Multicomponent Model Research Articles

Numerical modeling to assess the effect of soil texture on transport and attenuation of petroleum hydrocarbons in unsaturated zone.

Soil texture in the unsaturated zone is a critical factor affecting the transport, accumulation, and attenuation rate of petroleum hydrocarbons (PHCs) in unsaturated conditions. The scope of this study is to investigate the soil texture impact on the fate of PHCs in unsaturated zones. The main objective is to formulate a coupled flow and multicomponent transport model for simulating the PHC plumes in various soil textures. Zeroth spatial moment (ZSM) of simulated PHC plumes is estimated to quantify the transient effect of soil textures on the dissolved PHC mass in the system. A BTEX (benzene, toluene, ethylbenzene, and xylene) spill is considered at the source zone for modeling. Simulations are carried out for clay, sand, and loam textures. The outcome of the study suggests that the infiltration rate in the unsaturated zone is minimal in clay texture. Wetting front depths and BTEX source depletion rates are found to be in the following order: clay < loam < sand. The migration depth of BTEX components in the sand texture is approximately twice the depth for clay and loam after 50days. An increment in the BTEX source zone length by twofold enhances the dissolved BTEX mass in the unsaturated system by approximately 33% in all soil textures. Overall, the modeling and sensitivity studies conclude that the soil texture, vertical dispersivity, source zone length and composition, sorption characteristics, and volatility critically affect the depth and extent of BTEX migration in unsaturated zones.

Particle force-based density segregation theory for multi-component granular mixtures in a periodic chute flow

Density segregation of multi-component granular mixtures in a dense, gravity-driven flow over a rough and bumpy periodic chute surface is studied using theory and simulations. An existing theoretical model for predicting the steady-state concentration field of each species in a binary mixture using the forces acting on the particles is generalised for multi-component mixtures in this work. In addition, the rheological model for binary mixtures is also extended to multi-component mixtures. In contrast to the percolation velocity-based empirical segregation models that do not account for the rheology and need prior knowledge of the velocity field, the present approach accounts for the inter-coupling of rheology with segregation. The momentum balance equations are solved, along with the mixture rheological model as well as the multi-component density segregation model, to obtain concentration fields using an iterative numerical method. The theoretical predictions are compared with discrete element method (DEM) simulations for ternary, quaternary and quinary granular mixtures differing in density. The steady-state profiles for the concentration of different species as well as other flow properties predicted from the theory are in excellent agreement with the DEM simulation results for a variety of compositions over a range of inclination angles for different density ratios. Through this work, we take the first essential step towards proposing a generalised particle force-based segregation theory for multi-component mixtures differing in size and/or density.

A numerical study on chloride transport in alkali-activated fly ash/slag concretes

Alkali-activated binders for concrete composites are emerging as the available low-embodied-carbon alternatives to ordinary Portland cement (OPC). Despite decades of research, the durability of alkali-activated concrete remains a concern, especially the issues related to chloride penetration and the potential for chloride-induced corrosion of embedded steel bars. In this study, a multi-phase, multi-component ionic numerical model is developed to investigate the chloride transport in alkali-activated fly ash/slag (AAFS) concretes. The model framework considers the porosity of concrete, the chloride binding, and the electrochemical coupling between multi-species. Based on the proposed model, the parametric studies of a series of influencing factors on both chloride transport and initiation time of reinforcement corrosion are performed and discussed. The results indicate that the slag content and the water to binder ratio are the dominant factors affecting chloride penetration and corrosion initiation time of steel bars in AAFS concretes due to their greater contributions to reduce the porosity, while the aggregate volume fraction presents a limited effect compared with other factors. The transport model proposed in this study brings insights to the prediction of the service life of alkali-activated reinforced concrete structures.

Advancing textural heterogeneity: Effect of manipulating multi-component model foods on the perception of textural complexity

The aim of this study was to identify the individual and interacting effects of varying the mechanical properties of two inserts (к-carrageenan beads; 1, 2 and 4% w/w and/or agar-based disks; 0.3, 1.2 and 3% w/w) in pectin-based gels on the perception of textural complexity.A full factorial design was utilised, 16 samples were characterised with sensory and instrumental tests. Rate-All-That-Apply (RATA) was performed by 50 untrained participants. RATA selection frequency provided different information to attribute intensity regarding the detection of low yield stress inserts.In the two-component samples, the perception of textural complexity (n = 89) increased with insert yield stress for both к-carrageenan beads and agar disks. However, with the addition of medium and high yield stress к-carrageenan beads to three-component samples, the increases in perceived textural complexity caused by increased agar yield stress were eliminated.The definition of textural complexity, the number and intensity of texture sensations, as well as their interactions and contrasts, was in line with the results, and the hypothesis that not only mechanical properties but also the interaction of components play a key role in the perception of textural complexity.

Thermodynamically consistent phase-field modelling of activated solute transport in binary solvent fluids

Active diffusion of substances in binary immiscible and incompressible fluids with different densities occurs universally in nature and industry, but relevant mathematical models and numerical simulation have been studied scarcely so far. In this paper, a thermodynamically consistent phase-field model is established to describe the activated solute transport in binary fluids with different densities. A mixed free-energy function for multiple solutes is proposed, which leads to different solute chemical potentials in binary solvent fluids, thus it has the ability to characterize the solubility difference of the solutes in two solvents. The two-phase flow is governed by a general hydrodynamic phase-field model that can account for general average velocity and different densities. The proposed model is derived rigorously using the second law of thermodynamics. Moreover, a general multi-component solute diffusion model is established using the Maxwell–Stefan approach, which involves the crossing influences between different solutes. To solve the model effectively, an efficient, linearized and decoupled numerical method is proposed for the model as well. The proposed numerical method can preserve the thermodynamical consistency, i.e. obeying an energy dissipation law at the discrete level, as well as guarantee the mass conservation law for the solutes and solvent fluids. Numerical experiments are carried out to show that the proposed model and numerical method can simulate various processes of the solute active diffusion in two-phase solvent fluids.

Simplified Approach to the Parameterization of the NRTL Model for Partially Miscible Binary Systems: Tττ LLE Methodology

A new approach to parameterizing the NRTL model for binary liquid–liquid equilibria (LLE) is presented. It allows for the incorporation of a priori knowledge into the parameterization procedure rather than using the “black box” approach often employed. The method first converts the compositional Txx data to a set of unique binary interaction parameters, Tττ data. Thereafter, the second step improves the parameterization of frequently used temperature-dependent parameters (TDPs) by reducing the traditional nonlinear regression problem to simpler linear regression. This method is less susceptible to poor initial guesses, finding local minima, and significantly reduces computational requirements, with comparable/improved performance to published parameters. A total of 29 binary systems, including upper and/or lower critical solution temperatures, were evaluated using the approach to provide generalized recommendations and understanding of the TDP requirements for each system type. Inclusion of such information and use of the approach will significantly simplify multicomponent LLE model parameterization.

Solidification modes during additive manufacturing of steel revealed by high-speed X-ray diffraction

Solidification during fusion-based additive manufacturing (AM) is characterized by high solidification velocities and large thermal gradients, two factors that control the solidification mode of metals and alloys. Using two synchrotron-based, in situ setups, we perform high-speed X-ray diffraction measurements to investigate the impact of the solidification velocities and thermal gradients on the solidification mode of a hot-work tool steel over a wide range of thermal conditions of relevance to AM of metals. The solidification mode of primary δ-ferrite is observed at a cooling rate of 2.12 × 104 K/s, and at a higher cooling rate of 1.5 × 106 K/s, δ-ferrite is suppressed, and primary austenite is observed. The experimental thermal conditions are evaluated and linked to a Kurz-Giovanola-Trivedi (KGT) based solidification model. The modelling results show that the predictions from the multicomponent KGT model agree with the experimental observations. This work highlights the role of in situ XRD measurements for a fundamental understanding of the microstructure evolution during AM and for validation of computational thermodynamics and kinetics models, facilitating parameter and alloy development for AM processes.

Importance of Social Support of Parents of Children with Cancer: A Multicomponent Model Using Partial Least Squares-Path Modelling.

The purpose of the present study is to build a model combining some variables that have been previously studied separately to improve our understanding on how they relate in parents of children with cancer. A total of 112 parents with an average age of 41 completed the self-assessment questionnaires containing the factors studied: social support received, social support provided, stress, adjustment of parents and life satisfaction. Two models were developed: one for social support received and one for social support provided. Structural equation models based on the variance estimated through partial least squares were used to analyze factors involved in quality of life based on an exploratory model of second order. The estimated model was robust in terms of quality of measurement (reliability and validity). According to results from the structural model, in the model of social support received, the impact of social support received on stress was considerable (β = -0.26; p = 0.02) and it explained 16% of the variance. The impact of social support received by parents on their adjustment (β = -0.56; p < 0.001) was also considerable, explaining 32% of the variance. Finally, adjustment of parents also showed an effect on life satisfaction (β = -0.33; p < 0.001) and it explained 26% of the variance. However, the relation between social support received (β = 0.15; p = 0.11) and life satisfaction, the relation between stress (β = -0.15; p = 0.08) and life satisfaction, and the relation between adjustment of parents (β = 0.20; p = 0.07) and stress were not significant. In the model of social support provided by parents, social support provided (β = 0.35; p < 0.001), and adjustment of parents (β = -0.31; p < 0.01) impacted life satisfaction, explaining 36% of the variance. Social support provided (β = -0.34; p < 0.01) impacted adjustment of parents and it explained 12% of the variance. Adjustment of parents (β = 0.28; p < 0.05) also impacted parents' perception of stress, explaining 14% of the variance. However, the relation between social support provided (β = -0.17; p = 0.06) and stress, and the relation between stress (β = -0.13; p = 0.08) and life satisfaction, were not significant. Social support received showed a strong connection with stress and parents' adjustment. Additionally, social support received showed a decrease in stress and parents' adjustment. Social support provided by parents and the adjustments they experience are linked to their life satisfaction. Additionally, social support provided showed a decrease in adjustment and an increase in parents' life satisfaction. The models can be used to improve parents' situations and it has strong practical implications.

Pore-scale simulation of gas displacement after water flooding using three-phase lattice Boltzmann method

Water flooding is a commonly used technique to improve oil recovery, although the amount of oil left in reservoirs after the procedure is still significant. Gas displacement after water flooding is an effective way to recover residual oil, but the occurrence state and flow principles of multiphase fluid after gas injection are still ambiguous. Therefore, the gas displacement process after water flooding should be studied on the pore scale to provide a basis for formulating a reasonable gas injection program. Most of the current pore-scale studies focus on two-phase flow, while simulations that account for the influence of oil-gas miscibility and injected water are seldom reported. In this work, the multi-component multi-phase Shan-Chen lattice Boltzmann model is used to simulate the gas displacement after water flooding in a porous medium, and the effects of injected water, viscosity ratio, pore structure, and miscibility are analyzed. It is established that the injected water will cause gas flow path variations and lead to premature gas channeling. Under the impact of capillary pressure, the water retained in the porous medium during the water flooding stage further imbibes into the tiny pores during gas injection and displaces the remaining oil. When miscibility is considered, the oil-gas interface disappears, eliminating the influence of the capillary effect on the fluid flow and enabling the recovery of remaining oil at the corner. This study sheds light on the gas displacement mechanisms after water flooding from the pore-scale perspective and provides a potential avenue for improving oil recovery. Cited as: Wang, S., Chen, L., Feng, Q., Chen, L., Fang, C., Cui, R. Pore-scale simulation of gas displacement after water flooding using three-phase lattice Boltzmann method. Capillarity, 2023, 6(2): 19-30. https://doi.org/10.46690/capi.2023.02.01

Multicomponent numerical model for heat pump control with low-temperature heat storage: A benchmark in the conditions of Central Europe

This paper presents a computational parametric study on increasing the Seasonal Coefficient of Performance for residential heat pumps, utilizing an enhanced computational model and comparing it to previous research. The model computes a system that consists of a heat pump, low-temperature heat storage, heat exchanger and circulation pump, and a control unit which allows the heat pump to choose either low-temperature heat storage or ambient air as the favorable heat source. A parametric study is conducted to obtain results from a numerical model describing in detail the heat storage, surrounding soil, and the behavior of a water tank with and without temperature stratification and with two different geometries. These are combined into three different systems. Each system uses an algorithm for heat pump control that combines equithermal regulation and deferred heat storage discharging based on long-term temperature trends. Python is used to transform the numerical model into a computational model, and the assessment of heat pump operation is made based on meteorological data from the years 2012–2021 recorded in the city of Brno, Czech Republic, Central Europe. Previous studies have suggested that this combination for heat pump control and a more detailed numerical model of the system should result in a SCOP increase. In this study, heat losses of an actual occupied building with floor area of 140 m2 without considering heat radiation are used. The results show that stratification cannot be omitted for numerical modelling, and that the geometry of the storage influences how the storage should be designed. For a wide and shallow storage, it is better to insulate the system and increase the SCOP from 3.8 to 4.65, but non-insulated deep and narrow storage can increase the from 3.8 to 4.95. Flow rate is also an important parameter with a local maximum between 0.01 and 0.02 kg/s for every cubic meter of the storage. When a system consisting of parts readily available on the market is used at optimal conditions, the resulting increase can be from 11.8% up to as high as 25.7% with low-temperature heat storage ranging from 9 to 25 cubic meters.

The multicomponent diffuse-interface model and its application to water/air interfaces

Fundamental properties of the multicomponent diffuse-interface model (DIM), such as the maximum entropy principle and conservation laws, are used to explore the basic interfacial dynamics and phase transitions in fluids. Flat interfaces with monotonically changing densities of the components are proved to be stable. A liquid layer in contact with oversaturated but stable vapour is shown to either fully evaporate or eternally expand (depending on the initial perturbation), whereas a liquid in contact with saturated vapour always evaporates. If vapour is bounded by a solid wall with a sufficiently large contact angle, spontaneous condensation occurs in the vapour. The external parameters of the multicomponent DIM – e.g. the Korteweg matrix describing the long-range intermolecular forces – are determined for the water/air combination. The Soret and Dufour effects are shown to be negligible in this case, and the interfacial flow, close to isothermal.

Noncompact lattice Higgs model with Abelian discrete gauge groups: Phase diagram and gauge symmetry enlargement

We study the phase diagram and phase transitions of the three dimensional multicomponent lattice Higgs model with noncompact Abelian discrete groups. The model with noncompact U(1) gauge group is known to undergo, for a sufficiently large number of scalar fields $N$, a continuous transition associated to the charged fixed point of the continuous Abelian Higgs field theory. We show that in the model with gauge group ${\mathbb{Z}}_{q}^{(nc)}\ensuremath{\equiv}2\ensuremath{\pi}\mathbb{Z}/q$ only critical transitions in the orthogonal universality classes are present for small values of $N$, while a symmetry enlargement to the continuous Abelian Higgs universality class happens when $q\ensuremath{\ge}5$ and $N$ is large enough.

On estimating parameters of a multi-component Chirp Model with equal chirp rates

Multi-component chirp signal models with equal chirp rates appear in various radar applications, e.g., synthetic aperture radar, echo signal of a rapid mobile target, etc. Many sub-optimal estimators have been developed for such models, however, these suffer from the problem of either identifiability or error propagation effect. In this paper, we have developed theoretical properties of the least squares estimators (LSEs) of the parameters of multi-component chirp model with equal chirp rates, where the model is contaminated with linear stationary errors. We also propose two computationally efficient estimators as alternative to LSEs, namely sequential combined estimators and sequential plugin estimators. Strong consistency and asymptotic normality of these estimators have been derived. Interestingly, it is observed that sequential combined estimator of the chirp rate parameter is asymptotically efficient. Extensive numerical simulations have been performed, which validate satisfactory computational and theoretical performance of all three estimators. We have also analysed a simulated radar data with the help of our proposed estimators of multi-component chirp model with equal chirp rates, which performs efficiently in recovery of inverse synthetic aperture radar (ISAR) image of a target from a noisy data.

PORE SCALE INVESTIGATION ON THE EFFECT OF TEMPERATURE ON THREE-PHASE REACTIVE FLOW IN POROUS MEDIA USING THE LATTICE BOLTZMANN METHOD

In this study, the process of carbonate rock acidification with three-phase immiscible fluid &amp;#91;water, oil, and supercritical carbon dioxide (scCO&lt;sub&gt;2&lt;/sub&gt;)&amp;#93; reactive flow in nonisothermal condition at pore scale was simulated by the lattice Boltzmann method (LBM). The three immiscible fluids' flow, solute transport, and heat transfer were solved by the Shan-Chen multiphase multicomponent lattice Boltzmann model, mass transport lattice Boltzmann model, and multicomponent thermal lattice Boltzmann model, respectively. The solid phase was updated by the volume-of-pixel method. In addition, the effect of temperature on the multiphase multicomponent reactive flow was numerically investigated. The results show that the dissolution rate is determined by three-phase distribution. The increase of temperature can accelerate the dissolution rate and decrease the inhibition influence of the non-acid phase on dissolution. Furthermore, the influence of temperature decreases with the increase of inlet velocity and oil wettability.

A Dynamic Maintenance Strategy for Multi-Component Systems Using a Genetic Algorithm

In multi-component systems, the components are dependent, rather than degenerating independently, leading to changes in maintenance schedules. In this situation, this study proposes a grouping dynamic maintenance strategy. Considering the structure of multi-component systems, the maintenance strategy is determined according to the importance of the components. The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements. First, multi-component models are grouped. Then, a failure probability model of multi-component systems is established. The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components. Second, the component importance indicator is introduced into the grouping model, and the optimization model, which aimed at a maximum economic profit, is established. A genetic algorithm is used to solve the non-deterministic polynomial (NP)-complete problem in the optimization model, and the optimal grouping is obtained through the initial grouping determined by random allocation. An 11-component series and parallel system is used to illustrate the effectiveness of the proposed strategy, and the influence of the system structure and the parameters on the maintenance strategy is discussed.

Estimation of reliability in multicomponent stress-strength based on exponential Frechet distributions

When strength and stress variables follow the exponential Frechet distribution with different shape parameters and common scale parameters, the multicomponent stress-strength reliability model of an s-out-of-k system is studied in this paper. Based on samples from stress and strength distributions, the maximum likelihood estimation of the model parameters is obtained. The asymptotic confidence interval for the system reliability is also calculated. The comparison of the reliability estimates based on small sample is given by Monte-Carlo simulation.

Simultaneous removal of Methylene Blue and Direct Blue 71 with Pb(II) ions from multi-component systems: application of the multi-component Langmuir model

Simultaneous removal of Methylene Blue and Direct Blue 71 with Pb(II) ions from multi-component systems: application of the multi-component Langmuir model

Competitive Removal of Perchlorate Ions by Quaternary Amine Modified Reed in the Presence of Nitrate and Phosphate

We report a kinetic and equilibrium study in which we examined the removal of perchlorate anions from water by adsorption onto modified reed (MR), an adsorption material constituted by giant reed (GR) particles whose anion adsorption properties have been enhanced by quaternary amine (QA) crosslinking. In particular, we examined how MR adsorption of perchlorate interacts competitively with concomitant adsorption of agriculture-derived phosphate and nitrate contaminants. Equilibrium and pH experiments were first conducted in single-component systems, the results of which were best described by the Langmuir-Freundlich (L-F) isotherm. Subsequent analyses of competitive effects on adsorption showed that although MR had a higher adsorption capacity for perchlorate alone than for nitrate or phosphate alone, the addition of either phosphate or nitrate to a perchlorate solution had a diminishing effect on MR adsorption of perchlorate within a natural-water pH range, with phosphate having the stronger competitive effect. Perchlorate adsorption on MR varied inversely with competing ion concentrations, providing direct evidence of the perchlorate diminution effect being attributable to anion competition. Finally, we developed a multicomponent isotherm model that describes the binary adsorption of perchlorate in the presence of each of these competing anions. The results of this work provide perchlorate removal efficiency information that is directly applicable to the design of water treatment systems.

High friction limits of Euler–Navier–Stokes–Korteweg equations for multicomponent models

High friction limits of Euler–Navier–Stokes–Korteweg equations for multicomponent models

Successful ingredients of effective Collaborative Care programs in low- and middle-income countries: A rapid review.

Integrating mental health care in primary healthcare settings is a compelling strategy to address the mental health treatment gap in low- and middle-income countries (LMICs). Collaborative Care is the integrated care model with the most evidence supporting its effectiveness, but most research has been conducted in high-income countries. Efforts to implement this complex multi-component model at scale in LMICs will be enhanced by understanding the model components that have been effective in LMIC settings. Following Cochrane Rapid Reviews Methods Group recommendations, we conducted a rapid review to identify studies of the effectiveness of Collaborative Care for priority adult mental disorders of mhGAP (mood and anxiety disorders, psychosis, substance use disorders and epilepsy) in outpatient medical settings in LMICs. Article screening and data extraction were performed using Covidence software. Data extraction by two authors utilized a checklist of key components of effective interventions. Information was aggregated to examine how frequently the components were applied. Our search yielded 25 articles describing 20 Collaborative Care models that treated depression, anxiety, schizophrenia, alcohol use disorder or epilepsy in nine different LMICs. Fourteen of these models demonstrated statistically significantly improved clinical outcomes compared to comparison groups. Successful models shared key structural and process-of-care elements: a multi-disciplinary care team with structured communication; standardized protocols for evidence-based treatments; systematic identification of mental disorders, and a stepped-care approach to treatment intensification. There was substantial heterogeneity across studies with respect to the specifics of model components, and clear evidence of the importance of tailoring the model to the local context. This review provides evidence that Collaborative Care is effective across a range of mental disorders in LMICs. More work is needed to demonstrate population-level and longer-term outcomes, and to identify strategies that will support successful and sustained implementation in routine clinical settings.