Improved Settling Velocity for Microplastic Fibers: A New Shape-Dependent Drag Model.

Microplastics are abundant in aquatic environments and are an emerging environmental concern. The prediction of their settling velocities is central to predictions of the residence time and concentration depth profiles of microplastics in aquatic environments. The main scientific challenge in improving the current understanding of the settling motions of microplastics is that existing drag models are deficient at reasonably predicting the settling velocities of various microplastics, especially microplastic fibers. This is because the shape factors used in the existing drag models cannot morphologically distinguish fibers from fragments and films. In this study, a new shape factor, specifically the Aschenbrenner shape factor, is proposed as a vehicle to explicitly distinguish among the morphologies of fibers, films, and fragments. With this new shape factor, a new drag model is developed and then systematically evaluated against the unique set of data provided by new experiments conducted in this study along with four other published data sets in the literature. The proposed model allows the prediction of the terminal settling velocity of microplastic fibers more accurately than existing drag models. Moreover, the new model has also shown its applicability to microplastic films and fragments. Notwithstanding, the new model appears deficient at reasonably predicting the terminal settling velocity of weathered microplastics in the field, which requires further investigations.

A Drag Model-LIDAR-IMU Fault-Tolerance Fusion Method for Quadrotors.

In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme.

Towards realistic predictions of microplastic fiber transport in aquatic environments: Secondary motions.

Microplastics fibers are abundant in aquatic environments and are an emerging environmental threat. Understanding how fibers are transported in aquatic environments is essential for identifying pollution hotspots and developing remediation strategies. Over recent years, an increasing number of drag models have been proposed to describe the transport of microplastics in aquatic environments. However, none of the proposed models consider secondary motions, which are responsible for non-vertical settling motions. To investigate the role of secondary motions, an experimental setup with an image processing technique was developed to capture the spatial-temporal kinematics of microplastic fibers settling in quiescent water. A new drag model, which adopts the crosswise sphericity to consider the effects of secondary motions of a microplastic fiber and the Aschenbrenner shape factor to account for the unique morphology of the microplastic fiber, was proposed and evaluated. Secondary motions of microplastic fibers have profound effects on their settling trajectories and deposited positions. The settling motion and drag coefficient of a microplastic fiber is an orientation-dependent process. Moreover, the secondary motion is strongly dependent on the fiber dimension and density. The here-proposed drag model is proven to more accurately characterize the settling motion of microplastic fibers compared to existing models that neglect secondary motions. The methodology and model from this study can be used to progress towards improved and realistic predictions of the transport of microplastic fibers in aquatic environments.

A heterogeneous model of endovascular devices for the treatment of intracranial aneurysms.

Numerical computations of hemodynamics inside intracranial aneurysms treated by endovascular braided devices such as flow-diverters contribute to understanding and improving such treatment procedures. Nevertheless, these simulations yield high computational and meshing costs due to the heterogeneity of length scales between the dense weave of the fine struts of the device and the arterial volume. Homogeneous strategies developed over the last decade to circumvent this issue substitute local dissipations due to the wires with a global effect in the form of a pressure-drop across the device surface. However, these methods cannot accurately reproduce the flow-patterns encountered near the struts, the latter strongly dictating the intra-saccular flow environment. In this work, a versatile theoretical framework which aims at correctly reproducing the local flow heterogeneities due to the wires while keeping memory consumption, meshing and computational times as low as possible is introduced. This model reproduces the drag forces exerted by the device struts onto the fluid, thus producing local and heterogeneous effects on the flow. Extensive validation for various flow and geometric configurations using an idealized device is performed. To further illustrate the method capabilities, a real patient-specific aneurysm endovascularly treated with a flow-diverter is used, enabling quantitative comparisons with classical approaches for both intra-saccular velocities and computational costs reduction. The proposed heterogeneous model endeavors to bridge the gap between computational fluid dynamics and clinical applications and ushers in a new era of numerical treatment planning with minimally costing computational tools.