34 research outputs found

    Depression and resilience in ostomates of inflammatory bowel disease

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    ์ž„์ƒ๊ฐ„ํ˜ธ์ „๊ณต/์„์‚ฌ๋ณธ ์—ฐ๊ตฌ๋Š” ์—ผ์ฆ์„ฑ ์žฅ์งˆํ™˜์„ ์ง„๋‹จ ๋ฐ›์€ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ๊ณผ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์šฐ์šธ๊ณผ ๊ทน๋ณต๋ ฅ์˜ ์ •๋„ ๋ฐ ๊ด€๊ณ„๋ฅผ ํ™•์ธํ•˜์—ฌ ์—ผ์ฆ์„ฑ ์žฅ์งˆํ™˜ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ ๊ฐ„ํ˜ธ ์ค‘์žฌ๋ฅผ ๊ฐœ๋ฐœํ•˜๊ธฐ ์œ„ํ•œ ๊ธฐ์ดˆ์ž๋ฃŒ๋ฅผ ์ œ๊ณตํ•˜๊ณ ์ž ์‹œ๋„๋œ ์„œ์ˆ ์  ์ƒ๊ด€๊ด€๊ณ„ ์—ฐ๊ตฌ์ด๋‹ค. ์ž๋ฃŒ์ˆ˜์ง‘์€2012๋…„ 11์›”๋ถ€ํ„ฐ 12์›”๊นŒ์ง€ ์„œ์šธํŠน๋ณ„์‹œ์— ์†Œ์žฌํ•˜๋Š” ์ผ์ข…ํ•ฉ ๋ณ‘์›์ธ A๋ณ‘์›์˜ ์†Œํ™”๊ธฐ๋‚ด๊ณผ์™€ ๋Œ€์žฅํ•ญ๋ฌธ์™ธ๊ณผ์— ๋“ฑ๋ก๋œ ์—ผ์ฆ์„ฑ ์žฅ์งˆํ™˜ ์žฅ๋ฃจ ๋ณด์œ ์ž 90๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ๊ตฌ์กฐํ™”๋œ ์„ค๋ฌธ์ง€๋ฅผ ํ†ตํ•ด ์ด๋ฃจ์–ด์กŒ๋‹ค. ์—ฐ๊ตฌ ๋„๊ตฌ๋Š” ์—ผ์ฆ์„ฑ ์žฅ์งˆํ™˜ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ ์šฐ์šธ์„ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•ด ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” Beck, Steer, & Brown(1996)์˜ Beck Depression Inventory(BDI-โ…ก)๋ฅผ Kim, Lee, & Lee(2010)๊ฐ€ ๋ฒˆ์•ˆํ•œ ์šฐ์šธ ๋„๊ตฌ์™€ Wagnild & Young(1993)์ด ๊ฐœ๋ฐœํ•˜๊ณ  Kim(2010)์ด ๋ฒˆ์•ˆํ•œ ๊ทน๋ณต๋ ฅ ๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์ˆ˜์ง‘๋œ ์ž๋ฃŒ๋Š”SPSS Win version 18.0 ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•˜์—ฌ ๊ธฐ์ˆ ํ†ต๊ณ„, ๊ต์ฐจ๋ถ„์„, ๋…๋ฆฝ-t๊ฒ€์ •, ๋ถ„์‚ฐ๋ถ„์„, Mann-whitney ๊ฒ€์ •, Kruskal-Wallis ๊ฒ€์ •, Pearson ์ƒ๊ด€๋ถ„์„, Spearman ์ƒ๊ด€๋ถ„์„์„ ์ด์šฉํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. 1. ๋ณธ ์—ฐ๊ตฌ์— ํฌํ•จ๋œ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž ์ค‘ ๋‚จ์ž๋Š” ์ „์ฒด 24๋ช… ์ค‘ 18๋ช…(75.0%)๋กœ ์—ฌ์ž๋ณด๋‹ค 3๋ฐฐ ๊ฐ€๋Ÿ‰ ๋งŽ์•˜์œผ๋ฉฐ ํ‰๊ท  ์—ฐ๋ น์€ 53.0์„ธ์ด์—ˆ๋‹ค. ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž๋Š” ์ „์ฒด 66๋ช… ์ค‘ ๋‚จ์ž๋Š” 35๋ช…(53.0%)์œผ๋กœ ์—ฌ์ž์™€ ๋น„์Šทํ•˜์˜€์œผ๋ฉฐ ํ‰๊ท  ์—ฐ๋ น์€ 34.3์„ธ์ด์—ˆ๋‹ค. 2. ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ 21๋ช…(87.5%)๋Š” ๊ธฐํ˜ผ์ด์˜€์œผ๋ฉฐ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ 41๋ช…(62.1%)๋Š” ๋ฏธํ˜ผ์ด์—ˆ๋‹ค. ๊ถค์–‘์„ฑ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ ํ‰๊ท  ์ˆ˜๋ฉด์‹œ๊ฐ„์€ 6.9์‹œ๊ฐ„์ด๋ฉฐ 6์‹œ๊ฐ„ ์ด์ƒ ์ˆ˜๋ฉดํ•˜๋Š” ์‚ฌ๋žŒ์ด 18๋ช…(75.0%)์ด์—ˆ์œผ๋ฉฐ 12๋ช…(50.0%)์ด ์ˆ˜๋ฉด ์žฅ์• ๊ฐ€ ์—†๋‹ค๊ณ  ์กฐ์‚ฌ๋˜์—ˆ๋‹ค. ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ ํ‰๊ท  ์ˆ˜๋ฉด ์‹œ๊ฐ„์€ 6.7์‹œ๊ฐ„์ด๋ฉฐ 58๋ช…(87.9%)์ด 6์‹œ๊ฐ„ ์ด์ƒ ์ˆ˜๋ฉดํ•˜๋‚˜ 37๋ช…(56.1%)์—์„œ ์ˆ˜๋ฉด ์žฅ์• ๊ฐ€ ์žˆ๋‹ค๊ณ  ์กฐ์‚ฌ๋˜์—ˆ๋‹ค. 3. ์—ผ์ฆ์„ฑ ์žฅ์งˆํ™˜์˜ ํ‰๊ท  ์ง„๋‹จ ํ›„ ๊ธฐ๊ฐ„์€ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž 10.1๋…„์œผ๋กœ 10๋…„ ์ด์ƒ์ธ ๊ฒฝ์šฐ๊ฐ€ 12๋ช…(50.0%)์ด์—ˆ์œผ๋ฉฐ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž๋Š” 10.8๋…„์œผ๋กœ 10๋…„ ์ด์ƒ์ธ ๊ฒฝ์šฐ๊ฐ€ 30๋ช…(45.5%)์ด์—ˆ๋‹ค. ํ‰๊ท  ์žฅ๋ฃจ ๋ณด์œ  ๊ธฐ๊ฐ„์€ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž๋Š”2.3๋…„์œผ๋กœ 5๋…„ ๋ฏธ๋งŒ์ธ ๊ฒฝ์šฐ๊ฐ€ 20๋ช…(83.3%)์ด ์—ˆ์œผ๋ฉฐ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž 3.0๋…„์œผ๋กœ 5๋…„ ๋ฏธ๋งŒ์ธ ๊ฒฝ์šฐ๊ฐ€ 48๋ช…(72.7%)๋กœ ๊ฐ€์žฅ ๋งŽ์•˜๋‹ค. 4. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ ์šฐ์šธ ์ ์ˆ˜๋Š” ํ‰๊ท 13.42์ ์ด์—ˆ ์œผ๋ฉฐ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž๋Š” ํ‰๊ท  14.24์ ์œผ๋กœ ์ค‘๋“ฑ๋„ ์šฐ์šธ ์ด์ƒ์ธ ๊ฒฝ์šฐ๋Š” ๊ฐ๊ฐ 5๋ช…(20.9%), 17๋ช…(23.8%)์ด์—ˆ๋‹ค. ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž๋Š” ์ผ๋ฐ˜์  ํŠน์„ฑ์— ๋”ฐ๋ฅธ ์šฐ์šธ์˜ ์œ ์˜ํ•œ ์ฐจ์ด๋Š” ์—†์—ˆ๋‹ค. ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž๋Š” ๊ฒฐํ˜ผ ์—ฌ๋ถ€(t=2.27, p=.027), ์›” ๊ฐ€๊ณ„ ์†Œ๋“(F=3.96, p=.012), ์ˆ˜๋ฉด ์‹œ๊ฐ„(t=2.11, p=.039), ์ˆ˜๋ฉด ์žฅ์•  ์—ฌ๋ถ€(t=4.73, p<.001)์— ๋”ฐ๋ผ ์šฐ์šธ์˜ ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. 5. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž์™€ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž ๋ชจ๋‘ ์งˆ๋ณ‘์  ํŠน์„ฑ์— ๋”ฐ๋ฅธ ์šฐ์šธ์˜ ์œ ์˜ํ•œ ์ฐจ์ด๋Š” ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. 6. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž์™€ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ ๊ทน๋ณต๋ ฅ ์ ์ˆ˜๋Š” ํ‰๊ท  123.75์ ๊ณผ 119.18์ ์ด์—ˆ๋‹ค. ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž๋Š” ์ผ๋ฐ˜ ์  ํŠน์„ฑ์— ๋”ฐ๋ฅธ ๊ทน๋ณต๋ ฅ์˜ ์œ ์˜ํ•œ ์ฐจ์ด๋Š” ์—†์—ˆ๋‹ค. ๋ฐ˜๋ฉด์— ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž๋Š” ์ผ๋ฐ˜์  ํŠน์„ฑ ์ค‘ ๊ฒฐํ˜ผ ์—ฌ๋ถ€(t=2.47, p=.016), ์›” ๊ฐ€๊ณ„ ์†Œ๋“(F=4.06, p=.011), ์ˆ˜๋ฉด ์žฅ์•  ์—ฌ๋ถ€(t=3.11, p=.003)์— ๋”ฐ๋ผ ๊ทน๋ณต๋ ฅ์˜ ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. 7. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž์™€ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž ๋ชจ๋‘ ์งˆ๋ณ‘์  ํŠน์„ฑ์— ๋”ฐ๋ฅธ ๊ทน๋ณต๋ ฅ์˜ ์œ ์˜ํ•œ ์ฐจ์ด๋Š” ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. 8. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž(r=-.668, p<.001)์™€ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž(r=-.604, p<.001)์˜ ์šฐ์šธ๊ณผ ๊ทน๋ณต๋ ฅ์€ ์„œ๋กœ ์œ ์˜ํ•œ ์Œ์˜ ์ƒ๊ด€ ๊ด€๊ณ„๋ฅผ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ์ด์ƒ์˜ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ์—ผ์ฆ์„ฑ ์žฅ์งˆํ™˜ ์žฅ๋ฃจ ๋ณด์œ ์ž์˜ ์šฐ์šธ ๋ฐœ์ƒ์„ ์˜ˆ๋ฐฉํ•˜๊ณ  ๊ทน๋ณต๋ ฅ์„ ์ฆ์ง„์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๊ทผ๊ฑฐ ๊ธฐ๋ฐ˜ ๊ฐ„ํ˜ธ ์ค‘์žฌ๋ฅผ ๋งˆ๋ จํ•˜๊ณ  ์ถ”ํ›„ ๊ถค์–‘์„ฑ ๋Œ€์žฅ์—ผ ์žฅ๋ฃจ ๋ณด์œ ์ž์™€ ํฌ๋ก ๋ณ‘ ์žฅ๋ฃจ ๋ณด์œ ์ž์— ๋Œ€ํ•œ ๋ณด๋‹ค ๊ด‘๋ฒ”์œ„์ ์ธ ์—ฐ๊ตฌ๊ฐ€ ์ด๋ฃจ์–ด์ ธ์•ผ ํ•  ํ•„์š”์„ฑ์ด ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค.ope

    Monotone iterative methods for a coupled system of fractional diffusion equations

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    (A)Reference image self-generating method for pattered wafers

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    The Effects of a Commercial Complex on Pedestrian Behavior in Commercial Districts

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฑด์„คํ™˜๊ฒฝ๊ณตํ•™๋ถ€, 2012. 2. ์•ˆ๊ฑดํ˜.์ตœ๊ทผ ๋‹จ์ˆœ ๊ตฌ๋งค์— ๋”๋ถˆ์–ด ๋‹ค์–‘ํ•œ ๊ฒฝํ—˜์„ ํ•จ๊ป˜ ์ฆ๊ธฐ๊ณ ์ž ํ•˜๋Š” ์†Œ๋น„ ์ˆ˜์š”๊ฐ€ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์˜ ๊ฐœ๋ฐœ์ด ํ™œ๋ฐœํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ์œผ๋ฉฐ, ํŠนํžˆ ์ด๋Ÿฌํ•œ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์€ ๊ฐ•ํ•œ ์ง‘๊ฐ๋ ฅ์„ ๋ฐ”ํƒ•์œผ๋กœ ์‡ ํ‡ดํ•œ ๊ตฌ๋„์‹ฌ์˜ ์ƒ์—…์ง€์—ญ์„ ํ™œ์„ฑํ™”์‹œํ‚ค๋Š” ์ฃผ์š” ๋ฐฉ์•ˆ์œผ๋กœ์„œ ์ธ์‹๋˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์€ ์‹œ์„ค์˜ ๊ทœ๋ชจ๊ฐ€ ํฌ๊ณ  ๋‹ค์–‘ํ•œ ํ–‰์œ„๋ฅผ ์ˆ˜์šฉํ•  ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ์ง€์—ญ์˜ ๋ณดํ–‰์ž๋ฅผ ์‹œ์„ค ๋‚ด๋ถ€๋กœ ๋Œ์–ด๋“ค์ด๋Š” ํšจ๊ณผ๋ฅผ ๊ฐ€์ง€๋ฉฐ, ์ด๋กœ ์ธํ•ด ์ƒ์—…์ง€์—ญ ๋‚ด ๊ธฐ์กด ์†Œ๊ทœ๋ชจ ์ ํฌ ๋ฐ ๊ฐ€๋กœ์—๋Š” ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น  ๊ฐ€๋Šฅ์„ฑ์ด ์กด์žฌํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ณดํ–‰ํ–‰ํƒœ ์ธก๋ฉด์—์„œ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์ด ์ƒ์—…์ง€์—ญ์˜ ๋ฐฉ๋ฌธ์ž์—๊ฒŒ ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ๋ถ„์„ํ•˜๊ณ ์ž ํ•˜๋ฉฐ, ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ง€์—ญ ์ „์ฒด์˜ ํ™œ์„ฑํ™”์— ๋ณด๋‹ค ์œ ๋ฆฌํ•œ ๋ณดํ–‰์ž ํ–‰ํƒœ๋ฅผ ์œ ๋„ํ•  ์ˆ˜ ์žˆ๋Š” ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค ๊ณ„ํš ๋ฐฉํ–ฅ์„ ๋„์ถœํ•˜๋Š” ๊ฒƒ์„ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ช…๋™ ์ƒ์—…์ง€์—ญ์„ ๋ฐฉ๋ฌธํ•œ ๋ฐฉ๋ฌธ์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์‹ค์‹œ๋œ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ์ด๋ฃจ์–ด์กŒ์œผ๋ฉฐ, ๊ตฌ์ฒด์ ์ธ ์—ฐ๊ตฌ๋ฌธ์ œ์™€ ๋ถ„์„ ๋ฐฉ๋ฒ•์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ ๋ฒˆ์งธ ์—ฐ๊ตฌ๋ฌธ์ œ๋Š” ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์ด ๋ณดํ–‰์ž ํ–‰ํƒœ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋ถ„์„ํ•˜๋Š” ๊ฒƒ์œผ๋กœ์„œ ์ด๋ฅผ ์œ„ํ•ด ์„ค๋ฌธ ๋Œ€์ƒ์ž๋ฅผ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์— ๋Œ€ํ•œ ๋ชฉ์  ๋ฐ ์ด์šฉ ์—ฌ๋ถ€์— ๋”ฐ๋ผ ์„ธ๋ถ€ ์ง‘๋‹จ์œผ๋กœ ๋ถ„๋ฅ˜ํ•œ ํ›„ ๊ฐ ์ง‘๋‹จ ๊ฐ„ ๋ณดํ–‰๋™์„  ๋ฐ ๋ณดํ–‰ํ–‰ํƒœ ๊ด€๋ จ ์ง€ํ‘œ ๊ฐ’์˜ ์ฐจ์ด๋ฅผ ๋น„๊ต ๋ถ„์„ํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ ์—ฐ๊ตฌ๋ฌธ์ œ๋Š” ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์˜ ํŠน์„ฑ์ด ๋ณดํ–‰์ž ํ–‰ํƒœ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋ถ„์„ํ•˜๋Š” ๊ฒƒ์œผ๋กœ์„œ ์ด๋ฅผ ์œ„ํ•ด ์„ค๋ฌธ์— ์‘๋‹ตํ•œ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค ์ด์šฉ์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์˜ ์œ„์น˜ ๋ฐ ๋ณตํ•ฉ ์œ ํ˜•์— ๋”ฐ๋ผ ์„ธ๋ถ€ ์ง‘๋‹จ์œผ๋กœ ๋ถ„๋ฅ˜ํ•œ ํ›„ ๊ฐ ์ง‘๋‹จ ๊ฐ„ ๋ณดํ–‰๋™์„  ๋ฐ ๋ณดํ–‰ํ–‰ํƒœ ๊ด€๋ จ ์ง€ํ‘œ ๊ฐ’์˜ ์ฐจ์ด๋ฅผ ๋น„๊ต ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์€ ์ƒ์—…์ง€์—ญ ๋ฐฉ๋ฌธ์ž์˜ ๋ณดํ–‰ ๋ฒ”์œ„, ๊ธฐ์กด ์†Œ๊ทœ๋ชจ ์ ํฌ ๋ฐ ๊ฐ€๋กœ์—์„œ์˜ ํ™œ๋™์„ ์ถ•์†Œ์‹œํ‚ค๋Š” ๊ฒฝํ–ฅ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํŠนํžˆ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์— ์˜ํ•ด ์ƒ์—…์ง€์—ญ์œผ๋กœ์˜ ์œ ์ž…์ธ๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ•˜๋”๋ผ๋„ ์ด๋“ค ๋Œ€๋ถ€๋ถ„์ด ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์„ ์ค‘์‹ฌ์œผ๋กœ ํ•œ์ •๋œ ๊ณต๊ฐ„๋งŒ์„ ์ด์šฉํ•˜๋ฉฐ, ํ™œ๋™์˜ ๋Œ€๋ถ€๋ถ„์„ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์— ์ง‘์ค‘์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค๊ณผ ๊ด€๊ณ„์—†์ด ์ƒ์—…์ง€์—ญ์„ ๋ฐฉ๋ฌธํ•œ ๊ธฐ์กด ๋ฐฉ๋ฌธ์ž์— ์žˆ์–ด์„œ๋„ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์„ ์ด์šฉํ•  ๊ฒฝ์šฐ ํ™œ๋™์˜ ๋งŽ์€ ๋ถ€๋ถ„์„ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค ๋‚ด์—์„œ ํ–‰ํ•จ์œผ๋กœ์จ ๊ธฐ์กด ์†Œ๊ทœ๋ชจ ์ ํฌ ๋ฐ ๊ฐ€๋กœ์—์„œ์˜ ํ™œ๋™์€ ์ถ•์†Œ๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰, ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์˜ ์ง‘๊ฐ๋ ฅ์€ ์ƒ์—…์ง€์—ญ ์ฐจ์›์—์„œ๋Š” ๊ธ์ •์ ์ธ ๊ฒƒ์œผ๋กœ ๋ณด์ด์ง€๋งŒ, ์ƒ์—…์ง€์—ญ ๋‚ด์—์„œ ๊ทธ ํšจ๊ณผ๊ฐ€ ํŒŒ๊ธ‰๋˜๋Š” ๊ณต๊ฐ„์  ๋ฒ”์œ„์— ์žˆ์–ด์„œ๋Š” ํ•œ๊ณ„๊ฐ€ ์กด์žฌํ•˜๋ฉฐ ์ผ๋ถ€ ์†Œ๊ทœ๋ชจ ์ ํฌ ๋ฐ ๊ฐ€๋กœ ์ฐจ์›์—์„œ๋Š” ์˜คํžˆ๋ ค ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ๋˜ํ•œ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์˜ ์œ„์น˜ ๋ฐ ๋ณตํ•ฉ ์œ ํ˜•์— ๋”ฐ๋ผ์„œ๋„ ๋ฐฉ๋ฌธ์ž์˜ ๋ณดํ–‰ ๋ฒ”์œ„, ๊ธฐ์กด ์†Œ๊ทœ๋ชจ ์ ํฌ ๋ฐ ๊ฐ€๋กœ์—์„œ์˜ ํ™œ๋™์ด ๋‹ฌ๋ผ์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ๋Œ€์ƒ์ง€ ์ž…๊ตฌ๋กœ๋ถ€ํ„ฐ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค๊นŒ์ง€์˜ ๊ฑฐ๋ฆฌ๊ฐ€ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ์ผ์ • ์ˆ˜์ค€๊นŒ์ง€ ์ด ์ด์šฉ์‹œ์„ค ์ˆ˜, ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์„ ์ œ์™ธํ•œ ๊ธฐํƒ€ ์‹œ์„ค ์ด์šฉ ์ˆ˜, ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค ์™ธ๋ถ€์—์„œ์˜ ์ง€์ถœ์•ก์ด ์ฆ๊ฐ€ํ•˜๊ฒŒ ๋˜๋ฉฐ, ๊ทธ ๊ฐ’์ด ์ตœ๋Œ€๊ฐ€ ๋˜๋Š” ์‹œ์ ์€ 200m์ด์ƒ 300m๋ฏธ๋งŒ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค ๋‚ด์— ์˜ํ™”๊ด€์ด ์ž…์ ํ•˜๊ฒŒ ๋  ๊ฒฝ์šฐ ์ด์šฉ์ž๋Š” ์ด ์‹œ๊ฐ„ ์ค‘ ์ƒ๋Œ€์ ์œผ๋กœ ๋งŽ์€ ๋ถ€๋ถ„์„ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค ๋‚ด์—์„œ ๋ณด๋‚ด๊ฒŒ ๋˜๋ฉฐ, ์‹ค์ œ ํ–‰์œ„ ์ˆ˜๋‚˜ ์ง€์ถœ์˜ ๋Œ€๋ถ€๋ถ„์„ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์— ์ง‘์ค‘์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์ด ํ•ด๋‹น ์ƒ์—…์ง€์—ญ ๋ฐฉ๋ฌธ์ž์˜ ๋ณดํ–‰ํ–‰ํƒœ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์‹ค์ฆ์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๊ตฌ์ฒด์ ์œผ๋กœ๋Š” ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์˜ ์ง‘๊ฐ๋ ฅ์ด ์ง€์—ญ ์ฐจ์›๊ณผ ์ง€์—ญ ๋‚ด๋ถ€์˜ ์ฐจ์›์—์„œ ๊ฐ๊ฐ ์–ด๋–ค ์˜๋ฏธ๋ฅผ ๊ฐ€์งˆ ์ˆ˜ ์žˆ๋Š”์ง€์— ๋Œ€ํ•œ ๋…ผ์˜๋ฅผ ์ „๊ฐœํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๋ฅผ ์ง€๋‹ˆ๋‹ค. ๋˜ํ•œ ์ƒ์—… ์ง€์—ญ ๋‚ด ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์„ ๊ฐœ๋ฐœํ•จ์— ์žˆ์–ด์„œ ์‹œ์„ค์˜ ์œ„์น˜ ๋ฐ ๋ณตํ•ฉ ์œ ํ˜•์„ ๊ณ ๋ คํ•œ ๊ณ„ํš์˜ ํ•„์š”์„ฑ์— ๋Œ€ํ•œ ์ด๋ก ์  ๊ทผ๊ฑฐ๋ฅผ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๋ฅผ ๊ฐ–๋Š”๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ–ฅํ›„ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค ๊ฐœ๋ฐœ์„ ์ถ”์ง„ํ•จ์— ์žˆ์–ด์„œ ๋ณด๋‹ค ๋„“์€ ์ƒ์—…์ง€์—ญ์˜ ์ƒ๊ถŒ์„ ํ™œ์„ฑํ™”๋ฅผ ๋„๋ชจํ•  ์ˆ˜ ์žˆ๋Š” ๋Œ€์•ˆ์„ ๋งˆ๋ จํ•  ์ˆ˜ ์žˆ์œผ๋ฆฌ๋ผ ๊ธฐ๋Œ€ํ•œ๋‹ค. ํŠนํžˆ ๋ณตํ•ฉ์ƒ์—…์‹œ์„ค์˜ ์œ„์น˜์™€ ๊ด€๋ จํ•˜์—ฌ ๋Œ€์ƒ์ง€ ๋‚ด๋ถ€์— ์ž…์ง€์‹œํ‚ค๋Š” ๊ฒƒ์ด ๋„์›€์ด ๋˜๋ฉฐ, ๊ตฌ์ฒด์ ์œผ๋กœ๋Š” ๋Œ€์ƒ์ง€ ์ž…๊ตฌ๋กœ๋ถ€ํ„ฐ 200m์ด์ƒ 300m๋ฏธ๋งŒ์ด ๋˜๋Š” ์ง€์ ์— ์œ„์น˜์‹œํ‚ค๋Š” ๊ฒƒ์ด ์ข‹์„ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ๋˜ํ•œ ๋ณตํ•ฉ ๊ธฐ๋Šฅ์— ์˜ํ™”๊ด€๊ณผ ๊ฐ™์€ ์—”ํ„ฐํ…Œ์ธ๋จผํŠธ ์š”์†Œ๊ฐ€ ๋„์ž…๋  ๊ฒฝ์šฐ ๋ณด๋‹ค ๋‹ค์–‘ํ•œ ๊ฐ€๋กœ๋ฅผ ํ†ตํ•ด ์ ‘๊ทผํ•  ์ˆ˜ ์žˆ๋Š” ๋‚ด๋ถ€์— ์ž…์ง€์‹œํ‚ค๋Š” ๊ฒƒ์ด ๋ฐ”๋žŒ์งํ•  ๊ฒƒ์ด๋‹ค.Maste

    ํ•ด์–‘ ๋ชจ๋“ˆ ๋ฐฐ์น˜๋ฅผ ๊ณ ๋ คํ•œ FEED ๋‹จ๊ณ„์—์„œ์˜ LNG FPSO ์šฉ ์ตœ์  ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‹œ์Šคํ…œ ์„ ์ • ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์กฐ์„ ํ•ด์–‘๊ณตํ•™๊ณผ, 2013. 2. ์ด๊ทœ์—ด.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ํ–ฅํ›„ LNG FPSO์— ์ ์šฉ ๊ฐ€๋Šฅํ•œ ์ตœ์  ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‹œ์Šคํ…œ ์„ ์ •์— ๊ด€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ ํ•˜์˜€๋‹ค. ์ด๋Š” ํ–ฅํ›„ LNG ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‹œ์Šคํ…œ์˜ FEED ์„ค๊ณ„์— ํฐ ๊ธฐ์—ฌ๋ฅผ ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ ํ•œ๋‹ค. ํ•ด์–‘ ์ ์šฉ์„ ์œ„ํ•œ ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‹œ์Šคํ…œ์€ ์œก์ƒ์— ์ ์šฉํ•˜๋Š” ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‹œ์Šคํ…œ๊ณผ๋Š” ํฐ ์ฐจ์ด๊ฐ€ ์žˆ๋‹ค. ์œก์ƒ์— ์ ์šฉํ•˜๊ธฐ ์œ„ํ•œ ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‚ฌ์ดํด์„ ์„ ์ •ํ•˜๋Š”๋ฐ ์žˆ์–ด ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์š”์†Œ๋Š” ์—ด์—ญํ•™์  ํšจ์œจ ์ด๋‹ค. ๊ทธ๋กœ ์ธํ•˜์—ฌ ์—ดํšจ์œจ์ด ๋†’์€ Pre-cooled mixed refrigerant ์‚ฌ์ดํด๊ณผ optimized cascade ์‚ฌ์ดํด์„ ์ ์šฉํ•œ ์•กํ™” ์‚ฌ์ดํด๋“ค์ด ์œก์ƒ LNG ์•กํ™” ํ”Œ๋žœํŠธ์— ์ฃผ๋ฅผ ์ด๋ฃจ์—ˆ๋‹ค. ์ด๋Ÿฐ ์—ดํšจ์œจ์ด ๋†’์€ ์œก์ƒ์šฉ LNG ์•กํ™” ์‚ฌ์ดํด๋“ค์€ ํ•ด์–‘์ ์šฉ์„ ์œ„ํ•ด์„œ๋Š” ์—ฌ๋Ÿฌ๊ฐ€์ง€ ๊ธฐ์ˆ ์ ์ธ ๋ฌธ์ œ๋“ค๋กœ ์ธํ•˜์—ฌ ์ ์ ˆ์น˜ ์•Š์„ ์ˆ˜ ์žˆ๋‹ค. ํ•ด์–‘ ์ ์šฉ์„ ์œ„ํ•œ ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‚ฌ์ดํด์€ ์—ด์—ญํ•™์  ํšจ์œจ๊ณผ ๋”๋ถˆ์–ด ์‚ฌ์ดํด์ด ๊ฐ„๊ฒฐํ•ด์•ผ ํ•˜๋ฉฐ ๋ฌด๊ฒŒ๊ฐ€ ๊ฐ€๊ฒน๊ณ  ์ฐจ์ง€ ํ•˜๋Š” ๋ฉด์ ์ด ์ž‘์•„์•ผ ํ•œ๋‹ค๋Š” ํ•ด์–‘ ํ™˜๊ฒฝ์„ ๊ณ ๋ คํ•œ ์ถ”๊ฐ€์ ์ธ ์ค‘์š”ํ•œ ์š”์†Œ๋“ค์ด ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ํ•ด์–‘์— ์ ์šฉ๊ฐ€๋Šฅํ•œ ์ตœ์  ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‚ฌ์ดํด์„ ์„ ์ €ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์œก์ƒ ์ ์šฉ ์‹œ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์š”์†Œ์ธ ํšจ์œจ(Efficiency)๊ณผ ํ•ด์–‘ ์ ์šฉ์‹œ ์ถ”๊ฐ€์ ์œผ๋กœ ๊ณ ๋ คํ•ด์•ผ ๋  ์ค‘์š”ํ•œ ์š”์†Œ๋“ค์ธ ๊ฐ„๊ฒฐ์„ฑ(Simplicity) ์‚ฌ์ด์— Trade-offs์™€ ์ ˆ์ถฉ์ด ํ•„์š”ํ•˜๋‹ค. ๊ทธ ์™ธ์—๋„ ํ•ด์–‘ ์ ์šฉ ์‹œ ๊ณ ๋ คํ•ด์•ผ ๋  ์š”์†Œ๋“ค๋กœ๋Š” ์œ ์—ฐ์„ฑ(Flexibility), ์•ˆ์ „(Safety), ๋ฐฐ์˜ ์›€์ง์ž„(Vessel Motion), ๋ƒ‰๋งค ํƒฑํฌ ์œ„ํ—˜์„ฑ(Refrigerant Storage Hazard), ๊ฒ€์ฆ๋œ ๊ธฐ์ˆ (Proven Technology), ์šด์ „์˜ ๊ฐ„๊ฒฐ์„ฑ(Simplicity of Operation), ์ดˆ๊ธฐ ์šด์ „/์šด์ „ ์ •์ง€์˜ ์šฉ์ด์„ฑ(Ease of Start-Up/Shutdown)๊ณผ ์ž๋ณธ(Capital Cost) ๋“ฑ์„ ๊ณ ๋ คํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” LNG FPSO ์ ์šฉ ๊ฐ€๋Šฅํ•œ ์ตœ์  ์•กํ™” ํ”„๋กœ์„ธ์Šค ์‚ฌ์ดํด ์„ ์ •์„ ์œ„ํ•ด์„œ ํšจ์œจ(Efficieny)๊ณผ ๊ฐ„๊ฒฐ์„ฑ(Simplicity)์„ ๊ณ ๋ คํ•˜์˜€์œผ๋ฉฐ ์ด๋ฅผ ์œ„ํ•ด ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์—ฐ๊ตฌ๋“ค์„ ์ง„ํ–‰ ํ•˜์˜€๋‹ค. ์ฒซ๋ฒˆ์งธ๋กœ, Generic MR(mixed Refrigerant) ์•กํ™” ์‚ฌ์ดํด์„ ์ œ์•ˆํ•˜์˜€์œผ๋ฉฐ ์ด๋ฅผ ๊ทผ๊ฑฐ๋กœ ๊ธฐ๊ณ„์ ์œผ๋กœ ์‹คํ˜„ ๊ฐ€๋Šฅํ•œ 27๊ฐœ MR ์•กํ™” ์‚ฌ์ดํด๋“ค์„ ์ตœ์  ํ•ฉ์„ฑ ํ•˜์˜€๋‹ค. 27๊ฐœ MR ์‚ฌ์ดํด๋“ค ์ค‘ ํšจ์œจ(Efficiency) ์ธก๋ฉด์—์„œ ์••์ถ•๊ธฐ ์†Œ์š” ๋™๋ ฅ์„ ์ตœ์†Œ๋กœ ํ•˜๋Š” ์ตœ์  ์šด์ „ ์กฐ๊ฑด๋“ค์„ ๊ตฌํ•˜์—ฌ ์ƒ์œ„ 10๊ฐœ MR ์•กํ™” ์‚ฌ์ดํด๋“ค์„ ์„ ์ • ํ•˜์˜€๋‹ค. ๊ทธ ํ›„ 10๊ฐœ MR ์‚ฌ์ดํด๋“ค ์ค‘ ๊ฐ„๊ฒฐ์„ฑ(Simplicity) ์ธก๋ฉด์—์„œ ํ•œ๊ฐ€์ง€ MR ์•กํ™” ์‚ฌ์ดํด์„ ์„ ์ • ํ•˜์˜€์œผ๋ฉฐ ์„ ์ •๋œ ํ•œ๊ฐ€์ง€ ์•กํ™” ์‚ฌ์ดํด์„ ์ž ์žฌ์  MR ์•กํ™” ์‚ฌ์ดํด๋กœ ๋ช…๋ช… ํ•˜์˜€๋‹ค. ์ด ๋‹จ๊ณ„์—์„œ ๊ณ ๋ คํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ„๊ฒฐ์„ฑ(Simplicity) ์ธก๋ฉด์€ ์žฅ๋น„ ๊ฐœ์ˆ˜๊ฐ€ ์œ ์ผํ•˜์—ฌ ์ด๋ฅผ ๊ธฐ์ค€์œผ๋กœ ํ•˜์˜€๋‹ค. ์ดํ›„, ์—ฌ๊ธฐ์„œ ์„ ์ •๋œ ์ž ์žฌ์  MR ์•กํ™” ์‚ฌ์ดํด๊ณผ ์ถ”๊ฐ€์ ์œผ๋กœ ๊ณ ๋ คํ•œ ํ•ด์–‘ ์•กํ™” ์‚ฌ์ดํด๋“ค์— ๋Œ€ํ•œ ๊ฐ„๊ฒฐ์„ฑ(Simplicity)์—ฐ๊ตฌ๋Š” ๊ฐ ์‚ฌ์ดํด๋“ค์— ๋Œ€ํ•œ ์ตœ์  ์žฅ๋น„ ๋ชจ๋“ˆ ๋ฐฐ์น˜(Optimal Equipment Module Layout)๋ฅผ ๊ตฌํ•˜์—ฌ ๋ณด๋‹ค ์‹ค์ œ์ ์ธ ๊ฐ„๊ฒฐ์„ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ ํ•˜์˜€๋‹ค. ๋‘๋ฒˆ์งธ๋กœ, ์„ ์ •๋œ ์ž ์žฌ์  MR ์•กํ™” ์‚ฌ์ดํด๊ณผ ์ถ”๊ฐ€์ ์œผ๋กœ 3๊ฐ€์ง€ ํ•ด์–‘ ์•กํ™” ์‚ฌ์ดํด๋“ค์„ ์„ ์ •ํ•˜์—ฌ ์ด๋“ค ์‚ฌ์ด์— LNG FPSO ์šฉ ์ตœ์  ์•กํ™” ์‚ฌ์ดํด์„ ์„ ์ •ํ•˜๊ธฐ ์œ„ํ•œ ํšจ์œจ(Efficiency) ๊ณผ ๊ฐ„๊ฒฐ์„ฑ(Simplicity) ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ ํ•˜์˜€๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ ๊ณ ๋ คํ•œ 3๊ฐ€์ง€ ํ•ด์–‘ ์•กํ™” ์‚ฌ์ดํด๋“ค๋กœ๋Š” ํ˜„์žฌ ์‹ค์ œ LNG FPSO์— ์ ์šฉ ์ค‘์ธ DMR ์‚ฌ์ดํด, Dual N2 Expander ์‚ฌ์ดํด๊ณผ ์œก์ƒ์—์„œ ๊ฐ€์žฅ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๋Š” C3 MR ์‚ฌ์ดํด๋“ค ์ด๋‹ค. ์ด 4๊ฐ€์ง€ ์‚ฌ์ดํด๋“ค์— ๋Œ€ํ•œ ํšจ์œจ(Efficiency) ์ธก๋ฉด์—์„œ๋Š” ๊ฐ ์‚ฌ์ดํด์„ ๊ตฌ์„ฑํ•˜๋Š” ์žฅ๋น„๋“ค ์ค‘ ์••์ถ•๊ธฐ ์†Œ์š” ๋™๋ ฅ์„ ์ตœ์†Œํ™”ํ•˜๋Š” ๊ธฐ์ค€์œผ๋กœ 4๊ฐ€์ง€ LNG ์ƒ์‚ฐ ์šฉ๋Ÿ‰(4.0 MTPA, 3.0 MTPA, 2.0 MTPA, and 1.0 MTPA)์— ๋Œ€ํ•œ ๊ฐ ์‚ฌ์ดํด๋“ค์„ ๋น„๊ต ๋ถ„์„ ํ•˜์˜€๋‹ค. ๋‹ค์Œ์œผ๋กœ ํ•ด์–‘ ์ ์šฉ ์‹œ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ๊ฐ„๊ฒฐ์„ฑ(Simplicity) ์ธก๋ฉด์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์–ธ๊ธ‰ ํ•˜๊ฒ ๋‹ค. ์ด ๋‹จ๊ณ„์—์„œ 4๊ฐ€์ง€ ์‚ฌ์ดํด๋“ค์˜ ์‹ค์ œ์ ์ธ ๊ฐ„๊ฒฐ์„ฑ(Simplicity) ์ฐจ์›์˜ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์žฅ๋น„ ๋ชจ๋“ˆ ๋ฐฐ์น˜ ์ตœ์ ํ™” ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์—ฌ ๊ฐ ์‚ฌ์ดํด๋“ค์ด ์ฐจ์ง€ํ•˜๋Š” ๋ฉด์ ๋“ค์„ ๊ตฌํ•จ์œผ๋กœ์จ ๊ฐ ์‚ฌ์ดํด๋“ค์„ ๋น„๊ต ๋ถ„์„์„ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ฐฐ๊ด€ ์—ฐ๊ฒฐ ๋น„์šฉ(Connectivity Cost), ์žฅ๋น„๋“ค์ด ์ฐจ์ง€ํ•˜๋Š” ๋ฉด์ ์— ๋น„๋ก€ํ•˜๋Š” ์ƒ์‚ฐ ๋น„์šฉ(Construction Cost), ๋ฐฐ์˜ ์šด๋™์— ๊ฐ€์žฅ ๋ฏผ๊ฐํ•œ ์žฅ๋น„๋“ค(Main Cryogenic Heat Exchanger, Phase Separator)์˜ ๋ฐฐ์˜ ์šด๋™์œผ๋กœ ์ธํ•œ ํšจ์œจ ๊ฐ์†Œ๋กœ ์ธํ•œ ๋น„์šฉ๋“ค์„ ๋ชฉ์ ํ•จ์ˆ˜๋กœ ์ •์˜ ํ•˜์˜€์œผ๋ฉฐ ์ด๋ฅผ ์ตœ์†Œํ™” ํ•˜์˜€๋‹ค. ์—ฌ๊ธฐ์„œ ๋ชฉ์ ํ•จ์ˆ˜๋ฅผ ํ†ตํ•ด ์•Œ ์ˆ˜ ์žˆ๋“ฏ์ด ํ•ด์–‘ ํ™˜๊ฒฝ์„ ๊ณ ๋Ÿฌํ•˜์—ฌ ๋ฐฐ์˜ ์šด๋™์— ๋ฏผ๊ฐํ•œ ์žฅ๋น„๋“ค์— ๋Œ€ํ•˜์—ฌ ํšจ์œจ์— ์ตœ๋Œ€ํ•œ ๋œ ์˜ํ–ฅ์„ ์ฃผ๊ธฐ ์œ„ํ•ด ๋ฐฐ์˜ ์ค‘์‹ฌ ๋ผ์ธ์— ๋ฐฐ์น˜๋  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ๋˜ํ•œ ํ•ด์–‘ ํ™˜๊ฒฝ ์ œ์•ฝ ์กฐ๊ฑด๋“ค์„ ๊ณ ๋ คํ•˜์—ฌ FEED ๋‹จ๊ณ„์—์„œ ๊ฐ ์‚ฌ์ดํด๋“ค์„ ๊ตฌ์„ฑํ•˜๋Š” ์žฅ๋น„๋“ค์ด ์ฐจ์ง€ํ•˜๋Š” ๋ฉด์ ์„ ์ตœ์†Œ๋กœ ํ•˜์˜€๋‹ค. ์ œ์•ฝ ์กฐ๊ฑด๋“ค๋กœ๋Š” ์•ˆ์ „์„ ๊ณ ๋ คํ•œ ์ œ์•ฝ ์กฐ๊ฑด๋“ค๊ณผ ๊ธธ์ด ๋ฐฉํ–ฅ์œผ๋กœ ๊ธด ์žฅ๋น„๋“ค์ด ์—ฌ๋Ÿฌ ์ธต์„ ๊ด€ํ†ตํ•˜๋Š” ์กฐ๊ฑด๋“ค ๋ฐ ํ•ด์–‘ ํ™˜๊ฒฝ์ƒ ํŠน๋ณ„ํžˆ ๊ณ ๋ คํ•ด์•ผ๋  ์ œ์•ฝ ์กฐ๊ฑด๋“ค์— ๋Œ€ํ•˜์—ฌ ์ •์˜ ํ•˜์˜€๋‹ค. ์ด๋Ÿฐ ์ œ์•ฝ ์กฐ๊ฑด๋“ค๊ณผ ๋ชฉ์ ํ•จ์ˆ˜๋ฅผ ๊ณ ๋Ÿฌํ•˜์—ฌ 4๊ฐ€์ง€ ์‚ฌ์ดํด๋“ค์— ๋Œ€ํ•œ ์ˆ˜ํ•™์  ๋ชจ๋ธ๋ง๋“ค์„ ๋„์ถœํ•˜์˜€์œผ๋ฉฐ Mixed Integer NonLinear Programming(MINLP)๋ฅผ ์ด์šฉํ•˜์—ฌ ์ตœ์ ํ™” ๋ฌธ์ œ๋“ค์„ ํ’€์–ด ์ตœ์  ์žฅ๋น„ ๋ชจ๋“ˆ ๋ฐฐ์น˜๋“ค์„ ๊ตฌํ•˜์—ฌ ๊ฒฐ๊ตญ ๊ฐ ์‚ฌ์ดํด๋“ค์ด ์ฐจ์ง€ํ•˜๋Š” ๋ฉด์ ๋“ค์„ ๊ตฌํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์‹ค์ œ LNG FPSO์— ์ ์šฉ์„ ์œ„ํ•˜์—ฌ ์ƒ๊ธฐ 4๊ฐ€์ง€ ์‚ฌ์ดํด๋“ค์˜ ํšจ์œจ(Efficiency) ์ธก๋ฉด์—์„œ ์ตœ์  ์šด์ „ ์กฐ๊ฑด๋“ค๊ณผ ๊ฐ„๊ฒฐ์„ฑ(Simplicity) ์ธก๋ฉด์—์„œ ์žฅ๋น„ ๋ชจ๋“ˆ ๋ฐฐ์น˜ ๊ฒฐ๊ณผ๊ฐ’๋“ค์„ ๊ทผ๊ฑฐ๋กœ ํšจ์œจ๊ณผ ๊ฐ„๊ฒฐ์ธก ์ธก๋ฉด์—์„œ Trade-offs ๋ฅผ ์ˆ˜ํ–‰ ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, Generic MR ์•กํ™” ์‚ฌ์ดํด๋กœ๋ถ€ํ„ฐ ์„ ์ •๋œ ์ž ์žฌ์  MR ์•กํ™” ์‚ฌ์ดํด์ด LNG FPSO ์šฉ ์ตœ์  ์•กํ™” ์‚ฌ์ดํด๋กœ ์„ ์ • ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ•ด์–‘ ๊ด€๋ จ ๊ฐ€์žฅ ์ตœ์‹  ๊ธฐ์ˆ ์ธ ์•กํ™” ๊ณต์ •์— ๋Œ€ํ•ด์„œ ์ง„ํ–‰ ํ•˜์˜€์œผ๋ฉฐ ์ด๋Š” ํ•ด์–‘ ๊ด€๋ จ ๋ชจ๋“  ์‹œ์Šคํ…œ๋“ค์—๋„ ์ ์šฉ ๊ฐ€๋Šฅํ•  ๊ฒƒ์ด๋ฉฐ ์ด๋ฅผ ํ†ตํ•ด์„œ ๊ฒฐ๊ตญ Topsides ์ „์ฒด ์‹œ์Šคํ…œ๋“ค์— ๋Œ€ํ•œ ์ตœ์ ํ™”๋œ ์ฐจ์ง€ํ•˜๋Š” ๋ฉด์ ๋“ค์„ ๊ตฌํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋จ์œผ๋กœ์จ ์ตœ์ข…์ ์œผ๋กœ ์ตœ์ ํ™”๋œ ๋ฐฐ์˜ ํฌ๊ธฐ๋ฅผ ๊ตฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.In this paper, the offshore selection criteria for the optimal liquefaction process system are studied to contribute to the future FEED engineering for the liquefied โ€“natural -gas (LNG) floating, production, storage, and offloading (LNG FPSO) liquefaction process system. From the foregoing, it is clear that offshore liquefaction plants have process requirements different from those of the traditional onshore liquefaction plants. While thermodynamic efficiency is the key technical process selection criterion for large onshore liquefaction plants, the high-efficiency pre-cooled mixed refrigerant and optimized cascade plants that dominate the onshore LNG installations are unlikely to meet the diverse technical and safety needs of offshore liquefaction facilities. Offshore liquefaction technology developers are rightly focusing on process simplicity, low weight, small footprint, and other criteria. The key criteria that influence process selection and plant optimization for the offshore liquefaction cycle lead to some trade-offs and compromises between efficiency and simplicity. In addition, other criteria for offshore liquefaction cycles should also be considered, such as flexibility, safety, vessel motion, refrigerant storage hazard, proven technology, simplicity of operation, ease of start-up/shutdown, and capital cost. First of all, this paper proposes a generic mixed refrigerant (MR) liquefaction cycle based on four configuration strategies. The 27 feasible MR liquefaction cycles from such generic MR liquefaction cycle are configured for optimal synthesis. From the 27 MR liquefaction cycles, the top 10 are selected based on the minimum amount of power required for the compressors. Then, one MR liquefaction cycle is selected based on simplicity among the 10 MR process cycles, and this is called a potential MR liquefaction cycle. Second, three additional offshore liquefaction cycles โ€” DMR for SHELL LNG FPSO, C3MR for onshore projects, and the dual N2 expander for FLEX LNG FPSO โ€” are considered for comparison with the potential MR liquefaction cycle for the selection of the optimal offshore liquefaction cycle. Such four cycles are compared based on simplicity, efficiency, and other criteria. Therefore, the optimal operating conditions for each cycle with four LNG capacities (4.0, 3.0, 2.0, and 1.0 MTPA) are calculated with the minimum amount of power required for the compressors. Then the preliminary equipment module layout for the four cycles are designed as multi-deck instead of single-deck, and this equipment module layout should be optimized to reduce the area occupied by the topside equipment at the FEED stage. In this paper, the connectivity cost, the construction cost proportional to the deck area, and the distance of the main cryogenic heat exchanger (MCHE) and separators from the centerline of the hull are considered objective functions to be minimized. Moreover, the constraints are proposed to ensure the safety and considering the deck penetration of the long equipment across several decks. Considering the above, mathematical models were formulated for them. For example, the potential MR liquefaction cycle has a mathematical model consisting of 257 unknowns, 193 equality constraints, and 330 inequality constraints. The preliminary optimal equipment module layouts with four LNG capacities (4.0, 3.0, 2.0, and 1.0 MTPA) are then obtained using mixed-integer nonlinear programming (MINLP). Based on the above optimal operating conditions and equipment module layouts for the four potential offshore liquefaction cycles, trade-offs between simplicity and efficiency are performed for actual offshore application, and finally, the potential MR liquefaction cycle is selected for the optimal liquefaction cycle for LNG FPSO.Abstract 1 1. Introduction 4 1.1. Motivation 4 1.2. LNG FPSO Topsides Process Systems 6 1.3. Key Technical Process Selection Criteria between Offshore and Onshore Natural Gas Liquefaction 10 2. Related Works 14 2.1. Offshore Front-End Engineering Design (FEED) 14 2.2. Optimal Operating Conditions 16 2.3. Optimal Synthesis 20 2.4. Optimal Layout 23 3. Offshore Process FEED for the Offshore Liquefaction Process System 27 3.1. Offshore and Onshore Engineering 27 3.2. Offshore Process FEED Engineering 28 3.3. Offshore Process FEED Engineering Method 32 4. Optimal Synthesis for Potential Offshore Liquefaction Process Cycles 42 4.1. Generic MR (Mixed Refrigerant) Liquefaction Process Cycle 42 4.1.1. Configuration of the liquefaction cycle 42 4.1.2. Generic MR (Mixed Refrigerant) liquefaction process cycle 53 4.2. Selection of Top 10 Feasible MR Liquefaction Process Cycles considering Efficiency 55 4.2.1. Feasible MR liquefaction process cycles 55 4.2.2. Optimal operating conditions of feasible MR liquefaction process cycles by HYSYS 57 4.2.3. Top 10 feasible MR liquefaction process cycles considering efficiency 87 4.3. Selection of Potential MR Liquefaction Cycle considering simplicity 88 4.4. Potential Offshore Liquefaction Cycles 90 4.5. Dermination of the Optimal Operating Conditions of the Potential Offshore Liquefaction Cycles Using HYSYS 93 4.6. Equipment Selection of the Potential Offshore Liquefaction Cycles 99 5. Optimal Equipment Module Layout for Potential Offshore Liquefaction Cycles 119 5.1. Introduction 119 5.2. Equipment Module Layout for Potential Offshore Liquefaction Cycles 120 5.2.1. Potential MR liquefaction cycle (case 14) 120 5.2.2. DMR cycle 133 5.2.3. C3MR cycle 143 5.2.4. Dual N2 expander cycle 155 5.3. Mathematical Models for the Optimal Equipment Module Layout for the Potential Offshore Liquefaction Cycles 162 5.3.1. Potential MR liquefaction cycle (case 14) 162 5.3.2. DMR cycle 178 5.3.3. C3MR cycle 195 5.3.4. Dual N2 expander cycle 212 5.4. Determination of the Optimal Equipment Module Layout for the Potential Offshore Liquefaction Cycles 225 5.4.1. Potential MR liquefaction cycle (case 14) 225 5.4.2. DMR cycle 244 5.4.3. C3MR cycle 265 5.4.4. Dual N2 expander cycle 285 5.5. Simplicity Analysis of the Preliminary Equipment Module Layouts 296 6. Offshore Trade-offs between Liquefaction Simplicity and Efficiency 299 6.1. Offshore Liquefaction Process Cycle Selection Criteria 299 6.2. Optimal Liquefaction Cycle for Actual Offshore Application 304 7. Conclusions 305 References 308 ๊ตญ๋ฌธ ์ดˆ๋ก 314 ํ›„๊ธฐ 318Docto

    ๋ฌผ๋ฆฌ์  ํฌ๊ธฐ ํŒ๋‹จ ๊ณผ์ œ์—์„œ ์ˆซ์ž๊ฐ’์ด ๋ฏธ์น˜๋Š” ์˜ํ–ฅ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ์‹ฌ๋ฆฌํ•™๊ณผ, 2017. 8. ์˜ค์„ฑ์ฃผ.In the fields of the numerical Stroop-like tasks, it has been known that the conceptual magnitude of numbers influences the size comparison process (Henik & Tzelgov, 1982Tzelgov, Meyer, & Henik, 1992). When the physical size of a larger number is bigger than that of a smaller number, it is a congruent condition. In contrast, the physical size of a larger number is smaller than that of a smaller number, it is an incongruent condition. Two distinguished information of numbers, the numerical value and the physical size, interact during the number comparison task, which triggers the different performance of reaction time and accuracy between the congruent and the incongruent conditions. Researchers have been mainly focused on response time and accuracy to verify the size coincidence effect. Accordingly, it is still unidentified whether the effect reflects the perceptual results during the comparison process, or simply the cognitive bias in the response stage. The purpose of this paper is to identify the effect of numerical value when people compare the physical size of numbers. The main hypothesis was that a number with a bigger value looks physically larger than a number with a smaller value. We measured the perceived size of Arabic numbers depending on the conceptual magnitude by applying the Ebbinghaus paradigm which is known to enhance the size contrast induced by the conceptual meaning of the displayed stimuli. Each stimulus consisted of a central number and six surrounding numbers. Participants were asked to respond to whether or not the target number looked smaller or larger than the inducers. As Dixon (2008) suggested the Generalized Linear Mixed Model to the repeated measures design with binary responses, we test the results with the GLMM model putting a random effect on each subject variation. Furthermore, the points of subjective equality (PSE) were calculated from binary responses on the perceptual decision as being smaller or larger. The analysis showed that participants were more likely to perceive the physical size of the target number as being smaller when surrounded by numerically larger inducers, vice versa. In study 1, we tested this perceptual effect by the influence of magnitude with two sets of font size conditions. Furthermore, we found the similar pattern on both the upright and inverted number conditions by rotating the number stimuli in study 2. In study 3, the expected result was partially observed in the range of 3 to 7 of the inducers. These results indicate that the conceptual magnitude of numbers influences the perceived size of numbers during the number comparison process.Introduction 1 1. The size congruity effect 1 2. The autonomic processing of numbers 3 3. The shared representation versus the shared decision 5 4. The Ebbinghaus illusion effect 8 5. The present study 10 Experiment 1 18 Experiment 2 38 Experiment 3 51 General Discussions 61 Appendix 77 References 81 Abstract in Korean 86Maste

    ์œ„์•”์—์„œ olaparib ๊ฐ์ˆ˜์„ฑ ์˜ˆ์ธก ์ธ์ž๋กœ์จ DNA ์†์ƒ ๋ณต๊ตฌ ์œ ์ „์ž ๋ณ€์ด์™€ ํ˜„๋ฏธ๋ถ€์ˆ˜์ฒด ๋ถˆ์•ˆ์ •์„ฑ ๋ฐ ์ข…์–‘๋ณ€์ด๋ถ€๋‹ด์— ๋Œ€ํ•œ ํ‰๊ฐ€

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    ์•”์˜ ๋งŽ์€ ์›์ธ ์ค‘ ํ•˜๋‚˜์ธ DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ์˜ ๊ธฐ๋Šฅ ์žฅ์• ์ด๋‹ค. ๋Œ์—ฐ๋ณ€์ด, ๋ฉ”ํ‹ธํ™” ๋˜๋Š” ๊ธฐํƒ€ ์ด์œ ๋กœ ์ธํ•ด ์ƒ๋™์„ฑ ์žฌ์กฐํ•ฉ ๊ธฐ๋Šฅ์— ๊ฒฐํ•์ด ์žˆ๋Š” ์•”์€ PARP ์–ต์ œ์ œ์˜ ๊ฐ์ˆ˜์„ฑ๊ณผ ์œ ์ „์ฒด ๋ถˆ์•ˆ์ •์„ฑ์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋˜ํ•œ, DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ์— ๊ฒฐํ•์ด ์žˆ๋Š” ์•” ์—ญ์‹œ ๋น„์Šทํ•œ ํŠน์ง•์„ ๊ฐ–๋Š” ๊ฒƒ์œผ๋กœ ๋ณด๊ณ ๋˜๊ณ  ์žˆ๋‹ค. ๊ฒŒ๋‹ค๊ฐ€, ์ผ๋ถ€ ์—ฐ๊ตฌ์—์„œ๋Š” ํ˜„๋ฏธ๋ถ€์ˆ˜์ฒด ๋ถˆ์•ˆ์ •์„ฑ์ด ๋†’๊ฑฐ๋‚˜ ์ข…์–‘ ๋ณ€์ด๋ถ€๋‹ด์ด ๋†’์€ ์•”๊ณผ ๊ฐ™์ด ๋Œ์—ฐ๋ณ€์ด๊ฐ€ ๋งŽ์€ ์•”์˜ ๊ฒฝ์šฐ DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ ๊ธฐ๋Šฅ์— ๊ฒฐํ•์ด ์žˆ์„ ํ™•๋ฅ ์ด ๋†’๋‹ค. ๊ทธ๋Ÿผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ์—ฌ์ „ํžˆ olaparib ๊ฐ์ˆ˜์„ฑ ์˜ˆ์ธก ์ธ์ž๋กœ์„œ ์ฃผ์š” ์ƒ๋™์„ฑ ์žฌ์กฐํ•ฉ ๊ธฐ๋Šฅ ๊ด€๋ จ ์œ ์ „์ž ๋Œ์—ฐ๋ณ€์ด์—๋งŒ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ฃผ์š” ์ƒ๋™์„ฑ ์žฌ์กฐํ•ฉ ๊ธฐ๋Šฅ ๊ด€๋ จ ์œ ์ „์ž๋ฟ๋งŒ ์•„๋‹ˆ๋ผ DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ ๊ด€๋ จ ์œ ์ „์ž ๋Œ์—ฐ๋ณ€์ด ๋ฐ ์œ ์ „์ฒด ๋ถˆ์•ˆ์ •์„ฑ ์˜ˆ์ธก ์ธ์ž์™€ 49๊ฐœ ์œ„์•” ์„ธํฌ์ฃผ์—์„œ olaparib ๊ฐ์ˆ˜์„ฑ๊ณผ์˜ ์—ฐ๊ด€์„ฑ์„ ํ™•์ธํ•œ๋‹ค. Olaparib์˜ ํšจ๋Šฅ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ์„ธํฌ์ฃผ๋ฅผ olaparib์œผ๋กœ 5์ผ๊ฐ„ ์ฒ˜๋ฆฌํ•œ ํ›„ CCK-8 ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. IC50์€ CalcuSyn ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ํ†ตํ•ด ๊ณ„์‚ฐ๋˜์—ˆ์œผ๋ฉฐ, ์„ธํฌ์ฃผ๋Š” IC50์ด 10ฮผM ๋ฏธ๋งŒ์ด๋ฉฐ 10ฮผM์—์„œ ์–ต์ œ์œจ์ด 50% ์ด์ƒ์ผ ๋•Œ olaparib์— ๋ฏผ๊ฐํ•˜๋‹ค๊ณ  ๋ถ„๋ฅ˜๋œ๋‹ค. ๊ทธ๋Ÿฐ ๋‹ค์Œ, ํ‘œ์  ์‹œํ€€์‹ฑ์„ ์ด์šฉํ•˜์—ฌ 49๊ฐœ์˜ DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ ๊ด€๋ จ ์œ ์ „์ž, ํ˜„๋ฏธ๋ถ€์ˆ˜์ฒด ๋ถˆ์•ˆ์ •์„ฑ ์ƒํƒœ ๋ฐ ์ข…์–‘ ๋ณ€์ด๋ถ€๋‹ด์„ ํ™•์ธํ–ˆ๋‹ค. BRCA1, RAD51C ๋ฐ MLH1 ๋ฉ”ํ‹ธํ™”๋Š” bisulfite ์‹œํ€€์‹ฑ์— ์˜ํ•ด ํ™•์ธํ–ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, 20๊ฐœ์˜ ์„ธํฌ์ฃผ์—์„œ 16๊ฐœ์˜ DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ ๊ด€๋ จ ์œ ์ „์ž์—์„œ ๋Œ์—ฐ๋ณ€์ด๊ฐ€ ์žˆ์Œ์„ ํ™•์ธํ–ˆ๋‹ค. ์ „์ฒด ์„ธํฌ์ฃผ ์ค‘ 12 ๊ฐœ์˜ ์„ธํฌ์ฃผ๋Š” olaparib์— ๊ฐ์ˆ˜์„ฑ์ด ๋†’์•˜๊ณ , DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ ์œ ์ „์ž์˜ ๋ณ€์ด๊ตฐ์€ olaparib์— ๋” ๋ฏผ๊ฐํ–ˆ๋‹ค (p = 0.034). ๊ตฌ์ฒด์ ์œผ๋กœ ์ƒ๋™์„ฑ ์žฌ์กฐํ•ฉ ๊ธฐ๋Šฅ๊ณผ DNA ๋ถˆ์ผ์น˜ ๋ณต๊ตฌ ๊ธฐ๋Šฅ์—๋ณ€์ด๊ฐ€ ์žˆ๋Š” ์„ธํฌ์ฃผ๋Š” ์•ผ์ƒ๊ตฐ์— ๋น„ํ•ด olaparib์— ๋ฏผ๊ฐํ–ˆ๋‹ค (p = 0.005, p = 0.018). ํฅ๋ฏธ๋กญ๊ฒŒ๋„ ๋น„์ƒ๋™๋ง๋‹จ์—ฐ๊ฒฐ ๊ธฐ๋Šฅ ์œ ์ „์ž์— ๋ณ€์ด๋Š” olaparib ๋ฏผ๊ฐ์„ฑ์— ํฐ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€ ์•Š์•˜๋‹ค. ์ข…์–‘๋ณ€์ด๋ถ€๋‹ด์€ ์„ธํฌ์ฃผ (๋ฒ”์œ„ = 1.45 ~ 61.03, ์ค‘์•™๊ฐ’ = 8.70)์— ๋ถ„ํฌ๋˜์–ด ์žˆ๋‹ค. ํฅ๋ฏธ๋กญ๊ฒŒ๋„, olaparib ๊ฐ์ˆ˜์„ฑ ๊ทธ๋ฃน์€ ์ €ํ•ญ์„ฑ ๊ทธ๋ฃน๋ณด๋‹ค TMB๊ฐ€ ๋” ๋†’์•˜๋‹ค (์ค‘์•™๊ฐ’ = 15.3 ๋Œ€ 10.9, p <0.0001). 4 ๊ฐœ์˜ ์„ธํฌ์ฃผ (SNU-1, SNU-638, IM95m, NUGC-3)๋Š” ํ˜„๋ฏธ๋ถ€์ˆ˜์ฒด ๋ถˆ์•ˆ์ •์„ฑ์„ ๋ณด์˜€์œผ๋ฉฐ ๋ชจ๋‘ MLH1 ๋‹จ๋ฐฑ์งˆ ๋ฐœํ˜„์ด ์—†์—ˆ๋‹ค. ํ˜„๋ฏธ๋ถ€์ˆ˜์ฒด ๋ถˆ์•ˆ์ •์„ฑ ์„ธํฌ์ฃผ๋Š” ๋‹ค๋ฅธ ์„ธํฌ์ฃผ๋ณด๋‹ค ์ƒ๋‹นํžˆ ๋†’์€ ์ข…์–‘ ๋ณ€์ด๋ถ€๋‹ด์„ ๊ฐ€์กŒ๋‹ค (์ค‘์•™๊ฐ’ : 47.96 ๋Œ€ 8.72, p <0.0001). 3 ๊ฐœ์˜ ํ˜„๋ฏธ๋ถ€์ˆ˜์ฒด ๋ถˆ์•ˆ์ •์„ฑ ์„ธํฌ์ฃผ๋Š” olaparib์— ๋ฏผ๊ฐํ•˜์˜€์œผ๋‚˜ ํ˜„๋ฏธ๋ถ€์ˆ˜์ฒด ๋ถˆ์•ˆ์ •์„ฑ ์„ธํฌ์ฃผ ์ค‘ ์ข…์–‘ ๋ณ€์ด๋ถ€๋‹ด์ด ๊ฐ€์žฅ ๋‚ฎ์€ NUGC-3 (29.07)์€ ๋‚ด์„ฑ์ด ์žˆ์—ˆ๋‹ค. ๊ฐ ์š”์ธ์˜ ์ค‘์š”์„ฑ๊ณผ ์˜ฌ๋ผ ํŒŒ๋ฆฝ ๊ฐ์ˆ˜์„ฑ ์˜ˆ์ธก ๋Šฅ๋ ฅ์„ ๋ถ„์„ ํ•œ ๊ฒฐ๊ณผ, ์ฃผ์š” ์ƒ๋™์„ฑ ์žฌ์กฐํ•ฉ ๊ธฐ๋Šฅ ๋ฐ ๋น„์ƒ๋™๋ง๋‹จ์—ฐ๊ฒฐ์„ ์ œ์™ธํ•œ DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ ๋ณ€์ด๊ฐ€ ๋น„์Šทํ•˜๊ฒŒ ์ค‘์š”ํ–ˆ์œผ๋ฉฐ (2.53 ๋Œ€ 2.48), ๋น„์ƒ๋™๋ง๋‹จ์—ฐ๊ฒฐ์„ ์ œ์™ธํ•œ DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ ๋ณ€์ด๊ฐ€ olaparib ๋ฏผ๊ฐ์„ฑ์„ ๊ฐ€์žฅ ์ •ํ™•ํžˆ ์˜ˆ์ธกํ–ˆ๋‹ค. ์šฐ๋ฆฌ ์—ฐ๊ตฌ๋Š” olaparib ๋ฏผ๊ฐ์„ฑ์„ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•ด ์ฃผ์š” ์ƒ๋™์„ฑ ์žฌ์กฐํ•ฉ ๊ธฐ๋Šฅ๋ณ€์ด๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‚˜์•„๊ฐ€ DNA ์†์ƒ ๋ณต๊ตฌ ๊ฒฝ๋กœ ๊ด€์—ฐ ์œ ์ „์ž ๋ณ€์ด ์—ญ์‹œ ํ™•์ธํ•ด์•ผํ•œ๋‹ค๊ณ  ์ œ์•ˆํ•œ๋‹ค. One of the many factors that causes cancer is a dysfunction of the DNA damage response pathway (DDR). Cancers with homologous recombination (HR) deficiency due to mutation, methylation, or other reasons, are known to be increased the sensitivity of PARP inhibitors and genomic instability. Besides, DDR, like mismatch repair (MMR), deficiency cancers have been recently reported to have similar features. Furthermore, some studies suggested that many of hypermutated cancers, such as microsatellite instability-high (MSI-H) or high tumor mutational burden (TMB) are DDR deficient. Nevertheless, many studies still have focused on HR-related gene mutations as a predictor of olaparib. Here, we aim to determine whether the DDR gene alterations and genomic instability markers can predict olaparib efficacy in 49 gastric cancer cell lines. We profiled the genomic status of selected DDR genes, MSI status, and TMB using targeted sequencing. BRCA1, RAD51C, and MLH1 methylation were detected by bisulfite sequencing. We separated cell lines as an altered group when it had the truncated mutation, homozygous deletion, or methylation of more than 40% in those genes. RAD51C and MMR-related protein expression was determined by western blot. Then, to determine the efficacy of olaparib, cells were treated with olaparib for 5 days and assessed using CCK-8 assay. Cell lines were classified as a sensitive group when it had less than 10 ยตM of IC50 and more than 50% of inhibition rate at 10ยตM. As a result, twenty of 49 cell lines had the alteration in one or more of the 16 DDR-related genes. In our cell line panel, twelve cell lines were sensitive to olaparib, and DDR without NHEJ altered group was more sensitive to olaparib than the wild type group (p = 0.004). In detail, cell lines with alterations in the HR and MMR subpathways were significantly sensitive among the subtype of DDR pathways respectively, p = 0.005 and p = 0.018. TMB level was widely distributed among the GC cell lines (range = 1.45 to 61.03, median = 8.70), and the DDR altered without NHEJ group had higher TMB than wild type group (p = 0.021). Four cell lines (SNU-1, SNU-638, IM95m, and NUGC-3) were MSI-H, and all of them were no MLH1 protein expression. MSI-H cell lines had significantly higher TMB than other cell lines (median : 47.96 vs 8.72, p < 0.0001). Three MSI-H cell lines were sensitive to olaparib, but NUGC-3 with the lowest TMB (29.07mt/mb) among MSI-H cell lines was resistant. As a result of analyzing the importance and olaparib sensitivity predictive ability of each factor, core HR alteration and DDR alteration excluding NHEJ were similarly important (2.53 vs 2.48), and the area under the curve (AUC) was the largest for DDR alteration excluding NHEJ. In our result, the olaparib sensitive group had the alteration in DDR genes and high TMB. MSI-H cell lines were sensitive to olaparib when it had high TMB. When we analyzed single factors and combined scores, the predictive ability of olaparib sensitivity was better with DDR alteration excluding NHEJ. For accurate predictions that are sensitive to olaparib, our data suggest that it is necessary to analysis DDR alteration by extending core HR alteration.open์„

    ํŒจ์…˜์ƒํ’ˆํ‰๊ฐ€์— ๋Œ€ํ•œ ๋‹ค์ค‘์›์‚ฐ์ง€ ํšจ๊ณผ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜๋ฅ˜ํ•™๊ณผ,2008.2.Maste

    High-efficiency klystron design with multi-cell output cavity

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    Doctor๋Œ€๊ทœ๋ชจ ๊ณผํ•™์‹œ์„ค์ด ๊ฐœ๋ฐœ๋จ์— ๋”ฐ๋ผ ํด๋ผ์ด์ŠคํŠธ๋ก ์˜ ํšจ์œจ์€ ์ดˆ๊ธฐ ์„ค๋ฆฝ ๋น„์šฉ ๋ฐ ์šด์˜ ๋น„์šฉ์„ ์ ˆ๊ฐํ•˜๋Š” ์ค‘์š”ํ•œ ๋ฌธ์ œ๊ฐ€ ๋ฉ๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ธฐ์กด์˜ ํด๋ผ์ด์ŠคํŠธ๋ก  ํšจ์œจ์„ฑ์„ ๋†’์ด๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๋…ธ๋ ฅ์ด ์ง„ํ–‰ ์ค‘์ž…๋‹ˆ๋‹ค. ๊ทธ ์ค‘ ํฌํ•ญ๊ฐ€์†๊ธฐ์—ฐ๊ตฌ์†Œ์—์„œ 40%์˜ ํšจ์œจ๋กœ ์‚ฌ์šฉ๋˜๋Š” S-band 80-MW ํด๋ผ์ด์ŠคํŠธ๋ก ๊ณผ ๊ฐ™์ด ๋†’์€ ํผ๋น„์–ธ์Šค ๋น”์„ ์‚ฌ์šฉํ•˜๋Š” ํด๋ผ์ด์ŠคํŠธ๋ก  ํšจ์œจ์„ ๋†’์ด๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€์Šต๋‹ˆ๋‹ค. ๋‹ค์ค‘ ์…€ ์ถœ๋ ฅ ๊ณต๋™ ๊ฐœ๋…์„ ์—ฐ๊ตฌ์— ์ ์šฉํ–ˆ๊ณ  ๋‹ค์ค‘ ์…€ ์ถœ๋ ฅ ๊ณต๋™์˜ ์„ค๊ณ„ ๋งค๊ฐœ ๋ณ€์ˆ˜์ธ ์…€ ์ฃผํŒŒ์ˆ˜, ์…€ ๊ฐ„ ๊ฑฐ๋ฆฌ, ์…€ ๊ฐ„ ์ปคํ”Œ๋ง ๋ฐ ๋งˆ์ง€๋ง‰ ์…€์˜ ๋กœ๋“œ Q๋ฅผ ์ตœ์ ํ™”ํ•˜์—ฌ ์ตœ๋Œ€ 60%์˜ ํšจ์œจ์„ ๋‹ฌ์„ฑํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด 2-D PIC ์ฝ”๋“œ์ธ FCI๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋‹ค์ค‘ ์…€ ์ถœ๋ ฅ ๊ณต๋™์˜ ์„ค๊ณ„ ๋งค๊ฐœ ๋ณ€์ˆ˜๋ฅผ ์ตœ์ ํ™”ํ•˜์˜€๊ณ  ์‹ค์ œ ๊ณต๋™ ๊ตฌ์กฐ๋Š” 3-D ์ฝ”๋“œ์ธ CST์˜ MWS์™€ PIC๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์„ค๊ณ„ํ•˜์˜€์Šต๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋‹ค์ค‘ ์…€ ์ถœ๋ ฅ ๊ณต๋™์˜ ์ „๋ ฅ ๋ณ€ํ™˜ ํ”„๋กœ์„ธ์Šค๋ฅผ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ์–ป์€ ์ž…์ž ์šด๋™ ๋ฐ ์ „์ž๊ธฐ์žฅ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„ํ•˜์—ฌ ์ตœ์ ํ™”ํ•˜์˜€์Šต๋‹ˆ๋‹ค.As large-scale scientific facilities develop, klystron efficiency becomes an important issue to reduce high operating costs. Various efforts are in progress in order to enhance the efficiency of existing klystrons. We designed high-perveance (~2 ฮผP) klystrons with much improved power-conversion efficiency for the S-band 80-MW klystrons used at the Pohang Accelerator Laboratory (PAL) having 40% efficiency. The multi-cell output cavity concept was adapted for the study. Efficiency as high as 60% was achieved by full optimization of the design parameters, such as cell frequencies, cell-to-cell distances, coupling between cells, and the loaded Q of the last cell, in the multi-cell output cavity. Simulation of the beam-dynamics was performed using the field charge interaction (FCI) code with a MATALB script to find the design parameters that maximize efficiency. The multi-cell output structure, on the other hand, was designed using Microwave Studio (MWS) in Computer Simulation Technology (CST) based on the FCI results. Finally, the verification of the multi-cell output cavity design was performed using the Particle-in-Cell (PIC) solver in CST, resulting in 56% efficiency. The power conversion process was optimized by analyzing particle motions and electromagnetic field data generated from the FCI and CST-PIC codes
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