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https://github.com/CoolProp/CoolProp.git
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474 lines
32 KiB
Plaintext
474 lines
32 KiB
Plaintext
{
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"metadata": {
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"name": ""
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "heading",
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"level": 1,
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"metadata": {},
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"source": [
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"Forming the Phase Envelope"
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]
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Overview"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The analysis in this section follows the methodologies proposed in the GERG 2004 monograph published in 2007\n",
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"\n",
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"System of Equations"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Our residual vector $\\mathbf{F}$ is equal to \n",
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"\n",
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"$$F_i = \\ln\\phi(T,p,\\mathbf{y})-\\ln \\phi(T,p,\\mathbf{x})+\\ln K_i=0, i=1,2,3... N$$\n",
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"\n",
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"$$F_{N+1} = \\sum_{i=1}^{N}(y_i-x_i)=0$$\n",
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" \n",
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"where\n",
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"\n",
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"$$x_i = \\frac{z_i}{1-\\beta+\\beta K_i}$$\n",
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" \n",
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"and \n",
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"\n",
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"$$y_i = \\frac{K_iz_i}{1-\\beta+\\beta K_i}$$\n",
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" \n",
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"DO NOT NORMALIZE $x$ and $y$ !!!!\n",
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"\n",
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"$$F_{N+2} = X_s - S = 0$$\n",
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" \n",
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"and the system to be solved is equal to\n",
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"\n",
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"$$\\mathbf{J}\\mathbf{\\Delta X}= -\\mathbf{F}$$\n",
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" "
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]
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Building the Jacobian matrix"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This is the trickiest part of this method. There are a lot of derivatives to implement, and we want to implement all of them analytically.\n",
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"\n",
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"$$\\frac{\\partial F_i}{\\partial \\ln T} = T\\left[ \\left(\\frac{\\partial \\ln \\phi_i}{\\partial T}\\right)''_{p,\\mathbf{n}} -\\left(\\frac{\\partial \\ln \\phi_i}{\\partial T}\\right)'_{p,\\mathbf{n}}\\right]$$\n",
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" \n",
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"$$\\frac{\\partial F_i}{\\partial \\ln p} = p\\left[ \\left(\\frac{\\partial \\ln \\phi_i}{\\partial p}\\right)''_{T,\\mathbf{n}} -\\left(\\frac{\\partial \\ln \\phi_i}{\\partial p}\\right)'_{T,\\mathbf{n}}\\right]$$\n",
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" \n",
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"$$ \\frac{\\partial F_i}{\\partial \\ln K_j} = \\frac{K_jz_j}{(1-\\beta+\\beta K_j)^2}[(1-\\beta)\\phi_{ij}''+\\beta\\phi_{ij}']+\\zeta $$\n",
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"\n",
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"$\\zeta$ is the Kronecker delta or $\\zeta = 0$ for $i\\neq j$ , and $\\zeta = 0$ for $i=j$. Also\n",
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"\n",
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"$$\\phi_{ij} = n\\left( \\frac{\\partial \\ln \\phi_i}{\\partial n_j}\\right)_{T,p}$$\n",
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"\n",
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"For the $F_{N+1}$ term,\n",
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"\n",
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"$$\\frac{\\partial F_{N+1}}{\\partial \\ln K_j}=\\frac{K_jz_j}{(1-\\beta+\\beta K_j)^2}$$\n",
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"\n",
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"and all other partials of $F_{N+1}$ in the Jacobian are zero. For the specified term\n",
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"\n",
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"$$\\frac{\\partial F_{N+2}}{X_s}=1$$\n",
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" \n",
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"and all other partials of $F_{N+2}$ in the Jacobian are zero.\n",
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"\n",
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"From GERG 2004 Monograph, Eqn 7.27:\n",
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"\n",
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"\n",
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"$$\\ln \\phi_i = \\left( \\frac{\\partial n\\alpha^r}{\\partial n_i}\\right)_{T,V,n_j}-\\ln Z$$\n",
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" \n",
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"and (Kunz, 2012, Table B4)\n",
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"\n",
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"$$\\left( \\frac{\\partial n\\alpha^r}{\\partial n_i}\\right)_{T,V,n_j} = \\alpha^r + n\\left( \\frac{\\partial \\alpha^r}{\\partial n_i}\\right)_{T,V,n_j}$$\n",
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" \n",
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"so\n",
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"\n",
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"$$\\ln \\phi_i = \\alpha^r + n\\left( \\frac{\\partial \\alpha^r}{\\partial n_i}\\right)_{T,V,n_j}-\\ln Z$$"
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]
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Density marching phase envelope construction(T,P)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Another two alternatives have been proposed in A DENSITY MARCHING METHOD FOR CALCULATING PHASE ENVELOPES\n",
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"Gadhiraju Venkatarathnam, I&ECR, 2014\n",
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"\n",
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"In this paper, density marching methods are proposed rather than methods that march in temperature, pressure, or K-factor.\n",
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"\n",
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"The system of equations to be solved is similar to that of the GERG 2004 formulation, where the unknowns are $\\ln(T)$, $\\ln(p)$, and $\\ln(K_i)$\n",
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"\n",
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"(A1) - OK\n",
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"$$F_i = \\ln K_i+\\ln\\phi(T,p,\\mathbf{y})-\\ln \\phi(T,p,\\mathbf{x})=0, i=1,2,3... N$$\n",
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"\n",
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"(A2) - OK\n",
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"$$F_{N+1} = \\sum_{i=1}^{N}\\frac{z_i(K_i-1)}{1-\\beta+\\beta K_i}=0$$\n",
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" \n",
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"(A3) - TYPO, should be $\\ln(\\rho)$ rather than $\\rho$, and should be all on left-hand-side\n",
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"$$F_{N+2} = \\ln \\rho ''-\\ln\\rho''_{S} = 0$$\n",
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"\n",
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"(A6) - TYPO, missing an n to multiply the terms $\\left( \\frac{\\partial \\ln \\phi_i}{\\partial n_j}\\right)_{T,p}$\n",
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"$$ \\frac{\\partial F_i}{\\partial \\ln K_j} = \\frac{K_jz_j}{(1-\\beta+\\beta K_j)^2}[(1-\\beta)\\phi_{ij}''+\\beta\\phi_{ij}']+\\zeta $$\n",
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"\n",
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"$\\zeta$ is the Kronecker delta or $\\zeta = 0$ for $i\\neq j$ , and $\\zeta = 0$ for $i=j$.\n",
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"\n",
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"(A7) - OK\n",
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"$$\\frac{\\partial F_i}{\\partial \\ln T} = T\\left[ \\left(\\frac{\\partial \\ln \\phi_i}{\\partial T}\\right)''_{p,\\mathbf{n}} -\\left(\\frac{\\partial \\ln \\phi_i}{\\partial T}\\right)'_{p,\\mathbf{n}}\\right]$$\n",
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"\n",
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"(A8) - OK\n",
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"$$\\frac{\\partial F_i}{\\partial \\ln p} = p\\left[ \\left(\\frac{\\partial \\ln \\phi_i}{\\partial p}\\right)''_{T,\\mathbf{n}} -\\left(\\frac{\\partial \\ln \\phi_i}{\\partial p}\\right)'_{T,\\mathbf{n}}\\right]$$\n",
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" \n",
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"(A9) - OK\n",
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"$$\\frac{\\partial F_{N+1}}{\\partial \\ln K_j}=\\frac{K_jz_j}{(1-\\beta+\\beta K_j)^2}$$\n",
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"\n",
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"(A11) - OK\n",
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"$$ \\frac{\\partial F_{N+2}}{\\partial \\ln K_j} = \\frac{K_jz_j(1-\\beta)\\beta}{(1-\\beta+\\beta K_j)^2}\\left(n\\left(\\frac{\\partial \\rho}{\\partial n_j}\\right)''_{T,p}\\right)\\left(\\frac{1}{\\rho''_{S}}\\right)$$\n",
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"\n",
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"(A12) - OK\n",
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"$$\\frac{\\partial F_{N+2}}{\\partial \\ln T}=\\left(\\frac{\\partial \\rho}{\\partial T}\\right)''_{p,n}\\frac{T}{\\rho''_{S}}$$\n",
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"\n",
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"(A13) - OK\n",
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"$$\\frac{\\partial F_{N+2}}{\\partial \\ln p}=\\left(\\frac{\\partial \\rho}{\\partial p}\\right)''_{T,n}\\frac{p}{\\rho''_{S}}$$\n"
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]
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Density marching phase envelope construction (density)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Another two alternatives have been proposed in A DENSITY MARCHING METHOD FOR CALCULATING PHASE ENVELOPES\n",
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"Gadhiraju Venkatarathnam, I&ECR, 2014\n",
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"\n",
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"In this paper, density marching methods are proposed rather than methods that march in temperature, pressure, or K-factor.\n",
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"\n",
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"The system of equations to be solved is similar to that of the GERG 2004 formulation, where the unknowns are $\\ln(T)$, $\\ln(p)$, and $\\ln(K_i)$\n",
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"\n",
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"(A14) - OK\n",
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"$$F_i = \\ln K_i+\\ln\\phi(T,\\rho'',\\mathbf{y})-\\ln \\phi(T,\\rho',\\mathbf{x})=0, i=1,2,3... N$$\n",
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"\n",
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"(A15) - OK\n",
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"$$F_{N+1} = \\sum_{i=1}^{N}\\frac{z_i(K_i-1)}{1-\\beta+\\beta K_i}=0$$\n",
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" \n",
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"(A16) - OK\n",
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"$$F_{N+2} = p(T,\\rho',\\mathbf{y})-p(T,\\rho'',\\mathbf{x}) = 0$$\n",
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"\n",
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"(A17) - TYPO, missing an n to multiply the terms $\\left( \\frac{\\partial \\ln \\phi_i}{\\partial n_j}\\right)_{T,p}$\n",
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"$$ \\frac{\\partial F_i}{\\partial \\ln K_j} = \\frac{K_jz_j}{(1-\\beta+\\beta K_j)^2}[(1-\\beta)\\phi_{ij}''+\\beta\\phi_{ij}']+\\zeta $$\n",
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"\n",
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"$\\zeta$ is the Kronecker delta or $\\zeta = 0$ for $i\\neq j$ , and $\\zeta = 0$ for $i=j$.\n",
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"\n",
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"(A18) - OK\n",
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"$$\\frac{\\partial F_i}{\\partial \\ln T} = T\\left[ \\left(\\frac{\\partial \\ln \\phi_i}{\\partial T}\\right)''_{p,\\mathbf{n}} -\\left(\\frac{\\partial \\ln \\phi_i}{\\partial T}\\right)'_{p,\\mathbf{n}}\\right]$$\n",
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"\n",
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"(A19) - OK\n",
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"$$\\frac{\\partial F_i}{\\partial \\ln \\rho'} = -\\rho'\\left(\\frac{\\partial \\ln \\phi_i}{\\partial \\rho}\\right)'_{T,n}$$\n",
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" \n",
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"(A20) - OK\n",
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"$$\\frac{\\partial F_{N+1}}{\\partial \\ln K_j}=\\frac{K_jz_j}{(1-\\beta+\\beta K_j)^2}$$\n",
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"\n",
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"(A22) - TYPO Second derivative of ln(phi) with respect to rho' needs constraints, first needs to have the constraints in the right place\n",
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"$$ \\frac{\\partial F_{N+2}}{\\partial \\ln K_j} = \\frac{RTK_jz_j}{(1-\\beta+\\beta K_j)^2}\\left[(1-\\beta)\\left(\\frac{\\partial \\ln \\phi_i}{\\partial \\rho}\\right)''_{T,n}+\\beta\\left(\\frac{\\partial \\ln \\phi_i}{\\partial \\rho}\\right)'_{T,n}\\right]$$\n",
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"\n",
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"(A23) - TYPO Should be A23\n",
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"$$\\frac{\\partial F_{N+2}}{\\partial \\ln T}=T\\left[\\left(\\frac{\\partial p}{\\partial T}\\right)'_{\\rho',n}-\\left(\\frac{\\partial p}{\\partial T}\\right)''_{\\rho'',n} \\right]$$\n",
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"\n",
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"(A24) - TYPO Should be A24\n",
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"$$\\frac{\\partial F_{N+2}}{\\partial \\ln p'}=\\rho'\\left(\\frac{\\partial p}{\\partial \\rho}\\right)'_{T,n}$$\n"
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]
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},
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{
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"cell_type": "heading",
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"level": 2,
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"metadata": {},
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"source": [
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"Other analytic derivatives"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Three analyic derivatives are not provided in GERG and need to be rederived:\n",
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"\n",
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"$$\\left(\\frac{\\partial \\ln \\phi_i}{\\partial \\rho}\\right)_{T,n}$$\n",
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"\n",
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"$$\\left(\\frac{\\partial \\ln \\phi_i}{\\partial T}\\right)_{\\rho,n}$$\n",
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"\n",
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"$$n\\left(\\frac{\\partial \\rho}{\\partial n_j}\\right)_{T,p}$$\n",
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"The last is for T,p marching, the first two are for density marching."
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]
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},
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{
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"cell_type": "heading",
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"level": 3,
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"metadata": {},
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"source": [
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"Derivations"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"For $n\\left( \\frac{\\partial \\rho}{\\partial n_i}\\right)_{T,p,n_j}$\n",
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"-----------------------------------------------------------------\n",
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"\n",
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"GERG 2007 Monograph Equation 7.32 gives\n",
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"\n",
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"$$\\left( \\frac{\\partial V}{\\partial n_i}\\right)_{T,p,n_j} = \\dfrac{-\\left(\\dfrac{\\partial p}{\\partial n_i}\\right)_{T,V,n_j}}{\\left(\\dfrac{\\partial p}{\\partial V}\\right)_{T,n}}$$\n",
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"\n",
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"expand the left hand side with \n",
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"\n",
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"$V = vn = \\dfrac{n}{\\rho}$\n",
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"\n",
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"n held constant in derivative, so get\n",
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"\n",
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"$$\\left( \\frac{\\partial V}{\\partial n_i}\\right)_{T,p,n_j} = n\\left( \\frac{\\partial (1/\\rho)}{\\partial n_i}\\right)_{T,p,n_j} = -\\frac{n}{\\rho^2}\\left( \\frac{\\partial \\rho}{\\partial n_i}\\right)_{T,p,n_j}$$\n",
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"\n",
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"so\n",
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"\n",
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"$$ n\\left( \\frac{\\partial \\rho}{\\partial n_i}\\right)_{T,p,n_j} = -\\rho^2\\left( \\frac{\\partial V}{\\partial n_i}\\right)_{T,p,n_j} $$\n",
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"\n",
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"For $\\left(\\frac{\\partial \\ln \\phi_i}{\\partial \\rho}\\right)_{T,n}$ and $\\left(\\frac{\\partial \\ln \\phi_i}{\\partial T}\\right)_{\\rho,n}$\n",
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"--------------------------------------------------------------------------------------------------------------------------------------------\n",
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"\n",
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"GERG 2007 Monograph 7.27\n",
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"$$\\ln \\phi_i = \\left(\\frac{\\partial n \\alpha^r}{\\partial n_i} \\right)_{T,V,n_j} - \\ln Z $$\n",
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"\n",
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"GERG 2007 Monograph 7.34\n",
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"$$\\ln \\left(\\frac{f_i}{n_i}\\right) = \\ln\\left(\\frac{RT}{V}\\right)+\\left(\\frac{\\partial n\\alpha^r}{\\partial n_i} \\right)_{T,V,n_j}$$\n",
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"\n",
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"and $Z = (pV)/(nRT)$, thus\n",
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"\n",
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"$$\\ln \\phi_i = \\ln \\left(\\frac{f_i}{n_i}\\right) - \\ln\\left(\\frac{RT}{V}\\right) - \\ln \\left(\\frac{pV}{nRT}\\right) ?= \\ln \\left(\\frac{f_i}{n_i}\\right) -\\ln\\left(\\frac{p}{n}\\right)$$\n",
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"\n",
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"$$\\frac{\\partial \\left[\\ln\\left(\\frac{p}{n}\\right)\\right]}{\\partial T} = \\frac{1}{pn}\\left(\\frac{\\partial p}{\\partial T}\\right)_{\\rho,n}$$\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Equivalent fugacities for the $i$-th component\n",
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"\n",
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"$$ F_k^A = \\ln f_i(T,p,\\mathbf{x})-\\ln f_i(T,p,\\mathbf{y}) = 0\\mbox{ for } k = i = 1...N $$\n",
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"\n",
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"Material balance\n",
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"\n",
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"$$ F_k^B = \\frac{z_i-x_i}{y_i-x_i}-\\frac{z_{N-1}-x_{N-1}}{y_{N-1}-x_{N-1}}\\mbox{ for }i=1..N-2; k = i+N; k = N+1..2N-2$$\n",
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"\n",
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"The independent variables to be obtained are\n",
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"\n",
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"$$ \n"
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]
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},
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{
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"cell_type": "heading",
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"level": 1,
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"metadata": {},
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"source": [
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"Conversion of derivatives"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"To convert partial with $T$, $V$, $x_k$ held constant to one with $\\tau$, $\\delta$, $x_k$ held constant, use Gernert 3.118, or\n",
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"\n",
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"$$ \\frac{\\partial}{\\partial x_j} [Y]_{T,V,x_k} = \\frac{\\partial}{\\partial x_j} [Y]_{\\tau,\\delta,x_k}+\\left(\\frac{\\partial\\delta}{\\partial x_j}\\right)_{T,V,x_k}\\left.\\frac{\\partial Y}{\\partial\\delta}\\right|_{\\tau,\\bar x}+\\left(\\frac{\\partial\\tau}{\\partial x_j}\\right)_{T,V,x_k}\\left.\\frac{\\partial Y}{\\partial\\tau}\\right|_{\\delta,\\bar x} $$\n",
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"\n",
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"To convert pressure,\n",
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"\n",
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"$$ p=\\rho R T(1+\\delta \\alpha_\\delta) $$\n",
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"\n",
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"convert $\\rho$ and $T$ to reduced variables\n",
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"\n",
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"$$ p=\\rho_r(\\bar x)\\delta R \\frac{T_r(\\bar x)}{\\tau}(1+\\delta \\alpha_\\delta) = \\rho_r(\\bar x)R \\frac{T_r(\\bar x)}{\\tau}\\delta (1+\\delta \\alpha_\\delta)$$\n",
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"\n",
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"All the derivatives\n",
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"\n",
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"$$ \\frac{dp}{d\\tau}\\times\\frac{d\\tau}{dx_j} = -\\rho_r(\\bar x)\\delta R \\frac{T_r(\\bar x)}{\\tau^2}(1+\\delta \\alpha_\\delta) \\times \\frac{1}{T}\\frac{\\partial T_r}{\\partial x_j}|_{T,V,x_k}$$\n",
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"\n",
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"$$ \\frac{dp}{d\\delta}\\times\\frac{d\\delta}{dx_j} = \\rho_r(\\bar x) R \\frac{T_r(\\bar x)}{\\tau}[ (1+\\delta \\alpha_\\delta)+ \\delta(\\alpha_\\delta+\\delta \\alpha_{\\delta\\delta})] \\times \\frac{-\\delta}{\\rho_r}\\frac{\\partial \\rho_r}{\\partial x_j}|_{T,V,x_k}$$\n",
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"\n",
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"$$ \\frac{\\partial p}{\\partial x_j}|_{\\tau,\\delta,x_k} = \\frac{\\delta R}{\\tau}\\left[\\rho_r(\\bar x)T_r(\\bar x)(\\delta \\frac{\\partial}{\\partial x_j}[\\alpha_\\delta]_{\\tau, \\delta, x_k})+(1+\\delta \\alpha_\\delta)\\left(\\rho_r \\frac{\\partial T_r}{\\partial x_j}+T_r \\frac{\\partial \\rho_r}{\\partial x_j}\\right)\\right]$$\n",
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"\n",
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"with $\\delta$ factored out"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Turn back into normal variables\n",
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|
"$$ \\frac{dp}{d\\tau}\\times\\frac{d\\tau}{dx_j} = -\\frac{\\rho R}{\\tau}(1+\\delta \\alpha_\\delta)\\frac{\\partial T_r}{\\partial x_j}|_{T,V,x_k}$$\n",
|
|
"\n",
|
|
"$$ \\frac{dp}{d\\delta}\\times\\frac{d\\delta}{dx_j} = - R T[ (1+\\delta \\alpha_\\delta)+ \\delta(\\alpha_\\delta+\\delta \\alpha_{\\delta\\delta})]\\delta\\frac{\\partial \\rho_r}{\\partial x_j}|_{T,V,x_k}$$\n",
|
|
"\n",
|
|
"$$ \\frac{\\partial p}{\\partial x_j}|_{\\tau,\\delta,x_k} = R\\left[\\rho T (\\delta \\frac{\\partial}{\\partial x_j}[\\alpha_\\delta]_{\\tau, \\delta, x_k})+(1+\\delta \\alpha_\\delta)\\left(\\frac{\\rho}{\\tau} \\frac{\\partial T_r}{\\partial x_j}+\\delta T \\frac{\\partial \\rho_r}{\\partial x_j}\\right)\\right]$$"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"First term cancels with a term in the third one, yielding\n",
|
|
"\n",
|
|
"$$ \\frac{dp}{d\\delta}\\times\\frac{d\\delta}{dx_j} = -\\delta R T[ (1+\\delta \\alpha_\\delta)+ \\delta(\\alpha_\\delta+\\delta \\alpha_{\\delta\\delta})]\\frac{\\partial \\rho_r}{\\partial x_j}|_{T,V,x_k}$$\n",
|
|
"\n",
|
|
"$$ \\frac{\\partial p}{\\partial x_j}|_{\\tau,\\delta,x_k} = \\rho R T (\\delta \\frac{\\partial}{\\partial x_j}[\\alpha_\\delta]_{\\tau, \\delta, x_k})+(1+\\delta \\alpha_\\delta)\\delta R T \\frac{\\partial \\rho_r}{\\partial x_j}$$"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"First term in first line cancels with term at end of second line, yielding\n",
|
|
"\n",
|
|
"$$ \\frac{dp}{d\\delta}\\times\\frac{d\\delta}{dx_j} = -\\delta R T[ \\delta(\\alpha_\\delta+\\delta \\alpha_{\\delta\\delta})]\\frac{\\partial \\rho_r}{\\partial x_j}|_{T,V,x_k}$$\n",
|
|
"\n",
|
|
"$$ \\frac{\\partial p}{\\partial x_j}|_{\\tau,\\delta,x_k} = \\rho R T (\\delta \\frac{\\partial}{\\partial x_j}[\\alpha_\\delta]_{\\tau, \\delta, x_k})$$"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Total equation is\n",
|
|
"\n",
|
|
"$$ \\frac{\\partial p}{\\partial x_j}|_{T,V,x_k} = \\rho R T \\left(\\delta \\frac{\\partial}{\\partial x_j}[\\alpha_\\delta]_{\\tau, \\delta, x_k}-\\frac{\\delta}{\\rho_r}(\\alpha_\\delta+\\delta \\alpha_{\\delta\\delta})\\frac{\\partial \\rho_r}{\\partial x_j}|_{T,V,x_k}\\right)$$"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"$$ p=\\rho R T(1+\\delta \\alpha_\\delta) $$\n",
|
|
"\n",
|
|
"$$ p=\\rho R T(1+\\frac{\\rho}{\\rho_r} \\alpha_\\delta) $$"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"$$ \\frac{\\partial p}{\\partial x_j}|_{T,V,x_k} = \\rho R T \\left(\\rho\\frac{-1}{\\rho_r^2}\\left(\\frac{\\partial \\rho_r}{\\partial x_j}\\right)_{x_{k\\neq j}}\\alpha_\\delta + \\frac{\\rho}{\\rho_r}\\left(\\frac{\\partial}{\\partial x_j}\\left(\\frac{\\partial \\alpha_r}{\\partial \\delta}_{\\tau,\\bar x}\\right)\\right)_{T,V,x_{k\\neq j}}\\right)$$\n",
|
|
"\n",
|
|
"$$ \\frac{\\partial p}{\\partial x_j}|_{T,V,x_k} = \\delta\\rho R T \\left(\\frac{-1}{\\rho_r}\\left(\\frac{\\partial \\rho_r}{\\partial x_j}\\right)_{x_{k\\neq j}}\\alpha_\\delta + \\left(\\frac{\\partial}{\\partial x_j}\\left(\\frac{\\partial \\alpha_r}{\\partial \\delta}_{\\tau,\\bar x}\\right)\\right)_{T,V,x_{k\\neq j}}\\right)$$"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"import numpy as np\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"import CoolProp.CoolProp as CP\n",
|
|
"%matplotlib inline"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"prompt_number": 1
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"p = np.linspace(1000, 12000, 100)\n",
|
|
"mix = 'REFPROP-MIX:Water[0.7]&Ethanol[0.3]'\n",
|
|
"rhoL = CP.Props('D','P',p,'Q',0,mix)\n",
|
|
"rhoV = CP.Props('D','P',p,'Q',1,mix)"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"prompt_number": 2
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"plt.plot(rhoL,p,rhoV,p)"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 3,
|
|
"text": [
|
|
"[<matplotlib.lines.Line2D at 0x5d5e350>,\n",
|
|
" <matplotlib.lines.Line2D at 0x5d5e530>]"
|
|
]
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"output_type": "display_data",
|
|
"png": 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cTNHUIh1FLSIho7gYrrrKnNRv0qTK96+Jml4wyNcexFXArcCnwFanbRowA3gD\nsyopB/ip89wup30XUAJMoGz4aQLwKlAPWMoPi0OFSieoVRxEJJTExMCCBdC3L1x5JVxxhe1E5xYq\n364/6EG8sOEFdh7dyewfzbYUSUTEd2+9BVOmwObNcOGFgfmMiL3kaMaRDM0/iEjI+slPYNgwc3yE\nWy9TGtIFotMlWsEkIqHrqafg2DF44gnbSSpWk1VM1pz1nGXnkZ381yX/ZTuKiIjPYmLgzTehZ0/o\n1s2cJtxNQrIHkXsil7i6cVxYL0ADdyIiQZKUZIrEHXfA7t2203xfSBYIDS+JSDi58kozzHTTTVBY\naDtNmdAsEAUZGl4SkbAybpwpELfcYo6VcIPQLBDqQYhIGHrqKXNN61/8AjwBPVFR1YRkgdhxZIfO\nwSQiYad2bZg3D3buhN/+1naaEFzFVHymmOzj2bS/uL3tKCIiftegAbz7rjkdR2IijB9vL0vIFYjd\nX+wmOT6ZutF1bUcREQmIxERzWvD+/c1ZYEeOtJMj5ApExhFNUItI+GvVCpYtg+uvh3r1zFHXwRZy\ncxA7juzQBLWIRITOnc1w0113QVqVTmPqXyFXINSDEJFI0rMnLFoEY8bA0qXB/eyQKxDqQYhIpOnb\n11xgaOxYUyyCJaQKxJmzZ+japCutLmxlO4qISFD17m3mJII51BSy14MQEZHzi9jrQYiISGCpQIiI\nSIVUIEREpEIqECIiUiEVCBERqZAKhIiIVEgFQkREKqQCISIiFVKBEBGRCqlAiIhIhVQgRESkQioQ\nIiJSIbcUiMFAJrAXeNhyFhERwR0FojbwIqZIdARGAx2sJvJRenq67QhVopz+FQo5QyEjKKfbuKFA\n9AKygBzgNLAAGG4zkK9C5X8a5fSvUMgZChlBOd3GDQWiGXDQ63Ge0yYiIha5oUDoSkAiIi7khivK\n9QGmY+YgAKYBZ4EnvfbJAloHN5aISMjLBtrYDlET0ZgfIhmIAbYRopPUIiLif0OA3ZiewjTLWURE\nREREJJS55SC6V4ACIMOrLQH4ANgDLAfivZ6bhsmcCQwKUkaAFsAqYCewA5jktLsta11gA2ZIcRfw\nhEtzlqoNbAWWOI/dmDMH+BSTc6PT5rac8cBbwGeY/+69XZjxMszvsPRWhPl35LacpZ+7E/O9NA+4\nwKU5A6I2ZtgpGaiD3fmJ/kA3vl8gngKmONsPAzOc7Y6YrHUw2bMI3oqxJkBXZzsWM3TXwaVZ6zv3\n0cB6oJ8jH6UEAAACzklEQVRLcwL8Evg/YLHz2I0592O+HLy5Ledc4E5nOxqIc2FGb7WAzzF/eLkt\nZzKwD1MUAP4J3O7CnAHTF0jzejzVudmSzPcLRCaQ6Gw3cR6DqdLevZ00zGotGxYC1+HurPWBT4DL\ncWfO5sAKYABlPQg35twPXFSuzU054zBfaOW5KWN5g4CPnG235UzA/AF4IabYLgGu92dOt1cPtx9E\nl4gZdsK5L/2PkoTJWspW7mRMr2cD7sxaC/MXTQFlw2JuzPks8BBm+XUpN+b0YArZJuDnTpubcqYA\nR4G/A1uAvwINXJaxvFHAfGfbbTkLgT8BB4BDwAnM0JLfcrq9QITSQXQezp832D9LLPA2MBn4TwVZ\n3JD1LGY4rDlwNeYv9PI5bOf8EXAEMxZ9ruOG3JAT4CrMHwRDgHsxw6Llc9jMGQ10B2Y691/xwxEB\n2xm9xQA3AW+eI4ftnK2B+zF/CCZh/s3fWkEOn3O6vUDkY8b+SrXg+xXQtgJMFw6gKeaLBH6Yu7nT\nFix1MMXhdcwQE7g3K5hJwPeAHrgv55XAMMzwzXzgWszv1W05wYyVg/kr/V+Y85y5KWeec/vEefwW\nplAcdlFGb0OAzZjfJ7jrdwlwBbAWOAaUAO9ghuXd+vv0O7cdRJfMDyepS8f0pvLDyaAYTLc6m+Ad\ntR4FvIYZFvHmtqwXU7a6oh6wBhjowpzerqFsDsJtOesDDZ3tBsC/MePnbsu5BmjnbE938rktY6kF\nmEnfUm7L2QWzUrGe83lzMT1Ht+UMKLccRDcfM85XjJkXGYuZJFpBxcvJfo3JnAncEMSc/TBDN9so\nW6Y32IVZO2HGobdhlmY+5LS7Lae3ayhbxeS2nCmY3+U2zJdG6b8Vt+XsgulBbMf8xRvnwoxgiuwX\nlBVdcGfOKZQtc52LGT1wY04REREREREREREREREREREREREREREREREREZHg+3+dbWZKGhzUjgAA\nAABJRU5ErkJggg==\n",
|
|
"text": [
|
|
"<matplotlib.figure.Figure at 0x37ea9f0>"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 3
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"prompt_number": 3
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"K_i=\\frac{y_i}{x_i}"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {}
|
|
}
|
|
]
|
|
} |