AI Structural Design
Generative Optimization for Material Efficiency and Concrete Safety
Design safer structures with lower carbon footprints. Our generative AI engine iterates through thousands of load scenarios to produce optimal, code-compliant steel and concrete schedules.
The Industry Challenge
Why traditional engineering processes fail to meet modern structural schedules.
Engineers typically only have time to evaluate 2 or 3 manual design iterations. This results in conservative, over-designed members that increase project material costs, waste concrete, and inflate building carbon emissions.
Operational Pipeline
Parameter Ingestion
Input your project grid, geometry boundaries, soil conditions, and target safety factors.
Scenario Generation
Generative models construct hundreds of cross-section configurations and steel rebar profiles.
Load Path Testing
Finite Element Method (FEM) loops test each option under gravity, wind, and seismic load scenarios.
Optimal Solution Selection
The engine outputs optimized member schedules ranked by cost, material usage, and ease of casting.
Core Module Capabilities
Multi-Objective Generative Engine
Optimizes member sizes and reinforcement percentages concurrently for weight, structural capacity, and steel cost.
Seismic & Wind Optimization
Performs dynamic load-path optimization complying with earthquake and wind conditions.
Carbon Footprint Tracking
Calculates embodied carbon savings against baseline designs to meet green building certifications.
Commercial IT Park, Hubli
By feeding structural grids into our generative design engine, engineering consultants shaved 14.8% off the total concrete volume and reinforcement weight while maintaining a safety factor of 1.6 across all column members.