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Unsteady Magneto-hydrodynamic Behavior of TiO2-Kerosene Nanofluid Flow in Wavy Octagonal Cavity

The aim of this study is to mathematically model the behavior of magneto-hydrodynamics (MHD) in a two-dimensional unsteady flow, specifically focusing on natural convection (NC) and heat transfer (HT) within a wavy octagonal cavity. The study investigates how heat is transferred and fluid flows within this cavity under specific conditions. In particular, it examines the impact of various parameters, such as the Hartmann number (Ha), Rayleigh number (Ra), and the volume fraction of nanoparticles (ϕ) on the flow and heat transfer patterns. This cavity includes a rectangular vertical wall (RVW) at the center of its bottom wall, filled with kerosene-TiO2 nanofluid of spherical shape. Within this setup, the RVW is maintained at a high temperature (T = Th), while the wavy wall is kept at a lower temperature (T = Tc, where Tc <Th). All other boundaries of the domain are assumed to be adiabatic. The finite element method (FEM) is employed as the solver for the relevant partial differential equations in numerical simulations. The results show excellent agreement with previously published research papers. The numerical solution transitions from an unsteady state to a steady state in approximately 0.68 dimensionless time units during the HT process. Throughout the study, various parameters are explored, including Ha, ranging from 0 to 100, Ra, ranging from 103 to 106, and ϕ, ranging from 0 to 0.05. The findings reveal distinct patterns in streamlines and isotherms. Specifically, a reduction in the rate of HT is observed as the Lorentz force increases, while the rate of HT is enhanced with increasing buoyancy force. Additionally, an expansion in ϕ led to an increase in the rate of HT. The study's findings could contribute to our understanding of fluid dynamics, heat transfer, and the behavior of nanofluids in complex geometries, potentially leading to improvements in various engineering and industrial applications.

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Isolation and Characterization of Cellulose from Date Palm Waste using Rejected Brine Solution

This study introduces a new and waste-to-waste treatment approach to isolate cellulose from lignocellulosic biomass. Rejected brine solution from desalination plant was utilized to remove noncellulosic components from the date palm leaves. Free chlorine available in rejected brine solution was responsible for the separation of cellulose from lignocellulosic structure. The proximate analysis revealed that the isolated cellulose exhibited a substantial volatile content of 83.70%, rendering it well-suited to produce bio-oil. Various other analytical techniques including FTIR, chemical composition analysis, proximate and ultimate analysis, X-ray diffraction (XRD), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA) were employed to confirm the cellulose enrichment. Cellulose fibers with needle−shaped morphology were obtained. Cellulose fibers were having high thermal stability (Tonset = 250 ○C) and crystallinity index (64.75%) compared to raw waste (Tonset = 226 ○C; 53.58%). In addition, the activation energy (Ea) of both date palm leaves and isolated cellulose were investigated using the Coats−Redfern model−fitting method. The activation energy values obtained were 79.39 kJ/mol for date palm leaves and 103.27 kJ/mol for isolated cellulose. This research shows a completely new process for pretreatment of lignocellulosic wastes to isolate cellulose. This approach helps reduce the waste management cost associated with date palm waste and desalination plants to promote the concept of circular economy. Moreover, enriched cellulose derived from waste palm leaves using desalination brine presents sustainable options for eco−friendly packaging, textiles, biodegradable composites, and enhanced bio-oil production applications.

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Covalent Organic Frameworks (COFs): Characteristics and Applications for Lithium-Ion Batteries (LIBs) and Sodium Ion Batteries (SIBs)

Covalent Organic Frameworks (COFs) belong to a family of porous organic materials that form 2D or 3D tuned structures via a covalent bond formation between organic blocks. COFs exhibit a remarkable array of characteristics that make them highly promising materials for various applications. COFs are characterized by their chemical and physical stability, their highly porous structure, and their easy structural tunability. They emerged as promising candidates for electrode materials in advanced energy storage devices such as sodium-ion batteries (SIBs) and lithium-ion batteries (LIBs). COFs can be precisely customized for each application via pore engineering and framework functionalization as well as the pre- and post-synthesis. Research has been conducted to examine the effect of various functional groups, active redox sites, pore size, and interlayer distances on the performance of COFs as electrode materials. Herein, this review reports the most recent advances in using COFs as electrode materials in both LIBs and SIBs. It also discusses the synthesis of COFs, structural engineering, and pore engineering. The main advantages and challenges that arise with the application of COFs in rechargeable batteries are presented. This review concluded that COFs do have the potential as anode materials in both LIBs and SIBs by virtue of their crystalline structure and high porosity that enable efficient ion diffusion and storage. COFs provided enhanced battery electrochemical performance, improved energy density, and prolonged cycle life.

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Novel approach to cooling microelectronics with complex fins configuration

This paper presents a numerical simulation and optimisation of a complex microchannel featuring innovative fin designs. The primary objective of the study is to minimise resistance in the heat sink by utilizing intricate fin structures. Three different approaches are explored: firstly, cylindrical solid fins are designed and placed on the heat sink; secondly, the solid fins are drilled halfway (50%); and in the third scenario, the solid fins are drilled 87.5% and mounted on the heat sink. In the simulation set-up, the heat sink has a heat load of 250 W imposed on the bottom wall and single-phase water of Reynolds number between 400 and 500 flows in a forced convection laminar condition to remove the heat at the bottom and internally within the fins walls surface area, while an air stream of Reynolds number between 3 to 6 flows convectively across the cylindrical fins to dissipate excess heat externally. The finite volume method and computational fluid dynamic code, are employed to discretise the geometry with heat and fluid fields solved. The optimisation is performed for parallel and counter flows and the outcomes compete favorably. Similarly, the influence of the Reynolds number on minimised temperature and resistance results is discussed. The results show that in parallel flow the integrated heat sink with half hollow fins is best with a minimised resistance of 27.2%, while in the counter flow the hollow fins are superior with a declined resistance of 19%. The study is validated with experimental results in open literature.

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Management Mode and Path of Digital Transformation of Power Grid Enterprises Based on Artificial Intelligence Algorithm

Facing the arrival of the digital transformation (DT) era, power grid enterprises are currently grappling with pressures arising from economic cycles and structural factors, and for them, the integration and development of energy revolution and digital revolution are intertwined. At this stage, people have increasing requirements for power service quality. However, electric power enterprises (EPEs) are unable to meet such demands because of several limitations, such as the surge of power grid operation risk, insufficient systematic service level and unreasonable enterprise architecture. DT is an effective way for EPEs to improve their management and service level. Power grid enterprises should follow the trend of digital development and actively carry out DT. In simulating the operation of the power system, the first step is to establish a grid connection between the simulated generator and the simulated power grid. This involves adjusting the generator excitation to regulate the generator voltage and adjusting the output of the prime mover to regulate the generator frequency. This study explored the management mode and implementation path of DT of EPEs, proposed the DT management mode of EPEs based on artificial intelligence (AI) algorithms and conducted an experimental research. The research showed that the average of the four- month informatisation project management level index of the enterprise S simulation model was 3.02% higher than that of the four-month informatisation project management level index of the enterprise T simulation model. The average value of the operation and maintenance (O&M) and service management index of the enterprise S simulation model was 3.14% higher than that of the enterprise T simulation model. The improvement of the management level index and the average O&M of simulation models can enhance the operational efficiency of enterprises and provide them with clear development directions. The average value of production security management index, network security management index and data asset management index of the enterprise S simulation model was higher than those of the enterprise T simulation model. The DT management mode of power grid enterprises based on AI algorithms is an effective driving force for power supply enterprises to achieve modernisation and standardised development.

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Sustainable system development for efficient management of waste tires through gasification and solar energy for useful outputs: A thermodynamic analysis

In this study, a solar based integrated waste tires gasification system with desalination is developed, and the respective analyses of this system are performed for multiple useful outputs, including electricity, hydrogen, fresh water as well as heat provided to the community. The thermodynamic assessment of this system is performed by using energy and exergy analyses. Moreover, both energy analysis and exergy analysis are performed for essentially investigating and evaluating the performance of the overall system. Moreover, analyses of the effects of varying operating conditions on the subsystems’ efficiencies are carried out. Both Aspen Plus and Engineering Equation Solver software packages are used for thermodynamic analyses and simulations. In this integrated system, solar energy is the prime source and utilized for producing steam. This study aims to bring up a unique solution for better resources management and sustainability. Furthermore, the waste tires are gasified to produce syngas in the designed system where both Rankine and Brayton cycles are utilized for producing electricity and heat. In addition to this, excess heat is transferred to the desalination system for producing fresh water. For improving the overall system performance, some parametric studies are performed to investigate both energy and exergy efficiencies. The energy efficiency of the integrated system is therefore calculated as 38.9 % while the exergy efficiency of this system is found to be 34.6 %. For the developed system, electricity generation and amount of heating are also calculated as 58.65 MW and 7.35 MW respectively. Moreover, the hydrogen and freshwater production capacities are determined to be 0.75 kg/s and 355.40 kg/s respectively.

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One-dimensional pump geometry prediction modeling for energy loss analysis of pumps working as turbines

Pumps as turbine (PAT) for small-scale hydropower, pressure relief valves, and hydro-pumping applications have recently gained popularity. In contrast to conventional turbines, pumps do not have movable guiding vanes to accommodate changes in flow rate and head. This limits their use to the single best operating point. As a result, the precise estimation of reverse mode operating parameters is critical. One of the most successful techniques in this regard is the energy loss model. However, it necessitates extremely detailed pump geometry and experimental data. Although it is claimed to be more accurate, the lack of data makes it impractical. This calls for the devising of a pump geometrical parameter prediction model from limited manufacturer information. Using 137 sets of commercial pump operating data, geometry redesign was carried out by MATLAB code. Following that, multivariate linear regression analysis was carried out, and a one-dimensional geometrical prediction model was developed. Then the result was validated with computational analysis and measurement. The model results were 99 %, 100 %, and 95 % correlated for pump inlet, volute, and throat inlet diameters, respectively, with the experimental results. Similarly, the model results were also 99 %, 71 %, and 89 % correlated for pump inlet, outlet, and volute blade width, respectively, with experimental results. The model gave a more accurate geometrical result than the analytical and numerical methods.

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