## 2 Basic Analysis of Prediction Models and Model Verification
### Prediction Models of Viscosity and Thermal Conductivity
#### 3.4.1 Prediction Models of Viscosity and Thermal Conductivity
 \tag{68}\]  
\[T_{\rm dim}\!=1.2593*T\;/\;T_{c} \tag{69}\]  
\[F^{*} =1-0.2756\omega+0.059035\mu_{\rm dim}^{4}+\kappa \tag{70}\]  
\[\mu_{\rm dim} =131.3\mu\;/\;(V_{c}\,T_{c})^{0.5} \tag{71}\]  
\[\lambda^{int}(T) =0.00132\frac{\eta^{*}}{M}[c^{*}-\frac{5}{2}\,R] \tag{72}\]  
\[\lambda^{*}(T)=\frac{15\,\times\,10^{-3}R\eta^{*}}{4M} \tag{73}\]  
where \(\Omega\) is the collision integral; \(F^{*}\) is the modified coefficient of the dilute gas viscosity; \(T_{dim}\) is the dimensionless temperature; \(\mu_{dim}\) is the dimensionless molecular dipole moment; \(c^{*}\) is the ideal gas specific heat, J/(kg\(\cdot\)K); and \(\kappa\) is the parameter related to hydrogen bonding interactions, which equals to 0 for electronic fluoride fluids. From the perspective of input parameters, [PERSON] et al. [109] divided the prediction models of viscosity into the following forms: viscosity varies with temperature, viscosity varies with density, viscosity varies with surface tension and viscosity varies with molecular property. Among them, temperature is easiest to obtain in engineering applications; so, the prediction models of viscosity varying with temperature are discussed in this work. From the perspective of the prediction principle, [PERSON] et al. [109] classified the prediction models into two categories: models based on the principle of corresponding states (PCS) and models based on the group contribution method (GCM). The models based on the principle of corresponding states take many forms, but the PCS model used in REFPROP v10.0 [107] is only discussed in this paper. For the models of viscosity (varying with temperature) based on the group contribution method, the viscosity at a specific temperature or the temperature corresponding to a certain viscosity is firstly obtained and then the viscosities at other temperatures are obtained further. [PERSON] et al. [110] proposed a model based on the relationship between viscosity and saturated vapor pressure. The liquid viscosity at the boiling point of pure organic substances by the group contribution method is obtained firstly and then, the liquid viscosities at other temperatures are extrapolated from the saturated vapor pressures. The expression of this model is shown as follows (hereinafter referred to as the SVIS1 model). \[\eta=\eta_{b}p^{-DV_{1}} \tag{74}\]  
\[\ln p=(4.5398+1.0309\ln T_{b})\ \times\]  
\[(1-\frac{(3-2T/T_{b})^{0.19}}{T/T_{b}}-0.38(3-2T\ /\ T_{b})^{-0.81}\ln(T\ /\ T_{b})),\ T<T_{b} \tag{75}\]  
\[\ln p= (\ln p_{c})T_{c}\ /\ (T_{c}-T_{b})(1-1\ /\ T_{b}\ T),\ T>T_{b} \tag{76}\]  
where \(\eta_{\text{b}}\) and \(DV_{1}\) are determined by the group contribution method, and \(p\) is the saturated vapor pressure. In addition, [PERSON] et al. [111] proposed another prediction model of the liquid viscosity for pure organic substances (hereinafter referred to as the SVIS2 model), which is suitable for a temperature range of 0.7 (the contrast temperature) around the critical temperature. The expression of the SVIS2 model is shown as Equation (77). \[\ln\eta=[\frac{\ln\eta_{b}}{\ln(0.248\eta_{b})}]^{\frac{1-T_{c}}{1-T_{b}}}\ln( 0.248\eta_{b}) \tag{77}\]  
For the model proposed by [PERSON] et al. [112] based on the group contribution method (hereinafter referred to as the NVIS model), when the liquid viscosities of 813 pure substances (12,139 data points) were predicted, the relative average deviation between the predicted and reference values was 15.3%. The NVIS model is shown in Equations (78)-(80):  
\[F^{*} =1-0.2756\omega+0.059035\mu_{\rm dim}^{4}+\kappa \tag{70}\]0  
\[F^{*} =1-0.2756\omega+0.059035\mu_{\rm dim}^{4}+\kappa \tag{70}\]1  
\[F^{*} =1-0.2756\omega+0.059035\mu_{\rm dim}^{4}+\kappa \tag{70}\]2  
where \(DV_{2}\) is the slope; \(T_{\textit{ref}}\) is the reference temperature of the viscosity, K; \(Num\) is the number of non-hydrogen atoms; and \(Sum\) (\(DV_{2}\)) and \(Sum\) (\(T_{\textit{ref}}\)) are obtained by the group contribution method.