Environmental friendly cutting fluids and cooling techniques in machining: a review

Atmospheric-pressure plasmas (APPs) have attracted great interest and have been widely applied in biomedical applications, as due to their non-thermal and reactive properties, they interact with living tissues, cells and bacteria. Various types of plasma sources generated at atmospheric pressure have been developed to achieve better performance in specific applications. This article presents an overview of the general characteristics of APPs and a brief summary of their biomedical applications, and reviews a wide range of these sources developed for biomedical applications. The plasma sources are classified according to their power sources and cover a wide frequency spectrum from dc to microwaves. The configurations and characteristics of plasma sources are outlined and their biomedical applications are presented.

https://iopscience.iop.org/article/10.1088/0963-0252/21/4/043001/pdf

Atmospheric-pressure plasma sources for biomedical applications

The generalization of the Local Density Approximation (LDA) method for the systems with strong Coulomb correlations is presented which gives a correct description of the Mott insulators. The LDA+U method is based on the model hamiltonian approach and allows to take into account the non-sphericity of the Coulomb and exchange interactions. parameters. Orbital-dependent LDA+U potential gives correct orbital polarization and corresponding Jahn-Teller distortion. To calculate the spectra of the strongly correlated systems the impurity Anderson model should be solved with a many-electron trial wave function. All parameters of the many-electron hamiltonian are taken from LDA+U calculations. The method was applied to NiO and has shown good agreement with experimental photoemission spectra and with the oxygen Kα X-ray emission spectrum.

http://absimage.aps.org/image/MAR06/MWS_MAR06-2005-007233.pdf

First-principles calculations of electronic structure and spectra of strongly correlated systems: the LDA+U method

Study on microstructure, mechanical properties and machinability of efficiently additive manufactured AISI 316L stainless steel by high-power direct laser deposition

Aluminum Metal Matrix Composites (MMCs) sought over other conventional materials in the field of aerospace, automotive and marine applications owing to their excellent improved properties. These materials are of much interest to the researchers from few decades. These composites initially replaced Cast Iron and Bronze alloys but owing to their poor wear and seizure resistance, they were subjected to many experiments and the wear behavior of these composites were explored to a maximum extent and were reported by number of research scholars for the past 25 years. In this paper an attempt has been made to consolidate some of the aspects of mechanical and wear behavior of Al-MMCs and the prediction of the Mechanical and Tribological properties of Aluminum MMCs.

/pdf/mechanical-and-tribological-behavior-of-particulate-4x05huiioi.pdf

Mechanical and Tribological Behavior of Particulate Reinforced Aluminum Metal Matrix Composites – a review

Drilling parameters have great influences on hole accuracy and defect production. In this study, single factor test is applied to obtain the relationship between the torque deviation and the spindle speed n at different feeds per revolution fr. White Light Interferometer (WLI) is applied to measure the hole shape. Based on the frequency domain analysis of torque deviation, the cause of hole shape deviation is investigated. Relationship between the hole shape accuracy and drilling parameters is established, which can be used to predict the hole shape by analyzing the torque deviation. Moreover, the reasonable processing parameters can be selected to obtain drilling hole with ideal shape and satisfying production efficiency.

Influences of Processing Parameters on Hole Shape Accuracy in Drilling Carbon Fiber Reinforced Composite

The invention relates to a method for preparing laminar composite ceramic cutter material blanks by using an electrojet deposition technology, and belongs to the technical field of mechanical cutter manufacturing. The method comprises the following steps: (1) firstly, ceramic powder is uniformly mixed with a solvent and a binding agent to prepare suspension; and then, the suspension is positionedin an injector of an electrojet deposition device; (2) a mold is positioned on a motion platform of a substrate of the electrojet deposition device; the motion distance and speed and the grid gap of the substrate of the motion platform are set; the flow of the suspension, the voltage of a high-voltage power supply and the distance between a metal nozzle and a graphite mold are set; and the suspension is deposited in the mold to form a ceramic thin layer; and (3) the step (2) is repeated to obtain the laminar composite ceramic cutter material blanks. The electrojet deposition technology is usedfor depositing the ceramic cutter pulp thin layer on micro-nanoscale to realize ordered arrangement of materials in the laminar composite ceramic cutter material blanks.

Method for preparing laminar composite ceramic cutter material blanks by using electrojet deposition technology

During part machining, as the tool usage time and the number of passes increase, the cutting edge of the tool gradually wears out. As a tool for parts processing, the degree of wear of cutting tools has an important influence on the quality of parts processing. In order to understand the tool wear in time and ensure the quality of parts processing, this paper proposes a tool wear monitoring method based on deep learning. The application of deep residual network in tool wear degree monitoring is investigated, the overall scheme of tool wear degree monitoring is designed, and the deep learning scheme is implemented in the PyTorch framework. The vibration and force signals from multiple parallel experiments are first collected by sensors. The signals are analyzed in time and frequency using the short-time Fourier trans-form, after which the transform results are used as the input of the ResNet34 deep residual network for supervised training. Finally, the model effect is tested using test data. The research results show that the accuracy rate of using the deep residual network to monitor the degree of tool wear can reach 98%, which has high monitoring accuracy.

Research on Tool Wear Detection Method Using Deep Residual Network

Abstract The Pelton turbine has been widely used to develop high-head water resources with sediments because of its advantages in life cycle costs. When a flood or monsoon season occurs, the sediment concentration in the river increases suddenly, causing severe erosion to the nozzle, needle, and runner of Pelton turbines. After decades of development, researchers have developed practical engineering experience to reduce the sediment concentration of the flow through the turbine and ensure the safety and efficiency of power generation. Research on the mechanism of sediment erosion, development of anti-erosion materials, and establishment of erosion prediction models have attracted scholarly interest in recent years. Extensive research has been conducted to determine a complete and valuable syndication erosion model. However, owing to the complexity of the flow and wear mechanisms, the influence of specific parameters of erosion and the syndication effect is still difficult to determine. Computational fluid dynamics and erosion monitoring technology have also been evaluated and applied. This paper presents a comprehensive review of the erosion of Pelton turbines, some of the latest technical methods, and possible future development directions. 

/pdf/sediment-erosion-on-pelton-turbines-a-review-3ab8fgjh.pdf

Sediment Erosion on Pelton Turbines: A Review

Based on the idea of regulating the variation on stiffness by controlling the number of springs involved in the work, this paper designs a kind of variable stiffness actuator (VSA) which can be applied to the field of robot. The variable stiffness structure takes the spiral tensile spring as the elastic element, and the number of springs Participating in the work is controlled by the push-pull electromagnet. It has the accurate positive and negative 32 kinds of stiffness adjustment values. The structure model was established by using SolidWorks. MATLAB analysis was used to optimize the design of the structure and conduct mechanical and structural stiffness analysis, and the angle range and stiffness range of the actuator were obtained, which had showed a uniform characteristic of distribution of adjustable stiffness values in stiffness range interval. The conclusion is that the VSA has the advantages of real-time and accurate change of stiffness, wide variation range of stiffness and wide adjustment range of angle.

Jie Sun

Papers

Influences of Processing Parameters on Hole Shape Accuracy in Drilling Carbon Fiber Reinforced Composite

Method for preparing laminar composite ceramic cutter material blanks by using electrojet deposition technology

Research on Tool Wear Detection Method Using Deep Residual Network

Sediment Erosion on Pelton Turbines: A Review

Variable Stiffness Actuator Structure for Robot.