The future of civil engineering is a human + machine team

Mott MacDonald and Continuum Industries have teamed up to combine the best of human and artificial intelligence (AI). This case study showcases how engineers can apply AI to do much faster, more detailed optioneering at the start of any linear project and save millions in project costs.

By Adam Cullum (Mott MacDonald) & Matt Blythe (Continuum Industries)

Plenty has been written about how artificial intelligence (AI) will transform civil engineering. One area where we see obvious applications for AI is in designing linear projects, which consist of repeated sections and are rule-based.

To put this into practice, we devised a test case on water pipelines to solve using both a traditional approach and AI. In the process, we set out to answer two important questions.

  • Can engineers use AI on linear projects to identify better design solutions?
  • If so, how can engineers use AI most effectively in designing linear projects?
1. TEST CASE PROBLEM
2. APPROACH 1: WITHOUT AI
3. APPROACH 2: WITH AI
4. RESULTS
5. CONCLUSIONS

Test case problem

We gave experienced engineers in Mott MacDonald’s water team a classic early stage design task:

Design 3 pressurised water pipeline schemes for the lowest whole lifecycle costs.

  • Use all GIS data available for the scheme areas
  • Prepare both horizontal and vertical alignments
  • Ensure compliance with engineering standards
  • Evaluate key quantities and estimate lifetime costs

“We gave them a blank piece of paper and asked them to develop outline designs for different water pipeline schemes from scratch.”

- Adam Cullum, Civil Engineer, Mott MacDonald

Example horizontal route alignments prepared with (yellow) and without AI (blue)

Test Case Results

Comparison of design solutions from Approaches 1 & 2:

  • Pipeline schemes ranged between 15-35km in length
  • Same data, design and cost parameters were used for each scheme
  • Manual approach produced shorter pipeline route options
  • AI approach yielded 2.8%, 8.5% and 10.7% lower lifetime costs across 3 schemes

“Using AI highlighted 7% average savings in lifetime costs in compared with traditional methods.”

- Matt Blythe, Co-Founder, Continuum Industries

Download the full case study to understand how the savings in lifetime costs were achieved.

Example vertical profile for route alignment

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the Full Case study

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