1. Introduction
Akselos offers a powerful set of tools designed for comprehensive asset integrity management of Hydrocracking Unit (HCU) reactors. A critical aspect of reactor operation is managing the risk of brittle fracture during startup and shutdown phases, which is accomplished through a Minimum Pressurization Temperature (MPT) assessment.
The Advanced Analytics page's "What-if" simulation feature is designed for proactive and predictive asset management. It allows you to move beyond analyzing historical data and into the realm of forecasting by modeling the impact of hypothetical operating conditions.
This capability is essential for data-driven operational planning, risk assessment, and optimizing processes. Unlike the standard monitoring page which uses live sensor data, the "What-if" analysis is driven by user-defined hypothetical scenarios that you upload. This allows you to safely evaluate non-standard events and optimize procedures before they are ever implemented in the real world.
This tutorial is part of a larger documentation series. For more specific details, please refer to:
- User Manual
- Use Case: Akselos reactors wizards walkthrough
- Use Case: MPT Dashboard – What If Scenario? (this document)
- FAQs
1.1. Problem Statement and Objectives
This use case explores a hypothetical startup scenario in which the heat-up rate of the Hydrocracking Unit is slightly increased. By running a "What-if" simulation using the Advanced Analytics page, the user can assess the structural response of the asset under these modified conditions.
1.2. Before we start
Account and Access
To follow this use case, it is assumed that you already have an operational reactor model and an MPT dashboard deployed within your Akselos environment. This ensures that the What-if simulation can be performed using the appropriate tools and configurations. If you are unable to locate the model or access the dashboard, please contact your team supervisor or the Akselos support team for further guidance. Proper access is required to upload scenarios, view results, and interact with the Advanced Analytics interface throughout this workflow.
If you do not yet have an Akselos account, you can create one by following the articles below. Once your account is created, please check with your supervisor or contact the Akselos support team to request the necessary permissions.
- [Create Akselos Portal Account] – Required to access the platform and use the tool.
- [Akselos Portal for New Users] – Provides an overview of the platform’s features and interface.
Preparation and Downloads
To follow along with the hands-on steps in this use case, you will need to download the following files.
- Download link: [csv files]
2. Running What-If Scenarios
The "What-if" simulation feature enables users to model hypothetical operational conditions and assess their potential impact on asset performance. This supports data-driven decision-making by identifying unsafe conditions, exploring optimization opportunities, and preparing for non-routine events without exposing the physical asset to risk. By comparing outcomes from multiple scenarios, users can define a safe and efficient operating envelope.
Step 1: Create the Hypothetical Data Set
Before running a simulation, users must define the scenario in a properly structured CSV file. The What-if page connects to sensor data in the same way as the live monitoring page, using predefined sensor tags from the simulation model.
The file must follow this structure:
- Datetime column: The first column contains timestamps in chronological order, defining the simulation timeline.
- Sensor tag columns: Each subsequent column corresponds to a specific sensor tag (e.g., tag00000, tag00001, etc.). These tags are defined in the simulation model and must match exactly.
- Values: Each cell contains the measurement value for the corresponding tag at the given timestamp. The unit for each sensor value is determined by the configuration in the Simulation Modeler (see Use Case 1 for details).
The dataset should reflect the hypothetical conditions to be simulated. Once completed, the file should be saved locally for upload.
Figure 2.1: Example of sensor data in CSV format
Step 2: Upload and Run the Scenario from the Applet
Once the hypothetical dataset is prepared, it must be uploaded to the following directory in the Akselos Portal: Your_Organization/Your_Reactor_Collection/input_data
After the file is uploaded, it will appear in the What-if Analyzer Applet, where it can be selected and executed.
Key features of the What-if Analyzer Applet:
- Upload Files – Import a newly prepared dataset (CSV format).
- Download – Retrieve an existing dataset for review or modification.
- Sensor Data File – Select from the list of uploaded datasets to use for simulation.
To start the simulation, select the required CSV file from the list and click Run MPT – What-if Analyzer. The applet will then process the dataset using the predefined simulation model and display the results for comparison with other scenarios.
Figure 2.2: What-if Analyzer Applet
Step 3: Check the Report on the Dashboard
Simulation progress can be tracked via the Job Page, where users can view elapsed time, current execution step, and logs for troubleshooting.
Once completed, the results will be automatically published to the What-If Simulations tab under the Advanced Analytics page. The scenario can then be selected using the Scenario Selection dropdown.
Figure 2.3: What-if Simulations interface
Step 4: Execute Multiple Runs for Comparison
To further refine operational decisions, users can run additional simulations following the same steps. Multiple scenarios can be compared against each other and historical data to evaluate trends and identify optimal conditions.
Use the Advanced Analytics dashboard to:
- Select each scenario from the dropdown
- Compare trends in temperature, pressure, utilization, and other key indicators
This iterative process allows users to test variations and gain insight into safe operating limits.
Figure 2.4: Scenarios Selection panel
Selecting a scenario will reload the Dashboard Report to that specific case, and the user can further analyze the result using the features offered by the Dashboard Report.
3. Interpreting Results
Once a What-if Scenario has been executed, results can be viewed from the Advanced Analytics page under the What-if Simulations tab. The scenario can be selected using the Scenario Selection dropdown, allowing comparison between Live data and the hypothetical case. Below is a walkthrough of how one might interpret the results when evaluating a faster heat-up cycle for the HCU Reactor.
Location with Max UF
Locate the Max. Location panel on the dashboard. This panel identifies the location where the maximum utilization occurs for the selected scenario. Switching between the Live and hypothetical scenarios allows users to observe if the identified location changes.
Figure 3.1: Max. Location panel
In the hypothetical scenario, the location indicated in the Max. Location panel differs from that shown in the Live scenario. This difference can be confirmed by comparing the displayed location names in each case.
Figure 3.2: Comparing the location names in the Live and Hypothetical scenarios
Sensor Data
Find the Sensors Data chart, which displays either temperature or pressure readings from various sensor points. The chart’s legend lists each sensor tag, while the plotted lines show measured values over time.
Figure 3.3: Sensor data chart panel
When switching from the Live scenario to the hypothetical case, the plotted lines shift in position, indicating changes in the recorded data across sensors. These differences can be identified by comparing the values and line trends between the two scenarios.
Figure 3.4: Comparing the values line in the Live and Hypothetical scenarios
Heatup/ Cooldown rate
Locate the Heatup / Cooldown Rate chart on the dashboard. This chart visualizes the rate at which temperature changes over time during the start-up phase. By switching between the baseline (Live) and hypothetical scenarios using the dropdown selector, users can directly compare how the heat-up rate varies between cases.
Figure 3.5: Heatup/Cooldown rate panel
In the hypothetical scenario, the shape and slope of the plotted lines in the heat-up rate chart differ from those in the Live scenario. These changes can be seen by comparing the curves on both displays.
Figure 3.6: Comparing the values line in the Live and Hypothetical scenarios
Historical Utilization Factor
Next, locate the Utilization Factor (UF) chart. This metric reflects the stress margin utilization of the reactor’s critical regions. Similar to the heat-up rate analysis, toggle between scenarios to compare how the stress profile changes in response to the adjusted temperature curve.
Figure 3.7: Historical Utilization chart panel
Users can refine the view of the results by expanding the dropdown menu at the top of the chart. This allows switching from the default All view to a specific predefined zone, such as an individual MPT location or SCL region. This feature helps focus the analysis on particular areas of interest within the reactor.
Figure 3.8: Comparing the values line in the Live and Hypothetical scenarios
In the hypothetical scenario, the plotted utilization curves differ from those in the Live scenario. These differences can be identified by comparing the positions and patterns of the lines between the two cases.
4. Final Thoughts
Thank you for following this Use Case Guide. We hope it has provided clear steps and practical insights for configuring, validating, and understanding the Reactor base models within the Structural Performance Management workflow. Please note that all settings, parameters, and configurations in this document are purely hypothetical and do not represent or duplicate any real-world asset. Any resemblance to actual equipment or operating conditions is entirely coincidental.
If you have any questions or require further assistance, contact our support team at [email protected]. For additional resources, updates, or to share feedback, please visit the Akselos Portal or reach out to your account representative.