Project Description

This project develops and validates a pervious concrete seawall system to reduce wave loads and mitigate scour-related degradation at lower cost and maintenance demand. The work integrates (i) high-fidelity finite element analysis for preliminary design, (ii) fabrication of pervious concrete with tuned porosity (15–35%) using durability-enhancing binders and engineered biochar, (iii) controlled wave flume experiments with instrumented specimens and backfill monitoring, and (iv) seawall design optimization accelerated by surrogate model and genetic algorithm.

To achieve the above mentioned integration, the research will proceed through a series of coordinated actions. First, we will build high-fidelity finite element model, analyze the wave load in seawall, and achieve a preliminary design. Next, pervious concrete specimens with controlled porosity will be fabricated using the preliminary design and tested in a wave flume, which simulates real coastal conditions by generating programmable waves and measuring forces, displacements, and backfill scour behind the seawall (Fig. 1). Finally, we will apply a HyperNetwork (Fig. 2), a neural architecture that dynamically generates predictive models, to estimate performance metrics such as energy dissipation and structural stability across different design configurations. Our team has rich experience in developing surrogate models for engineering applications and will complete building this HyperNetwork-based surrogate model in six months. This HyperNetwork will be used together with a Genetic Algorithm to search for Pareto-optimal designs that balance durability, hydraulic efficiency, and cost. This integrated approach ties together physical testing and advanced modeling to deliver practical, field-ready guidance with the objective of reducing wave-driven degradation and improving structural resilience in simple, cost-effective terms.

Outputs: 

• Design artifacts: Optimized geometric and material design guidance for pervious‑concrete seawalls (porosity ranges, height/slope recommendations). 
• Models & software: Validated finite element models; HyperNetwork‑based surrogate model; Genetic algorithm optimization workflow. 
• Data: Instrumentation datasets from wave‑flume tests (wave loads, displacements, soil deformation point clouds). 
• Scholarly products: Technical report(s), journal/conference papers, and presentations documenting design methodology and performance findings.

Outcomes/Impacts:

• Practice‑ready guidance enabling DOTs and municipal public works to deploy pervious‑concrete seawalls that reduce wave impact, scour-related degradation, and lifecycle costs. 
• Engineering practice impact by providing evidence and models that can inform updates to coastal infrastructure design practices and support novel solutions to provide “hard” infrastructure. 
• Economic benefits via reduced material quantities, lower maintenance, and improved performance of coastal transportation infrastructure.

_{Figure. 1 Experimental setup of wave flume testing.}

Figure. 2 The HyperNetwork Architecture for Performance Prediction.