13 research outputs found

    Inverse problems for dynamic structures using iterative system condensation

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€,2007.Maste

    ๊ฐ€์ƒ ๊ตญ๊ฐ€์˜ ์‹œ๊ฐํ™”๋ฅผ ํ†ตํ•œ ์šฐํšŒ์  ํ˜„์‹ค๋น„ํŒ์— ๊ด€ํ•œ ์—ฐ๊ตฌ - ๋ณธ์ธ์˜ ์ž‘์—…์„ ์ค‘์‹ฌ์œผ๋กœ -

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์„œ์–‘ํ™”๊ณผ, 2015. 8. ์œค๋™์ฒœ.๋‚˜๋Š” ๋™์‹œ๋Œ€์˜ ํ˜„์‹ค์—์„œ ์ผ์–ด๋‚˜๋Š” ์‚ฌ๊ฑด๊ณผ ์‚ฌ๊ณ , ๊ทธ๋ฆฌ๊ณ  ํ˜„์žฌ ๋‚ด๊ฐ€ ์‚ด๊ณ  ์žˆ๋Š” ์‚ฌํšŒ์˜ ์ฒด๊ณ„์™€ ๊ตฌ์กฐ์— ๊ด€์‹ฌ์ด ๋งŽ๋‹ค. ์ด๋Ÿฌํ•œ ๊ด€์‹ฌ์€ ๊ทธ๊ฒƒ์„ ๊ด€์ฐฐํ•˜๋Š” ๊ฒƒ์—์„œ๋ถ€ํ„ฐ ์‹œ์ž‘๋˜๋Š”๋ฐ, ์ฃผ๋กœ ๋งค์Šค์ปด์„ ํ†ตํ•ด ๊ฐ„์ ‘์ ์œผ๋กœ ๊ฒฝํ—˜ํ•œ ๋‚ด์šฉ์ด ๋Œ€๋ถ€๋ถ„์ด๋‹ค. ๋งค์ผ ์Ÿ์•„์ ธ ๋‚˜์˜ค๋Š” ๋ณด๋„์ž๋ฃŒ ์ค‘ ํŠนํžˆ ์ฃผ๋ชฉํ•˜๋Š” ๋ถ€๋ถ„์€ ์ธ๊ฐ„์˜ ํ–‰๋™์œผ๋กœ ์ธํ•ด ํŒŒ์ƒ๋˜๋Š” ๋ฒ”์ฃ„์  ์‚ฌ๊ฑด์ด๋‹ค. ์ด์™€ ๊ฐ™์€ ํ‰์•…ํ•œ ์‚ฌ๊ฑด์€ ๋‚˜์˜ ๊ด€์‹ฌ๊ณผ ํฅ๋ฏธ๋ฅผ ๋„๋Š” ๋™์‹œ์— ํ˜„์‹ค์— ๋Œ€ํ•œ ์‹ค๋ง์œผ๋กœ ์ด์–ด์ ธ ์‚ถ์„ ๋ฌด๊ธฐ๋ ฅํ•˜๊ฒŒ ํ•˜๋Š” ์ด์ค‘์ ์ธ ์—ญํ• ์„ ํ•œ๋‹ค. ๋‚˜๋Š” ์ด์™€ ๊ฐ™์€ ํ˜„์‹ค์˜ ๋ชจ์Šต์— ์‹ค๋งํ•˜์—ฌ ๋ฐฉ๊ด€ํ•˜๋Š” ๋Œ€์‹  ์ž‘์—…์œผ๋กœ ๋น„ํŒ์˜ ๋ชฉ์†Œ๋ฆฌ๋ฅผ ๋‚ด๊ณ ์ž ํ–ˆ๋‹ค. ํ˜„์žฌ ๋‚ด๊ฐ€ ์‚ด๊ณ  ์žˆ๋Š” ํ˜„์‹ค์˜ ๋ชจ์Šต๊ณผ ๋˜‘๊ฐ™์ด ๋‹ฎ์€ ๊ฐ€์ƒ์˜ ๊ตญ๊ฐ€๋ฅผ ๋งŒ๋“ค์–ด๋‚ด๊ณ , ์ž‘ํ’ˆ ์†์—์„œ ํ—ˆ๊ตฌ์  ์„ธ๊ณ„์˜ ๊ตฌ์กฐ์™€ ์ฒด๊ณ„์— ๋Œ€ํ•ด ๋น„ํŒํ•˜๊ณ , ํฌํ™”ํ™”ํ•˜๊ณ  ์กฐ๋กฑํ–ˆ๋‹ค. ์ด๊ฒƒ์€ ํ—ˆ๊ตฌ์˜ ์„ธ๊ณ„๋ผ๋Š” ์„ค์ •์„ ํ†ตํ•ด ์šฐํšŒ์ ์œผ๋กœ ํ˜„์‹ค์„ ๋น—๋Œ€์–ด ๋น„ํŒํ•˜๊ณ ์žํ•œ ์ „๋žต์œผ๋กœ, ํ˜„์‹ค์„ ์ง์ ‘์ ์œผ๋กœ ๋น„ํŒํ–ˆ์„ ๋•Œ๋ณด๋‹ค ๋‹ค์–‘ํ•œ ์ธต์œ„์˜ ๋น„ํŒ์˜ ํšจ๊ณผ๋ฅผ ๋‚ด๊ธฐ ์œ„ํ•ด ๊ณ ์•ˆ๋œ ๊ฒƒ์ด๋‹ค. ์ž‘ํ’ˆ ์†์˜ ๊ฐ€์ƒ ๊ตญ๊ฐ€๋Š” ํ˜„์‹ค์˜ ๊ฑฐ์šธ์ด๋ฏธ์ง€์ฒ˜๋Ÿผ ํ˜„์‹ค๊ณผ ๋งž๋‹ฟ์•„ ์žˆ๋‹ค. ๋•Œ๋ฌธ์— ํ—ˆ๊ตฌ์˜ ์„ธ๊ณ„๋ฅผ ๊ตฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ง€๊ธˆ, ์šฐ๋ฆฌ์˜ ํ˜„์‹ค์„ ๋ฉด๋ฐ€ํžˆ ๊ด€์ฐฐํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋‚˜๋Š” ํ˜„์‹ค์—์„œ ์ผ์–ด๋‚˜๋Š” ์‚ฌ๊ฑด๊ณผ ์‚ฌ๊ณ ์— ๋Œ€ํ•ด ๊ด€์ฐฐํ•˜๊ณ , ๊ทธ๊ฒƒ์„ ๊ธฐ๋กํ•œ ๊ฐ์ข… ๊ธฐ๋ก๋ฌผ๋“ค์„ ์ˆ˜์ง‘ํ•˜๊ธฐ ์‹œ์ž‘ํ–ˆ๋‹ค. ์ด๋ ‡๊ฒŒ ์ˆ˜์ง‘๋œ ์ž๋ฃŒ๋“ค์€ ํ•ญ๋ชฉ๋ณ„๋กœ ๋ถ„๋ฅ˜ํ•˜๊ณ  ์ •๋ฆฌ๋˜์–ด, ๊ฐ€์ƒ์˜ ์ด์•ผ๊ธฐ๋กœ ์žฌ๊ตฌ์„ฑ๋˜์—ˆ๋‹ค. ๋‚˜๋Š” ๊ฐ€์ƒ์˜ ๊ตญ๊ฐ€๋ฅผ ์ž„์˜๋กœ DIVERLAND๋ผ ์ด๋ฆ„ ์ง“๊ณ  ๊ตญ๊ฐ€์˜ ์ฒด๊ณ„, ์‚ฌํšŒ๊ตฌ์กฐ, ๊ตฌ์„ฑ์›๋“ค์˜ ์ด์•ผ๊ธฐ ๋“ฑ์— ๋Œ€ํ•ด ๊ธ€์„ ์ผ๋‹ค. ๊ธ€๋กœ ์ž‘์„ฑ๋œ ๊ฐ€์ƒ์˜ ๊ตญ๊ฐ€๋ฅผ ์‹œ๊ฐํ™”ํ•˜๋Š” ๊ฒƒ์ด ์ž‘์—…์˜ ํ•ต์‹ฌ์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ธ€์ด ๊ทธ๋ฆผ์œผ๋กœ ๋ณ€ํ™˜๋˜๋Š” ๊ณผ์ •์—์„œ ์ข€ ๋” ์ž์œ ๋กญ๊ฒŒ ์ƒ์ƒ๋ ฅ์ด ๊ฐœ์ž…ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋“œ๋กœ์ž‰์˜ ๋ฐฉ์‹์„ ์„ ํƒํ•˜์˜€๋‹ค. ๋“œ๋กœ์ž‰์˜ ๊ณผ์ •์—์„œ ์‹œ๊ฐํ™”๋ฅผ ์œ„ํ•œ ๊ณ„ํš๊ณผ ์ „๋žต์ด ๋ชจ๋‘ ์„ธ์›Œ์ง€๊ธฐ ๋•Œ๋ฌธ์— ์ „์ฒด ์ž‘์—…๊ณผ์ •์—์„œ ๋งค์šฐ ์ค‘์š”ํ•œ ๋ถ€๋ถ„์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ณ„ํš๋œ ๋“œ๋กœ์ž‰์„ ๋ฐ”ํƒ•์œผ๋กœ ์—ฌ๋Ÿฌ ๋งค์ฒด๋กœ ๊ตฌํ˜„ํ•˜๊ณ , ์ „์ฒด์˜ ์ž‘์—… ๊ณผ์ •์—์„œ ํŒŒ์ƒ๋œ ๋‹ค์–‘ํ•œ ๊ฒฐ๊ณผ๋ฌผ๋“ค์„ ์•„์นด์ด๋น™ ํ•˜๋Š” ๊ฒƒ์ด ์ž‘์—…์˜ ๊ธฐ๋ณธ ๊ตฌ์กฐ๋‹ค. ๊ฐ€์ƒ ๊ตญ๊ฐ€์˜ ๋ณต์žกํ•˜๊ณ  ๋‹ค์˜์ ์ธ ์„ฑ๊ฒฉ์„ ํšจ๊ณผ์ ์œผ๋กœ ๋‚˜ํƒ€๋‚ด๊ธฐ ์œ„ํ•ด ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์ „๋žต์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๋Œ€๋ฆฝ๋œ ์ƒํƒœ๊ฐ€ ๋™์‹œ์— ์กด์žฌํ•˜๋Š” ์–‘๊ฐ€์  ์ƒํ™ฉ์„ ๋“œ๋Ÿฌ๋‚ด๊ธฐ ์œ„ํ•œ ์—ญ์„ค์  ํ‘œํ˜„๊ณผ ๋ฐ˜์–ด์  ํ‘œํ˜„, ์ƒ์ง•๊ณผ ์•Œ๋ ˆ๊ณ ๋ฆฌ์˜ ํ˜ผ์šฉ ๋“ฑ์ด ๊ทธ ์˜ˆ๋‹ค. ๋˜ํ•œ ๊ทธ ์ž์ฒด๋กœ ๋น„๋…ผ๋ฆฌ์ ์ด๊ณ  ๋ถˆํ•ฉ๋ฆฌํ•œ ๊ตญ๊ฐ€์ฒด๊ณ„๋ฅผ ๋…ผ๋ฆฌ์ ์œผ๋กœ ๊ทธ๋Ÿด์‹ธํ•˜๊ฒŒ ๋ณด์ด๊ฒŒ ํ•˜๊ธฐ ์œ„ํ•œ ์†์ž„์ˆ˜์˜ ๋ฐฉ๋ฒ•์œผ๋กœ ์ž์—ฐ, ๊ณผํ•™, ๊ฑด์ถ• ๋“ฑ์˜ ๊ตฌ์กฐ๋ฅผ ์ฐจ์šฉํ•˜์˜€๋‹ค. ์กฐํ˜•์ ์ธ ์ธก๋ฉด์œผ๋กœ๋Š”, ๋จผ์ € ๊ฐ•๋ฐ•์ ์ธ ๋Œ€์นญ๊ณผ ๊ท ํ˜•์˜ ๊ตฌ๋„๋ฅผ ์‚ฌ์šฉํ•˜๊ณ  ์ ์ฐจ ๊ทธ๊ฒƒ์ด ๋ณ€ํ˜•๋˜๋Š” ๋ชจ์Šต์„ ๋ณด์—ฌ์คŒ์œผ๋กœ ํ˜„์‹ค์˜ ๊ตฌ์กฐ์™€ ์ฒด๊ณ„์˜ ๊ฒฌ๊ณ ํ•จ, ์—„๊ฒฉํ•จ์— ๋Œ€ํ•œ ํšŒ์˜์  ์ž…์žฅ์„ ๋“œ๋Ÿฌ๋‚ด๊ณ ์ž ํ–ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์†Œ๊ทน์ ์ธ ์›๊ทผ๋ฒ•๊ณผ ๋„์‹์ ์ธ ๋ช…์•”๋ฒ•์„ ์‚ฌ์šฉํ•ด ํ™”๋ฉด์„ ํ‰๋ฉด์ ์œผ๋กœ ๊ตฌ์„ฑํ•จ์œผ๋กœ์จ ์ด์•ผ๊ธฐ์˜ ๊ฐ€์ƒ์„ฑ, ํ—ˆ๊ตฌ์„ฑ์„ ๊ฐ•์กฐํ•˜๊ณ ์ž ํ–ˆ๋‹ค. ๋˜ํ•œ ์žฅ์‹์ ์ธ ํ˜•ํƒœ์™€ ์žฌ๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํ™”๋ฉด ์†์˜ ์ž”ํ˜นํ•œ ํ˜•์ƒ์„ ์ˆจ๊ธฐ๊ณ , ํ•œ ๋ฒˆ์— ๊ทธ๊ฒƒ์„ ํŒŒ์•…ํ•˜๊ธฐ ํž˜๋“ค๋„๋ก ํ•˜์˜€๋‹ค. ์ด๊ฒƒ์€ ์ถ”์•…ํ•œ ์‚ฌํšŒ์˜ ์ด๋ฉด(๏งง้ข)์— ์ ‘๊ทผํ•˜๊ธฐ ํž˜๋“ค๋„๋ก ๊ทธ๋Ÿด๋“ฏํ•˜๊ฒŒ ๋ณด์ด๋Š” ์—ฌ๋Ÿฌ ๊ฒน์˜ ๋ฐฉ์–ด๋ง‰์„ ์Œ“์•„ ์‚ฌ๋žŒ๋“ค์„ ํ˜ผ๋ž€์Šค๋Ÿฝ๊ฒŒ ํ•˜๋Š” ํ˜„์‹ค์˜ ๋ชจ์Šต์„ ์ž‘ํ’ˆ์˜ ํ˜•์‹์œผ๋กœ ๊ฐ€์ ธ์˜จ ๊ฒƒ์ด๋‹ค. ๋‚˜๋Š” ํ˜„์‹ค์˜ ๋ชจ์ˆœ๋œ ์ƒํ™ฉ์„ ์ž‘ํ’ˆ์˜ ํ˜•์‹์œผ๋กœ ๋ณด์—ฌ์คŒ์œผ๋กœ์จ ํ˜„์‹ค์„ ์šฐํšŒ์ ์œผ๋กœ ๋น„ํŒํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค.โ… . ์„œ๋ก  1 โ…ก. ๊ฐ€์ƒ์˜ ์„ธ๊ณ„ 4 1. ๋น„ํŒ์  ํ˜„์‹ค ์ธ์‹ 4 2. ํ˜„์‹ค ์† ์‚ฌ๊ฑด์˜ ์ˆ˜์ง‘ 8 3. ์žฌ๊ตฌ์„ฑ๋œ ์ด์•ผ๊ธฐ 11 โ…ข. ์ด์•ผ๊ธฐ์˜ ์‹œ๊ฐํ™” 21 1. ์‹œ๊ฐํ™”์˜ ๋‹จ๊ณ„ 21 2. ์–‘๊ฐ€์  ํ‘œํ˜„์„ ์œ„ํ•œ ๋ฐฉ๋ฒ•๋“ค 28 3. ๊ตฌ์กฐ์˜ ์ฐจ์šฉ 36 โ…ฃ. ์šฐํšŒ์  ํ˜„์‹ค๋น„ํŒ์˜ ํ‘œํ˜„ 45 1. ๊ฐ•๋ฐ•์  ํ‘œํ˜„: ๋Œ€์นญ๊ณผ ๊ท ํ˜• 45 2. ํ‰๋ฉด์  ๊ตฌ์„ฑ: ์›๊ทผ๊ณผ ์ƒ‰์ฑ„ 50 3. ์žฅ์‹์  ์š”์†Œ: ํ˜•ํƒœ์™€ ์žฌ๋ฃŒ 54 โ…ค. ๊ฒฐ๋ก  60 ๊ทธ๋ฆผ๋ชฉ๋ก 63 ์ฐธ๊ณ ๋ฌธํ—Œ 67 Abstract 69Maste

    Study on the multi-level substructuring scheme and system condensation for the large-scaled structural dynamic analysis

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    ์ปดํ“จํ„ฐ ์„ฑ๋Šฅ์˜ ์ง€์†์ ์ธ ๋ฐœ์ „์œผ๋กœ ์ธํ•˜์—ฌ ์œ ํ•œ ์š”์†Œ๋ฒ•์€ ๋ณต์žกํ•œ ๊ตฌ์กฐ๋ฌผ์˜ ํ•ด์„๊ณผ ํ†ตํ•ฉ์˜ ์ค‘์š”ํ•œ ๋ถ€๋ถ„์„ ์ฐจ์ง€ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ์ปดํ“จํ„ฐ ๋ฉ”๋ชจ๋ฆฌ์™€ ์—ฐ์‚ฐ ์†๋„๊ฐ€ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ์‹œ์Šคํ…œ์ด ๊ฐ€์ง€๋Š” ๋™์  ๊ฑฐ๋™์˜ ์ž์„ธํ•œ ๋ฌ˜์‚ฌ๋ฅผ ์œ„ํ•ด ๋ณด๋‹ค ํฐ ๊ทœ๋ชจ์˜ ํ•ด์„ ๋ชจ๋ธ์ด ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋Œ€ํ˜• ์‹œ์Šคํ…œ์œผ๋กœ๋ถ€ํ„ฐ ์‹ ๋ขฐ๋„ ๋†’์€ ํ•ด์„๊ฒฐ๊ณผ๋ฅผ ์–ป๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋ณด๋‹ค ํฐ ๊ทœ๋ชจ์˜ ์ „์‚ฐ ์ž์›๊ณผ ์—ฐ์‚ฐ ์‹œ๊ฐ„์ด ์š”๊ตฌ๋œ๋‹ค. ์ถ•์†Œ ์‹œ์Šคํ…œ ๊ธฐ๋ฒ•์€ ์ „์‚ฐ ์ž์›์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•  ์ˆ˜ ์žˆ๋Š” ์ค‘์š”ํ•œ ๊ธฐ์ˆ ๋กœ ๊ฐ๊ด‘๋ฐ›๊ณ  ์žˆ๊ณ  ๋‹ค์–‘ํ•œ ์ถ•์†Œ ์‹œ์Šคํ…œ ๊ธฐ๋ฒ•๋“ค์ด ์ œ์•ˆ๋˜์–ด์™”๋‹ค. ์ถ•์†Œ ์‹œ์Šคํ…œ ๊ธฐ๋ฒ•์€ ๊ฐ•์„ฑ ํ–‰๋ ฌ๊ณผ ์งˆ๋Ÿ‰ํ–‰๋ ฌ์„ ์ด์šฉํ•˜์—ฌ ์ €์ฐจ ๊ณ ์œ  ๋ชจ๋“œ๋ฅผ ๊ทผ์‚ฌํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์‹ ๋ขฐํ•  ๋งŒํ•œ ์ถ•์†Œ ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ฃผ์ž์œ ๋„๋ฅผ ์ ์ ˆํ•˜๊ฒŒ ์„ ์ •ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ธฐ์กด์˜ ์ฃผ์ž์œ ๋„ ์„ ์ • ๊ธฐ๋ฒ•๋“ค์€ ์—ฐ์‚ฐ์˜ ํšจ์œจ์„ฑ๊ณผ ํ•ด์„์˜ ์ •ํ™•์„ฑ์„ ๋™์‹œ์— ๋‹ด๋ณดํ•˜๋Š”๋ฐ ์žˆ์–ด์„œ ๋ฌธ์ œ์ ์ด ์กด์žฌํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ธฐ์กด์— ์ œ์•ˆ๋œ 2๋‹จ๊ณ„ ์ถ•์†Œ๊ธฐ๋ฒ•์„ ๋ฐ˜๋ณต์  ๊ฐœ์„ ๋œ ์‹œ์Šคํ…œ ์ถ•์†Œ ๊ธฐ๋ฒ•์„ ์ ์šฉํ•˜์—ฌ ์ค‘๊ฐ„ ์ฃผํŒŒ์ˆ˜ ๋Œ€์—ญ์—์„œ์˜ ์ •ํ™•๋„๊นŒ์ง€ ํ™•๋ณดํ•˜๋ฉด์„œ ํšจ์œจ์„ฑ์„ ๊ฐœ์„ ํ•˜๋Š” ๋ฐฉ์•ˆ์„ ๋ชจ์ƒ‰ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ ˆ์  ๋‹จ์œ„ 2๋‹จ๊ณ„ ์ถ•์†Œ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ด ๊ธฐ๋ฒ•์€ ๋‘ ๋‹จ๊ณ„๋กœ ์ด๋ฃจ์–ด์ง€๋Š”๋ฐ ์ฒซ ๋‹จ๊ณ„์—์„œ๋Š” ์ ˆ์  ๋‹จ์œ„์˜ ์—๋„ˆ์ง€ ํ‰๊ฐ€์ž๋ฅผ ํ†ตํ•ด์„œ ์ฃผ ์ ˆ์ ์„ ์„ ์ •ํ•˜๊ณ  ์„ ์ •๋œ ์ ˆ์ ์— ์—ฐ๊ณ„๋œ ์ž์œ ๋„๋กœ ๊ตฌ์„ฑ๋œ 1๋‹จ๊ณ„ ์ถ•์†Œ ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ•œ๋‹ค. ๋‹ค์Œ ๋‹จ๊ณ„์—์„œ๋Š” ์ด์ „ ๋‹จ๊ณ„์—์„œ ๊ตฌ์ถ•๋œ ์ถ•์†Œ ์‹œ์Šคํ…œ์— ์ˆœ์ฐจ์  ์†Œ๊ฑฐ๋ฒ•์„ ์ ์šฉํ•˜์—ฌ ์ตœ์ข…์ ์ธ ์ฃผ์ž์œ ๋„๋ฅผ ์„ ์ •ํ•œ๋‹ค. ์ด ๊ธฐ๋ฒ•์„ ํ†ตํ•˜์—ฌ ์ „์‚ฐ ์†Œ์š” ๋น„์šฉ์„ ํšจ๊ณผ์ ์œผ๋กœ ์ค„์ด๋ฉด์„œ ๊ด€์‹ฌ ์ฃผํŒŒ์ˆ˜ ์ „์ฒด์— ์žˆ์–ด์„œ ๋†’์€ ์ •ํ™•๋„๋ฅผ ๋ณด์žฅํ•œ๋‹ค. ๋น„๋ก ์ถ•์†Œ ์‹œ์Šคํ…œ์ด ์ •ํ™•ํ•œ ๊ณ ์œ ์น˜ ํ•ด์„์„ ๋ณด์žฅํ•˜๋”๋ผ๋„ ๋Œ€ํ˜• ์‹œ์Šคํ…œ์— ์ ์šฉํ•˜๋Š”๋ฐ ๋ช‡ ๊ฐ€์ง€ ๋ฌธ์ œ๊ฐ€ ๋‚จ์•„์žˆ๋‹ค. ์ฃผ์ž์œ ๋„์˜ ์„ ์ •์ด ์ง€์—ฝ์ ์ด๊ฑฐ๋‚˜ ์ €์ฐจ ๋ชจ๋“œ๋ฅผ ๊ณผ๋„ํ•˜๊ฒŒ ๊ฐ•์กฐํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋ฐœ์ƒํ•˜๊ณ  ๊ฐ„ํ˜น ์ค‘์š”ํ•œ ๋ชจ๋“œ๊ฐ€ ์ œ์™ธ๋˜๋Š” ๋“ฑ์˜ ๋ฌธ์ œ๋“ค์ด ๋ฐœ์ƒ๋œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋Œ€ํ˜• ์‹œ์Šคํ…œ์— ์ง์ ‘ ์ ์šฉํ•˜๋Š”๋ฐ ์žˆ์–ด์„œ ๋ฌด์‹œ ๋ชปํ•  ๊ทœ๋ชจ์˜ ์ „์‚ฐ์ž์›์ด ์š”๊ตฌ๋œ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ์ ์€ ๋ถ€๊ตฌ์กฐํ™” ๊ธฐ๋ฒ•์„ ์ถ•์†Œ ์‹œ์Šคํ…œ ๊ธฐ๋ฒ•๊ณผ ์—ฐ๋™ํ•จ์œผ๋กœ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ธฐ์กด์— ๋ณด๊ณ ๋œ ๋ถ€๊ตฌ์กฐํ™” ๊ธฐ๋ฒ•๊ณผ ์—ฐ๋™ํ•œ ์ถ•์†Œ ์‹œ์Šคํ…œ ๊ธฐ๋ฒ•์„ ๋ฐ˜๋ณต์  ์—ฐ์‚ฐ๊ณผ์ •์„ ํ†ตํ•˜์—ฌ ๊ฐœ์„ ํ•˜๋Š” ๋ฐฉ์•ˆ์„ ์‚ดํŽด๋ณธ๋‹ค. ๊ฐœ์„ ๊ณผ์ •์€ ๋ฐ˜๋ณต์  ๊ฐœ์„ ๋œ ์‹œ์Šคํ…œ ์ถ•์†Œ ๊ธฐ๋ฒ•(IIRS)๊ณผ ์œ ์‚ฌ์„ฑ์„ ๊ฐ€์ง„๋‹ค. ์ถ•์†Œ ์‹œ์Šคํ…œ ๊ธฐ๋ฒ•์˜ ํšจ์œจ์„ฑ์„ ๊ฐœ์„ ํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์˜ ์—ฐ์žฅ์„ ์—์„œ ๋‹ค๋‹จ๊ณ„ ์‹œ์Šคํ…œ ์ถ•์†Œ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ด ๊ธฐ๋ฒ•์€ ๊ธฐ๋ณธ์ ์œผ๋กœ 2๋‹จ๊ณ„ ์ถ•์†Œ๊ธฐ๋ฒ•์„ ๊ทผ๊ฐ„์œผ๋กœ ํ•œ๋‹ค. ์ „์ฒด ์‹œ์Šคํ…œ์„ ๊ทธ๋ž˜ํ”„ ๋ถ„ํ•  ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•œ ์ž๋™ํ™” ๊ณผ์ •์„ ํ†ตํ•ด ๊ณ„์ธต์ ์œผ๋กœ ๋‹ค์ˆ˜์˜ ๋ถ€๊ตฌ์กฐ๋กœ ๋ถ„ํ• ํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ ๊ฐ ๋ถ€๊ตฌ์กฐ์˜ ๋ถ„์ ˆํ™”๋œ ๊ณ ์œ ์น˜ ๋ฌธ์ œ๋ฅผ 2๋‹จ๊ณ„ ์ถ•์†Œ ๊ธฐ๋ฒ•๊ณผ IIRS๊ธฐ๋ฒ•์œผ๋กœ ์ถ•์†Œํ•˜๊ณ  ์ถ•์†Œ๋œ ๋ถ€๊ตฌ์กฐ์˜ ์‹œ์Šคํ…œ์„ ํ•ฉ์„ฑํ•˜์—ฌ ์ตœ์ข…์ ์ธ ์ถ•์†Œ ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ•œ๋‹ค. ์ด ๊ธฐ๋ฒ•์„ ๋™์  ๊ตฌ์กฐ ๋ฌธ์ œ์˜ ๋ชจ๋‹ฌ ํ•ด์„๊ณผ Newmark ์‹œ๊ฐ„ ์ ๋ถ„ ๊ธฐ๋ฒ•์„ ์ ์šฉํ•œ ๊ณผ๋„ ์‹œ๊ฐ„ ์‘๋‹ต ํ•ด์„, ์ฃผํŒŒ์ˆ˜ ์‘๋‹ตํ•ด์„์— ์ ์šฉํ•˜์˜€๋‹ค. ๋‹ค๋‹จ๊ณ„ ์‹œ์Šคํ…œ ์ถ•์†Œ ๊ธฐ๋ฒ•์˜ ์ •ํ™•๋„๋ฅผ ๋†’์ด๊ธฐ ์œ„ํ•ด์„œ ํ–ฅ์ƒ๋œ ๋‹ค๋‹จ๊ณ„ ๋ถ€๊ตฌ์กฐํ™” ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์—ฌ๋Ÿฌ ๋‹จ๊ณ„์˜ ๊ณ„์ธต์ ์œผ๋กœ ๋ถ„ํ• ๋œ ๋ถ€๊ตฌ์กฐ๊ฐ€ ๊ฐ€์ง€๋Š” ์žฅ์ ์— ๊ธฐ์ดˆํ•˜์—ฌ ์ด ๊ธฐ๋ฒ•์€ ๋ณด๋‹ค ๋„“์€ ๊ด€์‹ฌ ์ฃผํŒŒ์ˆ˜ ์˜์—ญ์—์„œ ๋งŒ์กฑํ• ๋งŒํ•œ ์ •ํ™•๋„๋ฅผ ๊ฐ€์ง€๊ณ  ์†Œ์ˆ˜์˜ ์ •๋ณด๋งŒ์„ ์ด์šฉํ•˜์—ฌ ์ถ•์†Œ ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ•œ๋‹ค. ํŠนํžˆ ๊ฒฝ๊ณ„์˜์—ญ์—์„œ์˜ ์œ ์—ฐ๋„๋ฅผ ๊ฒฐ์ •ํ•˜๋Š” ๊ฐ€์†๋„์˜ ์˜ํ–ฅ๋ ฅ์„ ํ‘œํ˜„ํ•˜๋Š” ๋™์  ๊ฐ€์ •์„ ๋„์ž…ํ•˜์—ฌ ๊ณ ์ • ๊ฒฝ๊ณ„์—์„œ ๊ตฌํ•œ ๋ชจ๋“œ์˜ ์ •ํ™•๋„๋ฅผ ๋†’์˜€๋‹ค. ๊ธฐ์กด์˜ ๋ฐฉ๋ฒ•๋“ค๊ณผ ๋‹ฌ๋ฆฌ ๋ถ€๊ตฌ์กฐ๋“ค์ด ๊ฐ€์ง€๋Š” ๋™์  ํŠน์„ฑ์„ ์ถ•์†Œ๋œ ์‹œ์Šคํ…œ์˜ ์žฌํ•ด์„ ๊ณผ์ •์ด๋‚˜ ๊ณผ๋„ํ•œ ์ˆ˜์˜ ์ถ•์†Œ ๊ธฐ์ €์˜ ์ถ”๊ฐ€ ์—†์ด ํ‘œํ˜„ํ•˜๋ฉด์„œ ๊ณ ์œ ์น˜ ํ•ด์„ ์ •ํ™•๋„๋ฅผ ํšจ์œจ์„ฑ์˜ ์ €ํ•˜๋ฅผ ์ตœ์†Œํ™” ํ•˜์˜€๋‹ค. ์ตœ์ข…์ ์œผ๋กœ ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์˜ ํšจ์œจ์„ฑ์„ ๋‹ค์–‘ํ•œ ์ˆ˜์น˜ ์˜ˆ์ œ๋“ค์„ ํ†ตํ•˜์—ฌ ๊ฒ€์ฆํ•œ๋‹ค.Ever-increasing capabilities of digital computer have enabled finite element method to serve as a practical tool for the analysis and synthesis of complex structures. As the speed and memory of computer increase, more and more large-scaled models are constructed for the detailed and accurate description of the system. a huge size of computational resources and a large amount of computing time is still needed for a reliable solution which represents the detailed description of dynamic behavior in large-scale problem. Reduced system method have been considered as important technique to resolve computational resource problem. For a few decades, various approximate techniques have been developed to calculate the eigenvalues in a reduced manner. Reduction system method approximates the lower eigenmodes that represent the global behavior of the structures. In order to construct reliable reduced systems it is essential to select the proper primary degrees of freedom (PDOFs). However, traditional schemes for selecting the PDOFs have not satisfied the efficiency of time cost and solution accuracy at the same time. In the previous study, a two-level condensation scheme (TLCS) proposed for selection scheme of the PDOFs. The present study proposes improve previous TLCS with combination of the iterated improved reduced system method (IIRS) to increase accuracy of the higher modes intermediate range. And also, this study proposes a node-based two-level condensation scheme. This scheme consists of two-steps. In the first step, the candidate region is selected for constructing the first reduced system by energy estimation in node-level. In the second step, PDOFs are selected by sequential elimination method from DOFs linked to the selected nodes through the first step. The proposed method saves computational cost efficiently and recovers eigenvalues of the full system with high accuracy in overall frequency range of interests. Although the reduced system can present accurate eigenvalue and eigenvector, they have several troubles for applying to the large scale problem. The selection of PDOFs might be localized and the eigenvalue prediction might emphasize excessively the lower modes or lose the important modes unless the PDOFs are selected satisfactory. Sometimes, it takes considerable amount of computing time to construct a reduced system in large-scale problem. These troubles in constructing reduced system can be avoided by applying reduction scheme in substructuring scheme. This study presents iterative enhancement of the previous TLCS combined with sucturcturing scheme applying interation process which similar with IIRS technique. The efforts to advance an efficiency of reduction scheme leads a development of the multi-level system condensation (MLSC) which is initially based on the TLCS method. In first step, the global system is recursively partitioned into a hierarchy of substructures by the graph partitioning program. And next, each uncoupled sub eigenvalue problems condensate by TLCS. After assembly process of each reduced sub-eigenvalue problem, final reduced system is constructed. The MLSC is applied into the modal analysis, the direct time response analysis and the frequency response analysis of structural dynamic problems. For the transient time response analysis, the MLSC is combined with the Newmarks time integration scheme. In order to accelerating the accuracy of the MLSC method, an enhanced multi-level substructuring scheme is presented. Based on the advantage of substructuring on several levels, the method constructs a reduced system of much smaller number of unknowns which still yields satisfactory accuracy over a wide frequency range of interest. Using the first order dynamic approximation, an enhanced methodology for synthesizing the modes obtained with a fixed interface component is proposed. The proposed approach can be used to improve the accuracy of calculated eigenproperties by utilizing the dynamic aspect of component modes without re-analyzing the reduced system or calculating additional normal modes of substructures. Finally, the efficiency of the proposed method is demonstrated by numerical examples.Docto

    ๊ฐ„์„ธํฌ์•”์˜ ์•ฝ๋ฌผ์ €ํ•ญ์„ฑ์— ๋Œ€์‘ํ•œ ์ž๊ทน๋ฐ˜์‘์„ฑ Pt ๋‚˜๋…ธํด๋Ÿฌ์Šคํ„ฐ ์กฐ๋ฆฝ์ฒด์˜ ํ•ฉ์„ฑ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€, 2017. 2. ํ˜„ํƒํ™˜.One of the major conundrums of cancer therapy is chemoresistance. A considerable resistance of tumors to conventional chemotherapeutic agents compromises the response rate, and therefore, the overall efficacy of established medical treatments against the disease. Small-sized platinum (Pt) nanocluster has been spotlighted as an alternative anticancer agent for its potency against cancer cells by virtue of the leached Pt ions. However, nonspecific treatment of Pt nanocluster would also incur toxicity to normal tissues, and this potential risk calls for an intricate delivery system, which would enhance the Pt nanocluster with preferential tumor-targeting and controlled Pt activation and release. In an effort to further the therapeutic potential of Pt nanocluster with a coordinated delivery system and to overcome the limitations of conventional chemotherapy, we synthesize a Pt-nanocluster assembly (Pt-NA) consisting of polymeric ligands with pH-sensitivity and cancer cell-targeting peptide encapsulating Pt nanoclusters. The Pt-NA is designed in such a way that it would remain latent in circulation, target the sporadic cancer cell subpopulations, release small Pt nanoclusters in acidic subcellular regions via pH-responsive dissociation, and eventually induce damage to diseased cells. The efficacy of Pt-NA as a prospective anticancer agent is demonstrated in vitro and in vivo in hepatocellular carcinoma (HCC) model, which is often associated with the resistance to Cisplatin, a Pt-based commercial anticancer agent.Chapter 1. Introduction 1 Chapter 2. Experimental Section 4 2.1. Chemicals. 4 2.2 Preparation of Pt Nanocluster Assembly (Pt-NA). 5 2.3. Characterization 8 2.4. In Vitro Studies 8 2.5 In Vivo Studies 10 Chapter 3. Result and Discussion 12 3.1. Design and Synthesis of Pt-NA 12 3.1.1. Ultrasmall Pt Nanoclusters 12 3.1.2. Functional Polymeric Ligands 13 3.1.3. Properties of Pt-NA 14 3.2. In vitro Efficacy and Cellular Uptake of Pt-NA 15 3.3 In vivo Therapeutic Effect and Distribution of Pt-NA 16 Chapter 4. Conclusion 17 References 31 ๊ตญ๋ฌธ ์ดˆ๋ก 35Maste

    Multi-agent path planning in adversarial environments using mixed integer linear programming

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2011.2. ๊น€ํ˜„์ง„.Maste

    ๋ฐฉํ–ฅ์„ฑ ์ „๊ธฐ๊ฐ•ํŒ์—์„œ ๊ณ ์˜จ์†Œ๋‘” ์Šน์˜จ์œจ์ด 2์ฐจ ์žฌ๊ฒฐ์ •๋ฆฝ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ

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    Master๋ฐฉํ–ฅ์„ฑ ์ „๊ธฐ๊ฐ•ํŒ์€ 2 ์ฐจ ์žฌ๊ฒฐ์ •์— ์˜ํ•œ Goss texture (110) [001] ๋กœ ์ธํ•˜์—ฌ ์••์—ฐ ๋ฐฉํ–ฅ์œผ๋กœ ์šฐ์ˆ˜ํ•œ ์ž๊ธฐ์  ํŠน์„ฑ์„ ๊ฐ€์ง„๋‹ค. ์ด๋Ÿฌํ•œ 2 ์ฐจ ์žฌ๊ฒฐ์ •์€ 1์ฐจ ์žฌ๊ฒฐ์ •๋ฆฝ ํฌ๊ธฐ ๋ฐ ์ตœ์ข… ์†Œ๋‘”์˜ ์Šน์˜จ ์†๋„์— ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค. ์ด๋Ÿฌํ•œ ํšจ๊ณผ๋ฅผ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์˜จ๋„์—์„œ 1 ์ฐจ ์žฌ๊ฒฐ์ • ์†Œ๋‘” ์ฒ˜๋ฆฌ๋œ ์‹œํŽธ์œผ๋กœ ์ตœ์ข… ์†Œ๋‘” ์Šน์˜จ ์†๋„๋ฅผ ๋ณ€๊ฒฝํ•˜์—ฌ 1 ์ฐจ ์žฌ๊ฒฐ์ •๋ฆฝ ํฌ๊ธฐ์™€ ๋‘๊ป˜ ๋ฐฉํ–ฅ์œผ๋กœ ์„์ถœ๋ฌผ์˜ ๋†๋„๋ฅผ ๋ถ„์„ ํ•˜์˜€๋‹ค. 2 ์ฐจ ์žฌ๊ฒฐ์ •์€ ์‹œํŽธ์˜ ํ‘œ๋ฉด์ธต ์„์ถœ๋ฌผ์ด ๋ถ„ํ•ด๋˜์–ด 0ppm์— ๊ทผ์ ‘ํ–ˆ์„ ๋•Œ ์ฆ‰, ์–ต์ œ๋ ฅ์ด ์ƒ์‹ค๋˜์—ˆ์„ ๋•Œ ๋ฐœ์ƒํ•˜๊ธฐ ์‹œ์ž‘ํ•˜๋ฉฐ, ์ด๋Ÿฌํ•œ ์‹œ์ ์€ ์ตœ์ข… ์†Œ๋‘”์˜ ์Šน์˜จ ์†๋„์— ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค. ์ด ๋•Œ, ๊ฒฐ์ •๋ฆฝ ์„ฑ์žฅ์˜ ๊ตฌ๋™๋ ฅ์œผ๋กœ ๋Œ€ํ‘œ๋˜๋Š” 1 ์ฐจ ์žฌ๊ฒฐ์ •๋ฆฝ ํฌ๊ธฐ ์—ญ์‹œ ์ตœ์ข…์ ์ธ 2 ์ฐจ ์žฌ๊ฒฐ์ •์˜ ํŠน์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค. ๋”ฐ๋ผ์„œ ์›ํ•˜๋Š” ์ž๊ธฐ ํŠน์„ฑ์„ ์–ป๊ธฐ ์œ„ํ•ด์„œ๋Š” 1 ์ฐจ ์žฌ๊ฒฐ์ •๋ฆฝ ํฌ๊ธฐ์™€ ์ตœ์ข… ์†Œ๋‘”์˜ ์Šน์˜จ ์†๋„์˜ ์กฐํ•ฉ์„ ์ตœ์ ํ™”ํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค.Grain-oriented electrical steel has excellent soft magnetic characteristics in the rolling direction with Goss texture (110)[001] due to secondary recrystallization. This secondary recrystallization is affected by the primary grain size and the heating rate of final annealing. To investigate this effect, specimens that had been annealed at various temperatures to achieve primary recrystallization were subjected to a final annealing process at various heating rates of final annealing, then primary grain size and precipitates in the thickness direction were analyzed. Secondary recrystallization started to occur when the precipitate of the surface layer had decomposed and had approached a content of 0 ppm, and the temperature at which the secondary recrystallization occurs depended on heating rate of final annealing. At this time, primary grain size represented by the driving force of grain growth also affects the final secondary recrystallization characteristics. Therefore, to obtain the desired the magnetic properties, the combination of primary grain size and heating rate of final annealing must be optimized
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