Role of Hydrodynamic Forces on Incipient Motion of Sediment in Unsteady Flows

<p dir="ltr">Sediment transport has intensively been investigated under steady flow conditions, but this does not reflect the typical sediment transport scenarios observed within natural channels, river mouth and on beaches. Under natural conditions, sediment particles always experience significant unsteady variations in flows and in its motion, especially during flood seasons in rivers, or in tidal and dam-break bores events in an estuaries or channels. Bores at coast and in natural rivers usually contain enormous energy and induce intense turbulent mixing, threatening hydraulic structures and seriously affecting the fluvial environment. In the laboratory a laser Doppler anemometer, a force sensor and ultrasonic displacement meters accompanied by video recordings were used to investigate the synchronised free water surface, velocities, hydrodynamic forces, and the incipient motion of sediment. A comprehensive study of tidal (i.e., undular bore, breaking bore) and dam-break bores was undertaken focusing on physical modelling of their turbulent velocity and hydrodynamic forces as well as the bore induced sediment transport. Given the complexity of the problem and the recent success of machine learning in addressing complex hydraulics problems, this thesis also investigates the potential of machine learning regression approaches to estimate hydrodynamic forces on a sediment particle that can stimulate incipient motion. Furthermore, a new equation of Shields curve was proposed and verified using both directly measured data in laboratory and data available in literature.</p><p dir="ltr">The complex fluid interactions between unsteady flow and sediment particle were explored. Detailed velocity and hydrodynamic force measurements were undertaken in a laboratory open channel for a range of Froude numbers to investigate the mechanism of sediment initiation beneath tidal and dam-break bores. In addition, a hypothetical approach was adopted to express the influence of vertical force on incipient sediment motion. The experimentally generated dataset was further used to develop a machine learning regression-based predictor to estimate the instantaneous hydrodynamic forces in rapidly varied flows. Random Forest model was reported best among the implemented machine learning models based on the standard evaluation measures (i.e., Mean Squared Error (MSE), Mean Absolute Error (MAE), Correlation Coefficient Score (��2)). The learning base method showed the potential for efficient prediction of complex hydrodynamic forces. Furthermore, A unified critical Shields stress criterion is proposed, which extends the conventional Shields diagram to express incipient sediment motion in non-uniform or rapidly varied unsteady flows.</p><p dir="ltr">The experimental results revealed that the uplift force due to swelling in free water surface was the main force in the destabilizing and movement of particles. During the initial impact of bores, uplift force was about 0.85 of submerged weight of target sphere. Later, a large longitudinal force was found to be the dominant cause promoting particle motion. The phases of both horizontal and vertical forces played an important role in tidal bore. Evidence suggests that contrary to the more commonly assumed longitudinal force and placement of bed particle, the incipient sediment motion is also induced by instantaneous vertical force. Furthermore, lateral force was found to have the least influence on incipient motion.</p><p dir="ltr">New equations were developed to express the influence of vertical force on sediment incipient motion based on the proposed apparent density concept. The effect of instantaneous lift force on critical shear stress was presented in a Prism diagram. Finally, it can be concluded that both instantaneous longitudinal and vertical direction parameters ix</p><p dir="ltr">(i.e., velocity, force and, the magnitude and direction of vertical force) play an important role for sediment incipient motion. This effort will aid in the validation of numerical models to improve our prediction capabilities of sediment transport phenomena such as coastal and mountainous stream erosion, and on a larger scale improve the coastal and natural streams processes and beach nourishment programs.</p>