Run a Simulation

Configure and execute simulations with custom parameters.

Time estimate: 15 minutes

Goal

By the end of this tutorial, you’ll be able to:

• Configure simulation time settings
• Modify initial conditions and parameters
• Monitor simulation progress
• Handle common simulation issues

Starting a Run

From any model detail page:

1. Click Run Simulation button
2. The run configuration panel opens
3. Configure settings (see below)
4. Click Start Run

Configuration Options

Time Settings

Initial Conditions

Override the default starting values for any species:

# Example
prey: 100 → 150
predator: 10 → 20

Click on any species to modify its initial value.

Parameter Overrides

Modify model parameters without editing the model:

# Example
alpha: 1.0 → 1.5
beta: 0.1 → 0.08

Monitoring Progress

After starting a run:

1. Status indicator shows current state:

   • 🟡 Queued
   • 🔵 Running
   • 🟢 Completed
   • 🔴 Failed

2. Progress bar shows completion percentage

3. Estimated time remaining (for longer simulations)

Run States

Handling Failures

Common Error: Numerical Instability

Symptoms: “Integration failed” or “NaN values”

Solutions:

• Reduce simulation duration
• Decrease output points
• Check for extreme parameter values
• Use a different integration method (if available)

Common Error: Timeout

Symptoms: “Simulation timed out”

Solutions:

• Reduce duration or complexity
• Break into smaller runs
• Contact support for long-running simulations

Common Error: Invalid Parameters

Symptoms: “Parameter out of bounds”

Solutions:

• Check parameter constraints in model documentation
• Reset to default values
• Use biologically reasonable values

Batch Runs

Run multiple simulations with different parameters:

1. From model page, click Parameter Sweep
2. Select parameter to vary
3. Define range: min, max, steps
4. Start batch

Results are collected and can be compared in the results viewer.

Best Practices

1. Start simple: Run with defaults first, then modify
2. Document changes: Note which parameters you changed
3. Save configurations: Bookmark configurations you use frequently
4. Compare systematically: Change one parameter at a time

Programmatic Runs

For automation, use the B-Simulant Library:

from bsim.adapters import TelluriumAdapter
 
# Load model and run simulation
adapter = TelluriumAdapter(model_path="model.sbml", parameters={"alpha": 1.5, "beta": 0.1})
adapter.setup({})
 
# Advance simulation
for t in range(0, 100, 1):
    adapter.advance_to(t)
    outputs = adapter.get_outputs()
    print(f"Time {t}: {outputs}")

The configuration varies by model standard:

• SBML: Use TelluriumAdapter with advance_to(...) and get_outputs()
• NeuroML: Use NeuroMLAdapter with advance_to(...) (ms)
• ONNX: Use MLAdapter with set_inputs(...), advance_to(...), and get_outputs()

See B-Simulant Library for full documentation.

Next Steps

• Analyze Results - Visualize your simulation
• B-Simulant Library - Automate simulations with Python