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김재열 ( Kim¸ Jae-yeol ) 한국구조물진단유지관리공학회 2007 한국구조물진단유지관리공학회 학술발표대회 논문집 Vol.11 No.1
This paper deals with a analysis method of Tensegrity Structures structures consisted with cables and struts which is a type of lightweight structural systems suitable for covering large column-free space. Tensegrity Structures derives its initial stiffness from appropriate combination of initial tension or compression introduced into the system. For the design of this type of structure, a special step to determine the self-equilibrium stress mode is necessary. In this paper, a simple method based on the use of generalized inverse will be described. The ultimate aim of the paper is to introduce a tool with which various shapes of Tensegrity Structures could be analyzed for design purpose.
Investigation of the numerical analysis for the ultrasonic vibration in the injection molding
Jaeyeol Lee,김낙수 한국유변학회 2009 Korea-Australia rheology journal Vol.21 No.1
We studied the flow characteristics of the polymer melt in the injection molding process with ultrasonic vibration by using the numerical analysis. To minimize the error between the experimental data and numerical result, we presented a methodology using the design of experiments and the response surface method for reverse engineering. This methodology can be applied to various fields to obtain a valid and accurate numerical analysis. Ultrasonic vibration is generally applied between an extruder and the entrance of a mold for improvement the flow rate in injection molding. In comparison with the general ultrasonic process, the mode shape of the mold must be also considered when the ultrasonic vibration is applied on the mold. The mode shape is defined as the periodic and spatial deformation of the structure owing to the effect of the vibration, and it varies greatly according to vibration conditions such as the forcing frequency. Therefore, we considered new index and found the forcing frequency for obtaining the highest flow rate within the range from 20 to 60 kHz on the basis of the index. Ultimately, we presented the methodology for not only obtaining a valid and accurate numerical analysis, but also for finding the forcing frequency to obtain the highest flow rate in injection molding using ultrasonic vibration.
Numerical analysis of injection molding for filling efficiency on ultrasonic process
Jaeyeol Lee,김낙수,이재욱 한국유변학회 2008 Korea-Australia rheology journal Vol.20 No.2
In this study, we focus on the improvement of the filling efficiency in injection molding by application of ultrasonic vibration. While studies about the filling efficiency of typical filling processes in the injection molding have been widely performed, there have been only few studies about the filling efficiency of an ultrasonic process. The effect of the ultrasonic vibration is an important process condition, which influences the flow characteristics of polymer melt. This new condition even affects well-known injection conditions such as cavity pressure, injection temperature and mold temperature. For this study, we carried out a numerical analysis by appropriate modeling and analysis of the ultrasonic process in the filling process. To verify this numerical analysis, we compared the numerical results with the experimental data. Also, we analyzed the filling process in a thin cavity using this numerical analysis. To understand the flow characteristics of polymer melt in the ultrasonic process, we substituted real and complex vibration conditions with simplified and classified conditions according to the position of vibrating cavity surfaces and the phase difference between two opposing cavity surfaces. We also introduced MFR (melt flow ratio) as a new index to estimate the filling efficiency in the ultrasonic process.
Jaeyeol Song,Jin-Kook Lee,Jungsik Choi,Inhan Kim 한국CDE학회 2020 Journal of computational design and engineering Vol.7 No.5
This paper describes an approach to extracting a predicate-argument structure (PAS) in building design rule sentences using natural language processing (NLP) and deep learning models. For the computer to reason about the compliance of building design, design rules represented by natural language must be converted into a computer-readable format. The rule interpretation and translation processes are challenging tasks because of the vagueness and ambiguity of natural language. Many studies have proposed approaches to address this problem, but most of these are dependent on manual tasks, which is the bottleneck to expanding the scope of design rule checking to design requirements from various documents. In this paper, we apply deep learning-based NLP techniques for translating design rule sentences into a computer-readable data structure. To apply deep learning-based NLP techniques to the rule interpretation process, we identified the semantic role elements of building design requirements and defined a PAS for design rule checking. Using a bidirectional long short-term memory model with a conditional random field layer, the computer can intelligently analyze constituents of building design rule sentences and automatically extract the logical elements. The proposed approach contributes to broadening the scope of building information modeling-enabled rule checking to any natural language-based design requirements.