具有联网功能的家用设备

现在,人人都能使用互联网,它具有采集新闻和内容共享到实时通信多种多样的用途.这些活动主要通过个人计算机和智能手机实现,而在家里联网电视已开始担当这个角色.     

High Thermal Conductivity Polymer Composites Fabrication through Conventional and 3D Printing Processes: State-of-the-Art and Future Trends

The lifespan and the performance of flexible electronic devices and components are affected by the large accumulation of heat, and this problem must be addressed by thermally conductive polymer composite films. Therefore, the need for the development of high thermal conductivity nanocomposites has a strong role in various applications. In this article, the effect of different particle reinforcements such as single and hybrid form, coated and uncoated particles, and chemically treated particles on the thermal conductivity of various polymers are reviewed and the mechanism behind the improvement of the required properties are discussed. Furthermore, the role of manufacturing processes such as injection molding, compression molding, and 3D printing techniques in the production of high thermal conductivity polymer composites is detailed. Finally, the potential for future research is discussed, which can help researchers to work on the thermal properties enhancement for polymeric materials.     

Selection of optimal process parameters in WEDM while machining Al7075/SiCp metal matrix composites

Aluminium metal matrix composites (MMCs) reinforced with silicon carbide particulate (SiCp) find several applications due to their improved mechanical properties over the conventional metals for a wide variety of aerospace and automotive applications. However, the presence of discontinuously distributed hard ceramic in the MMCs made them as difficult-to-cut materials for conventional machining methods. The wire electrical discharge machining (WEDM), as a widely adopted non-traditional machining method for difficult-to-cut precision components, found an appropriate metal removal process for MMCs to enhance quality of cut within the stipulated cost. While machining the advanced materials like MMCs, a clear understanding into the machining performance of the process for its control variables could make the process uncomplicated and economical. In light of the growing industrial need of making high performance-low cost components, the investigation aimed to explore the machining performance characteristics of SiCp reinforced Al7075 matrix composites (Al7075/SiCp) during WEDM. While conducting the machining experiments, surface roughness, metal removal rate, and wire wear ratio are considered the responses to evaluate the WEDM performance. Response surface methodology is used to develop the empirical models for these WEDM responses. SiC particulate size and volume percentages are considered the process variables along with pulse-on time, pulse-off time, and wire tension. Analysis of variance (ANOVA) is used to check the adequacy of the developed models. Since the machining responses are conflicting in nature, the problem is formulated as a multi-objective optimization problem and is solved using the Non-dominated Sorting Genetic Algorithm-II to obtain the set of Pareto-optimal solutions. The derived optimal process responses are confirmed by the experimental validation tests, and the results are analyzed by SEM.     

Predicting and optimizing the heat transfer performance of radiator with functionalized graphene nanofluids

Accurately predicting the heat transfer characteristics of coolants used in thermal management of energy systems like heat exchangers, power electronics, and heating, ventilation, and air conditioning is indispensable in maintaining its operating conditions within safety limits. Apart from safety, factors such as power consumption and operating cost are the most important constraints to be considered in designing an energy-efficient and cost-effective cooling solution. In this study, the experimental data available from previous research on the use of functionalized graphene-based nanofluids in compact heat exchangers such as the automotive radiator is used to optimize the heat transfer performance parameters like Nusselt number of the nanofluid, the friction factor, and effectiveness of the heat exchanger. A supervised machine learning technique like the artificial neural network is used to obtain the objective functions of the response variables in terms of input features such as Reynolds number, Prandtl number, the volume concentration of nanoparticles in the base fluid, number of transfer units, heat capacity, the density of nanofluid, pressure drop and velocity. On the current dataset, it is found that by using the Bayesian regularization training algorithm and tangent sigmoidal activation function in the neural network, the best accuracies in the prediction can be achieved. Well-known nature-inspired optimization algorithms like genetic algorithms and simulated annealing are used in optimizing the above-mentioned response variables. Both algorithms converged to the same values of the objective functions. The optimum values of Nusselt number, effectiveness, and friction factor are 105.65, 0.506, and 0.0038, respectively, for the given composition of the nanofluid and radiator configuration.     

In situ velocity measurements of very high power ultrasonic additive manufacturing using a photonic Doppler velocimeter

To understand the dynamic structural movements of very high power ultrasonic additive manufacturing, simultaneous in situ velocity measurements of the sonotrode, welding foil and substrate during consolidation were made using a photonic Doppler velocimeter. During consolidation in which the welding foil was successfully bonded to the substrate, the welding foil and substrate had similar vibration phase angles which came into and then out of phase of the sonotrode; in addition to having large changes in relative velocity as the normal force from the sonotrode was applied and then removed. A consolidation pass in which no bonding occurred, consisted of relatively constant velocity amplitude for all structures. The welding foil and sonotrode remained fully coupled and in phase, but was out of phase of the substrate during the entire welding pass. Therefore, by examining velocity and phase data, bonding versus non-bonding conditions can be determined in situ using the photonic Doppler velocimeter system.     

Microstructure and Mechanical Properties of Friction Stir Lap Welded Aluminum Alloy AA2014

Friction stir lap welds were produced in 3 mm thick Alclad sheets of Al alloy 2014-T4 using two different tools (with triangular and threaded taper cylindrical pins). The effects of tool geometry on weld microstructure, lap-shear performance and failure mode were investigated. The pin profile was found to significantly influence the hook geometry, which in turn strongly influenced the joint strength and the failure mode. Welds produced in alloy 2014-T4 Alclad sheets by using triangular and threaded taper cylindrical tools exhibited an average lap-shear failure load of 16.5 and 19.5 kN, respectively, while the average failure load for standard riveted joints was only 3.4 kN. Welds produced in alloy 2014-T6 Alclad sheets and in alloy 2014-T4 bare sheets (i.e., no Alclad) were comparatively evaluated with those produced in alloy 2014-T4 Alclad sheets. While the welds made (with threaded taper cylindrical tool) in T6 and T4 conditions showed very similar lap-shear failure loads, the joint efficiency of the welds made in T6 condition (43%) was considerably lower (because of the higher base material strength) than those made in T4 condition (51%). The Alclad layers were found to present no special problems in friction stir lap welding. Welds made with triangular tool in alloy 2014-T4 Alclad and bare sheets showed very similar lap-shear failure loads. The present work provides some useful insights into the use of friction stir welding for joining Al alloys in lap configuration.     

Superconductivity at 4 K in Pd-Deficient Layered Ta2Pd x S6

In the present short letter, we report on the low dimensional 4d and 5d transition metals-chalcogenide based compounds i.e., Ta2PdxS6, showing semiconducting to superconducting transition at around 4K with their upper critical fields outside the Pauli paramagnetic limit. It seems couple of different superconducting phases do exist in these new set of compounds. Our short letter in this regards is thought provoking, asking to explore various unearthed possible new superconducting phases in (Nb/Ta)2Pdx(S/Se/Te)y systems.     

Thermal behaviour of strontium tartrate single crystals grown in gel

Thermal behaviour of strontium tartrate crystals grown with the aid of sodium metasilicate gel is investigated using thermogravimetry (TG) and differential thermal analysis (DTA). Effect of magnetic field and dopant (Pb)²⁺ on the crystal stability is also studied using thermal analysis. This study reveals that water molecules are locked up in the lattice with different strengths in the grown crystals.     

Optimal utilization of renewable energy-based IPPs for industrial load management

Share of power generation from renewable energy sources has been steadily increasing all over the world, mainly due to the concern about clean environment. Cost of renewable power generation has reduced considerably during the last two decades due to technological advancements and at present some of the renewable energy sources can generate power at costs comparable with that of fossil fuels. In this paper, application of renewable energy-based power generation is proposed, for load management. The formulation utilizes non-linear programming technique for minimizing the electricity cost and reducing the peak demand, by supplementing power by renewable energy sources, satisfying the system constraints. Case study of twenty-two large-scale industries showed that, significant reduction in peak demand (about 34%) and electricity cost (about 14%) can be achieved, by the optimal utilization of the renewable energy from independent power producers (IPPs).