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An ultrasonic-wave system was developed to measure the rheological properties of non-Newtonian materials based on their responses to shear and pressure waves. This system was composed of a commercial shear wave transducer and various homemade devices, including a signal generator, a signal conditioner, and a transmission/receiving switch. The shear wave reflections at the interface between the delay line and the unknown test materials can be interpreted by the signals measured with calibration materials (e.g. air, water, olive oil and honey) that have well-known rheological properties. If the Voigt viscoelastic model is used to describe the dynamic behaviour of these test materials, the interpreted data can be used to determine the acoustic impedances, and thus solve for their shear moduli (G), kinematic viscosities (ν) and bulk densities (ρ). After the calibration procedures, the proposed system was used to test a consolidating kaolinite slurry with zero salinity and an initial suspended sediment concentration of 420 g l–1. The measurements showed that the shear modulus G is developed until consolidation for approximately 100 h. Afterward, the G gradually approached a value on the order of 500 N m–2 after approximately 200 h. This corresponded to an initial viscosity of approximately 7 × 10−5 m2 s–1, which decreased slowly over time to approximately 4 × 10−6 m2 s–1 after 300 h. With minor modification to capture pressure waves from the shear wave transducer, the bulk density can also be measured. The integrated system offers a non-invasive and efficient method for characterizing non-Newtonian fluids, providing valuable insights into their rheological properties, which are crucial for a wide range of industrial and scientific applications. [ABSTRACT FROM AUTHOR]

The rheological behaviors of suspended sediments are crucial for investigating near‐bed particle dynamics; for these investigations, the viscosity of a highly concentrated suspension is primarily focused on quantifying its resistance to deformation. By using a rotational viscometer, the relationships between relative viscosities (ηr) for different sediment types and their volumetric concentrations (ϕ) are studied for low‐to high‐concentration slurries. The results show that the conventional Einstein formula for diluted sand severely underestimates ηr. In the case of pure silts and non‐cohesive quartz, ηr demonstrates a gradual linear increase, reaching values around order of 101 as ϕ increases within the range of 0.2–0.4. Meanwhile, the ηr values of clays exhibit an exponential rise before leveling off at a plateau. Specifically, the ηr values of kaolinite, montmorillonite, and bentonite rise with ϕ lower than 0.3 and reach to plateau of values of thousands, which rise more rapidly than chlorite and illite. The modified viscosity model based on Costa (2005, https://doi.org/10.1029/2005GL024303) agrees reasonably well with observations and produces similar ηr ∼ ϕ relationships. In addition, the model is coupled with a hydrodynamic model to simulate the deposition of a thickened tailings slurry and a one‐dimensional dam break. The proposed model performs well in predicting the quasi‐equilibrium profiles of the non‐Newtonian fluid, which are validated by available analytical solutions. The results suggest that future models should be focused on the effects of flow properties, especially for non‐Newtonian fluids, and on large‐scale modeling applications, which can increase the accuracy of predictions of the transport characteristics of sediments and pollutants in rivers, lakes, and coastal areas. Plain Language Summary: Viscosity describes the resistance of a fluid, and it is defined as the ratio of shear stress to shear rate. Flow that is laden with sediment particles increases relative viscosity (ηr). Einstein (1906, https://doi.org/10.3929/ethz‐a‐000565688) conducted pioneering work to relate ηr with solid volumetric concentration (ϕ); this work is valid for dilute suspensions with coarse, non‐cohesive particles. Nevertheless, the near‐bed layer in muddy coastal waters is usually abundant with hyper‐concentrated cohesive sediment flocs, which may result in deviations using conventional equations for the viscosity. In this study, 79 experiments with eight different sediments (i.e., five clays, two silts, and quartz) are conducted to investigate the ηr ∼ ϕ relationship. We propose a modified viscosity model to further illustrate the impacts of sediment concentration, composition, and size on relative viscosity. For this model, only one parameter can be adjusted based on our experimental results with different minerals. In future research, our model could be expanded to incorporate the influence of mud/sand fractions, thereby capturing the rheological characteristics of mixed sediments more comprehensively. Key Points: The relative viscosity was measured for clays, silts, and quartz under different concentrations or flow environments by using a viscometerThe conventional Einstein formula severely underestimates the relative viscosity for fluid containing high concentrated cohesive sedimentsAn improved viscosity model was proposed to predict the ηr ∼ Φ relationship for different sediment suspensions [ABSTRACT FROM AUTHOR]

In estuaries and coastal waters, the flocculation of cohesive sediments is significantly affected by extracellular polymeric substances secreted by microalgae. In this study, laboratory experiments are carried out to explore the role of two typical microalgae (Skeletonema costatum and Cyclotella meneghiniana) on suspended fine‐grained sediments under various turbulent shear and environmental conditions. The results show that the shear rate is a dominant factor in controlling the biomineral flocculation processes, and the existence of microalgae generally enhances the aggregation of mineral sediments with microalgae. It is also found that floc size distributions (FSDs) and mean sizes are clearly influenced by different algal species and concentrations, especially under intensive turbulent environments. Moreover, a quasi‐Monte Carlo (QMC) based bivariate population balance model is developed to simulate the FSDs of sediment‐algae flocs. This model is reasonably validated by two analytical solutions and laboratory observations, and indicates a potential extension for tracking the properties of microalgae‐associated fine sediment flocs due to the discrete nature of the QMC method. Plain Language Summary: The transportation of fine‐grained suspended sediments in estuaries and coastal environments is a factor in many engineering and environmental issues (e.g., siltation, dredging, bed morphology, and water quality). One important characteristic that affects the transport and fate of cohesive sediment particles is flocculation, which is the tendency of particles to aggregate and breakup sequentially to form clusters (flocs) of various sizes, densities, and settling velocities. Since they are abundant in the natural environment, microalgae and their sticky secretions play important roles in the flocculation of cohesive sediment as biological glues. However, few studies have been carried out to reveal the correlation between microalgae and sediment flocculation. Thus, this study aims to investigate the influences of microalgae on the flocculation of cohesive sediment particles in various turbulent environments. We find turbulent shear is dominant in the biomineral flocculation and that biomineral flocs are generally larger than pure sediment flocs. In addition, we develop a bivariate flocculation model to simulate the floc size distribution of biomineral flocs, which is well validated by theoretical solutions and laboratory results. This innovative model offers a preliminary application for multivariate models in biomineral flocculation, which promotes a prospect of future research to develop advanced transportation models. Key Points: The influence of microalgae on the flocculation of cohesive sediments is investigated by laboratory experiments and numerical modelsThe existence of microalgae and their secreted extracellular polymeric substances generally enhances the aggregation of biomineral flocsThe quasi‐Monte Carlo based bivariate population balance model can mimic the biomineral flocculation processes with reasonable accuracy [ABSTRACT FROM AUTHOR]

The floc size distribution (FSD) is crucial to predict cohesive sediment dynamics in aquatic environments. Recently, increasing attention has been given to biofilm effects on the FSDs of suspended particles since the presence of biofilms on particle surfaces may lead to larger flocs and thus higher settling velocities. In this study, results from a settling column experiment conducted by Tang and Maggi (2018; https://doi.org/10.1002/2017JG004165) under nutrient‐free and biomass‐free, nutrient‐affected and biomass‐free, and nutrient‐affected and biomass‐affected conditions, with different suspended sediment concentrations, shear rates, and nutrient concentrations, have been used to validate modeled FSDs that is based on the population balance equation solved by the quadrature method of moments. In addition to the processes of aggregation and breakage, the effects of biofilm are expressed in the growth term of the population balance equation. The logistic growth pattern is used to account for an increase in biomass, which is primarily controlled by the specific growth rate and the carrying capacity. In this study, the biofilm growth rate is assumed nutrient dependent, and the carrying capacity of floc size is hypothesized to be proportional to the Kolmogorov microscale. With eight size classes to interpret a simulated FSD, the predicted and observed FSDs exhibit a reasonable match for all nutrient‐free and biomass‐free, nutrient‐affected and biomass‐free, and nutrient‐affected and biomass‐affected conditions. This simplified bioflocculation model fills the gap between the simulations of the FSDs of cohesive sediments without and with biofilms and has the potential to be included in large‐scale models in the future. Plain Language Summary: In estuaries or adjacent coastal regions, the transport of suspended sediment is responsible for many environmental and engineering issues, for example, siltation and dredging in navigation channels and harbors, water quality, water clarity, pollutants transport, and ecosystem responses. Suspended sediment particles can flocculate and thus can form aggregates with size, shape, density, and settling velocity largely different from the building particles. A challenge to predict the particle behaviors originates from a lack of flocculation models that are able to address the variations in floc size distributions. The aim of this study is to develop a flocculation model that includes besides the "classical" aggregation and breakage driven by turbulence also a biological process, which is biofilm growth. The biofilm growth and its impact on flocculation and thus floc size are simulated in a similar way as the growth of microbes but with different growth rates. The model is validated with laboratory experiments that have shown that the sizes of flocs made solely with sediment particles largely increase when incubated microbes are present. This model provides a sound basis to simulate the behavior of natural particles (minerals, organic, and biological particles) and particles from human origin (plastics) in future environmental risk assessment studies. Key Points: The quadrature‐based multiclass population balance model was used to model the floc size distributions of cohesive sedimentsThe effects of aggregation, breakage, and biofilm growth were included in the modelThe net increase in floc size due to biofilm effects is assumed to follow the logistic growth pattern [ABSTRACT FROM AUTHOR]

Abstract The time evolutions of local Particle Size Distributions (PSDs) of suspended kaolinite are explored under different hydrodynamic conditions. A setup that uses oscillating grids is adopted to generate a nearly isotropic turbulence in a settling column, and the results at the observation location show that the initial unimodal PSDs change to bimodal distributions due to flocculation processes. The first peak of the bimodal PSD, which represents primary particles (0.1–4 µm) and flocculi (4–20 µm), remains similar in size to the median size of the initial PSD. The second peak, which represents the flocs (> 50 µm), however, is size-varying under different experimental durations and shear rates. For low shear rates, the size of the second peak increases with time and reaches an equilibrium state; for high shear rates, it first increases and then decreases. Moreover, the two PSD peaks are reasonably simulated by a two-class population balance equation, with the experimental and predicted results comparing well. The results of this study also indicate that the optimum shear rate to boost flocculation is approximately 20 s−1. Highlights • Bimodal Particle Size Distributions (PSDs) were observed in a settling column with oscillating grids; • The first peak of the PSD, which represents the flocculi, remains close in size; • The second peak of the PSD, which represents the flocs, is size-varying under different environments; • The bimodal PSDs are reasonably predicted by the two-class population balance model; • The optimal shear rate to promote flocculation is around 20 s−1 in this experiment. [ABSTRACT FROM AUTHOR]

Abstract Estuarine and coastal regions are often characterized by a high variability of suspended sediment concentrations in their waters, which influences dredging projects, contaminant transport, aquaculture and fisheries. Although various three-dimensional open source software are available to model the hydrodynamics of coastal water with a sediment module, the prediction of the fate and transport of cohesive sediments is still far from satisfied due to the lack of an efficient and robust flocculation model to estimate the floc settling velocity and the deposition rate. Single-class and sometimes two-class flocculation models are oversimplified and fail to examine complicated floc size distributions, while quadrature-based or multi-class based flocculation models may be too complicated to be coupled with large scale estuarine or ocean models. Therefore, a three-class population balance model was developed to track the sizes and number concentrations of microflocs, macroflocs and megaflocs, respectively. With the assumption of a fixed size of microflocs and megaflocs, only four tracers are needed when coupled with the open-source TELEMAC system. It enables better settling flux estimates and better addresses the occurrence and concentration of larger megaflocs. This tri-modal flocculation model was validated with two experimental data sets: (1) 1-D settling column tests with the Ems mud and (2) in-situ measurements at the WZ Buoy station on the Belgian coast. Results show that the flocculation properties of cohesive sediments can be reasonably simulated in both environments. It is also found that the number of macroflocs created, when a larger macrofloc breaks up, is a statistical mean value and may not be an integer when applying the model in the field. Graphical abstract Image Highlights • The sizes of flocs are dynamically altered because of particle aggregation and breakage. • A three-class population balance flocculation model was developed. • This flocculation model has been successfully implemented in the open source TELEMAC. • Four tracer variables, representing the floc size distributions, were included in TELEMAC. • The model was validated with settling column tests and field measurements. [ABSTRACT FROM AUTHOR]

The observation of floc size distribution (FSD) for quantitative description of its properties over a sufficient size range, from a few microns to a few millimeters, is still a challenge in most marine environments. In this study, an inexpensive image acquisition and processing system is developed for achieving this objective. Images are acquired by using a Sony Alpha NEX-5R camera body with a CMOS sensor, a Sony E-mount to Nikon F-mount adaptor, extension tubes, a Nikon macro lens, and a close-up lens that can identify flocs with a minimum size of 5 μm. The light source and camera trigger are controlled by a micro-controller that was assembled for this project. These images are analyzed by using MATLAB Image Processing Toolbox. The processed floc size and their statistical distributions are confirmed with two available sample sets. The validated process is then applied to measure the steady state FSDs of kaolinite suspensions for different shear rates, suspended sediment concentrations, salinities, and a selected organic matter, guar gum. Although the presence of salt promotes flocculation of suspended kaolinite, only a small amount of salt, around 0.5 ppt, is needed to reach the saturation status. Thus for the test salinities (0.5, 1, 2, 3, 5, and 9 ppt), the measured FSDs show little difference among each other. On the other hand, guar gum affects kaolinite flocculation significantly and the maximum effect happens at a guar gum concentration around 15 mg/L when the kaolinite concentration is around 0.52 g/L. At this dosage the characteristic floc size is the largest. [ABSTRACT FROM AUTHOR]

An enhanced Quadrature Method Of Moments (QMOM) is employed to solve the population balance model (PBM) with a maximum of eight size classes for the purpose of describing the evolution of floc size distribution (FSD) of kaolinite suspension and colloidal montmorillonite. This approach can be used to estimate many representative sizes, e.g., d 32 (Sauter mean size), d 43 (De Broukere mean size), d 60 (hydrodynamic mean size), and D 50 (median size). The following three considerations are adopted to enhance the QMOM approach: (1) An adjustable factor, which is selected based on its ability to track up to eight size classes, is implemented; (2) moments higher than the third order are not necessarily simulated directly; (3) a restriction on the ratio between the minimum and maximum weights is used to exclude unreliable nodes. The above enhancements have been proposed by others, but are integrated for the first time in this study. Model results are verified by comparison with available experimental data. The results of this study suggest that the quadrature nodes and weights in the QMOM are the characteristic sizes and corresponding characteristic number densities to effectively predict the FSD of cohesive sediments. This study also demonstrates that the possible range of the correction factor (also sometimes referred to as “collision efficiency”) for the Euclidean collision frequency could be larger than one because of both the difference in floc structure represented by fractal dimension as well as the impacts of organic matter. [ABSTRACT FROM AUTHOR]

Mussels are suggested as bioindicators of marine microplastic pollution. However, they are selective in regards to accumulation of microplastics. To make studies more targeted and comparable, ultimately helping to determine the suitability of the mussel as a bioindicator species for microplastic exposure, we review the published literature that has directly or indirectly demonstrated particle selection in mussels. The reported difference between microplastic levels in mussel tissues and environmental matrices provides evidence for their selective uptake characteristics. Both the organ-specific fate characteristics of microplastics, and the different movement patterns of microplastics in the same organ, show that selective translocation processes take place. The selective elimination is reflected in multiple aspects which include (1) the different characteristics of microplastics in excretion and mussel body; (2) the different retention time of various microplastics in mussels; and (3) the tissue-specific change in the numbers of microplastics during the depuration process. This selectivity is affected by the characteristics of the microplastics, the environmental, or laboratory exposure concentrations, feeding status, and other factors. There are still many research gaps and contradictory viewpoints in this field due to this complexity. The current methodology needs improvement and a breakthrough in standardization. [Display omitted] • Selective accumulation of microplastics in mussels is reflected in multiple aspects. • Size of microplastics is the most implicated factor affecting selective accumulation. • Selective mechanisms of mussels for microplastics remain knowledge gaps. • More targeted and comparable experiment is needed for mussel's selectivity research. Mussels have particle selection for microplastics. [ABSTRACT FROM AUTHOR]

To manage coastal and estuarine waters, it is critical to accurately predict the movements of cohesive and non-cohesive sediments. There are well-established methods to estimate the behavior of non-cohesive sediments; however, without extensive knowledge on flocculation processes it remains difficult to predict the behavior of cohesive sediments. Flocculation is one of the main processes (e.g., erosion, deposition, settling, consolidation and flocculation) in cohesive sediment dynamics. The study of flocculation is an interdisciplinary work since it relates to various physical (e.g., transport, settling and deposition), chemical (e.g., contaminant uptake and transformation) and biological (e.g., community structure activities and metabolism) activities. Nevertheless, a widely-accepted flocculation model that can quantitative simulating the Floc Size Distributions (FSDs) for a relatively large study domain has not yet been fully developed. In this study, a multi-class population balance flocculation model was developed to address the occurrence of suspended microflocs, macroflocs and megaflocs in Belgian coastal waters (southern North Sea). The floc size distributions were represented by the size and mass fraction of each particle group. The representative sizes of macroflocs and megaflocs are unfixed and migrated between classes mainly due to the effects of turbulent shear, differential settling and biofilm growth. Specifically, the growth of an aggregate because of biofilm attachment and extracellular polymeric substance glue is averaged to each elementary particle, with its growth rate response to various bio-activities. This simple bio-flocculation model has been successfully coupled in the open source TELEMAC modeling system with five passive tracers in a quasi-1D vertical case. It was validated by observation data at the station MOW1 close to Zeebrugge harbor during both peak algae bloom and low biomass periods. It shows that when the biomass is abundant the predictions of the mean settling velocities are largely underestimated when the biological effect is neglected. This model will enhance our knowledge of the dynamics of suspended particulate matters, especially the biophysical influences on the fate and transport of estuarine aggregates. [ABSTRACT FROM AUTHOR]

Rivers have been recognized as the primary conveyors of microplastics to the oceans, and seaward transport flux of riverine microplastics is an issue of global attention. However, there is a significant discrepancy in how microplastic concentration is expressed in field occurrence investigations (number concentration) and in mass flux (mass concentration). Of urgent need is to establish efficient conversion models to correlate these two important paradigms. Here, we first established an abundant environmental microplastic dataset and then employed a deep neural residual network (ResNet50) to successfully separate microplastics into fiber, fragment, and pellet shapes with 92.67% accuracy. We also used the circularity ( C ) parameter to represent the surface shape alteration of pellet-shaped microplastics, which always have a more uneven surface than other shapes. Furthermore, we added thickness information to two-dimensional images, which has been ignored by most prior research because labor-intensive processes were required. Eventually, a set of accurate models for microplastic mass conversion was developed, with absolute estimation errors of 7.1, 3.1, 0.2, and 0.9% for pellet (0.50 ≤ C < 0.75), pellet (0.75 ≤ C ≤ 1.00), fiber, and fragment microplastics, respectively; environmental samples have validated that this set is significantly faster (saves ∼2 h/100 MPs) and less biased (7-fold lower estimation errors) compared to previous empirical models.

Objective: The purpose of this study was to investigate the effects of bracketless invisible orthodontics on the plaque index (PLI), the sulcus bleeding index (SBI), the gingival sulcus probing depth (SPD), and the gingival index (GI) in children with malocclusions and on their families' satisfaction with the orthodontic treatment., Methods: The baseline data of 113 children with malocclusions were retrospectively collected and divided into two groups according to the orthodontic mode each child underwent. Group A was treated with traditional fixed braces, and Group B was treated with bracketless invisible orthodontics. The clinical efficacy, the satisfaction, the PLI, the SBI, the SPD, and the GI, the tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and the interleukin-2 (IL-2) levels, the occurrence of adverse reactions, the COHIP (oral health-related quality of life scale, Chinese Version), and the changes in oral chewing function were compared between the two groups., Results: The total effective rate in group B was 96.49%, higher than the 69.64% in group A ( P <0.05). The total satisfaction rate in group B was 98.25%, higher than the 69.64% in group A ( P <0.05). Compared with group A, group B had higher PLI, SBI, SPD, and GI levels after the treatment ( P <0.05), lower of TNF-α and IL-6 levels, and higher IL-2 levels ( P <0.05). The quality of life and the chewing function scores in group B were higher than they were in group A ( P <0.05). The incidence rate of adverse events in group B was 5.26%, lower than the 17.86% in group A ( P <0.05)., Conclusion: The efficacy of bracketless invisible orthodontic treatment in children with malocclusions is higher than it is using traditional fixed orthodontic treatment, as it helps improve their chewing function, periodontal health, and quality of life, and helps reduce the inflammatory factor levels and improves their satisfaction with the orthodontic treatment., Competing Interests: None., (AJTR Copyright © 2021.)