This study relates about the mechanical properties, contour analysis and multi response method was implemented into the processed similar joint of AA5083 by friction stir welding (FSW). The ...processing was carried with fluted cylinder tool pin profile with applicable process parameters namely; tool traverse speed (35 to 65 mm/min), spinning speed (1250 to 1750 rpm) and tilt angle (1.5 to 2.50), respectively. These parameters are mingled together with Taguchi L9 array to reframe the parameters to identify the optimal by grey analysis technique. The hardness and tensile properties were employed with whole nine welded samples. The entire samples procured fine mechanical strength due to the influence of FSW parameters resulting in more plastic deformation was occurred in the stirred region. From the GRG responses the optimal FSW parameters are 50 mm/min of traverse speed, 1500 rpm of spinning speed and 2.5 of tilt angle. The hardness and tensile strength was attained more in those particular process parameters. Influence of tool traverse and spinning speed as major impact to improve their properties.
•As an incomplete recrystallization, mixed grain structure with numerous dislocation tangle in Non-DRX region.•Homogeneous equiaxed grains can be obtained at the optimum processing parameters ...identified by 3D processing map.•Grain growth may be responsible for the near< 001 > compression texture detected in super-solvus deformation.•DDRX and CDRX occur simultaneously in microstructure control for mixed grain structure.•DDRX is the dominant nucleation mechanism while CDRX belongs to the assistant one.
Mixed grain structure, as an incomplete recrystallization, should be homogenized and refined by subsequent processing to improve the mechanical properties of the aeroengine components. The microstructural origin and control mechanism is quite necessary for the microstructure homogenizing and grain refining through thermo-mechanical processing. In present research, microstructural origin and control mechanism of the mixed grain structure have been conducted deeply. With the consideration of temperature drop in practical industrial forging, the optimum processing parameters can be determined as 1110–1140 °C/1.0 s−1 to obtain homogeneous equiaxed grains. The microstructure evolution corresponding to the identified optimal parameters, viz., deformation temperature and strain rate, were systematically investigated. Higher dynamic recrystallization (DRX) fraction and coarser DRX grains can be observed at super-solvus temperature deformation (1140 °C). In addition, sub-solvus deformation (1110 °C) shows random orientated distribution while near< 001 > compression texture can be detected in super-solvus deformation. Particular attention was paid to the DRX mechanisms during hot deformation. Discontinuous dynamic recrystallization (DDRX) and continuous dynamic recrystallization (CDRX) occur simultaneously, and the synergistic effect of them contributes to microstructure control. Moreover, DDRX characterized by grain boundary bulging dominants the microstructure control. Progressive subgrain rotation labeled as CDRX can be regarded as an important assistant mechanism. The findings would provide theoretical support for microstructure control of Ni-based superalloys with mixed grain structure, which is of vital importance for components to obtain excellent performance.
Functionally graded materials (FGMs) are advanced materials with improved properties that enable them to withstand severe working environment which the traditional composite materials cannot ...withstand. FGM found their applications in several areas which include: military, medicine and aerospace. Various manufacturing processes are used to produce functionally graded materials that include: powder metallurgy, physical vapour deposition, chemical vapour deposition process and laser metal deposition process. Laser metal deposition (LMD) process is an additive manufacturing process that can be used to produce functionally graded material directly from the three dimensional (3D) computer aided design (CAD) model of the part in one single process. LMD process is a fairly new manufacturing process and a highly non-linear process. The process parameters are of great importance in LMD process and they need to be optimized for the required application. In this study, functionally graded titanium alloy composite was produced using optimized process parameters for each material combination as obtained through a model that was developed in an initial study and the FGM was characterized through metallurgical, mechanical and tribological studies. The results show that the produced FGM has improved properties when compared to those produced at constant processing parameters for all material combinations.
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•Functionally graded material (FGM) of Ti6Al4V/TiC was developed using optimized process parameters for each layer.•The FGM has better wear resistance than FGM produced at constant parameters.•The FGM has microhardness of four times that of the parent material (1200Hv).•Wear resistance can be improved by building each layer at optimized parameters.
Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks ...for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.
Defect formation is a common problem in selective laser melting （SLM）. This paper provides a review of defect formation mechanisms in SLM. It sum- marizes the recent research outcomes on defect ...findings and classification, analyzes formation mechanisms of the common defects, such as porosities, incomplete fusion holes, and cracks. The paper discusses the effect of the process parameters on defect formation and the impact of defect formation on the mechanical properties of a fabri- cated part. Based on the discussion, the paper proposes strategies for defect suppression and control in SLM.
Native starches have been modified by employing various methods for desired industrial applications over the last few decades. There have been intense interests to develop novel methods with ...advantages of high-efficiency, environment-friendly and easy operation for starch modification. Although there is more attention to the functional properties of modified starch for practical applications in the industry, structural changes are the basis of functional changes, hence understanding the structural alteration induced by processing techniques is a fundamental issue towards better utilization of starch and starch modification techniques.
The current review mainly presents the effects of several efficient physical processing techniques on the changes in the starch multi-scale structure including molecular structure, crystallinity, lamellae structure, and morphology characteristic. Among these techniques, the influences of high hydrostatic pressure, cold plasma, and microwave treatments are emphasized, and research gaps to better develop these techniques for starch modifications are suggested.
Physical processing techniques by means of pressure, heat, radiation or free radicals can affect amylose, amylopectin, and degree of their interactions in the crystalline and amorphous region, as well as the packing mode of the crystal structure, thereby resulting in various functional properties and extensive applications in starch industries. However, the exact mechanisms behind these modification techniques are inconclusive because there are many affecting factors mainly including processing parameters, starch origin, and environment. Exploring new research methods or improving modified equipment to reduce the influence of these interference factors should be a good inspiration to study physical modification.
•Novel physical techniques applied in starch modification are reviewed.•Changes in starch structure and gelatinization properties are compared and discussed.•Problems and challenges to apply these physical techniques are presented.
•An in-situ monitoring method for Selective Laser Melting (SLM) processes is proposed.•It relies on image-based analysis of plume properties for challenging materials like zinc and its ...alloys.•Thermal images are acquired via an off-axis mounted infrared camera.•The results show that the proposed approach allows detecting process unstable behaviours and anticipating severe defects.
Despite continuous technological improvements in metal additive manufacturing (AM) systems, process stability is still affected by several possible sources of defects especially in the presence of challenging materials. Thus, both the research community and the major AM system developers have focused an increasing attention on in situ sensing and monitoring tools in the last years. However, there is still a lack of statistical methods to automatically detect the onset of a defect and signal an alarm during the part's layer-wise production. This study contributes to this framework with two levels of novelty. First, it presents an in situ monitoring method that integrates the acquisition of infrared images with a data mining approach for feature extraction and a statistical process monitoring technique to design a data-driven and automated alarm rule. Second, the method is aimed at monitoring powder bed fusion processes for difficult-to-process materials like zinc and its alloys, which impose several challenges to the process stability and quality because of their low melting and boiling points. To this aim, the proposed approach analyzes the byproducts generated by the interaction between the energy source and the material. In particular, it detects unstable behaviors by analyzing the salient properties of the process plume to detect unstable melting conditions. This case study entails an SLM process on zinc powder, where different sets of process parameters were tested leading either to in-control or out-of-control quality conditions. A comparison analysis highlights the effectiveness of plume-based stability monitoring.
•Mechanism analysis of municipal solid waste incineration (MSWI) has been narrated.•Numerical simulation method of the MSWI process is compared and discussed.•Coupling several software can produce ...customized simulation models based on actual process data.•Digital twin model construction for environmental protection requires artificial intelligence.
Determining the status of the municipal solid waste incineration (MSWI) process due to the composition variations of MSW, operational differences of the MSWI plants, and maintenance uncertainties of the incineration devices is difficult. Moreover, the optimal control algorithms developed off-line lack the support of the incineration mechanism. These conditions complicate the cost-effective operation of the MSWI plants. The development of customized numerical simulation models can simulate the incineration effects and obtain the extreme value of key process parameters to support its operational optimal control. This article aims to review the mechanical characteristics and numerical simulation methods of the MSWI process based on mechanical grates, thus providing support for the construction of a customized numerical simulation model and the realization of a digital twin system for the actual MSWI process. First, the mechanical characteristic of the MSWI process is comprehensively analyzed. Then, the numerical simulation method based on commercial and self-developed software is summarized and compared. Furthermore, the difficulties in creating customized numerical simulations and constructing digital twin models are discussed. Finally, the conclusion and research directions are established on the basis of the concluding ideas and specific commentaries. Results show that coupling several types of software can facilitate the creation of customized simulations based on actual process data. The development of an intelligent digital twin encounters several difficulties that must be highlighted because the combination of the numerical simulation model of the entire process can analyze the mechanism and the realization of matching the model with actual process data. The current study revealed that the digital twin model based on mechanical characteristics and numerical simulations by using actual process data and artificial intelligence technology could play a significant role in the safety and operation optimization of the MSWI process.
The development of an industrially scalable method to produce large quantities of high quality graphene is essential for its practical application in electronics, composite materials, and energy ...storage devices. Here, we report a method for bulk preparation of few-layer graphene by shear exfoliation of graphite in liquids. We showed that high shear mixing of graphite and solvent in the Taylor vortex flow regime resulted in an efficient exfoliation of graphite into few-layer graphene with a high yield. According to Raman spectroscopy and X-ray photoelectron spectroscopy, the exfoliated graphene flakes were found to exhibited a low oxidation degree and a low content of defects. Optimization of Taylor flow processing parameters based on computational fluid dynamics (CFD) studies further improved the efficiency of graphite exfoliation, thereby achieving an overall yield of up to ∼5%. The described Taylor flow-based shear exfoliation of graphite may have great potential to produce high quality graphene on an industrially accessible scale.
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