Munitions deposited in water bodies are a big threat to human health, safety, and the environment. The understanding of the transport and fate of munitions is important for site assessment and remediation actions. The objective of this project is to develop and utilize a three-dimensional (3D) computational model to predict the initiation of motion and continuous movement of munitions. The model will be able to characterize the hydrodynamic forces on underwater munitions, predict their mobility, and model sediment scour around them. In addition, liquefaction of sediment bed has been identified as an important contributing factor to the stability and motion of munitions. To capture liquefaction, the 3D model also solves for the pore pressure within the sediment bed. With the proposed new model, a detailed plan of simulations and analysis is proposed to obtain results that cover a wide range of munition motion and transport regimes. The variation of regimes will be achieved by changing the identified key parameters, including munition size, geometric shape, density, storm intensity, and bed material properties. The analysis will answer a host of scientific questions related to munition response and test several hypotheses regarding munition density and liquefaction. Unlike many previous numerical models, the computational model in this project can describe in full detail the physical processes (turbulent flow, sediment transport, pore pressure, granular sediment behavior, and rigid body motion) that control the fate of munitions. This project addresses the research need outlined in MRSON-17-01 on the topic of “Characteristics of Munitions Underwater and Their Environment”.

This new computational model is the first of its kind to consider all the important physical processes contributing to the initiation of motion and the final fate of underwater munitions. These physical processes include turbulent flow and its induced sediment transport, hydrodynamic forces on munitions and their 6 degrees-of-freedom (DoF) motion, pore pressure within the bed and potential liquefaction, and the granular behavior of sediment. In most underwater environments, these processes co-exist and are coupled with each other. Therefore, computational modeling effort neglecting any of these processes is at the risk of over-simplification and will very likely yield results with large margin of error. Based on this rationale, the current project proposes a comprehensive modeling framework which integrates submodels for each of the physical processes. The whole simulation domain is comprised of four sub-domains, i.e., computational fluid dynamics (CFD) domain, porous bed domain, granular sediment domain (a subsect of the porous bed domain), and the munition rigid body domain. Each sub-domain uses a submodel which solves the physical processes within its boundary. The CFD model and the porous bed response model will both be implemented in the open source platform OpenFOAM, a widely used CFD package. The behavior of the saturated granular sediment underneath the munitions will be modeled by a meshless smoothed particle hydrodynamics (SPH) model suitable for large deformations using the open source code SPHysics. The 6-DoF motion of munitions will be simulated with the open source code Bullet- Physics. A detailed simulation and analysis plan is proposed to parameterize the munition response and test hypothesis regarding munition density and liquefaction. The proposed research complements the ongoing SERDP supported projects conducting field and laboratory experiments. The Principal Investigators (PIs) of two ongoing projects have committed to collaboration. Their data will be used for our model validation and analysis.

This project will result in a 3D computational model and a large set of simulation data. The simulation results will reveal rich information about turbulent flow, forces and moments, scour, pore pressure, dynamics of saturated granular sediment, and munition motion. This project will greatly benefit the SERDP MR research program by providing data and insights which are hard to be acquired from field and lab work. The proposed model is deterministic and physically-based. Its results can be integrated into stochastic models or expert systems. The product of this project can be used to evaluate site conditions and make informed decision underwater munition remediation actions. It contributes to the risk reduction of Department of Defense (DoD) practitioners.