Assessing the importance of sediment characterization on seabed embedment predictions of cylindrical objects

Abstract

The prediction of object embedment into the seabed is important for the deployment and efficacy of submerged sensors and sensor networks, as well as for other applications such as unexploded ordnance risk assessment, subaquatic search and rescue efforts, or anchors and moorings. The embedment of objects into the seabed during placement depends on the strength parameters of the seabed sediment. However, a detailed characterization of seabed strength can be complex and costly since quality seabed samples and/or in situ testing are required. This study evaluates the importance of a detailed geotechnical seabed sediment characterization over seabed classification from geoacoustic surveying or accepting unknown seabed conditions for the prediction of seabed embedment of cylindrical objects. Monte Carlo simulation was applied to model the uncertainty of sediment strength parameters. The results suggest that prior knowledge of the general sediment type (e.g., fine-grained versus coarse-grained as determined from side scan sonar imaging) significantly improves the precision of the embedment predictions over unknown conditions, reducing the coefficient of variation (CV) in prediction of percent embedment (PE) by about 50 % to 65 %. Performing a detailed geotechnical testing of sediment strength represented a further improvement by 15 % to 35 % over the knowledge of sediment type. Both the mean and standard deviation of PE in fine-grained sediments are at least about 3 times the values for coarse-grained sediments indicating a wider distribution of PE with deeper embedment for cohesive fine-grained soils. The embedment behavior is a function of the method of deployment (free fall with a certain speed versus placement with no speed) in stiff cohesive sediments but is less relevant in soft sediments since PE values are always greater than 100 % (i.e., full embedment). Similarly, in cohesionless sediments, PE is always less than 50 %.