encoder system and generate the three reference wave for making sinusoidal current input at a stator coil.

• Steel and Composite Structures
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• v.34 no.5
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.