, 4.2) utilise un gaz comprimé (12) pour délivrer une impulsion de pression pour un métal fondu (14) contenu dans une chambre (17) faisant partie du générateur de gouttes (10). L'augmentation de pression force une petite quantité de liquide à sortir à travers une buse (3) dans la paroi inférieure de la chambre, Le système de production de gouttes (Fig

. La-chambre-remplie-par-le-métal-fondu-consiste-d, une cavité (1) cylindrique (en acier inoxydable) chauffée au moyen d'une bande chauffante (2) enroulée autour de la cavité (Fig.4.3), à une température supérieure à la température de fusion du métal par un contrôleur de température (16) ; ou au moyen de la circulation de l'eau chaude autour de la cavité dans le cas d'un métal de faible température de fusion (comme le cas du métal de Field, La chambre est pressurisée par un gaz alimenté à travers de conduites (9) (stainless) à partir d'un cylindre de gaz comprimé

, Figure 4.2. Schéma de principe d'un système de génération pneumatique Source

A. Annexe,

, pression pour un sphéroïde aplati sous Mathematica print[expr_]:=Print[expr, ToExpression[expr]] deriv[expr_,var_]:=D[exprAbs'[e_]?(Re

, V=4/3*Pi*R0^3; U=1; print

. Coordsph, Sinh[xhi+I*eta]; z[a_,xhi_,eta_]:=Re[CoordSph[a,xhi,eta]]; r[a_,xhi_,eta_]:=Im[CoordSph[a,xhi

Z. Xhi-[-a_,

Z. Eta-[-a_,

. Prefacteur, *a^2*c^2)/(b*c-a^2*ArcCos

, Prefacteur:=(U/2*c^2)/(e*(1-e^2)^(1/2)-ArcSin

. Prefact, , p.ArcSin

. Psi, , p.2

, *r[a,xhi,eta]^2

Z. Psir-[-a_,

Z. ,

Z. ,

Z. Psis-[-a_,

. Datawork={}, . Dataec={}, and . Dataps={}, a0=1.01; af=2.3; p=24; print["a0"] print)*(n-1)/p; print, p.print

Z. Uz-[-a_ and R. Deriv,

Z. Ur-[-a_ and R. Deriv,

P. and Z. ,

, =a*Sqrt[1-z^2/b[a]^2-y^2/a^2]; yc[a_,z_,x_]:=a*Sqrt[1-z^2/b[a]^2-x^2/a^2]; zc[a_,x_,y_]:=b[a]*Sqrt, pp.1-2

W. ,

F. , , pp.2-3

. Gradi,

, Work, issue.002

*. Pi and *. ,

. Ec and . Re, ^2*Boole[Abs[Xhi

, PWork[y_]=parabolaWork Series[PWork[yy

. Show, . Listplot, . Datawork, . Plotstyle?red, and . Axeslabel?{y, Plot[{line, parabolaWork}, {y, a0, af}]] parabolaEc = Fit

. Show, . Listplot, . Dataec, . Plotstyle?red, and . Axeslabel?{y, Plot[{line, parabolaEc}, {y, a0, af},PlotRange?Full]] parabolaPs = Fit

, PPs[y_]=parabolaPs Series[PPs[yy

. Show,

, Show

Z. Vectorplota, R. Boolea, Z. , and R. Boole, Abs, issue.44, pp.1-4

/. 4}, . Framelabel?{z, and . Vectorplot, Boole[(r<0)&&(z<0)&&((r/a)^2+(z/b

D. , , p.883733

D. ,

D. ,

D. ,

D. ,

0. and {. ,

8. and {. , , p.762

, 1066},{1.81625,11.6728},{1.87,12.2692},{1.92375

4. and {. ,

5. and {. ,

D. ,

1. and {. ,

2. and {. , , p.8765

, 6039 (yy-1)+O[yy-1, 115792+39, issue.2

. Kpo,

. Kco,

, Kpo[1] Kco[1] 4.12003 9, p.97379

. Datawork-dataps,

0. and {. , 74024},{0.,-9.45243},{0.,-10.177},{0.,-10.9141}} PWork[y_]=parabolaWork Series[PWork[yy],{yy, p.1

, PPs[y_]=parabolaPs Series[PPs[yy],{yy

=. Parabolaps and . Fit,

. Pps and . Show,

, PPs[y_]=parabolaPs Series[PPs[yy

, 0899+24.8083 y+7.39785 y

, 604 (yy-1)+O[yy-1, 116212+39, issue.2

, EE

, V=4/3*Pi*R0^3; print

X. , Log, issue.2A

. Coordsphp, =CC[b]*Cosh[xhi+I*eta]; zp[b_,xhi_,eta_]:=Re[CoordSphp[b,xhi

Z. Xhip-[-b_,

Z. Etap-[-b_,

. Psi, , p.2

*. ,

Z. Psir-[-a_,

Z. Psi2rp-[-b_, , p.2

Z. ,

Z. Psis-[-a_,

Z. Psisp-[-b_, =1/2*U*R^2*(1-b^3/(Z^2+R^2)^(3

Z. Psis2p-[-b_,

. Dataworkp={} and . Dataecp={}, 5; bf=.99; p=10; print["b0"] print Do[ b=bf-(bf-b0)*(n-1)/p; print

Z. Uzp-[-b_,

Z. Urp-[-b_ and R. Deriv, , p.2

Z. Pp-[-b_, , p.2

, =b*Sqrt[1-y^2/b^2-z^2/A[b]^2]; ycp[b_,z_,x_]:=b*Sqrt[1-x^2/b^2-z^2/A[b]^2]; zcp[b_,x_,y_]:=A[b]*Sqrt, pp.1-2

. Wp and . Abs,

. Fp, , pp.2-3

. Gradip,

. Workp, , p.16

. Ecp, , p.0

W. Truc={b,

E. Trucmuch={b,

, AppendTo[DataWorkp,Truc

. Appendto and . Dataecp, TrucMuch]; printDataWorkp"]; print

, Plot[{line, parabolaWorkp}, {y, b0, bf}]] parabolaEcp = Fit

. Show,

Z. Vectorplotb, R. Booleb, Z. , and R. Boole, ^2<1.05)&&( (r/aa), pp.0-2

, RegionPlot, p.2

/. 4} and . Framelabel?{z, VectorPlot[{Wp[b,0,z], r>=0)&&(z?0)&&, pp.2-2

. Wp, , pp.0-0

. Wp, Boole[(r<0)&&(z<0)&&, p.2

, V_=, issue.4

, NIntegrate::eincr: The global error of the strategy GlobalAdaptive has increased more than _2000_ times. The global error is expected to decrease monotonically after a number of integrand evaluations Suspect one of the following: the working precision is insufficient for the specified precision goal; the integrand is highly oscillatory or it is not a (piecewise) smooth function; or the true value of the integral is 0. Increasing the value of the GlobalAdaptive option MaxErrorIncreases might lead to a convergent numerical integration. NIntegrate obtained _2.56363_+0. ? _ and _0.0005418850441368844`_ for the integral and error estimates for the integral and error estimates. ? General::stop: Further output of _NIntegrate::eincr_ will be suppressed during this calculation, NIntegrate::slwcon: Numerical integration converging too slowly; suspect one of the following: singularity0006115253336925903`_ for the integral and error estimates DataWorkp_=_{{0.99,-3.64832},{0.941,-3.08684},{0.892,-2.58066}} DataEcp_=_{{0.99

D. , 08684},{0.892,-2.58066},{0.843

1. and {. ,

1. and {. ,

1. and {. ,

, DataEcp_=_{{0.99,10.2545},{0.941,11.5067},{0.892,13.2425},{0.843,15.6394},{0.794

5. and {. ,

1. and {. , 745,-1.37346},{0.696,-1.06852},{0

5. and {. ,

, 593368}} DataEcp_=_{{0.99,10.2545},{0.941,11.5067},{0.892

5. and {. ,

5. and {. , 418563}} DataEcp_=_{{0.99,10.2545},{0.941

5. and {. ,

5. and {. ,

5. and {. , , pp.968-969

, 72_-9463.54 y+16349.9 y 2 -12723.9 y 3 +3739.49