• Structural Engineering and Mechanics
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• v.90 no.6
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• pp.601-610
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• 2024

Free vibration of layered conical shell frusta of thickness filled with fluid is investigated. The shell is made up of isotropic or specially orthotropic materials. Three types of thickness variations are considered, namely linear, exponential and sinusoidal along the radial direction of the conical shell structure. The equations of motion of the conical shell frusta are formulated using Love's first approximation theory along with the fluid interaction. Velocity potential and Bernoulli's equations have been applied for the expression of the pressure of the fluid. The fluid is assumed to be incompressible, inviscid and quiescent. The governing equations are modified by applying the separable form to the displacement functions and then it is obtained a system of coupled differential equations in terms of displacement functions. The displacement functions are approximated by cubic and quintics splines along with the boundary conditions to get generalized eigenvalue problem. The generalized eigenvalue problem is solved numerically for frequency parameters and then associated eigenvectors are calculated which are spline coefficients. The vibration of the shells with the effect of fluid is analyzed for finding the frequency parameters against the cone angle, length ratio, relative layer thickness, number of layers, stacking sequence, boundary conditions, linear, exponential and sinusoidal thickness variations and then results are presented in terms of tables and graphs.

• The Korean Journal of Petroleum Geology
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• v.5 no.1_2 s.6
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• pp.36-47
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• 1997

This study presents multi-variable sequence model for a broader application of sequence concept proposed by Exxon group. The concept of the multi-variable model is based on the fact that internal organization and boundary type of the sequences are determined by three varying factors including 3rd-order cycles of eustasy, and tectonic movement and sediment influx with 2nd-order changes. Instead of Exxon group's systems tracts, this model adopts parasequence sets as the fundamental building blocks of the sequence, because they are descriptive stratigraphic units simply defined by internal stacking pattern, reflecting interactions of accommodation and sediment influx. Seven sequence types which vary in number and type of internal parasequence sets are formulated as associations of four types of accommodation development and three grades of sediment influx. In the southwestern margin of Ulleung Basin, the multi-variable sequence analysis of shelf-slope sequence shows systematic changes in stratal patterns and the numbs, of constituent parasequence sets (i.e. sequence type). These changes are interpreted to reflect temporal and spatial changes in type and rate of tectonic movement and sediment influx, as a result of back-arc opening and closing. During the back-arc opening, rapid subsidence, continuous rise of relative sea level, and high sediment influx gave rise to sequences dominantly of single progradational parasequence set. In the early stage of back-arc closing accompanied by local contractional deformation, different types of sequences contemporaneously formed depending on the spatial changes in tectonically-controlled accommodation and influx rates. During the subsequent slow back-arc subsidence, rise-dominated relative sea-level cycle was coupled with moderate to high sedimentation rate to have resulted in sequences consisting of $2~3$ parasequence sets.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.103-116
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• 2008

This paper proposes quay crane (QC) scheduling algorithms that determine the working sequence of QCs over ship bays in a container vessel in automated container terminals. We propose two scheduling algorithms that examine the distribution of export containers in the stacking yard and determine the sequence of ship bays to balance the workload distribution among the yard blocks. One of the algorithms is a simple heuristic algorithm which dynamically selects the next ship bay based on the entropy of workloads among yard blocks whenever a QC finishes loading containers at a ship bay and the other uses genetic algorithm to search the optimal sequence of ship bays. To evaluate the fitness of each chromosome in the genetic algorithm, we have devised a method that is able to calculate an approximation of loading time of container vessels considering the workloads among yard blocks. Simulation experiments have been carried out to compare the efficiency of the proposed algorithms. The results show that our QC scheduling algorithms are efficient in reducing the turn-around time of container vessels.

• Composites Research
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• v.32 no.5
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• pp.216-221
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• 2019

Piecewise integrated composite (PIC) beam has different stacking sequences for several regions with respect to their superior load-resisting capabilities. On the interest of current research is to improve bending characteristics of PIC beam, with assigning specific stacking sequence to a specific region with the help of machine learning techniques. 240 elements of from the FE model were chosen to be reference points. Preliminary FE analysis revealed triaxialities at those regularly distributed reference points to obtain learning data creation of machine learning. Triaxiality values catagorise the type of loading i.e. tension, compression or shear. Machine learning model was formulated by learning data as well as hyperparameters and proper load fidelity was suggested by tuned values of hyperparameters, however, comparatively higher nonlinearity intensive region, such as side face of the beam showed poor load fidelity. Therefore, irregular distribution of reference points, i.e., dense reference points were distributed in the severe changes of loading, on the contrary, coarse distribution for rare changes of loading, was prepared for machine learning model. FE model with irregularly distributed reference points showed better load fidelity compared to the results from the model with regular distribution of reference points.

• Composites Research
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• v.35 no.5
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• pp.317-321
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• 2022

In this study, the PIC design method with machine learning that automatically assigning different stacking sequences according to loading types was applied bumper beam. The input value and labels of the training data for applying machine learning were defined as coordinates and loading types of reference elements that are part of the total elements, respectively. In order to compare the 2D and 3D implementation method, which are methods of representing coordinate value, training data were generated, and machine learning models were trained with each method. The 2D implementation method is divided FE model into each face and generating learning data and training machine learning models accordingly. The 3D implementation method is training one machine learning model by generating training data from the entire finite element model. The hyperparameter were tuned to optimal values through the Bayesian algorithm, and the k-NN classification method showed the highest prediction rate and AUC-ROC among the tuned models. The 3D implementation method revealed higher performance than the 2D implementation method. The loading type data predicted through the machine learning model were mapped to the finite element model and comparatively verified through FE analysis. It was found that 3D implementation PIC bumper beam was superior to 2D implementation and uni-stacking sequence composite bumper.

• Composites Research
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• v.35 no.1
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• pp.42-46
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• 2022

In this study, when the carbon fiber composite was manufactured, the correlation between the porosity and mechanical properties according to the number of glass fiber felts laminated together and the stacking sequence was confirmed. The carbon fiber composite was manufactured by stacking glass fiber felts, which are highly permeable materials, and using vacuum assisted resin transfer molding (VARTM). Porosity was measured by photographing the cross-section of the specimen with an optical microscope and then using porosity calculation code of MATLAB, and mechanical properties were measured for tensile strength, modulus by tensile test. Furthermore, Pearson correlation coefficient between porosity and mechanical properties was calculated to confirm the correlation between two variables. As a result, the number of glass fiber felt increased and the distance from the center of laminated composites increased, the porosity increasing were confirmed. In addition, tensile strength/modulus showed a weak positive correlation with porosity. Also, in order to confirm the effect of only porosity on tensile strength and modulus, mechanical properties calculated by CLPT (Classical Laminate Plate Theory) and experimental values were compared, and the difference in tensile strength showed a strong positive correlation with porosity and the difference in modulus showed a weak positive correlation with porosity.

• Composites Research
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• v.36 no.1
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• pp.53-58
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• 2023

The PIC design method is assigning different stacking sequences for each shell element through the preliminary FE analysis. In previous study, machine learning was applied to the PIC design method in order to assign the region efficiently, and the training data is labeled by dividing each region into tension, compression, and shear through the preliminary FE analysis results value. However, since buckling is not considered, when buckling occurs, it can't be divided into appropriate loading type. In the present study, it was proposed PIC-NTL (PIC design using novel technique for analyzing load type) which is method for applying a novel technique for analyzing load type considering buckling to the conventional PIC design. The stress triaxiality for each ply were analyzed for buckling analysis, and the representative loading type was designated through the determined loading type within decision area divided into two regions of the same size in the thickness direction of the elements. The input value of the training data and label consisted in coordination of element and representative loading type of each decision area, respectively. A machine learning model was trained through the training data, and the hyperparameters that affect the performance of the machine learning model were tuned to optimal values through Bayesian algorithm. Among the tuned machine learning models, the SVM model showed the highest performance. Most effective stacking sequence were mapped into PIC tube based on trained SVM model. FE analysis results show the design method proposed in this study has superior external loading resistance and energy absorption compared to previous study.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.2
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• pp.123-130
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• 2013

In this paper, the delamination and failures in frequency selected surface(FSS) caused by residual stresses in the FSS embedded hybrid composites due to the difference between the coefficients of thermal expansion of components and the transmission characteristic changes due to deformation of FSS patterns by residual stresses were studied. FSS may have different electromagnetic characteristics depending on the type of element, design variables, and arrangement. Design variables of dipole FSS were determined using PSO(Particle Swarm Optimization) to obtain the transmission characteristic for the target resonant frequency. Subsequently, the design variables of other types of N-pole(tripole, cross dipole, and Jerusalem cross) were determined based on the dimensions of the dipole for the comparisons of residual stresses of FSS embedded composite structures and transmission characteristics. In addition, effects of FSS pattern, and stacking sequence of composite laminates were considered.

• Composites Research
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• v.27 no.2
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• pp.37-41
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• 2014

Fiber reinforced composite materials have outstanding specific strength and specific stiffness. So the use of composite materials increases in various kinds of industrial fields including sports goods such as bicycles. Composite materials are used to make structural parts with various kinds of shapes. Specially, rectangular composite tubes are used to make a few of composite bicycle frames, but there has been a few of research on this issue. Rectangular composite tubes are designed to have appropriate radius of curvature and endure bending and torsional loads. In this research, nine kinds of rectangular composite tubes having aspect ratios 1:1, 1:1.5, 1:2 and radius of curvatures R5, R10, R15 were fabricated. The carbon fiber reinforced composite material was used to make tubes having same cross sectional areas. The stacking sequence of tubes is $[0/90/{\pm}45]s$. Experimental evaluation was accomplished to apply bending and torsional load to the tubes. Experimental results show that bending and torsional characteristics depend on radius of curvature and aspect ratio of rectangular composite tubes.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.250-258
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• 2014

Due to recent industrial growth and development, there has been a high demand for light and highly durable materials. Therefore, a variety of new materials has been developed. These new materials include carbon fiber reinforced plastic (CFRP or CRP), which is a wear-, fatigue-, heat-, and corrosion-resistant material. Because of its advantageous properties, CFRP is widely used in diverse fields including sporting goods, electronic parts, and medical supplies, as well as aerospace, automobile, and ship materials. However, this new material has several problems, such as delamination around the inlet and outlet holes at drilling, fiber separation, and tearing on the drilled surface. Moreover, drill chips having a fine particulate shape are harmful to the work environment and engineers' health. In fact, they deeply penetrate into machine tools, causing the reduction of lifespan and performance degradation. In this study, CFRP woven and unidirectional prepregs were formed at $45^{\circ}$ and $90^{\circ}$, respectively, in terms of orientation angle. Using a high-speed steel drill and a TiAIN-coated drill, the two materials were tested in three categories: cutting force with respect to RPM and feed speed; shape changes around the input and outlet holes; and the shape of drill chips.