• Advances in Computational Design
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• v.6 no.1
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• pp.15-30
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• 2021

With improvement in innovative manufacturing technologies, it became possible to fabricate any complex shaped structural design for practical applications. This allows for the fabrication of curvilinearly stiffened pressure vessels and pipes. Compared to straight stiffeners, curvilinear stiffeners have shown to have better structural performance and weight savings under certain loading conditions. In this paper, an optimization framework for designing curvilinearly stiffened composite pressure vessels and pipes is presented. NURBS are utilized to define curvilinear stiffeners over the surface of the pipe. An integrated tool using Python, Rhinoceros 3D, MSC.PATRAN and MSC.NASTRAN is implemented for performing the optimization. Rhinoceros 3D is used for creating the geometry, which later is exported to MSC.PATRAN for finite element model generation. Finally, MSC.NASTRAN is used for structural analysis. A Bi-Level Programming (BLP) optimization technique, consisting of Particle Swarm Optimization (PSO) and Gradient-Based Optimization (GBO), is used to find optimal locations of stiffeners, geometric dimensions for stiffener cross-sections and layer thickness for the composite skin. A cylindrical pipe stiffened by orthogonal and curvilinear stiffeners under torsional and bending load cases is studied. It is seen that curvilinear stiffeners can lead to a potential 10.8% weight saving in the structure as compared to the case of using straight stiffeners.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1195-1208
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• 1997

Bellows is a component in piping systems which absorbs mechanical deformation with flexibility. Its geometry is an axial symmetric shell which consists of two toroidal shells and one annular plate or conical shell. In order to analyze bellows, this study presents the finite element analysis using a conical frustum shell element. A finite element analysis is developed to analyze various bellows. The validity of the developed program is verified by the experimental results for axial and lateral stiffness. The formula for calculating the natural frequency of bellows is made by the simple beam theory. The formula for fatigue life is also derived by experiments. The shape optimal design problem is formulated using multiple objective optimization. The multiple objective functions are transformed to a scalar function by weighting factors. The stiffness, strength and specified stiffness are considered as the multiple objective function. The formulation has inequality constraints imposed on the fatigue limit, the natural frequencies, and the manufacturing conditions. Geometric parameters of bellows are the design variables. The recursive quadratic programming algorithm is selected to solve the problem. The results are compared to existing bellows, and the characteristics of bellows is investigated through optimal design process. The optimized shape of bellows is expected to give quite a good guideline to practical design.

• Journal of Fashion Business
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• v.18 no.2
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• pp.148-165
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• 2014

The purpose of this study is to establish a theory about the necessary structure for knitwear design, and to propose it with the practical data through the actual development of a high value added knit structure. For this study, the market was conducted along with literature reviews on the existing studies and the relevant books about knit structures. The market research aimed at the products released in the spring/summer and fall/winter seasons of 2012-2013, focusing on brand for middle aged women. The utilization of the structure by item and the characteristics of knit design were studied. The research was conducted on S/S products in May and July, and F/W products in October and December. As a result of the market research, it was shown that the lightweight structures with permeability such as plain, lace, links and links, this is repeated and rib structure were frequently utilized during the S/S season, while double structures with good shape stability were greatly utilized during the F/W season. Also, during the F/W season, a cable structure and tubular jacquard that emphasized the volume or cubic effect were frequently used, and there were many jacquard structures where a change of color sense and motive were added. Concerning the knit structures development, the researcher designed the knit structure at the actual production site of the knit fashion. A total of 5 pieces of knit structures were developed by asking a professional for programming and knitting. To the developed structures, the study added a multi-gauged effect, herringbone transformation effect, 3-dimensional surface effect, color effects, geometric patterns, lace penetration effect, and soft surface effect in a water-drop shape. In addition, the structures had differences in the added values by mixing various structures and diversely expressing color sense on the knitting line. This study proposes the direction for 21st century knitwear product design, through the development of a high value added knit structure.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.489-509
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• 2024

Slope stability analysis and prediction are of critical importance to geotechnical engineers, given the severe consequences associated with slope failure. This research endeavors to forecast the factor of safety (FOS) for slopes through the implementation of six distinct ML techniques, including back propagation neural networks (BPNN), feed-forward neural networks (FFNN), Takagi-Sugeno fuzzy system (TSF), gene expression programming (GEP), and least-square support vector machine (Ls-SVM). 344 slope cases were analyzed, incorporating a variety of geometric and shear strength parameters measured through the PLAXIS software alongside several loss functions to assess the models' performance. The findings demonstrated that all models produced satisfactory results, with BPNN and GEP models proving to be the most precise, achieving an R² of 0.86 each and MAE and MAPE rates of 0.00012 and 0.00002 and 0.005 and 0.004, respectively. A Pearson correlation and residuals statistical analysis were carried out to examine the importance of each factor in the prediction, revealing that all considered geomechanical features are significantly relevant to slope stability. However, the parameters of friction angle and slope height were found to be the most and least significant, respectively. In addition, to aid in the FOS computation for engineering challenges, a graphical user interface (GUI) for the ML-based techniques was created.