Grouting projects typically follow a similar process: design, preparation, execution, and reporting for quality control. Nicholson Construction, which employs two of the authors of this article, is an example of a contractor that has implemented software and hardware tools to guide and assist engineers and equipment operators in ensuring an optimized and high-quality final product. Nicholson uses a proprietary solution called Grout I.T., as shown in the workflow in Figure 1.
In the design phase, each injection site is modeled in 3D according to the design’s specifics (location, inclination, orientation, length, etc.). This approach allows the generation of a 3D grouting plan that incorporates all key design components. This can be communicated to the field staff in an easy-to-visualize manner.
During the preparation phase, the project is analyzed and divided into different areas with similar characteristics, based on the available geotechnical information and known site limitations. This work sequence is stored in the Grout I.T. database and is used to plan the work. Each grout hole and its design parameters are available to the project team when drilling begins.
In the execution phase, the instructions defined in the previous phase are implemented and monitored in real-time. For example, Grout I.T. software is connected to the pump to automatically control grout volume, flow rate, and other parameters in real-time to react and anticipate the soil’s response. Field engineers monitor and visualize progress through a monitoring station located in the site trailer. The collected data can be adapted to the project: for the Boone Dam repair in karst conditions in Tennessee (Figure 2), for example, Grout I.T. was updated to monitor parameters such as grout loss, grout composition, drilling fluids, and water tests. The engineer overseeing the operation can quickly and easily react and modify parameters to adapt to changing ground conditions without delay.
While it still requires engineer intervention, Grout I.T. is an important step toward integrating equipment responses and analyzing/modifying installation parameters in real-time to ensure optimal quality of the final product. The next step for full automation will be integrating ML components.
Once each injection point is completed, the reporting module can generate individual reports or 3D visualizations by area, as well as analyze productivity to provide valuable insights to engineering teams, operations teams, and estimators. Systems like Grout I.T. have the potential to bring grouting closer to a fully automated process. It’s important to remember that, just as robotic surgery didn’t replace surgeons, the goal is not to eliminate human decision-making from the process. Good engineering judgment remains critical. Machine learning or AI won’t replace good engineering, but they will reduce the risk of errors, improve understanding and response time to changing soil conditions, enhance productivity, reduce safety risks, and minimize rework, ultimately resulting in cost and time savings and a better-quality final product overall.
