Innovation · Meinhardt Infrastructure and Environment
Dulan Chinthaka is Senior Engineer at Meinhardt Infrastructure and Environment in Hong Kong, and writes the scripts that take repetitive modelling off a bridge team's hands. The usual case for automation is the hours it saves. The account below spends its length on what those hours were spent on instead.
In Dulan Chinthaka's own words.
"Leveraging automation to eliminate human error, not to bypass rigorous checking."
Scripting with the MIDAS API allows me to automate complex modeling and process data quickly. However, the real value of automation isn't just saving time, it gives me more time to focus on double-checking critical details. To me, the "right" way to modernize engineering is to use automation as a safety net so that nothing slips through the cracks.
At heart I am a fundamentals-first engineer, and the structural integrity of the system always comes first for me. Automation is how I protect it. I use advanced FEA and APIs to take the overhead out of the workflow, so more of my time goes into the engineering itself. And because I think like someone on the job site, I keep asking whether a complex, long-span bridge concept can actually be built, and I work to make sure it can.
In my previous bridge engineering roles, I noticed that our design teams spent an excessive amount of time manually setting up repetitive structural models and extracting data. This manual process was not only time-consuming but also limited our ability to iterate. Because modifying a model required significant manual effort, we could only test a few design variations, which restricted our ability to fully explore and find the most cost-effective, material-efficient structural solutions. I felt a new approach was necessary to eliminate these bottlenecks without compromising structural accuracy.
To streamline these repetitive tasks, I pioneered the integration of the Midas API to automate our modeling and analysis workflows. I developed custom scripts to automate the generation of structural elements, load distributions, and data extraction. By linking our design parameters directly to Midas via the API, I created a "one-click" system that could automatically build complex finite element models, execute the analysis, and instantly extract the necessary design results.
By eliminating hours of tedious data entry, the engineering team saved significant time. This allowed them to shift their focus away from repetitive tasks and toward critical engineering judgment, risk evaluation, and high-level decision-making.
Because we could now run models and extract results instantly, we had the freedom to analyze dozens of design alternatives rapidly. This iterative capability enabled us to find the absolute optimum design for our bridge structures, leading to a substantial reduction in material quantities and a more sustainable, cost-effective use of resources.
Q. You hand software troubleshooting to the support team rather than working through it yourself. Why?
Whenever I encounter a difficult issue, I can quickly find answers within their well-organized library of supporting materials. That is the most memorable aspect of MIDAS. It has highly efficient technical support system.
For complex problems, their online system allows me to submit a query and receive fast, precise solutions directly from a MIDAS expert. This reliable support shifted how I manage my workflow. Instead of wasting valuable project time troubleshooting software issues, I can confidently delegate those technical hurdles to their experts. This allows me to stay completely focused on critical day-to-day engineering decisions and project deadlines.
He allowed to evaluate dozens of design options instead of just a few. Rather than using that speed to skip steps, he redirected the saved hours into inspecting critical design details. His approach clearly shows how automation should empower engineers, raising a thoughtful question about how the engineer's role evolves alongside increasing efficiency.