Evaluation of thermal couple impedance model of power modules for accurate die temperature estimation up to 200 ◦C

This paper presents an experimental evaluation of the thermal couple impedance model of power modules (PMs), in which Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect-Transistor (MOSFET) dies are implemented. The model considers the thermal cross-coupling effect, representing the temperature rise of a die due to power dissipations by the other dies in the same PM. We propose a characterization method to obtain the thermal couple impedance of the SiC MOSFET-based PMs for model accuracy. Simulation based on the proposed model accurately estimates the measured die temperature of three PMs with different die placements. The maximum error between measured and simulated die temperatures is within 8.1 ◦C in a wide and practical operation range from 70 ◦C to 200 ◦C. The thermal couple impedance model is helpful to design die placements of high power PMs considering the thermal cross-coupling effect.

Utilization of Melt Fracture Phenomenon for the Preparation of Shark Skin Structured Hydrophobic Film

With the application of biomimetic shark skin microstructures with hydrophobicity in microfluidics, sensors and self-cleaning materials, microstructure processing methods are increasing. The preparation process has higher requirements for processing cost and efficiency. In this paper, linear low-density polyethylene (LLDPE) hydrophobic films were prepared with the help of melt fracture phenomenon. The equipment is a self-made single screw extruder. By adjusting the process parameters, the biomimetic shark skin structured LLDPE films with good hydrophobic property can be obtained. The surface microstructure shape of the product is related to kinds of additive, die temperature and screw speed. When AC5 was selected as an additive, the optimal processing parameter was found to be 160 °C die temperature and 80 r/min screw speed. A contact angle of 133° was obtained in this situation. In addition, the influences of die temperature and screw speed on the size of shark skin structure were also systematically investigated in this paper. It was found that the microstructure surface with hierarchical roughness had a better hydrophobic property.

Porosity formation studies in high pressure die castings of Al-9Si-3Cu alloy based on Taguchi method

PurposeNowadays, ample industries are fascinated to look for high strength and light weight materials for the development of robust parts. Because of light weight and high stiffness to weight ratio; usage of aluminum parts is growing rapidly, especially in automotive engineering. Process improvement of Al alloys and their grain structure refinement is the current area of interest in casting companies. In this research work, an investigation has been carried out to enhance the process improvement of die casting by optimization of various significant parameters and their refinement of grains by the effect of Nb-C novel grain refiner.Design/methodology/approachL27 orthogonal array (OA) has been considered to optimize the preferred casting input parameters such as molten metal temperature (°C), die temperature (°C), injection pressure (bar), Al-3.5Nb-1.5 C novel grain refiner and Ni alloying additions as key process parameters in order to increase the quality and efficiency of Al-9Si-3Cu aluminum alloy die casting by reducing the porosity formation.FindingsIt was observed that the porosity values have significantly decreased from 0.88% to 0.25% particularly at 0.1 wt.% of new grain refiner and 0.5 wt. % of Al-6Ni master alloy. As per the ANOVA results, it was observed that Al-3.5FeNb-1.5 C grain refiner (F value 2609.22), Al-6Ni alloying addition (F value 1329.13), molten metal temperature (F value 1002.43) and, injection pressure (F value 448.06) are the factors that significantly affects the porosity, whereas die temperature was found to be insignificant. The results show that new grain refiner is one the most significant factor among the other selected parameters. The contribution of the new grain refiner to the variation of mean casting porosity is around 57.74%. confidence interval (CI) has also been estimated as 0.013 for 95% consistency level to validate the predicted range of optimum casting porosity of aforesaid alloy.Originality/valueTo the best of the authors' knowledge, no study has been conducted in the past to investigate the combined effect of these die casting parameters and composition factors for the development of Al-Si robust cast parts. The paper represents original research and provides new information for the fabrication of die casting parts.

Fluidity Investigation of Pure Al and Al-Si Alloys

Fluidity tests of pure aluminum 1070 and Al-Si alloys with Si contents of up to 25% were conducted using a die cast machine equipped with a spiral die. The effects of the channel gap, die temperature, and injection speed on the fluidity were investigated. When the channel gap was small (0.5 mm), the flow length of the 1070 was minimized, and the fluidity increased monotonically at a gradual rate with increasing Si content. In contrast, larger gaps yielded convex fluidity–Si content curves. Additionally, heating the die had less of an influence on the fluidity of the 1070 than on that of the Al-Si alloy. These results are discussed in the context of the peeling of the solidification layer from the die based on the thicknesses of foils and strips cast by melt spinning and roll casting, respectively. At lower Si contents, heat shrinkage was greater and the latent heat was lower. When the heat shrinkage was greater, the solidification layer began to peel earlier, and the heat transfer between the solidification layer and the die became smaller. As a result, the fluidity of the 1070 was greatest when the channel gap was 0.8 mm.

A Decision-Making Method Providing Sustainability to FPGA-Based SoCs by Run-Time Structural Adaptation to Mode of Operation, Power Budget, and Die Temperature Variations

One of the growing areas of application of embedded systems in robotics, aerospace, military, etc. is autonomous mobile systems. Usually, such embedded systems have multitask multimodal workloads. These systems must sustain the required performance of their dynamic workloads in presence of varying power budget due to rechargeable power sources, varying die temperature due to varying workloads and/or external temperature, and varying hardware resources due to occurrence of hardware faults. This paper proposes a run-time decision-making method, called Decision Space Explorer, for FPGA-based Systems-on-Chip (SoCs) to support changing workload requirements while simultaneously mitigating unpredictable variations in power budget, die temperature, and hardware resource constraints. It is based on the concept of Run-Time Structural Adaptation (RTSA); whenever there is a change in a system’s set of constraints, Explorer selects a suitable hardware processing circuit for each active task at an appropriate operating frequency such that all the constraints are satisfied. Explorer has been experimentally deployed on the ARM Cortex-A9 core of Xilinx Zynq XC7Z020 SoC. Its worst-case decision-making time for different scenarios ranges from tens to hundreds of microseconds. Explorer is thus suitable for enabling RTSA in systems where specifications of multiple objectives must be maintained simultaneously, making them self-sustainable.

Numerical modeling and optimization of process parameters in continuous extrusion process through response surface methodology, artificial neural network & genetic algorithm

The product of high complex profile, high strength, high productivity and excellent material properties with infinite length can be produced by Continuous Extrusion (CE) process. The numerical simulation of Aluminum (AA 1100) feedstock material at different wheel velocities, product diameter, feedstock temperature, die temperature and friction condition has been carried out using 3D simulation tool Design Environment for Forming (DEFORM-3D) in this paper. The development of mathematical model is carried out to investigate the influence of wheel velocity, extrusion ratio, feedstock temperature, die temperature and friction conditions on total load required for the deformation and extrusion of feedstock material through Response Surface Methodology (RSM). The statistical significance of mathematical model is verified through analysis of variance (ANOVA). The most optimum value of extrusion load has been found to be 136.4[Formula: see text]kN through iterative process of Genetic Algorithm (GA) using Artificial Neural Network (ANN). The optimized value of input process variables for minimum value of extrusion load obtained has been found to be 13 Revolutions per Minute (RPM) as wheel velocity, 5[Formula: see text]mm as product diameter, 0.95 as friction condition, 650[Formula: see text]C as feedstock temperature and 550[Formula: see text]C as die temperature. This paper with proposed methodology will be helpful for industries working in the area of CE in terms of minimizing energy consumption during production process of bus bars, tubes, wires, cables, sheets, plates, strips, etc.

Foamability of Cellulose Palmitate Using Various Physical Blowing Agents in the Extrusion Process

Polymer foams are widely used in several fields such as thermal insulation, acoustics, automotive, and packaging. The most widely used polymer foams are made of polyurethane, polystyrene, and polyethylene but environmental awareness is boosting interest towards alternative bio-based materials. In this study, the suitability of bio-based thermoplastic cellulose palmitate for extrusion foaming was studied. Isobutane, carbon dioxide (CO2), and nitrogen (N2) were tested as blowing agents in different concentrations. Each of them enabled cellulose palmitate foam formation. Isobutane foams exhibited the lowest density with the largest average cell size and nitrogen foams indicated most uniform cell morphology. The effect of die temperature on foamability was further studied with isobutane (3 wt%) as a blowing agent. Die temperature had a relatively low impact on foam density and the differences were mainly encountered with regard to surface quality and cell size distribution. This study demonstrates that cellulose palmitate can be foamed but to produce foams with greater quality, the material homogeneity needs to be improved and researched further.

Modeling and experimental study of pore structure in melt-blown fiber assembly

It is widely known that the pore size of a meltblown fiber assembly extensively affects the final applications of its products. We have developed a model for simulating melt-blowing production to investigate the formation mechanism of a fiber assembly. In this study, we calculated the pore size under different production conditions using the model. The predicted results reveal the relationship between the pore size and the production conditions, namely, the air jet pressure, suction pressure, die temperature, polymer flow rate, die to collector distance, and collector speed. The predicted results also verified the experimental trends reported in previous studies. High air jet pressure and die temperature tend to generate smaller pores, while a large polymer flow rate, die to collector distance, and collector movement speed contribute to the production of larger pores in the fiber assembly. In addition, the circularity was predicted in this study to describe the pore shape. The numerical investigation of virtual production is a novel method in which the expected pore size and corresponding production conditions can be easily obtained using a computer with a few keystrokes and mouse clicks.