Dynamic Simulation

Learn to set up and run time-varying simulations to analyze plant performance under changing conditions such as flow variations, storm events, and process upsets.

Overview

Dynamic simulation models how a wastewater treatment plant responds to time-varying inputs and conditions. Unlike steady-state simulation (which assumes constant conditions), dynamic simulation tracks changes over hours, days, or weeks.

In this guide you'll learn:

• Differences between steady-state and dynamic simulation
• Time-step selection and integration methods
• Configuring dynamic influent patterns
• Importing time-series data
• Controller integration for automated response
• Analyzing temporal results
• Simulating specific events (storms, upsets, startups)

Estimated Time: 45 minutes

Difficulty: Advanced

Prerequisites

• Completed Running-Simulations (steady-state)
• Understanding of First-Simulation
• Familiarity with Building-Process-Diagrams
• Basic knowledge of wastewater treatment dynamics
• Time-series data (optional, but helpful)

Step 1: Dynamic vs Steady-State

1.1 When to Use Dynamic Simulation

Use steady-state simulation when:

• Analyzing average long-term performance
• Comparing design alternatives
• Sizing process units
• Checking permit compliance under typical conditions
• Initial feasibility studies

Use dynamic simulation when:

• Analyzing wet weather/storm events
• Evaluating process control strategies
• Studying startup/shutdown procedures
• Assessing peak loading impacts
• Optimizing equalization basin operations
• Validating tank sizing for fluctuating loads
• Analyzing diurnal (daily) load variations

Tip: Start with steady-state to ensure your configuration is correct, then add dynamics for detailed analysis.

1.2 Key Differences

Aspect	Steady-State	Dynamic
Time	Single point in time	Time-series over hours/days
Inputs	Constant values	Time-varying profiles
Outputs	Single set of results	Temporal profiles
Computation	Algebraic equations	Differential equations
Solve Time	Seconds to minutes	Minutes to hours
Use Case	Design, avg performance	Operations, control, events

1.3 Dynamic Simulation Concepts

State Variables: Values that change over time

• Biomass concentrations
• Substrate concentrations
• Dissolved oxygen
• Tank volumes (for variable volume tanks)

Time Integration: Methods to solve differential equations

• Euler: Simple, fast, less accurate
• Runge-Kutta 4: Balanced accuracy and speed (recommended)
• Rosenbrock: Stiff systems, high accuracy

Time Step: Interval between calculations

• Smaller steps = more accurate, slower
• Larger steps = faster, may miss dynamics
• Typical: 2-15 minutes for most applications

Note: ErgoPlanner uses adaptive time-stepping by default to balance accuracy and performance.

Step 2: Create Dynamic Simulation Project

2.1 Start from Existing Project

The easiest way to set up dynamic simulation:

1. Create and configure a steady-state project first (see Creating-Projects)
2. Run steady-state simulation successfully
3. Use steady-state results as initial conditions for dynamic run

Why? Steady-state provides realistic initial concentrations and flows. Starting dynamic "cold" (from zero) requires long equilibration time.

2.2 Configure for Dynamic Simulation

1. Open your configured project
2. Click "Run Simulation" in the toolbar
3. Select "Dynamic" as simulation type
4. The interface will update to show dynamic-specific options

Screenshot placeholder: Run Simulation dialog with "Dynamic" radio button selected, showing additional time-related configuration options.

2.3 Set Simulation Duration

Configure the time period to simulate:

Parameter	Typical Value	Range	Use Case
Duration	7 days	6 hours - 30 days	Length of simulation
Time Step	5 minutes	1-30 minutes	Calculation interval
Output Interval	15 minutes	5-60 minutes	Results saving frequency

Example Configurations:

Storm Event:

• Duration: 24-48 hours
• Time Step: 2-5 minutes
• Output Interval: 10 minutes

Diurnal Cycle:

• Duration: 7 days
• Time Step: 5-10 minutes
• Output Interval: 30 minutes

Plant Startup:

• Duration: 14-30 days
• Time Step: 15-30 minutes
• Output Interval: 2 hours

Tip: Shorter time steps increase accuracy but also computation time. Start with default (5 min) and adjust if needed.

Screenshot placeholder: Dynamic simulation configuration panel showing Duration: 7 days, Time Step: 5 min, Output Interval: 15 min.

Step 3: Configure Dynamic Influent

The key to dynamic simulation is time-varying influent conditions.

3.1 Influent Pattern Types

ErgoPlanner supports several influent pattern types:

1. Diurnal Pattern - Daily repeating pattern (typical day)
2. Storm Event - Wet weather hydrograph
3. Custom Time-Series - Import from CSV file
4. Synthesized Pattern - Generate from parameters

3.2 Configure Diurnal Pattern

Most WWTPs experience daily flow and load patterns:

1. Click on the Influent stream
2. In properties panel, click "Dynamic Configuration"
3. Select "Diurnal Pattern"
4. Configure the pattern:

Typical Municipal Diurnal Pattern:

Time of Day	Flow Multiplier	COD Multiplier	TKN Multiplier
00:00 - 06:00	0.6	0.5	0.5
06:00 - 09:00	1.4	1.3	1.4
09:00 - 12:00	1.2	1.1	1.2
12:00 - 15:00	1.1	1.0	1.1
15:00 - 18:00	1.0	0.9	1.0
18:00 - 21:00	1.3	1.2	1.3
21:00 - 24:00	0.8	0.7	0.8

Base flow: 10,000 m³/day Base COD: 500 mg/L Base TKN: 40 mg/L

The multipliers are applied to base values at each time.

Tip: Peak flows typically occur during morning hours (6-9 AM) when domestic water use is highest.

Screenshot placeholder: Diurnal pattern configuration showing time-of-day table with flow and concentration multipliers. Graph preview shows flow pattern over 24 hours.

3.3 Configure Storm Event

For wet weather analysis:

1. Select "Storm Event" pattern type
2. Choose storm characteristics:

Parameter	Value	Description
Storm Type	Design Storm	Type of event
Return Period	10 years	Frequency (2, 5, 10, 25, 50, 100 yr)
Duration	6 hours	Length of storm
Peak Intensity	50 mm/hr	Maximum rainfall rate
Pattern	SCS Type II	Temporal distribution

3. Configure I&I (Inflow & Infiltration):

Parameter	Value	Unit
I&I Coefficient	2.5	-
Response Time	2	hours
Decay Time	12	hours

The resulting hydrograph shows:

• Pre-storm base flow: 10,000 m³/day
• Peak flow: 45,000 m³/day (4.5x base)
• Duration of peak: ~8 hours total
• Return to base: ~18 hours after storm start

Warning: Ensure your process units can handle peak flows. Check clarifier overflow rates and tank volumes.

Screenshot placeholder: Storm event configuration dialog with parameters above. Preview graph shows flow hydrograph with steep rise to peak and gradual recession.

3.4 Import Time-Series Data

For actual plant data or custom patterns:

1. Select "Import Time-Series"
2. Click "Choose File"
3. Select CSV file with this format:

Time,Flow_m3d,COD_mgL,BOD_mgL,TSS_mgL,TKN_mgL,NH4N_mgL,TP_mgL,Temp_C
0,8500,450,220,280,38,22,7.5,19.5
15,8800,460,225,285,39,23,7.6,19.6
30,9200,475,230,290,40,24,7.7,19.8
45,9800,490,240,300,41,25,7.8,20.0
60,10500,510,250,310,42,26,7.9,20.1
...

CSV Format Requirements:

• First column: Time in minutes from start
• Header row: Parameter names with units
• Data rows: Numeric values

4. Click "Import and Validate"
5. Preview shows the imported data graphically
6. Click "Apply"

Tip: You can export data from SCADA systems, lab databases, or Excel to create input files.

Screenshot placeholder: Import time-series dialog showing file upload area and preview graph of imported flow and COD data over time.

Step 4: Configure Process Units for Dynamics

Some process units need additional dynamic configuration.

4.1 Reactor Initial Conditions

Set starting concentrations for reactors:

1. Click on Aeration Tank
2. Navigate to "Dynamic" tab in properties
3. Choose initial condition source:

Option 1: From Steady-State

• Use results from previous steady-state run
• Recommended - provides realistic starting point

Option 2: Manual Entry

• Enter concentrations manually
• Use when steady-state not available

Option 3: Default Values

• Use typical values from literature
• Requires long equilibration period

Component	Default	Typical Range
X_H (heterotrophs)	1,800	1,000-3,000 mg COD/L
X_A (autotrophs)	80	20-150 mg COD/L
S_S (substrate)	2	1-10 mg COD/L
S_O (oxygen)	2.0	0-8 mg/L
S_NO (nitrate)	0	0-20 mg N/L
S_NH (ammonia)	1	0-5 mg N/L

Tip: Always use "From Steady-State" if possible. It eliminates equilibration time.

Screenshot placeholder: Reactor dynamic configuration tab showing "Initial Conditions" dropdown set to "From Steady-State" with preview of concentrations.

4.2 Clarifier Dynamic Settings

Secondary clarifiers have settling dynamics:

1. Click on Secondary Clarifier
2. Dynamic tab → Settling Model: Takács (dynamic)
3. Configure layers:

Parameter	Value	Description
Number of Layers	10	Vertical discretization
Hindered Settling	Enabled	Accounts for concentration effects
Compression	Enabled	Bottom sludge thickening

Note: More layers = more accurate but slower. 10 layers is typically adequate.

4.3 Controller Settings

Controllers respond dynamically to process changes:

1. Click on DO Controller (if present)
2. Configure PID parameters:

Parameter	Typical Value	Range
Setpoint	2.0 mg/L	1.0-4.0
Kp (proportional)	10	1-50
Ki (integral)	0.5	0.1-2.0
Kd (derivative)	1.0	0-5.0
Sample Time	5 min	1-15 min

See Controller-Setup for detailed controller configuration.

Tip: Conservative controller tuning (lower gains) prevents oscillations during dynamic runs.

Screenshot placeholder: PID controller configuration panel showing setpoint, Kp, Ki, Kd parameters with sample time setting.

Step 5: Advanced Dynamic Settings

5.1 Integration Method Selection

Choose the numerical integration method:

Method	Accuracy	Speed	Best For
Euler	Low	Fast	Quick checks, stable systems
RK4	High	Medium	Most applications (recommended)
Rosenbrock	Very High	Slow	Stiff systems, high accuracy needs

Recommended: Start with RK4. Switch to Rosenbrock if you encounter:

• Numerical instability
• Concentration oscillations
• Solver crashes

5.2 Adaptive Time-Stepping

Enable for automatic time step adjustment:

1. Check ☑ "Enable Adaptive Time-Stepping"
2. Configure parameters:

Parameter	Value	Description
Min Time Step	0.5 min	Smallest allowed step
Max Time Step	15 min	Largest allowed step
Target Error	1e-4	Error tolerance
Max Step Increase	2.0x	Maximum step size growth

Adaptive stepping:

• Reduces step size during rapid changes (storms, control actions)
• Increases step size during stable periods
• Improves both accuracy and performance

Tip: Adaptive stepping can reduce simulation time by 30-50% without sacrificing accuracy.

5.3 Output Configuration

Control how results are saved:

Setting	Value	Impact
Output Interval	15 min	How often to save results
Save All State Variables	No	Disk space vs detail
Compress Output	Yes	Reduce file size

Example file sizes (7-day simulation):

• Output every 5 min, all variables: ~500 MB
• Output every 15 min, key variables only: ~50 MB
• Output every 30 min, key variables: ~25 MB

Warning: Saving every time step for long simulations generates huge files. Use output interval wisely.

Screenshot placeholder: Advanced dynamic settings showing integration method dropdown (RK4 selected) and adaptive time-stepping configuration.

Step 6: Run Dynamic Simulation

6.1 Pre-Flight Check

Before running, verify:

• ✓ Steady-state simulation successful (for initial conditions)
• ✓ Dynamic influent configured
• ✓ Simulation duration appropriate for analysis
• ✓ Time step selected (5-10 min recommended)
• ✓ Output interval set
• ✓ Sufficient disk space for results

6.2 Start Simulation

1. Review all settings in the Run Simulation dialog
2. Click "Start Dynamic Simulation"
3. Progress dialog appears showing:
   • Current simulation time (e.g., "Day 2, 14:30")
   • Progress bar (% complete)
   • Elapsed real time
   • Estimated time remaining

Screenshot placeholder: Dynamic simulation progress dialog showing "Simulating: Day 2 14:30 / 7 days (35% complete)", progress bar, elapsed time: 8:23, estimated remaining: 15:12.

6.3 Monitor During Simulation

The progress dialog shows real-time monitoring:

Key Indicators (updated every 10 steps):

• Current time in simulation
• Solver status (Integrating / Adjusting Step / Converged)
• Active time step size
• Average iterations per step
• Warning/error count

Common Progress Indicators:

• "Integrating steadily" - Normal operation
• "Reducing time step" - Handling rapid changes (expected during storms)
• "Increasing time step" - Stable period, speeding up

Tip: Dynamic simulations take longer than steady-state. A 7-day simulation may take 10-30 minutes of real time.

6.4 Pause and Resume

You can pause long simulations:

1. Click "Pause" in progress dialog
2. Simulation pauses at next time step
3. Click "Resume" to continue
4. Or click "Stop and Save" to end early

Results are saved up to the paused time.

Note: You can close your browser and the simulation continues on the server (for server deployments). Check simulation status from Projects page.

Step 7: Analyze Dynamic Results

7.1 Results Dashboard

When simulation completes, the Results page shows dynamic-specific views:

Available Views:

1. Time-Series Charts - Parameter vs time graphs
2. Animations - Animated flow through process
3. Snapshots - Results at specific times
4. Statistics - Min/max/average over simulation
5. Mass Balance - Time-integrated balances

Screenshot placeholder: Dynamic results dashboard with time-series chart showing effluent NH4-N varying over 7 days, with tabs for different view types.

7.2 Time-Series Charts

View how parameters change over time:

1. Select "Time-Series" tab
2. Choose location (e.g., "Effluent", "Aeration Tank")
3. Select parameters to plot:
   • ☑ Flow
   • ☑ COD
   • ☑ NH₄-N
   • ☐ NO₃-N
   • ☑ TSS

The chart displays all selected parameters with dual Y-axes if units differ.

Interactive Features:

• Zoom: Click and drag to zoom in
• Pan: Shift+drag to pan
• Cursor: Hover to see exact values
• Export: Save chart as PNG or SVG

Tip: Look for patterns like diurnal cycles, storm response, and equilibration periods.

Screenshot placeholder: Time-series chart showing multiple parameters over 7 days. Flow (blue) shows daily peaks, NH4-N (red) shows slight variation following flow pattern.

7.3 Storm Event Analysis

For storm simulations, analyze:

During Storm (first 12 hours):

• Peak flow rate and duration
• Washout of solids from clarifier
• DO drop in aeration (dilution effect)
• Effluent quality degradation

After Storm (12-48 hours):

• Return to normal concentrations
• Time to recover effluent quality
• Temporary nutrient accumulation

Example Storm Results:

Parameter	Pre-Storm	Peak Storm	24h Post	Permit Limit
Effluent NH₄-N	0.8 mg/L	15.2 mg/L	1.2 mg/L	2.0 mg/L
Effluent TSS	10 mg/L	48 mg/L	12 mg/L	30 mg/L
MLSS	3,500 mg/L	2,100 mg/L	3,200 mg/L	-
DO	2.0 mg/L	3.8 mg/L	2.1 mg/L	-

Interpretation:

• ✓ NH₄-N recovers quickly, stays within permit
• ✗ TSS exceeds limit during storm (peak 48 mg/L > 30 mg/L)
• MLSS diluted by 40% during peak flow
• DO increased due to reduced oxygen demand (dilution)

Action Items:

• Consider flow equalization to dampen peaks
• Evaluate clarifier capacity under wet weather
• Implement bypass treatment for extreme events

7.4 Diurnal Pattern Analysis

For diurnal simulations, check:

Pattern Stabilization:

• First 1-2 days: System equilibrates to dynamic pattern
• Days 3-7: Steady repeating diurnal cycle

Daily Variation:

• Identify minimum effluent quality time (usually morning)
• Quantify range of variation (e.g., NH₄-N: 0.5-1.5 mg/L)
• Verify all times stay within permits

Example Diurnal Results (Day 5):

Time	Influent Flow	Effluent NH₄-N	Effluent TSS	DO
00:00	6,000 m³/d	0.6 mg/L	8 mg/L	2.5 mg/L
06:00	14,000 m³/d	1.2 mg/L	12 mg/L	1.8 mg/L
12:00	11,000 m³/d	1.0 mg/L	10 mg/L	2.0 mg/L
18:00	13,000 m³/d	1.1 mg/L	11 mg/L	1.9 mg/L

All values repeat daily after Day 3, indicating stable operation.

Tip: Export Day 5-7 data only to focus on stabilized behavior and exclude equilibration period.

7.5 Statistics Summary

View summary statistics across the entire simulation:

Parameter	Min	Max	Mean	Std Dev	95th %
Effluent BOD₅	5.2	12.8	8.1	1.4	10.6
Effluent TSS	7.5	18.3	11.2	2.1	14.8
Effluent NH₄-N	0.4	1.8	0.9	0.3	1.4
MLSS	3,200	3,750	3,480	95	3,650
DO	1.5	2.8	2.0	0.2	2.3

Permit Compliance Check:

• 95th percentile values indicate worst-case normal operation
• All 95th percentile values should be < permit limits
• Maximum values may exceed limits briefly during upsets (check permit averaging period)

Screenshot placeholder: Statistics summary table showing min/max/mean/stdev for all effluent parameters, with permit limits column for comparison.

Step 8: Compare Scenarios

8.1 Run Multiple Scenarios

To compare control strategies or design alternatives:

1. Create base project with dynamic configuration
2. Run base case dynamic simulation
3. Duplicate project (File → Duplicate)
4. Modify scenario (e.g., add controller, increase volume)
5. Run modified scenario
6. Compare results side-by-side

Example Comparison: With vs Without DO Control

Screenshot placeholder: Side-by-side time-series charts comparing two scenarios: "Base Case" (red) and "With DO Control" (blue) showing effluent NH4-N over time.

8.2 Scenario Comparison Results

Metric	Base Case	With DO Control	Improvement
Avg NH₄-N	1.2 mg/L	0.6 mg/L	50% reduction
Max NH₄-N	2.8 mg/L	1.4 mg/L	50% reduction
Avg DO	2.0 mg/L	2.1 mg/L	Maintained
Energy Use	1,850 kWh/d	1,780 kWh/d	3.8% savings

Conclusion: DO control improves effluent quality AND reduces energy.

Step 9: Export Dynamic Results

9.1 Export Time-Series Data

Export to CSV for detailed analysis:

1. Click "Export" → "Time-Series CSV"
2. Select time range:
   • ○ Full simulation
   • ● Days 3-7 (exclude equilibration)
   • ○ Custom range
3. Select parameters:
   • ☑ All effluent parameters
   • ☑ Reactor concentrations
   • ☐ Intermediate streams
4. Click "Export"

Output: CSV file with columns:

Time_days,Flow_m3d,COD_mgL,BOD_mgL,NH4N_mgL,TSS_mgL,MLSS_mgL,DO_mgL
3.00,10200,125,8.2,0.7,10.5,3520,2.0
3.01,10350,128,8.4,0.8,10.8,3515,1.9
...

Use this data in Excel, Python, MATLAB, or R for advanced analysis.

9.2 Generate Dynamic Report

Create PDF report with dynamic results:

1. Click "Export" → "PDF Report"
2. Select report template: "Dynamic Simulation Report"
3. Configure report sections:
   • ☑ Executive Summary
   • ☑ Time-Series Charts (key parameters)
   • ☑ Statistical Summary
   • ☑ Event Analysis (storms, upsets)
   • ☑ Mass Balance
   • ☐ Full Time-Series Data Tables (can be very long)
4. Click "Generate"

Report includes:

• Project description and configuration
• Influent pattern description
• Key time-series charts (flow, effluent quality, reactor conditions)
• Statistical tables
• Permit compliance summary
• Conclusions and recommendations

Tip: Generate separate reports for different stakeholders: detailed for engineers, summary for management.

Screenshot placeholder: PDF report preview showing executive summary page with time-series charts and statistical table.

Step 10: Advanced Topics

10.1 Plant Startup Simulation

Simulate bringing new plant online:

Configuration:

• Duration: 30 days
• Initial conditions: Empty tanks, no biomass
• Seeding: Day 1, add seed sludge (200 mg/L)
• Influent: Gradually increase from 50% to 100% over 7 days

Track:

• Biomass growth (X_H, X_A)
• Effluent quality improvement over time
• Time to reach steady-state performance

Typical Results:

• Day 1-7: Biomass acclimation, poor effluent
• Day 7-14: Rapid biomass growth
• Day 14-21: Nitrification establishment
• Day 21-30: Stabilization at full performance

10.2 Process Upset Analysis

Simulate upsets to test resilience:

Toxic Shock:

• Inject high concentration toxic substance at specific time
• Observe biomass inhibition and recovery
• Estimate recovery time

Power Outage:

• Set DO = 0 for specified period
• Watch denitrification and sulfide production
• Analyze return to aerobic operation

Pump Failure:

• Stop RAS pump for period
• Observe solids accumulation in clarifier
• Check if system recovers or fails

Warning: These scenarios may cause simulation instability. Save project before attempting.

10.3 Seasonal Variation

Simulate annual temperature variation:

Temperature Profile:

Time_days,Temp_C
0,8
30,9
60,12
90,15
120,18
150,21
180,22
210,21
240,18
270,14
300,10
330,8

Effects to Observe:

• Winter: Slower kinetics, poorer nitrification
• Summer: Faster kinetics, potential DO limitation
• Spring/Fall: Transition periods

Analysis:

• Identify worst-case season for effluent quality
• Size equipment for most challenging conditions
• Plan operational adjustments (SRT, DO) seasonally

Summary

You've learned to:

• ✓ Understand when to use dynamic vs steady-state simulation
• ✓ Configure time-varying influent patterns (diurnal, storm, custom)
• ✓ Set up process units for dynamic operation
• ✓ Select integration methods and time steps
• ✓ Run dynamic simulations and monitor progress
• ✓ Analyze time-series results and statistics
• ✓ Compare scenarios to evaluate alternatives
• ✓ Export dynamic data and generate reports
• ✓ Simulate special events (storms, upsets, startup)

Common Issues

Issue	Cause	Solution
Simulation crashes early	Initial conditions unrealistic	Use steady-state results for initial conditions
Results oscillate	Time step too large	Reduce time step to 2-5 min
Very slow simulation	Time step too small	Increase time step or enable adaptive stepping
Concentrations go negative	Numerical instability	Switch to Rosenbrock integrator, reduce time step
No diurnal pattern visible	Simulation too short	Run at least 3-5 days to see pattern stabilize
Huge result files	Saving too frequently	Increase output interval to 15-30 min

For more troubleshooting, see Troubleshooting.

Next Steps

Continue your learning with advanced topics:

• Controller-Setup - Implement PID control for dynamic response
• Multi-Scenario - Advanced scenario comparison techniques
• Model-Calibration - Calibrate dynamic models to plant data
• Analyzing-Results - Advanced results interpretation
• Exporting-Data - Automation and batch export

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Related Topics:

• Running-Simulations - Steady-state simulation fundamentals
• Biokinetic-Models - Understanding model dynamics
• Performance-Tips - Optimize long simulations

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Last updated: December 2025Tutorial difficulty: AdvancedEstimated completion time: 45 minutes