EDSA(2)
C.2 jE.S*#fEB
138 ll a C CFD ‑>= 1 L/‑9%iejq Lf=E]&H:iBO)a;i&1EWhi&F*0)*tij
(.:I I:.̲il"./.i::
>c
i.
L>
O V
>
L Eq
? bh
=
i
bJ) dJ 'E3 4) bJ)
= Cg bD E
=
0.:
Time [sJ
Fig. C.2 Tilting velocity of pouring machine
Table C.1 Setting of the tilting input
SWIIChlng angle [deg] POuring SPe2d [%]
n=1 22 10
n=2 32 30
n=3 42 50
n=4 30
C.2.2
‑;i.3S*0)hlJF#l#tn#5b3g&t fL)L
I.:. lllllIi:..:L{.:.I
I.
I.‑ ill.
.:‑ !.:JTj.:../.I/!.i.i:I:.:.:'.i.J.;.:..:. . :..,..I.:II.. ....
.‑./. ::./I.ll.l=tl.I
ll
I.;:I.:.lI;..I ../.‑I..I.̲I‑I/.:...i...I.I.I.. . Ll[1. :: i‑.
I:.iL
.I‑:.I:...I.el.
... ;.. '..ll!LJ.‑I.
...:. :1.
./:‑.:...i::i.:...;I .::
,;:I,: : ..I:I.I.I...I....I:I̲ .:.
I
,:ll.:.;I/..1. .i‑I..:. /:. ..I:L'/,...:..,.‑. ..: ..
̲..;./I
'...:.: I.. I:.:I
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I.‑.
..
*rJkjn lr=Bi%3gf*Jdi% Table C.1 L=,ii1.
I.I i:I.I‑.:‑ I:.I. /:..:I̲.!1::.i‑::.:I///I:‑I: :..:...‑....‑: .:. :.:L:.:.i/..
Fjitj5bniAji%*tb L,r=. #aB!, BS*1Eg#jqB2tj5bRigBiLi%mf41 V.nax ‑ 5l.9[deg/s],
cy ‑ 200[deg/s2]7=.b7 f=. i: f=, &1f;*iRIJ#EBi tIEg&igBitj=)VE= J= a ‑> = i i/‑‑> 3
>GB;% Fig, C.3 E='j%1.
I. 〜...(
Ll I). lJ.. i ‑ ‑I.{i.7.i..I̲.J:I.iL.:L.lL.I:.:.]/I.:I:.:.:".̲J 1,ll .
EJ)
bD q>
'Q
ig,
U O q>>
L<
CI
= b&
E
<
ELJ) 4) 1
q}
aD E EI BD E=
F
40 30 20
80 60 40
I 2
Timersl
Fig, C.3 Result of identification
Fig. C.3 0),SEBij:9 , 1G&iifFxt5ll)I/t= A: 8 ‑>i i i,‑‑> 3 ySE5R t9s&#A:Rh<BtW‑
:̲ I/:.I .:I. :.:.I I.:.:.:; I/.:. I./. : I..ll..I:. .::ll:l!.l=J(!:I:..I. /. I:I...I<.(t'.‑:i....:IJ:ll!:
... lJ.../: ll./:I...:.:.:..:+/:=l!;/:.
C.3 CFD‑>=
ii/‑90)./Rib‑#LdZi
*mg%7?t8L #LliASfR1) 7 h T>I 7 7;tb 8 FlowScience a̲590) FLOW3D %jFU'8.
I a)‑J= 1 L'‑9 'i#EfWjRmh,6 I:̲IEbBb‑Bi%l#5 iR41, Jj:#JEE%jq‑).aLr=R41, = :I.../::
I
.:: :.. :
.::I::̲.':i I.I:I.'i..it:.l=.::,. :;I;/:.I:II..:J::I,J,...J..:I.1::...:‑:'L :ll;ll..!'..I,:/::/+:.. ‑̲ :. i .: ‑ ‑Il..ll:J.::.. I;.I./..'j:..:̲.:I::.I.̲‑l!lI.i.〜
gnTU,8T65)[93l(96)
*m9f7:tCj:, #*iFL1*% AC2B tTT%. *3Zbfa8i i.863 x
10‑3[m3],
9WH5B1*iBBilA29 x
10‑3[m3]?hb8.
h4!mL=b'Lj‑8 AC2B 0)%'RJBEj: Table C.2 0)i: 5 8=J#2 L,f=.3:r=, ty=1 L,‑.yj >SgBijEkh‑Lj‑8} ty.)10)8%5gBg% Fig. C.4 L=, i.y1)i)<9 }‑9Li Table C.3 8=ii1.
Table C.2 Fluid paramerets of AC2B
Fluid Parameters AC2B
Density [kgIm2] 2550
VISCOSlty [Pa･S] 0･00125
Temperature Of the Fluid [K] 993
C.3 CFD ‑)=1 i/‑90)Wf&=#lm 141
Table C,3 Mesh parameters of pouring machine Mesh block Cell Size [m] number Of Cell
X‑direction 0･0040 〜 0･080 108
YJdlreCIlOn 0･OC‑5O 54
Z.direction 0･0040 〜 0･〜8O 65
T〜tal number Or Celt 379080
Fig. C.4 Mesh setting of pouring machine
[:.ll.L.L. .
. '.‑:" .
..:.'l.=l:I.:I::..:i;:iL.::..:: //:.!::.. /I.:.:.. .::.I..::...I
ll::lil.:h:/: /:;
I.
:
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I..:.r. .I h .I.I. ::../.L I.:‑/:. : .̲I:lI ..:I....I;.̲:./J:I.1L."/.:..‑./ I/.i
I.I./ :. I:.:I/I;.:. : .I.: .I. /....:.I;:̲ i.. :..‑ :..='..‑I..
..:I.;.:I̲i..:....I.‑./:..:. .‑:
0)&g)ijliBig&‑&E% Table CA L=, 1Gaf5Bitjqigji, i L,Tj5bDigB2% Fig. C.5 8=
/jj1.
Table CA Input setting for the parameter identiAcation S〜1Chlng angle [deg] pouring SPeed [%]
n=1 22 20
n=2 32 10
n=3 42 10
n=4 10
Fig. C.6 (I, ij:iBBSL=h‑Lj‑85;# i ‑> i i i,‑‑> j >0)i#LA50)i:EF2/SEB;%ii1.
I/‑ I ‑. I..
...
I:ll.
:I..I:. .:.::1'. I./... :=ll ..,;..'..;I.:i..:.i /I::
Ll" .. ‑li .I...I
‑
:..:!l::..:i.:..
‑
:‑::/i':...i::.:. I...Ill.. :.
[1 Sac CFD.> a i L'‑9 %]:BjB L,T=B#Ttiii%g)Bi3a+B&3gjio)SLh
Gh
bq>
Its A U O q>
>
i Ct
= bD Ej
<
tJ) q>
't) qJ bD f=
cd OJ) E
I 15
10
80 60 40
6 tl lO
0 2 4 6 8
Time [sI
Fig, C,5 Tilting input for the parameter identification lO
〜..̲.
.... I...:;,.I....,..lliL.I;I‑I:l{:. :‑.I:.: LI:i. I//. '/.::ll.I..II:/I.l'.I‑:
f*i%7 ‑I)I/9 (ibm)bqiBiE8=JdfE%nTb'a. @mO)#ERk=8i
0.5[mm],
#0)*&L3:u50, 1*55 *7:tb8. *WR7:'Ci, CFD ‑)=1t/‑97ls=0)7‑I)i,9%PifR18f=
b8=, $7Lfi)u7)i, (LIT, )u7)i,tP*W118) %fqU'T=.
I....Ill.
...:I:. i
‑ ‑:
I;
‑̲‑.
l'::.I:.:..I.:..:.; I:..i:+ I:I;I;:I.I:.ll:.I...=':I.:..I‑̲ :I..::I.‑..
&bq %Sk8. bl i bq L3:Eq. (C.2)8=/j%1)Sty 7}t/WLif30)iE7?Riig418.
B ‑
i
(b.u.0.5bqulul) (C,2)= i T>, B 8i)u 7)i,i#tB, u 8i)i.y 7}L,Pq7?,0)i#L35E,L [3:WL&hqfEL;8iaf%it1.
･!/:.. I::: /‑:I.. i I : :/.:..
I
:.I..:.i;..:":::I,‑:. 1rl:‑I.:..i.1L:...ll̲‑I:i.I.'..'...:.'J./:.̲:.;
L'/.. .:̲‑. I:.:.::...llll:..::I..:.///..I.'l./i:I.,. i:I,I:I/,lljl/:.:.I..
̲.:.I:!.;.JL ‑:L! '.I̲.I ::
BSrn&bI 0)]3e*jE17?T=#g;Ba%Table C.5 i=it4. rd:B, 1,EgsmLifl83:bl‑ 0.00 ‑ I.5O i L, 0.05%rJbTRig%1j=‑3T=. }<.y7)Lj#L&%5%L&L/f=,)=1 L,‑‑y5 >#BR% Fig. C.7 i=i;1.
Table C,5 Parameters of porous bane
POrOSlly [l] 0･655
Linear loss COeIBC12nt =bl[l] 0･90 QuadrallCloss COeInC2enl =bl [l] 0･00 :.:::}:I.:I. :/:. : il::.I.:.
̲..I:I::I.:I:.:....::.:1:.I:....,,i..I ll l1.lI..I..:.
‑.
:...: I...:..
C.4 iEli;Bq7)I/jh1)X^L%FFlu,r=fai&iiiB^hD*ttj 143
Time Frame: 3.500508 Time Frame: 5.000366
;,TLL
".
̲i̲‑:‑.〜,iiq
̲
I
I‑
3.5 TsITLme Frame: 6.499896
‑I‑
"̲""[j̲.
I i ‑6.5 Ts]Time Franc: 7.999539
T ‑ ‑ ‑ 'I
":i.J̲.
L I ‑8.0 [s]Fig. C.6 Comparison offlow line between experiment and CFD simulation
C.4 iElfBq7JVj1 [) x'L>%J7]Llf=&i5‑,.i.B^hq)*th
C.4.I
‑Rig L'^JL/#(1#Pt=a:85gnE'[]*PGE]1ai&
:... .I:. "+':.. :.' ‑: :::::.: I..:I:.L..:.
....:..I:i.h.:: ..".i:;..:..:I :. :I :: ll.::
I.:I: I. ;.
‑.::I.‑...I:..:: .::̲.=l::..
' :‑.
I.
I.;:..
..ll
/.:. I
' fLiRo)5ffEREh
+ /I../:I: .:I ll::I: ;I.
J :..
I
. :." L.Ill::::.:./̲
I.
: I..::J:i I:/:.:.:..:i/..I.lf.I‑.. .I. .. I̲ ;..I I/
1..r.. I.I/ 'l. :/.. I.llll/l':I.1‑.Ill. lI:.ill: ll/:.... I .il.I. ..1.. .. I:...: .r:
llt .j:.:( tl1) : :i. 't':I:..̲ ;
'l.ll.I.
... ...I.;I.ll/I.. j..1: .
Fig. C.7 Comparison of nux in sprue cup between experiment and CFD simulation
I
.. /.:::...."..:.::I. I:̲:.. . .:: I. I.:.:li.:..:I:̲ll.ll̲ I.. ll.(..".:::J:.I/.I.I.:....i‑
‑
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'l
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. ./:I:..:...:Ill‑
ll.
C.4.2
&i51ERjjEEO)ZEIClb
.. /J:I::. .: :::::/:.‑:
I.: ::...I.. ..I. :I/:.:iil:.:i.:.
!!...:...ii.:1:::;;.;..fJ./.;I:I.:.:..:...''..
I.
/. I/.I:I.:";./:.I..I...;::I.:..
ll̲..
I:,:lh.I::.::li./I‑ . .':::.lTllill.:..:I.I.‑.I: .‑'〜
I.. ::̲'..: I"://. .:ll.:: .J!. ..:I..1/.;:i/:i.I.:.:.:.:.:/I‑:.j:.'':.:'..';i/:i:..:
1.
I/:
Ll.
.
ll I
I.:,::..:.:::I I/.. Ill. ̲' h!...(..;:... '/.:::://!.::i.l=..:/..;'.I:i. .::.:I
I:. l!.!./:i.,::̲:/ll.. : I/::.‑.I. ..
..:...:/./ ..ll...:..
..;:I../.;lt./:./:.:..:.',i/I
lL
i I.‑.I. :/./.I I..I. //: I...::I. I ‑:.:..
minimize : J‑lp+Jp h> 0.025
C.4 iEliiBq7)Vj1) RILh i:yH‑iL 'f=Llli;&ij:fi,,l}JJ0)5.qU'. 145
a =?A, ip Lj:[Eg##$7FSFB, Jp 8iEq. (C.5)8=jV<+}Vjl‑/Bg&, h 8ii%Dtf5h,6 1;JTrifu‑= rLTtLD‑,jt‑[1ri̲ir,,)t1.
Jp ‑ w1 +W2 (C.5)
Eq. (C.5)l=35‑L'T , LI.1 (.a:f'1IiL,JlO)I::y,‑!l=iL}.l‑L1.̲Tn‑iJ"‑)iL,,i‑H[^Ji(.li(.'i̲a:?tq)'A'(1(I‑j3So.u2:‑,[Jn]i:y FBI? r=lB% (h< 0.025)8=, w2 tiiii%m?1i5fR7?h%r3U,LWlibSfEBR=n7tiB%8=<+
}Vjl‑fqiw1, W2 ‑ 102 bl,hi#%6418.
C.4.3
%i51E;+##5Et.gJ5Lh‑>=
i L/‑‑> a 〜/Table C.6 (I,)i‑T.;'T‑I.;l:I(9 } ‑9jlr)TIL ,. iG(IJ'[f.]7)VjlT)7:LJ=J= Za,llli;a(E7LTJ'(i?JT=.
B3i@IEE+$0)#SB!% Fig. C.8 8=,jV. B3i@[E8=218BSFmi Intel Core2 Quad CPU fg#
0)/i') = '/?, 48 BSFEN%f L,r=.
Table C.6 Parameters for GA
Number Of Variable 7
Number OI population 10 Number OI elite Preservation 1
Mutation fraction 0･01 CrOSSOVer fraction 0･80
fj e
'J3
U a
a
+ a e
U
T...
5 10 15 20 25 30 35
Number of generation Fig. C.8 Cost function
40 45 50
Fig. C.8
cEE), I,]Jti41 [[‑l‑‑(t3:T1=(rT,'I!‑hSLfmiL,, lll{TL5(Lh',7T‑b4tr=I i }ir,I,‑rE::,i.JfL'.T.‑c*7J.
‑=‑
0)FS, Ef[Wi8i J ‑ 4.668 tr3 9, B%i&#LiTable C.7 8=,j%1)<9}‑9%1Sf:. Bi3@
)<9}‑9h'6f$6nf=IEg5hj5&. Bji% Fig. C.9 8=j%1. 5fT=, Fig. C.10 8=i@5iL,
〜VSr]/m%jqL81 L r=fB% i L,rib,? T=fB%0)%j{ a)FSFBL=A‑8j‑8Sf 0)Ze[E%j%1.
Ilo:Jfi'n7<i L rC, J'l;‑ufa‑lfrJ:L 0)i‑i;,i.'TTt(illill:‑'if()i‑[nL〜D 3f‑EliiJJ3jgL,I Js 6 7r‑1,+)JtTJ:I,tf*rrn‑
%[R?= tb'i?3TU'r3U'= tbl,'bb,8. %418=}qL, ifimr]/m^j]o)BiB[E%7i5
I i Tt. ‑LTCf^1,<.;i,Jl‑uJJ../7‑ji,t'[r[:1:r=‑TrlW‑fJ:ifWn‑t'〜Lt'fiuf31Ji:'Jjsl:il7Tt% TL, 73 I i hS bb18.
146 [1 a C CFD ‑>= 1 I/‑9%B2Fq L,f=B&ii#0)B%i@1ERa3ABEO)*th
Table C,7 Input setting of optimi2:ation result SWIIChlng angle [deg] POurlng SPeed I%]
n=1 12 54
n=2 15 78
n=3 39 86
n=4 10
V) ed q}
'Q
TE
O O 4}
>
L cg 5 bJ) G
<
ed 4>
'O
4}
5J)
= cl bJ) f=
‑
‑G
60
40
20
80 60 40 20
Time [$1
Fig. C.9 Tilting input of optimization result
C.5 %[]E][]fB%5gBELf=hSiG#AO)=iTd5
ApRDSBO)i%i#Ln‑>S 1 I/‑‑J3 >*E5R% Fig, C.ll t=i;1. =0)i %tai5t/〜L,Srj/m
L̲.. :I.
I
.:..〜ll:..1
ll : I: I..̲..;.I.‑...: /.I.::I‑.;/..'=Tll<..,..;̲.:..r‑; ': 'i.i.I̲:.:̲lI:l[J.
%fj=‑3f=. g]1FMbnli50)*=%Blj:0)#jZ‑i Fig. C.12 i=/ji1.
Fig. C.12 i Table C,8 j= 9 , En3f7=tO)^h ttbrkL,, &i&1E%115 = tT‑ijiiBFSFEg
I.I. ./": I.:/I/I.'.:i. I:I:.
I..
://:!:I...l! lj.:..::/I‑I‑.:/.].."lilli.:Ii .'l::‑.‑ !J.I:.:‑.
.‑I.
/I /: lil.:..
C.6 &#ifFi^h%j7]L'1t‑;i.B*lJ8PjES*
I.}:I::lit.I".̲ll::.'. :..:.i/ i
I
. ".. :.il...;...:'‑.
̲::/i/:I..L
:.:I...I.:I.
Table CA 8=/i;1^h%FqL,r=. *iEij:71B]&Li ll Ft L,, i%n 73J% WL,;%SVni%
C,7 #a= 147
4.0[sl 4.6[s)
OptimaHnput
5.2 [sJ 5.8 [s) 6.4 [s) 7.0 rs) 7.6 [sI 8.2 [s7 8.8 [s]
0.8rsl I.3[sI I.SFsJ 2.3[s] 2.8(s1 3.3FsI 3.8LsT 4.3lsI 4.8[s]
Fig. C.lO Comparison of surface height between optimal input and conventional input
Table C.8 Simulation results ofair entrainment COnVenIlOnal input OPIlmum input
COST function J 9･1 4･7
Filling Time [S] 9･2 5･3
Air enIlalnment 4･983 4･248
lSj?L'T=Apr]pJSzMEi'rjbulf%0)bDIW=fR41%*PBg)5ffE*%#1# L,T=. Fig. C.13 8=&^
J])<j}‑9%Ff]L'r=5;B*#aR Fig. C.14 L=%nfho)9(Bh5EfE*%,51.
#Ei#t L,I, Fig. C,13 A‑J=V7ig. C,14 8='j<1j: 5 8=, Bii*iii%igBf^j]%FEib,a =
I
://.ll/I:l':.'.I ./. l1.:"I:"'l :../ !l‑..:ll̲‑:i!../...//.:.
‑.
LL
I.
,.‑I: :./: :.. ‑ii.. I.:I..
....I;I
I !=.
h:.:.:I:I..I::I‑I.i
I. I.:I,i:.ll.I.:/../. /‑ I:::i:.:.I.I.:ll.I..I.
....:..l..:.i
'̲..
:I. I::/.I: ‑.I::.i :I. . :ll:.
C.7 #
I::./:. :.:.. ..'..i/.I. . :i. . :I̲.I:.il.:.rl.:.:..':"h.!l.::.ll.:...:..:.I.::I.:::.. i
..I.ll.I :':‑:I. ‑.I.. . . :: .
‑::I:I :/'i:‑. :‑..i...:;i. i.‑ .i
I‑
....I...:ll.I.li....:...
I.:
I I.Ill
Ill:...‑::;: ::I./:I. :.T...:.I:.. .'l..
:̲.:.:.I/.‑..:
. I.://:.. /..
...:.:.,
I.
: ./:;〜:lll=:I. ll.: /.. :I.i..I. ..I.:::::.I:::J.:ll:.J:I;.:/.. .ll.=l..I... :..‑:
::.:./:
:/ I:I/:. .'l Ill../..: / I:.I../:I//.:. ‑̲1L:..i....:..
l1.< ..; .I tll7 i:i‑I.I:i...̲. ;.;‑I"i..
....: .:/: .I..:̲....1:. .
I.4 [sJ
3.0 rs1
4.6 [s)
2.2 [s]
3.8 rs1
ltl.
Lt
<
5.3 rs1
Fig. CJ 1 1 Simulation result with optimum tilting velocity
C.7 #E= 149
Optimum input //
̲.ll
Fig. C.12 Air entrainment atmachining surface
Fig. C. 1 3 Experimental results
l50 ll tic CFD ‑>= 1 L,‑9%iBji] L,f=BSJutti*o)f&i&1G&iAFgO)*Ltj
I:
= e
〜 U c<
i
q>
>
‑ U
a
C}
E)
r
.･‑51
L
.il=Tl
ilT.
I･Yl･
:
I.JI.
/}:
ll I 1･.
Conventional input Optimum input
Fig. C. 14 Defect fraction of machining surface
151
1q *D SL55E*#i!55ti51b7JVjH) XIL1
0) #;a
D.1 infg]JR/*vS.6afEjEFp5EEt= h'Bj.%iElfBg7JVj1 I) xt%R
Ll f= F$0)qX3fLEE%E
:I)((I7{))!MJLEJ‑i,;.JL.‑I..:E=I)Jt[riL:(:filrfl‑]T#LY3dimL T= i =cVa) I‑1‑,;J)J]JI:̲0)rj:.i‑(l:.}ir,7j‑‑5. fj:,;‑u]‑i,1‑;i L,I
(i r4ui.,4i):iO)1J'qi:yf;LJii I.rlL:< 9 >9tlhTl'u;‑lI;‑&LIY/II‑‑L,,i‑I A, 6 Lh'.TJ*:fi[Jt3M!(Ji:y)Ill, TT35JiLL.‑F‑.7JifJ‑LJS7,;a1r7Tj:[LH.J[,'(..THEI'‑q‑a;'l7pj‑,3. 7̲giU)/LLf[l‑T.Ei/n1)tW;.[Ji11J(imL ,‑911,jB[̲7in'.)7 )L jt
7)Xb8=j=T3TfEBE18. =0)t%0)}i9}‑98iTable 5.1 tR#q)qb%jR,T=. 4 B]
9;1iLTf&Ek%1?u', %o),SaB!%3f tbf=qb% Table D.1 8=i,1. a =7:1, "Conv."8iL&
BiiA1{, "dist:'8Y7jiBkSrJ/m%5.q#18. Table D.1 %jiTb8 a, 4?0))<9‑,JO)Vg,
)q9 ‑ > 3 0)(JJIJi‑Jill)[')‑}i7,([h)H L 7T=l‑i,if‑illLilliJiLu‑fUJ',11 lu̲.ftT.,1:3bE), jff=i:,lr;‑[[Thi I.it)
i Lt^T 10 [[‑r',‑.jui< lust,I i hu:')..ljT7)‑r)I,'J.'I1.C=I;(['r?I L"?a I i f3t,tbJ),73.ktfL/EJ7:)i[.iJ((xii:yfIJ )IJL,r=1‑i,,i.I‑I(iEi Eft1'‑I,1o).i‑.I;‑(tIIi[[L'L‑ALL,,i‑(L,TU ,73 I i 1]"I,, l=:iI/T‑8=[Fr.'l!t‑JT.}Lr,I(i‑‑A‑CL,/3I i i)q)i)'T), I a) I i h'Lt3I,]ill1‑I(l1).']LCi'JJtl')t!(fgiC=Lt,<rJr)‑rIL].'Il.I.=[;(r'TE)1blu , i.‑I;5 I i hSbh,
Table D. 1 Optimization results to compare the use of inithial population with the distribution and without
Pattern 1 cost COnV. (X[mISl,y [ml)
Without dlSt. l･21 X lOI3 2 10･2510･265)
With dlSt. l･46 X 10‑3 3 10･2410･245)
Pattern 2 cost COnV. (X[mISl,y [ml)
Without dlSt. l･46 X 10.3 5 10･1810･146)
With dlSt. 0･26 X lO13 ll 10･2210･229)
Pattern 3 cost COnV. (X[mISl･y [ml)
Without dlSt. 9･90 X 10‑3 1 10･2910･296)
With dlSt. l･20 X 10‑3 8 10･2010･114)
Pattern 4 cost C OnV. (X[mISl･y [ml)
Without dlSt. 0･10 X 10‑3 5 10･2010･122)
With JISt. 0･29 X lO13 6 10･2210･228)
152 ll &RD S*fE*4gBii&[E7)I/j^1) RhLq)i*ER
7iD. i 6 B=, l15{niLrl̲‑[t}:ylt[fiiL,T7J7a i , L1)tJ(‑ar'J‑0)1);fgLii.TtLillX^i18fi::[t13'''[R<, t[
･Ii,1L'f'.].i‑tI;‑([lliO),Lu':L,[JYI1.l=ll*Ji‑3‑7a I i i)'6 llMiJrlliE=J]uiI , jt* i f8//j'‑(I7j:I;LTU ,fcL‑L'I i iJ',tbh,73. )i 9‑ > 4 }L.,i‑iT3*,3i, /)Jt7iJIT)]']‑0);;I);‑Iulib<'(bO))S9‑> EEL:[{{TjL:I.;;'i'l=fi
L ,I thtibh,73. L,f3,L,, )i9‑> 2 0)5ji['i‑JIT)TI]‑tLtLfi.iL,TbZG) tlTX‑kit̲Q̲.TtCirTfJi;T.ab
73. I 0) I i A, 6}i9‑ y 4 0)3:;tuiEi,9 > 911LJ= j=7a‑1''.)Jl,fJLJE9‑till/thSIILn.$1(‑,flI(]'‑tiEI.')J'r!EE:
Ill,I/N7jl;[t7E4t7T=f=W7!J:i‑341T=,1:.M!7:t358 i,Lil.b418. '7JliJlfl;‑uJd‑mui:y3&mL,f=}i 9 ‑ 1/
2 i )(9‑> 4 0)qb:F̲ft)!}ir,i:irEb73i, .i‑1''‑[JlntlnJ,l!iJtiti,C=E2tfrTfJt=lLl'(i:yji‑(L,TL'73 I th'i
･i‑)A"?a. tt/UI , )JiJi‑A:I;LrJf1:lJi!uJ61Y;&JIJL, T L'rd:L'li,iF̲‑TEilll3uJ‑.'Iiht,tj!T3TT7JkfT3 f=no:.li‑=UIJE.,jT(
L TL "‑5. I 0) I i JJ"‑/JJtliJ*fI;‑lJ'aLITLlujir.;&LHL,f=l‑>7,‑Esli).‑JTrrIRJ.'r!l=r;Gu)i!fE<, i 6 l=Ciifl iiU)1.'l.'I!j)Si‑i?Lj‑Li)i<fJ 7a i.‑ ;,‑i,3.
1?)i9 ‑ >0),lO:f̲i‑n!}={3: i bT n73 i , }lZ3:? f=lTliWuF‑0)a.T;‑[rIliO)hi)(i lll/i,lit.ltqiRpF
7D i 'JJt(F(lil:]‑0) /J‑h'.1l[l;d[nJ,'I!0)lll.[l;JJ',J(‑c}uII i 13'I‑3 )JY)I(l1)]']‑7?.(.ri')iL,JT=[ni,'f!(.;‑.ri[LIL7)Li.frJ:6 4I
rd:i,I i iJtib]),E). I(i)JT,fJ]JJIEJ;I;.L:i(I.5‑]il')tJ(,l;.ui1]JftrJXa=lllL,T=7}hS, cEE)fiW‑fd‑3:[h‑‑u!%ri<fl‑*j=L, Tn:]rL']1,‑aI i hllbJ)'73.
[L'J.I(W‑LJ=i>T 0)rluiJi,‑;JL.I:1j:yLIC='tEI L,, iJAuiJ*;'.rf.JJ15d;t]70)i,]'i‑7‑}:yL=i8.Fig. D. 1 ‑ Fig. D.4
Ei‑I‑,1t‑rEt4I)J1)tJ(['ll']‑TtI3‑I rj:7 r=/i9 ‑ > 1 ‑ )i9 ‑ > 4 0)H‑.il:0)iJAE,,iL.:J:a)L]q‑a‑m?.AE),
Fig. D.5 ‑ Fig. D.8 Li%41%h41ZDif&1&?B= r3? r=)<9‑1/ 1 ‑ )i9‑〜/ 4 0)B$0)A?#*
..:JtO)[71[!iLI}rElA 73. tic‑is,
/)J‑,‑0)[JLTlq.r:i7Jrf)J3[JjLT̲〜‑i;L7}ty,L,b1.
Fig. D.I ‑ Fig. D.4 %fiTb8 i, RfE$41Tb'f3b'SghijE8=h‑i}8&$lGti5>< 1ibn TU'r3U'= tb'ibb'8. L$8=}(9‑'/ 3 0)i*m58=ji6m8j=5 8=, Fig. D.3 8=h‑U'T
EL ITS;dur'J.'iJJVo,‑5Till'ili,kEii>< 1Flr,'i!‑1'rT‑i]'i'(i‑b41TU'rd:U'I i hlibh' t), )aT‑7‑rr[nJ,'l1‑(=r;ru?T=I tbSbh'8. 3: f=%B]q)A$1G?A)<9‑'/ 4 8=h‑U'T
(v,x)=(0.20[nJs],
0.123[m])b''tBi'Jln,TriT.AZB't5J‑ZWl34 tr=. Fig. D.4 i:yhrL,3>8 i , %0)li‑i.;SB[t'J.7f!jifl,A‑rEt[t'J.'[I‑m‑ilrS< I(i‑.‑3TU 1 8= th'ita<bb,8. Lb'L,r3h'i6, %=8=%*LT#iG%1i?TU'8Jtak, Itho) TiTil.Jn=J‑.iLTCil#rtllJRJ*i}ir.h‑.‑)TL,rJ,‑L ,I tJ31ibh"3. I 0)i‑il̲{iiLi)(9‑> 3 i r'ltitX 8=&=?Tis‑9, =0)= tb,6b)<9‑>4 Li9'/91'LWgfb'i[R%jiWTE>b?r=tu'
>‑i
,p5. r77JL= < )(Jt9‑> 3 h,i‑3llllB[(i.'riJ..JAl=.tH!y]iJISJ/*i.Ttij3'iRIIiiHE4tTU'8I i J]'L‑3, I 1)‑ I‑[[j,'I!iir,rf1,L1(I‑,1'kbS'(;‑b4LlpL,b3 I thSbh'8.
LJ.I I. :I/.I:: .I i,:I"I̲.;::ll.:.::i:/J:ll/''.:̲;Ill.‑.:/I.Ll:...:I...:.. .. I:.i
.i 0.25
E
C
･BL/. 0.20
O a..
,TOE
=
･BO
0 P<
0.05 0.10 0.l5 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Velocity [m/s]
Fig. D.1 Location ofall agents without distribute in pattern1
0.05 0.10 0.15 0.20 0,25 0.30 0.35 0.40 0.45 0.50 Velocity [m/s]
Fig. D.2 Location of all agents without distribute in pattern2
154 J1S/RD S*5B*39BSi&IE7)i,jL]) xlL>0)*iJt
'F
= 0
EJ) O a‑
0.05 0.10 0.15 0.20 0.25 0.30 035 0.40 0A5 0.50 Velocity [m/s]
Fig. D.3 Location of all agents without distribute in pattern3
I :Jnithi searchirlB POjr)Ls
'lL t'
,i 0.25
E
a
･BEJ5 0.20
O P<
･
.!!
I I
I +
)+4l.
I.
+
L I
+I
I L
(
++I
I
I .
I
I +
4I
0.05 0.lO 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Velocity [m/s]
Fig. D.4 Location of all agents without distribute in pattern4
D.2 ,][)J7)i,jt1) R'L%i&jq Lr=lB%0)#*jRo)RfE 155
;RL=/)jtL17kH;.rjTa317tj915L1%i@jq L,rc Fig. D.5 ‑ Fig. D.8 %5iTb8. iWmRfg%2j) rL&18= i?,FigL D.1 ‑Fig. D,48=t:E<a;< 8=i&?T#Si5%LTb,8E thlhJqi8. qS
:i 〜t'':ll..l1.i
::‑I‑:,! /I.I/1... :‑: I.::;I:h ‑ ..:...:.:.l'.:.;..I../.I..;::. ‑I;:.:.. :....I. .‑̲
lil. i /...::. .:..:I:I/:.I.I// . Jl."/:‑ : I ::.. .:‑:... .I..:I.;ll .:̲./:I... ..:I:y:
I.:L:‑::.. I...‑
:I
I :I..:..‑̲ : ̲ ! .I:.::..
/:./: I.::...J, /.I.: I.: ll.:H::.:./tlll'1.. ‑.:I.:.:...:
lt.
/I.:.:...I.::‑.: ';/. .:..:.
I:'r,..:;:.̲,: .I..:I.. I;.:/lr :‑.I:./:.I::.;::::.Lh. :I/!i.::r:.. I.‑, :̲... ‑. I.::. i..:...:..
..:"
iEilZf1']7)i,j'l)XLO)3f5a'F#̲6Eo)FqtbWg. D.5 ‑ FigJ D.8 A, 6 b6&a5hTtfr=.
0.35
,i 0,25
BJ
=
･BU) 0,20 O FL
I :lnitiu[ sciLrChirlt; Points
lL +Jl
L A
.I
++I I
L
I
+
l‑
+r4
I
I L
. :I
I I
A I
+
I
Jl +'I
0.05 0.lO 0.l5 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Velocity [m/s]
Fig. D,5 Location of all agents with distribute in pattern1
D.2 $ lh7JVjll) Xli1%i5B] Lf=l%%q)#/q!,S.a)RfTE
Fig.D.9 i Fig.D.10 E*%mfhS(h7)Vjll) XLLO)&JLE% Lf=tB%t, L,TL,rib,tE
%%'i;LTL'8. E: = 7?I, ){9}‑90)E&JLkEj: Table 5,2 0)&l[‑B%*jf8=, .jJh7}L'j) T)XILmS2E%%m%>mwR ‑ 0, ba ‑ 0,wR ‑ 0.1, ba ‑ 0,3 tLr=. 2r=Fig.D.9 i
Fig.D.10 0)#*j5,0)&LiFq%7?.b8. Fig.D.9 %RL8 i, #*jA%$4@8=S*E%TU,8
= tbbb'8, %41B=}1LT, SrJ]7)Vjl) XIL%;&JliLr=Fig.D.10 %5i% i, Fig,D.9
Ll̲. I..','..:..I I:::I::i:./:. I .J.. 〜:,.I;:.:=:.:../̲.;
I
̲‑....:.: I::..i...:.. ‑..:..
156 I1 %RD S*fE*4gB3i&[E7}VjhT) RhLOf*EE
60)#BB!j: 9, SFj]7)Vj1) X7>o)‑&E%18 a i?S*JEEhhizglEL, S*JBi%#fS L,r=L,fl,Jl‑[':}(i$ l)J7 )L jl 1)XILJ);i‑J;iLJJi:iEr.qlJRL, ;93E=)J1̲RD'.]fJ:liliGWJ.'[!0)‑.[.!i,}i7,i=i?i.‑Tr=
L ,li,i['JLEi,iI)J 7)Ljl T)Xti>0}.;‑%rLrLr/(jT‑5 JjlJ'iLiU' I i JJ1'tbJJ'8.
D.2 $ lh7}Vj1) XLLh%i&]q L,f=*%0)]#i5)5o)5T[fE l57
I :lrtiLi.1Lsearching poin(i
I I L
J L
I
= O
V3
O Dl
I
= 0
l^
O a‑
'!A!. b. L
.I.
I I
I Il
.'f.I+
b J
4I I I I
0,05 0.10 0.15 0.20 0.25 0.30 035 0.40 0.45 0.50 Velocity [m/s]
Fig. D.6 Location of all agents with distribute inpattern2
) :Tni(ia) searching T)Oints
I ''' 4 I ' L'
4Jo
I
+
I '
I I
I
+ +
L +
)
lI
J I .
0.05 0.10 0.l5 0.20 0.25 0.30 0,35 0.40 0.45 0.50 Velocity [m/s]
Fig. D.7 Location of all agents with distribute in pattern3
I..H ..i.::I) ll.'.J/::l{.::: :.:I:I.I/J'.lL‑J‑ll:./I. .:,;
I :[nitial scarchhg points
4A' I,
'l'' '
I +
.
I
lL
I .
:I
,i 0.25
i
=
･B 0.20
0 P<
' :. ‑ ''.
I 4 + LL
I.
'A
0.05 0.lO 0.l5 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Velocity [m/s]
Fig. D.8 Location of all agents widl distribute inpattern4
D.2 $ IJ]7)I/jh T)Xtil%i@FP Lf=iB%o)43E*J5o)WfEf 159
0 loo 200 300 400 500
X‑axis
Fig. D.9 Location of he searching points using MSSA without attractive force algorithm
100 200 300 400 500
X‑axis
Fig. D. 1 0 Location of the searching points using MSSA with attractive force algorithm
161
ll *E 5*&t=h.B+8SL55EEf)mi!55ti5 1E7J V j^ I) XILAO)'EE%E‑ER)i
E.I 9tlJ{h A L a)a4tHigF3E&i51EC=h.Bj.8qX5ELB#.30)‑iRZE
Ill‑‑I,+u3‑(+‑‑‑1 H a:TW)(f'J.Ill‑1')‑Ti''iJ>0)
‑'f?f‑9 trnJL.T, 9V }}A T,7o9 > ‑y1, a)l7;i.;&i4i )i.i+J 0) )JltRn'.JhJliliunJ.'l!ily}J:b.I 4.tier.T‑uH)L, Tll i;dB(LIJtf7Eq).;.I.,,Jltrr77‑:). )(i.iW'.]rj:
ill;LW)'L).'l!0)i.q(IrI.E=lL fiIIJ'.TJ:
,i‑1;.Ilthrrf‑I)‑:7f.i.'t':0)f1‑9 1),L3TTl)i(LI'L'Tt.;‑f.?.TL,I,TJi‑af;. I I
T1, IITI)i(lL't‑i Ci=/‑ Jt90)I,JL(],‑IIT,L,&11lZb/3i 0)Tt, I,]iLJ‑i/,tJt;JqiTtrJ:L,lil t?8=LJ‑i< [IJL,
lt,41,3jli‑1.iJIIl'(I.IIu"‑5.H‑T,Tiii‑Tt5/5. 1‑:]l,(I,iluJJi:i xfcL‑the)I)tat([L'(0)i.r!Z7tL!)i!bti'J'<, EE 7T=
,'r]YrL7)tlt.kJ‑f;/inl‑ill(T(i ‑1'‑‑i‑LJ[[,'ii r,AL:(.'J7l':iT.‑/TJl:rl[I,1,1J. IfJl)i([lfi‑EiEq. (E.1)&Jn ,I̲?.T..II.E n, Eq.(E.1)%i#f=1*jklim %/Rb8.
/
rn
〜
dF(I" ;, /mndF(x" ;
(E.1)Rbr=#EB!, *5}Bgr3BiBhSLmA1[m/s], 0.34[m/s],0.57[m/s],0.241[m], 0.322[m]?1b 8 = tb'ibb1?f=.
:*E=, ll<‑Jrl!JJJ,io)I,i:l'i&J(i‑‑5. 1<W‑Jj/eJ=3st,TEA ‑> l1 3̲ L,‑.9 i:y)‑HU,Tfq:lI̲ffTTiL7‑I(]‑.7T
L1 ZEU=d), )(i.irXn'.]rJ:lll;&n.JI!‑1Eil3:rLT.0)i;.:u;3ilu‑I‑rLTllf:.ffE&1YL[.I.:i‑9‑8 I i CijF:I.?;i.(I[L‑i.:r.'iJJlr
T;LLhT'3. i I Tt )JirR['T'.Jrd:lfl3&(nJ,'L!EErEtO)jfulj![[I:ItT.EHkf < , )Ji.R['1'.Jrd:LlijB[q,'[J.a)iC(.)I,<c=i!u lJfLr= [ii‑[u7,l[{,)i[rf‑.1ti L/I. lI,<JilJlinEo)lt.Ei.:2i:y71l‑?r=. jifB!U)J)‑llitL/C, (,[1.Ii‑)]i
･'IJ{o)iV1?)I)L1?3. Eq.(E.2)Li1{(1'Ii;JliI(o)iuy,T<L,TIs T), FTfliVIL'i‑A,60)'Jji.I,r/(]1(̲TL, ((i 6?i) %'j<1bO)?>b8.
i‑1
p‑
i=(xi
‑5)2 (E.2)n
I I Tt, 1'(i';I‑1'‑‑[[l[iIIl'L‑,I,Ci'J1;3lko)g(,.r.Ei.a.IWTO)(u̲'i‑,.I.(iEq.(E.1) T.}J‑ij:.37T=;i.fr:LITO).T.
9elEii%ii1. =q)t%zAif&I#% v? a L,
Jj5
5;1.5 tf3?T=t%%qX*igltt L,TS Lf't,lt.fiP1,h:1r=. a.i‑,.r(i‑‑fLi.0)lfuiJr!l!fJIEo);I:rl:u!Ea:ng. E.1 E=,I(7r.I I ‑Et, LtLfi+,H.J.'iitL,T Ei;iif1‑Jr'J7)L jt 1) 7:LJ=r m u,I ill‑u,, ^6.i‑irf1‑.LITj‑E.I(irTi]Lrf)Jlinn.q(i;i:rHIL,TIr'),'[1̲).‑lT.i:r F#?*<U'8. 5fJt v? 5;1.5 8=fr]3fLr3b,? f=tB%8iBSj(7?Iba 60 ift4Le%qx*iifft
tL,r=.
[L1,'J!1')I.〜,l+:ili‑rJ7'.3ii(LJr'.JT)LjlT)X'iJ=Lt,i, (f67fi)1.1j;1rJ:< , 3f f=lTmilA.Iu Ei/lrLTt A ,‑5I i 1)I,tbh'73. l1*JI[[1:(to)rI‑II)i(ll't‑i:ylrUai , 3u[L:‑N.J7)Vj1) 3:IhTt(i 35 tit‑[V=t7 7tO)8=*4LT, MSSA?h8u3.5tg4{?hL&Bih'iliATU,8 = tbhibb,9, #aB!, 33[97.]D
*b*ra̲tb'i5i641f=. r3h‑, iFfgo)lB%8iiEliiBq7)Vjh1) XhLi)'i34.7 tg1{, MSSA A,i
Lf..: :...: I 1 ::..I./:.:
.;:::..:i.J:.;I..ll..I:.::;../̲.I.:.ll I.'h'. .i‑.‑::I:‑.I
= O e
S40
5D i) E=
&30
4}
>G
a20
l 2 3 4 5 6 7 8 9 10
Number of tnal
Fig. E. 1 Convergence generation of the optimization trials
O E=
ed
lei
>
b eO
,a= 3 U Eg E=
'gV
E)
1 2 3 4 5 6 7 8 9 10
Number of trial
Fig. E.2 Determinate unbaiased variance of the optimization trials
26.1 tglLe7:.AO, 25[%] 0)a*F]ttr3:8. jfr= 60 tg:1Le3f?tE+S L,TS}tijSrLT=hqo) hi#Eg%‑WpV=#aBi% Fig. E.2 L=i;1. End: 9, iafii&W)i/jt1) RhLO)aiV1 1 t5Vj=
hl::i. ..::I L:.I,:..I.::.ill:.:./.'/: ‑:I..ll..: I..:/.:I.:':.:..:..I.'':Ill.:I.!:.::ILL.:.:I:.:I.;....
i&1Z;m7}t/j1) XtLLi: 1.1599, MSSA 8i0.8706 7:tb O, =0)#SB!b.6, MSSA 7=,L3:A
.,./I;I:.: ::/. /.Ill ."I. .: I.J:I::I:.I.:.:.‑̲:1.:..;:./I:.‑./‑. ;I.̲::. :/.::..
‑I:::::.:;i..
Bq7)i,jll) XLhbH.l5929, MSSA bu.1456?.a5‑3 r=.
Fig. E.3 i Fig. E.4 E= E.I 0)HXAPSL=B‑L}8B%i&1#%ii1. Fig. E.3 hqiEli;W7)I/jt l) X^Lki: 8#E3%, Figp EA bS MSSA kj= 8Gj%T>a58. MqjO)E&#Thii1 5 fqfE3i)i
L:.,..:I..̲.:::.:.rl::..... ‑̲.i./.. :... /.;ll. ut,tl1:i.:.:‑.;.I:‑:J;ll‑.I.: ::ll".:"I:.'..
I.
I/:. ‑:I ./ :I..I:.‑̲ll" :! I./:..
E.2 jlX 7‑Bg&%@?r=J&eEaagi 163 Velocity [m/s]
Fig. E.3 Optimum values of each trial by using CA Velocity [m/s]
Fig. E.4 Optimum values of each trial by using MSSA