The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.
Most artificial intelligence methods used in fault diagnosis are based on empirical risk minimisation principle and have poor generalisation when fault samples are few. Support vector machines (SVM) is a new general machine-learning tool based on structural risk minimisation principle that exhibits good generalisation even when fault samples are few. Fault diagnosis based on SVM is discussed. Since basic SVM is originally designed for two-class classification, while most of fault diagnosis problems are multi-class cases, a new multi-class classification of SVM named 'one to others' algorithm is presented to solve the multi-class recognition problems. It is a binary tree classifier composed of several two-class classifiers organised by fault priority, which is simple, and has little repeated training amount, and the rate of training and recognition is expedited. The effectiveness of the method is verified by the application to the fault diagnosis for turbo pump rotor.
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Subwavelength structural color filtering and printing technologies employing plasmonic nanostructures have recently been recognized as an important and beneficial complement to the traditional colorant-based pigmentation. However, the color saturation, brightness and incident angle tolerance of structural color printing need to be improved to meet the application requirement. Here we demonstrate a structural color printing method based on plasmonic metasurfaces of perfect light absorption to improve color performances such as saturation and brightness. Thin-layer perfect absorbers with periodic hole arrays are designed at visible frequencies and the absorption peaks are tuned by simply adjusting the hole size and periodicity. Near perfect light absorption with high quality factors are obtained to realize high-resolution, angle-insensitive plasmonic color printing with high color saturation and brightness. Moreover, the fabricated metasurfaces can be protected with a protective coating for ambient use without degrading performances. The demonstrated structural color printing platform offers great potential for applications ranging from security marking to information storage. PMID:26047486
Subwavelength structural color filtering and printing technologies employing plasmonic nanostructures have recently been recognized as an important and beneficial complement to the traditional colorant-based pigmentation. However, the color saturation, brightness and incident angle tolerance of structural color printing need to be improved to meet the application requirement. Here we demonstrate a structural color printing method based on plasmonic metasurfaces of perfect light absorption to improve color performances such as saturation and brightness. Thin-layer perfect absorbers with periodic hole arrays are designed at visible frequencies and the absorption peaks are tuned by simply adjusting the hole size and periodicity. Near perfectmore light absorption with high quality factors are obtained to realize high-resolution, angle-insensitive plasmonic color printing with high color saturation and brightness. Moreover, the fabricated metasurfaces can be protected with a protective coating for ambient use without degrading performances. The demonstrated structural color printing platform offers great potential for applications ranging from security marking to information storage. less
Traditional metallic gratings and novel metamaterials are two basic kinds of candidates for perfect absorption. Comparatively speaking, metallic grating is the preferred choice for the same absorption effect because it is structurally simpler and more convenient to fabricate. However, to date, most of the perfect absorption effects achieved based on metamaterials are also available using an metallic grating except the tunable dual(multi)-band perfect absorption. To fill this gap, in this paper, by adding subgrooves on the rear surface as well as inside the grating slits to a free-standing metallic grating, tunable dual-band perfect absorption is also obtained for the first time. The grooves inside the slits is to tune the frequency of the Cavity Mode(CM) resonance which enhances the transmission and suppresses the reflectance simultaneously. The grooves on the rear surface give rise to the phase resonance which not only suppresses the transmission but also reinforces the reflectance depression effect. Thus, when the phase resonance and the frequency tunable CM resonance occur together, transmission and reflection can be suppressed simultaneously, dual-band nearly perfect absorption with tunable frequencies is obtained. To our knowledge, this perfect absorption phenomenon is achieved for the first time in a designed metallic grating structure.
The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.
Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance. PMID:29027926
The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most often, the source of such molecules consists of commercially available compound databases, but they can also be searched for within the libraries of structures generated in silico from existing ligands. Various computational combinatorial approaches are based solely on the chemical structure of compounds, using different types of substitutions for new molecules formation. In this study, the starting point for combinatorial library generation was the fingerprint referring to the optimal substructural composition in terms of the activity toward a considered target, which was obtained using a machine learning-based optimization procedure. The systematic enumeration of all possible connections between preferred substructures resulted in the formation of target-focused libraries of new potential ligands. The compounds were initially assessed by machine learning methods using a hashed fingerprint to represent molecules; the distribution of their physicochemical properties was also investigated, as well as their synthetic accessibility. The examination of various fingerprints and machine learning algorithms indicated that the Klekota-Roth fingerprint and support vector machine were an optimal combination for such experiments. This study was performed for 8 protein targets, and the obtained compound sets and their characterization are publically available at -pan.krakow.pl/comb_lib/ .
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