SBIR Phase II: Sensor Platform for Novel Submerged Barriers

Award ID: 2604863

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to advance engineered structures that act as submerged barriers. The project will also develop monitoring systems to measure performance in real-world conditions. This information will help improve future designs and support more reliable coastal protection strategies. By combining infrastructure with ecological restoration, this work offers a more durable and cost-effective alternative to existing methods. The primary technical innovation of this project is the development and full-scale validation of a modular, engineered system that integrates predictable hydrodynamic performance with ecological function, coupled with in situ sensing to directly compare modeled and observed outcomes in high-energy nearshore settings. The high-risk element lies in demonstrating that a repeatable, parameterized geometry can achieve reliable attenuation under real-world conditions while also generating high-quality data for model calibration in settings where measurements are currently sparse or unavailable. The scope of this project is to design, deploy, and evaluate full-scale modules that function as submerged barriers. The project aims to: (1) advance the understanding of wave transformation and energy dissipation across structured, similar geometries, and (2) establish a framework for integrating physical infrastructure with continuous ambient monitoring to improve predictive coastal models. The proposed methodology includes fabrication of full-scale modular units using precast manufacturing techniques. Hydrodynamic performance will be assessed using a network of embedded and adjacent sensors measuring wave height, current velocity, and related environmental parameters. Baseline data collected prior to installation will be compared with post-installation measurements to quantify changes in wave energy, flow patterns, and sediment dynamics. Ecological monitoring will be conducted using a combination of visual surveys and ambient DNA sampling. These data will be used to validate and refine numerical models, enabling improved design of future installations and contributing to a more data-driven approach. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Rajesh Mehta