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    Application to 3D seismic data

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์—๋„ˆ์ง€์‹œ์Šคํ…œ๊ณตํ•™๋ถ€, 2023. 2. ๋ฏผ๋™์ฃผ.์ •๋Ÿ‰์  ๊ณ ํ•ด์ƒ๋„ ์ง€ํ•˜ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•˜๊ธฐ ์œ„ํ•œ ์ž๋ฃŒ ์ ํ•ฉ ์ ‘๊ทผ ๋ฐฉ์‹์ธ ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ(full waveform inversion; FWI)์€ ๊ด‘๋Œ€์—ญ/๊ด‘๊ฐ ํƒ„์„ฑํŒŒ ์ž๋ฃŒ๋ฅผ ๋‹ค๋ฃจ๊ธฐ ์œ„ํ•ด ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๋Š” ์ˆ˜๋‹จ๋“ค ์ค‘ ํ•˜๋‚˜๊ฐ€ ๋˜์—ˆ๋‹ค. ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ์€ ํƒ„์„ฑํŒŒ ์ž๋ฃŒ์— ํฌํ•จ๋œ ์ „์ฒด ํŒŒ๋™์˜ ์šด๋™ํ•™์ โˆ™๋™์—ญํ•™์  ์„ฑ์งˆ์„ ํ•จ๊ป˜ ๊ณ ๋ คํ•˜๊ฒŒ ๋˜๋Š”๋ฐ, ์ด๋Š” ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ์„ ๋งค์šฐ ๋น„์„ ํ˜•์ ์œผ๋กœ ๋งŒ๋“ค๊ฒŒ ๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ์€ ์„ ํ˜• ๊ตญ๋ถ€ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ดˆ๊ธฐ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์ด ๋ถ€์ •ํ™•ํ•  ๊ฒฝ์šฐ ๊ตญ๋ถ€ ์ตœ์†Ÿ๊ฐ’์— ๋น ์ง€๊ฒŒ ๋œ๋‹ค. ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ์˜ ๋น„์„ ํ˜•์„ฑ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์šฐ์„ ์ ์œผ๋กœ ์žฅํŒŒ์žฅ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•œ ๋’ค, ์ˆœ์ฐจ์ ์œผ๋กœ ๋‹จํŒŒ์žฅ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ์„ ๋ณต์›ํ•˜๋Š” ๊ณผ์ •์ด ํ•„์š”ํ•˜๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ์˜ ์ดˆ๊ธฐ ๋‹จ๊ณ„์—์„œ ๋ฐ˜์‚ฌํŒŒ์— ์˜ํ•œ ์žฅํŒŒ์žฅ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ์˜ ๊ฐฑ์‹ ์€ ๊ฑฐ์˜ ๋ฐœ์ƒํ•˜์ง€ ์•Š์œผ๋ฉฐ, ๋ฐ˜์‚ฌํŒŒ๋Š” ๋‹จํŒŒ์žฅ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ๋งŒ์„ ๊ฐฑ์‹ ํ•˜๊ฒŒ ๋œ๋‹ค. ๋”ฐ๋ผ์„œ ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ ์ด๋ผ๋Š” ๋ช…์นญ๊ณผ๋Š” ๋‹ฌ๋ฆฌ, ๊ธฐ์กด ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ์€ ์ฃผ๋กœ ๋‹ค์ด๋น™ํŒŒ์— ์˜์กดํ•˜์—ฌ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•˜๋ฉฐ ๋ฐ˜์‚ฌํŒŒ์˜ ์ฃผ์‹œ ์ •๋ณด๋Š” ์—ญ์‚ฐ ๊ณผ์ •์—์„œ ๊ฑฐ์˜ ๋ฐ˜์˜๋˜์ง€ ์•Š๋Š”๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ ๋ฐ˜์‚ฌํŒŒ๋ฅผ ํ™œ์šฉํ•ด ์ดˆ๊ธฐ ์—ญ์‚ฐ๋‹จ๊ณ„์—์„œ ์žฅํŒŒ์žฅ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ๊ฐฑ์‹ ํ•˜๊ธฐ ์œ„ํ•ด์„œ, ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ๊ณผ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ๋กœ ๋ถ„๋ฆฌํ•˜์—ฌ ์—ญ์‚ฐ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ˜์‚ฌํŒŒ ํŒŒํ˜•์—ญ์‚ฐ์ด ์ œ์‹œ๋˜์—ˆ๋‹ค. ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ์„ ์ง์ ‘์ ์œผ๋กœ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ, ๋ฐ˜์‚ฌํŒŒ์˜ ํŒŒ๋™๊ฒฝ๋กœ๋ฅผ ๋”ฐ๋ผ ์ถ”๊ฐ€์ ์œผ๋กœ ์žฅํŒŒ์žฅ ์†๋„๊ตฌ์กฐ๋ฅผ ๊ฐฑ์‹ ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋œ๋‹ค. ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ์€ ์ƒˆ๋กญ๊ฒŒ ๊ฐฑ์‹ ๋œ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์— ๋Œ€ํ•ด ๋ฐ˜๋ณต์ ์œผ๋กœ ๊ตฌ์ถ•๋˜์–ด์•ผ ํ•˜๋ฉฐ, ์ด๋Ÿฌํ•œ ์ผ๋ จ์˜ ๊ณผ์ •์„ ํ†ตํ•ด ์žฅํŒŒ์žฅ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ๊ณผ ๋‹จํŒŒ์žฅ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ์ด ๋ฒˆ๊ฐˆ์•„๊ฐ€๋ฉฐ ์—ญ์‚ฐ๋œ๋‹ค. ์ด๋ฅผ ํฐ ๊ทœ๋ชจ์˜ ์‹ค์ œ ํƒ์‚ฌ ์ž๋ฃŒ์— ์ ์šฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ์žฅํŒŒ์žฅ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ๊ณผ ๋‹จํŒŒ์žฅ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ๋กœ ๋ถ„๋ฆฌํ•˜๊ธฐ ์œ„ํ•œ ๊ณ„์‚ฐํšจ์œจ์ ์ธ ๋ฐฉ๋ฒ•์ด ํ•„์š”ํ•˜๋‹ค. ๋˜ํ•œ, ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ๋ฅผ ๊ตฌ์ถ•ํ•˜๋Š” ๊ณผ์ •์—์„œ ๋‹ค์ด๋น™ํŒŒ์™€ ๋ฐ˜์‚ฌํŒŒ์— ์˜ํ•œ ์ •๋ณด๊ฐ€ ํ•จ๊ป˜ ํšจ์œจ์ ์œผ๋กœ ๊ณ ๋ ค๋˜์–ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋จผ์ € ํƒ„์„ฑํŒŒ ๋ฐ˜์‚ฌ๋ฒ•ํƒ์‚ฌ์—์„œ ํƒ„์„ฑํŒŒ ์ž๋ฃŒ์— ํฌํ•จ๋œ ๋‹ค์ด๋น™ํŒŒ์™€ ๋ฐ˜์‚ฌํŒŒ๊ฐ€ ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ ๊ทธ๋ž˜๋””์–ธํŠธ์˜ ํŒŒ์žฅ ์„ฑ๋ถ„์— ์–ด๋–ป๊ฒŒ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ๋ถ„์„ํ•œ๋‹ค. ๊ทธ ํ›„, ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ ๊ทธ๋ž˜๋””์–ธํŠธ์˜ ํŒŒ์žฅ ์„ฑ๋ถ„์„ ์กฐ์ ˆํ•˜๊ธฐ ์œ„ํ•ด ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง ๊ธฐ๋ฒ•์„ ๋„์ž…ํ•˜๊ณ , 5๊ฐœ์˜ ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง ๋ชจ๋“œ๋กœ ์ธํ•ด ๋‹ค์ด๋น™ํŒŒ์™€ ๋ฐ˜์‚ฌํŒŒ๊ฐ€ ๊ทธ๋ž˜๋””์–ธํŠธ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์ด ์–ด๋–ป๊ฒŒ ๋ณ€ํ™”ํ•˜๋Š”์ง€ ์‚ดํŽด๋ณธ๋‹ค. ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ ๊ทธ๋ž˜๋””์–ธํŠธ์™€ ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง ๊ธฐ๋ฒ•์— ๋Œ€ํ•œ ๋ถ„์„์„ ๊ธฐ๋ฐ˜์œผ๋กœ, ๋‹ค์ด๋น™ํŒŒ์™€ ๋ฐ˜์‚ฌํŒŒ๋ฅผ ํ•จ๊ป˜ ํ™œ์šฉํ•˜์—ฌ ์‹ ๋ขฐํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ๋ฅผ ๊ตฌ์ถ•ํ•  ์ˆ˜ ์žˆ๋Š” ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง ๊ธฐ๋ฐ˜ ์ค‘์ฒฉ ์•Œ๊ณ ๋ฆฌ๋“ฌ์„ ์‚ฌ์šฉํ•œ ์Œํ–ฅํŒŒ ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ ๊ธฐ์ˆ ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์•Œ๊ณ ๋ฆฌ๋“ฌ์ƒ์—์„œ, ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง์€ ๋ฐ˜์‚ฌํŒŒ ํŒŒํ˜•์—ญ์‚ฐ๊ณผ ๊ฐ™์ด ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ๊ณผ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ๋กœ ๋ถ„๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ์šฉ๋œ๋‹ค. ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง์€ ํฐ ์—ฐ์‚ฐ๋Ÿ‰์˜ ์ฆ๊ฐ€ ์—†์ด ๊ณ„์‚ฐํšจ์œจ์ ์œผ๋กœ ๊ตฌํ˜„๋  ์ˆ˜ ์žˆ์œผ๋ฉฐ, 3์ฐจ์› ํƒ„์„ฑํŒŒ ํƒ์‚ฌ ์ž๋ฃŒ์™€ ๊ฐ™์€ ํฐ ๊ทœ๋ชจ์˜ ํƒ์‚ฌ ์ž๋ฃŒ์— ๋Œ€ํ•ด์„œ๋„ ์•Œ๊ณ ๋ฆฌ๋“ฌ์„ ์ ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•ด์ค€๋‹ค. 5๊ฐœ์˜ ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง ๋ชจ๋“œ ์ค‘, ๋ชจ๋“œ IV์™€ V๊ฐ€ ๊ฐ๊ฐ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ๊ณผ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ์„ ๊ฐฑ์‹ ํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ์šฉ๋œ๋‹ค. ๋ชจ๋“œ V๋ฅผ ํ†ตํ•ด ๊ตฌ์ถ•๋œ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ์€ ๋ฐ˜์‚ฌํŒŒ ํŒŒ๋™๊ฒฝ๋กœ๋ฅผ ๋”ฐ๋ผ ์ถ”๊ฐ€์ ์ธ ์žฅํŒŒ์žฅ ์†๋„๊ตฌ์กฐ ๊ฐฑ์‹ ์„ ๋ฐœ์ƒ์‹œํ‚จ๋‹ค. ๋ชจ๋“œ IV๋Š” ์ง์ ‘์ ์œผ๋กœ ๋‹ค์ด๋น™ํŒŒ์™€ ๋ฐ˜์‚ฌํŒŒ์˜ ํŒŒ๋™๊ฒฝ๋กœ๋ฅผ ๋”ฐ๋ผ ๋ฐœ์ƒํ•˜๋Š” ์žฅํŒŒ์žฅ ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ ๊ทธ๋ž˜๋””์–ธํŠธ ์„ฑ๋ถ„์„ ์ถ”์ถœํ•˜์—ฌ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๊ตฌ์ถ•์— ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ฐœ์„ ๋œ ์žฅํŒŒ์žฅ ์†๋„๊ตฌ์กฐ ๊ฐฑ์‹  ๋ฒ”์œ„๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ด€์ธก ๋‹ค์ด๋น™ํŒŒ์™€ ๋ฐ˜์‚ฌํŒŒ์˜ ์ฃผ์‹œ ์ •๋ณด๋ฅผ ๋” ์ •ํ™•ํžˆ ๋ฌ˜์‚ฌํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ๋ฅผ ๊ตฌ์ถ•ํ•  ์ˆ˜ ์žˆ๋‹ค. 3์ฐจ์› SEG/EAGE ์˜ค๋ฒ„์Šค๋Ÿฌ์ŠคํŠธ ๋ชจ๋ธ์„ ์ด์šฉํ•ด ๋งŒ๋“  ํ•ฉ์„ฑ ์ž๋ฃŒ ๋ฐ ๋ถํ•ด ๋ณผ๋ธŒ(Volve) ์ง€์—ญ์˜ 3์ฐจ์› ํ•ด์ €์ผ€์ด๋ธ”(ocean-bottom cable) ์ž๋ฃŒ์— ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง ๊ธฐ๋ฐ˜ ์ค‘์ฒฉ ์•Œ๊ณ ๋ฆฌ๋“ฌ์„ ์ ์šฉํ•ด๋ด„์œผ๋กœ์จ ์ง€ํ•˜๊ตฌ์กฐ๊ฐ€ ๋งค์šฐ ๋ณต์žกํ•˜๊ฑฐ๋‚˜, ํƒ„์„ฑํŒŒ ์ž๋ฃŒ์— ํƒ„์„ฑ ๋ฐ ์ด๋ฐฉ์„ฑ ํšจ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚˜๋Š” ๊ฒฝ์šฐ์— ๋Œ€ํ•ด์„œ๋„ ์•Œ๊ณ ๋ฆฌ๋“ฌ์ด ์‹ ๋ขฐํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ํšŒ์ ˆ๊ฐ ํ•„ํ„ฐ๋ง์˜ ๋ชจ๋“œ IV์™€ ๋ชจ๋“œ V๋ฅผ ํ†ตํ•ด ์„ฑ๊ณต์ ์œผ๋กœ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์„ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ๊ณผ ๋ฐ˜์‚ฌ์ธต๊ตฌ์กฐ ๋ชจ๋ธ๋กœ ๋ถ„๋ฆฌํ•  ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ตฌ์ถ•๋œ ๋ฐฐ๊ฒฝ ์†๋„๊ตฌ์กฐ ๋ชจ๋ธ์€ ๋” ์ •ํ™•ํ•œ ๊ณ ํ•ด์ƒ๋„ ์†๋„๊ตฌ์กฐ๋ฅผ ๊ตฌ์ถ•ํ•˜๊ธฐ ์œ„ํ•œ ์ฐจํ›„ ์Œํ–ฅํŒŒ ๋ฐ ํƒ„์„ฑํŒŒ ์™„์ „ํŒŒํ˜•์—ญ์‚ฐ์„ ์œ„ํ•œ ์ดˆ๊ธฐ ์†๋„๋ชจ๋ธ๋กœ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.Full waveform inversion (FWI), which is a data-fitting approach that aims at building quantitative high-resolution subsurface velocity models, becomes one of the most popular tools to image wide-aperture and broadband seismic data. Considering both the kinematic and dynamic properties of all waves in seismic data makes FWI highly non-linear. However, because FWI is solved in the linearized local optimization framework, it often falls into local minima when initial models deviate from true models. To mitigate its non-linearity, one can preferentially reconstruct low-wavenumber macro velocity structures and then gradually recover higher-wavenumber reflectivity structures. However, in the early stage of conventional FWI, short-spread reflection data hardly contribute to the low-wavenumber update. Contribution of the reflection data to the update of FWI appears in the high-wavenumber reflectivity image. Therefore, contrary to the literal meaning of full waveform inversion, conventional FWI mainly relies on the diving waves to recover the background velocity model, which is crucial to stably converge to the global minimum. To additionally derive the low-wavenumber update from the reflected waves in the early stage of inversion, reflection waveform inversion (RWI) is proposed incorporating the scale separation of the velocity model into the background velocity and reflectivity models. By explicitly using the reflectivity model, the low-wavenumber update along the reflection wavepaths is available in the early stage of inversion, which are used to update the background velocity model. Once the background velocity model has been newly updated, the reflectivity model is then re-inverted from the new background velocity model. In this manner, the background velocity and reflectivity models are alternately updated. For a large-scale practical application, the approach to separate the high- and low-wavenumber components of the velocity model should avoid a large increase in computational effort. Meanwhile, to secure wider low-wavenumber update coverage, the contribution of the diving waves to the low-wavenumber update has to be appropriately considered during inversion of the background velocity model. In this thesis, the FWI gradient in reflection seismology is first analyzed to demonstrate how the diving and reflected waves contribute to the wavenumber components of the FWI gradient. Then, a diffraction-angle filtering technique, which has been proposed to control low-, intermediate- and high-wavenumber components of the FWI gradient in acoustic FWI, is introduced for the scale separation of the velocity model. The effects of the five modes of diffraction-angle filtering on the FWI gradient are illustrated only to show how diffraction-angle filtering changes the contributions of the diving and reflected waves to the FWI gradient. Based on the analysis of the FWI gradient and diffraction-angle filtering, I propose a new acoustic FWI technique with the diffraction-angle-filtering-based nested algorithm to build a reliable P-wave background velocity model using both the diving and reflected waves assuming a large-scale seismic data acquisition. In the nested algorithm, diffraction-angle filtering is applied in the framework of RWI, which allows the scale separation of the velocity model with reasonable computational efforts. Among the five modes of diffraction-angle filtering, modes IV and V are applied to the FWI gradient to update the background velocity and reflectivity structures, respectively. The prior reflectivity structures reconstructed by applying mode V provides the low-wavenumber update generated along the reflection wavepaths in addition to the conventional FWI update in the early stage of inversion. Then, mode IV can directly extract the low-wavenumber update generated along the wavepaths of the diving and reflected waves. With the improved low-wavenumber coverage, the background velocity model that accurately describes the kinematic behaviors of the observed diving and reflected waves can be reconstructed. Applications to the synthetic data for the 3D SEG/EAGE overthrust model and real 3D ocean-bottom cable (OBC) data from the Volve field at the North sea demonstrate that the diffraction-angle-filtering-based nested algorithm builds reliable background velocity models even when the subsurface structures are highly complex, or seismic data are affected by elasticity or anisotropy, which is common in field data applications. Modes IV and V of diffraction-angle filtering are successfully implemented for the scale separation in the framework of RWI. The background velocity models reconstructed by the nested algorithm can be used as new initial models for the subsequent acoustic or elastic FWI, which allows us to yield more accurate high-resolution subsurface velocity models.Chapter 1. Introduction 1 1.1. Background of the study 1 1.2. Research objective 5 1.3. Outline 8 Chapter 2. Implementation of acoustic FWI 10 2.1. Acoustic wave modeling 10 2.1.1. Acoustic wave equation 10 2.1.2. Staggered-grid finite-difference method 11 2.1.3. Boundaries 13 2.2. Acoustic FWI 19 2.2.1. Formulation of acoustic FWI 19 2.2.2. Other techniques for acoustic FWI 22 2.2.2.1. Two-level message passing interface-based parallelization 22 2.2.2.2. Boundary saving 23 2.2.2.3. Gradient preconditioning 26 2.2.2.4. Source estimation 27 Chapter 3. Acoustic FWI with the diffraction-angle-filtering-based nested algorithm 28 3.1. Wavenumber characteristics of acoustic FWI gradient 30 3.2. Diffraction-angle filtering for acoustic FWI 41 3.2.1. Formulation and mechanism of diffraction-angle filtering 41 3.2.2. Implementation on a staggered grid set 47 3.2.3. Computational requirements 54 3.3. Wavenumber characteristics of acoustic FWI gradient with diffraction-angle filtering 59 3.4. Design of the diffraction-angle-filtering-based nested algorithm 63 3.5. Workflow of the diffraction-angle-filtering-based nested algorithm 67 Chapter 4. Application to synthetic data: 3D SEG/EAGE overthrust model 69 4.1. Modeling and inversion parameters 71 4.2. Inversion results 74 Chapter 5. Application to field data: North Sea Volve oil field OBC data 89 5.1. Inversion parameters and strategies 94 5.2. Inversion results 102 Chapter 6. Conclusions 116 References 119 Appendix A. Derivation of the gradient using the adjoint-state method 130 Appendix B. Application to synthetic data: 2D Marmousi-II model 134 B.1. Modeling and inversion parameters 134 B.2. Inversion results 139 Appendix C. Application to field data: North Sea Volve oil field 2D OBC data 151 C.1. Inversion parameters and strategies 151 C.2. Inversion results 157 Abstract in Korean 165๋ฐ•

    ์Œ์ฃผ๋ฌธํ™”๋ฅผ ํ†ตํ•œ ใ€ˆํ•œ๋ฆผ๋ณ„๊ณกใ€‰์˜ ์ผ๊ณ ์ฐฐ

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    In Tang dynasty, popular customs from the countries bordering on western China, Buddhism music and dances, and cultures from China are combined to develop luxurious drinking culture that centralized by courtesans. Also the combination of culture and customs makes drinking rules to be more with music and dancing. The Silla nobility accept the new drinking rules and apply them to their feasts. It can be proved with the 14-sided dice from Anapji Pond. Jwajumunsaengyeon(ๅบงไธป้–€็”Ÿๅฎด: the background of ใ€ˆHanrim Byeolgokใ€‰), is based on gwageo, the highest-level state examination during the Gwangjong era in Goryeo dynasty. It has various types such as Youngchinhoei(ๆฆฎ่ฆชๆœƒ), Myungjokhoei(ๅ็ฐ‡ๆœƒ), Banghoei(ๆฆœๆœƒ), Yongdoohoei(๏ง„้ ญๆœƒ), Poomjung(ๅ“ๅ‘ˆ), and so on. In those feasts, the civil official in Goryeo dynasty enjoyed the games with drinking rules using the themes of ใ€ˆHanrim Byeolgokใ€‰ and heightened the conviviality. ใ€ˆHanrim Byeolgokใ€‰ is produced by many people and has hierarchical characteristics like a troll. It belongs to words characteristic, one of drinking rules and borrows the way(Chaksaryeng: ่‘—่พญไปค) that fills in the names of related topics with prior consultation and consistently arranges them. However, it is thought that the arrangement of the subject seems to be changed consistently and the stories of drinking rules in the structure and historical stories of ใ€ˆHanrim Byeolgokใ€‰ are confirmed to follow the same arrangement. Therefore, it is possible to infer that ใ€ˆHanrim Byeolgokใ€‰ is completed with re-arrangement of subjects of various drinking games in Jwajumunsaengyeon in 250 years. But it is hard to find its identification in future generation due to the settlement of lyrics and severance of drinking rules. To conclude, ใ€ˆHanrim Byeolgokใ€‰ is the collection of various drinking game pieces in Jwajumunsaengyeon made by the Chaksaryeng way and the song with lyrics but it is difficult to call a drinking game itself

    ๊ฒฝ์ œ๋ฐœ์ „์— ์žˆ์–ด์„œ์˜ ์ •๋ถ€์˜ ์—ญํ•  - ์žฌ์ •์ •์ฑ…์„ ์ค‘์‹ฌ์œผ๋กœ -

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    ์ด ๋…ผ๋ฌธ์€ ๊ทธ๊ฐ„์˜ ์šฐ๋ฆฌ๋‚˜๋ผ ๊ฒฝ์ œ๋ฐœ์ „์— ์žˆ์–ด์„œ ์žฌ์ •์ •์ฑ…์ด ์–ด๋– ํ•œ ์—ญํ• ์„ ํ•ด ์™”๋Š”๊ฐ€์— ๋Œ€ํ•œ ์ •์น˜๊ฒฝ์ œํ•™์  ์ ‘๊ทผ๋ถ„์„์„ ์‹œ๋„ํ•˜๊ณ  ์žˆ๋‹ค. ์žฌ์ •์ •์ฑ…์ด ์–ด๋–ป๊ฒŒ ๊ณตํ—Œํ•˜์˜€๋Š”๊ฐ€๋ฅผ ์‚ดํŽด๋ณด๋Š”๋ฐ ์žˆ์–ด ์ •์ฑ…๊ฒฐ์ •์ฐธ์—ฌ์ž๋“ค์˜ ์—ญํ• ์„ ์ค‘์‹ฌ์œผ๋กœ ๋ถ„์„ํ•˜๋ฉฐ, ์ด๋“ค์˜ ์—ญํ• ์„ ํ™•์ธํ•˜๊ณ ์žํ•˜๋Š” ๋ชฉ์ ์œผ๋กœ ๋ถ€๊ฐ€๊ฐ€์น˜์„ธ๋ฅผ ์‚ฌ๋ก€๋กœ ๊ทธ ์ฑ„ํƒ๊ณผ์ •์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ๊ฒฐ๋ก ์œผ๋กœ๋Š” ์šฐ๋ฆฌ๋‚˜๋ผ ์žฌ์ •์ •์ฑ…์ด ๊ทธ๊ฐ„์˜ ๊ฒฝ์ œ์„ฑ์žฅ์— ์ƒ๋‹นํ•œ ๊ณตํ—Œ์„ ํ•œ ๊ฒƒ์€ ํ‹€๋ฆฝ์—†์œผ๋‚˜, ์†Œ๋“๋ถ„๋ฐฐ์ƒ์˜ ์ทจ์•ฝ์ด๋ผ๋“ ๊ฐ€ ์ง€์—ญ๊ฐœ๋ฐœ์˜ ๋ถˆ๊ท ํ˜•๋“ฑ์˜ ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐ์‹œ์ผฐ์Œ์„ ๋‹ค์‹œ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์žฌ์ •์ •์ฑ…์˜ ์šด์˜๋ฉด์— ์žˆ์–ด์„œ๋„ ์ƒ๋‹นํ•œ ๊ฒฝ์šฐ๊ฐ€ ์ง€์†์„ฑ๊ณผ ์ผ๊ด€์„ฑ์„ ๊ฒฐ์—ฌํ•œ ์ฑ„ ์šด์˜๋˜์–ด ์™”์Œ์ด ๋˜ํ•œ ์ง€์ ๋˜์—ˆ๋‹ค. ์ •์ฑ…์ด ๊ฒฐ์ •๋˜๋Š” ๊ณผ์ •์— ์žˆ์–ด์„œ๋Š” ์ •๋ถ€๊ด€๋ฃŒ๋“ค์˜ ์ ˆ๋Œ€์ ์ธ ์ง€๋ฐฐํ•˜์—์„œ ๊ฒฐ์ •๋˜์–ด ์šด์˜๋˜์—ˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ๊ณผ์ •์—์„œ ๋‹ค๋ฅธ ์ดํ•ด์ง‘๋‹จ๋“ค์—๊ฒŒ ๊ทธ๋“ค์˜ ๊ฒฌํ•ด๋ฅผ ๋ฐํžˆ๋Š” ๊ธฐํšŒ๋Š” ์ถฉ๋ถ„ํžˆ ์ฃผ์–ด์กŒ์œผ๋‚˜ ๊ทธ๋“ค์˜ ์š”๊ตฌ์‚ฌํ•ญ์ด ๊ณต์‹์ ์œผ๋กœ ๋ฐ˜์˜๋œ ๊ฒƒ์€ ๊ฑฐ์˜ ์—†์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์ดํ•ด์ง‘๋‹จ๋“ค์˜ ๋ถˆ๋งŒ๊ณผ ๋ฐ˜๋Œ€์˜๊ฒฌ๋“ค์ด ๊ณต์‹์ ์ธ ์ ˆ์ฐจ๊ณผ์ •์—์„œ๋Š” ๊ธฐ๊ฐ๋˜์—ˆ๋‹ค๊ณ  ํ•˜๋”๋ผ๋„ ๋น„๊ณต์‹์ ์œผ๋กœ ์–ด๋Š์ •๋„ ์ ˆ์ถฉ๋˜์–ด ์ƒ๋‹นํžˆ ๋ฐ˜์˜๋˜์—ˆ์Œ์„ ๋˜ํ•œ ๋ฐœ๊ฒฌํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค

    ๋น„์šฉํŽธ์ต๋ถ„์„๊ณผ SOC ํˆฌ์ž์ •์ฑ… : ์ฒ ๋„ํˆฌ์ž๋ฅ  ์ค‘์‹ฌ์œผ๋กœ

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    ๋ณธ ๋…ผ๋ฌธ์€ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์ฒ ๋„ํˆฌ์ž์˜ ํ˜„ํ™ฉ์„ ์‚ดํŽด๋ณด๊ณ , ๊ทธ ๋™์•ˆ์˜ ๋„๋กœ์œ„์ฃผ์˜ ๊ตํ†ตํˆฌ์ž๊ฐ€ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋Š” ๊ฒƒ์— ๋”ฐ๋ฅธ ๋ฌธ์ œ์ ๊ณผ ํ•จ๊ป˜, ํŠนํžˆ ์ฒ ๋„ํˆฌ์ž ํƒ€๋‹น์„ฑ ๋ถ„์„์ƒ์˜ ๋ฌธ์ œ๊ฐ€ ์ฒ ๋„์— ๋Œ€ํ•œ ๊ณผ์†Œํˆฌ์ž๋ฅผ ์•ผ๊ธฐํ•œ ์›์ธ์ค‘์˜ ํ•˜๋‚˜์ž„์„ ๋ฐํžˆ๊ณ , ๊ทธ ๊ฐœ์„ ๋ฐฉ์•ˆ์„ ๋ชจ์ƒ‰ํ•˜๊ณ  ์žˆ๋‹ค. ์ฒ ๋„์‚ฌ์—…์˜ ํŽธ์ต์„ ์ด์šฉ์ž, ๋น„์ด์šฉ์ž (์ผ๋ฐ˜์ธ ๋ฐ ์‚ฌ์—…์ž)ํŽธ์ต์œผ๋กœ ๋‚˜๋ˆ„์–ด๋ณด๋ฉด์„œ ๋„๋กœ์ด์šฉ์ž์˜ ์ฒ ๋„์ด์šฉ์œผ๋กœ์˜ ์ „ํ™˜์— ๋”ฐ๋ฅธ ๋„๋กœ์ด์šฉ ๊ฐ์†Œ์— ๋”ฐ๋ฅธ ์šดํ–‰์‹œ๊ฐ„ ๋‹จ์ถ•, ๋Œ€๊ธฐ์˜ค์—ผ ๊ฐ์ถ• ๋“ฑ ๊ฐ์ข…์˜ ํŽธ์ต์„ ์ค‘์ ์ ์œผ๋กœ ๋…ผ์˜ํ•˜๊ณ  ์žˆ๋‹ค. ํ™˜๊ฒฝ์˜ค์—ผ ์™„ํ™” ๋“ฑ์˜ ํšจ๊ณผ๋Š” ์ธ๊ตฌ๋ฐ€๋„๊ฐ€ ๋†’์€ ์šฐ๋ฆฌ๋‚˜๋ผ์—์„œ ํŠนํžˆ ์„œ์šธ ๋“ฑ ๋Œ€๋„์‹œ ์ธ๊ตฌ๋ฐ€์ง‘์ง€์—ญ์—์„œ๋Š” ๋†’๊ฒŒ ๊ณ„์ƒ๋˜๋Š” ํŽธ์ต์œผ๋กœ ์ธ์ •๋˜์–ด์•ผ ํ•œ๋‹ค. ๋˜ํ•œ ์‚ฌ์—…์ž ํŽธ์ต ์ฆ‰, ์ฒ ๋„์ˆ˜์š”์˜ ์ฆ๊ฐ€์— ๋”ฐ๋ผ ๋ฐœ์ƒํ•œ ์ฒ ๋„์‚ฌ์—…์˜ ์ˆ˜์ต์„ ํŽธ์ตํ•ญ๋ชฉ์œผ๋กœ ๊ณ ๋ คํ•  ๊ฒƒ์„ ์ œ์•ˆํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋ ‡๊ฒŒ ๋ณผ ๋•Œ ์ฒ ๋„์ด์šฉ์œผ๋กœ ์ธํ•œ ํŽธ์ต์€ ์ง€๊ธˆ๊นŒ์ง€ ์šฐ๋ฆฌ๊ฐ€ ๊ณ ๋ คํ•ด์˜จ ๊ฒƒ๋ณด๋‹ค ํ›จ์”ฌ ํฌ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ์ƒ๋Œ€์ ์œผ๋กœ ๋†’์€ ๋น„์ด์šฉ์ž ํŽธ์ต์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์ฒ ๋„๋ถ€๋ฌธ์ด ํˆฌ์ž์‹ฌ์‚ฌ ๊ณผ์ •์—์„œ ์ด๋Ÿฌํ•œ ํŽธ์ต์„ ์ฒด๊ณ„์ ์œผ๋กœ ๊ณ„์ƒํ•˜์ง€ ๋ชปํ•œ ๊ฒƒ์ด ์ •๋ถ€์˜ SOC ์˜ˆ์‚ฐ๊ฒฐ์ •๊ณผ์ •์—์„œ ๋„๋กœ๋ถ€๋ฌธ์— ๋น„ํ•ด ์ƒ๋Œ€์ ์œผ๋กœ ์†Œ์™ธ๋˜์–ด ์˜จ ๊ฒƒ์— ์ผ์กฐํ•˜์˜€๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ์œผ๋ฏ€๋กœ, ์•ž์œผ๋กœ ๋ณด๋‹ค ๊ฐ๊ด€์ ์ด๊ณ  ์ •๊ตํ•œ ํ‰๊ฐ€์ ˆ์ฐจ์˜ ์š”๊ตฌ์™€ ํ•จ๊ป˜ ์ด๋Ÿฌํ•œ ์ถ”๊ฐ€์ ์ธ ํŽธ์ตํ•ญ๋ชฉ๋“ค์„ ๊ณ„๋Ÿ‰ํ™”ํ•˜์—ฌ ๋ฐ˜์˜ํ•˜๋Š” ๊ฒƒ์ด ๋ฐ”๋žŒ์งํ•˜๋‹ค

    ํ™”ํ•™์  ํ™˜์›๋ฒ•์— ์˜ํ•˜์—ฌ ์ œ์กฐ๋œ ๋ฆฌํŠฌ ์ด์ฐจ ์ „์ง€์šฉ ์ดˆ๋ฏธ๋ฆฝ Sn-Cu-B ํ•ฉ๊ธˆ ์Œ๊ทน์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์žฌ๋ฃŒ๊ณตํ•™๋ถ€,2001.Maste

    Identification of protein antigens of treponema pallidum reacting with serum IgG and IgM antibodies of patients with syphilis

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    ์˜ํ•™๊ณผ/๋ฐ•์‚ฌ[ํ•œ๊ธ€] ๋งค๋…์˜ ์›์ธ๊ท ์ธ T. pallidum์„ ๊ตฌ์„ฑํ•˜๋Š” ๋‹จ๋ฐฑํ•ญ์›๋“ค์„ ์•Œ์•„๋‚ด๊ณ , ๊ทธ๋“ค์˜ ์ƒ๋ฌผํ•™์ , ์ƒ ํ™”ํ•™์  ํŠน์„ฑ์„ ๊ทœ๋ช…ํ•˜๋Š” ๊ฒƒ์€ ๋งค๋…์˜ ๋ณ‘์ธ๋ก ์„ ๋ฐํ˜€๋‚ด๋Š” ๊ธฐ๋ณธ์š”์†Œ๊ฐ€ ๋˜๋ฉฐ, ๋‚˜์•„๊ฐ€์„œ๋Š” ๋ฐฑ ์‹ ์˜ ๊ฐœ๋ฐœ ๋ฐ ์ƒˆ๋กœ์šด ๋ฉด์—ญํ•™์  ์ง„๋‹จ๋ฒ• ๊ฐœ๋ฐœ์— ํฌ๊ฒŒ ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ์ด์— ์—ฌ๋Ÿฌํ•™ ์ž๋“ค์ด sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE)์™€ immun oblotting์„ ์ด์šฉํ•˜์—ฌ ๋งค๋…๊ท  ๋‹จ๋ฐฑํ•ญ์›์˜ ์ •์ฒด ๊ทœ๋ช…์„ ์œ„ํ•œ ์—ฐ๊ตฌ๋ฅผ ํ•ด ์™”์œผ๋‚˜, ์—ฐ๊ตฌ์ž์— ๋”ฐ๋ผ ๋งค๋…ํ™˜์ž ํ˜ˆ์ฒญ์— ์ถœํ˜„ํ•˜๋Š” ํ•ญ์ฒด์™€ ๋ฐ˜์‘ํ•˜๋Š” ๋งค๋…๊ท  ํ•ญ์›์˜ ์ˆ˜๊ฐ€ ๋‹ค๋ฅด๊ณ  ๊ฐ ์ž„์ƒ๊ธฐ๋ณ„ ๋กœ ํ•ญ์ฒด์™€ ๋ฐ˜์‘ํ•˜๋Š” ๋ถ„์ž๋Ÿ‰์— ๋”ฐ๋ฅธ ๋งค๋…๊ท  ํ•ญ์›์˜ ์ข…๋ฅ˜์—๋„ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋Š” ๋งค๋… ์น˜๋ฃŒ์ „์— ์ถœํ˜„ํ•˜๊ณ  ์น˜๋ฃŒํ›„์— ์†Œ์‹ค๋˜๋Š” ํ˜ˆ์ฒญ IgG ๋ฐ IgM ํ•ญ์ฒด์™€ ๋ฐ˜์‘ํ•˜๋Š” ๋งค๋…๊ท  ๋‹จ๋ฐฑํ•ญ์›์„ ๊ทœ๋ช…ํ•˜๊ณ  ๋˜ํ•œ T. pallidum๊ณผ T. phagedenis์˜ ๊ณต์œ ํ•ญ์›, T. pallidum ํŠน์ดํ•ญ ์›์„ ๊ทœ๋ช…ํ•˜๊ณ ์ž ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์‹คํ—˜์„ ํ•˜์˜€๋‹ค. ๊ฐ€ํ† ์˜ ๊ณ ํ™˜์— ๊ณ„๋Œ€์ ‘์ข…ํ•˜์—ฌ ๋ณด์กดํ•ด ์˜ค๋˜ T. pallidum, Nichols strain์„ ์ถ”์ถœํ•˜์—ฌ Per coll์„ ์ด์šฉํ•œ ๋ฐ€๋„๊ตฌ๋ฐฐ ์›์‹ฌ๋ถ„๋ฆฌ๋กœ ์ˆœ์ˆ˜๋ถ„๋ฆฌ ํ•˜๊ณ  SDS-PAGE์™€ immunoblottingํ•˜์˜€๋‹ค. ์ด ๋ฅผ ๊ฐ ์ž„์ƒ๊ธฐ ๋งค๋…ํ™˜์ž ๊ฐ๊ธฐ 3๋ช…์œผ๋กœ๋ถ€ํ„ฐ ์น˜๋ฃŒ์ „๊ณผ ์น˜๋ฃŒํ›„ 3๊ฐœ์›”๋งˆ๋‹ค ์ฑ„์ทจํ•˜์—ฌ poolingํ•œ ํ˜ˆ์ฒญ๊ณผ 2๊ธฐ, ์กฐ๊ธฐ ์ž ๋ณต ๋˜๋Š” ๋งŒ๊ธฐ ์ž ๋ณต๋งค๋…์—์„œ ์น˜๋ฃŒํ›„ 2โˆผ14๋…„๋œ 14๋ช…์˜ ์น˜๋ฃŒ๋œ ๋งค๋…ํ™˜ ์ž ํ˜ˆ์ฒญ๊ณผ ๋ฐ˜์‘์‹œ์ผœ autoradiography ํ˜น์€ immunoperoxidase ๋ฐฉ๋ฒ•์œผ๋กœ IgG ๋ฐ IgM ํ•ญ์ฒด์— ๋ฐ˜์‘ํ•˜๋Š” ๋งค๋…๊ท  ๋‹จ๋ฐฑํ•ญ์›์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ๋˜ํ•œ thioglycollate broth media์— ๊ณ„๋Œ€๋ฐฐ์–‘ ํ•ด ์˜ค๋˜ T. phagedenis, biotype Reiter๋ฅผ SDS-PAGE์™€ immunoblottingํ•œ ํ›„, ์ด๋ฅผ ๊ฐ ์ž„ ์ƒ๊ธฐ ๋งค๋…ํ™˜์ž ๊ฐ๊ธฐ 3๋ช…์œผ๋กœ๋ถ€ํ„ฐ ์น˜๋ฃŒ์ „์— ์ฑ„์ทจํ•˜์—ฌ poolingํ•œ ํ˜ˆ์ฒญ๊ณผ ๋ฐ˜์‘์‹œ์ผœ autoradi ography๋ฐฉ๋ฒ•์œผ๋กœ ํ˜ˆ์ฒญ IgG ํ•ญ์ฒด์™€ ๋ฐ˜์‘ํ•˜๋Š” ๋‹จ๋ฐฑํ•ญ์›์„ ๊ด€์ฐฐํ•˜์—ฌ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์„ฑ์ ์„ ์–ป ์—ˆ๋‹ค. 1. SDS-PAGE๋กœ ๋ถ„๋ฆฌํ•˜์—ฌ ์—ผ์ƒ‰ํ•œ ๊ฒฐ๊ณผ, T. pallidum, Nichols strain๊ณผ T. phagedenis, biotype Reiter์—์„œ ๊ฐ๊ฐ 45๊ฐœ ๋ฐ 43๊ฐœ์˜ ๋‹จ๋ฐฑํ•ญ์›์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. 2. ์น˜๋ฃŒ์ „ ๋งค๋…ํ™˜์ž ํ˜ˆ์ฒญ IgG ํ•ญ์ฒด์™€ ๋ฐ˜์‘ํ•˜๋Š” ๋ถ„์ž๋Ÿ‰ 47,000, 36,500, 15,500, 14,000 ์˜ ๋‹จ๋ฐฑํ•ญ์›๊ณผ IgM ํ•ญ์ฒด์™€ ๋ฐ˜์‘ํ•˜๋Š” ๋ถ„์ž๋Ÿ‰ 47,000, 34,000, 29,500์˜ ๋‹จ๋ฐฑํ•ญ์›์ด ๊ฐ€์žฅ ๊ฐ•ํ•œ ๋ฐ˜์‘์„ ๋ณด์—ฌ ์ด๋“ค์ด ๋งค๋…๊ท  ์ฃผํ•ญ์›์ž„์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. 3. ์น˜๋ฃŒ์ „, ํ›„ ๋งค๋…ํ™˜์ž์—์„œ ํ˜ˆ์ฒญ IgG ๋ฐ IgM ํ•ญ์ฒด์™€ ๋ฐ˜์‘ํ•˜๋Š” ๋งค๋…๊ท  ๋‹จ๋ฐฑํ•ญ์›์„ ๊ด€์ฐฐ ํ•œ ๊ฒฐ๊ณผ, 1๊ธฐ, 2๊ธฐ ๋ฐ ์กฐ๊ธฐ ์ž ๋ณต๋งค๋…์—์„œ๋Š” ์†Œ์ˆ˜์˜ ํ•ญ์› ์†Œ์‹ค๊ณผ ๋ฐ˜์‘๋„์˜ ๊ฐ์†Œ๋ฅผ ๊ด€์ฐฐํ•˜ ์˜€์œผ๋‚˜, ๋งŒ๊ธฐ์ž ๋ณต ๋ฐ ์žฌ๊ฐ์—ผ๋œ ๋งค๋…์—์„œ๋Š” ๋ณ€ํ™”๋ฅผ ๋ณผ ์ˆ˜ ์—†์—ˆ๋‹ค. 4. ์น˜๋ฃŒ๋œ ๋งค๋…ํ™˜์ž์—์„œ ํ˜ˆ์ฒญ ํ•ญ์ฒด์™€ ๋งค๋…๊ท  ์ฃผํ•ญ์›์˜ ๋ฐ˜์‘๋„๋ฅผ ๊ด€์ฐฐํ•œ ๊ฒฐ๊ณผ, IgM ํ•ญ์ฒด ์™€ ๋ฐ˜์‘ํ•˜๋Š” ๋ถ„์ž๋Ÿ‰ 47,700์˜ ํ•ญ์›์—์„œ๋งŒ ํ˜„์ €ํ•˜๊ฒŒ ๋ฐ˜์‘๋„๊ฐ€ ๊ฐ์†Œํ•˜์˜€๋‹ค. 5. T. pallidum๊ณผ T. phagedenis์˜ ๊ณต์œ ํ•ญ์›์„ ๊ด€์ฐฐํ•œ ๊ฒฐ๊ณผ ๋ชจ๋‘ 11๊ฐœ์˜€๊ณ , ๋ถ„์ž๋Ÿ‰ 86, 500, 68,500, 15,500, 14,000์˜ ํ•ญ์›์ด ๊ณต์œ ํ•ญ์›์ด ์•„๋‹Œ ๋งค๋…๊ท  ํŠน์ด ํ•ญ์›์ž„์„ ์•Œ ์ˆ˜ ์žˆ ์—ˆ๋‹ค. ์ด์ƒ์˜ ๊ฒฐ๊ณผ๋กœ ๋งค๋…๊ท  ์ฃผํ•ญ์›์ค‘ ๋ถ„์ž๋Ÿ‰ 15,500, 14,400์˜ ํ•ญ์›๊ณผ ๋ถ„์ž๋Ÿ‰ 47,000์˜ ํ•ญ์› ์ด ๊ฐ๊ฐ ํ–ฅํ›„ ๋งค๋…ํ˜ˆ์ฒญ๊ฒ€์‚ฌ ๋ฐ ์น˜๋ฃŒํŒ์ •์— ๋„์›€์ด ๋  ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค. [์˜๋ฌธ] Knowledge of the constituent protein antigens of T. pallidum, the causative microorganism for syphilis, and their biological functions and biochemical properties would not only serve to lay the groundwork in elucidating the pathogenesis of syphilis, but would also further contribute significantly in the development of both vaccinations and new immunodiagnostic methods for syphilis. For these reasons, many researchers employing SDS-PAGE and immunoblotting techniques have been attempting to characterize protein antigens of syphilis but with differing results in terms of number of antigens reacting with antibodies in the sera of patients with syphilis and with respect to antigens reacting with antibodies in the sera of different stages of syphilis which were of different types in terms of their molecular weights. This study was conducted to identify the protein antigens reacting with IgG and IgM antibodies in the sera of patients with syphilis, which appear before and disappear after treatment, the antigens common to both T. pallidum and T. phagedenis, and the antigens specific only to T. pallidum. T. pallidum, Nichols strain maintained by rabbit testicular passage was extracted and purified by Percoll density gradient centrifugation, followed by SDS-PAGE and immunoblotting. The protein antigens of T. pallidum reacting with IgG and IgM antibodies in the sera were observed using autoradiography and immunoperoxidase technique after the reactions between the prepared antigens of T. pallidum and the sera of patients with syphilis in groups of 3 at each clinical stage before and after treatment at 3 months intervals, where each group of 3 was pooled and the sera of 14 patients with treated syphilis who had been treated for secondary, early latent and late latent syphilis 2-14 years ago. T. phagedenis, biotype Reiter maintained in the thioglycollate broth media was separated and transferred by SDS-PAGE and immunoblotting. After the reaction between the prepared antigens of T. phagedenis and the sera of patients with syphilis in groups of 3 at each clinical stage before treatment, where each group of 3 was pooled, protein antigens of T. phagedenis reacting with IgG antibodies in the sera were observed using autoradiography. The results obtained from the above observations were as follows; 1. After separation by SDS-PAGE and staining with Coomassie Blue dye, 45 protein antigens of T. pallidum, Nichols strain and 43 protein antigens of T. phagedenis, biotype Reiter were observed. 2. Before treatment, the most strongly reacting antigens of T. pallidum precipitated by IgG antibodies in the sera of patients were polypeptides of molecular weights 47,000, 36,500, 15,500 and 14,000 and those precipitated by IgM antibodies were polypeptides of molecular weights 47,000, 34,000 and 29,500. So it was observed that those were the major antigens of T. pallidum. 3. After observing protein antigens of T. pallidum reacting with IgG and IgM antibodies in the sera of patients with syphilis before and after treatment, it was seen that in primary, secondary and early latent syphilis there was a loss of several antigens and a decrease in reactivity, but no changes occurred in late latent and reinfected syphilis. 4. From the observation of the reaction between serum antibodies of patients with treatedsyphilis and major antigens of T. pallidum, an evident decrease in reactivity was observed only with protein antigen of molecular weight 47,000 which reacts with IgM antibody. 5. The total number of antigens common to both T. pallidum and T. phagdenis was observed to be 11, and antigens of molecular weights 86,500, 68,500, 15,500 and 14,000 showed to be non-common but antigens specific to T. pallidum. From the above results, it could be concluded that of the major antigens of T. pallidum, the antigens of the molecular weights 15,500 and 14,000 could serve to develop newer serologic tests for syphilis, and that of molecular weight 47,000 could contribute to the assessment of the efficacy of treatment.restrictio

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    ํ˜„๋Œ€์˜ ์ •๋ถ€๋Š” ์—ฌ๋Ÿฌ๊ฐ€์ง€ ์ข…๋ฅ˜์˜ ์žฌํ™”์™€ ์„œ์–ด๋น„์Šค๋ฅผ ๊ณต๊ธ‰ํ•˜๊ณ  ์žˆ๋‹ค. ์ฆ‰ ๊ตญ๋ฐฉ, ๊ฒฝ์ฐฐ, ์‚ฌ๋ฒ•๋“ฑ๊ณผ ๊ฐ™์ด ์ˆœ์ˆ˜๊ณต๋ฌด์žฌ๋กœ๋ถ€ํ„ฐ ๋‹ด๋ฐฐ, ์ˆ  ๋“ฑ์˜ ์ˆœ์ˆ˜๋ฏผ๊ฐ„์žฌ์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ๋‹ค์–‘ํ•œ ์ข…๋ฅ˜์˜ ๊ณต์ ๊ณต๊ธ‰์ด ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋Š” ๊ฒƒ์ด๋‹ค. ์ด์— ๋”ฐ๋ผ์„œ ๊ณต์ ๊ณต๊ธ‰์„ ์œ„ํ•œ ์žฌ์›์กฐ๋‹ฌ๋„ ๋งค์šฐ ๋‹ค์–‘ํ•œ ๋ฐฉ๋ฒ•์„ ํ†ตํ•˜์—ฌ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ์ •๋ถ€๊ฐ€ ๋ฏผ๊ฐ„์žฌ๋ฅผ ์ƒ์‚ฐํ•˜์—ฌ ๊ณต๊ธ‰ํ•  ๋•Œ์—๋Š” ๋ฏผ๊ฐ„์žฌ์˜ ์„ฑ๊ฒฉ์—๋”ฐ๋ผ ๊ณ ๊ฐœ์˜ ์žฌํ™”์— ๊ฐ€๊ฒฉ์„ ๋ถ€๊ณผํ•  ์ˆ˜ ์žˆ๊ณ  ์žฌ์›์กฐ๋‹ฌ๋„ ๊ฐ€๊ฒฉ์„ ํ†ตํ•œ ๊ฐœ๋ณ„๋ฐฉ์‹์œผ๋กœ ์ด๋ฃจ์–ด ์งˆ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ณต๊ณต์žฌ์˜ ๊ฒฝ์šฐ ๊ณต๊ณต์žฌ์˜ ๋น„๊ฒฝํ•ฉ์  ์†Œ๋น„์„ฑ(nonrival consumption)๊ณผ ๋น„๋ฐฐ์ œ์„ฑ(non-excludability) ๋“ฑ์˜ ํŠน์„ฑ๋•Œ๋ฌธ์— ๋ฏผ๊ฐ„์žฌ์—์„œ ์ ์šฉ๋˜๋Š” ๊ฐœ๋ณ„์  ๋ณด์ƒ์›๋ฆฌ์— ์˜ํ•œ ์žฌ์›์กฐ๋‹ฌ์€ ์–ด๋ ต๋‹ค ํ•  ๊ฒƒ์ด๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ๊ณต๊ณต์žฌ๋Š” ์ „์•ก ํ˜น์€ ๋ถ€๋ถ„์ ์œผ๋กœ ๋ฌด๋ฃŒ์ธ ํ˜•ํƒœ๋กœ ๊ณต๊ธ‰๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ทธ๊ฒƒ์ด ๋ณธ์งˆ์ ์œผ๋กœ ๋ฌด๋ฃŒ๋กœ ๊ณต๊ธ‰๋˜๋Š” ๊ฒƒ์€ ์•„๋‹ˆ๋‹ค. ์™œ๋ƒํ•˜๋ฉด ๊ทธ ๊ณต๊ณต์žฌ๋ฅผ ๊ณต๊ธ‰ํ•˜๊ธฐ ์œ„ํ•œ ๋น„์šฉ์€ ์กฐ์„ธ์˜ ํ˜•ํƒœ๋กœ ๊ฐ ์†Œ๋น„์ž์—๊ฒŒ ๋ถ€๊ณผ๋˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๊ฒฐ๊ตญ ๊ณต์  ๊ณต๊ธ‰์ด ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋Š” ๊ฐ์ข…์˜ ์žฌํ™”์— ๋Œ€ํ•˜์—ฌ ๊ฐ ์†Œ๋น„์ž๋Š” ์–ด๋– ํ•œ ํ˜•ํƒœ๋กœ๋“ ์ง€ ๊ทธ ๋Œ€๊ฐ€๋ฅผ ์ง€๋ถˆํ•˜๊ณ  ์žˆ๋Š” ๊ฒƒ์ด๋‹ค. ๋‹ค๋งŒ ๋ฏผ๊ฐ„์žฌ์˜ ๊ฒฝ์šฐ๋Š” ๊ทธ ์†Œ๋น„์™€ ๋น„์šฉ๋ถ€๋‹ด์ด ์ง์ ‘ ์—ฐ๊ฒฐ๋˜๊ณ  ์žˆ๋Š”๋ฐ ๋ฐ˜ํ•˜์—ฌ ๊ณต๊ณต์žฌ์˜ ๊ฒฝ์šฐ๋Š” ๊ทธ ๊ด€๊ณ„๊ฐ€ ๊ฐ„์ ‘์ ์ด๋ผ๋Š” ๊ฒƒ์ด ๋‹ค๋ฅผ ๋ฟ์ด๋‹ค

    ๊ธˆ์œต์œ„๊ธฐ์™€ ์žฌ์ •์˜ ๋Œ€์‘

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    ๋ณธ ๋…ผ๋ฌธ์€ ๊ธˆ์œต์œ„๊ธฐ์— ์ง๋ฉดํ•œ ๊ตญ๊ฐ€๊ฐ€ ์ด์— ๋Œ€์ฒ˜ํ•˜๊ธฐ ์œ„ํ•œ ์—ฌ๋Ÿฌ ์ •์ฑ…์  ์กฐ์น˜๊ฐ€์šด๋ฐ์„œ ์žฌ์ •์˜ ์—ญํ• ๊ณผ ํ•œ๊ณ„๊ฐ€ ๋ฌด์—‡์ธ๊ฐ€๋ฅผ ๊ทœ๋ช…ํ•˜๊ณ ์ž ํ•˜๋Š”๋ฐ ๋ชฉ์ ์ด ์žˆ๋‹ค. ํŠนํžˆ ๋ฏธ๊ตญ์˜ 1980๋…„๋Œ€ ๊ธˆ์œต๊ธฐ๊ด€ ๋ถ€์‹คํ™” ํ˜„ํ™ฉ๊ณผ ๋ฐฐ๊ฒฝ์„ ์‚ดํŽด๋ณด๊ณ  ์ด๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๋ฏธ๊ตญ์ •๋ถ€๋Š” ์–ด๋–ค ์กฐ์น˜๋ฅผ ์ทจํ•˜์˜€์œผ๋ฉฐ ๊ทธ ๊ฒฐ๊ณผ๋Š” ์–ด๋– ํ–ˆ๋Š”์ง€๋ฅผ ์‚ดํŽด๋ณธ๋‹ค. ๋ฏธ๊ตญ์˜ ๊ธˆ์œต์œ„๊ธฐ ๊ทน๋ณต์€ ๋น„๊ต์  ์„ฑ๊ณต์  ์ด์˜€๋‹ค๊ณ  ํ‰๊ฐ€๋˜๋ฉฐ ๋ฏธ๊ตญ์ •๋ถ€์˜ ๊ฐ•๋ ฅํ•œ ์ถ”์ง„๋ ฅ์ด ์„ฑ๊ณต์˜ ๋ฐ‘๊ฑฐ๋ฆ„์ด์˜€๋‹ค. ๋™์‹œ์— ๊ธˆ์œต๊ตฌ์กฐ์กฐ์ •์„ ์œ„ํ•œ ๋ฏธ์—ฐ๋ฐฉ์ •๋ถ€์˜ ์žฌ์ •์ง€์›์ด ๋ง‰๋Œ€ํ•˜์˜€๋Š”๋ฐ ์ด๋Š” ๊ธˆ์œต๊ณผ ์žฌ์ •์˜ ์Šฌ๊ธฐ๋กœ์šด ์กฐํ™”๋ฅผ ๋‹ค์‹œ ํ™•์ธํ•˜๊ฒŒ ๋˜๋ฉฐ ์šฐ๋ฆฌ๋‚˜๋ผ์—๊ฒŒ๋„ ๋งŽ์€ ์ •์ฑ…์  ์‹œ์‚ฌ์ ์„ ์ œ๊ณตํ•ด ์ฃผ๊ณ  ์žˆ๋‹ค

    ๋ณต์ง€์žฌ์ •๊ฐ•ํ™”์™€ ๋ถˆ๊ท ํ˜•์˜ ์‹œ์ •

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    ๋ณธ๋…ผ๋ฌธ์€ ์šฐ๋ฆฌ๋‚˜๋ผ๊ฐ€ ๋ณต์ง€์žฌ์ •์„ ๊ฐ•ํ™”ํ•˜๋ฉด์„œ ๊ทธ๋™์•ˆ ๋ˆ„์ ๋˜์–ด์˜จ ๊ณ„์ธต๊ฐ„, ์ง€์—ญ๊ฐ„, ์‚ฐ์—…๊ฐ„์˜ ๋ถˆ๊ท ํ˜•์„ ์–ด๋–ป๊ฒŒ ์‹œ์ •ํ•  ์ˆ˜ ์žˆ๋Š”๊ฐ€์— ์ดˆ์ ์„ ๋งž์ถ”์–ด ์„œ์ˆ ๋˜์—ˆ๋‹ค. ์šฐ๋ฆฌ๊ฒฝ์ œ๊ฐ€ 1986๋…„์ดํ›„ ๊ธ‰๊ฒฉํžˆ ๋ณ€ํ™”๋˜์—ˆ๊ณ  ์ด๋Ÿฌํ•œ ๊ณผ์ •์—์„œ ์ œ๊ธฐ๋œ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ๊ณผ์ œ๊ฐ€ ๋ถˆ๊ท ํ˜•์˜ ์‹œ์ •์ด๋ฉฐ ์ด์˜ ์‹œ์ •์„ ๋ณต์ง€์žฌ์ •์˜ ๊ฐ•ํ™”๋ผ๋Š” ์ธก๋ฉด์—์„œ ์กฐ๋ช…ํ•ด ๋ณธ ๊ฒƒ์ด๋‹ค. ๊ตญ์ œ์ˆ˜์ง€์˜ ํ‘์ž๋Š” ์žฌ์ •์šด์šฉ์— ๋งŽ์€ ์–ด๋ ค์›€์„ ์•ผ๊ธฐ์‹œ์ผœ ์™”๊ณ , ์ •๋ถ€์˜ ์žฌ์ •๊ธฐ๋Šฅ์„ ์žฌ์ •๋ฆฝํ•˜๋Š” ๊ณ„๊ธฐ๋ฅผ ๋งˆ๋ จํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ณต์ง€์žฌ์ •์˜ ๋ฒ”์œ„์™€ ์ˆ˜์š”์ „๋ง์„ ๋ช…ํ™•ํžˆ ํ•˜์ง€ ์•Š์œผ๋ฉด ํ˜ผ๋ž€๋งŒ ์˜ฌ ์ˆ˜ ์žˆ์Œ์„ ์ธ์‹ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋ฌด์—‡๋ณด๋‹ค๋„ ์ค‘์š”ํ•œ ๊ฒƒ์€ ์žฌ์›ํ™•๋ณด๋ฐฉ์•ˆ์ด๋ฉฐ ๋‹ค์–‘ํ•˜๊ณ  ํ˜„์‹ค์ ์ธ ๋ฐฉ๋ฒ•์„ ๊ฐ•๊ตฌํ•˜์—ฌ์•ผ ๋œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์žฌ์ •์šด์šฉ์˜ ํšจ์œจ์„ฑ์„ ์ œ๊ณ ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ์˜ˆ์‚ฐ์ง€์ถœํ•ญ๋ชฉ์˜ ๋Šฅ๋™์ ์ธ ์šฐ์„ ์ˆœ์œ„ ์กฐ์ •์ด ์žˆ์–ด์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ๋์œผ๋กœ ๋ฏผ๊ฐ„๋ถ€๋ฌธ๊ณผ์˜ ๊ธฐ๋Šฅ์žฌ์กฐ์ •์ด ์ ˆ์‹คํžˆ ์š”์ฒญ๋˜๋ฉฐ ์ •๋ถ€์˜ ๊ณผ๊ฐํ•œ ํ–‰์ •๊ฐœํ˜๋„ ํ•จ๊ป˜ ์ด๋ฃจ์–ด์ ธ์•ผ ํ•  ๊ฒƒ์ด๋‹ค

    A Study on the Development of a LED Floodlight for Naval Vessels

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    ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ตœ๊ทผ ๊ณ ํšจ์œจ ์นœํ™˜๊ฒฝ ๊ด‘์›์œผ๋กœ ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋Š” LED ๊ด‘์›์˜ ํ•จ์ •์šฉ ํˆฌ๊ด‘๋“ฑ ์ ์šฉ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ธฐ์กด 500W ํ• ๋กœ๊ฒ๋“ฑ์„ ์‚ฌ์šฉํ•˜๋Š” 12โ€œ ํˆฌ๊ด‘๋“ฑ์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜์˜€์œผ๋ฉฐ, ์„ค๊ณ„ ๊ธฐ์ค€์€ ๊ตญ๋ฐฉ๊ทœ๊ฒฉ(KDC 6230-R4002), ํ•œ๊ตญ์‚ฐ์—…๊ทœ๊ฒฉ(KS V 8427) ๋ฐ ๊ตญ์ œ๊ทœ๊ฒฉ(IEC 7712)๋ฅผ ๊ทผ๊ฑฐ๋กœ ํ•˜๊ณ  ์žˆ๋‹ค. ์„ค๊ณ„์˜ ์ค‘์š” ์š”์†Œ๋Š” ๊ด‘๊ฐ(beam angle), ๊ด‘๋„ ๋ฐ ๋ฐฉ์—ด์ด๋ฏ€๋กœ, ๊ด‘ํ•™์  ํŠน์„ฑ ๋ถ„์„์œผ๋กœ๋ถ€ํ„ฐ LED package์™€ ๋ Œ์ฆˆ๋ฅผ ์„ ์ •ํ•˜์˜€์œผ๋ฉฐ, ๊ณ ํšจ์œจ ์ •์ „๋ฅ˜ ๋ฐฉ์‹์˜ ๊ตฌ๋™ํšŒ๋กœ๋ฅผ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ๋ฐฉ์—ด์€ ์•Œ๋ฃจ๋ฏธ๋Š„ ํžˆํŠธ์‹ฑํฌ์™€ ๋ฐฉ์—ด ๊ตฌ์กฐ PCB๋ฅผ ์ ์šฉํ•˜์—ฌ, LED ๊ด‘์›์˜ ๋ฐฐ์น˜์— ๋”ฐ๋ฅธ ์˜จ๋„๋ถ„ํฌ ๋ถ„์„์„ ํ†ตํ•ด ์ตœ์ ์˜ LED package ๋ฐฐ์น˜๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. ์ตœ์ข…์ ์œผ๋กœ ์ œ์ž‘ํ•œ LED ํˆฌ๊ด‘๋“ฑ์˜ ์ด ์†Œ๋น„์ „๋ ฅ์€ 44W์ด๋ฉฐ, ๊ด€๋ จ ๊ทœ๊ฒฉ์— ๋”ฐ๋ฅธ ์ „๊ธฐ์ , ๊ด‘ํ•™์  ๋ฐ ํ™˜๊ฒฝ์  ์š”๊ตฌ์‚ฌํ•ญ๋“ค์„ ํ‰๊ฐ€ํ•œ ๊ฒฐ๊ณผ, ๋ชจ๋‘ ๋งŒ์กฑํ•˜์˜€๋‹ค. ์‹œ์ œ์ž‘ ํ•จ์ •์šฉ LED ํˆฌ๊ด‘๋“ฑ์€ ๊ธฐ์กด ํ• ๋กœ๊ฒ ํˆฌ๊ด‘๋“ฑ ๋Œ€๋น„ 91.2%์˜ ์†Œ๋น„์ „๋ ฅ ์ ˆ๊ฐ์ด ์žˆ์œผ๋ฉฐ, ํŠนํžˆ ํ•จ์ • ๋˜๋Š” ์„ ๋ฐ•๊ณผ ๊ฐ™์ด ์ง„๋™์ด ํฐ ์šด์˜ ํ™˜๊ฒฝ์—์„œ ํ•„๋ผ๋ฉ˜ํŠธ ๊ด‘์›๋ณด๋‹ค 15๋ฐฐ ์ด์ƒ ์žฅ์ˆ˜๋ช…์œผ๋กœ ์œ ์ง€๋ณด์ˆ˜๋น„ ์ ˆ๊ฐ์„ ๊ธฐ๋Œ€ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด์™€ ๊ฐ™์ด ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ํ•จ์ •์šฉ LED ํˆฌ๊ด‘๋“ฑ์„ ๊ฐœ๋ฐœํ•จ์— ์žˆ์–ด ์ „๊ธฐ์ , ๊ด‘ํ•™์  ๋ฐ ํ™˜๊ฒฝ์  ์„ฑ๋Šฅ ์š”๊ตฌ์‚ฌํ•ญ์„ ์‹คํ—˜์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ  ์„ค๊ณ„ ๊ธฐ์ˆ ์„ ํ™•๋ณดํ•˜์˜€๋‹ค.๋ชฉ ์ฐจ โ…ฐ ๊ทธ๋ฆผ ๋ฐ ํ‘œ ๋ชฉ์ฐจ โ…ฒ Abstract โ…ด ์ œ 1 ์žฅ ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 1 1.2 ์—ฐ๊ตฌ ๋ชฉ์  ๋ฐ ๋‚ด์šฉ 3 ์ œ 2 ์žฅ ์ด ๋ก  4 2.1 ํ•จ์ •์šฉ ํˆฌ๊ด‘๋“ฑ 4 2.2 ์„ฑ๋Šฅ ๋ฐ ์š”๊ตฌ์‚ฌํ•ญ 7 ์ œ 3 ์žฅ ์„ค๊ณ„ ๋ฐ ์ œ์ž‘ 11 3.1 LED ๋ชจ๋“ˆ 11 3.1.1 ๊ด‘ํ•™๊ณ„ 12 3.1.2 ๊ตฌ๋™ํšŒ๋กœ 17 3.1.3 ๋ฐฉ์—ด์„ค๊ณ„ 23 3.2 LED ํˆฌ๊ด‘๋“ฑ 27 ์ œ 4 ์žฅ ์‹คํ—˜ ๋ฐ ๋ถ„์„ 29 4.1 ์ „๊ธฐ์  ํŠน์„ฑ 29 4.2 ๊ด‘ํ•™์  ํŠน์„ฑ 31 4.3 ํ™˜๊ฒฝ์  ํŠน์„ฑ 37 ์ œ 5 ์žฅ ๊ฒฐ ๋ก  40 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 4
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