• 한국조경학회지
• /
• 제32권5호
• /
• pp.43-51
• /
• 2004

Recently, the importance of choosing correct pavement materials has been increasing in urban spaces and streets. Much research regarding the pavement theory and construction method have been conducted, but analysis in terms of human psychological character has not yet been performed. The purpose of this study is to investigate the psychological characters to 12 pavement materials, that are commonly used in our urban spaces and streets. The results of the psychological character for each pavement material can be summarized as follows: 1. The psychological characters to each pavement material were as follows: ① Clay embodies a natural, traditional, soft and intimate psychological character; ② Pebble stone has a natural, hard, cool and intimate psychological character; ③ Turf grass incorporates an intimate and soft psychological character; ④ Ceramic brick has an artificial and hard psychological character; ⑤ Tile pavement has a modern, artificial, hard and cool psychological character; ⑥ Water permeable concrete has a modern and artificial psychological character; ⑦ Flag stone has a natural psychological character; ⑧ Granite has a modern and artificial psychological character; ⑨ Portland concrete has an artificial and hard psychological character; ⑩ Small compacted brick has an artificial, dynamic and modern psychological character; ⑪ Wood block pavement has a natural and traditional psychological character; ⑫ Asphalt concrete pavement has a modern, hard and artificial character. 2. On the results of the cluster analysis regarding psychological indexes for 12 pavement materials, pavement materials were categorized in 3 clusters. Among them, one cluster was mainly used as the most popular pavement material in our urban spaces and streets. From this point of view, psychological character for pavement material in our urban spaces and streets was not as various as we expected. 3. In conclusion, the proper selection of pavement materials was very important and the factors affecting the human psychological character should be considered in the design of urban spaces and streets.

• 한국실내디자인학회논문집
• /
• 제21권3호
• /
• pp.22-30
• /
• 2012

Nowadays the issue of environmental pollution and ecological destruction is not a simple issue but an important issue to be continuously considered. It is deemed that a study for recycled new materials is immediately required and this study is to analyze features and processing methods of new materials which can be used to interior space. We found the recycled new materials used for space through researching various web sits. And then we analyzed what the base materials are and classified that base materials are whether natural or artificial of the recycled materials. We classified processing methods of the recycled new materials after researching general processing methods. The result of this study would be an important material to the research and development of new finishing materials with consideration of environment and to the research for a guideline of applicable new materials. The results of this study are as follows : First, we could classify widely 2 categories into natural material and artificial material and then 10 subcategories into metal, glass, wood, rubber, stone, plastic, leather or fabric, ceramic, concrete and so on, and analyzed that which material is mostly used and whether it is single material or multiple material. In order to analyze the feature of processing method. Second, we could classify into 4 categories such as junction, surface process, molding, and insert, and found out which processing method is applied based on objects of research. Third, as an analysis result of the recycled new material feature, in order to develop various new materials, it is required to study on combination and application of 2 materials or more rather than single material. Four, as a analysis result of the processing method feature, I would like to suggest that development and application of various processing methods are required. Especially, it is necessary to grope for a way to develop new functional materials for interior space through a systemic research and analysis of processing method of other fields. Furthermore, a way to reuse recycled new materials should be considered in a stage of selection and application of processing method.

• 한국환경복원기술학회지
• /
• 제7권6호
• /
• pp.12-18
• /
• 2004

This study is to make plans for perpendicular greening with artificial ground of planter type to improve urban environment. The experiments of this study are performed to find out the suitable soil and irrigation method for artificial ground of planter greening. Thereupon, organic or inorganic soil improvement material is mixed with soil of each planter as experiment, In result, the plants in soil mixed organic soil improvement material thrive rather than that in soil mixed inorganic material, It is to be desired that the planter equip with the irrigation system, be wider than planter and be planted shrubs for positive plant growth. As for irrigation system, drip irrigation is effective on plant growth southern exposure but Ebb and Flow is effective eastern exposure. Therefore, irrigation system should consist of two types above plus keeping water on the bottom of planter to save water and store rainwater.

• Structural Engineering and Mechanics
• /
• 제85권1호
• /
• pp.15-27
• /
• 2023

Using artificial intelligence and internet of things methods in engineering and industrial problems has become a widespread method in recent years. The low computational costs and high accuracy without the need to engage human resources in comparison to engineering demands are the main advantages of artificial intelligence. In the present paper, a deep neural network (DNN) with a specific method of optimization is utilize to predict fundamental natural frequency of a cylindrical structure. To provide data for training the DNN, a detailed numerical analysis is presented with the aid of functionally modified couple stress theory (FMCS) and first-order shear deformation theory (FSDT). The governing equations obtained using Hamilton's principle, are further solved engaging generalized differential quadrature method. The results of the numerical solution are utilized to train and test the DNN model. The results are validated at the first step and a comprehensive parametric results are presented thereafter. The results show the high accuracy of the DNN results and effects of different geometrical, modeling and material parameters in the natural frequencies of the structure.

• 한국암반공학회:학술대회논문집
• /
• 한국암반공학회 2008년도 국제학술회의
• /
• pp.43-51
• /
• 2008

Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.

• Steel and Composite Structures
• /
• 제24권5호
• /
• pp.635-641
• /
• 2017

Safety service improvement and development of efficient maintenance strategies for corroded steel structures are undeniably essential. Therefore, understanding the influence of damage caused by corrosion on the remaining load-carrying capacities such as tensile strength is required. In this study, artificial neural network (ANN) approach is proposed in order to produce a simple, accurate, and inexpensive method developed by using tensile test results, material properties and finite element method (FEM) results to train the ANN model. Initially in reproducing corroded model process, FEM was used to obtain tensile strength of artificial corroded plates, for which surface is developed by a spatial autocorrelation model. By using the corroded surface data and material properties as input data, with tensile strength as the output data, the ANN model could be trained. The accuracy of the ANN result was then verified by using leave-one-out cross-validation (LOOCV). As a result, it was confirmed that the accuracy of the ANN approach and the final output equation was developed for predicting tensile strength without tensile test results and FEM in further work. Though previous studies have been conducted, the accuracy results are still lower than the proposed ANN approach. Hence, the proposed ANN model now enables us to have a simple, rapid, and inexpensive method to predict residual tensile strength more accurately due to corrosion in steel structures.

• Steel and Composite Structures
• /
• 제51권2호
• /
• pp.203-223
• /
• 2024

This study shows functionally graded material structural topology optimization under buckling constraints. The SIMP (Solid Isotropic Material with Penalization) material model is used and a method of moving asymptotes is also employed to update topology design variables. In this study, the quadrilateral element is applied to compute buckling load factors. Instead of artificial density properties, functionally graded materials are newly assigned to distribute optimal topology materials depending on the buckling load factors in a given design domain. Buckling load factor formulations are derived and confirmed by the resistance of functionally graded material properties. However, buckling constraints for functionally graded material topology optimization have not been dealt with in single material. Therefore, this study aims to find the minimum compliance topology optimization and the buckling load factor in designing the structures under buckling constraints and generate the functionally graded material distribution with asymmetric stiffness properties that minimize the compliance. Numerical examples verify the superiority and reliability of the present method.

• 한국세라믹학회지
• /
• 제47권5호
• /
• pp.445-449
• /
• 2010

The purpose of this study is to improve recycling rate of the waste glasses by investigating bloating mechanism. In this study, we use waste glass(W/G) and hard clay(H/C) as raw materials. The artificial lightweight aggregates were formed by plastic forming($\phi$=10 mm) and sintered by fast firing method at different temperatures(between 700 and $1250^{\circ}C$). The physical properties of the aggregates such as bulk specific gravity, adsorption and microstructure of surface and cross-section are investigated with the sintering temperature and rate of W/G-H/C contents. As the result of the bulk specific gravity graphs, we can found out the inflection point at content of W/G 60 wt%. From the microstructure images, we considered the artificial lightweight aggregates content of W/ G over 60wt% are distributed numerous micro-pores by organic oxidation without Black Core and the artificial lightweight aggregates of W/G below 60 wt% are distributed macro-pores with Black Core.

• Environmental Analysis Health and Toxicology
• /
• 제27권
• /
• pp.5.1-5.10
• /
• 2012

Objectives: The purpose of this study was to assess the risk of ingestion exposure of lead by particle sizes of crumb rubber in artificial turf filling material with consideration of bioavailability. Methods: This study estimated the ingestion exposure by particle sizes (more than 250 um or less than 250 um) focusing on recyclable ethylene propylene diene monomer crumb rubber being used as artificial turf filling. Analysis on crumb rubber was conducted using body ingestion exposure estimate method in which total content test method, acid extraction method and digestion extraction method are reflected. Bioavailability which is a calibrating factor was reflected in ingestion exposure estimate method and applied in exposure assessment and risk assessment. Two methods using acid extraction and digestion extraction concentration were compared and evaluated. Results: As a result of the ingestion exposure of crumb rubber material, the average lead exposure amount to the digestion extraction result among crumb rubber was calculated to be $1.56{\times}10^{-4}$ mg/kg-day for low grade elementary school students and $4.87{\times}10^{-5}$ mg/kg-day for middle and high school students in 250 um or less particle size, and that to the acid extraction result was higher than the digestion extraction result. Results of digestion extraction and acid extraction showed that the hazard quotient was estimated by about over 2 times more in particle size of lower than 250 um than in higher than 250 um. There was a case of an elementary school student in which the hazard quotient exceeded 0.1. Conclusions: Results of this study confirm that the exposure of lead ingestion and risk level increases as the particle size of crumb rubber gets smaller.

• Advances in concrete construction
• /
• 제15권4호
• /
• pp.269-286
• /
• 2023

In the present study, we aim to utilize the numerical solution frequency results of functionally graded beam under thermal and dynamic loadings to train and test an artificial neural network. In this regard, shear deformable functionally-graded beam structure is considered for obtaining the natural frequency in different conditions of boundary and material grading indices. In this regard, both analytical and numerical solutions based on Navier's approach and differential quadrature method are presented to obtain effects of different parameters on the natural frequency of the structure. Further, the numerical results are utilized to train an artificial neural network (ANN) using AdaGrad optimization algorithm. Finally, the results of the ANN and other solution procedure are presented and comprehensive parametric study is presented to observe effects of geometrical, material and boundary conditions of the free oscillation frequency of the functionally graded beam structure.