Model Of Mixture Research Articles

Multicomponent vapor-liquid equilibrium measurements and modeling of triethylene glycol, water, and natural gas mixtures at 6.0, 9.0 and 12.5 MPa

Triethylene glycol (TEG) is commonly used for natural gas dehydration, and with subsea processing facilities on the rise, an increasing interest is being shown in complex phase equilibria involving petroleum fluids and polar compounds. In this study, examples of such phase equilibria have been studied. New measurements for multicomponent vapor-liquid equilibrium (VLE) of TEG/Water/Natural Gas systems have been performed at pressures ranging from 6.0 MPa to 12.5 MPa and temperatures in the range 15 °C to 40 °C. Two types of natural gas, a Synthetic Gas (xCH4=0.62) and a Real Gas (xCH4=0.92), were mixed with an aqueous TEG solution, with TEG weight percentages ranging from 95 wt.% to 99 wt.%. Glycol in gas (y1), water in gas (y2), and gas solubility in liquid (xNG) were measured with relative experimental uncertainties below 32%. Since the systems are highly associating, the Cubic-Plus-Association (CPA) equation of state (EoS) was selected to model their phase behavior . Different association schemes (4C, 4F, 5F, 6F and 5C) were tested for TEG, and the classical 4C scheme is shown to perform best. The CPA EoS performed in general terms well, considering the number of components in the systems, the associated complexities, and high measurement uncertainty for such low concentrations (<1 ppm) in the gas phase. Furthermore, the content of N2, CO2, CH4 and ethane were modelled in the liquid phase at various conditions.

Derivation and analysis of a phase field crystal model for a mixture of active and passive particles

We discuss an active phase field crystal (PFC) model that describes a mixture of active and passive particles. First, a microscopic derivation from dynamical density functional theory is presented that includes a systematic treatment of the relevant orientational degrees of freedom. Of particular interest is the construction of the nonlinear and coupling terms. This allows for interesting insights into the microscopic justification of phenomenological constructions used in PFC models for active particles and mixtures, the approximations required for obtaining them, and possible generalizations. Second, the derived model is investigated using linear stability analysis and nonlinear methods. It is found that the model allows for a rich nonlinear behavior with states ranging from steady periodic and localized states to various time-periodic states. The latter include standing, traveling, and modulated waves corresponding to spatially periodic and localized traveling, wiggling, and alternating peak patterns and their combinations.

Review of Visualization Technique and Its Application of Road Aggregates Based on Morphological Features

The sustainable performance of asphalt pavement depends on the quality and mix design of road aggregates. Identifying aggregate morphology and size is a prerequisite step for material design and numerical modeling of asphalt mixtures. The paper aims to review the morphometric measurement, characteristic parameters and visualization technique of road aggregates. Types, calculation methods and advantages of aggregate morphological characteristics are highlighted. The applications of aggregate morphological features on the volumetric design, compaction processes, mechanical properties and size effect of asphalt mixtures are summarized. Although digital image processing technology has been studied for years, aggregates in the complex accumulation are still difficult to measure accurately. In the current research, the morphological parameters of aggregates remain diverse without a standard protocol. Compared to theoretical models, numerical models have more difficulties establishing irregular morphology features in the simulated specimens but provide a volume parameter closer to the real value. The future investigation of road performance under dynamic loading should account for the microscopic evolution of shape, orientation and distribution of aggregates over time.

Evaluation and calibration of dynamic modulus prediction models of asphalt mixtures for hot climates: Qatar as a case study

The dynamic modulus (|E*|) of asphalt mixtures is one of the most important inputs in Mechanistic-Empirical (ME) pavement analysis and design. Several models have been developed to predict the dynamic modulus based on mixture volumetrics and material properties. This study aimed to calibrate and validate two commonly used models (i.e., Hirsch model and Alkhateeb model) for predicting the dynamic modulus of asphalt mixtures in Qatar. Based on the study outcomes, the Hirsch model was found to have a high prediction performance of asphalt mixture moduli before calibration with a coefficient of determination (R2) of 87.2 % between predicted and measured values. This R2 value improved slightly after calibration to 89.2 %, Alkhateeb model, on the other hand, had a coefficient of determination of 70.8 % before calibration, which also improved to 89.2 % after calibration. The moduli predicted by the Hirsch model before and after calibration were employed in this study to perform a mechanistic-empirical analysis of the performance of various typical pavement sections in Qatar. According to the findings, the percentage change in the predicted fatigue damage due to the use of the calibrated Hirsch model reached more than 50 % with an average value of 17.33 %, while the percent change in rutting reached 14 % with an average value of 3.65 %. These results highlight the importance of using locally calibrated models for the dynamic modulus in order to improve performance predictions.

POROSITY, PERMEABILITY AND TORTUOSITY RELATIONSHIP IN BINARY SPHERICAL PARTICALS

The complexity of processes in industry, which involved the formation of granular beds, has limited information about permeability (k), which is directly related with packing porosity ε and tortuosity T. For an understanding of the relationship between k, ε and T in mixed beds of particles that are different in size, simplified porous media model of binary mixture of spheres have been. A continuous function relating the porosity of a mixture (ε) with the volume fraction (xD) of binary mixture has been established. The incorporation of the proposed porosity model into the conventional Kozeny-Carmen equation gives a good agreement between the measured and predicted permeability vs.xD. Based on this relation and on the dependence of ε vs.xD, a model predicted tortuosity and permeability was obtained, having demonstrated that the tortuosity may significantly alter the permeability of a mixed bed. This search is useful for transport phenomena analysis in granular beds as well as in engineering applications, such as deep bed filtration used for drinking water purification.

Calorimetry characterization and crystallization modelling of wax-based mixtures under isokinetic and non-isokinetic cooling

Characterization and modelling of wax crystallization must be carefully addressed to understand wax-oil organogels formation. During casting process of wax-based mixtures, wax crystallization occurs under concomitant non-constant and high cooling rates. In this study, the crystallization kinetics of two representative wax-based materials were studied by power-compensated Differential Scanning Calorimetry (DSC) with moderate-high cooling rates (from − 20 to − 200 °C min−1) in constant cooling rate (isokinetic) conditions and in simplified non-constant cooling rate (non-isokinetic) conditions. Analyses based on the evolution of the mass fraction of solid wax calculated from heat flow (DSC signal) show similar kinetics trend and enthalpy of crystallization for the different isokinetic conditions, but with a significant influence on the supercooling effects. Considering the limits of the classic Avrami kinetics modelling for high aspect ratio crystals and complex mixtures, a semi-empirical modelling approach of non-isokinetic cooling conditions in a differential form is proposed. The modelling shows a good correlation with experimental results.

Toward the Identification of Stoichiometric Models for Complex Reaction Mixtures

We present an approach to identify stoichiometric and kinetic models that accurately represent the composition data from batch experiments without a priori knowledge of candidate stoichiometries. Possible reactions between the measured species that fulfill mass balance constraints and pass a target factor analysis (TFA) test are considered. From the qualified reaction candidates, reaction networks are enumerated. Four kinetic models, including reversible and irreversible kinetics, are estimated for each reaction within a candidate network. The most accurate kinetic models for each network are chosen using the Bayesian information criterion. Reaction networks are subsequently ranked according to their regression sum of squares. The kinetic parameters of the most accurate networks are re-estimated in a centralized fashion against the measured concentrations. An F test between the networks’ regression sums of squares reveals the most accurate network. Two case studies are analyzed, involving three and six species participating in two and three reactions. The proposed algorithm identifies the actual stoichiometric and kinetic model for both systems.

Surface water contamination from pesticide mixtures and risks to aquatic life in a high-input agricultural region of Brazil

The environmental risks of pesticides found in surface waters of an important agricultural basin in Brazil were estimated by adopting two approaches: individual pesticides risk quotients (RQ) and concentration addition model for pesticide mixtures (∑RQs) contained in each water sample. Monitoring was carried out in the Mogi Guaçu River basin, Brazil, from October 2017 to May 2018. Four sampling points were selected in the Mogi Guaçu River and seven in its tributaries A multiresidue method with solid-phase extraction and subsequent analysis by UPLC-ESI-QqQ-MS/MS was developed to quantify 19 pesticides. Herbicides, except for simazine, presented the highest detection frequencies with values above 70%. Tebuthiuron was found in all 55 analyzed samples, presenting the highest concentration (6437 ng L−1) over the monitoring period. Fungicides and insecticides showed similar detection frequency (DF) values, ranging from 1.8% to 21.8%. Tebuconazole and carbofuran were the fungicides and insecticides most frequently detected, respectively. January 2018 sampling showed the highest total concentration of pesticides, differing from March 2018 and May 2018 (p < 0.05). The MG2 > TMG8 > MG1 > TMG6 sites showed the highest concentration total of pesticides while MG4 > TMG4 > TMG3 (p < 0.05) sites showed the lowest values: MG4 > TMG4 > TMG3 (p < 0.05). Most pesticide occurrences presented no risks to aquatic organisms. Only 19 out of the 175 pesticide occurrences > LOQ presented individual risks to aquatic biota. Contrary to the results obtained by the individual risk assessment, most pesticide mixtures presented risks to aquatic biota. In 36 out of the 55 samples analyzed during monitoring, pesticide mixtures presented risks to aquatic life.

Sorption of benzo(a)pyrene and of a complex mixture of petrogenic polycyclic aromatic hydrocarbons onto polystyrene microplastics

Microplastics (MPs) largely occur in aquatic ecosystems due to degradation of larger plastics or release from MP-containing products. Due to the hydrophobic nature and large specific surface of MPs, other contaminants, such as polycyclic aromatic hydrocarbons (PAHs), can potentially sorb onto MPs. Several studies have addressed the potential impact of MPs as vectors of PAHs for aquatic organisms. Therefore the role of MPs as sorbents of these compounds should be carefully investigated. The present study aimed to determine the sorption capacity of benzo(a)pyrene (B(a)P), as a model pyrolytic PAH, to polystyrene (PS) MPs of different sizes (4.5 and 0.5 μm). In addition, the sorption of PAHs present in the water accommodated fraction (WAF) of a naphthenic North Sea crude oil to 4.5 μm MPs was also studied as a model of a complex mixture of petrogenic PAHs that could appear in oil-polluted environments. The results indicated that 0.5 μm MPs showed higher maximum sorption capacity (Qmax) for B(a)P (145–242.89 μg/g) than 4.5 μm MPs (30.50–67.65 μg/g). From the WAF mixture, naphthalene was sorbed at a higher extent than the other PAHs to 4.5 μm MPs but with weak binding interactions (Kf = 69.25 L/g; 1/n = 0.46) according to the analysis of the aqueous phase, whereas phenanthrene showed stronger binding interactions (Kf = 0.24 L/g; 1/n = 0.98) based on the analysis of the solid phase. Sorption of PAHs of the complex WAF mixture to 4.5 μm MPs was relatively limited and driven by the hydrophobicity and initial concentration of each PAH. Overall, the results indicate that sorption estimations based solely on the analysis of the aqueous phase could overestimate the capacity of MPs to carry PAHs. Therefore, controlled laboratory assays assessing the “Trojan Horse effect” of MPs for aquatic organisms should consider these findings in order to design accurate and relevant experimental procedures.

Towards numerical simulation of high part load pulsations in Francis turbines

One of the most interesting operating points of Francis turbines is the high part load point, which is characterized by synchronous pressure pulsations of large amplitude. Physical mechanisms of these pulsations are not well understood. Experimental observations show that the frequency of the pulsations is 1.5 to 4 times higher than the runner rotation frequency and there exists a 180 degree phase shift of pressure signal measured in the spiral casing and in the draft tube. Numerical modeling this operating point is challenging as it has to account several complex phenomena: cavitation, rotating vortex rope and interaction of the turbine flow with the whole water system of the test rig. In the present paper we carried out a series of 1D-3D calculations of a model turbine in an attempt to simulate the high part load pulsations. 1D hydro-acoustic equations were used for the upstream waterways, while 3D Reynolds averaged Navier-Stokes model of two-phase mixture was used for the turbine. Although the main factors were taken into account, these computations were not able to capture the high part load pulsations. Namely, the frequency and amplitude of the pressure pulsations were significantly lower than those in the experiment, and there was no phase shift in turbine domain. In order to investigate the shortcomings of the present model, we considered a problem of propagation of disturbances in two-phase “liquid-gas” flows. Several 2D test cases were numerically investigated using both incompressible and compressible gaseous phase model. It was shown that in the absence of phase transfer the compressible model correctly represents the speed of sound in both homogeneous and stratified flow regimes. From the other hand, in case of phase transfer the model damps out propagation of pressure disturbances in upstream direction. This behavior explains the failure of the present 1D-3D model to correctly describe the acoustic properties of the two-phase flow in the draft tube, playing a crucial role in the development of high part load pulsations.

A Sensitivity-Enhanced Sensor Based on Zeroth-Order Resonance for Liquid Characterization

A high-sensitivity planar microfluidic sensor is proposed in this paper based on composite left/right-handed transmission line (CRLH TL). By employing the series zeroth-order resonance (ZOR), the resonance of proposed sensor is only determined by surface capacitance and inductance. The short-circuit structure reduces the energy loss due to edge radiation and generates a highly concentrated electric field on the top surface of the substrate, which can be used to detect the dielectric loading samples. The presented sensor has been simulated, fabricated and tested. The sensor on the printed circuit board (PCB) is integrated with the fluidic container made of polydimethylsiloxane (PDMS) to form the test device. The water-ethanol binary mixture and sucrose solution are used to proof the concept. Finally, the prediction model for the water-ethanol mixture based on measured parameters has been established and the analysis of prediction error has been carried out. The sensor works around 4 GHz, and the maximum sensitivity reaches 1.04. Due to the high sensitivity and simple structure, the proposed structure is a competitive candidate for the applications including bio-sensing and portable biomedical device.

Partition Constant of Binary Mixtures for the Equilibrium between a Bulk and a Confined Phase.

It is well-known that the thermodynamic, kinetic and structural properties of fluids, and in particular of water and its solutions, can be drastically affected in nanospaces. A possible consequence of nanoscale confinement of a solution is the partial segregation of its components. Thereby, confinement in nanoporous materials (NPM) has been proposed as a means for the separation of mixtures. In fact, separation science can take great advantage of NPM due to the tunability of their properties as a function of nanostructure, morphology, pore size, and surface chemistry. Alcohol-water mixtures are in this context among the most relevant systems. However, a quantitative thermodynamic description allowing for the prediction of the segregation capabilities as a function of the material-solution characteristics is missing. In the present study we attempt to fill this vacancy, by contributing a thermodynamic treatment for the calculation of the partition coefficient in confinement. Combining the multilayer adsorption model for binary mixtures with the Young equation, we conclude that the liquid-vapor surface tension and the contact angle of the pure substances can be used to predict the separation ability of a particular material for a given mixture to a semiquantitative extent. Moreover, we develop a Kelvin-type equation that relates the partition coefficient to the radius of the pore, the contact angle, and the liquid-vapor surface tensions of the constituents. To assess the validity of our thermodynamic formulation, coarse grained molecular dynamics simulations were performed on models of alcohol-water mixtures confined in cylindrical pores. To this end, a coarse-grained amphiphilic molecule was parametrized to be used in conjunction with the mW potential for water. This amphiphilic model reproduces some of the properties of methanol such as enthalpy of vaporization and liquid-vapor surface tension, and the minimum of the excess enthalpy for the aqueous solution. The partition coefficient turns out to be highly dependent on the molar fraction, on the interaction between the components and the confining matrix, and on the radius of the pore. A remarkable agreement between the theory and the simulations is found for pores of radius larger than 15 Å.

Spatially Varying BRDF Map Filtering

In recent years, the use of spatially varying bidirectional reflectance distribution function (SVBRDF) textures has been steadily increasing in real-time rendering. To reduce aliasing, it is necessary to prefilter SVBRDF textures before rendering. A comprehensive filtering algorithm is proposed that considers the contribution of each component of the SVBRDF texels. First, the weight of each texel is defined as the sum of the luminance of its diffuse albedo and specular albedo. Next, the model of mixture of von Mises-Fisher (vMF) is examined and weighting mechanism is added to it. Finally, by heuristically choosing the initial values for the <italic>k</italic>-means algorithm, an improved method for calculating SVBRDF Mipmap in a bottom-up fashion is proposed. To evaluate the algorithm, 4 SVBRDF materials with different microscopic normal distributions are crafted by hand. When rendering complex SVBRDF materials, the proposed method could achieve an RMSE value 25.5% lower than that of the reference algorithm. When changing the number of fitted lobes, the proposed algorithm can obtain a better result with 2 vMF lobes than previous methods with 4 lobes.

Integrated Exposure and Algal Ecotoxicological Assessments of Effluents from Secondary and Advanced-Tertiary Wastewater-Treatment Plants.

The great concern over the environmental impact of wastewaters has led to the designing of advanced treatment processes to upgrade conventional treatment plants and achieve a significant reduction of contaminants in receiving waters. In the present study we combined chemical and ecotoxicological analyses, aiming to evaluate the reduction of toxicity effects associated with the removal of micropollutants and to define the contribution of the detected compounds to the overall toxicity of the mixtures in a series of wastewater effluents collected from a secondary treatment (OUT 2) and from a tertiary activated carbon treatment (OUT 3) plant. The target compounds were selected after a screening procedure among pharmaceuticals, musk fragrances, and trace metals. The classical algal growth inhibition test was conducted on the original effluent samples and on different fractions obtained by solid-phase extraction (SPE) treatment. A good accordance was found between the removal of toxicity (30%-80%) and organic compounds (70%-80%) after the tertiary treatment, suggesting its high efficiency to improve the wastewater quality. The discrepancy between the contribution to the overall toxicity of the nonadsorbable compounds (i.e., inorganic or very polar organic compounds) as experimentally measured by the SPE bioassays (18%-76%) and calculated by the concentration addition approach (>97%) could be mitigated by including the bioavailability correction in metal-toxicity modeling of wastewater mixtures. For the organic compounds, the toxic equivalency method enabled us to quantify the portion of toxicity explained by the detected chemicals in both OUT 2 (82%-104%) and OUT 3 (5%-57%), validating the selection of the target molecules. The applied integrating approach could be implemented by the inclusion of both additional target chemicals and toxicity endpoints. Environ Toxicol Chem 2022;41:2404-2419. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Viscosity Deviation Modeling for Binary and Ternary Mixtures of Benzyl Alcohol-N-Hexanol-Water.

Knowing the thermodynamic and transport properties of liquid systems is very important in engineering for the development of theoretical models and for the design of new technologies. Models that allow accurate predictions of thermodynamic and transport properties are needed in chemical engineering calculations involving fluid, heat, and mass transfer. In this study, the modeling of viscosity deviation for binary and ternary systems containing benzyl alcohol, n-hexanol, and water, less studied in the literature, was carried out using Redlich and Kister (R-L) models, multiple linear regression (MLR) models and artificial neural networks (ANN). The viscosity of the binary and ternary systems was experimentally determined at the following temperatures: 293.15, 303.15, 313.15, and 323.15 K. Viscosity deviation was calculated and then correlated with mole fractions, normalized temperature, and refractive index. The neural model that led to the best performance in the testing and validation stages contains 4 neurons in the input layer, 12 neurons in the hidden layer, and one neuron in the output layer. In the testing stage for this model, the standard deviation is 0.0067, and the correlation coefficient is 0.999. In the validation stage, a deviation of 0.0226 and a correlation coefficient of 0.996 were obtained. The MLR model led to worse results than those obtained with the neural model and also with the R-L models. The standard deviation for this model is 0.099, and the correlation coefficient is 0.898. Its advantage over the R-L type models is that the influence of both composition and temperature are included in a single equation.

Modified couple stress theory for wave propagation in viscoelastic sandwich microplates with FG-GPLRC core and piezoelectric face sheets as sensor and actuator

In the present investigation, wave propagation of the viscoelastic sandwich microplates with functionally graded graphene nanoplatelets’ reinforced composite (FG-GPLRC) core and piezoelectric face sheets as sensor and actuator has been analyzed by the refined zigzag theory (RZT). Electromagnetic field is exposed to core and piezoelectric layers. Young's modulus, mass density, and Poisson's ratio are calculated based on the modified Halpin–Tsai model and rule of mixtures because FG-GPLs are arranged as uniform, parabolic, and linear patterns along the thickness of core. In addition, viscoelastic properties of the structure are simulated by the Kelvin–Voigt model. The system is located on an orthotropic visco Pasternak medium. The modified couple stress theory (MCST) is applied to simulate the microscale effects of the structure. Hamilton's principle is utilized for deriving the motion equations. Phase velocity, cut-off, and escape frequencies are computed with an analytical solution. The influence of valuable parameters, such as geometrical dimensions of the system, magnetic field, external voltage, small scale parameter, viscoelastic structural damping coefficient, various foundation types, weight fraction, and different distributions of GPLs on phase velocity, will be studied. The results of this study have a significant effect on the design and fabrication of sandwich micro-structures used in various industrial equipment.

Giant Dipole Multi-Resonances Excited by High-Frequency Laser Pulses

The worldwide advent of new laser facilities makes possible the investigation of the nuclear response to a very strong electromagnetic field. In this paper, we inquire on the excitation of one of the most conspicuous collective excitations, the giant dipole resonance, within the hydrodynamical model for a proton-neutron fluid mixture placed in a Skyrme mean-field and interacting with an external ultra-strong electromagnetic field. The variables of this approach are: proton and neutron displacement (velocity) fields, density fluctuations, and fluctuations of the electric field due to the coupling of the laser electromagnetic field to the dynamical distortions of the baryonic system (electro-magneto-hydrodynamical effect). We point out the occurrence of a multiresonance structure of the absorption cross-section.

Erratum: “Comment on ‘Kinetic theory models for granular mixtures with unequal granular temperature: Hydrodynamic velocity’” [Phys. Fluids 33, 043321 (2021)

First Page

Experimental-based modeling of complex mixtures

The generalized bracket approach to non-equilibrium thermodynamics (NET) is a mesoscopic, microstructure-based framework that allows one to formulate the transport equations in a thermodynamically consistent manner and relate the flow kinematics and mechanical properties to the different length and time scales of the structural components.In this talk, I will present an extension of this framework to mixtures that include components with different physicochemical properties and mixing behaviors. While immiscible and miscible fluids have been described using different approaches in the past, this framework can successfully cover the entire range of miscibility, as confirmed by comparing our OpenFOAM predictions with Y-shaped microchannel measurements. One of the challenges of dealing with multicomponent materials is accounting for their interactions, and frequent backtesting against experimental data is essential. In the future, we will use our OpenFOAM implementation for large-scale simulations of real-world engineering applications such as liquid-liquid extraction.

Packing density of limestone calcined clay binder

The partial substitution of Portland cement by a mixture of calcined clays and limestone fillers offers a promising way to reduce the environmental impact of concrete while improving its long-term mechanical performance and durability properties. However, the literature shows that calcined clays can display a higher water demand than Portland cement, which implies the use of additional mixing water or superplasticizer to maintain appropriate workability. This study aims to determine the optimal proportion of ternary mixes, i.e. cement, calcined clays and limestone fillers, in order to obtain the highest possible packing density influencing the water demand. The associated experiments were conducted with one CEM I, two metakaolins (calcined clay) and three limestone fillers. Optimization was performed using the Compressible Packing Model of granular mixtures, which notably considers the grain size distribution and virtual packing densities (βi) of the various materials. In conjunction with this model, the tests carried out on pastes of normal consistency controlled by the Vicat apparatus or the spread of mortars show that the type and amount of metakaolin used have a high impact on compactness given their particularly low virtual packing densities (βi). Moreover, this study demonstrates that the addition of limestone fillers improves packing density, but the grain size distribution proves not to be the key parameter, especially in mortars. Lastly, when the water demand of the metakaolin is high, a large limestone proportion (30% vol.) allows significantly enhancing the spread and manufacturing mortars with a compressive strength of close to 32.5 MPa at 28 days.