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The purpose of this paper is to develop a coupled lattice Boltzmann model for the simulation of the freezing process in unsaturated porous media.

In the developed model, the porous structure with complexity and disorder was generated by using a stochastic growth method, and then the Shan-Chen multiphase model and enthalpy-based phase change model were coupled by introducing a freezing interface force to describe the variation of phase interface. The pore size of porous media in freezing process was considered as an influential factor to phase transition temperature, and the variation of the interfacial force formed with phase change on the interface was described.

The larger porosity (0.2 and 0.8) will enlarge the unfrozen area from 42 mm to 70 mm, and the rest space of porous medium was occupied by the solid particles. The larger specific surface area (0.168 and 0.315) has a more fluctuated volume fraction distribution.

The concept of interfacial force was first introduced in the solid–liquid phase transition to describe the freezing process of frozen soil, enabling the formulation of a distribution equation based on enthalpy to depict the changes in the water film. The increased interfacial force serves to diminish ice formation and effectively absorb air during the freezing process. A greater surface area enhances the ability to counteract liquid migration.

Particles bed binding by selective cement activation (SCA) method is a computer-aided manufacturing (CAM) technique used to produce cementitious elements. A computer-aided design file is sliced to generate G-codes before printing. This paper aims to study the effect of key input parameters for slicer software on the final properties of printed products.

The one factor at a time (OFAT) methodology is used to investigate the impact of selected parameters on the final properties of printed specimens, and the causes for the variations in outcomes of each variable are discussed.

Finer aggregates can generate a more compact layer, resulting in a denser product with higher strength. Fluid pressure is directly determined by voxel rate (r_V); however, high pressures enable better fluid penetration control for fortified products; for extreme r_Vs, residual voids in the interfaces between successive layers and single-line primitives impair mechanical strength. It was understood that printhead movement along the orientation of the parts in the powder bed improved the mechanical properties.

The design of experiment (DOE) method assesses the influence of process parameters on various input printing variables at the same time. As the resources are limited, a fractional factorial plan is carried out on a subset of a full factorial design; hence, providing physical interpretation behind changes in each factor is difficult. OFAT aids in analyzing the effect of a change in one factor on output while all other parameters are kept constant. The results assist engineers in properly considering the influence of variable variations for future DOE designs.

This study aims to present a unique hybrid metaheuristic approach to solving the nonlinear analysis of hall currents and electric double layer (EDL) effects in multiphase wavy flow by merging the firefly algorithm (FA) and the water cycle algorithm (WCA).

Nonlinear Hall currents and EDL effects in multiphase wavy flow are originally described by partial differential equations, which are then translated into an ordinary differential equation model. The hybrid FA-WCA technique is used to take on the optimization challenge and find the best possible design weights for artificial neural networks. The fitness function is efficiently optimized by this hybrid approach, allowing the optimal design weights to be determined.

The proposed strategy is shown to be effective by taking into account multiple variables to arrive at a single answer. The numerical results obtained from the proposed method exhibit good agreement with the reference solution within finite intervals, showcasing the accuracy of the approach used in this study. Furthermore, a comparison is made between the presented results and the reference numerical solutions of the Hall Currents and electroosmotic effects in multiphase wavy flow problem.

This comparative analysis includes various performance indices, providing a statistical assessment of the precision, efficiency and reliability of the proposed approach. Moreover, to the best of the authors’ knowledge, this is a new work which has not been explored in existing literature and will add new directions to the field of fluid flows to predict most accurate results.

To explore the fusion of dust particles and of polymers in a viscous liquid is the main purpose of this article. Newtonian fluid as a base fluid is considered and the mutual presence of polymers and dusty bodies is investigated. It discusses the steady laminar flow and heat transportation of a polymeric dusty liquid induced by a uniformly heated, penetrable and stretchable surface inside the boundary layer.

The mathematical system incorporates separate equations of energy and momentum for dusty bodies and for fluid. The classical Oldroyd-B model is chosen for exploring polymer presence. For the fluid phase, this model adds another stress to the conservation law of momentum. Appropriate similarity variables are introduced to transform the system of partial differential equations (PDEs) into a system of nonlinear ordinary differential equations (ODEs). The problem is solved by introducing a numerical iterative procedure which turned out to be fastly converging.

Expeditious changes inside the boundary layer cause polymers to deform. No changes outside the boundary layer are noticed on account of polymer stretching. The dependence of heat transfer rate and skin friction on the parameter of polymer concentration and Weissenberg number is analyzed and displayed graphically against interaction parameters for temperature and velocity, dust particles’ mass concentration, Eckert and Prandtl numbers. Combining effects of polymers and dust particles cause skin friction to decrease and heat transfer rate to increase. Increasing values of interaction parameter for velocity, dust particles’ mass concentration and Eckert number reduces the drag coefficient and local Nusselt number. On the other hand, the Prandtl number and interaction parameter of temperature magnify the heat flux at the wall.

This article studies the infinite extensibility of polymers. FENE and FENE-P models can be used to investigate the polymer presence in dusty fluids in the future.

In this article, the authors’ aim is to study the combined presence of polymers and dusty bodies. Keeping the existing literature in view, this type of fusion is not studied yet. Polymer inclusion in a viscous dusty fluid is studied and the behavior of fluid flow and heat transportation is investigated within the boundary layer over a permeable linearly stretching sheet.

Whilst a modest number of investigations have been undertaken concerning nanofluids (NFs), the exploration of fluid flow under exponentially stretching velocities using NFs remains comparatively uncharted territory. This work presents a distinctive contribution through the comprehensive examination of heat and mass transfer phenomena in the NF ND–Cu/H₂O under the influence of an exponentially stretching velocity. Moreover, the investigation delves into the intriguing interplay of gyrotactic microorganisms and convective boundary conditions within the system.

Similarity transformations have been used on PDEs to convert them into dimensionless ODEs. The solution is derived by using the homotopy analysis method (HAM). The pictorial notations have been prepared for sundry flow parameters. Furthermore, some engineering quantities are calculated in terms of the density of motile microbes, Nusselt and Sherwood numbers and skin friction, which are presented in tabular form.

The mixed convection effect associated with the combined effect of the buoyancy ratio, bioconvection Rayleigh constant and the resistivity due to the magnetization property gives rise to attenuating the velocity distribution significantly in the case of hybrid nanoliquid. The parameters involved in the profile of motile microorganisms attenuate the profile significantly.

The current simulations have uncovered fascinating discoveries about how metallic NFs behave near a stretched surface. These insights give us valuable information about the characteristics of the boundary layer close to the surface under exponential stretching.

The novelty of the current investigation is the analysis of NF ND–Cu/H₂O along with an exponentially stretching velocity in a system with gyrotactic microorganisms. The investigation of fluid flow at an exponentially stretching velocity using NFs is still relatively unexplored.

There are three double bonds in the chemical structure of diallyl maleate. The purpose of this study is that the acrylate is modified with diallyl maleic anhydride to make the propionate resin present a spatial network structure, thereby improving the performance of the acrylate resin.

Methyl methacrylate (MMA) and butyl acrylate(BA) were used as were used as main monomers. Diallyl maleate (DAM) was used as crosslinking monomer and dodecafluoroheptyl methacrylate (DFMA) was used as fluoromonomer. Potassium persulfate (KPS) was used as thermal decomposition initiator, sodium lauryl sulfate (AS) and sodium dodecyl sulfonate (SDS) were used as anionic emulsifiers, and EFS-470 (Alkyl alcohol polyether type nonionic emulsifier) was a non-ionic emulsifier.

Through optimizing the reaction conditions, the uniform and stable latex is obtained. The polymer of structure was characterized by Fourier transform infrared spectroscopy (FTIR). Thermogravimetric analysis (TGA) and contact angle (CA) were tested on latex films. The particle size and distribution range of emulsion were tested with nano particle size analyzer.

The experimental results showed that the thermal decomposition temperature of the acrylic coating film increased by 20.56°C after modification. In addition, the effect of cross-linking density on the water contact angle of the fluorocarbon groups in DFMA when they migrate to the surface of the latex film during drying has been explored. The experimental results show that a higher degree of cross-linking will hinder the migration of fluorocarbon groups to the surface of the resin film.

The purpose of this study is to prepare a robust superhydrophobic coating on concrete substrate with remarkable chemical and mechanical durability through “all-covalent” strategy.

Amino-modified silica nano/micro-particles were prepared through two synthetic steps. “All-covalent” strategy was introduced to prepare a robust superhydrophobic coating on concrete surface via a “all-in-one” dispersion and a simple spraying method. The successful construction of the products was confirmed by Fourier transform infrared spectroscopy, water contact angles (WCA), X-ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM). The concrete protective properties were verified by solution immersion test, pull-off test and rapid chloride migration coefficient test. The mechanical durability was tested by falling sand impact.

Hierarchical structures combined with the low-surface-energy segments lead to typically superhydrophobic coating with a WCA of 156° and a sliding angle of 1.3°. The superhydrophobic coating prepared through “all-covalent” strategy not only improves chemical and mechanical durability but also achieves higher corrosion and wear resistance than the comparison sample prepared by physically blending strategy. More importantly, the robust superhydrophobic coating showed excellent adhesion and protective performance of concrete engineerings.

This new “all-covalent” superhydrophobic coating could be applied as a concrete protective layer with properties of self-cleaning, anti-graffiti, etc.

Introduction of both silica nanoparticles and silica microparticles to prepare a robust superhydrophobic coating on concrete surface through “all-covalent” strategy has not been systematically studied previously.

This paper aims to present a new hybrid algorithm of Particle Swarm Optimization and the Genetic Algorithm (PSOGA) to optimize the space trusses with continuous design variables. The PSOGA is an efficient hybridized algorithm to solve optimization problems.

These algorithms have shown outstanding performance in solving optimization problems with continuous variables. The PSO conceptually models the social behavior of birds, in which individual birds exchange information about their position, velocity and fitness. The behavior of a flock is influencing the probability of migration to other regions with high fitness. The GAs procedure is based on the mechanism of natural selection. The present study uses mutation, random selection and reproduction to reach the best genetic algorithm by the operators of natural genetics. Thus, only identical chromosomes or particles can be converged.

In this research, using the idea of hybridization PSO and GA algorithms are hybridized and a new meta-heuristic algorithm is developed to minimize the space trusses with continuous design variables. To showing the efficiency and robustness of the new algorithm, several benchmark problems are solved and compared with other researchers.

The results indicate that the hybrid PSO algorithm improved in both exploration and exploitation. The PSO algorithm can be used to minimize the weight of structural problems under stress and displacement constraints.

Cloud computing (CC) refers to the usage of virtualization technology to share computing resources through the internet. Task scheduling (TS) is used to assign computational resources to requests that have a high volume of pending processing. CC relies on load balancing to ensure that resources like servers and virtual machines (VMs) running on real servers share the same amount of load. VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data.

VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data. With a large number of VM or jobs, this method has a long makespan and is very difficult. A new idea to cloud loads without decreasing implementation time or resource consumption is therefore encouraged. Equilibrium optimization is used to cluster the VM into underloaded and overloaded VMs initially in this research. Underloading VMs is used to improve load balance and resource utilization in the second stage. The hybrid algorithm of BAT and the artificial bee colony (ABC) helps with TS using a multi-objective-based system. The VM manager performs VM migration decisions to provide load balance among physical machines (PMs). When a PM is overburdened and another PM is underburdened, the decision to migrate VMs is made based on the appropriate conditions. Balanced load and reduced energy usage in PMs are achieved in the former case. Manta ray foraging (MRF) is used to migrate VMs, and its decisions are based on a variety of factors.

The proposed approach provides the best possible scheduling for both VMs and PMs. To complete the task, improved whale optimization algorithm for Cloud TS has 42 s of completion time, enhanced multi-verse optimizer has 48 s, hybrid electro search with a genetic algorithm has 50 s, adaptive benefit factor-based symbiotic organisms search has 38 s and, finally, the proposed model has 30 s, which shows better performance of the proposed model.

User’s request or data transmission in a cloud data centre may cause the VMs to be under or overloaded with data. To identify the load on VM, initially EQ algorithm is used for clustering process. To figure out how well the proposed method works when the system is very busy by implementing hybrid algorithm called BAT–ABC. After the TS process, VM migration is occurred at the final stage, where optimal VM is identified by using MRF algorithm. The experimental analysis is carried out by using various metrics such as execution time, transmission time, makespan for various iterations, resource utilization and load fairness. With its system load, the metric gives load fairness. How load fairness is worked out depends on how long each task takes to do. It has been added that a cloud system may be able to achieve more load fairness if tasks take less time to finish.

The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.