This study explores the influence of Zinc Oxide (ZnO) nanofluids on solar water heaters with Dimple Tubes and Helical Twisted Tape (DTHTT) surfaces. The helical twisted tape design enhances turbulence, improving nanofluid mixing and thermal exchange. Computational fluid dynamics (CFD) validates the efficiency of the parabolic trough solar water heater (PTSWH) with emphasis on solar light concentration and feed water flow velocity. Optimal conditions include a 0.3% ZnO nanofluid volume concentration, mass flow rates between 1.0 kg/min and 5.0 kg/min, and copper-type twisted helical tapes. Experimental results reveal Nusselt number enhancements of 15.1% and 20.96% at H/D = 10, and 16.72% and 32.12% at H/D = 3, for 0.3% ZnO nanofluid, at Reynolds numbers from 3000 to 8000. The twisted tape arrangement at H/D = 3 exhibits increased fluid mixing, leading to higher convective heat transfer. Friction factor enhancements at Reynolds numbers 3000 and 8000 are 0.26% and 0.38%, respectively, compared to the base fluid. At a 3.0 kg/min mass flow rate, thermal efficiency increases to 39.25%, a 13.25% gain over plain tapes. The model shows a ±3.24% deviation from the expected friction factor, with a total ±1.2% discrepancy between experimental and simulated findings, remaining within an acceptable range. 

Twisted helical Tape's impact on heat transfer and friction in zinc oxide (ZnO) nanofluids for solar water heaters: Biomedical insight

Pulsating heat pipe (PHP) is an implicit technique through a passive two-stage heat transfer system. This paper presents the experimentations on PHP contrived using copper with different inner tube diameters of 1, 1.5, 2, and 2.5 mm, respectively. The PHP is accused of acetone as a functional liquid with filling proportions varying from 50 to 90% of its volume with an increment of 10%. The effects of filling proportion and tube diameter on the thermal performance of PHP were investigated. The evaporator zone is electrically heated using a mica heater in the range of 20–80 W, and the condenser area is kept cool by the water circulation method. The results show that a 2 mm inner tube diameter performs best compared to other tube diameters, with a lower rate of thermal resistance of 0.49 K/W. Also, the performance of PHP is enhanced at a filling proportion of 60% for all the tube diameters. Further, CFD analysis was carried out for different filling ratios for a 2 mm diameter pipe at a constant heat input of 80 W, and it revealed that test outcomes were in line with CFD results. The deviation between the experimental and numerical studies was 10%. Considering the optimized parameters, i.e., tube diameter and filling ratio, the work was extended by adding SiO2 nanoparticles to the base fluid with 1–5 % mass concentration. The results showed a lower thermal resistance value of 0.3 W/K and a higher heat transfer coefficient of 828.64 W/m2 °K was obtained at 2% mass concentration of SiO2. Also, the proportional rise in heat transfer coefficient at 60 W is 11.46, 17, 14, 4.15, and 1.94% for 1, 2, 3, 4, and 5% mass concentration of SiO2 nanoparticles, respectively. Hence, the PHP operates better at a 2 mm diameter with a 60% filling ratio and 2% mass concentration of SiO2 nanoparticles. 

Characteristics of pulsating heat pipe with variation of tube diameter, filling ratio, and SiO2 nanoparticles: Biomedical and engineering implications

The growing demand for fiber-reinforced polymer (FRP) in industrial applications has prompted the exploration of natural fiber-based composites as a viable alternative to synthetic fibers. Using jute–rattan fiber-reinforced composite offers the potential for environmentally sustainable waste material decomposition and cost reduction compared to conventional fiber materials. This article focuses on the impact of different machining constraints on surface roughness and delamination during the drilling process of the jute–rattan FRP composite. Inspired by this unexplored research area, this article emphasizes the influence of various machining constraints on surface roughness and delamination in drilling jute–rattan FRP composite. Response surface methodology designs the experiment using drill bit material, spindle speed, and feed rate as input variables to measure surface roughness and delamination factors. The technique of order of preference by similarity to the ideal solution method is used to optimize the machining parameters, and for predicting surface roughness and delamination, two machine learning-based models named random forest (RF) and support vector machine (SVM) are utilized. To evaluate the accuracy of the predicted values, the correlation coefficient (R2), mean absolute percentage error, and mean squared error were used. RF performed better in comparison with SVM, with a higher value of R2 for both testing and training datasets, which is 0.997, 0.981, and 0.985 for surface roughness, entry delamination, and exit delamination, respectively. Hence, this study presents an innovative methodology for predicting surface roughness and delamination through machine learning techniques.

Machinability investigation of natural fibers reinforced polymer matrix composite under drilling: Leveraging machine learning in bioengineering applications

Stress can increase the heart rate, causing dangerous conditions that cause significant harm and even death. Therefore, managing stress well to control the heart rate is vital. Monitoring stress levels using biomedical devices is essential to prevent further damage to the individual. Regular monitoring facilitates the acquisition of individual stress levels through heart rate information. In this research, a MAX30100 sensor can produce Beats Per Minute (BPM) data, which show the stress experienced by a person during four daily activities (sitting, walking, running, and sleeping) and when watching a horror movie. This research underscores the potential of cost-effective wireless solutions to increase portability and facilitate real-time monitoring and remote surveillance. The researchers introduced an innovative methodology by reusing everyday consumer devices, initially intended for routine activities, to measure stress levels in a unique context—precisely in a controlled experiment involving a movie-watching scenario. The ultimate achievement of this research was creating a stationary heart rate monitoring device that is easy to access, easy to use, space-saving, and adept at effectively tracking stress indicators. BPM readings obtained from the MAX30100 sensor have scores similar to those obtained from the heart rate app. The researchers proposed the inclusion of other sensors, such as a photoplethysmograph, an electrocardiogram, and galvanic skin response, to provide a more holistic assessment of stress. Leveraging cloud technology for data storage enables long-term monitoring and in-depth analysis of stress patterns over time.

Wireless-based portable device heart rate measurement as biomedical devices for stress detection

Optimization of Turbulent Flow Heat Transfer in a 3D Cubic Shell Heat Exchanger using Non-Mixture Multiphase Nanofluids

The thermal properties of paraffin wax were upgraded by utilizing rice husk-derived graphene nanoparticles. In terms of performance, the stability of NPEPCM is an essential aspect. The stability of REPCM is checked using surfactants (CTAB, SDBS, SDS) and sonication time. An increment in the thermal conductivity of paraffin wax was perceived. Maximum conductivity of 0.59 Wm−1K−1 was achieved at 304 K for 1.5 wt% of RGP’s. The maximum thermal conductivity of 0.69 Wm−1K−1 was achieved using pure Graphene at 304 K. Using RGPEPW at different concentrations of RGP’s, the thermal efficiency was calculated for different flow rates of fluid and solar irradiance, and the consequence of the abridged temperature coefficient on the efficiency of FPSC observed. Maximum efficiencies of 67.5 % and 63.9 % were noted for 1 wt% of graphene nanoparticles and 1.5 wt% of RGPs at a 3 Lt/min flow rate, respectively. The improvement of 29.8 % and 22.8 % in the efficiency of FPSC is observed for 1 wt per cent of Graphene and 1.5 wt per cent of RGPs, respectively. Using RGPEPW with a 9.2 % increment in the outlet, the temperature was noticed in the afternoon at a 1.2 Lt/min flow rate. The bioengineering approach gives an understanding of engineering, biology, and environmental science involvement in the present study. 

Thermal performance evaluation of solar collector with rice husk Graphene-PCM: Bioengineering approach

In this work, the microwave process is optimized for graphene preparation from rice husk using RSM (Response Surface Methodology) as the graphene has exceptional qualities and is highly used in many industrial applications. The experiments are designed by using Box-Behnken Design (BBD) approach. The characterization of prepared graphene is done by FESEM (Field Emission Scanning Electron Microscope), UV–Visible spectroscopy, and FTIR (Fourier transform infrared Spectroscopy). The best route to finding good-quality graphene is the objective of this research. The higher value R2 describes the satisfactory correlation between experimental and predicted data. The obtained optimized minimum crystallite size of graphene is 28.39 nm. The characterization, prediction, and process optimization are done, and the validation of the developed model confirms the model can be used for the preparation of graphene from rice husk. The prediction and optimization of the process parameters are done for the synthesis of graphene from rice husk. RSM is used as a statistical technique to obtain a quadratic model for the response. As the properties of graphene mostly depend upon the size of the particle, so the prediction of the crystalline size is done by this RSM technique.

https://iopscience.iop.org/article/10.1088/1755-1315/1110/1/012069/pdf

Use of Response Surface Methodology to Optimize the crystalline size of rice husk derived graphene produced by microwave process

The method that is most frequently utilised to speed up changeover is known as Single Minute Exchange of Dies (SMED). SMED helps shorten lead times and boost system flexibility so that the unit may react rapidly to changes in market trends or customer requests. To achieve positive outcomes, SMED must be implemented effectively. Instead of shifting internal operations to external activities, more emphasis needs to be placed on streamlining and simplifying existing activities. In the food processing business, where cleaning various parts was the primary task during the changeover, this study concentrated on the application of SMED. Before the deployment of SMED, operator-specific time studies were carried out at two separate stations (Station A & Station B), and observed actions were critically examined while using the ECRS tool. Failure mode effect analysis (FMEA), which prioritises potential risks that could lengthen changeover times, was incorporated into the procedure. Based on risk analysis, twelve root causes were prioritised, and an action plan was created while considering risk analysis trends. To benefit, rapid fixes and other changes were made when necessary. At stations A and B, the results of a post-SMED time analysis showed a reduction in changeover time of 35.54% and 49.94%, respectively. The production unit’s overall equipment effectiveness (OEE) improved to 0.89. 

Enhancing sustainability in manufacturing: A case study on reducing changeover time through single minute exchange of dies and risk analysis

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Thermal performance evaluation of solar collector with rice husk Graphene-PCM: Bioengineering approach

Use of Response Surface Methodology to Optimize the crystalline size of rice husk derived graphene produced by microwave process

Enhancing sustainability in manufacturing: A case study on reducing changeover time through single minute exchange of dies and risk analysis