[1D/Examples] Use new default values for Jacobian and time stepping settings

These values were selected for optimal performance across a large set of flames
in each configuration and using mechanisms of various sizes to give good average
performance. It should not generally be necessary for users to change these
values.

interfaces/cython/cantera/examples/onedim/adiabatic_flame.py

@@ -32,8 +32,6 @@ f.show_solution()
 # Solve with the energy equation disabled
 f.energy_enabled = False
 f.transport_model = 'Mix'
-f.set_max_jac_age(10, 10)
-f.set_time_step(1e-5, [2, 5, 10, 20])
 f.solve(loglevel=loglevel, refine_grid=False)
 f.save('h2_adiabatic.xml', 'no_energy',
        'solution with the energy equation disabled')

interfaces/cython/cantera/examples/onedim/burner_flame.py

@@ -29,7 +29,6 @@ f.show_solution()
 
 f.energy_enabled = False
 f.transport_model = 'Mix'
-f.set_max_jac_age(10, 10)
 f.solve(loglevel, refine_grid=False)
 f.save('h2_burner_flame.xml', 'no_energy',
        'solution with the energy equation disabled')

interfaces/cython/cantera/examples/onedim/flame_fixed_T.py

@@ -58,8 +58,6 @@ f.energy_enabled = False
 # first solve the flame with mixture-averaged transport properties
 f.transport_model = 'Mix'
 f.set_refine_criteria(ratio=3.0, slope=0.3, curve=1)
-f.set_max_jac_age(50, 50)
-f.set_time_step(1.0e-5, [1, 2, 5, 10, 20])
 
 f.solve(loglevel, refine_grid)
 f.save('ch4_flame_fixed_T.xml','mixav',

interfaces/cython/cantera/examples/onedim/flamespeed_sensitivity.py

@@ -29,8 +29,6 @@ f.flame.set_transient_tolerances(default=tol_ts)
 
 # Solve with the energy equation disabled
 f.energy_enabled = False
-f.set_max_jac_age(10, 10)
-f.set_time_step(1e-5, [2, 5, 10, 20])
 f.solve(loglevel=1, refine_grid=False)
 
 # Solve with the energy equation enabled

interfaces/cython/cantera/test/test_onedim.py

@@ -157,8 +157,6 @@ class TestFreeFlame(utilities.CanteraTest):
     def solve_fixed_T(self):
         # Solve with the energy equation disabled
         self.sim.energy_enabled = False
-        self.sim.set_max_jac_age(50, 50)
-        self.sim.set_time_step(1e-5, [2, 5, 10, 20])
         self.sim.solve(loglevel=0, refine_grid=False)
 
         self.assertFalse(self.sim.energy_enabled)

src/oneD/OneDim.cpp

@@ -17,7 +17,7 @@ OneDim::OneDim()
       m_rdt(0.0), m_jac_ok(false),
       m_bw(0), m_size(0),
       m_init(false), m_pts(0), m_solve_time(0.0),
-      m_ss_jac_age(10), m_ts_jac_age(20),
+      m_ss_jac_age(20), m_ts_jac_age(20),
       m_interrupt(0), m_nevals(0), m_evaltime(0.0), m_nsteps(0),
       m_nsteps_max(500)
 {
@@ -29,7 +29,7 @@ OneDim::OneDim(vector<Domain1D*> domains) :
     m_rdt(0.0), m_jac_ok(false),
     m_bw(0), m_size(0),
     m_init(false), m_solve_time(0.0),
-    m_ss_jac_age(10), m_ts_jac_age(20),
+    m_ss_jac_age(20), m_ts_jac_age(20),
     m_interrupt(0), m_nevals(0), m_evaltime(0.0), m_nsteps(0),
     m_nsteps_max(500)
 {

src/oneD/Sim1D.cpp

@@ -28,7 +28,7 @@ Sim1D::Sim1D(vector<Domain1D*>& domains) :
 
     // set some defaults
     m_tstep = 1.0e-5;
-    m_steps = { 1, 2, 5, 10 };
+    m_steps = { 10 };
 }
 
 void Sim1D::setInitialGuess(const std::string& component, vector_fp& locs, vector_fp& vals)