How to Find Overstressed Elements in FEA with Peak Finder

How Peak Finder Can Help You in this Workflow

The Peak Finder tool acts as a rule-based filter applied directly to your existing results. Instead of manually inspecting the contour plot, you define a condition and let the tool extract only the regions that match it. 

Here, the rule is simple and practical: 

• Source: From Load  
• Category: Stress  
• Direction: chosen stress direction/component  
• Threshold: ≥ 200 MPa  

Here, the threshold is simply the filter condition used to isolate relevant zones; it is not a built-in pass/fail limit. 

Image: Model with highlighted stress zones 

Once applied, Peak Finder scans the results and identifies all areas that meet this criterion. The output is not just a visual highlight; it is a structured set of peak zones that can be further analyzed. 

Each detected zone can be displayed with labels, element IDs, or stress values, depending on how you configure the output. These zones can also be organized into tables, making it easy to review and compare them. 

Beyond identification, Peak Finder enables deeper analysis by linking each zone to the loads that influence it. This allows you to generate tables and graphs showing load contribution, so you can clearly see which load cases are driving the peak results in each zone. 

If you need background on peak stress, singularities, and stress concentrations, see our earlier Peak Finder article. 

1) Start from a Contour Plot

The workflow begins with a standard stress contour plot based on your analysis results. In the demonstrated setup, the model includes a combination of beam and shell elements, which reflects a typical structural FEA scenario. 

The job itself contains multiple loading definitions, including: 

• five individual loads  
• five load sets  
• several load groups  

To review the results, you start by right-clicking the envelope load sets group and creating a contour plot. After selecting the appropriate result category and load group, the stress distribution is displayed. 

Image: The contour plot in SDC Verifier software 

At this stage, it is already clear that some stress values exceed 200 MPa. However, the contour plot alone does not provide enough clarity. The overstressed regions are visible, but they are embedded within the full model, making it difficult to isolate exactly which elements are responsible. 

This limitation is what drives the need for Peak Finder: transforming a general stress visualization into a focused view of only the critical zones.

2) Configure Peak Finder

Once you’ve identified that the contour plot alone is not enough, the next step is to add a Peak Finder tool that isolates only the relevant results. This is where the workflow becomes structured and repeatable. 

Start by opening the Postprocessing section in the model tree. Then right-click on Peak Finder and select Add. This opens the Peak Finder configuration window, where you define the criteria for detecting peak zones. 

Image: Peak Finder tool 

In this example, the setup is based directly on stress results: 

• Select From Load as the source  
• Set Category = Stress  
• Choose the appropriate direction depending on the stress component you want to evaluate  

Next, define the result range. This is the key parameter that controls which elements will be included. Here, the goal is to capture all potentially critical areas, so the threshold is set to: 

• values greater than or equal to 200 MPa  

With this condition, Peak Finder will scan the model and identify every region that meets or exceeds this stress level. 

After completing the setup, click OK. The Peak Finder rule will appear in the model tree, ready to be used for generating tables, visualizations, and further analysis of the detected peak zones.

3) Create a Table of Peak Zones

After defining the Peak Finder rule, the next step is to turn the filtered results into a structured list of peak zones. This allows you to move from a visual interpretation to a clear, reviewable dataset. 

To do this, right-click the Peak Finder rule in the model tree and create a table. In the table settings, you can control how the results are presented and what data is included. 

Image: Peak Zone Table window 

You can select: 

• loads for which the peak zones should be evaluated (e.g., envelope load set)  
• model selection (specific parts or the full model)  
• plot type, choosing whether to display values or element IDs  
• label type and font size for better readability  
• whether to display results for welds only or the full model  

Once all parameters are defined, click Fill to generate the table. 

In this example, the rule is set at ≥ 200 MPa, and the resulting detected zones all happen to be above 220 MPa. 

Image: Four peak zones in the Peak Zone Table 

Instead of scanning the entire contour plot, you now have a clearly defined set of critical regions that can be directly analyzed and compared.

4) Visualize Only the Zones that Matter

Once the peak zones are identified in the table, you can switch back to the graphical view and focus only on those critical areas. This step connects the structured data with a clear visual representation. 

Select the zones directly from the table and preview them on the plot. The visualization updates immediately: only the selected peak zones remain visible, while the rest of the model becomes transparent. 

Image: 4 peak zones in the model, visualization  

Each zone is displayed with its corresponding stress value, making it easy to interpret the severity of each region. Instead of a full contour with overlapping gradients, you now see a clean and focused view of only the elements that meet your defined criteria. 

5) Analyze Which Loads Drive the Peaks

After isolating the peak zones, the next step is to understand what is causing them. Peak Finder allows you to move beyond identification and analyze how different loads contribute to each critical region. 

To do this, create a table with load set content and factors from the Peak Finder window. 

Image: Table with identified loads for peak zones 

This table provides a breakdown for each detected zone, showing: 

• the zone itself  
• the loads influencing the result  
• the percentage contribution of each load  

This makes it immediately clear which load has the dominant effect and whether the peak is driven by a single load case or a combination of several. 

For a more visual interpretation, you can also generate a graph. The graph displays the influence of each individual load, allowing you to quickly compare their contributions across zones. 

Image: Graph with the loads on peak zones 

Together, the table and graph give you a complete picture of not just where the peaks occur, but which loads are responsible for them — turning raw results into a clear explanation of which loads drive each peak zone.

When to Use this Workflow

This workflow is most useful when standard contour plots stop being informative and start becoming overwhelming. Instead of manually interpreting dense result fields, you can apply a clear criterion and immediately focus on what matters. 

Use this approach when: 

• a contour plot shows “too much red” and it’s unclear which regions actually govern  
• you need to isolate only zones above a defined threshold  
• you must explain which load combination or individual load drives the result  
• you are working with large or complex models and need a faster, structured post-processing workflow  

In these situations, Peak Finder helps convert a visual problem into a clear post-processing workflow.

Conclusion

A contour plot shows that a problem exists, but it does not clearly show which elements govern. Peak Finder solves that by isolating the exact peak zones that meet your criteria. The table shows where those zones are, and the load influence table reveals which loads are driving them.