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49 | 49 |
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50 | 50 | # Electrolyte properties
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51 | 51 | c_e_typ = pybamm.Parameter("Typical electrolyte concentration [mol.m-3]")
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52 |
| -t_plus = pybamm.Parameter("Cation transference number") |
53 | 52 | V_w = pybamm.Parameter("Partial molar volume of water [m3.mol-1]")
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54 | 53 | V_plus = pybamm.Parameter("Partial molar volume of cations [m3.mol-1]")
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55 | 54 | V_minus = pybamm.Parameter("Partial molar volume of anions [m3.mol-1]")
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171 | 170 | "2. Dimensional Functions"
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172 | 171 |
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173 | 172 |
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| 173 | +def t_plus(c_e): |
| 174 | + "Dimensionless transference number (i.e. c_e is dimensional)" |
| 175 | + return pybamm.FunctionParameter("Cation transference number", c_e * c_e_typ) |
| 176 | + |
| 177 | + |
174 | 178 | def D_e_dimensional(c_e, T):
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175 | 179 | "Dimensional diffusivity in electrolyte"
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176 | 180 | return pybamm.FunctionParameter("Electrolyte diffusivity [m2.s-1]", c_e)
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@@ -310,7 +314,7 @@ def U_p_dimensional(c_e, T):
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310 | 314 | centre_z_tab_p = pybamm.geometric_parameters.centre_z_tab_p
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311 | 315 |
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312 | 316 | # Diffusive kinematic relationship coefficient
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313 |
| -omega_i = c_e_typ * M_e / rho_typ * (t_plus + M_minus / M_e) |
| 317 | +omega_i = c_e_typ * M_e / rho_typ * (t_plus(1) + M_minus / M_e) |
314 | 318 | # Migrative kinematic relationship coefficient (electrolyte)
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315 | 319 | omega_c_e = c_e_typ * M_e / rho_typ * (1 - M_w * V_e / V_w * M_e)
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316 | 320 | C_e = tau_diffusion_e / tau_discharge
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@@ -347,12 +351,10 @@ def U_p_dimensional(c_e, T):
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347 | 351 | # Main
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348 | 352 | s_plus_n_S = s_plus_n_S_dim / ne_n_S
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349 | 353 | s_plus_p_S = s_plus_p_S_dim / ne_p_S
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350 |
| -s_n = -(s_plus_n_S + t_plus) # Dimensionless rection rate (neg) |
351 |
| -s_p = -(s_plus_p_S + t_plus) # Dimensionless rection rate (pos) |
352 |
| -s = pybamm.Concatenation( |
353 |
| - pybamm.FullBroadcast(s_n, ["negative electrode"], "current collector"), |
| 354 | +s_plus_S = pybamm.Concatenation( |
| 355 | + pybamm.FullBroadcast(s_plus_n_S, ["negative electrode"], "current collector"), |
354 | 356 | pybamm.FullBroadcast(0, ["separator"], "current collector"),
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355 |
| - pybamm.FullBroadcast(s_p, ["positive electrode"], "current collector"), |
| 357 | + pybamm.FullBroadcast(s_plus_p_S, ["positive electrode"], "current collector"), |
356 | 358 | )
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357 | 359 | j0_n_S_ref = j0_n_S_ref_dimensional / interfacial_current_scale_n
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358 | 360 | j0_p_S_ref = j0_p_S_ref_dimensional / interfacial_current_scale_p
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@@ -407,7 +409,9 @@ def U_p_dimensional(c_e, T):
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407 | 409 | ) / potential_scale
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408 | 410 |
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409 | 411 | # Electrolyte volumetric capacity
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410 |
| -Q_e_max = (l_n * eps_n_max + l_s * eps_s_max + l_p * eps_p_max) / (s_p - s_n) |
| 412 | +Q_e_max = (l_n * eps_n_max + l_s * eps_s_max + l_p * eps_p_max) / ( |
| 413 | + s_plus_n_S - s_plus_p_S |
| 414 | +) |
411 | 415 | Q_e_max_dimensional = Q_e_max * c_e_typ * F
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412 | 416 | capacity = Q_e_max_dimensional * n_electrodes_parallel * A_cs * L_x
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413 | 417 |
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@@ -490,7 +494,7 @@ def kappa_e(c_e, T):
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490 | 494 | def chi(c_e, c_ox=0, c_hy=0):
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491 | 495 | return (
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492 | 496 | chi_dimensional(c_e_typ * c_e)
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493 |
| - * (2 * (1 - t_plus)) |
| 497 | + * (2 * (1 - t_plus(c_e))) |
494 | 498 | / (V_w * c_T(c_e_typ * c_e, c_e_typ * c_ox, c_e_typ * c_hy))
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495 | 499 | )
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496 | 500 |
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