Real projects demonstrating AI-native engineering approaches with quantifiable results and validated methodologies.
Comprehensive fatigue life assessment for a 40-year-old fixed platform using machine learning to incorporate 15 years of operational monitoring data. Reduced assessment time by 85% while improving prediction accuracy by 23%.
Python automation pipeline for NASTRAN FEA post-processing that eliminated manual data extraction bottlenecks. Reduced post-processing time by 90% and enabled 50+ qualification reports per week with zero manual errors.
Structural integrity assessments for 92 monopile foundations using machine learning-based load prediction and fatigue assessment. Achieved 70% reduction in analysis time and 25% foundation weight optimization through site-specific probabilistic analysis.
OrcaFlex batch automation reduced Steel Catenary Riser sensitivity analysis from 50 engineer-hours to 4 hours overnight. Delivered 70% cost savings for mid-market engineering firm with complete results in 3 days instead of 3 weeks.
We're documenting additional projects across these areas: