Incorporates Particle Size Research Articles

Characterization of road-deposited sediment wash-off and accurate splitting of initial runoff pollution in heterogeneous urban spaces

Particulate materials arising from road-deposited sediments (RDS) are an essential target for the control and management of surface runoff pollution. However, the heterogeneity of urban spaces hinders the identification and quantification of particulate pollution, which is challenging when formulating precise control measures. To elucidate the factors that drive particulate pollution in heterogeneous urban spaces, the accumulation of RDS on dry days and the total suspended solids during six natural rainfall events were investigated across three urban–rural spatial units (central urban, central suburban, and remote suburban). The underlying surface type (asphalt or cement roads) and particle size composition jointly determined the spatial heterogeneity in the static accumulation and dynamic output loads of RDS during rainfall. These two factors explained 59.6% and 18.9% of the spatial heterogeneity, respectively, according to principal component analysis. A novel CPSI exponential wash-off equation that incorporates particle size composition and underlying surface type was applied. It precisely described the spatial heterogeneity of RDS wash-off loads, the estimated values exhibiting event mean concentration errors of 10.8–18.2%. When coupled with the M(V) curve, this CPSI exponential wash-off equation more precisely split the initial volume of runoff: a lower total volume (17.6–38.0%) was shown to carry a higher proportion of the load (70.0–93.7%) compared to the traditional coupled exponential wash-off equation (volume: 31.6–49.0%, load: 37–90%). This study provides a new approach to characterizing RDS wash-off processes and splitting initial runoff in heterogeneous spaces.

Analytical modeling and optimization of electrostatic particle sensors for particle number detection: incorporating particle size influence

Developing measurement devices and methods to track increasingly stringent emission standards, including particle number, is crucial. This paper presents a novel analytical model to describe the signal response of an electrostatic particle sensor not only to particle mass concentration, but also to the particle number concentration of in-flowing particles. The uniqueness of this model lies in its ability to calculate the signal as a function of particle diameter, enabling the determination of particle number concentration from the signal. The model considers the effects of aerosol flow, electrode voltage and temperature, and can be used for the optimization of the sensor geometry parameters, length, width, and electrode gap. The model was designed to optimize the sensor’s geometry and signal retrieval as well as the optimization of the electric field between the electrodes. Comparative analysis was conducted between the proposed model and a model from the literature as well as experimental data from literature and experimental data collected in this paper.

Predicting clay compressibility for foundation design with high reliability and safety: A geotechnical engineering perspective using artificial neural network and five metaheuristic algorithms

This study aims at predicting clay compressibility (clay compressibility) for foundation design with unprecedented reliability and safety. To achieve this goal, we set forth several scientific objectives to enhance the accuracy of clay compressibility predictions and ensure the robustness of our models. Firstly, we explored an updated dataset comprising diverse clay types, focusing on the intricate relationship between clay compressibility and essential soil properties. By incorporating particle size distribution, the ratio between liquid limit (wLL) and plasticity index (PI), and the ratio between void ratio (eLL) and wLL, our objective was to gain a comprehensive understanding of clay behavior, facilitating more accurate predictions. Secondly, we employed Artificial Neural Networks (ANNs) as our primary modeling tool. ANNs, with their capacity to discern complex patterns within data, formed the foundation of our predictive model. Our scientific objective was to harness the power of ANNs to capture subtle relationships among input variables, thereby ensuring a robust foundation for clay compressibility predictions. To further refine our predictions, our third objective was to optimize the ANN model. We utilized five distinct metaheuristic algorithms—Bird Swarm Algorithm (BSA), Dragonfly Optimization (DO), Elephant Herding Optimization (EHO), Jaya Algorithm (JA), and Whale Optimization Algorithm (WOA). Our aim was to fine-tune the ANN model's parameters using these algorithms, capitalizing on their strengths to achieve superior predictive performance. Additionally, our study aimed to pioneer the development and evaluation of hybrid models for forecasting clay compressibility. By integrating the ANN model with the metaheuristic algorithms (BSA-ANN, DO-ANN, EHO-ANN, JA-ANN, and WOA-ANN), our objective was to create hybrid frameworks that synergistically combined the strengths of both approaches. We rigorously evaluated these hybrid models, ensuring their efficacy and reliability in practical engineering applications. Crucially, we validated our models through practical engineering scenarios. For this purpose, we prepared 30 new soil samples mirroring real-world conditions. Our objective was to apply the developed models to these samples, affirming their effectiveness and reliability in actual foundation design applications. In pursuit of identifying the most accurate and reliable predictive model, our final objective focused on the BSA-ANN model. Remarkably, this model demonstrated an exceptional accuracy of 99.8%. Our objective was to establish the BSA-ANN model as the preferred choice for practical engineering applications, ensuring high reliability and safety in foundation design.

Theoretical evaluation on CO2 removal potential of enhanced weathering based on shrinking core model

The discrepancy between current CO2 emission trend and the targeted 1.5 °C warming requires the implementation of carbon dioxide removal (CDR) technologies. Among the engineered CDRs, enhanced weathering (EW) is expected to exhibit substantial potential for CO2 removal, owing to the availability of abundant reserves of ultramafic rocks and demonstration of worldwide liming practice. While the shrinking core model (SCM) has been commonly adopted in previous theoretical and experimental studies, there still lacks a comprehensive assessment on the impacts of model parameters, such as rock particle size, size distribution, weathering rate and time length on the weathering kinetics and the resultant CDR potential. Herein, this study incorporates particle size distribution of rock powder into the surface reaction-controlled SCM, and conducts sensitivity analysis on EW’s CDR potential quantitatively. Even fully powered by low-carbon energy in the optimistic case, the application of EW with olivine only achieves maximum CDR per unit of rock and energy consumption of 0.01 kg CO2 per kg rock and 19 g per kWh at size of 8 and 22 μm respectively, indicating the limitations of EW. The derived optimal application parameters with olivine powers within 3.7–79 μm provide valuable insights into the practical real-world applications to achieve net CO2 removal.

Influences of size, shape and strain rate on mechanical properties of single coral particle

To understand the roles of particle size, shape, and strain rate on their mechanical properties, the crushing behavior of 800 coral particles with different shape factors and size groups (i.e., 2.36–4.75 mm, 4.75–9.5 mm and 9.5–16 mm) at various loading rates (i.e., 0.06 mm/min, 0.6 mm/min, 3 mm/min and 10 mm/min) are studied. The results show that the particle crushing strength and Young's modulus perfectly conform to the Weibull statistic law. Particle crushing strength decreases with an exponent of (−0.816) of particle size and increases with an exponent of 0.062 of strain rate, and a mathematical model incorporating particle size, shape, and strain rate is proposed to explain the change of characteristic crushing strength. Additionally, irregularity, elongation, and flatness strongly relate to the crushing strength and Young's modulus, and establish a functional relationship with the geometric similarity parameter of the Weibull model. The fragmentation behavior is classified into three typical modes, and the change of fragmentation modes is affected by particle size, strain rate, and irregularity. Young's modulus calculated by Hertz theory is 0.7–0.9 GPa. The characteristic Young's modulus is in descending order of rodlike, flaky, blocky, and dendritic particles, hardly influenced by particle size and strain rate. The results can provide a reference for the microscopic numerical analysis of coral concrete.

Pressure Effects with Incorporated Particle Size Dependency in Graphene Oxide Layers through Observing Spin Crossover Temperature

This research highlights the pressure effects with the particle size dependency incorporated in two-dimensional graphene oxide (GO)/reduced graphene oxide (rGO). GO and rGO composites employing nanorods (NRs) of type [Fe(Htrz)2(trz)](BF4) have been prepared, and their pressure effects in the interlayer spaces through observing the changes of the spin crossover (SCO) temperature (T1/2) have been discussed. The composites show the decrease of interlayer spaces from 8.7 Å to 3.5 Å that is associated with GO to rGO transformation. The shorter interlayer spaces were induced by pressure effects, resulting in the increment of T1/2 from 357 K to 364 K. The pressure effects in the interlayers spaces estimated from the T1/2 value correspond to 24 MPa in pristine [Fe(Htrz)2(trz)](BF4) NRs under hydrostatic pressure. The pressure observed in the composites incorporating NRs (30 × 200 nm) is smaller than that observed in the composite incorporating nanoparticles (NPs) (30 nm). These results clearly demonstrated that the incorporated particle size and shape influenced the pressure effects between the GO/rGO layer.

Concentration-dependent correlated scattering properties of Intralipid 20% dilutions.

Dilutions of Intralipid 20% are widely used as optical phantoms for mimicking scattering properties of turbid media such as tissues. One of the frequently used methodologies for quantifying the scattering coefficient and anisotropy of Intralipid 20% is the use of single-particle Mie scattering theory, which in fact is not valid for nontenuous media. Hence, two methodologies consisting of analytical wave theory and effective medium theory, incorporating particle size distribution and concentration-dependent correlated scattering phenomena, are used to estimate the effective scattering coefficient and anisotropy of Intralipid 20% dilutions (1%-100% v/v) from 380 to 1000 nm.

Experimental investigation of the effect of nanoparticle size on thermal conductivity of in-situ prepared silica–ethanol nanofluid

In this study the effects of particle size, temperature and volume fraction of SiO2 nanoparticles on thermal conductivity of nanofluid were investigated. Silica nanoparticles were prepared by the Stöber method. The results of experiments showed that with the increase of particle size, temperature and volume fraction the thermal conductivity of silica–ethanol nanofluid increased. Effect of particle size on thermal conductivity of nanofluid was attributed to high surface hydrophilicity of silica nanoparticles resulting decrease in interfacial thermal resistance with the increase of particle size. Also an empirical equation incorporating particle size, volume fraction and temperature was proposed for estimation of thermal conductivity of nanofluid. Comparison between this correlation and measurements showed that the deviation of calculated data from experimental results is within −9.5% to 5.4%. The literature results agree well with the predictions by correlation proposed.

Fine‐suspended sediment and water budgets for a large, seasonally dry tropical catchment: Burdekin River catchment, Queensland, Australia

AbstractThe Burdekin River catchment (∼130,400 km2) is a seasonally dry tropical catchment located in north‐east Queensland, Australia. It is the single largest source of suspended sediment to the Great Barrier Reef (GBR). Fine sediments are a threat to ecosystems on the GBR where they contribute to elevated turbidity (reduced light), sedimentation stress, and potential impacts from the associated nutrients. Suspended sediment data collected over a 5 year period were used to construct a catchment‐wide sediment source and transport budget. The Bowen River tributary was identified as the major source of end‐of‐river suspended sediment export, yielding an average of 530 t km−2 yr−1 during the study period. Sediment trapping within a large reservoir (1.86 million ML) and the preferential transport of clays and fine silts downstream of the structure were also examined. The data reveal that the highest clay and fine silt loads—which are of most interest to environmental managers of the GBR—are not always sourced from areas that yield the largest total suspended sediment load (i.e., all size fractions). Our results demonstrate the importance of incorporating particle size into catchment sediment budget studies undertaken to inform management decisions to reduce downstream turbidity and sedimentation. Our data on sediment source, reservoir influence, and subcatchment and catchment yields will improve understandings of sediment dynamics in other tropical catchments, particularly those located in seasonally wet‐dry tropical savannah/semiarid climates. The influence of climatic variability (e.g., drought/wetter periods) on annual sediment loads within large seasonally dry tropical catchments is also demonstrated by our data.

Application of GIS-Coupled Modified MMF Model to Estimate Sediment Yield on a Watershed Scale

AbstractIn this study, the Morgan and Duzant version of the modified Morgan-Morgan-Finney (MMF) model coupled with geographical information system (GIS) is used for sediment yield estimation from the Gamber watershed, Satluj basin, Himachal Pradesh, India. The model incorporates particle size selectivity in the process of erosion, transport, and deposition, i.e., it simulates these processes for clay, silt, and sand separately. This modified MMF model also allows for surface runoff and sediment routing, which improves sediment yield estimation accuracy. It also determines the watershed contributions to the total sediment yield at the basin outlet. The present research fetches the MMF model in a geospatial environment and develops a system that can be used to estimate the actual sediment yield. Generally, it has been observed that the detachment of soil is greatly affected by raindrop impact. Therefore, the estimation of kinetic energy of erosive rainfall is a very important factor. Moreover, it has been n...

Investigation of magnetic properties of Fe3O4 nanoparticles using temperature dependent magnetic hyperthermia in ferrofluids

Rate of heat generated by magnetic nanoparticles in a ferrofluid is affected by their magnetic properties, temperature, and viscosity of the carrier liquid. We have investigated temperature dependent magnetic hyperthermia in ferrofluids, consisting of dextran coated superparamagnetic Fe3O4 nanoparticles, subjected to external magnetic fields of various frequencies (188–375 kHz) and amplitudes (140–235 Oe). Transmission electron microscopy measurements show that the nanoparticles are polydispersed with a mean diameter of 13.8 ± 3.1 nm. The fitting of experimental dc magnetization data to a standard Langevin function incorporating particle size distribution yields a mean diameter of 10.6 ± 1.2 nm, and a reduced saturation magnetization (∼65 emu/g) compared to the bulk value of Fe3O4 (∼95 emu/g). This is due to the presence of a finite surface layer (∼1 nm thickness) of non-aligned spins surrounding the ferromagnetically aligned Fe3O4 core. We found the specific absorption rate, measured as power absorbed per gram of iron oxide nanoparticles, decreases monotonically with increasing temperature for all values of magnetic field and frequency. Using the size distribution of magnetic nanoparticles estimated from the magnetization measurements, we have fitted the specific absorption rate versus temperature data using a linear response theory and relaxation dissipation mechanisms to determine the value of magnetic anisotropy constant (28 ± 2 kJ/m3) of Fe3O4 nanoparticles.

Titanium dioxide synthesized using titanium chloride: size effect study using Raman spectroscopy and photoluminescence

AbstractTitanium dioxide nanocrystals were prepared by the wet chemical method and characterized by X‐ray diffraction (XRD), transmission electron microscopy (TEM), Raman scattering (RS) and photoluminescence techniques. The XRD pattern shows the formation of single phase anatase structure of average sizes ∼7 nm (sample A) and ∼15 nm (sample B) for two samples. Additionally, TEM and RS were used to confirm the anatase crystal structure for both samples. The PL spectra show that the intensity of the sample A is more than that of sample B, which has been attributed to defect(s) and particle size variation. A modified phonon confinement model incorporating particle size distribution function and averaged dispersion curves for two most dispersive phonon branch (Γ‐X direction) have been used to interpret the size effect in Raman spectra. The obtained Raman peak shift and full width at half‐maximum agree well with the experimental data. Our observations suggest that the phonon confinement effects are responsible for a significant shift and broadening for the Raman peaks. Copyright © 2009 John Wiley & Sons, Ltd.

Size Analysis of PDMS−Magnetite Nanoparticle Complexes: Experiment and Theory

Biocompatible, hydrophobic nanoparticles show great promise as biomaterials. This paper reports the synthesis, magnetic separation, and characterization of magnetite nanoparticles with polydimethylsiloxane (PDMS) adsorbed onto their surfaces. The particle size distributions were narrowed by employing a magnetic separation/fractionation technique to remove larger particles and aggregates from an original distribution. A probability averaging method that incorporates particle size distributions of the magnetite cores derived from TEM is proposed, together with implementation of a polymer brush model for calculating the thickness of the polymer surfactant, for predicting the sizes and size distributions of these complexes in suspension. The intensity, volume, and number average size distributions in solution were predicted, and the values were compared to sizes of the complexes measured by DLS. This approach provides a tool for a more precise characterization of the size distributions of polymer−nanoparticle complexes relative to previous methods that utilized only a mean (single) core particle size. The predicted sizes of the complexes in dispersion closely approximate measured values from DLS for particles with narrow size distributions. Agreement between the predicted and measured sizes improves as the particle size distribution becomes narrower.

Numerical Simulations Investigating the Regional and Overall Deposition Efficiency of the Human Nasal Cavity

Numerical simulations have been carried out on a model of the right passageway of an anonymous, adult male's nasal cavity, constructed from magnetic resonance imagery (MRI) scans. Steady, laminar, inspiratory flow was assumed to simulate inhalation. Analysis shows smoothly varying streamlines with a peak in velocity magnitude occurring in the nasal valves and a peak in vorticity magnitude immediately posterior. Dilute, uniform concentrations of inertial (1 μm dae 10 μm) particles were released at the nostril and tracked via a Lagrangian tracking algorithm. Deposition efficiency is shown to increase with particle size and flow rate. Preferential deposition is seen in the anterior third of the nasal cavity for large Stokes number particles. An empirical expression for particle deposition is proposed that incorporates particle size, flow rate, and nose anatomy.

Validation of a model for impact breakage incorporating particle size effect

Investigation of a breakage probability model published by Vogel and Peukert [Vogel, L. and Peukert, W., 2004. Determination of material properties relevant to grinding by practicable labscale milling tests. Int. J. Miner. Process., 74S, 329–338.] has led to a modification of their model to describe the degree of impact breakage, t 10. The modified model takes a form similar to the JKMRC prior art breakage model, but with particle size and breakage properties incorporated explicitly in the model. The present breakage model was validated using eight sets of detailed drop weight test data on various types of ore and quarry material over a wide range of impact specific energies and particle sizes. The validation revealed that the present breakage model fits all the data sets well with fewer model parameters. The results from the validation study suggest the present breakage model has a fundamentally better structure for describing the effect of particle size on the breakage distribution function.

Self-stresses and crack formation by particle swelling in cohesive granular media

We present a molecular-dynamics study of force patterns, tensile strength, and crack formation in a cohesive granular model where the particles are subjected to swelling or shrinkage gradients. Nonuniform particle size change generates self-equilibrated forces that lead to crack initiation as soon as the strongest tensile contacts begin to fail. We find that the tensile strength is well below the theoretical strength as a result of inhomogeneous force transmission in granular media. The cracks propagate either inward from the edge upon shrinkage or outward from the center upon swelling. We show that the coarse-grained stresses are correctly predicted by an elastic model that incorporates particle size change as metric evolution.

Particle size distribution effects in an FEM model of sintering porous ceramics

A numerical simulation is presented on the sintering of porous alumina structures prepared by a controlled sedimentation technique. By forming this functionally gradient material with a very broad powder size distribution, the samples were able to remain flat through sintering. This experimental result is reflected in the present simulation results, which incorporated particle size distribution effects. In general, sintering functionally gradient ceramics can often introduce defects. Despite these common problems, the asymmetric structures considered in this paper featured a vertical functionality of continuously overlapping broad powder size distributions in the structure. This arrangement served to homogenize sintering rates. Modelling presented in connection with this shows that such structures can be readily sintered without warpage or cracking. To demonstrate these effects, a finite element method numerical simulation was developed to model the sintering characteristics of porous asymmetric ceramic structures by incorporating the powder particle size distribution into the model as a field variable. This work presents novel advances in the sintering model such that the contributions to the desired product properties attributable to particle size distribution effects can be demonstrated. These additions to the model produce numerical results which properly match observed structural profiles of physical samples.

Suspended sediment sources in two small lowland agricultural catchments in the UK

In recent years there has been increasing recognition of the need to include sediment control strategies within catchment management plans. Information on the source of the sediment transported by a river is an important requirement for designing effective sediment control strategies. This paper uses the source fingerprinting approach to establish suspended sediment sources within two small (<4 km 2) lowland agricultural catchments in the UK, which are both extensively under drained. Representative samples of suspended sediment were collected from both catchments to encompass the expected inter- and intra-storm variability in sediment source. Statistically verified composite fingerprints and multivariate mixing models, incorporating particle size correction factors, were used to estimate the relative contribution of the potential sediment sources. These included surface sources (classified by land use, geology and soil type), eroding channel banks and field drains (subsurface sources). Field drains were shown to be important suspended sediment sources in both catchments, accounting for 27–55% of the sediment yields. Bank erosion contributes ca. 10% or less of the sediment yields. Surface sources were found to be important in both catchments contributing between 34–65% of the sediment yield. The above estimates of the relative contribution of the individual sediment sources within the study catchments to the overall sediment yield were shown to conceal significant inter- and intra-storm variability in the source contributions.

Effect of particle size and temperature on evolution rate of volatiles from coal

Pyrolysis runs were carried out in the temperature range ambient to 900°C and the particle size range +38 to −2360 μm on a low ash coal from the Waterberg area. Empirical correlations were established for the evolution rates of hydrogen, carbon monoxide and methane as a function of particle size and instantaneous temperature. The rate for hydrogen and carbon monoxide can be represented by an Arrhenius type equation incorporating particle size. The observations suggest that tar deposition is rate determining. The observations for the rate of evolution of methane suggest that it is governed by several complex reactions of which methanation and secondary cracking of tar are possibilities.

Model to predict aerial dispersal of bacteria during environmental release.

Risk assessment for genetically engineered bacteria sprayed onto crops includes determination of off-site dispersal and deposition. The ability to predict microbial dispersal patterns is essential to characterize the uncertainty (risk) associated with environmental release of recombinant organisms. Toward this end, a particle dispersal model was developed to predict recovery of bacteria on fallout plates at various distances and directions about a test site. The microcomputer simulation incorporates particle size distribution, wind speed and direction, turbulence, evaporation, sedimentation, and mortality, with a time step of 0.5 s. The model was tested against data reported from three field applications of nonrecombinant bacteria and two applications of recombinant bacteria. Simulated dispersal of 10(5) particles was compared with reported deposition measurements. The model may be useful in defining appropriate populations of organisms for release, methods of release or application, characteristics of a release site that influence containment or dispersal, and in developing an appropriate sampling methodology for monitoring the dispersal of organisms such as genetically engineered bacteria.