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SciML / NonlinearSolve.jl

High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
https://docs.sciml.ai/NonlinearSolve/stable/
MIT License
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Solving a nonlinear equation using NonlinearSolve.jl with AutoFiniteDiff() yields errors about dual number #408

Closed qlx17 closed 2 months ago

qlx17 commented 2 months ago

EDIT: This issue has been posted in the julia forum.

Describe the bug 🐞

I am trying to solve a nonlinear equation, which is constructed using the thermophysical properties of fluids via CoolProp package (See MRE 1). The error message seems to indicate that PropsSI() cannot accept a dual number as an argument. Following the FAQ: The solver tried to set a Dual Number in my Vector of Floats. How do I fix that? in the NonlinearSolve.jl documentation, I have initialized the rho_fre with the same element type as p, but that doesn’t help.

I am not familiar with dual number, by google what it is, I think it is used when automatically differentiating the objective function. Therefore, I tried another solution in the FAQ, which is to specify the autodiff to be AutoFiniteDiff() (using the RobustMultiNewton() solver). The revised code is as MRE 2, but it yields the same error message, complaining about the dual number usage in PropsSI(). I find a similar issue being reported #360 , but in my case, using TrustRegion() still does not resolve the problem (See MRE 3).

My questions are:

  1. Should the PropsSI() function in the CoolProp package be modified to accept a dual number as an argument?

  2. Why does the AutoFiniteDiff() still yield the error about dual number? I expect this error only happens when automatic differentiation is used.

Expected behavior

The equation can be solved successfully when specifying autodiff = AutoFiniteDiff()

Minimal Reproducible Example 1 (not specifying autodiff = AutoFiniteDiff())👇

using NonlinearSolve, CoolProp

function myfun_P_MWE(p, (T, init_m))
    r_cont_ads = 10e-3
    r_ads_heat = 2.5e-3
    L = 0.5
    row_GGHS = 3
    row_cont = 3
    row_ads = 10
    delta_r_ads = (r_cont_ads - r_ads_heat) / row_ads

    rho_fre = zeros(typeof(p), row_ads)
    for i in eachindex(rho_fre)
        # Obtain the density of nitrogen according to temperature and pressure
        rho_fre[i] = PropsSI("D", "T", T[row_GGHS+row_cont+i], "P", p, "nitrogen")
    end

    # Construct the nonlinear equation
    f = 0.0
    for i in eachindex(rho_fre)
        f = f + rho_fre[i] * ((r_cont_ads - (i - 1) * delta_r_ads)^2 - (r_cont_ads - i * delta_r_ads)^2) / 2 * L
    end
    return f - init_m
end

# Solving the equation
T = collect(range(200.0, 500.0, 19))
p = 1e5
init_m = 2e-4

# myfun_P_MWE(p,(T, init_m))
p_new = solve(
    NonlinearProblem(myfun_P_MWE, p, (T, init_m))
    # RobustMultiNewton(; autodiff=AutoFiniteDiff())
).u

Error & Stacktrace 1⚠️

ERROR: MethodError: no method matching Float64(::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})

Closest candidates are:
  (::Type{T})(::Real, ::RoundingMode) where T<:AbstractFloat
   @ Base rounding.jl:207
  (::Type{T})(::T) where T<:Number
   @ Core boot.jl:792
  Float64(::IrrationalConstants.Sqrt2)
   @ IrrationalConstants C:\Users\qlx\.julia\packages\IrrationalConstants\vp5v4\src\macro.jl:112
  ...

Stacktrace:
  [1] convert(::Type{Float64}, x::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})
    @ Base .\number.jl:7
  [2] cconvert(T::Type, x::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})
    @ Base .\essentials.jl:543
  [3] PropsSI(output::String, name1::String, value1::Float64, name2::String, value2::ForwardDiff.Dual{…}, fluid::String)
    @ CoolProp C:\Users\qlx\.julia\packages\CoolProp\RDEcq\src\CoolProp.jl:81
  [4] myfun_P_MWE(p::ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 1}, ::Tuple{Vector{…}, Float64})
    @ Main c:\Users\qlx\Desktop\RB4_AP4_multi_stage_Julia_CoolProp\test2.jl:15
  [5] NonlinearFunction
    @ C:\Users\qlx\.julia\packages\SciMLBase\NjslX\src\scimlfunctions.jl:2185 [inlined]
  [6] JacobianWrapper
    @ C:\Users\qlx\.julia\packages\SciMLBase\NjslX\src\function_wrappers.jl:103 [inlined]
  [7] __value_derivative
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:186 [inlined]
  [8] JacobianCache
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:118 [inlined]
  [9] JacobianCache
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:106 [inlined]
 [10] __step!(cache::NonlinearSolve.GeneralizedFirstOrderAlgorithmCache{…}; recompute_jacobian::Nothing, kwargs::@Kwargs{})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generalized_first_order.jl:208
 [11] __step!
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generalized_first_order.jl:204 [inlined]
 [12] #step!#210
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:55 [inlined]
 [13] step!
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:50 [inlined]
 [14] solve!(cache::NonlinearSolve.GeneralizedFirstOrderAlgorithmCache{…})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:13
 [15] #__solve#209
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:4 [inlined]
 [16] __solve
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:1 [inlined]
 [17] macro expansion
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\default.jl:278 [inlined]
 [18] __solve(::NonlinearProblem{…}, ::NonlinearSolvePolyAlgorithm{…}; alias_u0::Bool, verbose::Bool, kwargs::@Kwargs{…})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\default.jl:248
 [19] __solve
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\default.jl:248 [inlined]
 [20] #__solve#329
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\default.jl:511 [inlined]
 [21] __solve
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\default.jl:508 [inlined]
 [22] #__solve#72
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1394 [inlined]
 [23] __solve
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1386 [inlined]
 [24] #solve_call#44
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:612 [inlined]
 [25] solve_call
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:569 [inlined]
 [26] #solve_up#53
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1072 [inlined]
 [27] solve_up
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1066 [inlined]
 [28] #solve#52
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1060 [inlined]
 [29] solve(::NonlinearProblem{…})
    @ DiffEqBase C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1050
 [30] top-level scope
    @ c:\Users\qlx\Desktop\RB4_AP4_multi_stage_Julia_CoolProp\test2.jl:33
Some type information was truncated. Use `show(err)` to see complete types.

Minimal Reproducible Example 2 (using RobustMultiNewton() with autodiff = AutoFiniteDiff())👇

using NonlinearSolve, CoolProp

function myfun_P_MWE(p, (T, init_m))
    r_cont_ads = 10e-3
    r_ads_heat = 2.5e-3
    L = 0.5
    row_GGHS = 3
    row_cont = 3
    row_ads = 10
    delta_r_ads = (r_cont_ads - r_ads_heat) / row_ads

    rho_fre = zeros(typeof(p), row_ads)
    for i in eachindex(rho_fre)
        # Obtain the density of nitrogen according to temperature and pressure
        rho_fre[i] = PropsSI("D", "T", T[row_GGHS+row_cont+i], "P", p, "nitrogen")
    end

    # Construct the nonlinear equation
    f = 0.0
    for i in eachindex(rho_fre)
        f = f + rho_fre[i] * ((r_cont_ads - (i - 1) * delta_r_ads)^2 - (r_cont_ads - i * delta_r_ads)^2) / 2 * L
    end
    return f - init_m
end

# Solving the equation
T = collect(range(200.0, 500.0, 19))
p = 1e5
init_m = 2e-4

# myfun_P_MWE(p,(T, init_m))
p_new = solve(
    NonlinearProblem(myfun_P_MWE, p, (T, init_m)),
    RobustMultiNewton(; autodiff=AutoFiniteDiff())
).u

Error & Stacktrace 2⚠️

ERROR: MethodError: no method matching Float64(::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})

Closest candidates are:
  (::Type{T})(::Real, ::RoundingMode) where T<:AbstractFloat
   @ Base rounding.jl:207
  (::Type{T})(::T) where T<:Number
   @ Core boot.jl:792
  Float64(::IrrationalConstants.Sqrt2)
   @ IrrationalConstants C:\Users\qlx\.julia\packages\IrrationalConstants\vp5v4\src\macro.jl:112
  ...

Stacktrace:
  [1] convert(::Type{Float64}, x::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})
    @ Base .\number.jl:7
  [2] cconvert(T::Type, x::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})
    @ Base .\essentials.jl:543
  [3] PropsSI(output::String, name1::String, value1::Float64, name2::String, value2::ForwardDiff.Dual{…}, fluid::String)
    @ CoolProp C:\Users\qlx\.julia\packages\CoolProp\RDEcq\src\CoolProp.jl:81
  [4] myfun_P_MWE(p::ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 1}, ::Tuple{Vector{…}, Float64})
    @ Main c:\Users\qlx\Desktop\RB4_AP4_multi_stage_Julia_CoolProp\test2.jl:15
  [5] NonlinearFunction
    @ C:\Users\qlx\.julia\packages\SciMLBase\NjslX\src\scimlfunctions.jl:2185 [inlined]
  [6] JacobianWrapper
    @ C:\Users\qlx\.julia\packages\SciMLBase\NjslX\src\function_wrappers.jl:103 [inlined]
  [7] __value_derivative
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:186 [inlined]
  [8] JacobianCache
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:118 [inlined]
  [9] JacobianCache
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:106 [inlined]
 [10] __step!(cache::NonlinearSolve.GeneralizedFirstOrderAlgorithmCache{…}; recompute_jacobian::Nothing, kwargs::@Kwargs{})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generalized_first_order.jl:208
 [11] __step!
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generalized_first_order.jl:204 [inlined]
 [12] #step!#210
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:55 [inlined]
 [13] step!
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:50 [inlined]
 [14] solve!(cache::NonlinearSolve.GeneralizedFirstOrderAlgorithmCache{…})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:13
 [15] #__solve#209
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:4 [inlined]
 [16] __solve
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:1 [inlined]
 [17] macro expansion
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\default.jl:278 [inlined]
 [18] __solve(::NonlinearProblem{…}, ::NonlinearSolvePolyAlgorithm{…}; alias_u0::Bool, verbose::Bool, kwargs::@Kwargs{})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\default.jl:248
 [19] __solve
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\default.jl:248 [inlined]
 [20] #solve_call#44
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:612 [inlined]
 [21] solve_call
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:569 [inlined]
 [22] #solve_up#53
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1072 [inlined]
 [23] solve_up
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1066 [inlined]
 [24] #solve#52
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1060 [inlined]
 [25] solve(prob::NonlinearProblem{…}, args::NonlinearSolvePolyAlgorithm{…})
    @ DiffEqBase C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1050
 [26] top-level scope
    @ c:\Users\qlx\Desktop\RB4_AP4_multi_stage_Julia_CoolProp\test2.jl:33
Some type information was truncated. Use `show(err)` to see complete types.

Minimal Reproducible Example 3 (using TrustRegion() with autodiff = AutoFiniteDiff())👇

using NonlinearSolve, CoolProp

function myfun_P_MWE(p, (T, init_m))
    r_cont_ads = 10e-3
    r_ads_heat = 2.5e-3
    L = 0.5
    row_GGHS = 3
    row_cont = 3
    row_ads = 10
    delta_r_ads = (r_cont_ads - r_ads_heat) / row_ads

    rho_fre = zeros(typeof(p), row_ads)
    for i in eachindex(rho_fre)
        # Obtain the density of nitrogen according to temperature and pressure
        rho_fre[i] = PropsSI("D", "T", T[row_GGHS+row_cont+i], "P", p, "nitrogen")
    end

    # Construct the nonlinear equation
    f = 0.0
    for i in eachindex(rho_fre)
        f = f + rho_fre[i] * ((r_cont_ads - (i - 1) * delta_r_ads)^2 - (r_cont_ads - i * delta_r_ads)^2) / 2 * L
    end
    return f - init_m
end

# Solving the equation
T = collect(range(200.0, 500.0, 19))
p = 1e5
init_m = 2e-4

# myfun_P_MWE(p,(T, init_m))
p_new = solve(
    NonlinearProblem(myfun_P_MWE, p, (T, init_m)),
    # RobustMultiNewton(; autodiff=AutoFiniteDiff())
    TrustRegion(autodiff=AutoFiniteDiff(), radius_update_scheme=RadiusUpdateSchemes.Bastin)
).u

Error & Stacktrace 3⚠️

ERROR: MethodError: no method matching Float64(::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})

Closest candidates are:
  (::Type{T})(::Real, ::RoundingMode) where T<:AbstractFloat
   @ Base rounding.jl:207
  (::Type{T})(::T) where T<:Number
   @ Core boot.jl:792
  Float64(::IrrationalConstants.Sqrt2)
   @ IrrationalConstants C:\Users\qlx\.julia\packages\IrrationalConstants\vp5v4\src\macro.jl:112
  ...

Stacktrace:
  [1] convert(::Type{Float64}, x::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})
    @ Base .\number.jl:7
  [2] cconvert(T::Type, x::ForwardDiff.Dual{ForwardDiff.Tag{SciMLBase.JacobianWrapper{…}, Float64}, Float64, 1})
    @ Base .\essentials.jl:543
  [3] PropsSI(output::String, name1::String, value1::Float64, name2::String, value2::ForwardDiff.Dual{…}, fluid::String)
    @ CoolProp C:\Users\qlx\.julia\packages\CoolProp\RDEcq\src\CoolProp.jl:81
  [4] myfun_P_MWE(p::ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 1}, ::Tuple{Vector{…}, Float64})
    @ Main c:\Users\qlx\Desktop\RB4_AP4_multi_stage_Julia_CoolProp\test2.jl:15
  [5] NonlinearFunction
    @ C:\Users\qlx\.julia\packages\SciMLBase\NjslX\src\scimlfunctions.jl:2185 [inlined]
  [6] JacobianWrapper
    @ C:\Users\qlx\.julia\packages\SciMLBase\NjslX\src\function_wrappers.jl:103 [inlined]
  [7] __value_derivative
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:186 [inlined]
  [8] JacobianCache
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:118 [inlined]
  [9] JacobianCache
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\internal\jacobian.jl:106 [inlined]
 [10] __step!(cache::NonlinearSolve.GeneralizedFirstOrderAlgorithmCache{…}; recompute_jacobian::Nothing, kwargs::@Kwargs{})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generalized_first_order.jl:208
 [11] __step!
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generalized_first_order.jl:204 [inlined]
 [12] #step!#210
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:55 [inlined]
 [13] step!
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:50 [inlined]
 [14] solve!(cache::NonlinearSolve.GeneralizedFirstOrderAlgorithmCache{…})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:13
 [15] __solve(::NonlinearProblem{…}, ::GeneralizedFirstOrderAlgorithm{…}; kwargs::@Kwargs{})
    @ NonlinearSolve C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:4
 [16] __solve
    @ C:\Users\qlx\.julia\packages\NonlinearSolve\R8LAH\src\core\generic.jl:1 [inlined]
 [17] #solve_call#44
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:612 [inlined]
 [18] solve_call
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:569 [inlined]
 [19] #solve_up#53
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1072 [inlined]
 [20] solve_up
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1066 [inlined]
 [21] #solve#52
    @ C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1060 [inlined]
 [22] solve(prob::NonlinearProblem{…}, args::GeneralizedFirstOrderAlgorithm{…})
    @ DiffEqBase C:\Users\qlx\.julia\packages\DiffEqBase\O8cUq\src\solve.jl:1050
 [23] top-level scope
    @ c:\Users\qlx\Desktop\RB4_AP4_multi_stage_Julia_CoolProp\test2.jl:33
Some type information was truncated. Use `show(err)` to see complete types.

Environment (please complete the following information):

  [6e4b80f9] BenchmarkTools v1.5.0        
  [e084ae63] CoolProp v0.2.0
  [0c46a032] DifferentialEquations v7.13.0
  [6a86dc24] FiniteDiff v2.23.0
  [f6369f11] ForwardDiff v0.10.36
  [86223c79] Graphs v1.10.0
  [10e44e05] MATLAB v0.8.4
⌃ [961ee093] ModelingToolkit v9.9.0
  [8913a72c] NonlinearSolve v3.9.1
  [7f7a1694] Optimization v3.24.3
  [4e6fcdb7] OptimizationNLopt v0.2.0
⌃ [91a5bcdd] Plots v1.40.3
Info Packages marked with ⌃ have new versions available and may be upgradable.
  [47edcb42] ADTypes v0.2.7
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.36
  [79e6a3ab] Adapt v4.0.4
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.9.0
⌃ [4c555306] ArrayLayouts v1.9.1
  [aae01518] BandedMatrices v1.6.1
  [6e4b80f9] BenchmarkTools v1.5.0
  [e2ed5e7c] Bijections v0.1.6
  [d1d4a3ce] BitFlags v0.1.8
  [62783981] BitTwiddlingConvenienceFunctions v0.1.5
  [764a87c0] BoundaryValueDiffEq v5.7.1
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.4
  [00ebfdb7] CSTParser v3.4.2
  [49dc2e85] Calculus v0.5.1
  [d360d2e6] ChainRulesCore v1.23.0
  [fb6a15b2] CloseOpenIntervals v0.1.12
  [944b1d66] CodecZlib v0.7.4
  [35d6a980] ColorSchemes v3.24.0
⌃ [3da002f7] ColorTypes v0.11.4
  [c3611d14] ColorVectorSpace v0.10.0
  [5ae59095] Colors v0.12.10
  [861a8166] Combinatorics v1.0.2
  [a80b9123] CommonMark v0.8.12
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.0
  [34da2185] Compat v4.14.0
⌃ [b152e2b5] CompositeTypes v0.1.3
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [f0e56b4a] ConcurrentUtilities v2.4.1
  [88cd18e8] ConsoleProgressMonitor v0.1.2
  [187b0558] ConstructionBase v1.5.5
  [d38c429a] Contour v0.6.3
  [e084ae63] CoolProp v0.2.0
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
⌃ [864edb3b] DataStructures v0.18.18
  [e2d170a0] DataValueInterfaces v1.0.0
  [bcd4f6db] DelayDiffEq v5.47.1
  [8bb1440f] DelimitedFiles v1.9.1
  [2b5f629d] DiffEqBase v6.149.0
⌃ [459566f4] DiffEqCallbacks v3.5.0
  [77a26b50] DiffEqNoiseProcess v5.21.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [0c46a032] DifferentialEquations v7.13.0
  [b4f34e82] Distances v0.10.11
  [31c24e10] Distributions v0.25.107
  [ffbed154] DocStringExtensions v0.9.3
⌃ [5b8099bc] DomainSets v0.7.11
  [fa6b7ba4] DualNumbers v0.6.8
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⌃ [f151be2c] EnzymeCore v0.6.6
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⌃ [f2c3362d] RecursiveFactorization v0.2.21
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⌃ [0bca4576] SciMLBase v2.31.0
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⌅ [b22a6f82] FFMPEG_jll v4.4.4+1
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⌅ [e9f186c6] Libffi_jll v3.2.2+1
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⌅ [89763e89] Libtiff_jll v4.5.1+1
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Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`
Julia Version 1.10.2
Commit bd47eca2c8 (2024-03-01 10:14 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 12 × Intel(R) Core(TM) i5-10400F CPU @ 2.90GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, skylake)
Threads: 12 default, 0 interactive, 6 GC (on 12 virtual cores)
Environment:
  JULIA_EDITOR = code
avik-pal commented 2 months ago

Ah it's a scalar problem, that case was hard coded for dual numbers. let me fix it