Items tagged with equations

I have four matrix equations

P1, P2, P3 are known 4x4 matrix.

A1 A2 A3 A4 are known 1x4 matrix.

x1 x2 x3 x4 are 1x1 known matrix.

U is 4x4 unknown matrix.

These equations are 

(A1T*U*P1*A1) +( (P2*A1)T*U*P1*A1) + ( (P3*A1)T*U*A1) + ( ( P3*A 2)T*U*P1*A1) + x1 =0;

(A2T*U*P1*A2) +( (P2*A2)T*U*P1*A2) + ( (P3*A2)T*U*A2) + ( ( P3*A2 )T*U*P1*A2) + x2 =0;

(A3T*U*P1*A3) +( (P2*A3)T*U*P1*A3) + ( (P3*A3)T*U*A3) + ( ( P3*A3 )T*U*P1*A3) + x3 =0;

(A4T*U*P1*A4) +( (P2*A4)T*U*P1*A4) + ( (P3*A4)T*U*A4) + ( ( P3*A4 )T*U*P1*A4) + x4 =0;

How can i find 4x4 matrix U by using these above four equations??

Thank you

E_T := (2/mu-2/r)*exp(-r/mu)*Pi^2;

How do I extract the numbers out of the equation, so it becomes

2*Pi^2*(1/mu-1/r)*exp(-r/mu) instead? 


 

restart; with(plots); beta := 0.1e-1; Bi := 1; Pr := 3.0; L0 := 1; w = 0.2e-1

Eq1 := diff(f(eta), eta, eta, eta)+f(eta)*(diff(f(eta), eta, eta))-(diff(f(eta), eta))^2+beta*H(eta)*(F(eta)-(diff(f(eta), eta))) = 0

diff(diff(diff(f(eta), eta), eta), eta)+f(eta)*(diff(diff(f(eta), eta), eta))-(diff(f(eta), eta))^2+0.1e-1*H(eta)*(F(eta)-(diff(f(eta), eta))) = 0

(1)

Eq2 := G(eta)*(diff(F(eta), eta))+F(eta)^2+beta*(F(eta)-(diff(f(eta), eta))) = 0

G(eta)*(diff(F(eta), eta))+F(eta)^2+0.1e-1*F(eta)-0.1e-1*(diff(f(eta), eta)) = 0

(2)

Eq3 := G(eta)*(diff(G(eta), eta))+beta*(f(eta)+G(eta)) = 0

G(eta)*(diff(G(eta), eta))+0.1e-1*f(eta)+0.1e-1*G(eta) = 0

(3)

Eq4 := H(eta)*F(eta)+H(eta)*(diff(G(eta), eta))+G(eta)*(diff(H(eta), eta)) = 0

H(eta)*F(eta)+H(eta)*(diff(G(eta), eta))+G(eta)*(diff(H(eta), eta)) = 0

(4)

Eq5 := (diff(theta(eta), eta, eta))/Pr+f(eta)*(diff(theta(eta), eta))+(2*beta*H(eta)*(1/3))*(theta[p](eta)-theta(eta)) = 0

.3333333333*(diff(diff(theta(eta), eta), eta))+f(eta)*(diff(theta(eta), eta))+0.6666666667e-2*H(eta)*(theta[p](eta)-theta(eta)) = 0

(5)

Eq6 := G(eta)*(diff(theta[p](eta), eta))+L0*beta*(theta[p](eta)-theta(eta)) = 0

G(eta)*(diff(theta[p](eta), eta))+0.1e-1*theta[p](eta)-0.1e-1*theta(eta) = 0

(6)

bcs1 := f(0) = 0, (D(f))(0) = 1, (D(theta))(0) = -Bi*(1-theta(0)), (D(f))(5) = 0, F(5) = 0, G(5) = -f(5), H(5) = w, theta(5) = 0, theta[p](5) = 0

f(0) = 0, (D(f))(0) = 1, (D(theta))(0) = -1+theta(0), (D(f))(5) = 0, F(5) = 0, G(5) = -f(5), H(5) = w, theta(5) = 0, theta[p](5) = 0

(7)

p := dsolve({Eq1, Eq2, Eq3, Eq4, Eq5, Eq6, bcs1}, numeric)

Error, (in dsolve/numeric/process_input) system must be entered as a set/list of expressions/equations

 

odeplot(p, [eta, f(eta)], 0 .. 10);

odeplot(p, [eta, f(eta)], 0 .. 10)

(8)

``

 

 


 

Download from_net.mw

Hi guys,

 

I am trying to solve a Fredholm equation of the second kind using Maple. An analytical expression cannot be in principle found. I was wondering whether Maple does numerical evaluation of such integral equations. Please see the equation in attach. Any help is highly appreciated.

Thanks

F

 

Question.mw

The material below was presented in the "Semantic Representation of Mathematical Knowledge Workshop", February 3-5, 2016 at the Fields Institute, University of Toronto. It shows the approach I used for “digitizing mathematical knowledge" regarding Differential Equations, Special Functions and Solutions to Einstein's equations. While for these areas using databases of information helps (for example textbooks frequently contain these sort of databases), these are areas that, at the same time, are very suitable for using algorithmic mathematical approaches, that result in much richer mathematics than what can be hard-coded into a database. The material also focuses on an interesting cherry-picked collection of Maple functionality, that I think is beautiful, not well know, and seldom focused inter-related as here.

 

 

Digitizing of special functions,

differential equations,

and solutions to Einstein’s equations

within a computer algebra system

 

Edgardo S. Cheb-Terrab

Physics, Differential Equations and Mathematical Functions, Maplesoft

Editor, Computer Physics Communications

 

 

Digitizing (old paradigm)

 

• 

Big amounts of knowledge available to everybody in local machines or through the internet

• 

Take advantage of basic computer functionality, like searching and editing

 

 

Digitizing (new paradigm)

• 

By digitizing mathematical knowledge inside appropriate computational contexts that understand about the topics, one can use the digitized knowledge to automatically generate more and higher level knowledge

 

 

Challenges


1) how to identify, test and organize the key blocks of information,

 

2) how to access it: the interface,

 

3) how to mathematically process it to automatically obtain more information on demand

 

 

 

 

                                           Three examples


Mathematical Functions

 

"Mathematical functions, are defined by algebraic expressions. So consider algebraic expressions in general ..."

The FunctionAdvisor (basic)

 

"Supporting information on definitions, identities, possible simplifications, integral forms, different types of series expansions, and mathematical properties in general"

Examples

   

General description

   

References

   

 

Differential equation representation for generic nonlinear algebraic expressions - their use

 

"Compute differential polynomial forms for arbitrary systems of non-polynomial equations ..."

The Differential Equations representing arbitrary algebraic expresssions

   

Deriving knowledge: ODE solving methods

   

Extending the mathematical language to include the inverse functions

   

Solving non-polynomial algebraic equations by solving polynomial differential equations

   

References

   

 

Branch Cuts of algebraic expressions

 

"Algebraically compute, and visualize, the branch cuts of arbitrary mathematical expressions"

Examples

   

References

   

 

Algebraic expresssions in terms of specified functions

 

"A conversion network for arbitrary mathematical expressions, to rewrite them in terms of different functions in flexible ways"

Examples

   

General description

   

References

   

 

Symbolic differentiation of algebraic expressions

 

"Perform symbolic differentiation by combining different algebraic techniques, including functions of symbolic sequences and Faà di Bruno's formula"

Examples

   

References

   

 

Ordinary Differential Equations

 

"Beyond the concept of a database, classify an arbitrary ODE and suggest solution methods for it"

General description

   

Examples

   

References

   

 

Exact Solutions to Einstein's equations

 

 

Lambda*g[mu, nu]+G[mu, nu] = 8*Pi*T[mu, nu]

 

"The authors of "Exact solutions toEinstein's equations" reviewed more than 4,000 papers containing solutions to Einstein’s equations in the general relativity literature, organized the whole material into chapters according to the physical properties of these solutions. These solutions are key in the area of general relativity, are now all digitized and become alive in a worksheet"


The ability to search the database according to the physical properties of the solutions, their classification, or just by parts of keywords (old paradigm) changes the game.

More important, within a computer algebra system this knowledge becomes alive (new paradigm).

• 

The solutions are turned active by a simple call to one commend, called the g_  spacetime metric.

• 

Everything else gets automatically derived and set on the fly ( Christoffel symbols  , Ricci  and Riemann  tensors orthonormal and null tetrads , etc.)

• 

Almost all of the mathematical operations one can perform on these solutions are implemented as commands in the Physics  and DifferentialGeometry  packages.

• 

All the mathematics within the Maple library are instantly ready to work with these solutions and derived mathematical objects.

 

Finally, in the Maple PDEtools package , we have all the mathematical tools to tackle the equivalence problem around these solutions.

Examples

   

References

   

 

Download:  Digitizing_Mathematical_Information.mw,    Digitizing_Mathematical_Information.pdf

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

hi....how i can extract Coefficients  (i.e. {f1[2],f2[2],f2[3],f3[2],.....f3[6]}) from every algebric equations and create matrix A ,in form AX=0, (X are f1[2],f2[2],f2[3],f3[2],.....f3[6] ) then the determinant of the matrix of coefficients (A) set to zero for obtaining unknown parameter omega.?

Note that  if m=3 then 6 equations is appeare and if m=4 then 9 equations is appeare.thus i need a procedure that works for every arbitary value of ''m''.

in attached file below m=4 thus we have 9 equations, i.e. 3 for eq1[k_] and 3 for eq2[k_] and so on...

also we should use boundary conditions for some amount of fi[j] (i=1,2,3 and j=2,3,...,7)

be extacting above Coefficients for example from first equation ,

''**:= (1/128)*f1[2]*omega^2-(1/4)*f2[2]-(1/2)*f2[3]+(1/4)*f2[4]+(1/4)*f3[2]-(1/2)*f3[3]+(1/4)*f3[4]+140*f1[2]-80*f1[3]+20*f1[4]'''

must compute

coeff(**, f1[2]); coeff(**, f2[2]) and so on...

 

 

 

 

 

fdm-maple.mw

 

 ############################Define some parameters

 

 
restart; Digits := 15; A1 := 10; A2 := 10; A3 := 10; A4 := 1; A5 := 1; A6 := 1; A7 := 1; A8 := 1; A9 := 1; A10 := 1; A11 := 1; B1 := 10; B2 := 10; B3 := 10; B4 := 1; B5 := 1; B6 := 1; B7 := 1; B8 := 1; B9 := 1; B10 := 1; B11 := 1; C1 := 10; C2 := 10; C3 := 10; C4 := 1; C5 := 1; C6 := 1; C7 := 1; C8 := 1; C9 := 1; C10 := 1; C11 := 1; C12 := 1; C13 := 1; C14 := 1; C15 := 1; C16 := 1; A12 := 1; B12 := 1; C18 := 1; C17 := 1; C19 := 1; n := 1; U := proc (x, theta) options operator, arrow; f1(x)*cos(n*theta) end proc; V := proc (x, theta) options operator, arrow; f2(x)*sin(n*theta) end proc; W := proc (x, theta) options operator, arrow; f3(x)*cos(n*theta) end proc; n := 1; m := 4; len := 1; h := len/m; nn := m+1
 ############################Define some equation

eq1[k_] := -2*f1[k]*(-A11*n^4+A10*n^2+A12*omega^2)*h^4+(A6*(f2[k-1]-f2[k+1])*n^3+A9*(f3[k-1]-f3[k+1])*n^2-A5*(f2[k-1]-f2[k+1])*n-A8*(f3[k-1]-f3[k+1]))*h^3+(4*(f1[k]-(1/2)*f1[k-1]-(1/2)*f1[k+1]))*(A3*n^2-A2)*h^2+(-A4*(f2[k-2]-2*f2[k-1]+2*f2[k+1]-f2[k+2])*n-A7*(f3[k-2]-2*f3[k-1]+2*f3[k+1]-f3[k+2]))*h+12*A1*(f1[k]+(1/6)*f1[k-2]-(2/3)*f1[k-1]-(2/3)*f1[k+1]+(1/6)*f1[k+2]):
  ``

 

 

 

 

                                     ######################################  APPLY BOUNDARY CONDITIONS

f1[nn+1] := f1[m]:
 

for k from 2 to m do eq1[k_]; eq2[k_]; eq3[k_] end do

-(1/64)*f2[4]+(1/128)*f2[3]+(1/64)*(f3[4]-(1/2)*f3[3])*(omega^2-1)-(1/64)*f1[2]+(1/32)*f1[3]+(1/64)*f1[4]-280*f3[4]-120*f3[2]+300*f3[3]+20*f3[7]

(1)

``



Download fdm-maple.mw

 

hi...how i can convert 3 couple equations to 1 equation with Placement each other?

thanks...

 

3-1.mw

pd1 := A1*(diff(U(x, theta), x, x, x, x))+A2*(diff(U(x, theta), x, x))+A3*(diff(U(x, theta), x, x, theta, theta))+A4*(diff(V(x, theta), x, x, x, theta))+A5*(diff(V(x, theta), x, theta))+A6*(diff(V(x, theta), x, theta, theta, theta))+A7*(diff(W(x, theta), x, x, x))+A8*(diff(W(x, theta), x))+A9*(diff(W(x, theta), x, theta, theta))+A10*(diff(U(x, theta), theta, theta))+A11*(diff(U(x, theta), theta, theta, theta, theta))-A12*omega^2*U(x, theta)

A1*(diff(diff(diff(diff(U(x, theta), x), x), x), x))+A2*(diff(diff(U(x, theta), x), x))+A3*(diff(diff(diff(diff(U(x, theta), theta), theta), x), x))+A4*(diff(diff(diff(diff(V(x, theta), theta), x), x), x))+A5*(diff(diff(V(x, theta), theta), x))+A6*(diff(diff(diff(diff(V(x, theta), theta), theta), theta), x))+A7*(diff(diff(diff(W(x, theta), x), x), x))+A8*(diff(W(x, theta), x))+A9*(diff(diff(diff(W(x, theta), theta), theta), x))+A10*(diff(diff(U(x, theta), theta), theta))+A11*(diff(diff(diff(diff(U(x, theta), theta), theta), theta), theta))-A12*omega^2*U(x, theta)

(1)

pd2 := B1*(diff(V(x, theta), x, x, x, x))+B2*(diff(V(x, theta), x, x))+B3*(diff(V(x, theta), theta, theta, theta, theta))+B4*(diff(V(x, theta), theta, theta))+B5*(diff(V(x, theta), x, x, theta, theta))+B6*(diff(U(x, theta), x, x, x, theta))+B7*(diff(U(x, theta), x, theta, theta, theta))+B8*(diff(U(x, theta), x, theta))+B9*(diff(W(x, theta), x, x, theta))+B10*(diff(W(x, theta), theta, theta, theta))+B11*(diff(W(x, theta), theta))-B12*omega^2*V(x, theta)

B1*(diff(diff(diff(diff(V(x, theta), x), x), x), x))+B2*(diff(diff(V(x, theta), x), x))+B3*(diff(diff(diff(diff(V(x, theta), theta), theta), theta), theta))+B4*(diff(diff(V(x, theta), theta), theta))+B5*(diff(diff(diff(diff(V(x, theta), theta), theta), x), x))+B6*(diff(diff(diff(diff(U(x, theta), theta), x), x), x))+B7*(diff(diff(diff(diff(U(x, theta), theta), theta), theta), x))+B8*(diff(diff(U(x, theta), theta), x))+B9*(diff(diff(diff(W(x, theta), theta), x), x))+B10*(diff(diff(diff(W(x, theta), theta), theta), theta))+B11*(diff(W(x, theta), theta))-B12*omega^2*V(x, theta)

(2)

pd3 := C1*(diff(W(x, theta), x, x, x, x, x, x))+C2*(diff(W(x, theta), x, x, x, x))+C3*(diff(W(x, theta), x, x, x, x, theta, theta))+C4*(diff(W(x, theta), x, x))+C5*(diff(W(x, theta), x, x, theta, theta))+C6*(diff(W(x, theta), x, x, theta, theta, theta, theta))+C7*(diff(U(x, theta), x, x, x))+C8*(diff(U(x, theta), x))+C9*(diff(U(x, theta), x, theta, theta))+C10*(diff(V(x, theta), x, x, theta))+C11*(diff(V(x, theta), theta))+C12*(diff(V(x, theta), theta, theta, theta))+C13*W(x, theta)+C14*(diff(W(x, theta), theta, theta))+C15*(diff(W(x, theta), theta, theta, theta, theta))+C16*(diff(W(x, theta), theta, theta, theta, theta, theta, theta))-C19*omega^2*W(x, theta)-C18*omega^2*(diff(W(x, theta), theta, theta))-C17*omega^2*(diff(W(x, theta), x, x))

C1*(diff(diff(diff(diff(diff(diff(W(x, theta), x), x), x), x), x), x))+C2*(diff(diff(diff(diff(W(x, theta), x), x), x), x))+C3*(diff(diff(diff(diff(diff(diff(W(x, theta), theta), theta), x), x), x), x))+C4*(diff(diff(W(x, theta), x), x))+C5*(diff(diff(diff(diff(W(x, theta), theta), theta), x), x))+C6*(diff(diff(diff(diff(diff(diff(W(x, theta), theta), theta), theta), theta), x), x))+C7*(diff(diff(diff(U(x, theta), x), x), x))+C8*(diff(U(x, theta), x))+C9*(diff(diff(diff(U(x, theta), theta), theta), x))+C10*(diff(diff(diff(V(x, theta), theta), x), x))+C11*(diff(V(x, theta), theta))+C12*(diff(diff(diff(V(x, theta), theta), theta), theta))+C13*W(x, theta)+C14*(diff(diff(W(x, theta), theta), theta))+C15*(diff(diff(diff(diff(W(x, theta), theta), theta), theta), theta))+C16*(diff(diff(diff(diff(diff(diff(W(x, theta), theta), theta), theta), theta), theta), theta))-C19*omega^2*W(x, theta)-C18*omega^2*(diff(diff(W(x, theta), theta), theta))-C17*omega^2*(diff(diff(W(x, theta), x), x))

(3)

``


Download 3-1.mw

Dear All,

I have a problem solving the attached nonlinear system of equations using shooting method.
I will be grateful if you could help me finding the solutions out.

 

restart; Shootlib := "C:/Shoot9"; libname := Shootlib, libname; with(Shoot);
with(plots);
N1 := 1.0; N2 := 2.0; N3 := .5; Bt := 6; Re_m := N1*Bt; gamma1 := 1;
FNS := {f(eta), fp(eta), fpp(eta), g(eta), gp(eta), m(eta), mp(eta), n(eta), np(eta), fppp(eta)};
ODE := {diff(f(eta), eta) = fp(eta), diff(fp(eta), eta) = fpp(eta), diff(fpp(eta), eta) = fppp(eta), diff(g(eta), eta) = gp(eta), diff(gp(eta), eta) = N1*(2.*g(eta)+(eta-2.*f(eta)).gp(eta)+2.*g(eta)*fp(eta)+2.*N2.N3.(m(eta).np(eta)-n(eta).mp(eta))), diff(m(eta), eta) = mp(eta), diff(mp(eta), eta) = Re_m.(m(eta)+(eta-2.*f(eta)).mp(eta)+2.*m(eta)*fp(eta)), diff(n(eta), eta) = np(eta), diff(np(eta), eta) = Re_m.(2.*n(eta)+(eta-2.*f(eta)).np(eta)+2.*N2/N3.m(eta).gp(eta)), diff(fppp(eta), eta) = N1*(3.*fpp(eta)+(eta-2.*f(eta)).fppp(eta)-2.*N2.N2.m(eta).(diff(mp(eta), eta)))};
blt := 1.0; IC := {f(0) = 0, fp(0) = 0, fpp(0) = alpha1, g(0) = 1, gp(0) = beta1, m(0) = 0, mp(0) = beta2, n(0) = 0, np(0) = beta3, fppp(0) = alpha2};
BC := {f(blt) = .5, fp(blt) = 0, g(blt) = 0, m(blt) = 1, n(blt) = 1};
infolevel[shoot] := 1;
S := shoot(ODE, IC, BC, FNS, [alpha1 = 1.425, alpha2 = .425, beta1 = -1.31, beta2 = 1.00, beta3 = 1.29]);
Error, (in isolate) cannot isolate for a function when it appears with different arguments
p := odeplot(S, [eta, fp(eta)], 0 .. 15);
Error, (in plots/odeplot) input is not a valid dsolve/numeric solution
display(p);
Error, (in plots:-display) expecting plot structure but received: p
p2 := odeplot(S, [eta, theta(eta)], 0 .. 10);
Error, (in plots/odeplot) input is not a valid dsolve/numeric solution
display(p2);
Error, (in plots:-display) expecting plot structure but received: p2

 

 

      General description of the method of solving underdetermined systems of equations. As a particular application of the idea proposed a universal method  kinematic analysis for all kinds of linkage (lever) mechanisms. With the description and examples.
      The method can be used for powerful CAD linkages.

Description: Calculation_method_of_linkages.pdf

Attachment:
figure_1.mw
figure_2.mw

Or all in one
Calculation_method_of_linkages_(with_attach.).pdf


        Some examples of a much larger number calculated by the proposed method. Examples gathered here not to look for them on the forum and opportunity to demonstrate the method.  Among the examples, I think, there are very complicated.

https://vk.com/doc242471809_408704758
https://vk.com/doc242471809_408704572
https://vk.com/doc242471809_376439263
https://vk.com/doc242471809_402619761
https://vk.com/doc242471809_402610228
https://vk.com/doc242471809_401188803
https://vk.com/doc242471809_400465891
https://vk.com/doc242471809_400711315
https://vk.com/doc242471809_387358164
https://vk.com/doc242471809_380837279
https://vk.com/doc242471809_379935473
https://vk.com/doc242471809_380217387
https://vk.com/doc242471809_363266817
https://vk.com/doc242471809_353980472
https://vk.com/doc242471809_375452868
https://vk.com/doc242471809_353988163 
https://vk.com/doc242471809_353986884 
https://vk.com/doc242471809_353987119
https://vk.com/doc242471809_324249241
https://vk.com/doc242471809_324102889
https://vk.com/doc242471809_322219275
https://vk.com/doc242471809_437298137
https://vk.com/doc242471809_437308238
https://vk.com/doc242471809_437308241
https://vk.com/doc242471809_437308243
https://vk.com/doc242471809_437308245
https://vk.com/doc242471809_437308246
https://vk.com/doc242471809_437401651
https://vk.com/doc242471809_437664558

 

 

hello every one.please help me with solving this equations.i can not solve this and i need it.thanks


eq1 := (cos(beta2)-1)*w11-sin(beta2)*w12+(cos(alpha2)-1)*z11-sin(alpha2)*z12-cos(delta2) = 0; eq2 := (cos(beta2)-1)*w12+sin(beta2)*w11+(cos(alpha2)-1)*z12+sin(alpha2)*z11-2*sin(delta2) = 0; eq3 := (cos(beta3)-1)*w11-sin(beta3)*w12+(cos(alpha3)-1)*z11-sin(alpha3)*z12-3*cos(delta3) = 0; eq4 := (cos(beta3)-1)*w12+sin(beta3)*w11+(cos(alpha3)-1)*z12+sin(alpha3)*z11-4*sin(delta3) = 0; eq5 := (cos(beta4)-1)*w11-sin(beta4)*w12+(cos(alpha4)-1)*z11-sin(alpha4)*z12-5*cos(delta4) = 0; eq6 := (cos(beta4)-1)*w12+sin(beta4)*w11+(cos(alpha4)-1)*z12+sin(alpha4)*z11-6*sin(delta4) = 0; eq7 := (cos(beta5)-1)*w11-sin(beta5)*w12+(cos(alpha5)-1)*z11-sin(alpha5)*z12-7*cos(delta5) = 0; eq8 := (cos(beta5)-1)*w12+sin(beta5)*w11+(cos(alpha5)-1)*z12+sin(alpha5)*z11-8*sin(delta5) = 0; alpha2 := -20; alpha3 := -45; alpha4 := -75; alpha5 := -90; delta2 := 15.5; delta3 := -15.9829; delta4 := -13.6018; delta5 := -16.7388; P21 = .5217; P31 = 1.3421; P41 = 2.3116; P51 = 3.1780;

Hi,

I have attached a Maple file. My problem is that the solve for the simultaneous equation does not give me understandable results. I even simplified my equations by saying some parameters are zero although my final goal is to find an expression for a and varphi. Any idea how to solve this analytically? I know how to do it numerically. I need an analytical expression.

Thanks,

Baharm31

 

how i can calculate roots of the characteristic polynomial equations {dsys and dsys2}
and dsolve them with arbitrary initial condition for differennt amont of m and n?
thanks
Kr.mw

restart; a := 1; b := 2; Number := 10; q := 1; omega := 0.2e-1
``

Q1 := besselj(0, xi*b)*(eval(diff(bessely(0, xi*r), r), r = a))-(eval(diff(besselj(0, xi*r), r), r = a))*bessely(0, xi*b):

J := 0:

m := 0:

U1 := (int(r*K1[m]*(diff(K_01[m], r)+K_01[m]/r), r = a .. b))/(int(r*K1[m]^2, r = a .. b)); -1; U2 := -(int(r*K_01[m]*(diff(K1[m], r)), r = a .. b))/(int(r*K_01[m]^2, r = a .. b)); -1; U3 := (int(r^2*omega^2*K_01[m], r = a .. b))/(int(r*K_01[m]^2, r = a .. b))

0.6222222222e-3/K_01[12]

(1)

Q2 := besselj(1, eta*b)*(eval(diff(bessely(1, eta*r), r), r = a))-(eval(diff(besselj(1, eta*r), r), r = a))*bessely(1, eta*b):

E2 := unapply(Q2, eta):

m := 0:

 
dsys := {diff(S_mn(t), t, t, t)+xi[m]^2*(diff(S_mn(t), t, t))+(-U1*U2+eta__n^2)*(diff(S_mn(t), t))+xi[m]^2*eta__n^2*S_mn(t) = -(2*U2*b_m/(Pi*xi[m])*(-besselj(0, xi[m]*b)/besselj(1, xi[m]*a)))*q+xi[m]^2*U3}; 1; dsolve(dsys)

{S_mn(t) = (3111111111/5000000000000)/(K_01[12]*eta__n^2)+_C1*cos(eta__n*t)+_C2*sin(eta__n*t)+_C3*exp(-xi[12]^2*t)}

(2)

dsys2 := {diff(Q_mn(t), t, t, t)+xi[m]^2*(diff(Q_mn(t), t, t))+(-U1*U2+eta__n^2)*(diff(Q_mn(t), t))+xi[m]^2*eta__n^2*Q_mn(t) = -2*besselj(0, xi[m]*b)*U1*U2*b_m*(1-exp(-xi[m]^2*t))/(besselj(1, xi[m]*a)*Pi*xi[m]^3)}; 1; dsolve(dsys2)

{Q_mn(t) = _C1*exp(-xi[12]^2*t)+_C2*sin(eta__n*t)+_C3*cos(eta__n*t)}

(3)

``

 

``



Download Kr.mw

 

I have been working on a general solution to motion analysis and seem to be going backwards.  I have an numerical solution in Octave I use for comparison.  I have reduced the problem to a small example that exhibits the problem.

I posted a question similar to this, but, without a set of known values.

I am doing something wrong, but, what?

Tom Dean

## bearing.mpl, solve the target motion problem with bearings only.
##
## Consider a sensor platform moving through points (x,y) at times
## t[1..4] with the target bearings, Brg[1..4] taken at times t[1..4]
## with the target proceeding along a constant course and speed.
##
## time t, bearing line slope m, sensor position (x,y) are known
## values.
##
## Since this is a generated problem the target position at time t is
## provided to compare with the results.
##
#########################################################################
##
restart;
##
genKnownValues := proc()
    description "set the known values",
    "t - relative time",
    "x - sensor x location at time t[i]",
    "y - sensor y location at time t[i]",
    "m - slope of the bearing lines at time t[i]",
    "tgtPosit - target position at time t[i]";
    global t, m, x, y, tgtPosit;
    local dt, Cse, Spd, Brg, A, B, C, R, X;
    local tgtX, tgtY, tgtRange, tgtCse, tgtSpd;
## relative and delta time
    t := [0, 1+1/2, 3, 3+1/2];
    dt := [0, seq(t[idx]-t[idx-1],idx=2..4)];
## sensor motion
    Cse := [90, 90, 90, 50] *~ Pi/180; ## true heading
    Spd := [15, 15, 15, 22];  ## knots
## bearings to the target at time t
    Brg := [10, 358, 340, 330] *~ (Pi/180);
## slope of the bearing lines
    m:=map(tan,Brg);
## calculate the sensor position vs time
    x := ListTools[PartialSums](dt *~ Spd *~ map(cos, Cse));
    y := ListTools[PartialSums](dt *~ Spd *~ map(sin, Cse));
## target values  start the target at a known (x,y) position at a
## constant course and speed
    tgtRange := 95+25/32; ## miles at t1, match octave value...
    tgtCse := 170 * Pi/180; ## course
    tgtSpd := 10; ## knots
    tgtX := tgtRange*cos(Brg[1]);
    tgtX := tgtX +~ ListTools[PartialSums](dt *~ tgtSpd *~ cos(tgtCse));
    tgtY := tgtRange*sin(Brg[1]);
    tgtY := tgtY +~ ListTools[PartialSums](dt *~ tgtSpd *~ sin(tgtCse));
## return target position vs time as a matrix
    tgtPosit:=Matrix(4,2,[seq([tgtX[idx],tgtY[idx]],idx=1..4)]);
end proc:
##
#########################################################################
## t[], m[], x[], and y[] are known values
##
## equation of the bearing lines
eq1 := tgtY[1] - y[1]    = m[1]*(tgtX[1]-x[1]):
eq2 := tgtY[2] - y[2]    = m[2]*(tgtX[2]-x[2]):
eq3 := tgtY[3] - y[3]    = m[3]*(tgtX[3]-x[3]):
eq4 := tgtY[4] - y[4]    = m[4]*(tgtX[4]-x[4]):
## target X motion along the target line
eq5 := tgtX[2] - tgtX[1] = tgtVx*(t[2]-t[1]):
eq6 := tgtX[3] - tgtX[2] = tgtVx*(t[3]-t[2]):
eq7 := tgtX[4] - tgtX[3] = tgtVx*(t[4]-t[3]):
## target Y motion along the target line
eq8 := tgtY[2] - tgtY[1] = tgtVy*(t[2]-t[1]):
eq9 := tgtY[3] - tgtY[2] = tgtVy*(t[3]-t[2]):
eq10:= tgtY[4] - tgtY[3] = tgtVy*(t[4]-t[3]):
##
#########################################################################
##
## solve the equations
eqs  := {eq1,eq2,eq3,eq4,eq5,eq6,eq7,eq8,eq9,eq10}:

Sol:= solve(eqs, {tgtVx, tgtVy, seq([tgtX[k], tgtY[k]][], k= 1..4)}):
##

genKnownValues():
## these values are very close to Octave
evalf(t);evalf(m);evalf(x);evalf(y);evalf(tgtPosit);
## The value of tgtX[] and tgtY[] should equal the respective tgtPosit values
seq(evalf(eval([tgtX[idx],tgtY[idx]], Sol)),idx=1..4);

 


Dear all,

I wold like to find the solution of the next system of two equations with three unknowns but we assume that the unknows are positive integers. How the following code can work. Many thanks

 

 

 

> restart;
> assume(J, integer, J >= 0);
> assume(A, integer, A >= 0);
> assume(T, integer, T >= 0);
> eq1 := J+10*A+50*T=500;
   eq2 := J+A+T = 100;
  solve( {eq1,eq2},{J,A,T});

     Example of the equidistant surface at a distance of 0.25 to the surface
x3
-0.1 * (sin (4 * x1) + sin (3 * x2 + x3) + sin (2 * x2)) = 0
Constructed on the basis of universal parameterization of surfaces.

equidistant_surface.mw 


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