An artificial neural network approach on parametric optimization of laser micro-machining of die-steel

In the present research, laser micro machining (LMM) of tungsten-molybdenum general purpose high speed steel (Rex M2) has been studied. Selection of optimum machining parameter combinations for obtaining higher depth of groove and smaller height of recast layer is a challenging task in LMM due to the presence of a large number of process variables. There is no perfect combination of parameters which can simultaneously result in both the highest depth of groove and lowest height of recast layer. This paper presents an attempt to develop a strategy for predicting the optimum machining parameter setting for the generation of the maximum depth of groove with minimum height of recast layer. A feed forward back-propagation neural network has been developed to model the machining process. The model, after proper training, is capable of predicting the response parameters as a function of four different control parameters. Experimental results demonstrate that the machining model is suitable and the optimization strategy satisfies practical requirements. The developed model has been found to be quite unique, powerful and flexible.     

Fuzzy Learning of Talbot Effect Guides Optimal Mask Design for Proximity Field Nanopatterning Lithography

Processing methods used in photonics and nanotechnology possess many limitations restricting their application areas such as high cost, inability to produce fine details, problems with scalability, and long processing time. Proximity field nanopatterning is a lithography method which surpasses these limitations. By using interference patterns produced by a two-dimensional phase mask, the technique is able to generate a submicron detailed exposure on a millimeter-size slab of light sensitive photopolymer, which is then developed like a photographic plate to reveal three-dimensional interference patterns from the phase mask. While it is possible to use simulations to obtain the interference patterns produced by a phase mask, realizing the mask dimensions necessary for producing a desired interference pattern is analytically challenging due to the intricacies of light interactions involved in producing the final interference pattern. An alternative method is to iteratively optimize the phase mask until the interference patterns obtained converge to the desired pattern. However, depending on the optimization technique used, one either risks a significant probability of failure or requires a prohibitive number of iterations. We argue that an optimization technique that is to take advantage of the physics of the problem using machine learning methods (here fuzzy learning) can lead to competent mask design. This technique is described in this letter.     

A 0.9 V 92 dB Double-Sampled Switched-RC Delta-Sigma Audio ADC

A 0.9 V third-order double-sampled delta-sigma audio ADC is presented. A new method using a combination of a switched-RC technique and a floating switched-capacitor double-sampling configuration enabled low-voltage operation without clock boosting or bootstrapping. A three-level quantizer with simple dynamic element matching was used to improve linearity. The prototype IC implemented in a 0.13 CMOS process achieves 92 dB DR, 91 dB SNR and 89 dB SNDR in a 24 kHz audio signal bandwidth, while consuming 1.5 mW from a 0.9 V supply. The prototype operates from 0.65 V to 1.5 V supply with minimal performance degradation.     

Prony-Based Optimal Bayes Fault Classification of Overcurrent Protection

The development of deregulation and demand for high-quality electrical energy has lead to a new requirement in different fields of power systems. In the protection field, this means that high sensitivity and fast operation during the fault are required while maltripping of relay protection is not acceptable. One case that may lead to a maltrip of the high-sensitive overcurrent relay is the starting current of the induction motor or inrush current of the transformer. This transient current has the potential to affect the correct operation of protection relays close to the component being switched. In the case of switching events, such transients must not lead to overcurrent relay operation; therefore, a reliable and secure relay response becomes a critical matter. Meanwhile, proper techniques must be used to prevent maltripping of such relays, due to transient currents in the network. In this paper, the optimal Bayes classifier is utilized to develop a method for discriminating the fault from nonfault events. The proposed method has been designed based on extracting the modal parameters of the current waveform using the Prony method. By feeding the fundamental frequency damping and ratio of the 2nd harmonic amplitude over the fundamental harmonic amplitude to the classifier, the fault case is discriminated from the switching case. The suitable performance of this algorithm is demonstrated by simulation of different faults and switching conditions on a power system using PSCAD/EMTDC software.     

Influence of inhibitor addition on the corrosion protection performance of sol–gel coatings on AA2024

Sol–gel films are actively investigated during the last decade as possible candidates for environmentally friendly pre-treatments. However, the important drawback in this case is the lack of active corrosion protection and self-healing ability.     

Physico-chemical properties of ceramic pigments for high-temperature application

Heat resistant coatings are required primarily for stacks, exhaust pipes, reactors, space crafts and similar equipments that are permanently or occasionally exposed to elevated temperatures. High-temperature coatings are generally based on silicone resin with ceramic and metallic pigments. In this study, iron oxide, cobalt oxide (thermo chromic compound) and aluminum oxide are used for the preparation of four new types of coloured pigments. The thermal resistant characteristics of these ceramic pigments were studied by differential thermal analysis, thermo gravimetric analysis and differential scanning calorimetric analysis. These ceramic pigments are found to be thermally stable up to 400 °C.     

Selective Transport of Bismuth Ions through Supported Liquid Membrane

A new supported liquid membrane (SLM) system was prepared for the selective transport of bismuth ions from the aqueous feed into the aqueous permeate phase. The support of the SLM was a thin porous polypropylene or polyvinylidene fluoride membrane impregnated with diisooctyldithiophosphinic acid (Cyanex 301) as mobile carrier in 4‐chloroacetophenon as organic solvent. Cyanex 301 acts as a highly selective carrier for the uphill transport of bismuth ions through the SLM. In the presence of HNO₃ as a metal ion acceptor in the strip solution, the transport of bismuth ions into the strip side reached 70 % of the initial feed concentration after 3.5 hours. The selectivity and efficiency of bismuth transport from aqueous solutions containing different mixtures of cations were investigated. In the presence of P₂O₇^2– ions as suitable masking agent in the feed solution, the interfering effects of other cations were completely eliminated. The selective transport of bismuth through SLM is superior to liquid‐liquid extraction or through bulk liquid membranes. This is due to the high efficiency. The SLM reduces the solvent requirements, combines extraction and stripping operations in a single process and allows the use of highly selective extractants. The system may be applied to samples containing very low bismuth concentrations.     

Gasification of Biogenic Solid Fuels

As a result of shrinking fossil fuels, biomass as a regenerative energy source gains importance. To realize biomass projects it is essential to investigate in convenient thermal procedures. On this evidence an analysis and evaluation of diverse gasification technologies with different boundary conditions and diverse biomasses are indispensable. Form and kind of the biomass as well as the type of the gasification plant cause different compositions of the product gas. The gasifiers show advantages and disadvantages concerning the biomass and the produced gas quality, depending on reactor type, kind of heat supply, gasification medium, and the pressure ratio in the reactor. As the ideal gasifier for different biomass is presently not available, it will be shown, which biomass is suitable for fixed bed or fluidized bed gasifiers.