Force dtmin and cap maxiters on oval2 qmax sweep

Stops the hard trajectories grinding near dtmin, so the sweep completes with 0 fails instead of stalling.

Author: jitendravjh

benchmarks/AdaptiveSDE/qmaxDetermination.jmd

@@ -39,8 +39,6 @@ println("Setup Complete")
 
 ## Timing Runs
 
-# Multithreaded ensemble over the Oval2 model; each trajectory gets its own seed
-# so the runs are independent and reproducible across qmax values.
 oval2_ensemble = EnsembleProblem(prob, prob_func = (p, ctx) -> remake(p, seed = ctx.sim_id))
 
 #Compile
@@ -58,7 +56,8 @@ for k in eachindex(qs)
     Random.seed!(99)
     adaptiveTime = @elapsed sol = solve(oval2_ensemble, SOSRI(), EnsembleThreads();
         dt = 1/2^(8), abstol = 2.0^(-15), reltol = 2.0^(-10), verbose = SciMLLogging.None(),
-        maxiters = Int(1e12), controller = PIController(SOSRI(); qmax = qs[k], gamma = 0.7),
+        maxiters = Int(1e6), force_dtmin = true,
+        controller = PIController(SOSRI(); qmax = qs[k], gamma = 0.7),
         trajectories = num_runs)
     numFails = sum(Int(any(isnan, sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:num_runs)
     println("k was $k. The number of Adaptive Fails is $numFails. Elapsed time was $adaptiveTime")