Shotcrete Application AI
AI monitoring and optimization of shotcrete application for tunnels and retaining structures.
Definition
Shotcrete Application AI uses sensors and machine learning to optimize shotcrete placement. It monitors application thickness, rebound, and curing conditions while adjusting mix parameters and application technique for consistent quality in tunnel linings, slope stabilization, and structural repairs.
In Depth
Shotcrete (pneumatically applied concrete) is used for swimming pools, retaining walls, tunnels, and slope stabilization. AI monitors the application process — nozzle distance, velocity, rebound rate, and layer thickness — to ensure quality and compliance with ACI 506 standards. Real-time monitoring catches application defects before the shotcrete cures.
Examples
Monitoring shotcrete thickness in tunnels
Optimizing shotcrete mix design
Tracking shotcrete curing conditions
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Frequently Asked Questions
Shotcrete Application AI uses sensors and machine learning to optimize shotcrete placement. It monitors application thickness, rebound, and curing conditions while adjusting mix parameters and application technique for consistent quality in tunnel linings, slope stabilization, and structural repairs.
Monitoring shotcrete thickness in tunnels. Optimizing shotcrete mix design. Tracking shotcrete curing conditions.
Project Research: Instantly access all project-critical information from a single search interface.