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Index

Cubic Models

All cubic models in Clapeyron.jl follow a common evaluation order:

function CubicModel(args...)
    # get params for database, initialize other models, etc.
    recombine!(model)  # we calculate the mixing rules, caches for the translation models if necessary, etc.
end

function cubic_ab(model::CubicModel,V,T,z=SA[1.0])
    invn2 = (one(n)/n)^2
    a = model.params.a.values
    b = model.params.b.values
    α = α_function(model,V,T,z,model.alpha)
    c = translation(model,V,T,z,model.translation)
    ā,b̄,c̄ = mixing_rule(model,V,T,z,model.mixing,α,a,b,c)
    return ā, b̄, c̄
end

function a_res(model::CubicModel,V,T,z,data = (sum(z),cubic_ab(model,V,T,z)))
    n, ā, b̄, c̄ = data
    # depends on the specific EoS
    return result
end
  • A Mixing Rule Model creates aᵢⱼ and bᵢⱼ from the critical temperature, critical pressure and a matrix of pair coefficients.
  • An Alpha Model creates a vector of αᵢ(T) values.
  • A Translation Model creates a vector of cᵢ values.
  • The same Mixing rule, given aᵢⱼ, bᵢⱼ, αᵢ(T) and cᵢ returns the the mixture values of ā, b̄ and c̄ that are then used by the corresponding cubic model. A Mixing Rule can contain activity models to participate in the mixing (for example, Huron–Vidal rules).

Common Definitions

Clapeyron.ab_premixing — Function
ab_premixing(model,mixing,kij = nothing,lij = nothing)

Given a model::CubicModel, that has a::PairParam, b::PairParam, a mixing::MixingRule and kij,lij matrices, ab_premixing will perform an implace calculation to obtain the values of a and b, containing values aᵢⱼ and bᵢⱼ. by default, it performs the Van der Waals One-Fluid mixing rule. that is:

aᵢⱼ = sqrt(aᵢ*aⱼ)*(1-kᵢⱼ)
bᵢⱼ = (bᵢ + bⱼ)/2
source
Clapeyron.mixing_rule — Function
mixing_rule(model::CubicModel,V,T,z,mixing_model::MixingRule,α,a,b,c)

Interface function used by cubic models. with matrices a and b, vectors α and c, a model::CubicModel and mixing_model::MixingRule, returns the scalars ā,b̄ and c̄, corresponding to the values mixed by the amount of components and the specifics of the mixing rule.

Example

function mixing_rule(model::CubicModel,V,T,z,mixing_model::vdW1fRule,α,a,b,c)
    ∑z = sum(z)
    ā = dot(z .* sqrt(α),a,z .* sqrt(α))/(∑z*∑z) #∑∑aᵢⱼxᵢxⱼ√(αᵢαⱼ)
    b̄ = dot(z,b,z)/(∑z*∑z)  #∑∑bᵢⱼxᵢxⱼ
    c̄ = dot(z,c)/∑z ∑cᵢxᵢ
    return ā,b̄,c̄
end
source

van der Walls Models

Clapeyron.vdW — Type
vdW(components;
idealmodel = BasicIdeal,
alpha = NoAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)

Input models

  • idealmodel: Ideal Model
  • alpha: Alpha model
  • mixing: Mixing model
  • activity: Activity Model, used in the creation of the mixing model.
  • translation: Translation Model

Description

Van der Waals Equation of state.

P = RT/(V-Nb) + a•α(T)/V²

Model Construction Examples

# Using the default database
model = vdW("water") #single input
model = vdW(["water","ethanol"]) #multiple components
model = vdW(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = vdW(["water","ethanol"],alpha = SoaveAlpha) #modifying alpha function
model = vdW(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = vdW(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = vdW(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = SoaveAlpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = vdW(["ethane","butane"],alpha = my_alpha)

# User-provided parameters, passing files or folders

model = vdW(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = vdW(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Van der Waals JD. Over de Continuiteit van den Gasen Vloeistoftoestand. PhD thesis, University of Leiden; 1873
source
Clapeyron.Clausius — Type
Clausius(components;
idealmodel = BasicIdeal,
alpha = NoAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = ClausiusTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Molar Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Molar Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)

Description

Clausius Equation of state.

P = RT/(v-b) + a•α(T)/((v - Δ₀b)^2)

aᵢᵢ =27/64 * (RTcᵢ)²/Pcᵢ
bᵢᵢ = Vcᵢ - 1/4 * RTcᵢ/Pcᵢ
cᵢ = 3/8 * RTcᵢ/Pcᵢ - Vcᵢ

Δ₀ = ∑cᵢxᵢ/∑bᵢxᵢ

References

  1. Clausius, R. (1880). Ueber das Verhalten der Kohlensäure in Bezug auf Druck, Volumen und Temperatur. Annalen der Physik, 245(3), 337–357. doi:10.1002/andp.18802450302
source
Clapeyron.Berthelot — Type
Berthelot(components;
idealmodel = BasicIdeal,
alpha = ClausiusAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • Vc: Single Parameter (Float64) - Molar Volume [m³·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)

Model Parameters

  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)
  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Molar Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]

Input models

  • idealmodel: Ideal Model
  • alpha: Alpha model
  • mixing: Mixing model
  • activity: Activity Model, used in the creation of the mixing model.
  • translation: Translation Model

Description

Berthelot Equation of state. It uses the Volume-Pressure Based mixing rules, that is:

a = 8*Pc*Vc^2
b = Vc/3
R = (8/3)*Pc*Vc/Tc
P = RT/(V-Nb) + a•α(T)/V²
α(T) = Tc/T

References

  1. Berthelot, D. (1899). Sur une méthode purement physique pour la détermination des poids moléculaires des gaz et des poids atomiques de leurs éléments. Journal de Physique Théorique et Appliquée, 8(1), 263–274. doi:10.1051/jphystap:018990080026300
source

Redlich-Kwong Models

Clapeyron.RK — Type
RK(components; 
idealmodel = BasicIdeal,
alpha = PRAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
verbose = false,
reference_state = nothing)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)

Input models

  • idealmodel: Ideal Model
  • alpha: Alpha model
  • mixing: Mixing model
  • activity: Activity Model, used in the creation of the mixing model.
  • translation: Translation Model

Description

Redlich-Kwong Equation of state.

P = RT/(V-Nb) + a•α(T)/(V(V+Nb))

Model Construction Examples

# Using the default database
model = RK("water") #single input
model = RK(["water","ethanol"]) #multiple components
model = RK(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = RK(["water","ethanol"],alpha = Soave2019) #modifying alpha function
model = RK(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = RK(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = RK(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = SoaveAlpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = RK(["ethane","butane"],alpha = my_alpha) #this is efectively now an SRK model

# User-provided parameters, passing files or folders

# Passing files or folders
model = RK(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = RK(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Redlich, O., & Kwong, J. N. S. (1949). On the thermodynamics of solutions; an equation of state; fugacities of gaseous solutions. Chemical Reviews, 44(1), 233–244. doi:10.1021/cr60137a013
source
Clapeyron.SRK — Function
SRK(components::Vector{String};
idealmodel = BasicIdeal,
alpha = SoaveAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[], 
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Description

Soave-Redlich-Kwong equation of state. it uses the following models:

Model Construction Examples

# Using the default database
model = SRK("water") #single input
model = SRK(["water","ethanol"]) #multiple components
model = SRK(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = SRK(["water","ethanol"],alpha = Soave2019) #modifying alpha function, using 2019 correlation
model = SRK(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = SRK(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = SRK(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = SoaveAlpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = SRK(["ethane","butane"],alpha = my_alpha)

# User-provided parameters, passing files or folders

model = SRK(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = SRK(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Soave, G. (1972). Equilibrium constants from a modified Redlich-Kwong equation of state. Chemical Engineering Science, 27(6), 1197–1203. doi:10.1016/0009-2509(72)80096-4
source
Clapeyron.PSRK — Function
function PSRK(components;
idealmodel = BasicIdeal,
alpha = SoaveAlpha,
mixing = PSRKRule,
activity = PSRKUNIFAC,
translation = PenelouxTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Description

Predictive Soave-Redlich-Kwong equation of state. it uses the following models:

References

  1. Horstmann, S., Jabłoniec, A., Krafczyk, J., Fischer, K., & Gmehling, J. (2005). PSRK group contribution equation of state: comprehensive revision and extension IV, including critical constants and α-function parameters for 1000 components. Fluid Phase Equilibria, 227(2), 157–164. doi:10.1016/j.fluid.2004.11.002
source
Clapeyron.tcRK — Function
tcRK(components::Vector{String};
idealmodel = BasicIdeal,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false,
estimate_alpha = true,
estimate_translation = true)

translated and consistent Redlich-Kwong equation of state. it uses the following models:

If Twu parameters are not provided, they can be estimated from the acentric factor (acentricfactor). If translation is not provided, it can be estimated, using Rackett compresibility Factor (ZRA) or the acentric factor (acentricfactor).

The use of estimates for the alpha function and volume translation can be turned off by passing estimate_alpha = false or estimate_translation = false.

References

  1. Le Guennec, Y., Privat, R., & Jaubert, J.-N. (2016). Development of the translated-consistent tc-PR and tc-RK cubic equations of state for a safe and accurate prediction of volumetric, energetic and saturation properties of pure compounds in the sub- and super-critical domains. Fluid Phase Equilibria, 429, 301–312. doi:10.1016/j.fluid.2016.09.003
  2. Pina-Martinez, A., Le Guennec, Y., Privat, R., Jaubert, J.-N., & Mathias, P. M. (2018). Analysis of the combinations of property data that are suitable for a safe estimation of consistent twu α-function parameters: Updated parameter values for the translated-consistent tc-PR and tc-RK cubic equations of state. Journal of Chemical and Engineering Data, 63(10), 3980–3988. doi:10.1021/acs.jced.8b00640
  3. Piña-Martinez, A., Privat, R., & Jaubert, J.-N. (2022). Use of 300,000 pseudo‐experimental data over 1800 pure fluids to assess the performance of four cubic equations of state: SRK , PR , tc ‐RK , and tc ‐PR. AIChE Journal. American Institute of Chemical Engineers, 68(2). doi:10.1002/aic.17518
source

Peng-Robinson Models

Clapeyron.PR — Type
PR(components;
idealmodel = BasicIdeal,
alpha = PRAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
verbose = false,
reference_state = nothing)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)

Input models

  • idealmodel: Ideal Model
  • alpha: Alpha model
  • mixing: Mixing model
  • activity: Activity Model, used in the creation of the mixing model.
  • translation: Translation Model

Description

Peng-Robinson Equation of state.

P = RT/(V-Nb) + a•α(T)/(V-Nb₁)(V-Nb₂)
b₁ = (1 + √2)b
b₂ = (1 - √2)b

Model Construction Examples

# Using the default database
model = PR("water") #single input
model = PR(["water","ethanol"]) #multiple components
model = PR(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = PR(["water","ethanol"],alpha = Soave2019) #modifying alpha function
model = PR(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = PR(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = PR(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = PR78Alpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = PR(["ethane","butane"],alpha = my_alpha)

# User-provided parameters, passing files or folders
model = PR(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = PR(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Peng, D.Y., & Robinson, D.B. (1976). A New Two-Constant Equation of State. Industrial & Engineering Chemistry Fundamentals, 15, 59-64. doi:10.1021/I160057A011
source
Clapeyron.PR78 — Function
PR78(components::Vector{String};
idealmodel = BasicIdeal,
alpha = PR78Alpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[], 
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Peng Robinson (1978) equation of state. It uses the following models:

Model Construction Examples

# Using the default database
model = PR78("water") #single input
model = PR78(["water","ethanol"]) #multiple components
model = PR78(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = PR78(["water","ethanol"],alpha = Soave2019) #modifying alpha function
model = PR78(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = PR78(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = PR78(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = PRAlpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = PR78(["ethane","butane"],alpha = my_alpha) #this model becomes a normal PR EoS

# User-provided parameters, passing files or folders
model = PR78(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = PR78(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Robinson DB, Peng DY. The characterization of the heptanes and heavier fractions for the GPA Peng-Robinson programs. Tulsa: Gas Processors Association; 1978
source
Clapeyron.cPR — Function
cPR(components::Vector{String};
idealmodel = BasicIdeal,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Consistent Peng Robinson equation of state. It uses the following models:

References

  1. Bell, I. H., Satyro, M., & Lemmon, E. W. (2018). Consistent twu parameters for more than 2500 pure fluids from critically evaluated experimental data. Journal of Chemical and Engineering Data, 63(7), 2402–2409. doi:10.1021/acs.jced.7b00967
source
Clapeyron.VTPR — Function
VTPR(components;
idealmodel = BasicIdeal,
userlocations = String[],
group_userlocations = String[]
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Volume-translated Peng Robinson equation of state. It uses the following models:

References

  1. Ahlers, J., & Gmehling, J. (2001). Development of an universal group contribution equation of state. Fluid Phase Equilibria, 191(1–2), 177–188. doi:10.1016/s0378-3812(01)00626-4
source
Clapeyron.UMRPR — Function
UMRPR(components;
idealmodel = BasicIdeal,
userlocations = String[],
group_userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Universal Mixing Rule Peng Robinson equation of state. It uses the following models:

References

  1. Voutsas, E., Magoulas, K., & Tassios, D. (2004). Universal mixing rule for cubic equations of state applicable to symmetric and asymmetric systems: Results with the Peng−Robinson equation of state. Industrial & Engineering Chemistry Research, 43(19), 6238–6246. doi:10.1021/ie049580p
source
Clapeyron.tcPR — Function
tcPR(components;
idealmodel = BasicIdeal,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false,
estimate_alpha = true,
estimate_translation = true)

Translated and consistent Peng Robinson equation of state. It uses the following models:

If Twu parameters are not provided, they can be estimated from the acentric factor (acentricfactor). If translation is not provided, it can be estimated, using Rackett compresibility Factor (ZRA) or the acentric factor (acentricfactor).

References

  1. Le Guennec, Y., Privat, R., & Jaubert, J.-N. (2016). Development of the translated-consistent tc-PR and tc-RK cubic equations of state for a safe and accurate prediction of volumetric, energetic and saturation properties of pure compounds in the sub- and super-critical domains. Fluid Phase Equilibria, 429, 301–312. doi:10.1016/j.fluid.2016.09.003
  2. Pina-Martinez, A., Le Guennec, Y., Privat, R., Jaubert, J.-N., & Mathias, P. M. (2018). Analysis of the combinations of property data that are suitable for a safe estimation of consistent twu α-function parameters: Updated parameter values for the translated-consistent tc-PR and tc-RK cubic equations of state. Journal of Chemical and Engineering Data, 63(10), 3980–3988. doi:10.1021/acs.jced.8b00640
  3. Piña-Martinez, A., Privat, R., & Jaubert, J.-N. (2022). Use of 300,000 pseudo‐experimental data over 1800 pure fluids to assess the performance of four cubic equations of state: SRK , PR , tc ‐RK , and tc ‐PR. AIChE Journal. American Institute of Chemical Engineers, 68(2). doi:10.1002/aic.17518
source
Clapeyron.tcPRW — Function
tcPR(components;
idealmodel = BasicIdeal,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Translated and consistent Peng Robinson equation of state, with an gE mixing rule. It uses the following models:

If Twu parameters are not provided, they can be estimated from the acentric factor (acentricfactor). If translation is not provided, it can be estimated, using Rackett compresibility Factor (ZRA) or the acentric factor (acentricfactor).

References

  1. Le Guennec, Y., Privat, R., & Jaubert, J.-N. (2016). Development of the translated-consistent tc-PR and tc-RK cubic equations of state for a safe and accurate prediction of volumetric, energetic and saturation properties of pure compounds in the sub- and super-critical domains. Fluid Phase Equilibria, 429, 301–312. doi:10.1016/j.fluid.2016.09.003
  2. Pina-Martinez, A., Le Guennec, Y., Privat, R., Jaubert, J.-N., & Mathias, P. M. (2018). Analysis of the combinations of property data that are suitable for a safe estimation of consistent twu α-function parameters: Updated parameter values for the translated-consistent tc-PR and tc-RK cubic equations of state. Journal of Chemical and Engineering Data, 63(10), 3980–3988. doi:10.1021/acs.jced.8b00640
  3. Piña-Martinez, A., Privat, R., & Jaubert, J.-N. (2022). Use of 300,000 pseudo‐experimental data over 1800 pure fluids to assess the performance of four cubic equations of state: SRK , PR , tc ‐RK , and tc ‐PR. AIChE Journal. American Institute of Chemical Engineers, 68(2). doi:10.1002/aic.17518
  4. Piña-Martinez, A., Privat, R., Nikolaidis, I. K., Economou, I. G., & Jaubert, J.-N. (2021). What is the optimal activity coefficient model to be combined with the translated–consistent Peng–Robinson equation of state through advanced mixing rules? Cross-comparison and grading of the Wilson, UNIQUAC, and NRTL aE models against a benchmark database involving 200 binary systems. Industrial & Engineering Chemistry Research, 60(47), 17228–17247. doi:10.1021/acs.iecr.1c03003
source
Clapeyron.EPPR78 — Function
EPPR78(components_or_groups;
idealmodel = BasicIdeal,
alpha = PR78Alpha,
mixing = PPR78Rule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Enhanced Predictive Peng Robinson equation of state. It uses the following models:

References

  1. Jaubert, J.-N., Privat, R., & Mutelet, F. (2010). Predicting the phase equilibria of synthetic petroleum fluids with the PPR78 approach. AIChE Journal. American Institute of Chemical Engineers, 56(12), 3225–3235. doi:10.1002/aic.12232
  2. Jaubert, J.-N., Qian, J.-W., Lasala, S., & Privat, R. (2022). The impressive impact of including enthalpy and heat capacity of mixing data when parameterising equations of state. Application to the development of the E-PPR78 (Enhanced-Predictive-Peng-Robinson-78) model. Fluid Phase Equilibria, (113456), 113456. doi:10.1016/j.fluid.2022.113456
source
Clapeyron.QCPR — Function
QCPR(components;
    idealmodel = BasicIdeal,
    userlocations = String[], 
    ideal_userlocations = String[],
    alpha_userlocations = String[],
    mixing_userlocations = String[],
    activity_userlocations = String[],
    translation_userlocations = String[],
    reference_state = nothing,
    verbose = false)

Quantum-corrected Peng Robinson equation of state. It uses the following models:

References

  1. Aasen, A., Hammer, M., Lasala, S., Jaubert, J.-N., & Wilhelmsen, Ø. (2020). Accurate quantum-corrected cubic equations of state for helium, neon, hydrogen, deuterium and their mixtures. Fluid Phase Equilibria, 524(112790), 112790. doi:10.1016/j.fluid.2020.112790
source

Patel-Teja Models

Clapeyron.PatelTeja — Type
PatelTeja(components;
idealmodel = BasicIdeal,
alpha = PatelTejaAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)
  • c: Pair Parameter (Float64)

Description

Patel-Teja Equation of state.

P = RT/(v-b) + a•α(T)/((v - Δ₁b)*(v - Δ₂b))
aᵢᵢ = Ωaᵢ(R²Tcᵢ²/Pcᵢ)
bᵢᵢ = Ωbᵢ(R²Tcᵢ/Pcᵢ)
cᵢ = Ωcᵢ(R²Tcᵢ/Pcᵢ)
Zcᵢ = Pcᵢ*Vcᵢ/(R*Tcᵢ)
Ωaᵢ = 3Zcᵢ² + 3(1 - 2Zcᵢ)Ωbᵢ + Ωbᵢ² + 1 - 3Zcᵢ
Ωbᵢ: maximum real solution of 0 = -Zcᵢ³ + (3Zcᵢ²)*Ωbᵢ + (2 - 3Zcᵢ)*Ωbᵢ² + Ωbᵢ³
Ωcᵢ = 1 - 3Zcᵢ

γ = ∑cᵢxᵢ/∑bᵢxᵢ
δ = 1 + 6γ + γ²
ϵ = 1 + γ

Δ₁ = -(ϵ + √δ)/2
Δ₂ = -(ϵ - √δ)/2

if Vc is not known, Zc can be estimated, using the acentric factor:

Zc = 0.329032 - 0.076799ω + 0.0211947ω²

Model Construction Examples

# Using the default database
model = PatelTeja("water") #single input
model = PatelTeja(["water","ethanol"]) #multiple components
model = PatelTeja(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = PatelTeja(["water","ethanol"],alpha = TwuAlpha) #modifying alpha function
model = PatelTeja(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = PatelTeja(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = PatelTeja(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = PR78Alpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = PatelTeja(["ethane","butane"],alpha = my_alpha)

# User-provided parameters, passing files or folders
model = PatelTeja(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = PatelTeja(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Vc = [4.25e-5, 6.43e-5],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Patel, N. C., & Teja, A. S. (1982). A new cubic equation of state for fluids and fluid mixtures. Chemical Engineering Science, 37(3), 463–473. doi:10.1016/0009-2509(82)80099-7
source
Clapeyron.PTV — Type
PTV(components;
idealmodel = BasicIdeal,
alpha = NoAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = PTVTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
verbose = false,
reference_state = nothing)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)
  • c: Pair Parameter (Float64)

Description

Patel-Teja-Valderrama Equation of state.

P = RT/(v-b) + a•α(T)/((v - Δ₁b)*(v - Δ₂b))
aᵢᵢ = Ωaᵢ(R²Tcᵢ²/Pcᵢ)
bᵢᵢ = Ωbᵢ(R²Tcᵢ/Pcᵢ)
cᵢ = Ωcᵢ(R²Tcᵢ/Pcᵢ)
Zcᵢ = Pcᵢ*Vcᵢ/(R*Tcᵢ)
Ωaᵢ = 0.66121 - 0.76105Zcᵢ
Ωbᵢ = 0.02207 + 0.20868Zcᵢ
Ωcᵢ = 0.57765 - 1.87080Zcᵢ

γ = ∑cᵢxᵢ/∑bᵢxᵢ
δ = 1 + 6γ + γ²
ϵ = 1 + γ

Δ₁ = -(ϵ + √δ)/2
Δ₂ = -(ϵ - √δ)/2

Model Construction Examples

# Using the default database
model = PTV("water") #single input
model = PTV(["water","ethanol"]) #multiple components
model = PTV(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = PTV(["water","ethanol"],alpha = TwuAlpha) #modifying alpha function
model = PTV(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = PTV(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = PTV(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = PR78Alpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = PTV(["ethane","butane"],alpha = my_alpha)

# User-provided parameters, passing files or folders
model = PTV(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = PTV(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Vc = [4.25e-5, 6.43e-5],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Valderrama, J. O. (1990). A generalized Patel-Teja equation of state for polar and nonpolar fluids and their mixtures. Journal of Chemical Engineering of Japan, 23(1), 87–91. doi:10.1252/jcej.23.87
source
Clapeyron.YFR — Type
YFR(components;
idealmodel = BasicIdeal,
alpha = YFRAlpha,
mixing = YFRfRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)
  • c: Pair Parameter (Float64)

Input models

  • idealmodel: Ideal Model
  • alpha: Alpha model
  • mixing: Mixing model
  • activity: Activity Model, used in the creation of the mixing model.
  • translation: Translation Model

Description

Yang-Frotscher-Richter Equation of state.

P = RT/(v-b) + a•α(T)/((v - Δ₁b)*(v - Δ₂b))
aᵢᵢ = Ωaᵢ(R²Tcᵢ²/Pcᵢ)
bᵢᵢ = Ωbᵢ(R²Tcᵢ/Pcᵢ)
cᵢ = Ωcᵢ(R²Tcᵢ/Pcᵢ)
Zcᵢ = Pcᵢ*Vcᵢ/(R*Tcᵢ)
Trᵢ = T/Tcᵢ
ξcᵢ = 0.144894*exp(-Trᵢ^4) − 0.129835*exp(-Trᵢ^3) + 0.957454*Zcᵢ + 0.036884
Ωaᵢ = 3ξcᵢ² + 3(1 - 2ξcᵢ)Ωbᵢ + Ωbᵢ² + 1 - 3ξcᵢ
Ωbᵢ: maximum real solution of 0 = -ξcᵢᵢ³ + (3ξcᵢ²)*Ωbᵢ + (2 - 3ξcᵢ)*Ωbᵢ² + Ωbᵢ³
Ωcᵢ = 1 - 3ξcᵢ

γ = ∑cᵢxᵢ/∑bᵢxᵢ
δ = 1 + 6γ + γ²
ϵ = 1 + γ

Δ₁ = -(ϵ + √δ)/2
Δ₂ = -(ϵ - √δ)/2

Model Construction Examples

# Using the default database
model = YFR("water") #single input
model = YFR(["water","ethanol"]) #multiple components
model = YFR(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = YFR(["water","ethanol"],alpha = SoaveAlpha) #modifying alpha function
model = YFR(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = YFR(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = YFR(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = SoaveAlpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = YFR(["ethane","butane"],alpha = my_alpha)

# User-provided parameters, passing files or folders

model = YFR(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = YFR(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

Notes

The original paper also uses correlations for Ωaᵢ and Ωbᵢ. We opt to use the full solution instead to make the EoS consistent at the critical point.

References

  1. Yang, X., Frotscher, O., & Richter, M. (2025). Symbolic-regression aided development of a new cubic equation of state for improved liquid phase density calculation at pressures up to 100 MPa. International Journal of Thermophysics, 46(2). doi:10.1007/s10765-024-03490-5
source

Other cubic Models

Clapeyron.RKPR — Type
RKPR(components;
idealmodel = BasicIdeal,
alpha = RKPRAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) (optional) - Critical Volume [m³·mol⁻¹]
  • delta: Single Parameter (Float64) (optional) - constant parameter (no units)
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)
  • delta: Single Parameter (Float64) - constant parameter (no units)

Input models

  • idealmodel: Ideal Model
  • alpha: Alpha model
  • mixing: Mixing model
  • activity: Activity Model, used in the creation of the mixing model.
  • translation: Translation Model

Description

Redlich-Kwong-Peng-Robinson Equation of state.

P = RT/(v-b) + a•α(T)/((v + Δ₁b)*(v + Δ₂b))
Δ₁ = δ
Δ₂ = (1 - δ)/(1 + δ)
δ = ∑cᵢxᵢ

aᵢᵢ = Ωaᵢ(R²Tcᵢ²/Pcᵢ)
bᵢᵢ = Ωbᵢ(R²Tcᵢ/Pcᵢ)
Ωaᵢ = (3*yᵢ^2 + 3yᵢdᵢ + dᵢ^2 + dᵢ - 1)/(3yᵢ + dᵢ - 1)^2
Ωbᵢ = 1/(3yᵢ + dᵢ - 1)
dᵢ = (1 + cᵢ^2)/(1 + cᵢ)
yᵢ = 1 + (2(1 + cᵢ))^(1/3) + (4/(1 + cᵢ))^(1/3)

If c is not provided, cᵢ is fitted to match:

if Zcᵢ[exp] > 0.29
    cᵢ = √2 - 1
else
    Zcᵢ = 1.168Zcᵢ[exp]
    f(cᵢ) == 0
    f(cᵢ) = Zcᵢ - yᵢ/(3yᵢ + dᵢ - 1)

Model Construction Examples

# Using the default database
model = RKPR("water") #single input
model = RKPR(["water","ethanol"]) #multiple components
model = RKPR(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = RKPR(["water","ethanol"],alpha = TwuAlpha) #modifying alpha function
model = RKPR(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = RKPR(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = RKPR(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = PR78Alpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = RKPR(["ethane","butane"],alpha = my_alpha)

# User-provided parameters, passing files or folders
model = RKPR(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = RKPR(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Vc = [4.25e-5, 6.43e-5],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Cismondi, M., & Mollerup, J. (2005). Development and application of a three-parameter RK–PR equation of state. Fluid Phase Equilibria, 232(1–2), 74–89. doi:10.1016/j.fluid.2005.03.020
  2. Tassin, N. G., Mascietti, V. A., & Cismondi, M. (2019). Phase behavior of multicomponent alkane mixtures and evaluation of predictive capacity for the PR and RKPR EoS’s. Fluid Phase Equilibria, 480, 53–65. doi:10.1016/j.fluid.2018.10.005
source
Clapeyron.KU — Type
KU(components;
idealmodel = BasicIdeal,
alpha = KUAlpha,
mixing = vdW1fRule,
activity = nothing,
translation = NoTranslation,
userlocations = String[],
ideal_userlocations = String[],
alpha_userlocations = String[],
mixing_userlocations = String[],
activity_userlocations = String[],
translation_userlocations = String[],
reference_state = nothing,
verbose = false)

Input parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³]
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • k: Pair Parameter (Float64) (optional)
  • l: Pair Parameter (Float64) (optional)

Model Parameters

  • Tc: Single Parameter (Float64) - Critical Temperature [K]
  • Pc: Single Parameter (Float64) - Critical Pressure [Pa]
  • Vc: Single Parameter (Float64) - Critical Volume [m³]
  • omega_a: Single Parameter (Float64) - Critical Constant for a - No units
  • omega_b: Single Parameter (Float64) - Critical Constant for b - No units
  • Mw: Single Parameter (Float64) - Molecular Weight [g·mol⁻¹]
  • a: Pair Parameter (Float64)
  • b: Pair Parameter (Float64)

Input models

  • idealmodel: Ideal Model
  • alpha: Alpha model
  • mixing: Mixing model
  • activity: Activity Model, used in the creation of the mixing model.
  • translation: Translation Model

Description

Kumar-Upadhyay Cubic Equation of state. Ωa and Ωb are component-dependent

P = RT/(v-b) + a•κ(T)/((v²-1.6bv - 0.8b²)
a = Ωa(R²Tcᵢ²/Pcᵢ)
b = Ωb(R²Tcᵢ²/Pcᵢ)
Ωa = Zc[(1 + 1.6α - 0.8α²)²/((1 - α²)(2 + 1.6α))]
χ = ∛[√(1458Zc³ - 1701Zc² + 540Zc -20)/32√3Zc² - (729Zc³ - 216Zc + 8)/1728Zc³]
α = [χ + (81Zc² - 72Zc + 4)/144Zc²χ + (3Zc - 2)/12Zc]
Ωa = Zc[(1 + 1.6α - 0.8α²)²/((1 - α²)(2 + 1.6α))]
Ωb = αZc

Model Construction Examples

# Using the default database
model = KU("water") #single input
model = KU(["water","ethanol"]) #multiple components
model = KU(["water","ethanol"], idealmodel = ReidIdeal) #modifying ideal model
model = KU(["water","ethanol"],alpha = TwuAlpha) #modifying alpha function
model = KU(["water","ethanol"],translation = RackettTranslation) #modifying translation
model = KU(["water","ethanol"],mixing = KayRule) #using another mixing rule
model = KU(["water","ethanol"],mixing = WSRule, activity = NRTL) #using advanced EoS+gᴱ mixing rule

# Passing a prebuilt model

my_alpha = PR78Alpha(["ethane","butane"],userlocations = Dict(:acentricfactor => [0.1,0.2]))
model = KU(["ethane","butane"],alpha = my_alpha)

# User-provided parameters, passing files or folders
model = KU(["neon","hydrogen"]; userlocations = ["path/to/my/db","cubic/my_k_values.csv"])

# User-provided parameters, passing parameters directly

model = KU(["neon","hydrogen"];
        userlocations = (;Tc = [44.492,33.19],
                        Pc = [2679000, 1296400],
                        Vc = [4.25e-5, 6.43e-5],
                        Mw = [20.17, 2.],
                        acentricfactor = [-0.03,-0.21]
                        k = [0. 0.18; 0.18 0.], #k,l can be ommited in single-component models.
                        l = [0. 0.01; 0.01 0.])
                    )

References

  1. Kumar, A., & Upadhyay, R. (2021). A new two-parameters cubic equation of state with benefits of three-parameters. Chemical Engineering Science, 229(116045), 116045. doi:10.1016/j.ces.2020.116045
source

Alpha (α(T)) Models

Clapeyron.α_function — Function
α_function(model::CubicModel,V,T,z,αmodel::AlphaModel)

Interface function used in cubic models. It should return a vector of αᵢ(T).

Example:

function α_function(model::CubicModel,V,T,z,alpha_model::RKAlphaModel)
    return 1 ./ sqrt.(T ./ Tc)
end
source
Clapeyron.NoAlpha — Type
NoAlpha(args...) <: NoAlphaModel

Input Parameters

None

Description

Cubic alpha (α(T)) model. Default for vdW EoS

αᵢ = 1 ∀ i

Model Construction Examples

# Because this model does not have parameters, all those constructors are equivalent:
alpha = NoAlpha()
alpha = NoAlpha("water")
alpha = NoAlpha(["water","carbon dioxide"])
source
Clapeyron.ClausiusAlpha — Type
ClausiusAlpha <: ClausiusAlphaModel

ClausiusAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • none

Description

Cubic alpha (α(T)) model. Default for Clausius and [Berthelot]

αᵢ = 1/Trᵢ
Trᵢ = T/Tcᵢ

Model Construction Examples

# Because this model does not have parameters, all those constructors are equivalent:
alpha = ClausiusAlpha()
alpha = ClausiusAlpha("water")
alpha = ClausiusAlpha(["water","carbon dioxide"])
source
Clapeyron.RKAlpha — Type
RKAlpha <: RKAlphaModel

RKAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • none

Description

Cubic alpha (α(T)) model. Default for RK EoS.

αᵢ = 1/√(Trᵢ)
Trᵢ = T/Tcᵢ

Model Construction Examples

# Because this model does not have parameters, all those constructors are equivalent:
alpha = RKAlpha()
alpha = RKAlpha("water")
alpha = RKAlpha(["water","carbon dioxide"])
source
Clapeyron.SoaveAlpha — Type
SoaveAlpha <: SoaveAlphaModel

SoaveAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Cubic alpha (α(T)) model. Default for SRK EoS.

αᵢ = (1+mᵢ(1-√(Trᵢ)))^2
Trᵢ = T/Tcᵢ
mᵢ = 0.480 + 1.547ωᵢ - 0.176ωᵢ^2

To use different polynomial coefficients for mᵢ, overload Clapeyron.α_m(::CubicModel,::SoaveAlphaModel) = (c₁,c₂,...cₙ)

Model Construction Examples

# Using the default database
alpha = SoaveAlpha("water") #single input
alpha = SoaveAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = SoaveAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = SoaveAlpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))
source
Clapeyron.Soave2019Alpha — Type
Soave2019Alpha <: SoaveAlphaModel

Soave2019Alpha(components::Vector{String};
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Cubic alpha (α(T)) model. Updated m(ω) correlations for PR and SRK with better results for heavy molecules.

αᵢ = (1+mᵢ(1-√(Trᵢ)))^2
Trᵢ = T/Tcᵢ
mᵢ = 0.37464 + 1.54226ωᵢ - 0.26992ωᵢ^2

where, for Peng-robinson:

mᵢ = 0.3919 + 1.4996ωᵢ - 0.2721ωᵢ^2 + 0.1063ωᵢ^3

and, for Redlich-Kwong:

mᵢ = 0.4810 + 1.5963ωᵢ - 0.2963ωᵢ^2 + 0.1223ωᵢ^3

Model Construction Examples

# Using the default database
alpha = Soave2019Alpha("water") #single input
alpha = Soave2019Alpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = Soave2019Alpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = Soave2019Alpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))

References

  1. Pina-Martinez, A., Privat, R., Jaubert, J.-N., & Peng, D.-Y. (2019). Updated versions of the generalized Soave α-function suitable for the Redlich-Kwong and Peng-Robinson equations of state. Fluid Phase Equilibria, 485, 264–269. doi:10.1016/j.fluid.2018.12.007
source
Clapeyron.PRAlpha — Type
PRAlpha <: SoaveAlphaModel

PRAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Cubic alpha (α(T)) model. Default for PR EoS.

αᵢ = (1+mᵢ(1-√(Trᵢ)))^2
Trᵢ = T/Tcᵢ
mᵢ = 0.37464 + 1.54226ωᵢ - 0.26992ωᵢ^2

It is equivalent to SoaveAlpha.

Model Construction Examples

# Using the default database
alpha = PRAlpha("water") #single input
alpha = PRAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = PRAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = PRAlpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))
source
Clapeyron.PR78Alpha — Type
PR78Alpha <: PR78AlphaModel

PR78Alpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Cubic alpha (α(T)) model. Default for PR78 and EPPR78 EoS.

αᵢ = (1+mᵢ(1-√(Trᵢ)))^2
Trᵢ = T/Tcᵢ
if ωᵢ ≤ 0.491
    mᵢ = 0.37464 + 1.54226ωᵢ - 0.26992ωᵢ^2
else
    mᵢ = 0.379642 + 1.487503ωᵢ - 0.164423ωᵢ^2 - 0.016666ωᵢ^3

Model Construction Examples

# Using the default database
alpha = PR78Alpha("water") #single input
alpha = PR78Alpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = PR78Alpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = PR78Alpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))
source
Clapeyron.CPAAlpha — Type
CPAAlpha <: CPAAlphaModel

CPAAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • c1: Single Parameter (Float64)

Description

Cubic alpha (α(T)) model. Default for CPA EoS.

αᵢ = (1+c¹ᵢ(1-√(Trᵢ)))^2

Model Construction Examples

# Using the default database
alpha = CPAAlpha("water") #single input
alpha = CPAAlpha(["water","carbon dioxide"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = CPAAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","cpa/alpha.csv"])

# Passing parameters directly
alpha = CPAAlpha(["water","carbon dioxide"];userlocations = (;c1 = [0.67,0.76]))
source
Clapeyron.sCPAAlpha — Type
sCPAAlpha <: sCPAAlphaModel

sCPAAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • c1: Single Parameter

Description

Cubic alpha (α(T)) model. Default for sCPA EoS.

αᵢ = (1+c¹ᵢ(1-√(Trᵢ)))^2

Model Construction Examples

# Using the default database
alpha = sCPAAlpha("water") #single input
alpha = sCPAAlpha(["water","carbon dioxide"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = sCPAAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","scpa/alpha.csv"])

# Passing parameters directly
alpha = sCPAAlpha(["water","carbon dioxide"];userlocations = (;c1 = [0.67,0.76]))
source
Clapeyron.MTAlpha — Type
MTAlpha <: MTAlphaModel

MTAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Magoulas & Tassios Cubic alpha (α(T)) model. Default for UMRPR EoS. Also defined for vdW models.

αᵢ = (1+mᵢ(1-√(Trᵢ)))^2
Trᵢ = T/Tcᵢ
mᵢ = 0.384401 + 1.52276ωᵢ - 0.213808ωᵢ^2 + 0.034616ωᵢ^3 - 0.001976ωᵢ^4 (PR)
mᵢ = 0.483798 + 1.643232ωᵢ - 0.288718ωᵢ^2 + 0.066013ωᵢ^3 (vdW)

Model Construction Examples

# Using the default database
alpha = MTAlpha("water") #single input
alpha = MTAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = MTAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = MTAlpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))

References

  1. Magoulas, K., & Tassios, D. (1990). Thermophysical properties of n-Alkanes from C1 to C20 and their prediction for higher ones. Fluid Phase Equilibria, 56, 119–140. doi:10.1016/0378-3812(90)85098-u
source
Clapeyron.BMAlpha — Type
BMAlpha <: BMAlphaModel

BMAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Boston Mathias Cubic alpha (α(T)) model. Identical to a Soave model when Tr <= 1, while having the correct behaviour at supercritical temperatures (via extrapolation at the critical point).

if Trᵢ > 1
    αᵢ = (exp((1-2/(2+mᵢ))*(1-Trᵢ^(1+mᵢ/2))))^2
else
    αᵢ = (1+mᵢ*(1-√(Trᵢ)))^2

Trᵢ = T/Tcᵢ

for PR models, RK, vdW models:
    mᵢ = m(Soave)
other cubic models:
    mᵢ = m(Leivobici)

Model Construction Examples

# Using the default database
alpha = BMAlpha("water") #single input
alpha = BMAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = BMAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = BMAlpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))

References

  1. .M. Boston, P.M. Mathias, Proceedings of the 2nd International Conference on Phase Equilibria and Fluid Properties in the Chemical Process Industries, West Berlin, March, 1980, pp. 823–849
source
Clapeyron.TwuAlpha — Type
TwuAlpha <: TwuAlphaModel
Twu91Alpha = TwuAlpha
TwuAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • M: Single Parameter
  • N: Single Parameter
  • L: Single Parameter

Description

Cubic alpha (α(T)) model. Default for VTPR EoS. Also known as Twu-91 alpha

αᵢ = Trᵢ^(N*(M-1))*exp(L*(1-Trᵢ^(N*M))
Trᵢ = T/Tcᵢ

Model Construction Examples

# Using the default database
alpha = TwuAlpha("water") #single input
alpha = Twu91Alpha("water") #same function
alpha = TwuAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = TwuAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","twu.csv"])

# Passing parameters directly
alpha = TwuAlpha(["neon","hydrogen"];
    userlocations = (;L = [0.40453, 156.21],
                    M = [0.95861, -0.0062072],
                    N = [0.8396, 5.047])
                )

References

  1. Twu, C. H., Lee, L. L., & Starling, K. E. (1980). Improved analytical representation of argon thermodynamic behavior. Fluid Phase Equilibria, 4(1–2), 35–44. doi:10.1016/0378-3812(80)80003-3
source
Clapeyron.Twu88Alpha — Function
Twu88Alpha::TwuAlpha

Twu88Alpha(components::Vector{String};
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • M: Single Parameter
  • N: Single Parameter (optional)
  • L: Single Parameter

Model Parameters

  • M: Single Parameter
  • N: Single Parameter
  • L: Single Parameter

Description

Cubic alpha (α(T)) model. Also known as Twu-88 alpha.

αᵢ = Trᵢ^(N*(M-1))*exp(L*(1-Trᵢ^(N*M))
N = 2
Trᵢ = T/Tcᵢ

if N is specified, it will be used instead of the default value of 2.

Model Construction Examples

# Using the default database
alpha = Twu88Alpha("water") #single input
alpha = Twu88Alpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = Twu88Alpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","twu88.csv"])

# Passing parameters directly
alpha = Twu88Alpha(["neon","hydrogen"];
    userlocations = (;L = [0.40453, 156.21],
                    M = [0.95861, -0.0062072],
                    N = [0.8396, 5.047]) #if we don't pass N, then is assumed N = 2
                )

References

  1. Twu, C. H., Lee, L. L., & Starling, K. E. (1980). Improved analytical representation of argon thermodynamic behavior. Fluid Phase Equilibria, 4(1–2), 35–44. doi:10.1016/0378-3812(80)80003-3
source
Clapeyron.PatelTejaAlpha — Type
PatelTejaAlpha <: SoaveAlphaModel

PatelTejaAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Cubic alpha (α(T)) model. Default for PatelTeja EoS.

αᵢ = (1+mᵢ(1-√(Trᵢ)))^2
Trᵢ = T/Tcᵢ
mᵢ = 0.452413 + 1.30982ωᵢ - 0.295937ωᵢ^2

Model Construction Examples

# Using the default database
alpha = PatelTejaAlpha("water") #single input
alpha = PatelTejaAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = PatelTejaAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = PatelTejaAlpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))
source
Clapeyron.KUAlpha — Type
KUAlpha <: AlphaModel

KUAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Cubic alpha (α(T)) model. Default for KU EoS.

For Tr < 1

αᵢ = (1+mᵢ(1-√(Trᵢ))^nᵢ)^2
Trᵢ = T/Tcᵢ
mᵢ = 0.37790 + 1.51959ωᵢ - 0.46904ωᵢ^2 + 0.015679ωᵢ^3
nᵢ = 0.97016 + 0.05495ωᵢ - 0.1293ωᵢ^2 + 0.0172028ωᵢ^3

For Tr > 1 is a 6th order taylor expansion around T = Tc.

Model Construction Examples

# Using the default database
alpha = KUAlpha("water") #single input
alpha = KUAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = KUAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = KUAlpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))

References

  1. Kumar, A., & Upadhyay, R. (2021). A new two-parameters cubic equation of state with benefits of three-parameters. Chemical Engineering Science, 229(116045), 116045. doi:10.1016/j.ces.2020.116045
source
Clapeyron.RKPRAlpha — Type
RKPRAlpha <: RKPRAlphaModel

RKPRAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • k1: Single Parameter (Float64)
  • k1: Single Parameter (Float64)
  • acentricfactor: Single Parameter (Float64) (optional), acentric factor. used to estimate the value of k1 and k2 when not provided.

Description

Cubic alpha (α(T)) model. Default for RKPR EoS.

αᵢ = ((k₂ᵢ + 1)/(k₂ᵢ + Trᵢ))^k₁ᵢ

in the case of RKPR EoS. if no values of k1 and k2 are provided, the following correlation is used:

k₁ = (12.504Zc -2.7238) + (7.4513*Zc + 1.9681)ωᵢ + (-2.4407*Zc + 0.0017)ωᵢ^2
Trᵢ = T/Tcᵢ
k₂ = 2

for Other cubic EoS, the k is calculated via the Leivobici alpha:

k₂ = 2
k₁ = log(αᵢ(leivovici,Tr = 0.7))/log(3/2.7)

Model Construction Examples

# Using the default database
alpha = RKPRAlpha("water") #single input
alpha = RKPRAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = RKPRAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = RKPRAlpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))
source
Clapeyron.LeiboviciAlpha — Type
LeiboviciAlpha <: LeiboviciAlphaModel

LeiboviciAlpha(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Leibovici Cubic alpha (α(T)) model. Generalized soave model that works for all common cubic models.

αᵢ = (1+mᵢ(1-√(Trᵢ)))^2
Trᵢ = T/Tcᵢ
mᵢ = ∑aᵢωᵢ^(i-1)
aᵢ = ∑bᵢu₀^(i-1)
u₀ = (u + 2)* √(2/(1 + u + w)) - 2
u = - Δ1 - Δ2
w = Δ1*Δ2

Model Construction Examples

# Using the default database
alpha = LeiboviciAlpha("water") #single input
alpha = LeiboviciAlpha(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
alpha = LeiboviciAlpha(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
alpha = LeiboviciAlpha(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))

References

  1. Leibovici, C. F. (1994). A unified m(ω) relation for cubic equations of state. Fluid Phase Equilibria, 101, 1–2. doi:10.1016/0378-3812(94)02603-3
source

Volume Translation Models

Clapeyron.translation — Function
translation(model::CubicModel,V,T,z,translation_model::TranslationModel)

Interface function used in cubic models. It should return a vector of cᵢ. Such as Ṽ = V + mixing(c,z)

Example:

function translation(model::CubicModel,V,T,z,translation_model::RackettTranslation)
    Tc = model.params.Tc.values
    Pc = model.params.Pc.values
    Vc = translation_model.params.Vc.values
    R = Clapeyron.R̄
    Zc = Pc .* Vc ./ (R .* Tc)
    c = 0.40768 .* (0.29441 .- Zc) .* R .* Tc ./ Pc
    return c
end
source
Clapeyron.NoTranslation — Type
NoTranslation(args...) <: TranslationModel

Input Parameters

None

Description

Default volume translation model for cubic models. It performs no translation:

V = V₀ + mixing_rule(cᵢ)
cᵢ = 0 ∀ i

Model Construction Examples

# Because this model does not have parameters, all those constructors are equivalent:
translation = NoTranslation()
translation = NoTranslation("water")
translation = NoTranslation(["water","carbon dioxide"])
source
Clapeyron.ConstantTranslation — Type
ConstantTranslation <: ConstantTranslationModel
ConstantTranslation(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • v_shift: Single Parameter (Float64) - Volume shift [m³·mol⁻¹]

Description

Constant Translation model for cubics:

V = V₀ + mixing_rule(cᵢ)

where cᵢ is constant. It does not have parameters by default, the volume shifts must be user-supplied.

Model Construction Examples

# Using user-provided parameters

# Passing files or folders
translation = ConstantTranslation(["neon","hydrogen"]; userlocations = ["path/to/my/db","properties/critical.csv"])

# Passing parameters directly
translation = ConstantTranslation(["neon","hydrogen"];userlocations = (;Vc = [4.25e-5, 6.43e-5]))
source
Clapeyron.RackettTranslation — Type
RackettTranslation <: RackettTranslationModel

RackettTranslation(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]

Model Parameters

  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • v_shift: Single Parameter (Float64) - Volume shift [m³·mol⁻¹]

Description

Rackett Translation model for cubics:

V = V₀ + mixing_rule(cᵢ)
cᵢ = 0.40768*RTcᵢ/Pcᵢ*(0.29441-Zcᵢ)
Zcᵢ = Pcᵢ*Vcᵢ/(RTcᵢ)

Model Construction Examples

# Using the default database
translation = RackettTranslation("water") #single input
translation = RackettTranslation(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
translation = RackettTranslation(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/Vc.csv"])

# Passing parameters directly
translation = RackettTranslation(["neon","hydrogen"];userlocations = (;Vc = [4.25e-5, 6.43e-5]))

References

  1. Rackett, H. G. (1970). Equation of state for saturated liquids. Journal of Chemical and Engineering Data, 15(4), 514–517. doi:10.1021/je60047a012
source
Clapeyron.PenelouxTranslation — Type
PenelouxTranslation <: PenelouxTranslationModel

PenelouxTranslation(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]

Model Parameters

  • Vc: Single Parameter (Float64) - Critical Volume [m³·mol⁻¹]
  • v_shift: Single Parameter (Float64) - Volume shift [m³·mol⁻¹]

Description

Peneloux Translation model for cubics:

V = V₀ + mixing_rule(cᵢ)
cᵢ = -0.252*RTcᵢ/Pcᵢ*(1.5448Zcᵢ - 0.4024)
Zcᵢ = Pcᵢ*Vcᵢ/(RTcᵢ)

Model Construction Examples

# Using the default database
translation = PenelouxTranslation("water") #single input
translation = PenelouxTranslation(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
translation = PenelouxTranslation(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/Vc.csv"])

# Passing parameters directly
translation = PenelouxTranslation(["neon","hydrogen"];userlocations = (;Vc = [4.25e-5, 6.43e-5]))

References

  1. Péneloux A, Rauzy E, Fréze R. (1982) A consistent correction for Redlich‐Kwong‐Soave volumes. Fluid Phase Equilibria 1, 8(1), 7–23. doi:10.1016/0378-3812(82)80002-2
source
Clapeyron.MTTranslation — Type

MTTranslation <: MTTranslationModel

MTTranslation(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

  • acentricfactor: Single Parameter (Float64)

Description

Magoulas Tassios Translation model for cubics:

V = V₀ + mixing_rule(cᵢ)
cᵢ = T₀ᵢ+(T̄cᵢ-T̄₀ᵢ)*exp(β*abs(1-Trᵢ))
Trᵢ = T/T̄cᵢ
T̄cᵢ = (RTcᵢ/Pcᵢ)*(0.3074-Zcᵢ)
T̄₀ᵢ = (RTcᵢ/Pcᵢ)*(-0.014471 + 0.067498ωᵢ - 0.084852ωᵢ^2 + 0.067298ωᵢ^3 - 0.017366ωᵢ^4)
Zcᵢ = 0.289 - 0.0701ωᵢ - 0.0207ωᵢ^2
βᵢ  = -10.2447 - 28.6312ωᵢ

Model Construction Examples

# Using the default database
translation = MTTranslation("water") #single input
translation = MTTranslation(["water","ethanol"]) #multiple components

# Using user-provided parameters

# Passing files or folders
translation = MTTranslation(["neon","hydrogen"]; userlocations = ["path/to/my/db","critical/acentric.csv"])

# Passing parameters directly
translation = MTTranslation(["neon","hydrogen"];userlocations = (;acentricfactor = [-0.03,-0.21]))

References

  1. Magoulas, K., & Tassios, D. (1990). Thermophysical properties of n-Alkanes from C1 to C20 and their prediction for higher ones. Fluid Phase Equilibria, 56, 119–140. doi:10.1016/0378-3812(90)85098-u
source

Mixing Rule Models

Clapeyron.vdW1fRule — Type
vdW1fRule <: vdW1fRuleModel

vdW1fRule(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Description

Van der Waals One-Fluid mixing rule for cubic parameters:

aᵢⱼ = √(aᵢaⱼ)(1 - kᵢⱼ)
bᵢⱼ = (1 - lᵢⱼ)(bᵢ + bⱼ)/2
ā = ∑aᵢⱼxᵢxⱼ√(αᵢ(T)αⱼ(T))
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ

Model Construction Examples

# Because this model does not have parameters, all those constructors are equivalent:
mixing = vdW1fRule()
mixing = vdW1fRule("water")
mixing = vdW1fRule(["water","carbon dioxide"])
source
Clapeyron.KayRule — Type
KayRule <: KayRuleModel

KayRule(components;
userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Description

Kay mixing rule for cubic parameters:

aᵢⱼ = √(aᵢaⱼ)(1 - kᵢⱼ)
bᵢⱼ = (1 - lᵢⱼ)(bᵢ + bⱼ)/2
ā = b̄*(∑[aᵢⱼxᵢxⱼ√(αᵢ(T)αⱼ(T))/bᵢⱼ])^2
b̄ = (∑∛(bᵢⱼ)xᵢxⱼ)^3
c̄ = ∑cᵢxᵢ

Model Construction Examples

# Because this model does not have parameters, all those constructors are equivalent:
mixing = KayRule()
mixing = KayRule("water")
mixing = KayRule(["water","carbon dioxide"])
source
Clapeyron.HVRule — Type
HVRule{γ} <: HVRuleModel

HVRule(components;
activity = Wilson,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Huron-Vidal Mixing Rule

b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ
ā = b̄(∑[xᵢaᵢᵢαᵢ/(bᵢᵢ)] - gᴱ/λ)
for Redlich-Kwong:
    λ = log(2) (0.6931471805599453)
for Peng-Robinson:
    λ = 1/(2√(2))log((2+√(2))/(2-√(2))) (0.6232252401402305)

λ is a coefficient indicating the relation between gᴱ and gᴱ(cubic) at infinite pressure. see [1] for more information. it can be customized by defining HV_λ(::HVRuleModel,::CubicModel,z)

References

  1. Huron, M.-J., & Vidal, J. (1979). New mixing rules in simple equations of state for representing vapour-liquid equilibria of strongly non-ideal mixtures. Fluid Phase Equilibria, 3(4), 255–271. doi:10.1016/0378-3812(79)80001-1

Model Construction Examples

# Using the default database
mixing = HVRule(["water","carbon dioxide"]) #default: Wilson Activity Coefficient.
mixing = HVRule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model.
mixing = HVRule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = HVRule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = HVRule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = HVRule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )
source
Clapeyron.MHV1Rule — Type
MHV1Rule{γ} <: MHV1RuleModel

MHV1Rule(components;
activity = Wilson,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Modified Huron-Vidal Mixing Rule, First Order

bᵢⱼ = (1 - lᵢⱼ)(bᵢ + bⱼ)/2
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ
ā = b̄RT(∑[xᵢaᵢᵢαᵢ/(RTbᵢᵢ)] - [gᴱ/RT + ∑log(bᵢᵢ/b̄)]/q)

if the model is Peng-Robinson:
    q = 0.53
if the model is Redlich-Kwong:
    q = 0.593

to use different values for q, overload Clapeyron.MHV1q(::CubicModel,::MHV1Model) = q

Model Construction Examples

# Using the default database
mixing = MHV1Rule(["water","carbon dioxide"]) #default: Wilson Activity Coefficient.
mixing = MHV1Rule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model.
mixing = MHV1Rule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = MHV1Rule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = MHV1Rule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = MHV1Rule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )

References

  1. Michelsen, M. L. (1990). A modified Huron-Vidal mixing rule for cubic equations of state. Fluid Phase Equilibria, 60(1–2), 213–219. doi:10.1016/0378-3812(90)85053-d
source
Clapeyron.MHV2Rule — Type
MHV2Rule{γ} <: MHV2RuleModel

MHV2Rule(components;
activity = Wilson,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Modified Huron-Vidal Mixing Rule, Second Order.

bᵢⱼ = (1 - lᵢⱼ)(bᵢ + bⱼ)/2
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ
ᾱᵢ  = aᵢαᵢ/bᵢRT
ċ = -q₁*Σᾱᵢxᵢ - q₂*Σᾱᵢxᵢ^2 - gᴱ/RT - ∑log(bᵢᵢ/b̄)
ā = (-q₁ - √(q₁^2 - 4q₂ċ))/(2q₂)

if the model is Peng-Robinson:
    q₁ = -0.4347, q₂ = -0.003654
if the model is Redlich-Kwong:
    q₁ = -0.4783, q₂ = -0.0047
    (-0.4783,-0.0047)

to use different values for q₁ and q₂, overload Clapeyron.MHV1q(::CubicModel,::MHV2Model) = (q₁,q₂)

Model Construction Examples

# Using the default database
mixing = MHV2Rule(["water","carbon dioxide"]) #default: Wilson Activity Coefficient.
mixing = MHV2Rule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model.
mixing = MHV2Rule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = MHV2Rule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = MHV2Rule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = MHV1Rule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )

References

  1. Michelsen, M. L. (1990). A modified Huron-Vidal mixing rule for cubic equations of state. Fluid Phase Equilibria, 60(1–2), 213–219. doi:10.1016/0378-3812(90)85053-d
source
Clapeyron.LCVMRule — Type
LCVMRule{γ} <: LCVMRuleModel

LCVMRule(components;
activity = Wilson,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Linear Combination of Vidal and Michaelsen (LCVM) Mixing Rule

bᵢⱼ = (1 - lᵢⱼ)(bᵢ + bⱼ)/2
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ
ᾱᵢ  = aᵢαᵢ/bᵢRT
ċ = -q₁*Σᾱᵢxᵢ - q₂*Σᾱᵢxᵢ^2 - gᴱ/RT - ∑log(bᵢᵢ/b̄)
ā = b̄RT(-1.827[gᴱ/RT - 0.3∑log(bᵢᵢ/b̄)] + Σᾱᵢxᵢ)

Model Construction Examples

# Using the default database
mixing = LCVMRule(["water","carbon dioxide"]) #default: Wilson Activity Coefficient.
mixing = LCVMRule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model.
mixing = LCVMRule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = LCVMRule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = LCVMRule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = LCVMRule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )

References

  1. Boukouvalas, C., Spiliotis, N., Coutsikos, P., Tzouvaras, N., & Tassios, D. (1994). Prediction of vapor-liquid equilibrium with the LCVM model: a linear combination of the Vidal and Michelsen mixing rules coupled with the original UNIFAC. Fluid Phase Equilibria, 92, 75–106. doi:10.1016/0378-3812(94)80043-x
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Clapeyron.WSRule — Type
WSRule{γ} <: WSRuleModel

WSRule(components;
activity = Wilson,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Wong-Sandler Mixing Rule.

aᵢⱼ = √(aᵢaⱼ)(1 - kᵢⱼ)
bᵢⱼ = (bᵢ + bⱼ)/2
c̄ = ∑cᵢxᵢ
B̄ = ΣxᵢxⱼB̄ᵢⱼ
B̄ᵢⱼ = (1 - kᵢⱼ)((bᵢ - aᵢ/RT) + (bⱼ - aⱼ/RT))/2
b̄  = B̄/(1 - gᴱ/λRT - Σxᵢaᵢαᵢ/bᵢRT)
ā = RT(b̄ - B̄)
for Redlich-Kwong:
    λ = log(2) (0.6931471805599453)
for Peng-Robinson:
    λ = 1/(2√(2))log((2+√(2))/(2-√(2))) (0.6232252401402305)

λ is a coefficient indicating the relation between gᴱ and gᴱ(cubic) at infinite pressure. See [1] for more information. It can be customized by defining WS_λ(::WSRuleModel,::CubicModel).

Model Construction Examples

# Using the default database
mixing = WSRule(["water","carbon dioxide"]) #default: Wilson Activity Coefficient.
mixing = WSRule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model.
mixing = WSRule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = WSRule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = WSRule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = WSRule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )

References

  1. Wong, D. S. H., & Sandler, S. I. (1992). A theoretically correct mixing rule for cubic equations of state. AIChE journal. American Institute of Chemical Engineers, 38(5), 671–680. doi:10.1002/aic.690380505
source
Clapeyron.modWSRule — Type
modWSRule{γ} <: WSRuleModel

modWSRule(components;
activity = Wilson,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

modified Wong-Sandler Mixing Rule.

aᵢⱼ = √(aᵢaⱼ)(1 - kᵢⱼ)
bᵢⱼ = (bᵢ + bⱼ)/2
c̄ = ∑cᵢxᵢ
B̄ = Σxᵢxⱼ(bᵢⱼ - aᵢⱼ√(αᵢαⱼ)/RT)
b̄  = B̄/(1 - gᴱ/λRT - Σxᵢaᵢαᵢ/bᵢRT)
ā = RT(b̄ - B̄)
for Redlich-Kwong:
    λ = log(2) (0.6931471805599453)
for Peng-Robinson:
    λ = 1/(2√(2))log((2+√(2))/(2-√(2))) (0.6232252401402305)

λ is a coefficient indicating the relation between gᴱ and gᴱ(cubic) at infinite pressure. see [1] for more information. it can be customized by defining WS_λ(::WSRuleModel,::CubicModel,z)

Model Construction Examples

# Using the default database
mixing = modWSRule(["water","carbon dioxide"]) #default: Wilson Activity Coefficient.
mixing = modWSRule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model.
mixing = modWSRule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = modWSRule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = modWSRule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = modWSRule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )

References

  1. Wong, D. S. H., & Sandler, S. I. (1992). A theoretically correct mixing rule for cubic equations of state. AIChE journal. American Institute of Chemical Engineers, 38(5), 671–680. doi:10.1002/aic.690380505
  2. Orbey, H., & Sandler, S. I. (1995). Reformulation of Wong-Sandler mixing rule for cubic equations of state. AIChE journal. American Institute of Chemical Engineers, 41(3), 683–690. doi:10.1002/aic.690410325
source
Clapeyron.VTPRRule — Type
VTPRRule{γ} <: VTPRRuleModel

VTPRRule(components;
activity = UNIFAC,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Mixing Rule used by the Volume-translated Peng-Robinson VTPR equation of state. only works with activity models that define an excess residual Gibbs energy function Clapeyron.excess_g_res(model,P,T,z) function (like UNIQUAC and UNIFAC models)

aᵢⱼ = √(aᵢaⱼ)(1-kᵢⱼ)
bᵢⱼ = ((bᵢ^(3/4) + bⱼ^(3/4))/2)^(4/3)
log(γʳ)ᵢ = lnγ_res(model.activity,V,T,z)
gᴱᵣₑₛ = ∑RTlog(γʳ)ᵢxᵢ
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ
ā = b̄RT(∑[xᵢaᵢᵢαᵢ/(RTbᵢᵢ)] - gᴱᵣₑₛ/(0.53087RT))

Model Construction Examples

# Note: this model was meant to be used exclusively with the VTPRUNIFAC activity model.

# Using the default database
mixing = VTPRRule(["water","carbon dioxide"]) #default: VTPRUNIFAC Activity Coefficient.
mixing = VTPRRule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model
mixing = VTPRRule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = VTPRRule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = VTPRRule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = VTPRRule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )

References

  1. Ahlers, J., & Gmehling, J. (2001). Development of an universal group contribution equation of state. Fluid Phase Equilibria, 191(1–2), 177–188. doi:10.1016/s0378-3812(01)00626-4
source
Clapeyron.PSRKRule — Type
PSRKRule{γ} <: MHV1RuleModel

PSRKRule(components;
activity = Wilson,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Mixing Rule used by the Predictive Soave-Redlich-Kwong PSRK EoS, derived from the First Order modified Huron-Vidal Mixing Rule.

Model Construction Examples

# Note: this model was meant to be used exclusively with the PSRKUNIFAC activity model.

# Using the default database
mixing = PSRKRule(["water","carbon dioxide"]) #default: PSRKUNIFAC Activity Coefficient.
mixing = PSRKRule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model
mixing = PSRKRule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = PSRKRule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = PSRKRule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = PSRKRule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )
source
Clapeyron.UMRRule — Type
UMRRule{γ} <: UMRRuleModel

UMRRule(components;
activity = UNIFAC,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Mixing Rule used by the Universal Mixing Rule Peng-Robinson UMRPR equation of state.

aᵢⱼ = √(aᵢaⱼ)(1 - kᵢⱼ)
bᵢⱼ = (1 - lᵢⱼ)((√bᵢ +√bⱼ)/2)^2
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ
ā = b̄RT(∑[xᵢaᵢᵢαᵢ/(RTbᵢᵢ)] - [gᴱ/RT]/0.53)

## Model Construction Examples

Note: this model was meant to be used exclusively with the UNIFAC activity model.

Using the default database

mixing = VTPRRule(["water","carbon dioxide"]) #default: UNIFAC Activity Coefficient. mixing = VTPRRule(["water","carbon dioxide"],activity = NRTL) #passing another Activity Coefficient Model mixing = VTPRRule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = ogUNIFAC) #passing a GC Activity Coefficient Model.

Passing a prebuilt model

actmodel = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0])) mixing = VTPRRule(["water","ethanol"],activity = actmodel)

Using user-provided parameters

Passing files or folders

mixing = VTPRRule(["water","ethanol"]; activity = NRTL, activityuserlocations = ["path/to/my/db","nrtlge.csv"])

Passing parameters directly

mixing = VTPRRule(["water","ethanol"]; activity = NRTL, userlocations = (a = [0.0 3.458; -0.801 0.0], b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]) )

source
Clapeyron.QCPRRule — Type
QCPRRule <: MHV2RuleModel

QCPRRule(components;
activity = Wilson,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Quantum-Corrected Mixing Rule, used by QCPR EoS:

aᵢⱼ = √(aᵢaⱼ)(1 - kᵢⱼ)
bᵢⱼ = (1 - lᵢⱼ)(bqᵢ + bqⱼ)/2
bqᵢ = bᵢβᵢ(T)
βᵢ(T) = (1 + Aᵢ/(T + Bᵢ))^3 / (1 + Aᵢ/(Tcᵢ + Bᵢ))^3
ā = ∑aᵢⱼxᵢxⱼ√(αᵢ(T)αⱼ(T))
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ

References

  1. Aasen, A., Hammer, M., Lasala, S., Jaubert, J.-N., & Wilhelmsen, Ø. (2020). Accurate quantum-corrected cubic equations of state for helium, neon, hydrogen, deuterium and their mixtures. Fluid Phase Equilibria, 524(112790), 112790. doi:10.1016/j.fluid.2020.112790
source
Clapeyron.PPR78Rule — Type
PPR78Rule <: PPR78RuleModel

PPR78Rule(components;
userlocations = String[],
group_userlocations = String[]
verbose::Bool=false)

Input Parameters

  • A: Pair Parameter (Float64) - Fitted Parameter [K]
  • B: Pair Parameter (Float64) - Fitted Parameter [K]

Description

PPR78 Mixing Rule, Uses E-PPR78 Group params. Default for EPPR78 EoS.

aᵢⱼ = √(aᵢaⱼ)
bᵢⱼ = (bᵢ +bⱼ)/2
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ
ā = b̄(∑[xᵢaᵢαᵢ/(bᵢᵢ)] - ∑xᵢxⱼbᵢbⱼEᵢⱼ/2b̄)
Eᵢⱼ = ∑(z̄ᵢₖ - z̄ⱼₖ)(z̄ᵢₗ - z̄ⱼₗ) × Aₖₗ × (298.15/T)^(Aₖₗ/Bₖₗ - 1)

References

  1. Jaubert, J.-N., Privat, R., & Mutelet, F. (2010). Predicting the phase equilibria of synthetic petroleum fluids with the PPR78 approach. AIChE Journal. American Institute of Chemical Engineers, 56(12), 3225–3235. doi:10.1002/aic.12232
  2. Jaubert, J.-N., Qian, J.-W., Lasala, S., & Privat, R. (2022). The impressive impact of including enthalpy and heat capacity of mixing data when parameterising equations of state. Application to the development of the E-PPR78 (Enhanced-Predictive-Peng-Robinson-78) model. Fluid Phase Equilibria, (113456), 113456. doi:10.1016/j.fluid.2022.113456
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Clapeyron.gErRule — Type
gErRule{γ} <: gErRuleModel

gErRule(components;
activity = NRTL,
userlocations = String[],
activity_userlocations = String[],
verbose::Bool=false)

Input Parameters

None

Input models

  • activity: Activity Model

Description

Mixing rule that uses the residual part of the activity coefficient model:

bᵢⱼ = ( (bᵢ^(2/3) + bⱼ^(2/3)) / 2 )^(3/2)
b̄ = ∑bᵢⱼxᵢxⱼ
c̄ = ∑cᵢxᵢ
ā/b̄ = b̄RT*(∑xᵢaᵢ/bᵢ + gᴱᵣ/Λ
Λ = 1/(r₂ - r₁) * log((1 - r₂)/(1 - r₁))

Model Construction Examples

# Using the default database
mixing = gErRule(["water","carbon dioxide"]) #default: NRTL Activity Coefficient.
mixing = gErRule(["water","carbon dioxide"],activity = Wilson) #passing another Activity Coefficient Model.
mixing = gErRule([("ethane",["CH3" => 2]),("butane",["CH2" => 2,"CH3" => 2])],activity = UNIFAC) #passing a GC Activity Coefficient Model.

# Passing a prebuilt model

act_model = NRTL(["water","ethanol"],userlocations = (a = [0.0 3.458; -0.801 0.0],b = [0.0 -586.1; 246.2 0.0], c = [0.0 0.3; 0.3 0.0]))
mixing = gErRule(["water","ethanol"],activity = act_model)

# Using user-provided parameters

# Passing files or folders
mixing = gErRule(["water","ethanol"]; activity = NRTL, activity_userlocations = ["path/to/my/db","nrtl_ge.csv"])

# Passing parameters directly
mixing = gErRule(["water","ethanol"];
                activity = NRTL,
                userlocations = (a = [0.0 3.458; -0.801 0.0],
                    b = [0.0 -586.1; 246.2 0.0],
                    c = [0.0 0.3; 0.3 0.0])
                )

References

  1. Piña-Martinez, A., Privat, R., Nikolaidis, I. K., Economou, I. G., & Jaubert, J.-N. (2021). What is the optimal activity coefficient model to be combined with the translated–consistent Peng–Robinson equation of state through advanced mixing rules? Cross-comparison and grading of the Wilson, UNIQUAC, and NRTL aE models against a benchmark database involving 200 binary systems. Industrial & Engineering Chemistry Research, 60(47), 17228–17247. doi:10.1021/acs.iecr.1c03003
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