Study On Acoustic Propagation Law Of Cohesiveless Seabed Sediments

Submarine sediment is the physical boundary between seawater and the solid earth,as well as the impedance interface between underwater acoustics and geoacoustics.Figuring out the acoustic propagation laws and the relationship between the acoustics and physical and mechanical properties of sediments is critical to seafloor and sub-bottom detection.In this paper,the cohesionless sediments are explored,mainly including sand and silt.By carrying out state-controllable laboratory simulation test,the cohesionless sediments with different states are prepared according to the original depositional environment and stress state of seafloor sediments.The compression wave velocity(CWV)of sediments are tested using ultrasonic detection and the bending-extension element method,and physical and mechanical parameters are measured accordingly.The effectiveness of measuring methods of CWV and its influence factors are discussed,and the internal connection between the CWV and physical and mechanical parameters are explored.Then,based on the test results,the parameter optimization method and parameterization scheme of the cohesionless sediment geoacoustic model are proposed.Combined with Biot-Stoll model,the seabed reflection loss is calculated and the sediment classification is carried out.The classification method is evaluated by using the measured results in the literature.The main work and innovation of dissertation are as follows:(1)Taking compactness as the controlling parameter,the sand sediments in different states are prepared,and the ultrasonic detection tests are carried out,so as to discuss the influencing factors,advantages,disadvantages and applicability of the measurement method of CWV.The test results show that the CWV is significantly affected by the saturation,which is a physical parameter that must be considered when measuring the CWV of sand.The multipath propagation of sound wave can cause the CWV measurement result of unsaturated sediments to be higher for the method with ultrasonic transducers touching the side wall of sediment container,while this effect can be avoided by measuring with a direct contact between transducers and sediment.The CWV and wave impedance of sand are less affected by particle size,but highly correlated with density,water content and porosity.(2)The silt samples under different sedimentary environment and stress state are prepared by using self-made consolidation device and stress path triaxial apparatus,taking over consolidation ratio(OCR)as the control parameter,to explore the variation of CWV with the physical and mechanical parameters during consolidation and shear process.The results showed that the ultrasonic detection and bending-extension element method are respectively suitable for testing the CWV of silt under low and high stress conditions,and the two test results are in good agreement.The CWV of silt increases with the increase of consolidation degree.After consolidation,the CWV of silt increases with the increase of density,saturation,and consolidation stress,and decreases with the increase of porosity and water content.During shear process,the variation of CWV of silt sediment is significantly affected by OCR,and has a good indication for strain,deviatoric stress and pore water pressure.(3)Based on the experimental results and the acoustic propagation law of cohesionless sediments,the optimization method and parameterization scheme of Biot-Stoll model for cohesionless sediments are proposed and compared with the measured results.The research results show that the CWV of sand and silt calculated by the existing Biot-Stoll model parameter value is low.Sensitivity analysis shows that porosity and fluid bulk modulus are the main optimization parameters.The porosity of sand and silt is parameterized by introducing compactness and OCR respectively and the revision method of fluid bulk modulus is proposed.The sediment classification is carried out by calculating bottom reflection loss based on the Biot-Stoll model and comparing with the measured values.The results show that the proposed method can further improve the accuracy of sediment classification from75.0% to 83.3%.