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longemen3000

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longemen3000
·3 ay önce·discuss
Hello,

The textbook seems nice and clear. The only nitpick i have is that it should talk more about equations of state. I understand that it may not be the focus of the text, but mentioning the current state of equations of state (SAFTs, cubics, multiparameter) would help guide readers looking on how to generate their own steam tables for their fluid of interest, even if the advice is just "go use CoolProp"

On the other hand, i really like the ilustrations on turbomachinery, helps ground the theoretical content.
longemen3000
·6 ay önce·discuss
some constants that may or may not be transcendental: - Percolation Thresholds: https://en.wikipedia.org/wiki/Percolation_threshold - Critical scalings in 3d: https://en.wikipedia.org/wiki/Universality_class#Ising_model
longemen3000
·7 ay önce·discuss
That is one thing i like about the Julia package ecosystem. The general Registry (where package metadata is stored and where you go to register a new package), recommends using explicit names over short acronyms. For example, DifferentialEquations.jl is a package that does differential equations in julia (recognizable via the .jl suffix). What does Garlic.jl do? Exactly, garlic (the vegetable) modelling.
longemen3000
·4 yıl önce·discuss
The Julia equivalent does a good job explaining the 0.0 case: https://docs.julialang.org/en/v1/base/math/#Base.isapprox
longemen3000
·4 yıl önce·discuss
In Julia at least, there are packages that provide alternatives to Bigfloats:

Logarithmic numbers: more range, less precision https://github.com/cjdoris/LogarithmicNumbers.jl

Double arithmetic: stitch 2 floats together https://github.com/JuliaMath/DoubleFloats.jl

Of course, if you are calling BLAS/LAPACK, you are constrained to use floats, but the recommendation on DoubleFloats is clear: if you know you algorithms, use the increased precision only in the parts that matter