Double pyrovanadates CaMgV2O7: Formation mechanism,phase structure,and thermodynamic properties

A double pyrovanadate CaMgV₂O₇ sample was synthesized via a facile solid-state route under an air atmosphere. The nonequilibrium formation pathways of the CaMgV₂O₇ were investigated via powder X-ray diffraction. A multistep reactions path (metavanadates–pyrovanadates–double pyrovanadate CaMgV₂O₇) was proposed to describe the formation of the CaMgV₂O₇ considering the thermodynamic and kinetic factors. The cell unit parameters of the CaMgV₂O₇ sample indicated the crystallization according to a monoclinic system with space group P12/c1(14), and the lattice parameters of a = 6.756 Å, b = 14.495 Å, c = 11.253 Å, β = 99.12, and V = 108.806 Å³. X-ray photoelectron spectroscopy also confirmed the +5 oxidation state vanadium in CaMgV₂O₇. The endothermic effects at 1033 and 1143 K were related to the incongruent melting and liquidus temperatures of CaMgV₂O₇, respectively. The comprehensive thermodynamic properties of CaMgV₂O₇ were established in both low- and high-temperature regions, utilizing a physical property measurement system and multi-high-temperature calorimetry (96 lines). The heat capacity (200 J mol K⁻¹) and entropy (198 J mol K⁻¹) at 298.15 K were computed based on the low-temperature heat capacity values, and the enthalpy of formation at 298.15 K was also estimated. The fitted high-temperature capacity can be used to obtain the changes in the enthalpy, entropy, and Gibbs free energy. This study is part of building a reliable thermodynamic database of the CaO–MgO–V₂O₅ system.     

MHD mixed convection of a Cu–water nanofluid flow through a channel with an open trapezoidal cavity and an elliptical obstacle

In the current work, numerical simulations are achieved to study the properties and the characteristics of fluid flow and heat transfer of (Cu–water) nanofluid under the magnetohydrodynamic effects in a horizontal rectangular canal with an open trapezoidal enclosure and an elliptical obstacle. The cavity lower wall is grooved and represents the heat source while the obstacle represents a stationary cold wall. On the other hand, the rest of the walls are considered adiabatic. The governing equations for this investigation are formulated, nondimensionalized, and then solved by Galerkin finite element approach. The numerical findings were examined across a wide range of Richardson number (0.1 ≤ Ri ≤ 10), Reynolds number (1 ≤ Re ≤ 125), Hartmann number (0 ≤ Ha ≤ 100), and volume fraction of nanofluid (0 ≤ φ ≤ 0.05). The current study's findings demonstrate that the flow strength increases inversely as the Reynolds number rises, which pushes the isotherms down to the lower part of the trapezoidal cavity. The Nu_avg rises as the Ri rise, the maximum Nu_avg = 10.345 at Ri = 10, Re = 50, ϕ = 0.05, and Ha = 0; however, it reduces with increasing Hartmann number. Also, it increase by increasing ϕ, at Ri = 10, the Nu_avg increased by 8.44% when the volume fraction of nanofluid increased from (ϕ = 0–0.05).     

Simultaneous fractionation of multiple classes of polyphenols from honeybush tea using solid-phase extraction

The structural diversity of polyphenols and the inherent limitations of current extraction techniques pose a challenge to extract polyphenols using a simple and green method. Hence, in this study, a method was developed to simultaneously fractionate multiple classes of polyphenols by only varying ethanol-water solutions. Honeybush tea, which is rich in polyphenols, was selected as a model for this study. Solvent extraction followed by solid-phase extraction (SPE) was developed to obtain a polyphenol-rich fraction from six honeybush samples. Based on a gradient elution programme (10%, 30%, 50%, 70% and 90% (v/v) ethanol-water solution) of SPE, the Strata X cartridge showed a better recovery of most targeted polyphenols under 0.9 mL of the drying volume and 1 mL min⁻¹ of the dispensing speed. The elution programme for fractionating most polyphenols was as follows: single elution with 50% ethanol, followed by twice elution with 70% ethanol. The antioxidant capacity was used to analyse the differences among the polyphenol-rich fractions from six honeybush samples. Principal component analysis (PCA) revealed that unfermented C. genistoides (GG) has the greatest antioxidant capacity among the honeybush species studied. Additionally, mangiferin, isomangiferin and vicenin-2 were the main contributors to the antioxidant capacity in six honeybush fractions according to the correlation study.     

Montmorillonite-perlite-iron ceramic membranes for the adsorption/removal of As(III) and other constituents from surface water

In this study, ceramic membranes made of montmorillonite, perlite and iron were used to remove As(III) from water. Membranes prepared with 0.0, 0.5, 1.0, and 1.5 wt% of iron content were used to filtrate As(III) synthetic water and surface water solutions. As(III) adsorption capacity and removal efficiency, and other parameters such as cations and anions content, turbidity, pH, electrical conductivity were used to evaluate the membranes' performance. Results show that the As(III) adsorption/removal capacity of membranes was improved by the addition of iron. Adsorption capacity of 7.5 μg As(III)/g and removal efficiency of 97% can be achieved in membranes with 1.0 wt% of iron filings content for surface water; however, a greater amount of iron in the membrane structure limits the adsorption capacity of As(III). Besides the capacity of ceramic membranes to adsorb/remove As(III), membranes were also effective to remove other ions, turbidity, and electrical conductivity from the surface water. The addition of iron to the ceramic membranes enhanced their capacity to remove such surface water constituents. These results are important from the practical viewpoint showing the potential of ceramic membranes for the removal of metalloids and other water constituents. Langmuir isotherm model best described the adsorption process in ceramic membranes, suggesting that adsorption of As(III) happened on a monolayered surface of the ceramic membrane.     

两种混合单元混合机理的数值模拟

为了研究SV型和SX型混合单元在全静态乳化器的混合机理,使用群体平衡模型对乳化器内部流场进行模拟分析。结果表明,SV型与SX型混合单元的混合机理是油相与水相材料通过混合单元时其空间流动方向改变,在流场内形成大量的漩涡,从而达到乳化的目的;通过比较流体在经过SV型和SX型混合单元后的水相索特平均直径(d_(32)),得出SV型混合单元的乳化效果更强,但同时消耗更多的能量,压降更大。     

Anchor plate bearing capacity in flexible mesh facings

This work addresses the problem of the loading capacity of an anchor plate coupled with a steel wire mesh in soil retaining applications. The interaction mechanism between the flexible mesh facing, the underlying soil layer and the plate is studied starting from the results of several laboratory punch tests involving both the plate and the mesh only, and the whole soil-mesh-plate system. The experimental tests have been reproduced by adopting a 3D discrete element model where also the wire mesh is discretized as an assembly of interconnected nodal particles. The interaction between these particles is ruled by elasto-plastic tensile force–displacement laws in which a distortion is introduced in a stochastic manner to account for the wires’ geometrical irregularities. The mesh model is then validated with reference to a set of punch tests in which the shape and size of the punching element as well as the nominal wire diameter were varied. Subsequently, the model is extended to a punch against soil test configuration permitting an insight into the nontrivial local mechanism between the mesh facing and the underlying granular layer. The good agreement between the numerical predictions and the experimental observations at the laboratory scale allowed us to extend the model towards more realistic field conditions for which the role of the mesh panel boundary conditions, the mesh mechanical properties, the soil mechanical properties and the anchor plate geometry is investigated.     

Consolidation considering increasing soil column radius for dredged slurries improved by vacuum preloading method

Soil column is often investigated in the improvement of dredged slurries. Different from the smear zone, the soil column forms gradually and has extremely low permeability. This study presents an analytical solution for soil consolidation considering the increasing radius of the soil column and time-dependent discharge capacity. Based on the solution, the influence of the radius' increase on the consolidation behavior is found significant when the soil column has low permeability and large final radius, and the increase of formation time can lead to the increase of consolidation speed and final consolidation degree.     

Finite element limit analysis of load-bearing performance of reinforced slopes using a non-associated flow rule

This paper presents a numerical study on the load-bearing performance of reinforced slopes under footing load using a finite element limit analysis (FELA) method where a non-associated flow rule is assumed in the analysis. The method was validated against results from full-scale model tests and a limit equilibrium (LE) analytical method. A series of parametric analyses was subsequently carried out to examine the influences that the soil dilation angle, footing location, and reinforcement design (i.e. length, tensile strength, and vertical spacing) could have on the load-bearing performance of reinforced slopes. Results indicate that dilation angle has a significant influence on the predicted magnitudes of bearing capacity, slope deformation, and mobilized reinforcement load. The predicted values of bearing capacity using the FELA are smaller than those from the Meyerhof's analytical method for unreinforced semi-infinite foundation, especially for larger friction angle values. Additionally, the ultimate bearing capacity of the slope and its corresponding horizontal deformation increase with the reinforcement tensile strength. Finally, the slip planes under the applied footing load are found to be y-shaped and primarily occur in the upper half of the slope.     

A comparison of shear stress estimation methods for a single geobag on a rough bed

There are several methods for estimating bed shear stress in the literature, but comprehensive comparisons among them are limited and under specific conditions. This study compared these methods first on a bare smooth bed, and then for a single geobag on a rough bed in the interest of determining the stability of geobags used in riverbank protection structures. The geobag was filled with cement or sand and tested under different open channel flow conditions. The turbulent kinetic energy method appeared to best represent the local bed shear stress on the geobag when using the newly calibrated proportionality constants. The Reynolds stress method via extrapolation was relatively unaffected by changes to the geobags shape and measurement locations, suggesting this method inadequately represents the local bed shear stress. The Patel method and the universal law of the wall method failed to represent local bed shear stress in the rough bed cases due to instrument limitations and the breakdown of the law of the wall. This study highlights the impact of different methods on the bed shear stress estimation.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).