# Component based ModelingToolkit

**URL:** <https://discourse.julialang.org/t/component-based-modelingtoolkit/85499>\
**Category:** Modelling & Simulations\
**Tags:** modelingtoolkit, differentialequation\
**Created:** [August 8, 2022, 7:21pm UTC](https://discourse.julialang.org/t/component-based-modelingtoolkit/85499 "2022-08-08T19:21:37Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![JOAO\_PEREIRA](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/joao_pereira/32/33420_2.png) [@JOAO\_PEREIRA](https://discourse.julialang.org/u/JOAO_PEREIRA)\
**Post date:** [August 8, 2022, 7:21pm UTC](https://discourse.julialang.org/t/component-based-modelingtoolkit/85499/1 "2022-08-08T19:21:37Z")

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Hi, I would like to solve the system below as a component based modeling. DifferentialEquations is a possibility to solve as steady states.

‘’’  
using ModelingToolkit, NonlinearSolve

function plant\_7\_1\_b()  
ModelingToolkit.@variables m2 p2  
ModelingToolkit.@parameters m1 p1

```
eqs = [0 ~ m1 - m2
0 ~ p1 - p2]
        

@named ns = NonlinearSystem(eqs, [m2,p2], [m1,p1])

guess = [m2 => 20.0,
p2 => 0.5]

ps = [  
    m1 => 20.0
    p1 => 0.5
    ]

prob = NonlinearProblem(ns,guess,ps)
sol = solve(prob,NewtonRaphson())

println("mcond_out = ", round(sol[1],digits=1)," kg/s")
println("pcond_out = ", round(sol[2],digits=1)," bar")

```

end

@time plant\_7\_1\_b();

‘’’

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<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [August 8, 2022, 9:45pm UTC](https://discourse.julialang.org/t/component-based-modelingtoolkit/85499/2 "2022-08-08T21:45:34Z")

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I’m not sure what your question is?