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This paper aims to develop a new 3D analytical model in cylindrical coordinates to study radial flux eddy current couplers (RFECC) while considering the magnetic edge and 3D curvature effects, and the field reaction due to the induced currents.

The analytical model is developed by combining two formulations. A magnetic scalar potential formulation in the air and the magnets regions and a current density formulation in the conductive region. The magnetic field and eddy currents expressions are obtained by solving the 3D Maxwell equations in 3D cylindrical coordinates with the variable separation method. The torque expression is derived from the field solution using the Maxwell stress tensor. In addition to 3D magnetic edge effects, the proposed model takes into account the reaction field effect due to the induced currents in the conducting part. To show the accuracy of the developed 3D analytical model, its results are compared to those from the 3D finite element simulation.

The obtained results prove the accuracy of the new developed 3D analytical model. The comparison of the 3D analytical model with the 2D simulation proves the strong magnetic edge effects impact (in the axial direction) in these devices which must be considered in the modelling. The new analytical model allows the magnetic edge effects consideration without any correction factor and also presents a good compromise between precision and computation time.

The proposed 3D analytical model presents a considerably reduced computation time compared to 3D finite element simulation which makes it efficient as an accurate design and optimization tool for radial flux eddy current devices.

A new analytical model in 3D cylindrical coordinates has been developed to find the electromagnetic torque in radial flux eddy current couplers. This model considers the magnetic edge effects, the 3D curvature effects and the field reaction (without correction factors) while improving the computation time.

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

Polymethyl methacrylate (PMMA) is a remarkable biocompatible material for bone cement and regeneration. It is also considered 3D printable but requires in-depth process–structure–properties studies. This study aims to elucidate the mechanistic effects of processing parameters and sterilization on PMMA-based implants.

The approach comprised manufacturing samples with different raster angle orientations to capitalize on the influence of the filament alignment with the loading direction. One sample set was sterilized using an autoclave, while another was kept as a reference. The samples underwent a comprehensive characterization regimen of mechanical tension, compression and flexural testing. Thermal and microscale mechanical properties were also analyzed to explore the extent of the appreciated modifications as a function of processing conditions.

Thermal and microscale mechanical properties remained almost unaltered, whereas the mesoscale mechanical behavior varied from the as-printed to the after-autoclaving specimens. Although the mechanical behavior reported a pronounced dependence on the printing orientation, sterilization had minimal effects on the properties of 3D printed PMMA structures. Nonetheless, notable changes in appearance were attributed, and heat reversed as a response to thermally driven conformational rearrangements of the molecules.

This research further deepens the viability of 3D printed PMMA for biomedical applications, contributing to the overall comprehension of the polymer and the thermal processes associated with its implementation in biomedical applications, including personalized implants.

The aim of this paper is to provide a simple yet accurate and efficient geometric method for thermal homogenization of impregnated and non-impregnated coil winding technologies based on the concept of thermal resistance.

For regular windings, the periodic microscopic cell in the winding space is identified. Also, for irregular windings, the average microscopic cell of the winding is determined. An approximation is used to calculate the thermal resistance of the winding cell. Based on this approximation, the winding insulation is considered as a circular ring around the wire. Mathematical equations are obtained to calculate the equivalent thermal resistance of the cell. The equivalent thermal conductivity of the winding is calculated using equivalent thermal resistance of the cell. Winding thermal homogenization is completed by determining the equivalent thermal properties of the cell.

The thermal pattern of different windings is simulated and compared with the results of different homogenization methods. The results show that the proposed method is applicable for a wide range of windings in terms of winding scheme, packing factor and winding insulation. Also, the results show that the proposed method is more accurate than other winding homogenization methods in calculating the equivalent thermal conductivity of the winding.

In this paper, the change of electrical resistance of the winding with temperature and thermal contact between the sub-components are ignored. Also, liquid insulators, such as oils, and rectangular wires were not investigated. Research in these topics is considered as future work.

Unlike other homogenization methods, the proposed method can be applied to non-impregnated and irregular windings. Also, compared to other homogenization methods, the proposed method has a simpler formulation that makes it easier to program and implement. All of these indicate the efficiency of the proposed method in the thermal analysis of the winding.

This study aims to present an experimental approach to develop a high-strength 3D-printed recycled polymer composite reinforced with continuous metal fiber.

The continuous metal fiber composite was 3D printed using recycled and virgin acrylonitrile butadiene styrene-blended filament (RABS-B) in the ratio of 60:40 and postused continuous brass wire (CBW). The 3D printing was done using an in-nozzle impregnation technique using an FFF printer installed with a self-modified nozzle. The tensile and single-edge notch bend (SENB) test samples are fabricated to evaluate the tensile and fracture toughness properties compared with VABS and RABS-B samples.

The tensile and SENB tests revealed that RABS-B/CBW composite 3D printed with 0.7 mm layer spacing exhibited a notable improvement in Young’s modulus, ultimate tensile strength, elongation at maximum load and fracture toughness by 51.47%, 18.67% and 107.3% and 22.75% compared to VABS, respectively.

This novel approach of integrating CBW with recycled thermoplastic represents a significant leap forward in material science, delivering superior strength and unlocking the potential for advanced, sustainable composites in demanding engineering fields.

Limited research has been conducted on the in-nozzle impregnation technique for 3D printing metal fiber-reinforced recycled thermoplastic composites. Adopting this method holds the potential to create durable and high-strength sustainable composites suitable for engineering applications, thereby diminishing dependence on virgin materials.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Electric motor heating during biomass recovery and its handling on conveyor is a serious concern for the motor performance. Thus, the purpose of this paper is to design and develop a hardware prototype of master–slave electric motors based biomass conveyor system to use the motors under normal operating conditions without overheating.

The hardware prototype of the system used master–slave electric motors for embedded controller operated robotic arm to automatically replace conveyor motors by one another. A mixed signal based embedded controller (C8051F226DK), fully compliant with IEEE 1149.1 specifications, was used to operate the entire system. A precise temperature measurement of motor with the help of negative temperature coefficient sensor was possible due to the utilization of industry standard temperature controller (N76E003AT20). Also, a pulse width modulation based speed control was achieved for master–slave motors of biomass conveyor.

As compared to conventional energy based mains supply, the system is self-sufficient to extract more energy from solar supply with an energy increase of 11.38%. With respect to conventional energy based \ of 47.31%, solar energy based higher energy saving of 52.69% was reported. Also, the work achieved higher temperature reduction of 34.26% of the motor as compared to previous cooling options.

The proposed technique is free from air, liquid and phase-changing material based cooling materials. As a consequence, the work prevents the wastage of these materials and does not cause the risk of health hazards. Also, the motors are used with their original dimensions without facing any leakage problems.

This paper aims to realize the vertical interconnection in 3D radio frequency (RF) circuit by coaxial transitions with broad working bandwidth and small signal loss.

An advanced packaging method, 12-inch wafer-level through-mold-via (TMV) additive manufacturing, is used to fabricate a 3D resin-based coaxial transition with a continuous ground wall (named resin-coaxial transition). Designation and simulation are implemented to ensure the application universality and fabrication feasibility. The outer radius R of coaxial transition is optimized by designing and fabricating three samples.

The fabricated coaxial transition possesses an inner radius of 40 µm and a length of 200 µm. The optimized sample with an outer radius R of 155 µm exhibits S11 < –10 dB and S21 > –1.3 dB at 10–110 GHz and the smallest insertion loss (S21 = 0.83 dB at 77 GHz) among the samples. Moreover, the S21 of the samples increases at 58.4–90.1 GHz, indicating a broad and suitable working bandwidth.

The wafer-level TMV additive manufacturing method is applied to fabricate coaxial transitions for the first time. The fabricated resin-coaxial transitions show good performance up to the W-band. It may provide new strategies for novel designing and fabricating methods of RF transitions.