JFE.dvi

Size: px
Start display at page:

Download "JFE.dvi"

Transcription

1 ,, Department of Civil Engineering, Chuo University Kasuga , Bunkyo-ku, Tokyo , JAPAN SATO KOGYO CO., LTD , Nihonbashi-Honcho 4-Chome, Chuo-ku, Tokyo , Japan Abstract This paper presents a numerical technique to predict a soft stratum ahead of an excavating face of a tunnel. The functional method is a parameter identification of the elastic property which is important coefficient at the actual site. The parameter identification is an useful technique in the reverse analysis to determine an unknown parameter using the observed data. The parameter identification is utilized to minimize the difference between the computed and observed displacements to determine the Young s modulus of the ground. In order to solve the minimization problem, the conjugate gradient method is applied. As a numerical model, the 3-D linear elastic body with the finite element method is used to excavate the natural ground and to identify the Young s modulus ahead of a tunnel face. Using the 3-D tunnel, the displacement of the axial direction can be considered. Key words: Parameter identification, 3-D tunnel, Excavation, Finite element method, Conjugate gradient method 1 2 σ,j ρb i = 0 (1) 1

2 σ, b i, ρ ε = 1 2 (u i,j + u j,i ) (2) ε u i σ = Dkl e ε kl (3) Dkl e Dkl e = λδ δ kl + µ(δ ik δ jl + δ il δ jk ) (4) δ λ µ λ = νe (1 2ν)(1 + ν) µ = E 2(1 + ν) (5) (6) E ν S S U S T u i =û i on S U, (7) t i = σ n j = ˆt i on S T, (8) û i ˆt i n i 3 K αiβk = ˆΓ αi = N αi 4 F V K αiβk u βk = ˆΓ αi (9) V (N α,j D e kln β,l )dv (10) (N α ρ ˆb i )dv (N α ˆt i )ds S T (11) F (1) u = du (1) (0) σ = dσ (0) (1) (0) (1) σ = σ + dσ p 2 p (2) u = du (1) (2) (1) (2) u (1) + σ = σ + dσ

3 n 1. n =0 2. u (0) i = du (0) i σ (0) = dσ (0) 3. σ (0) p (n+1) αi 4. p (n+1) αi 5. p (n+1) αi 6. du (n+1) i dσ (n+1) 7. u (n+1) i σ (n+1) 8. σ (n+1) p (n+2) αi 9. n = n +1 4 p αi p (n+1) αi = V N α,j σ (n) dv, (12) σ (n) 5 T T Z X B A α β B Y T = cos α cos β 0 cos α sin β 0 sin α 0 0 cos α cos β 0 cos α sin β 0 sin α. 3

4 Z EXCAVATION Y X 6 J J 1 J = 2 (u u ) T Q(u u )dv (13) V u u m E {P } T = {E} T = {E 1,E 2,E 3, E m }, (14) 1. P (0), ε j i =0 2. u(p ) (0) J (0) 3. [ ] (0) u(p ) 4. {d} (0) = { J 5. α = } (0) [ ] T = u(p ) (u(p ) u(p ) ) {d} T [ u(p ) { } {d} T J ] T [ 6. P (i+1) = P (i) + αd (i) u(p ) ] {d} 7. u(p ) (i+1) J (i+1) 8. [ ] (i+1) u(p ) 4

5 9. β = ψ{ J } (i+1), ψ{ J } (i), { { J J } (i+1)! } (i)! 10. {d} (i+1) = { J } (i+1) + β{d} (i) 11. J (i+1) <ε j 12. i = i +1 [5] 7 : ( ) F : ( ) 1. E init F 4. F = γh γ h E init Excavation Computational domain Natural ground Tunnel face 5

6 A (x1,y1,z1) A (x2,y2,z2) Excavation Origin Origin B (x1,y1,z1) B (x2,y2,z2) (a) (b) dux = x2 - x1 duy = y2 - y1 duz = z2 - z1 A dux B duz Excavation dux duy (c) [kn/m 2 ] [kn/m 2 ] 4.0[m] 6

7 (a) (b) [kn/m 2 ] 0m E1 10m E3 E2 16m 14m 12m E4 20m E(kN/m 2 ) E ( 0m - 12m ) E (12m - 14m ) E (14m - 16m ) E (16m - 20m ) 7

8 m - 12m ( E1 ) 12m - 14m ( E2 ) 14m - 16m ( E3 ) 16m - 20m ( E4 ) Youngs modulus [kn/m2] Iteration [kn/m 2 ] 0m E1 10m E3 E2 16m 14m 12m E4 20m Young s modulus Stratum E(kN/m 2 ) E Hard ( 0m - 12m ) E Hard (12m - 14m ) E Soft (14m - 16m ) E Hard (16m - 20m ) 8

9 m - 12m ( E1 ) 12m - 14m ( E2 ) 14m - 16m ( E3 ) 16m - 20m ( E4 ) Youngs modulus [kn/m2] Iteration 9 F = γh 100m 105m Domain1 Domain2 30m 0m 200m 0m 200m Sand Stone Figure 11. Soft layer 9

10 (a) (b) D(m) h(m) γ(t/m 3 ) F (kn/m 2 ) [kn/m 2 ] [kn/m 2 ] 0m E4 E3 E2 200m 105m 150m E1 130m 110m :Hardground Measured point : 100m E(kN/m 2 ) E Hard ( 0m - 110m ) E Hard (110m - 130m ) E Hard (130m - 150m ) E Hard (150m - 200m ) 10

11 Youngs modulus [kn/m2] m - 110m ( E1 ) 110m - 130m ( E2 ) 130m - 150m ( E3 ) 150m - 200m ( E4 ) Iteration [kn/m 2 ] 0m E4 E3 E2 200m 105m 150m E1 130m 110m :Hardground : Soft ground Measured point : 100m E(kN/m 2 ) E ( 0m - 110m ) E (110m - 130m ) E (130m - 150m ) E (150m - 200m ) 11

12 m - 110m ( E1 ) 110m - 130m ( E2 ) 130m - 150m ( E3 ) 150m - 200m ( E4 ) Youngs modulus [kn/m2] Iteration 10 References [1] Sakurai, H. and Tanigawa, M., Study of some problems on the back analysis of measured displacements in tunnelling, Vol.1, Journal of Geotechnical Engineering, pp85-94(1990). [2] Sugimoto, M., Sakurazawa, M. and Kageyama, S., Three dimensional reverse analysis on ground properties with time-dependence, 9th International Congress on Rock Mechanics, Vol.2, pp (1999). [3] Y.M. Hsieh and A.J. Whittle, A computational strategy for solving three-dimensional tunnel excavation problems, Second M.I.T. Conference on Computational Fluid and Solid Mechanics (2003). [4] Nojima, K. and Kawahara, M., Mesh Generation of Three-dimensional Underground Tunnels Based on the Three-Dimensional Delaunay Tetrahedration, Vol.5, Journal of Applied Mechanics JSCE, pp (2002). [5] R.Fletcher and C.M.Reeves., Function Minimization by Conjugate Gradients, Computer J., pp (1964). 12

28 Horizontal angle correction using straight line detection in an equirectangular image

28 Horizontal angle correction using straight line detection in an equirectangular image 28 Horizontal angle correction using straight line detection in an equirectangular image 1170283 2017 3 1 2 i Abstract Horizontal angle correction using straight line detection in an equirectangular image

More information

Title 混合体モデルに基づく圧縮性流体と移動する固体の熱連成計算手法 Author(s) 鳥生, 大祐 ; 牛島, 省 Citation 土木学会論文集 A2( 応用力学 ) = Journal of Japan Civil Engineers, Ser. A2 (2017), 73 Issue

Title 混合体モデルに基づく圧縮性流体と移動する固体の熱連成計算手法 Author(s) 鳥生, 大祐 ; 牛島, 省 Citation 土木学会論文集 A2( 応用力学 ) = Journal of Japan Civil Engineers, Ser. A2 (2017), 73 Issue Title 混合体モデルに基づく圧縮性流体と移動する固体の熱連成計算手法 Author(s) 鳥生, 大祐 ; 牛島, 省 Citation 土木学会論文集 A2( 応用力学 ) = Journal of Japan Civil Engineers, Ser. A2 (2017), 73 Issue Date 2017 URL http://hdl.handle.net/2433/229150 Right

More information

9. 05 L x P(x) P(0) P(x) u(x) u(x) (0 < = x < = L) P(x) E(x) A(x) P(L) f ( d EA du ) = 0 (9.) dx dx u(0) = 0 (9.2) E(L)A(L) du (L) = f (9.3) dx (9.) P

9. 05 L x P(x) P(0) P(x) u(x) u(x) (0 < = x < = L) P(x) E(x) A(x) P(L) f ( d EA du ) = 0 (9.) dx dx u(0) = 0 (9.2) E(L)A(L) du (L) = f (9.3) dx (9.) P 9 (Finite Element Method; FEM) 9. 9. P(0) P(x) u(x) (a) P(L) f P(0) P(x) (b) 9. P(L) 9. 05 L x P(x) P(0) P(x) u(x) u(x) (0 < = x < = L) P(x) E(x) A(x) P(L) f ( d EA du ) = 0 (9.) dx dx u(0) = 0 (9.2) E(L)A(L)

More information

第5章 偏微分方程式の境界値問題

第5章 偏微分方程式の境界値問題 October 5, 2018 1 / 113 4 ( ) 2 / 113 Poisson 5.1 Poisson ( A.7.1) Poisson Poisson 1 (A.6 ) Γ p p N u D Γ D b 5.1.1: = Γ D Γ N 3 / 113 Poisson 5.1.1 d {2, 3} Lipschitz (A.5 ) Γ D Γ N = \ Γ D Γ p Γ N Γ

More information

untitled

untitled - 37 - - 3 - (a) (b) 1) 15-1 1) LIQCAOka 199Oka 1999 ),3) ) -1-39 - 1) a) b) i) 1) 1 FEM Zhang ) 1 1) - 35 - FEM 9 1 3 ii) () 1 Dr=9% Dr=35% Tatsuoka 19Fukushima and Tatsuoka19 5),) Dr=35% Dr=35% Dr=3%1kPa

More information

1 [1, 2, 3, 4, 5, 8, 9, 10, 12, 15] The Boston Public Schools system, BPS (Deferred Acceptance system, DA) (Top Trading Cycles system, TTC) cf. [13] [

1 [1, 2, 3, 4, 5, 8, 9, 10, 12, 15] The Boston Public Schools system, BPS (Deferred Acceptance system, DA) (Top Trading Cycles system, TTC) cf. [13] [ Vol.2, No.x, April 2015, pp.xx-xx ISSN xxxx-xxxx 2015 4 30 2015 5 25 253-8550 1100 Tel 0467-53-2111( ) Fax 0467-54-3734 http://www.bunkyo.ac.jp/faculty/business/ 1 [1, 2, 3, 4, 5, 8, 9, 10, 12, 15] The

More information

1 Fig. 1 Extraction of motion,.,,, 4,,, 3., 1, 2. 2.,. CHLAC,. 2.1,. (256 ).,., CHLAC. CHLAC, HLAC. 2.3 (HLAC ) r,.,. HLAC. N. 2 HLAC Fig. 2

1 Fig. 1 Extraction of motion,.,,, 4,,, 3., 1, 2. 2.,. CHLAC,. 2.1,. (256 ).,., CHLAC. CHLAC, HLAC. 2.3 (HLAC ) r,.,. HLAC. N. 2 HLAC Fig. 2 CHLAC 1 2 3 3,. (CHLAC), 1).,.,, CHLAC,.,. Suspicious Behavior Detection based on CHLAC Method Hideaki Imanishi, 1 Toyohiro Hayashi, 2 Shuichi Enokida 3 and Toshiaki Ejima 3 We have proposed a method for

More information

: u i = (2) x i Smagorinsky τ ij τ [3] ij u i u j u i u j = 2ν SGS S ij, (3) ν SGS = (C s ) 2 S (4) x i a u i ρ p P T u ν τ ij S c ν SGS S csgs

: u i = (2) x i Smagorinsky τ ij τ [3] ij u i u j u i u j = 2ν SGS S ij, (3) ν SGS = (C s ) 2 S (4) x i a u i ρ p P T u ν τ ij S c ν SGS S csgs 15 C11-4 Numerical analysis of flame propagation in a combustor of an aircraft gas turbine, 4-6-1 E-mail: tominaga@icebeer.iis.u-tokyo.ac.jp, 2-11-16 E-mail: ntani@iis.u-tokyo.ac.jp, 4-6-1 E-mail: itoh@icebeer.iis.u-tokyo.ac.jp,

More information

k m m d2 x i dt 2 = f i = kx i (i = 1, 2, 3 or x, y, z) f i σ ij x i e ij = 2.1 Hooke s law and elastic constants (a) x i (2.1) k m σ A σ σ σ σ f i x

k m m d2 x i dt 2 = f i = kx i (i = 1, 2, 3 or x, y, z) f i σ ij x i e ij = 2.1 Hooke s law and elastic constants (a) x i (2.1) k m σ A σ σ σ σ f i x k m m d2 x i dt 2 = f i = kx i (i = 1, 2, 3 or x, y, z) f i ij x i e ij = 2.1 Hooke s law and elastic constants (a) x i (2.1) k m A f i x i B e e e e 0 e* e e (2.1) e (b) A e = 0 B = 0 (c) (2.1) (d) e

More information

第62巻 第1号 平成24年4月/石こうを用いた木材ペレット

第62巻 第1号 平成24年4月/石こうを用いた木材ペレット Bulletin of Japan Association for Fire Science and Engineering Vol. 62. No. 1 (2012) Development of Two-Dimensional Simple Simulation Model and Evaluation of Discharge Ability for Water Discharge of Firefighting

More information

N cos s s cos ψ e e e e 3 3 e e 3 e 3 e

N cos s s cos ψ e e e e 3 3 e e 3 e 3 e 3 3 5 5 5 3 3 7 5 33 5 33 9 5 8 > e > f U f U u u > u ue u e u ue u ue u e u e u u e u u e u N cos s s cos ψ e e e e 3 3 e e 3 e 3 e 3 > A A > A E A f A A f A [ ] f A A e > > A e[ ] > f A E A < < f ; >

More information

TOP URL 1

TOP URL   1 TOP URL http://amonphys.web.fc2.com/ 1 30 3 30.1.............. 3 30.2........................... 4 30.3...................... 5 30.4........................ 6 30.5.................................. 8 30.6...............................

More information

19 Systematization of Problem Solving Strategy in High School Mathematics for Improving Metacognitive Ability

19 Systematization of Problem Solving Strategy in High School Mathematics for Improving Metacognitive Ability 19 Systematization of Problem Solving Strategy in High School Mathematics for Improving Metacognitive Ability 1105402 2008 2 4 2,, i Abstract Systematization of Problem Solving Strategy in High School

More information

149 (Newell [5]) Newell [5], [1], [1], [11] Li,Ryu, and Song [2], [11] Li,Ryu, and Song [2], [1] 1) 2) ( ) ( ) 3) T : 2 a : 3 a 1 :

149 (Newell [5]) Newell [5], [1], [1], [11] Li,Ryu, and Song [2], [11] Li,Ryu, and Song [2], [1] 1) 2) ( ) ( ) 3) T : 2 a : 3 a 1 : Transactions of the Operations Research Society of Japan Vol. 58, 215, pp. 148 165 c ( 215 1 2 ; 215 9 3 ) 1) 2) :,,,,, 1. [9] 3 12 Darroch,Newell, and Morris [1] Mcneil [3] Miller [4] Newell [5, 6], [1]

More information

n (1.6) i j=1 1 n a ij x j = b i (1.7) (1.7) (1.4) (1.5) (1.4) (1.7) u, v, w ε x, ε y, ε x, γ yz, γ zx, γ xy (1.8) ε x = u x ε y = v y ε z = w z γ yz

n (1.6) i j=1 1 n a ij x j = b i (1.7) (1.7) (1.4) (1.5) (1.4) (1.7) u, v, w ε x, ε y, ε x, γ yz, γ zx, γ xy (1.8) ε x = u x ε y = v y ε z = w z γ yz 1 2 (a 1, a 2, a n ) (b 1, b 2, b n ) A (1.1) A = a 1 b 1 + a 2 b 2 + + a n b n (1.1) n A = a i b i (1.2) i=1 n i 1 n i=1 a i b i n i=1 A = a i b i (1.3) (1.3) (1.3) (1.1) (ummation convention) a 11 x

More information

all.dvi

all.dvi 72 9 Hooke,,,. Hooke. 9.1 Hooke 1 Hooke. 1, 1 Hooke. σ, ε, Young. σ ε (9.1), Young. τ γ G τ Gγ (9.2) X 1, X 2. Poisson, Poisson ν. ν ε 22 (9.) ε 11 F F X 2 X 1 9.1: Poisson 9.1. Hooke 7 Young Poisson G

More information

IV (2)

IV (2) COMPUTATIONAL FLUID DYNAMICS (CFD) IV (2) The Analysis of Numerical Schemes (2) 11. Iterative methods for algebraic systems Reima Iwatsu, e-mail : iwatsu@cck.dendai.ac.jp Winter Semester 2007, Graduate

More information

A Higher Weissenberg Number Analysis of Die-swell Flow of Viscoelastic Fluids Using a Decoupled Finite Element Method Iwata, Shuichi * 1/Aragaki, Tsut

A Higher Weissenberg Number Analysis of Die-swell Flow of Viscoelastic Fluids Using a Decoupled Finite Element Method Iwata, Shuichi * 1/Aragaki, Tsut A Higher Weissenberg Number Analysis of Die-swell Flow of Viscoelastic Fluids Using a Decoupled Finite Element Method Iwata, Shuichi * 1/Aragaki, Tsutomu * 1/Mori, Hideki * 1 Ishikawa, Satoshi * 1/Shin,

More information

all.dvi

all.dvi 5,, Euclid.,..,... Euclid,.,.,, e i (i =,, ). 6 x a x e e e x.:,,. a,,. a a = a e + a e + a e = {e, e, e } a (.) = a i e i = a i e i (.) i= {a,a,a } T ( T ),.,,,,. (.),.,...,,. a 0 0 a = a 0 + a + a 0

More information

, 3, STUDY ON IMPORTANCE OF OPTIMIZED GRID STRUCTURE IN GENERAL COORDINATE SYSTEM 1 2 Hiroyasu YASUDA and Tsuyoshi HOSHINO

, 3, STUDY ON IMPORTANCE OF OPTIMIZED GRID STRUCTURE IN GENERAL COORDINATE SYSTEM 1 2 Hiroyasu YASUDA and Tsuyoshi HOSHINO , 3, 2012 9 STUDY ON IMPORTANCE OF OPTIMIZED GRID STRUCTURE IN GENERAL COORDINATE SYSTEM 1 2 Hiroyasu YASUDA and Tsuyoshi HOSHINO 1 950-2181 2 8050 2 950-2181 2 8050 Numerical computation of river flows

More information

note1.dvi

note1.dvi (1) 1996 11 7 1 (1) 1. 1 dx dy d x τ xx x x, stress x + dx x τ xx x+dx dyd x x τ xx x dyd y τ xx x τ xx x+dx d dx y x dy 1. dx dy d x τ xy x τ x ρdxdyd x dx dy d ρdxdyd u x t = τ xx x+dx dyd τ xx x dyd

More information

(MIRU2008) HOG Histograms of Oriented Gradients (HOG)

(MIRU2008) HOG Histograms of Oriented Gradients (HOG) (MIRU2008) 2008 7 HOG - - E-mail: katsu0920@me.cs.scitec.kobe-u.ac.jp, {takigu,ariki}@kobe-u.ac.jp Histograms of Oriented Gradients (HOG) HOG Shape Contexts HOG 5.5 Histograms of Oriented Gradients D Human

More information

n-jas09.dvi

n-jas09.dvi Vol. 9 (2009 12 ), No. 03-091211 JASCOME CREEP ANALYSIS DISCONTINUOUS ROCK MASS AROUND UNDERGROUND CAVERN 1) 2) 3) Takakuni TATSUMI, Hidenori YOSHIDA and Masumi FUJIWARA 1) ( 761-0396 2217-20, E-mail:

More information

(2004 ) 2 (A) (B) (C) 3 (1987) (1988) Shimono and Tachibanaki(1985) (2008) , % 2 (1999) (2005) 3 (2005) (2006) (2008)

(2004 ) 2 (A) (B) (C) 3 (1987) (1988) Shimono and Tachibanaki(1985) (2008) , % 2 (1999) (2005) 3 (2005) (2006) (2008) ,, 23 4 30 (i) (ii) (i) (ii) Negishi (1960) 2010 (2010) ( ) ( ) (2010) E-mail:fujii@econ.kobe-u.ac.jp E-mail:082e527e@stu.kobe-u.ac.jp E-mail:iritani@econ.kobe-u.ac.jp 1 1 16 (2004 ) 2 (A) (B) (C) 3 (1987)

More information

Study on Throw Accuracy for Baseball Pitching Machine with Roller (Study of Seam of Ball and Roller) Shinobu SAKAI*5, Juhachi ODA, Kengo KAWATA and Yu

Study on Throw Accuracy for Baseball Pitching Machine with Roller (Study of Seam of Ball and Roller) Shinobu SAKAI*5, Juhachi ODA, Kengo KAWATA and Yu Study on Throw Accuracy for Baseball Pitching Machine with Roller (Study of Seam of Ball and Roller) Shinobu SAKAI*5, Juhachi ODA, Kengo KAWATA and Yuichiro KITAGAWA Department of Human and Mechanical

More information

Visit Japan Campaign OD OD 18 UNWTO 19 OD JNTO ODUNWTO 1 1

Visit Japan Campaign OD OD 18 UNWTO 19 OD JNTO ODUNWTO 1 1 UNWTO OD 2 FURUYA, Hideki 1 LCC 1 2 OD 1 2 OD 3 4 5 6 7 8 9 10 11 /1 GDP M. H. Mohd Hanafiah and M. F. Mohd Harun 12 GDP 1 13 Vol.15 No.4 2013 Winter 041 3 3.1 6222011 Visit Japan Campaign2003521 10119

More information

No δs δs = r + δr r = δr (3) δs δs = r r = δr + u(r + δr, t) u(r, t) (4) δr = (δx, δy, δz) u i (r + δr, t) u i (r, t) = u i x j δx j (5) δs 2

No δs δs = r + δr r = δr (3) δs δs = r r = δr + u(r + δr, t) u(r, t) (4) δr = (δx, δy, δz) u i (r + δr, t) u i (r, t) = u i x j δx j (5) δs 2 No.2 1 2 2 δs δs = r + δr r = δr (3) δs δs = r r = δr + u(r + δr, t) u(r, t) (4) δr = (δx, δy, δz) u i (r + δr, t) u i (r, t) = u i δx j (5) δs 2 = δx i δx i + 2 u i δx i δx j = δs 2 + 2s ij δx i δx j

More information

v v = v 1 v 2 v 3 (1) R = (R ij ) (2) R (R 1 ) ij = R ji (3) 3 R ij R ik = δ jk (4) i=1 δ ij Kronecker δ ij = { 1 (i = j) 0 (i

v v = v 1 v 2 v 3 (1) R = (R ij ) (2) R (R 1 ) ij = R ji (3) 3 R ij R ik = δ jk (4) i=1 δ ij Kronecker δ ij = { 1 (i = j) 0 (i 1. 1 1.1 1.1.1 1.1.1.1 v v = v 1 v 2 v 3 (1) R = (R ij ) (2) R (R 1 ) ij = R ji (3) R ij R ik = δ jk (4) δ ij Kronecker δ ij = { 1 (i = j) 0 (i j) (5) 1 1.1. v1.1 2011/04/10 1. 1 2 v i = R ij v j (6) [

More information

OHP.dvi

OHP.dvi 7 2010 11 22 1 7 http://www.sml.k.u-tokyo.ac.jp/members/nabe/lecture2010 nabe@sml.k.u-tokyo.ac.jp 2 1. 10/ 4 2. 10/18 3. 10/25 2, 3 4. 11/ 1 5. 11/ 8 6. 11/15 7. 11/22 8. 11/29 9. 12/ 6 skyline 10. 12/13

More information

技術研究所 研究所報 No.80

技術研究所 研究所報 No.80 Calculating Temperatures in Concrete Elements Exposed to Fire by Hideto Saito and Takeshi Morita Abstract Six concrete-filled steel tube column specimens without fire protection measures were subjected

More information

~nabe/lecture/index.html 2

~nabe/lecture/index.html 2 2001 12 13 1 http://www.sml.k.u-tokyo.ac.jp/ ~nabe/lecture/index.html nabe@sml.k.u-tokyo.ac.jp 2 1. 10/ 4 2. 10/11 3. 10/18 1 4. 10/25 2 5. 11/ 1 6. 11/ 8 7. 11/15 8. 11/22 9. 11/29 10. 12/ 6 1 11. 12/13

More information

Chebyshev Schrödinger Heisenberg H = 1 2m p2 + V (x), m = 1, h = 1 1/36 1 V (x) = { 0 (0 < x < L) (otherwise) ψ n (x) = 2 L sin (n + 1)π x L, n = 0, 1, 2,... Feynman K (a, b; T ) = e i EnT/ h ψ n (a)ψ

More information

n ξ n,i, i = 1,, n S n ξ n,i n 0 R 1,.. σ 1 σ i .10.14.15 0 1 0 1 1 3.14 3.18 3.19 3.14 3.14,. ii 1 1 1.1..................................... 1 1............................... 3 1.3.........................

More information

.2 ρ dv dt = ρk grad p + 3 η grad (divv) + η 2 v.3 divh = 0, rote + c H t = 0 dive = ρ, H = 0, E = ρ, roth c E t = c ρv E + H c t = 0 H c E t = c ρv T

.2 ρ dv dt = ρk grad p + 3 η grad (divv) + η 2 v.3 divh = 0, rote + c H t = 0 dive = ρ, H = 0, E = ρ, roth c E t = c ρv E + H c t = 0 H c E t = c ρv T NHK 204 2 0 203 2 24 ( ) 7 00 7 50 203 2 25 ( ) 7 00 7 50 203 2 26 ( ) 7 00 7 50 203 2 27 ( ) 7 00 7 50 I. ( ν R n 2 ) m 2 n m, R = e 2 8πε 0 hca B =.09737 0 7 m ( ν = ) λ a B = 4πε 0ħ 2 m e e 2 = 5.2977

More information

Stress Singularity Analysis at an Interfacial Corner Between Anisotropic Bimaterials Under Thermal Stress Yoshiaki NOMURA, Toru IKEDA*4 and Noriyuki M

Stress Singularity Analysis at an Interfacial Corner Between Anisotropic Bimaterials Under Thermal Stress Yoshiaki NOMURA, Toru IKEDA*4 and Noriyuki M Stress Singularity Analysis at an Interfacial Corner Between Anisotropic Bimaterials Under Thermal Stress Yoshiaki NOMURA, Toru IKEDA*4 and Noriyuki MIYAZAKI Department of Mechanical Engineering and Science,

More information

1 (Berry,1975) 2-6 p (S πr 2 )p πr 2 p 2πRγ p p = 2γ R (2.5).1-1 : : : : ( ).2 α, β α, β () X S = X X α X β (.1) 1 2

1 (Berry,1975) 2-6 p (S πr 2 )p πr 2 p 2πRγ p p = 2γ R (2.5).1-1 : : : : ( ).2 α, β α, β () X S = X X α X β (.1) 1 2 2005 9/8-11 2 2.2 ( 2-5) γ ( ) γ cos θ 2πr πρhr 2 g h = 2γ cos θ ρgr (2.1) γ = ρgrh (2.2) 2 cos θ θ cos θ = 1 (2.2) γ = 1 ρgrh (2.) 2 2. p p ρgh p ( ) p p = p ρgh (2.) h p p = 2γ r 1 1 (Berry,1975) 2-6

More information

all.dvi

all.dvi 29 4 Green-Lagrange,,.,,,,,,.,,,,,,,,,, E, σ, ε σ = Eε,,.. 4.1? l, l 1 (l 1 l) ε ε = l 1 l l (4.1) F l l 1 F 30 4 Green-Lagrange Δz Δδ γ = Δδ (4.2) Δz π/2 φ γ = π 2 φ (4.3) γ tan γ γ,sin γ γ ( π ) γ tan

More information

all.dvi

all.dvi 38 5 Cauchy.,,,,., σ.,, 3,,. 5.1 Cauchy (a) (b) (a) (b) 5.1: 5.1. Cauchy 39 F Q Newton F F F Q F Q 5.2: n n ds df n ( 5.1). df n n df(n) df n, t n. t n = df n (5.1) ds 40 5 Cauchy t l n mds df n 5.3: t

More information

20 Method for Recognizing Expression Considering Fuzzy Based on Optical Flow

20 Method for Recognizing Expression Considering Fuzzy Based on Optical Flow 20 Method for Recognizing Expression Considering Fuzzy Based on Optical Flow 1115084 2009 3 5 3.,,,.., HCI(Human Computer Interaction),.,,.,,.,.,,..,. i Abstract Method for Recognizing Expression Considering

More information

,,.,.,,.,.,.,.,,.,..,,,, i

,,.,.,,.,.,.,.,,.,..,,,, i 22 A person recognition using color information 1110372 2011 2 13 ,,.,.,,.,.,.,.,,.,..,,,, i Abstract A person recognition using color information Tatsumo HOJI Recently, for the purpose of collection of

More information

untitled

untitled 3 4 4 2.1 4 2.2 5 2.3 6 6 7 4.1 RC 7 4.2 RC 8 4.3 9 10 5.1 10 5.2 10 11 12 13-1 - Bond Behavior Between Corroded Rebar and Concrete Ema KATO* Mitsuyasu IWANAMI** Hiroshi YOKOTA*** Hajime ITO**** Fuminori

More information

日立金属技報 Vol.34

日立金属技報 Vol.34 Influence of Misorientation Angle between Adjacent Grains on Magnetization Reversal in Nd-Fe-B Sintered Magnet Tomohito Maki Rintaro Ishii Mitsutoshi Natsumeda Takeshi Nishiuchi Ryo Uchikoshi Masaaki Takezawa

More information

IPSJ SIG Technical Report Vol.2016-CE-137 No /12/ e β /α α β β / α A judgment method of difficulty of task for a learner using simple

IPSJ SIG Technical Report Vol.2016-CE-137 No /12/ e β /α α β β / α A judgment method of difficulty of task for a learner using simple 1 2 3 4 5 e β /α α β β / α A judgment method of difficulty of task for a learner using simple electroencephalograph Katsuyuki Umezawa 1 Takashi Ishida 2 Tomohiko Saito 3 Makoto Nakazawa 4 Shigeichi Hirasawa

More information

D v D F v/d F v D F η v D (3.2) (a) F=0 (b) v=const. D F v Newtonian fluid σ ė σ = ηė (2.2) ė kl σ ij = D ijkl ė kl D ijkl (2.14) ė ij (3.3) µ η visco

D v D F v/d F v D F η v D (3.2) (a) F=0 (b) v=const. D F v Newtonian fluid σ ė σ = ηė (2.2) ė kl σ ij = D ijkl ė kl D ijkl (2.14) ė ij (3.3) µ η visco post glacial rebound 3.1 Viscosity and Newtonian fluid f i = kx i σ ij e kl ideal fluid (1.9) irreversible process e ij u k strain rate tensor (3.1) v i u i / t e ij v F 23 D v D F v/d F v D F η v D (3.2)

More information

y = x x R = 0. 9, R = σ $ = y x w = x y x x w = x y α ε = + β + x x x y α ε = + β + γ x + x x x x' = / x y' = y/ x y' =

y = x x R = 0. 9, R = σ $ = y x w = x y x x w = x y α ε = + β + x x x y α ε = + β + γ x + x x x x' = / x y' = y/ x y' = y x = α + β + ε =,, ε V( ε) = E( ε ) = σ α $ $ β w ( 0) σ = w σ σ y α x ε = + β + w w w w ε / w ( w y x α β ) = α$ $ W = yw βwxw $β = W ( W) ( W)( W) w x x w x x y y = = x W y W x y x y xw = y W = w w

More information

untitled

untitled ( ) l 1991 1) 4) 5),6) 7) 8) 31) 39) 46) : () + +θ (c) l h A - : θ A () (d) 1 ε=/l=θ/cot 1(d) 1 () =tn( ) h + 1 u F m N F m =Ntn N N N F m N F m =Ntn N S α S1 R α+ R = tn( ) = tn = tn( + ) R R d = d ()

More information

H.Haken Synergetics 2nd (1978)

H.Haken Synergetics 2nd (1978) 27 3 27 ) Ising Landau Synergetics Fokker-Planck F-P Landau F-P Gizburg-Landau G-L G-L Bénard/ Hopfield H.Haken Synergetics 2nd (1978) (1) Ising m T T C 1: m h Hamiltonian H = J ij S i S j h i S

More information

7章 構造物の応答値の算定

7章 構造物の応答値の算定 (1) 2 (2) 5.4 5.8.4 2 5.2 (3) 1.8 1) 36 2) PS 3) N N PS 37 10 20m N G hg h PS N (1) G h G/G 0 h 3 1) G 0 PS PS 38 N V s G 0 40% Gh 1 S 0.11% G/G 0 h G/G 0 h H-D 2),3) R-O 4) 5),6),7) τ G 0 γ = 0 r 1 (

More information

Report98.dvi

Report98.dvi 1 4 1.1.......................... 4 1.1.1.......................... 7 1.1..................... 14 1.1.................. 1 1.1.4........................... 8 1.1.5........................... 6 1.1.6 n...........................

More information

第1章 微分方程式と近似解法

第1章 微分方程式と近似解法 April 12, 2018 1 / 52 1.1 ( ) 2 / 52 1.2 1.1 1.1: 3 / 52 1.3 Poisson Poisson Poisson 1 d {2, 3} 4 / 52 1 1.3.1 1 u,b b(t,x) u(t,x) x=0 1.1: 1 a x=l 1.1 1 (0, t T ) (0, l) 1 a b : (0, t T ) (0, l) R, u

More information

数値計算:有限要素法

数値計算:有限要素法 ( ) 1 / 61 1 2 3 4 ( ) 2 / 61 ( ) 3 / 61 P(0) P(x) u(x) P(L) f P(0) P(x) P(L) ( ) 4 / 61 L P(x) E(x) A(x) x P(x) P(x) u(x) P(x) u(x) (0 x L) ( ) 5 / 61 u(x) 0 L x ( ) 6 / 61 P(0) P(L) f d dx ( EA du dx

More information

TOP URL 1

TOP URL   1 TOP URL http://amonphys.web.fc.com/ 1 19 3 19.1................... 3 19.............................. 4 19.3............................... 6 19.4.............................. 8 19.5.............................

More information

鉄鋼協会プレゼン

鉄鋼協会プレゼン NN :~:, 8 Nov., Adaptive H Control for Linear Slider with Friction Compensation positioning mechanism moving table stand manipulator Point to Point Control [G] Continuous Path Control ground Fig. Positoining

More information

Fig. 2 Signal plane divided into cell of DWT Fig. 1 Schematic diagram for the monitoring system

Fig. 2 Signal plane divided into cell of DWT Fig. 1 Schematic diagram for the monitoring system Study of Health Monitoring of Vehicle Structure by Using Feature Extraction based on Discrete Wavelet Transform Akihisa TABATA *4, Yoshio AOKI, Kazutaka ANDO and Masataka KATO Department of Precision Machinery

More information

seminar0220a.dvi

seminar0220a.dvi 1 Hi-Stat 2 16 2 20 16:30-18:00 2 2 217 1 COE 4 COE RA E-MAIL: ged0104@srv.cc.hit-u.ac.jp 2004 2 25 S-PLUS S-PLUS S-PLUS S-code 2 [8] [8] [8] 1 2 ARFIMA(p, d, q) FI(d) φ(l)(1 L) d x t = θ(l)ε t ({ε t }

More information

DPA,, ShareLog 3) 4) 2.2 Strino Strino STRain-based user Interface with tacticle of elastic Natural ObjectsStrino 1 Strino ) PC Log-Log (2007 6)

DPA,, ShareLog 3) 4) 2.2 Strino Strino STRain-based user Interface with tacticle of elastic Natural ObjectsStrino 1 Strino ) PC Log-Log (2007 6) 1 2 1 3 Experimental Evaluation of Convenient Strain Measurement Using a Magnet for Digital Public Art Junghyun Kim, 1 Makoto Iida, 2 Takeshi Naemura 1 and Hiroyuki Ota 3 We present a basic technology

More information

Part () () Γ Part ,

Part () () Γ Part , Contents a 6 6 6 6 6 6 6 7 7. 8.. 8.. 8.3. 8 Part. 9. 9.. 9.. 3. 3.. 3.. 3 4. 5 4.. 5 4.. 9 4.3. 3 Part. 6 5. () 6 5.. () 7 5.. 9 5.3. Γ 3 6. 3 6.. 3 6.. 3 6.3. 33 Part 3. 34 7. 34 7.. 34 7.. 34 8. 35

More information

JKR Point loading of an elastic half-space 2 3 Pressure applied to a circular region Boussinesq, n =

JKR Point loading of an elastic half-space 2 3 Pressure applied to a circular region Boussinesq, n = JKR 17 9 15 1 Point loading of an elastic half-space Pressure applied to a circular region 4.1 Boussinesq, n = 1.............................. 4. Hertz, n = 1.................................. 6 4 Hertz

More information

Dirac 38 5 Dirac 4 4 γ µ p µ p µ + m 2 = ( p µ γ µ + m)(p ν γ ν + m) (5.1) γ = p µ p ν γ µ γ ν p µ γ µ m + mp ν γ ν + m 2 = 1 2 p µp ν {γ µ, γ ν } + m

Dirac 38 5 Dirac 4 4 γ µ p µ p µ + m 2 = ( p µ γ µ + m)(p ν γ ν + m) (5.1) γ = p µ p ν γ µ γ ν p µ γ µ m + mp ν γ ν + m 2 = 1 2 p µp ν {γ µ, γ ν } + m Dirac 38 5 Dirac 4 4 γ µ p µ p µ + m 2 p µ γ µ + mp ν γ ν + m 5.1 γ p µ p ν γ µ γ ν p µ γ µ m + mp ν γ ν + m 2 1 2 p µp ν {γ µ, γ ν } + m 2 5.2 p m p p µ γ µ {, } 10 γ {γ µ, γ ν } 2η µν 5.3 p µ γ µ + mp

More information

58 10

58 10 57 Multi-channel MAC Protocol with Multi-busytone in Ad-hoc Networks Masatoshi Fukushima*, Ushio Yamamoto* and Yoshikuni Onozato* Abstract Multi-channel MAC protocols for wireless ad hoc networks have

More information

Vol. 36, Special Issue, S 3 S 18 (2015) PK Phase I Introduction to Pharmacokinetic Analysis Focus on Phase I Study 1 2 Kazuro Ikawa 1 and Jun Tanaka 2

Vol. 36, Special Issue, S 3 S 18 (2015) PK Phase I Introduction to Pharmacokinetic Analysis Focus on Phase I Study 1 2 Kazuro Ikawa 1 and Jun Tanaka 2 Vol. 36, Special Issue, S 3 S 18 (2015) PK Phase I Introduction to Pharmacokinetic Analysis Focus on Phase I Study 1 2 Kazuro Ikawa 1 and Jun Tanaka 2 1 2 1 Department of Clinical Pharmacotherapy, Hiroshima

More information

A Study on Throw Simulation for Baseball Pitching Machine with Rollers and Its Optimization Shinobu SAKAI*5, Yuichiro KITAGAWA, Ryo KANAI and Juhachi

A Study on Throw Simulation for Baseball Pitching Machine with Rollers and Its Optimization Shinobu SAKAI*5, Yuichiro KITAGAWA, Ryo KANAI and Juhachi A Study on Throw Simulation for Baseball Pitching Machine with Rollers and Its Optimization Shinobu SAKAI*5, Yuichiro KITAGAWA, Ryo KANAI and Juhachi ODA Department of Human and Mechanical Systems Engineering,

More information

soturon.dvi

soturon.dvi 12 Exploration Method of Various Routes with Genetic Algorithm 1010369 2001 2 5 ( Genetic Algorithm: GA ) GA 2 3 Dijkstra Dijkstra i Abstract Exploration Method of Various Routes with Genetic Algorithm

More information

Auerbach and Kotlikoff(1987) (1987) (1988) 4 (2004) 5 Diamond(1965) Auerbach and Kotlikoff(1987) 1 ( ) ,

Auerbach and Kotlikoff(1987) (1987) (1988) 4 (2004) 5 Diamond(1965) Auerbach and Kotlikoff(1987) 1 ( ) , ,, 2010 8 24 2010 9 14 A B C A (B Negishi(1960) (C) ( 22 3 27 ) E-mail:fujii@econ.kobe-u.ac.jp E-mail:082e527e@stu.kobe-u.ac.jp E-mail:iritani@econ.kobe-u.ac.jp 1 1 1 2 3 Auerbach and Kotlikoff(1987) (1987)

More information

A Feasibility Study of Direct-Mapping-Type Parallel Processing Method to Solve Linear Equations in Load Flow Calculations Hiroaki Inayoshi, Non-member

A Feasibility Study of Direct-Mapping-Type Parallel Processing Method to Solve Linear Equations in Load Flow Calculations Hiroaki Inayoshi, Non-member A Feasibility Study of Direct-Mapping-Type Parallel Processing Method to Solve Linear Equations in Load Flow Calculations Hiroaki Inayoshi, Non-member (University of Tsukuba), Yasuharu Ohsawa, Member (Kobe

More information

IPSJ SIG Technical Report Vol.2014-CG-155 No /6/28 1,a) 1,2,3 1 3,4 CG An Interpolation Method of Different Flow Fields using Polar Inter

IPSJ SIG Technical Report Vol.2014-CG-155 No /6/28 1,a) 1,2,3 1 3,4 CG An Interpolation Method of Different Flow Fields using Polar Inter ,a),2,3 3,4 CG 2 2 2 An Interpolation Method of Different Flow Fields using Polar Interpolation Syuhei Sato,a) Yoshinori Dobashi,2,3 Tsuyoshi Yamamoto Tomoyuki Nishita 3,4 Abstract: Recently, realistic

More information

2002 11 21 1 http://www.sml.k.u-tokyo.ac.jp/members/nabe/lecture2002 http://www.sml.k.u-tokyo.ac.jp/members/nabe/lecture nabe@sml.k.u-tokyo.ac.jp 2 1. 10/10 2. 10/17 3. 10/24 4. 10/31 5. 11/ 7 6. 11/14

More information

SO(3) 7 = = 1 ( r ) + 1 r r r r ( l ) (5.17) l = 1 ( sin θ ) + sin θ θ θ ϕ (5.18) χ(r)ψ(θ, ϕ) l ψ = αψ (5.19) l 1 = i(sin ϕ θ l = i( cos ϕ θ l 3 = i ϕ

SO(3) 7 = = 1 ( r ) + 1 r r r r ( l ) (5.17) l = 1 ( sin θ ) + sin θ θ θ ϕ (5.18) χ(r)ψ(θ, ϕ) l ψ = αψ (5.19) l 1 = i(sin ϕ θ l = i( cos ϕ θ l 3 = i ϕ SO(3) 71 5.7 5.7.1 1 ħ L k l k l k = iϵ kij x i j (5.117) l k SO(3) l z l ± = l 1 ± il = i(y z z y ) ± (z x x z ) = ( x iy) z ± z( x ± i y ) = X ± z ± z (5.118) l z = i(x y y x ) = 1 [(x + iy)( x i y )

More information

Vol. 5, 29 39, 2016 Good/Virtue actions for competitive sports athlete Actions and Choices that receive praise Yo Sato Abstract: This paper focuses on

Vol. 5, 29 39, 2016 Good/Virtue actions for competitive sports athlete Actions and Choices that receive praise Yo Sato Abstract: This paper focuses on Vol. 5, 29 39, 2016 Good/Virtue actions for competitive sports athlete Actions and Choices that receive praise Yo Sato Abstract: This paper focuses on actions taken by athletes in competitive sports, building

More information

xx/xx Vol. Jxx A No. xx 1 Fig. 1 PAL(Panoramic Annular Lens) PAL(Panoramic Annular Lens) PAL (2) PAL PAL 2 PAL 3 2 PAL 1 PAL 3 PAL PAL 2. 1 PAL

xx/xx Vol. Jxx A No. xx 1 Fig. 1 PAL(Panoramic Annular Lens) PAL(Panoramic Annular Lens) PAL (2) PAL PAL 2 PAL 3 2 PAL 1 PAL 3 PAL PAL 2. 1 PAL PAL On the Precision of 3D Measurement by Stereo PAL Images Hiroyuki HASE,HirofumiKAWAI,FrankEKPAR, Masaaki YONEDA,andJien KATO PAL 3 PAL Panoramic Annular Lens 1985 Greguss PAL 1 PAL PAL 2 3 2 PAL DP

More information

Flow Around a Circular Cylinder with Tangential Blowing near a Plane Boundary (2nd Report, A Study on Unsteady Characteristics) Shimpei OKAYASU, Kotar

Flow Around a Circular Cylinder with Tangential Blowing near a Plane Boundary (2nd Report, A Study on Unsteady Characteristics) Shimpei OKAYASU, Kotar Flow Around a Circular Cylinder with Tangential Blowing near a Plane Boundary (2nd Report, A Study on Unsteady Characteristics) Shimpei OKAYASU, Kotaro SATO*4, Toshihiko SHAKOUCHI and Okitsugu FURUYA Department

More information

1 a b cc b * 1 Helioseismology * * r/r r/r a 1.3 FTD 9 11 Ω B ϕ α B p FTD 2 b Ω * 1 r, θ, ϕ ϕ * 2 *

1 a b cc b * 1 Helioseismology * * r/r r/r a 1.3 FTD 9 11 Ω B ϕ α B p FTD 2 b Ω * 1 r, θ, ϕ ϕ * 2 * 448 8542 1 e-mail: ymasada@auecc.aichi-edu.ac.jp 1. 400 400 1.1 10 1 1 5 1 11 2 3 4 656 2015 10 1 a b cc b 22 5 1.2 * 1 Helioseismology * 2 6 8 * 3 1 0.7 r/r 1.0 2 r/r 0.7 3 4 2a 1.3 FTD 9 11 Ω B ϕ α B

More information

微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 初版 1 刷発行時のものです.

微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます.   このサンプルページの内容は, 初版 1 刷発行時のものです. 微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. ttp://www.morikita.co.jp/books/mid/00571 このサンプルページの内容は, 初版 1 刷発行時のものです. i ii 014 10 iii [note] 1 3 iv 4 5 3 6 4 x 0 sin x x 1 5 6 z = f(x, y) 1 y = f(x)

More information

Optical Flow t t + δt 1 Motion Field 3 3 1) 2) 3) Lucas-Kanade 4) 1 t (x, y) I(x, y, t)

Optical Flow t t + δt 1 Motion Field 3 3 1) 2) 3) Lucas-Kanade 4) 1 t (x, y) I(x, y, t) http://wwwieice-hbkborg/ 2 2 4 2 -- 2 4 2010 9 3 3 4-1 Lucas-Kanade 4-2 Mean Shift 3 4-3 2 c 2013 1/(18) http://wwwieice-hbkborg/ 2 2 4 2 -- 2 -- 4 4--1 2010 9 4--1--1 Optical Flow t t + δt 1 Motion Field

More information

(1.2) T D = 0 T = D = 30 kn 1.2 (1.4) 2F W = 0 F = W/2 = 300 kn/2 = 150 kn 1.3 (1.9) R = W 1 + W 2 = = 1100 N. (1.9) W 2 b W 1 a = 0

(1.2) T D = 0 T = D = 30 kn 1.2 (1.4) 2F W = 0 F = W/2 = 300 kn/2 = 150 kn 1.3 (1.9) R = W 1 + W 2 = = 1100 N. (1.9) W 2 b W 1 a = 0 1 1 1.1 1.) T D = T = D = kn 1. 1.4) F W = F = W/ = kn/ = 15 kn 1. 1.9) R = W 1 + W = 6 + 5 = 11 N. 1.9) W b W 1 a = a = W /W 1 )b = 5/6) = 5 cm 1.4 AB AC P 1, P x, y x, y y x 1.4.) P sin 6 + P 1 sin 45

More information

1 n 1 1 2 2 3 3 3.1............................ 3 3.2............................. 6 3.2.1.............. 6 3.2.2................. 7 3.2.3........................... 10 4 11 4.1..........................

More information

Input image Initialize variables Loop for period of oscillation Update height map Make shade image Change property of image Output image Change time L

Input image Initialize variables Loop for period of oscillation Update height map Make shade image Change property of image Output image Change time L 1,a) 1,b) 1/f β Generation Method of Animation from Pictures with Natural Flicker Abstract: Some methods to create animation automatically from one picture have been proposed. There is a method that gives

More information

¼§À�ÍýÏÀ – Ê×ÎòÅŻҼ§À�¤È¥¹¥Ô¥ó¤æ¤é¤® - No.7, No.8, No.9

¼§À�ÍýÏÀ – Ê×ÎòÅŻҼ§À�¤È¥¹¥Ô¥ó¤æ¤é¤® - No.7, No.8, No.9 No.7, No.8, No.9 email: takahash@sci.u-hyogo.ac.jp Spring semester, 2012 Introduction (Critical Behavior) SCR ( b > 0) Arrott 2 Total Amplitude Conservation (TAC) Global Consistency (GC) TAC 2 / 25 Experimental

More information

24 I ( ) 1. R 3 (i) C : x 2 + y 2 1 = 0 (ii) C : y = ± 1 x 2 ( 1 x 1) (iii) C : x = cos t, y = sin t (0 t 2π) 1.1. γ : [a, b] R n ; t γ(t) = (x

24 I ( ) 1. R 3 (i) C : x 2 + y 2 1 = 0 (ii) C : y = ± 1 x 2 ( 1 x 1) (iii) C : x = cos t, y = sin t (0 t 2π) 1.1. γ : [a, b] R n ; t γ(t) = (x 24 I 1.1.. ( ) 1. R 3 (i) C : x 2 + y 2 1 = 0 (ii) C : y = ± 1 x 2 ( 1 x 1) (iii) C : x = cos t, y = sin t (0 t 2π) 1.1. γ : [a, b] R n ; t γ(t) = (x 1 (t), x 2 (t),, x n (t)) ( ) ( ), γ : (i) x 1 (t),

More information

Table 1 Experimental conditions Fig. 1 Belt sanded surface model Table 2 Factor loadings of final varimax criterion 5 6

Table 1 Experimental conditions Fig. 1 Belt sanded surface model Table 2 Factor loadings of final varimax criterion 5 6 JSPE-54-04 Factor Analysis of Relationhsip between One's Visual Estimation and Three Dimensional Surface Roughness Properties on Belt Sanded Surface Motoyoshi HASEGAWA and Masatoshi SHIRAYAMA This paper

More information

Influence of Material and Thickness of the Specimen to Stress Separation of an Infrared Stress Image Kenji MACHIDA The thickness dependency of the temperature image obtained by an infrared thermography

More information

4. C i k = 2 k-means C 1 i, C 2 i 5. C i x i p [ f(θ i ; x) = (2π) p 2 Vi 1 2 exp (x µ ] i) t V 1 i (x µ i ) 2 BIC BIC = 2 log L( ˆθ i ; x i C i ) + q

4. C i k = 2 k-means C 1 i, C 2 i 5. C i x i p [ f(θ i ; x) = (2π) p 2 Vi 1 2 exp (x µ ] i) t V 1 i (x µ i ) 2 BIC BIC = 2 log L( ˆθ i ; x i C i ) + q x-means 1 2 2 x-means, x-means k-means Bayesian Information Criterion BIC Watershed x-means Moving Object Extraction Using the Number of Clusters Determined by X-means Clustering Naoki Kubo, 1 Kousuke

More information

tomocci ,. :,,,, Lie,,,, Einstein, Newton. 1 M n C. s, M p. M f, p d ds f = dxµ p ds µ f p, X p = X µ µ p = dxµ ds µ p. µ, X µ.,. p,. T M p.

tomocci ,. :,,,, Lie,,,, Einstein, Newton. 1 M n C. s, M p. M f, p d ds f = dxµ p ds µ f p, X p = X µ µ p = dxµ ds µ p. µ, X µ.,. p,. T M p. tomocci 18 7 5...,. :,,,, Lie,,,, Einstein, Newton. 1 M n C. s, M p. M f, p d ds f = dxµ p ds µ f p, X p = X µ µ p = dxµ ds µ p. µ, X µ.,. p,. T M p. M F (M), X(F (M)).. T M p e i = e µ i µ. a a = a i

More information

液晶の物理1:連続体理論(弾性,粘性)

液晶の物理1:連続体理論(弾性,粘性) The Physics of Liquid Crystals P. G. de Gennes and J. Prost (Oxford University Press, 1993) Liquid crystals are beautiful and mysterious; I am fond of them for both reasons. My hope is that some readers

More information

研修コーナー

研修コーナー l l l l l l l l l l l α α β l µ l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l

More information

変 位 変位とは 物体中のある点が変形後に 別の点に異動したときの位置の変化で あり ベクトル量である 変位には 物体の変形の他に剛体運動 剛体変位 が含まれている 剛体変位 P(x, y, z) 平行移動と回転 P! (x + u, y + v, z + w) Q(x + d x, y + dy,

変 位 変位とは 物体中のある点が変形後に 別の点に異動したときの位置の変化で あり ベクトル量である 変位には 物体の変形の他に剛体運動 剛体変位 が含まれている 剛体変位 P(x, y, z) 平行移動と回転 P! (x + u, y + v, z + w) Q(x + d x, y + dy, 変 位 変位とは 物体中のある点が変形後に 別の点に異動したときの位置の変化で あり ベクトル量である 変位には 物体の変形の他に剛体運動 剛体変位 が含まれている 剛体変位 P(x, y, z) 平行移動と回転 P! (x + u, y + v, z + w) Q(x + d x, y + dy, z + dz) Q! (x + d x + u + du, y + dy + v + dv, z +

More information

1 filename=mathformula tex 1 ax 2 + bx + c = 0, x = b ± b 2 4ac, (1.1) 2a x 1 + x 2 = b a, x 1x 2 = c a, (1.2) ax 2 + 2b x + c = 0, x = b ± b 2

1 filename=mathformula tex 1 ax 2 + bx + c = 0, x = b ± b 2 4ac, (1.1) 2a x 1 + x 2 = b a, x 1x 2 = c a, (1.2) ax 2 + 2b x + c = 0, x = b ± b 2 filename=mathformula58.tex ax + bx + c =, x = b ± b 4ac, (.) a x + x = b a, x x = c a, (.) ax + b x + c =, x = b ± b ac. a (.3). sin(a ± B) = sin A cos B ± cos A sin B, (.) cos(a ± B) = cos A cos B sin

More information

chap10.dvi

chap10.dvi . q {y j } I( ( L y j =Δy j = u j = C l ε j l = C(L ε j, {ε j } i.i.d.(,i q ( l= y O p ( {u j } q {C l } A l C l

More information

Bulletin of JSSAC(2014) Vol. 20, No. 2, pp (Received 2013/11/27 Revised 2014/3/27 Accepted 2014/5/26) It is known that some of number puzzles ca

Bulletin of JSSAC(2014) Vol. 20, No. 2, pp (Received 2013/11/27 Revised 2014/3/27 Accepted 2014/5/26) It is known that some of number puzzles ca Bulletin of JSSAC(2014) Vol. 20, No. 2, pp. 3-22 (Received 2013/11/27 Revised 2014/3/27 Accepted 2014/5/26) It is known that some of number puzzles can be solved by using Gröbner bases. In this paper,

More information

7 OpenFOAM 6) OpenFOAM (Fujitsu PRIMERGY BX9, TFLOPS) Fluent 8) ( ) 9, 1) 11 13) OpenFOAM - realizable k-ε 1) Launder-Gibson 15) OpenFOAM 1.6 CFD ( )

7 OpenFOAM 6) OpenFOAM (Fujitsu PRIMERGY BX9, TFLOPS) Fluent 8) ( ) 9, 1) 11 13) OpenFOAM - realizable k-ε 1) Launder-Gibson 15) OpenFOAM 1.6 CFD ( ) 71 特集 オープンソースの大きな流れ Nonlinear Sloshing Analysis in a Three-dimensional Rectangular Pool Ken UZAWA, The Center for Computational Sciences and E-systems, Japan Atomic Energy Agency 1 1.1 ( ) (RIST) (ORNL/RSICC)

More information

20 4 20 i 1 1 1.1............................ 1 1.2............................ 4 2 11 2.1................... 11 2.2......................... 11 2.3....................... 19 3 25 3.1.............................

More information