Abstract The current research focuses mainly on the manufacturing industries in terms of energy savings and cleaner production in order to impart sustainability. The use of conventional cutting fluid is not beneficial for high cutting speeds and feeds, as it can lead to increased tool wear and reduced machining efficiency. In addition, such cutting fluid contaminates the atmosphere in high-production machining, leading to environmental concerns and potential health risks for workers exposed to these harmful substances, such as respiratory issues and skin irritations from prolonged exposure to the chemicals present in the fluid. Cryogenic cooling is useful in lowering the high-flow cutting temperatures, which increases the quality of the workpiece and tool life. This review comprehensively analyses the relevant literature on cryogenic cooling in various machining processes. It provides a review and summary of cryogenic cooling, analyzes and evaluates benefits and developmental challenges in each area, and outlines the future developmental directions of cryogenic cooling. These cooling techniques are found to enhance the sustainability of machining processes and production as a whole, particularly by reducing energy consumption and minimizing waste generated during manufacturing. This study aims to develop new strategies for the research and development of cryogenic cooling technology in machining industries.
This study investigates the flow physics of tomato puree through a sudden expansion pipe joint in a processing plant. Tomato is a widely cultivated vegetable crop. The food processing industry uses tomato juice and tomato paste to produce finished food products such as sauce, ketchup, and pulp. In terms of fluid flow physics, tomato puree exhibits non-Newtonian, shear-thinning behavior. Viscosity of tomato puree is modeled using non-Newtonian power-law model available in ANSYS FLUENT Computational Fluid Dynamics (CFD) modeling software. An important engineering result for this type of problem is major loss or friction power loss. Results are presented for friction power loss inside sudden expansion pipe flow geometrical configuration for a range of Reynolds numbers using the steady-state analysis. Zones of possible tomato puree mass accumulation are identified. The larger the accumulation zone, the worse is the engineering design. The rheological response of tomato puree following an accidental shutdown of the pumping mechanism is investigated through transient CFD simulations. Based on the findings of the analysis, an alternate geometrical configuration that may potentially avoid puree mass accumulation and reduce energy loss is suggested. The effects of key input parameters, including Reynolds number and rheological parameters governing viscosity, on the friction factor are quantified through empirical correlations, constituting a valuable outcome of the analysis.
Dried leaves are a highly regarded renewable resource and the primary source of cellulosic plant material. It is rumored that dried leaf fibers may enhance the strength of polymer laminates comparably to synthetic fibers. This study is distinctive as it used artificial neural network (ANN) methodology to investigate the influence of dried leaves fiber, alumina, copper, and silicon carbide reinforcement on the thermal, physical, and mechanical properties of epoxy, polylactic acid, and vinyl-ester polymers. The wet layup procedure supported by an ultrasonication bath was employed to fabricate these composites under ambient circumstances. The findings indicate that the dried leaves-alumina fillers enhanced the mechanical and thermal stability of all three polymers compared to the other samples. The Fourier-transform infrared (FTIR) spectra indicate that the fillers within the matrix form robust interfacial bonds, possibly due to the generation of novel hydroxyl functional groups. The thermogravimetric analysis indicated that the hybrid composites composed of dried leaves, silicon carbide filler, and polymer exhibited superior thermal stability. The findings were statistically significant at the 95
Abstract This study investigates the flow characteristics and thermal performance of Straight Vortex Tubes (SVTs) and Convergent–Divergent Vortex Tubes (CDVTs) under identical operating conditions using computational fluid dynamics (CFD). A three-dimensional model with compressed air as the working fluid was simulated using the finite volume method and the RNG k–ε turbulence model. Grid independence was verified to ensure numerical reliability. Results show that while the straight tube (0°/0°) configuration achieves the highest instantaneous temperature separation (ΔT ≈ 48 K), its performance is highly sensitive to geometric variations and deteriorates with changes in diameter and length. In contrast, the CDVT with fixed 10° convergent and 6° divergent angles demonstrates superior cold outlet temperature reduction and vortex stability for shorter tube lengths (90–130 mm), where compactness and robustness are critical. These findings highlight that geometric modifications do not universally maximize ΔT but provide enhanced stability and efficiency in constrained geometries, offering valuable insights for designing compact, energy-efficient vortex-based cooling systems.
The integration of Hybrid Renewable Energy Sources (HRESs), combining Photovoltaic (PV) and Wind Turbine (WT) systems, presents significant Power Quality (PQ) challenges in modern electrical grids. Grid connection of these systems often results in reliability concerns due to generation fluctuations and harmonic distortions introduced by power electronic converters. To address these issues, this manuscript proposes a novel hybrid approach-Fennec Fox Optimization-Amplitude Transformed Quantum Convolutional Neural Network (FFOATQCNN)-to enhance PQ in grid-connected HRESs employing a Cascaded H-Bridge Multilevel Inverter (CHBMLI). The FFO algorithm optimizes energy allocation and control parameters to reduce power losses and fluctuations, while the ATQCNN model predicts future power generation or demand, enabling proactive system control and improved PQ. The proposed technique aims to reduce Total Harmonic Distortion (THD), stabilize voltage levels, and maximize overall system performance. Implementation in MATLAB and comparative analysis with existing methods-including GA-PSO, NBO-RERNN, EO, IANN, CNN, MAO-RERNN, and SCANN-demonstrate the superior performance of the FFO-ATQCNN approach. The system achieves an efficiency of 98.6 % and reduces THD to 1.4 %, significantly enhancing PQ in grid-connected HRESs. This approach offers a reliable and intelligent solution for managing hybrid renewable energy systems, ensuring their stable and efficient operation in modern power networks.
