25 research outputs found

    ๋‹จ๊ธฐ ์นจ์ง€ ์‹คํ—˜(Short-Term Ponding Test)์„ ์ด์šฉํ•œ ์‹œ๋ฉ˜ํŠธ ๊ณ„ ์žฌ๋ฃŒ ๋‚ด๋ถ€๋กœ์˜ ์—ผ์†Œ์ด์˜จ ์นจํˆฌ ํ‰๊ฐ€

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฑด์„คํ™˜๊ฒฝ๊ณตํ•™๋ถ€, 2014. 8. ์กฐ์žฌ์—ด.Many concrete structures have recently been constructed on the seashore. In structures exposed to seawater, chloride ion is transported through concrete by various mechanisms such as diffusion, and results in the corrosion of embedded steel in concrete structures. So, the chloride transport rate in concrete needs to be predicted, to prevent degradation of the durability of concrete structures in service life. The chloride ion diffusion coefficient is a crucial factor in evaluating the chloride transport rate in concrete. A number of test methods have been developed to measure the chloride ion diffusion coefficient of concrete. Most of these test methods require excessive test duration, or else represent a chloride ion penetration mechanism that does not adequately reflect chloride ion transport in real concrete structures. This thesis proposes a new test method to determine the chloride ion diffusion coefficient, while avoiding these deficiencies. The proposed method incorporates a new analytical approach that determines the diffusion coefficient from the change of chloride ion concentration in a source solution. The proposed method can be called a short-term ponding test, in comparison with traditional long-term immersion tests. Validation tests were performed to verify the developed test method and mathematical model. It was found that the proposed test method and analytical solution could estimate the chloride ion diffusion coefficient within two weeks. The short-term ponding test was validated by comparison with a long-term immersion test, and an electrical migration-diffusion test (CTH test). Both the long-term immersion test and the short-term ponding test produced similar results, but the CTH test results differed significantly. This indicates that the short-term ponding test is a time-efficient and realistic method that reflects the actual marine environment. Numerical analysis was performed to verify assumptions in the mathematical model of the short-term ponding test. Pdepe function, one of the Matlab functions, was used to calculate the chloride concentration with time in the source solution, solving the governing equation of the mathematical model. The effects of concrete age and concentration change in the source solution on the diffusion coefficient in the short-term ponding test were verified. From numerical analysis, it can be concluded that in the short-term ponding test, the effect of concrete age and concentration change in the source solution can be neglected. The chloride binding isotherm of the short-term ponding test was also verified. Inverse analysis was adopted to estimate the effective diffusion coefficient, and Freundlich binding isotherm coefficients. It was found that the linear binding isotherm could be assumed in the short-term ponding test.ABSTRACT i TABLE OF CONTENTS iv LIST OF TABLES viii LIST OF FIGURES x NOTATIONS xv 1 . Introduction 1 1.1 Research background 1 1.2 Objectives and Scope 5 1.3 Outline 6 2 . Theoretical Backgrounds 7 2.1 Mechanisms of steel corrosion 7 2.2 Chloride binding 9 2.2.1 Generals 9 2.2.2 Binding isotherms 10 2.2.3 Factors affecting chloride binding 13 2.3 Chloride ion diffusion in concrete 18 2.3.1 General 18 2.3.2 Diffusion in concrete 18 2.4 Existing test methods 20 2.4.1 Long-term immersion test (Conventional immersion test) 20 2.4.2 Diffusion cell test 23 2.4.3 Rapid Chloride Permeability Test (RCPT) 25 2.4.4 Electrical-migration test (NT Build 355) 26 2.4.5 Chalmers Tekniska Hogskola (CTH) test 28 2.4.6 Resistivity Technique 32 2.4.7 Pressure penetration techniques 34 3 . Short-Term Ponding Test 38 3.1 Experimental set-up 38 3.2 Mathematical model 41 3.2.1 Governing equation 41 3.2.2 Initial and Boundary conditions 43 3.2.3 Analytical solution 45 4 . Validation Tests and Discussions 50 4.1 Experimental conditions 50 4.1.1 Materials and mixture proportions 50 4.1.2 Source solution 51 4.1.3 Measurement of chloride concentration in source solution 52 4.1.4 Other tests performed in this thesis 53 4.2 Chloride concentration in source solution 55 4.2.1 Concentration change in source solution 55 4.2.2 Effect of W/C 59 4.2.3 Effect of compression strength 59 4.2.4 Effect of concentration in source solution 59 4.2.5 Cautions for measurement using ion selective electrode 60 4.3 Diffusion coefficient 61 4.3.1 Determination method of diffusion coefficient 61 4.3.2 Diffusion coefficient and coefficient of determination (R-square) 62 4.3.3 Discussions 65 4.3.4 Reproducibility of short-term ponding test 67 4.3.5 Standard for curve-fitting 71 4.3.6 Consistency of apparent diffusion coefficient 73 4.4 Specimen numbers for target uncertainty 78 4.5 Comparison with existing tests 79 4.5.1 Test results obtained from NT Build 492 and NT Build 443 79 4.5.2 Discussions 88 5 . Numerical analysis 91 5.1 Numerical formulation 91 5.1.1 General 91 5.1.2 Pdepe function 93 5.2 Verification of results of numerical analysis 95 5.3 Verification of assuming infinite specimen depth 98 5.4 Effect of age on diffusion coefficient 99 5.4.1 General 99 5.4.2 Diffusion coefficient model 100 5.4.3 Numerical analysis 102 5.4.4 Results and discussion 103 5.5 Effect of concentration change in source solution 110 5.5.1 General 110 5.5.2 Relationship between concentration and diffusion coefficient 111 5.5.3 Regression analysis 112 5.5.4 Governing equation, initial and boundary conditions 114 5.5.5 Results and discussions 115 5.6 Verification of linear binding 121 5.6.1 General 121 5.6.2 Apparent diffusion coefficient 121 5.6.3 Effective diffusion coefficient ( ) 122 5.6.4 Inverse analysis 123 5.6.5 Results and discussions 125 6 . Conclusions and Recommendations 131 6.1 Conclusions 131 6.2 Recommendations 134 References 136 ๊ตญ๋ฌธ์ดˆ๋ก 148Docto

    A Study on Usage Behavior and Content Analysis of Smartphone 'Textphoto'

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› : ๋””์ง€ํ„ธ์ •๋ณด์œตํ•ฉํ•™๊ณผ, 2012. 8. ์ด์ค‘์‹.์Šค๋งˆํŠธํฐ๊ณผ ์Šค๋งˆํŠธํŒจ๋“œ์™€ ๊ฐ™์€ ์Šค๋งˆํŠธ ๊ธฐ๊ธฐ์˜ ๋ณด๊ธ‰์ด ๋ณดํŽธํ™” ๋˜๋ฉด์„œ ํ”ผ์ฒ˜ํฐ๊ณผ ๋””์ง€ํ„ธ ์นด๋ฉ”๋ผ๋ฅผ ํ•จ๊ป˜ ์‚ฌ์šฉํ•˜๋˜ ์‹œ๊ธฐ์™€๋Š” ๋‹ค๋ฅธ ์‚ฌ์ง„ ์ด์šฉํ–‰ํƒœ๊ฐ€ ๊ด€์ฐฐ๋˜๊ณ  ์žˆ๋‹ค. ํœด๋Œ€ํฐ ์นด๋ฉ”๋ผ์˜ ํ•ด์ƒ๋„๊ฐ€ ๋†’์•„์ง€๊ณ , ํ„ฐ์น˜ ๊ธฐ๋ฐ˜์˜ ํ™•๋Œ€ ๊ธฐ๋Šฅ์ด ์ง€์›๋˜๋Š” ๋™์‹œ์— ๋น ๋ฅธ ์†๋„์˜ ๋ฐ์ดํ„ฐ ์ „์†ก์ด ๊ฐ€๋Šฅํ•œ ์Šค๋งˆํŠธํฐ์˜ ๊ธฐ์ˆ ์  ํŠน์„ฑ์€ ์‚ฌ์ง„ ์ด์šฉ์˜ ๋ฌธํ™”์  ์–‘์ƒ์—๋„ ๋ณ€ํ™”๋ฅผ ๊ฐ€์ ธ์™”๋‹ค. ์ดฌ์˜ํ•  ๊ฐ€์น˜๊ฐ€ ์žˆ๋Š” ๋Œ€์ƒ์— ๋Œ€ํ•œ ์ธ์‹์˜ ์ „ํ™˜์ด ์ผ์–ด๋‚ฌ์Œ์€ ๋ฌผ๋ก , ์ดฌ์˜์˜ ๋™๊ธฐ, ์‚ฌ์ง„์˜ ํ™œ์šฉ๋ฐฉ์•ˆ๊ณผ ๊ด€๋ จํ•ด์„œ๋„ ๋ณ€ํ™”๊ฐ€ ์ผ์–ด๋‚ฌ๋‹ค. ๋˜ํ•œ ์Šค๋งˆํŠธํฐ ๋“ฑ์žฅ ์ดํ›„ ํœด๋Œ€ํฐ ์‚ฌ์ง„์ฒฉ์—์„œ ํฅ๋ฏธ๋กœ์šด ํ˜„์ƒ์ด ๊ด€์ฐฐ๋˜๋Š”๋ฐ, ํ…์ŠคํŠธ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์ดฌ์˜๋œ ์‚ฌ์ง„๋“ค์ด ๊ทธ๊ฒƒ์ด๋‹ค. ์ด๋“ค์€ ์ „ํ†ต์  ์‚ฌ์ง„์˜ ๋ฒ”์ฃผ์— ํฌํ•จ ๋œ๋‹ค๊ณ  ๋ณด๊ธฐ ์–ด๋ ค์šด ๋…ํŠนํ•œ ์–‘์‹์„ ๋ณด์ด๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ์ƒˆ๋กœ์šด ๋งค์ฒด๋ฅผ ํ…์ŠคํŠธ์‚ฌ์ง„์œผ๋กœ ์ •์˜ ํ•˜๊ณ , ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์‚ฌ์ง„์ฒฉ ๋‚ด์˜ ์‚ฌ์ง„๋“ค์„ ์ˆ˜์ง‘ํ•˜์—ฌ ํ…์ŠคํŠธ์‚ฌ์ง„ ๋ถ„ํฌ์˜ ํŠน์ง•๊ณผ ํ•จ๊ป˜ ์ดฌ์˜๋™๊ธฐ, ํ™œ์šฉ๋ฐฉ์•ˆ์„ ์กฐ์‚ฌํ•˜๊ณ , ์ด๋“ค ์‚ฌ์ง„์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๊ฐ€์ƒํ™”๋œ ํ…์ŠคํŠธ์˜ ๋‚ด์šฉ์  ํŠน์„ฑ ๋ณ€ํ™”๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์ž๋ฃŒ๋Š” ๋ฏธ๋ฆฌ๋ณด๊ธฐ์šฉ ์ธ๋„ค์ผ ์‚ฌ์ง„์„ ์ˆ˜์ง‘ํ•œ ์‹คํ—˜-A์™€, ์ด์™€ ๋ณ„๋„๋กœ ์ง„ํ–‰๋œ ์›๋ณธ ํฌ๊ธฐ ํ…์ŠคํŠธ์‚ฌ์ง„๋งŒ์„ ์ˆ˜์ง‘ํ•œ ์‹คํ—˜-B๋ฅผ ํ†ตํ•ด ์–ป์—ˆ๋‹ค. ์ „์ž์˜ ์‹คํ—˜์€ ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ๋ถ„ํฌ ๋ฐ ์ดฌ์˜๋™๊ธฐ์™€ ํ™œ์šฉ๋ฐฉ์•ˆ ์ „๋ฐ˜์„ ๊ด€์ฐฐํ•˜๊ธฐ ์œ„ํ•ด, ํ›„์ž์˜ ์‹คํ—˜์€ ํ…์ŠคํŠธ์‚ฌ์ง„์ด ์„ ํ˜ธํ•˜๋Š” ๋Œ€์ƒ์˜ ๋‚ด์šฉ์  ํŠน์„ฑ์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ์‹ค์‹œ๋˜์—ˆ๋‹ค. ์‹คํ—˜-A์—์„œ๋Š” ์—ฐ๋ น๋Œ€์— ์žˆ์–ด 20~30๋Œ€, ์ง์—…๊ตฐ์— ์žˆ์–ด ๋Œ€ํ•™์ƒ ๋˜๋Š” ์ง€์‹๋…ธ๋™์ž์ธ ์ง์žฅ์ธ ๋‚จ๋…€ 40๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ์ธ๋‹น 160๊ฐœ์˜ ์ธ๋„ค์ผ ์‚ฌ์ง„๊ณผ ํ•จ๊ป˜ ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ์ดฌ์˜๋™๊ธฐ ๋ฐ ํ™œ์šฉ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ๊ธฐ๋ก์„ ์ˆ˜์ง‘ํ•ด ๋ถ„์„ํ–ˆ๋‹ค. ์ด ์ž๋ฃŒ๋ฅผ ํ†ตํ•ด ๊ด€์ฐฐํ•˜๊ธฐ ์–ด๋ ค์šด ํ…์ŠคํŠธ์˜ ๋‚ด์šฉ์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ์‹คํ—˜-B๋ฅผ ํ†ตํ•ด 22๋ช…์˜ ์‹คํ—˜์ฐธ๊ฐ€์ž๋กœ๋ถ€ํ„ฐ ์›๋ณธ ํฌ๊ธฐ์˜ ํ…์ŠคํŠธ์‚ฌ์ง„ 151๊ฐœ์™€ ํ•จ๊ป˜ ์ด์šฉํ–‰ํƒœ์™€ ๊ด€๋ จ๋œ ๊ฐœ๋ฐฉํ˜• ์„ค๋ฌธ์˜ ๋‹ต์„ ์ˆ˜์ง‘ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ์Šค๋งˆํŠธํฐ ์‚ฌ์ง„์ฒฉ ๋‚ด ํ…์ŠคํŠธ์‚ฌ์ง„์€ ํ‰๊ท  30% ์ •๋„์˜ ๋น„์œจ๋กœ ๋ถ„ํฌํ•˜๊ณ  ์žˆ์—ˆ๋‹ค. ์ดฌ์˜๋™๊ธฐ ๋ฐ ํ™œ์šฉ๋ฐฉ์•ˆ๊ณผ ๊ด€๋ จํ•ด์„œ๋Š” ๋ฏธ๋ž˜์˜ ์–ด๋Š ์‹œ์ ์— ์ฐธ๊ณ ํ•˜๊ธฐ ์œ„ํ•ด ์ดฌ์˜ํ•œ ์‚ฌ์ง„๋“ค์ด ๊ฐ€์žฅ ๋งŽ์•˜๋Š”๋ฐ, ์‹ค์ œ๋กœ๋Š” ์ด๋“ค์ค‘ ์žŠํ˜€์ง„ ์ฑ„ ์‚ฌ์ง„์ฒฉ ์†์— ์ €์žฅ๋˜์–ด ์žˆ๋Š” ์‚ฌ์ง„๋“ค์ด ๊ฐ€์žฅ ๋งŽ์•˜๋‹ค. ํ™œ์šฉ๋™๊ธฐ๋ณ„๋กœ ๋ณด์•˜์„ ๋•Œ์—๋Š” ์‚ฌ์ง„์ฒฉ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ๋‹ค์‹œ ์‹คํ–‰์‹œ์ผœ ์ฐพ์•„๋ณธ ์‚ฌ์ง„๋“ค ์ค‘ ์ฐธ๊ณ ํ•˜๊ธฐ ์œ„ํ•ด ์ฐ์€ ์‚ฌ์ง„๋“ค์ด ๊ฐ€์žฅ ๋งŽ์•˜๊ณ , SNS๋ฅผ ํ†ตํ•ด ์ „์†กํ•˜๊ฑฐ๋‚˜ ์—…๋กœ๋“œํ•œ ํ…์ŠคํŠธ์‚ฌ์ง„๋“ค์˜ ๊ฒฝ์šฐ ์• ์ดˆ์— ๊ณต์œ ๋ฅผ ๋ชฉ์ ์œผ๋กœ ์ฐ์€ ๋น„์œจ์ด ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ๋‚ด์šฉ์  ํŠน์„ฑ์„ ์ •๋ณด ํ‘œ๋ฉด(information surface), ๋งค์ฒด ์ข…๋ฅ˜(media-type), ์ •๋ณด๋Ÿ‰, ์ •๋ณด ์ƒ์‚ฐ๋ฐฉ์‹, ์ •๋ณด ๋ฌถ์Œ๊ฐ„ ์กฐ์งํ™” ๋ฐฉํ–ฅ(์ฝ๊ธฐ ๋ฐฉํ–ฅ)์œผ๋กœ ๋‚˜๋ˆ„์–ด ๊ด€์ฐฐํ•œ ๊ฒฐ๊ณผ, ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ์ •๋ณด ํ‘œ๋ฉด์œผ๋กœ๋Š” ์Šค๋งˆํŠธํฐ์ด๋‚˜ PC ์Šคํฌ๋ฆฐ๊ณผ ๊ฐ™์€ ๊ฐœ์ธ์šฉ ๊ธฐ๊ธฐ์˜ ํ‘œ๋ฉด์ด ์••๋„์ ์œผ๋กœ ๋งŽ์•˜๋‹ค. ๋งค์ฒด ์ข…๋ฅ˜๋กœ์„œ๋Š” ํ…์ŠคํŠธ์™€ ์ด๋ฏธ์ง€ ํ˜ผํ•ฉํ˜•์ด 40% ์ •๋„์˜ ๋น„์œจ์„ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ์ •๋ณด ์ƒ์‚ฐ๋ฐฉ์‹์„ ๊ด€์ฐฐํ–ˆ์„ ๋•Œ์—๋Š” ์ˆ˜๊ธฐ(ๆ‰‹่จ˜), ํƒ€์ดํ•‘, ํ”„๋ฆฐํŒ…์˜ ์ƒ์‚ฐ๋ฐฉ์‹ ์ค‘ ์Šค๋งˆํŠธํฐ์ด๋‚˜ PC์™€ ๊ฐ™์€ ์ „์ž๋งค์ฒด ์ƒ์—์„œ ์ด๋ฃจ์–ด์ง€๋Š” ํƒ€์ดํ•‘์„ ํ†ตํ•œ ์ƒ์‚ฐ๋ฐฉ์‹์ด ๊ฐ€์žฅ ๋งŽ์•˜๋‹ค. ์ •๋ณด ๋ฌถ์Œ๊ฐ„ ์กฐ์งํ™” ๋ฐฉํ–ฅ(์ฝ๊ธฐ ๋ฐฉํ–ฅ) ์ฐจ์›์—์„œ๋Š” ๋น„์„ ํ˜•์  ์ฝ๊ธฐ ๋ฐฉํ–ฅ์„ ๋ณด์ด๋Š” ํ…์ŠคํŠธ์‚ฌ์ง„์ด ์„ ํ˜•์  ์ฝ๊ธฐ๋ฐฉ์‹์˜ ํ…์ŠคํŠธ ์‚ฌ์ง„๋ณด๋‹ค ๋งŽ์•˜๋‹ค. ๋˜ํ•œ ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ๋™๊ธฐ ๋ฐ ํ™œ์šฉ ์œ ํ˜• 20๊ฐœ์ค‘ ์ถœํ˜„ ๋นˆ๋„๊ฐ€ ๋†’์€ 8๊ฐœ ์œ ํ˜•๋ณ„๋กœ ๋Œ€ํ‘œ ์‚ฌ๋ก€๋ฅผ ์ถ”์ถœํ•ด ๊ด€์ฐฐํ•ด๋ณธ ๊ฒฐ๊ณผ, ๊ฐ ์œ ํ˜•๋ณ„๋กœ ํŠน์ • ์ข…๋ฅ˜์˜ ํ…์ŠคํŠธ์‚ฌ์ง„์ด ๋งŽ์ด ๋‚˜ํƒ€๋‚˜๊ณ , ์ด์— ๋”ฐ๋ผ ๋‚ด์šฉ์  ํŠน์„ฑ ๋˜ํ•œ ๋ณ€์ฃผ๋ฅผ ๋ณด์ด๋Š” ๊ฒƒ์„ ๊ด€์ฐฐํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด์ƒ์˜ ๋ถ„์„์„ ํ†ตํ•ด ์Šค๋งˆํŠธํฐ ํ…์ŠคํŠธ์‚ฌ์ง„ ๋“ฑ์žฅ์˜ ๊ธฐ์ˆ ์ , ๋ฌธํ™”์  ๋ฐฐ๊ฒฝ ๋ฐ ์‚ฌ์šฉ์ž๋“ค์ด ํ…์ŠคํŠธ์‚ฌ์ง„์ด๋ผ๋Š” ๋งค์ฒด๋ฅผ ํ†ตํ•ด ์ฃผ๋กœ ์ดฌ์˜ํ•˜๋Š” ๋Œ€์ƒ, ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ํ˜„์ƒ์ด ๊ฐ€์ง€๋Š” ์‚ฌํšŒ๋ฌธํ™”์  ํ•จ์˜์— ๋Œ€ํ•ด ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์Šค๋งˆํŠธํฐ์€ ํ•ด์ƒ๋„๊ฐ€ ๋†’๊ณ  ์ถฉ๋ถ„ํ•œ ์ €์žฅ ์šฉ๋Ÿ‰์„ ์ œ๊ณตํ•˜๋ฉฐ ํœด๋Œ€์„ฑ์ด ์ข‹์€ ๊ฐœ์ธ์šฉ ์ €์žฅ ๋งค์ฒด์ด๋‹ค. ๋งค์ฒด๊ณ„๋ณดํ•™์  ๊ด€์ ์—์„œ๋Š” ํœด๋Œ€ํฐ, ๋””์ง€ํ„ธ ์นด๋ฉ”๋ผ, ๊ฐœ์ธ์šฉ PC๋ฅผ ์žฌ๋งค๊ฐœํ•˜๋ฉฐ, ๋””์ง€ํ„ธ ์‚ฌ์ง„์˜ ์ƒ์‚ฐ๊ณผ ๊ด€๋ฆฌ ๋ฐ ํ™œ์šฉ์„ ํ•˜๋‚˜์˜ ๊ธฐ๊ธฐ ๋‚ด๋กœ ํ†ตํ•ฉ์‹œํ‚จ๋‹ค. ์ด์— ๋”ฐ๋ผ ๋ฌธํ™”์  ์ธก๋ฉด์—์„œ๋Š” ์ฃผ๋ณ€ ํ…์ŠคํŠธ ํ™˜๊ฒฝ์— ๋Œ€ํ•ด ๋ฌด์ฐจ๋ณ„์ ์œผ๋กœ ์ •๋ณด๋ฅผ ์ผ๋‹จ ์†Œ์œ ํ•˜๋ ค๋Š” ํƒœ๋„๊ฐ€ ๋‚˜ํƒ€๋‚˜๊ณ , ์ •๋ณด ์ž‰์—ฌ๊ฐ€ ๋ฐœ์ƒํ•œ๋‹ค. ์ดฌ์˜ ๋Œ€์ƒ์— ์žˆ์–ด ๊ฐœ์ธํ™”๋œ ์ •๋ณด ๊ธฐ๊ธฐ์˜ ํ‘œ๋ฉด์ด ๋งŽ์œผ๋ฉฐ, ๋งค์ฒด ์ข…๋ฅ˜์— ์žˆ์–ด์„œ๋Š” ์ด๋ฏธ์ง€์™€ ํ…์ŠคํŠธ๊ฐ€ ํ˜ผํ•ฉ๋œ ์–‘์‹, ์—ฌ๋Ÿฌ ๋‹จ๊ณ„์— ๊ฑธ์ณ ์ƒ์‚ฐ๋œ ์ •๋ณด๋“ค์ด ํ•œ ํ‘œ๋ฉด์— ์ค‘์ฒฉ๋˜์–ด ์žˆ๋Š” ๋Œ€์ƒ์ด ์„ ํ˜ธ๋˜๋Š” ๊ฒƒ ๋˜ํ•œ ์ด๋Ÿฌํ•œ ํ†ตํ•ฉ์  ์ •๋ณด ์†Œ๋น„ ์–‘์ƒ์„ ๋ฐ˜์˜ํ•œ๋‹ค. ํ†ตํ•ฉ์ , ์ž‰์—ฌ์  ์ •๋ณด ์ƒ์‚ฐ์€ ํ–‰์œ„์— ๋Œ€ํ•œ ํŒ๋‹จ์„ ํ˜„์žฌ์—์„œ ๋ฏธ๋ž˜๋กœ ์œ ๋ณดํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•๋Š” ํ†ต๋กœ๋กœ์จ ๊ธฐ๋Šฅํ•˜๊ธฐ๋„ ํ•œ๋‹ค. ๋˜ํ•œ ํ…์ŠคํŠธ ์ƒ์‚ฐ์˜ ์ธก๋ฉด์—์„œ ์“ฐ๊ธฐ ํ–‰์œ„๊ฐ€ ์บก์ณ๋ง (capturing) ํ–‰์œ„๋กœ ์ „ํ™›๋˜์—ˆ๋‹ค๋Š” ์ ์€ ์˜๋ฏธ๋ฅผ ๋˜์ƒˆ๊ธฐ๋ฉฐ ์ •๋ณด๋ฅผ ์žฌ์ƒ์‚ฐํ•˜๋Š” ๋Œ€์‹ ์— ์ž๋™์ ์ธ ๋ฐฉ์‹์œผ๋กœ ๊ธ€์“ฐ๊ธฐ ํ–‰์œ„๊ฐ€ ์ด๋ฃจ์–ด์ง€๊ธฐ ์‹œ์ž‘ํ–ˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค. ํ…์ŠคํŠธ์‚ฌ์ง„ ์ดฌ์˜ ๋Œ€์ƒ์— ์žˆ์–ด ๋ฌด์ฐจ๋ณ„์  ์ˆซ์ž๋‚˜ ๊ธฐํ˜ธ์˜ ๋ฐฐ์—ด, ํƒ€์ดํ•‘๊ณผ ๊ฐ™์€ ์ž๋™ํ™”๋œ ์“ฐ๊ธฐ ๊ธฐ์ˆ ๋กœ ์ƒ์‚ฐ๋œ ํ…์ŠคํŠธ๋“ค์ด ๋งŽ์Œ์€ ์ด๋Ÿฌํ•œ ํ•ด์„์„ ๋’ท๋ฐ›์นจํ•œ๋‹ค. ์Šค๋งˆํŠธํฐ์˜ ๋˜๋‹ค๋ฅธ ์ค‘์š”ํ•œ ๊ธฐ์ˆ ์  ํŠน์ง•์ธ ์›ํ™œํ•œ ๋„คํŠธ์›Œํฌ ์ง€์›์€ ๊ฐ€์ƒํ™”๋œ ํ…์ŠคํŠธ๋“ค์ด ํŠน์ • ๊ณต์œ  ๋Œ€์ƒ์ด๋‚˜ ๊ธฐ๊ธฐ๋ฅผ ์—ผ๋‘์— ๋‘๊ณ  ์ƒ์‚ฐ๋˜๋Š” ํ•ฉ๋ชฉ์ ์„ฑ์„ ๋„๋„๋ก ์œ ๋„ํ–ˆ๋‹ค. ์‚ฌ์ง„์ฒฉ์€ ์ด๋Ÿฌํ•œ ๋„คํŠธ์›Œํฌ ๊ธฐ๊ธฐ๋กœ์„œ์˜ ์Šค๋งˆํŠธํฐ์˜ ๊ฐ•์ ์„ ๋ณด์—ฌ์ฃผ๋Š” ๋™์‹œ์— ํ•œ๊ณ„์ ์„ ๋ณด์™„ํ•˜๋Š” ์™„์ถฉํŒ์œผ๋กœ์จ ์ž‘์šฉํ•˜๊ณ  ์žˆ๋Š”๋ฐ, ์ƒํ™ฉ์— ๋”ฐ๋ผ ๋„คํŠธ์›Œํฌ๋ฅผ ํ†ตํ•œ ์ ‘๊ทผ๋ณด๋‹ค ๋น ๋ฅธ ์ ‘๊ทผ(quick-access)์„ ์ œ๊ณตํ•˜๋Š” ์ •๋ณด ์ €์žฅ์†Œ ๊ฐ€ ๋˜์–ด์ฃผ๊ณ  ์žˆ๋Š” ํ˜„์ƒ์ด ์ด๋ฅผ ์ž˜ ๋ณด์—ฌ์ค€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ƒˆ๋กœ์šด ์—ฐ๊ตฌ ๋Œ€์ƒ ๋ฐ ๋ฐฉ๋ฒ•๋ก ์„ ๋ฐœ๊ตดํ•˜๊ณ , ์‚ฌ์ง„์˜ ์ƒˆ๋กœ์šด ์šฉ๋„ ๋ฐ ์‚ฌ์šฉ์ž์˜ ์ž ์žฌ์  ๋‹ˆ์ฆˆ๋ฅผ ๊ทœ๋ช…ํ–ˆ์œผ๋ฉฐ, ํ–ฅํ›„ ์Šค๋งˆํŠธ ์‚ฌ์ง„์ฒฉ์˜ ๋ณ€ํ™” ์–‘์ƒ์„ ์˜ˆ์ธกํ•˜๋Š” ์—ฐ๊ตฌ์˜ ์‹œ๋ฐœ์ ์ด ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๋ฅผ ๊ฐ–๋Š”๋‹ค.As smart devices like smartphones and smart pads become more common, a usage behavior different from that of using feature phones with digital cameras is being observed. Technical characteristics of smartphone such as high definition and zoom in function based on touch screen brought about changes in cultural aspects of photo usage. Not only the perception on objects worth taking picture have switched over but also the objective of picturing and practical use of photo have changed. In smartphones age, a interesting phenomenon is detected and emergence of photos aimed at text as object In this study, this kind of new media is defined as Textphoto and photos from users smartphone albums are collected as data to be examined. Characteristics of Textphoto distribution in an album, objectives of taking the pictures and practical uses of them were researched with the content analysis of this virtualized text. The data were collected with two experimentsexperiment-A which collected preview thumbnail photos in a smartphone album and a separate experiment, experiment-B which gathered only original sized Textphotos. The former was conducted to examine distribution of Textphotos, objectives of taking picture and practical uses of them. The latter experiment was carried out for a content analysis of the subject that Textphotos prefer. In experiment-A, 6400 thumbnail photos with users records of objective and practical use of each photo were collected from 40 smartphone users in their 20s to 30s in age, university students and knowledge workers in job occupation. To examine the content of the text in photos which was hard to be identified with thumbnail photos, experiment-B was conducted additionally. In experiment-B, 151 original sized Textphotos from 22 users collected and an open survey about the usage behavior was conducted. The analysis showed that Textphoto ratio in a smartphone album was average 30%. Concerning the objectives of taking picture and practical uses of them, photos taken as a reference for sometime in the future was the most but most of them were forgotten and just saved in the album. By objectives, among photos looked up with another album app running, photos taken for the reference was the most. Textphotos sent to other people or uploaded via Social Network Service were mostly taken for sharing in the first place. And the content analysis showed that a high portion of information surfaces of Textphotos were surfaces of personal devices like smartphone screens and PC screens. Regarding the media type, mixed type of text and image made up about 40% of Textphotos. As for the production method of Textphoto, among handwriting, typing and printing, typing on a electric media such as smartphone itself or PC was dominant. Regarding the organizing direction of information packets(reading direction), the non-linear was numerically superior to the linear. In this study, 8 most frequent cases among 20 cases classified by the objectives of taking picture and practical use of them were also analyzed at content level. It has been observed that specific types of Textphoto appeared with each different case and their characteristics played a variation at content level. This study has implications in that it discovered a new object and methodology of study and revealed a new use of photos as well as users underlying needs. It could be a starting point of researches that foresees changing aspect of a smart album.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 2 ์žฅ ๊ด€๋ จ ์—ฐ๊ตฌ 4 ์ œ 1 ์ ˆ ์‚ฌ์ง„์— ๋Œ€ํ•œ ํ•ด์„๊ณผ ์‚ฌ์ง„ ํ–‰์œ„์˜ ๋ถ„๋ฅ˜ 4 1. ์‚ฌ์ง„์„ ํ•ด์„ํ•˜๋Š” ๋‹ค์–‘ํ•œ ๊ด€์  4 1-1. ํ˜„์กด(presence, ๊ฑฐ๊ธฐ ์žˆ์Œ)์œผ๋กœ์„œ์˜ ์‚ฌ์ง„ 4 1-2. ๋ฐ˜์ถ”(reflection)๋กœ์„œ์˜ ์‚ฌ์ง„ 6 1-3. ์•„์šฐ๋ผ์˜ ๋ถ•๊ดด๋กœ์„œ์˜ ์‚ฌ์ง„ 7 1-4. ์ธ์ง€์  ๋ฌธ๋ฒ•์œผ๋กœ์„œ์˜ ์‚ฌ์ง„ 8 1-5. ์ž๋™ํ™” ์žฅ์น˜(apparatus)๋กœ์„œ์˜ ์‚ฌ์ง„ 8 2. ์‚ฌ์ง„ ํ–‰์œ„์˜ ๋ถ„๋ฅ˜ 9 2-1. ๋Œ€์ƒ์— ๋”ฐ๋ฅธ ๋ถ„๋ฅ˜ 9 2-2. ์ดฌ์˜ ๋™๊ธฐ, ๋ชฉ์ ์— ๋”ฐ๋ฅธ ๋ถ„๋ฅ˜ 9 ์ œ 2 ์ ˆ ๋ชจ๋ฐ”์ผ-ํ…์ŠคํŠธ๋กœ์„œ์˜ ์‚ฌ์ง„์˜ ๊ฐ€์ƒํ™”(virtualization) 12 1. ์ด๋™์„ฑ(mobility)์˜ ์ธก๋ฉด 13 2. ๊ฐ€๋ณ€์„ฑ(variability)์˜ ์ธก๋ฉด 16 3. ๊ณต์œ ๊ฐ€๋Šฅ์„ฑ(sharability)์˜ ์ธก๋ฉด 17 ์ œ 3 ์ ˆ ๊ฐ€์ƒํ™”๋œ ํ…์ŠคํŠธ์˜ ์กด์žฌ๋ก ์  ๋ณ€ํ™” 19 1. ํ…์ŠคํŠธ์‚ฌ์ง„๊ณผ ์ƒˆ๋กœ์šด ๊ธ€์“ฐ๊ธฐ์˜ ์–‘์‹ 19 2. ์†Œ์…œ(social) ์˜ ์˜๋ฏธ ๋ณ€ํ™” 21 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๋ฌธ์ œ ๋ฐ ๋ฐฉ๋ฒ• 23 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋ฌธ์ œ 23 ์ œ 2 ์ ˆ ์ธก์ •์„ ์œ„ํ•œ ๊ฐœ๋… ์ •์˜ 25 1. ํ…์ŠคํŠธ์‚ฌ์ง„ 25 2. ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ์ดฌ์˜๋™๊ธฐ ๋ฐ ํ™œ์šฉ๋ฐฉ์•ˆ ๋ถ„๋ฅ˜์ฒด๊ณ„ 27 3. ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ๋‚ด์šฉ์  ํŠน์„ฑ ์ •์˜ 28 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 29 1. ์Šค๋งˆํŠธํฐ ์‚ฌ์ง„์ฒฉ์˜ ์ •๋Ÿ‰์  ๋ถ„์„ 29 2. ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ๋‚ด์šฉ ๋ถ„์„ 30 ์ œ 4 ์žฅ ์‹ค ํ—˜ 31 ์ œ 1 ์ ˆ ์‹คํ—˜ ๋ฐฉ๋ฒ• 31 `1. ์‹คํ—˜ ํ™˜๊ฒฝ ์„ค์ • 33 1-1. ์‹คํ—˜ ๋„๊ตฌ ์ œ์ž‘ ๋ฐ ์„ค์น˜ 33 1-2. ํ”ผ์‹คํ—˜์ž ๋ชจ์ง‘ ๋ฐ ์„ ์ • 35 `2. ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘๊ณผ ๊ฒ€์ฆ 37 2-1. ์Šค๋งˆํŠธํฐ ์‚ฌ์ง„์ฒฉ ๋ฐ ์‚ฌ์šฉ์ž ๊ธฐ๋ก ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ 37 2-2. ํ…์ŠคํŠธ์‚ฌ์ง„ ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ 39 ์ œ 5 ์žฅ ๋ฐ์ดํ„ฐ ๋ถ„์„ 40 ์ œ 1 ์ ˆ ํ…์ŠคํŠธ์‚ฌ์ง„ ๋ถ„ํฌ์˜ ์ผ๋ฐ˜์  ํŠน์ง• 40 1. ํ…์ŠคํŠธ์‚ฌ์ง„ ๋ถ„ํฌ์˜ ์ธ๊ตฌํ†ต๊ณ„ํ•™์  ํŠน์ง• 40 2. ์ดฌ์˜๋™๊ธฐ์— ์žˆ์–ด์„œ์˜ ์ธ๊ตฌํ†ต๊ณ„ํ•™์  ํŠน์ง• 41 3. ํ™œ์šฉ๋ฐฉ์•ˆ์— ์žˆ์–ด์„œ์˜ ์ธ๊ตฌํ†ต๊ณ„ํ•™์  ํŠน์ง• 42 ์ œ 2 ์ ˆ ์ดฌ์˜๋™๊ธฐ์™€ ํ™œ์šฉ๋ฐฉ์•ˆ์˜ ์ƒ๊ด€๊ด€๊ณ„์— ์žˆ์–ด์„œ์˜ ํŠน์ง• 42 1. ์ดฌ์˜๋™๊ธฐ์— ๋”ฐ๋ฅธ ํ™œ์šฉ๋ฐฉ์•ˆ์— ์žˆ์–ด์„œ์˜ ํŠน์ง• 42 2. ํ™œ์šฉ๋ฐฉ์•ˆ๋ณ„ ์ดฌ์˜๋™๊ธฐ์— ์žˆ์–ด์„œ์˜ ํŠน์ง• 44 ์ œ 3 ์ ˆ ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ๋‚ด์šฉ์  ํŠน์„ฑ 45 1. ์ •๋ณด ํ‘œ๋ฉด(information surface)์„ ํ†ตํ•œ ๊ด€์ฐฐ 46 2. ๋งค์ฒด ์ข…๋ฅ˜(media type)๋ฅผ ํ†ตํ•œ ๊ด€์ฐฐ 47 3. ์ •๋ณด๋Ÿ‰ ๋ฐ ์ •๋ณด ์ƒ์‚ฐ ๋ฐฉ์‹์„ ํ†ตํ•œ ๊ด€์ฐฐ 48 4. ์ •๋ณด ๋ฌถ์Œ์˜ ์กฐ์งํ™” ๋ฐฉํ–ฅ(์ฝ๊ธฐ ๋ฐฉํ–ฅ) ๊ด€์ฐฐ 50 ์ œ 4 ์ ˆ ํ…์ŠคํŠธ์‚ฌ์ง„์˜ ๋™๊ธฐ ๋ฐ ํ™œ์šฉ ์œ ํ˜•์— ๋”ฐ๋ฅธ ๋‚ด์šฉ์  ํŠน์„ฑ 51 1. ์ธ์ƒ๊นŠ์–ด์„œ ์ฐ์—ˆ์œผ๋‚˜ ์žŠ์–ด๋ฒ„๋ฆฐ ์œ ํ˜•(I-F) 52 2. ์ฐธ๊ณ ํ•˜๋ ค๊ณ  ์ฐ์—ˆ๋‹ค๊ฐ€ ์žŠ์–ด๋ฒ„๋ฆฐ ์œ ํ˜•(R-F) 54 3. ์“ฐ๊ธฐ ๊ท€์ฐฎ์•„์„œ ์ฐ๊ณ  ๋‚˜์ค‘์— ๋‹ค์‹œ ์ฐพ์•„๋ณธ ์œ ํ˜•(W-L) 56 4. ์ฐธ๊ณ ํ•˜๋ ค๊ณ  ์ฐ์–ด์„œ ๋‚˜์ค‘์— ์ฐพ์•„๋ณธ ์œ ํ˜•(R-L) 57 5. ์ฐธ๊ณ ํ•˜๋ ค๊ณ  ์ฐ์–ด์„œ ๋ฌธ์„œ ๋“ฑ์— ์‚ฝ์ž…ํ•œ ์œ ํ˜•(R-P) ๋ฐ ์žฌ๋ฃŒ๋กœ ํ™œ์šฉํ•˜๋ ค๊ณ  ์ฐ์–ด์„œ ๋ฌธ์„œ ๋“ฑ์— ์‚ฝ์ž…ํ•œ ์œ ํ˜•(UD-P).. 59 6. ์ฐธ๊ณ ํ•˜๋ ค๊ณ  ์ฐ์–ด์„œ ์ „์†กํ•˜๊ฑฐ๋‚˜ ์—…๋กœ๋“œํ•œ ์œ ํ˜•(R-S) 60 7. ๊ณต์œ ํ•˜๋ ค๊ณ  ์ฐ์–ด์„œ ์ „์†กํ•˜๊ฑฐ๋‚˜ ์—…๋กœ๋“œํ•œ ์œ ํ˜•(US-S) 60 ์ œ 6 ์žฅ ๊ฒฐ ๋ก  62 ์ œ 1 ์ ˆ ์š” ์•ฝ 62 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ์‹œ์‚ฌ์  68 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ์ œ์–ธ 70 ์ฐธ๊ณ ๋ฌธํ—Œ 72 Abstract 75Maste
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