Merge pull request #2398 from ReactionMechanismGenerator/correct_troe

Correct Troe kinetics formula

Author: hwpang

rmgpy/kinetics/falloff.pyx

@@ -148,7 +148,7 @@ cdef class Lindemann(PDepKineticsModel):
     `efficiencies`      A dict associating chemical species with associated efficiencies
     `comment`           Information about the model (e.g. its source)
     =================== ========================================================
-    
+
     """
 
     def __init__(self, arrheniusHigh=None, arrheniusLow=None, Tmin=None, Tmax=None, Pmin=None, Pmax=None,
@@ -255,7 +255,7 @@ cdef class Troe(PDepKineticsModel):
     `efficiencies`      A dict associating chemical species with associated efficiencies
     `comment`           Information about the model (e.g. its source)
     =================== ========================================================
-    
+
     """
 
     def __init__(self, arrheniusHigh=None, arrheniusLow=None, alpha=0.0, T3=None, T1=None, T2=None, Tmin=None,
@@ -347,7 +347,7 @@ cdef class Troe(PDepKineticsModel):
             d = 0.14
             n = 0.75 - 1.27 * log10(Fcent)
             c = -0.4 - 0.67 * log10(Fcent)
-            F = 10.0 ** (log10(Fcent) / (1 + ((log10(Pr) + c) / (n - d * (log10(Pr)))) ** 2))
+            F = 10.0 ** (log10(Fcent) / (1 + ((log10(Pr) + c) / (n - d * (log10(Pr) + c))) ** 2))
 
         return kinf * (Pr / (1 + Pr)) * F
 
@@ -397,7 +397,7 @@ cdef class Troe(PDepKineticsModel):
         T3 = self.T3.value_si
         T1 = self.T1.value_si
         if self.T2 is None:
-            ct_reaction.falloff = ct.TroeFalloff(params=[A, T3, T1]) 
+            ct_reaction.falloff = ct.TroeFalloff(params=[A, T3, T1])
         else:
             T2 = self.T2.value_si
             ct_reaction.falloff = ct.TroeFalloff(params=[A, T3, T1, T2])

rmgpy/kinetics/falloffTest.py

@@ -615,10 +615,10 @@ def test_get_rate_coefficient(self):
         Tlist = np.array([300, 500, 1000, 1500])
         Plist = np.array([1e4, 1e5, 1e6])
         Kexp = np.array([
-            [1.00866e+08, 2.03759e+08, 2.55190e+08],
-            [4.74623e+07, 1.41629e+08, 2.47597e+08],
-            [3.97397e+06, 2.89521e+07, 9.57569e+07],
-            [5.91277e+05, 5.14013e+06, 3.12239e+07],
+            [1.00648177e+08, 2.01999460e+08, 2.53938097e+08],
+            [4.71247326e+07, 1.41526885e+08, 2.45386923e+08],
+            [3.94987723e+06, 2.87338709e+07, 9.57539092e+07],
+            [5.88566395e+05, 5.10614193e+06, 3.10462030e+07],
         ])
         for t in range(Tlist.shape[0]):
             for p in range(Plist.shape[0]):