Search results for: datepalm kernel powder

Authors: Ahmed N. Shmroukh, Ahmed Hamza H. Ali, Ali K. Abel-Rahman

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This study is experimentally targeting to develop effective in heat and mass transfer processes for the adsorbate to obtain applicable adsorption capacity data. This is done by using fin and tube heat exchanger core and the adsorbate is adhesive over its surface and located as the core of the adsorber. The pairs are activated carbon powder/R-134a, activated carbon powder/R-407c, activated carbon powder/R-507A, activated carbon granules/R-507A, activated carbon granules/R-407c and activated carbon granules/R-134a, at different adsorption temperatures of 25, 30, 35 and 50°C. The following is results is obtained: at adsorption temperature of 25 °C the maximum adsorption capacity is found to be 0.8352kg/kg for activated carbon powder with R-134a and the minimum adsorption capacity found to be 0.1583kg/kg for activated carbon granules with R-407c. While, at adsorption temperature of 50°C the maximum adsorption capacity is found to be 0.3207kg/kg for activated carbon powder with R-134a and the minimum adsorption capacity found to be 0.0609kg/kg for activated carbon granules with R-407c. Therefore, the activated carbon powder/R-134a pair is highly recommended to be used as adsorption refrigeration working pair because of its higher maximum adsorption capacity than the other tested pairs, to produce a compact, efficient and reliable for long life performance adsorption refrigeration system.

Keywords: Adsorption, Adsorbent/Adsorbate Pairs, Adsorption Capacity, Refrigeration.

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Authors: Mohd. Noor Md. Sap, A. Majid Awan

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Intelligent systems based on machine learning techniques, such as classification, clustering, are gaining wide spread popularity in real world applications. This paper presents work on developing a software system for predicting crop yield, for example oil-palm yield, from climate and plantation data. At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. This work gets inspiration from the notion that a non-linear data transformation into some high dimensional feature space increases the possibility of linear separability of the patterns in the transformed space. Therefore, it simplifies exploration of the associated structure in the data. Kernel methods implicitly perform a non-linear mapping of the input data into a high dimensional feature space by replacing the inner products with an appropriate positive definite function. In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering the data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.

Keywords: Pattern analysis, clustering, kernel methods, spatial data, crop yield

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Authors: Shiping Zhou, Minggen Cui

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This paper investigates the inverse problem of determining the unknown time-dependent leading coefficient in the parabolic equation using the usual conditions of the direct problem and an additional condition. An algorithm is developed for solving numerically the inverse problem using the technique of space decomposition in a reproducing kernel space. The leading coefficients can be solved by a lower triangular linear system. Numerical experiments are presented to show the efficiency of the proposed methods.

Keywords: parabolic equations, coefficient inverse problem, reproducing kernel.

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Authors: J. Mehena, M. C. Adhikary

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In this paper, a spatial multiple-kernel fuzzy C-means (SMKFCM) algorithm is introduced for segmentation problem. A linear combination of multiples kernels with spatial information is used in the kernel FCM (KFCM) and the updating rules for the linear coefficients of the composite kernels are derived as well. Fuzzy cmeans (FCM) based techniques have been widely used in medical image segmentation problem due to their simplicity and fast convergence. The proposed SMKFCM algorithm provides us a new flexible vehicle to fuse different pixel information in medical image segmentation and detection of MR images. To evaluate the robustness of the proposed segmentation algorithm in noisy environment, we add noise in medical brain tumor MR images and calculated the success rate and segmentation accuracy. From the experimental results it is clear that the proposed algorithm has better performance than those of other FCM based techniques for noisy medical MR images.

Keywords: Clustering, fuzzy C-means, image segmentation, MR images, multiple kernels.

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Authors: Rajneesh Rani, Renu Dhir, G. S. Lehal

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Script identification is one of the challenging steps in the development of optical character recognition system for bilingual or multilingual documents. In this paper an attempt is made for identification of English numerals at word level from Punjabi documents by using Gabor features. The support vector machine (SVM) classifier with five fold cross validation is used to classify the word images. The results obtained are quite encouraging. Average accuracy with RBF kernel, Polynomial and Linear Kernel functions comes out to be greater than 99%.

Keywords: Script identification, gabor features, support vector machines.

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Authors: H. Higashiyama, M. Sano, F. Nakanishi, M. Sugiyama, O. Takahashi, S. Tsukuma

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The heat island phenomenon becomes one of the environmental problems. As countermeasures in the field of road engineering, cool pavements such as water retaining pavements and solar radiation reflective pavements have been developed to reduce the surface temperature of asphalt pavements in the hot summer climate in Japan. The authors have studied on the water retaining pavements with cement–based grouting materials. The cement–based grouting materials consist of cement, ceramic waste powder, and natural zeolite. The ceramic waste powder is collected through the recycling process of electric porcelain insulators. In this study, mixing ratio between the ceramic waste powder and the natural zeolite and a type of cement for the cement–based grouting materials is investigated to measure the surface temperature of asphalt pavements in the outdoor. All of the developed cement–based grouting materials were confirmed to effectively reduce the surface temperature of the asphalt pavements. Especially, the cement–based grouting material using the ultra–rapid hardening cement with the mixing ratio of 0.7:0.3 between the ceramic waste powder and the natural zeolite reduced mostly the surface temperature by 20 °C and more.

Keywords: Ceramic waste powder, natural zeolite, road surface temperature, water retaining pavements.

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Authors: N. Mohseni, S. Janitabar, S. J. Ahmadi, M. Roshanzamir, M. Thaghizadeh

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In this research, thorium dioxide mesoporous nanocrystalline powder was synthesized through the sol-gel method using hydrated thorium nitrate and ammonium hydroxide as starting materials and Triton X100 as surfactant. ThO2 gel was characterized by thermogravimetric (TGA), and prepared ThO2 powder was subjected to scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer-Emett-Teller (BET) analyses studies. Detailed analyses show that prepared powder consisted of phase with the space group Fm3m of thoria and its crystalline size was 12.6 nm. The thoria possesses 16.7 m2/g surface area and the pore volume and size calculated to be 0.0423 cc/g and 1.947 nm, respectively.

Keywords: Thoria, sol-gel, mesoporous, nanocrystalline.

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Authors: Sandeep Kaur Chouhan, Jatinderdeep Kaur, S. S. Bhatia

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The existence of sine and cosine series as a Fourier series, their L1-convergence seems to be one of the difficult question in theory of convergence of trigonometric series in L1-metric norm. In the literature so far available, various authors have studied the L1-convergence of cosine and sine trigonometric series with special coefficients. In this paper, we present a modified cosine and sine sums and criterion for L1-convergence of these modified sums is obtained. Also, a necessary and sufficient condition for the L1-convergence of the cosine and sine series is deduced as corollaries.

Keywords: Conjugate Dirichlet kernel, Dirichlet kernel, L1-convergence, modified sums.

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Authors: Jatinderdeep Kaur

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In this paper, the results of Kano from one dimensional cosine and sine series are extended to two dimensional cosine and sine series. To extend these results, some classes of coefficient sequences such as class of semi convexity and class R are extended from one dimension to two dimensions. Further, the function f(x, y) is two dimensional Fourier Cosine and Sine series or equivalently it represents an integrable function or not, has been studied. Moreover, some results are obtained which are generalization of Moricz’s results.

Keywords: Conjugate Dirichlet kernel, conjugate Fejer kernel, Fourier series, Semi-convexity.

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Authors: A.T.Z. Mahamat, A.M. A Rani, Patthi Husain

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Copper based composites reinforced with WC and Ti particles were prepared using planetary ball-mill. The experiment was designed by using Taguchi technique and milling was carried out in an air for several hours. The powder was characterized before and after milling using the SEM, TEM and X-ray for microstructure and for possible new phases. Microstructures show that milled particles size and reduction in particle size depend on many parameters. The distance d between planes of atoms estimated from X-ray powder diffraction data and TEM image. X-ray diffraction patterns of the milled powder did not show clearly any new peak or energy shift, but the TEM images show a significant change in crystalline structure of corporate on titanium in the composites.

Keywords: ball milling, microstructures, titanium, tungstencarbides, X-ray

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Authors: K. A. D. N. K Wimalawarne

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In this paper we introduce a novel kernel classifier based on a iterative shrinkage algorithm developed for compressive sensing. We have adopted Bregman iteration with soft and hard shrinkage functions and generalized hinge loss for solving l1 norm minimization problem for classification. Our experimental results with face recognition and digit classification using SVM as the benchmark have shown that our method has a close error rate compared to SVM but do not perform better than SVM. We have found that the soft shrinkage method give more accuracy and in some situations more sparseness than hard shrinkage methods.

Keywords: Compressive sensing, Bregman iteration, Generalisedhinge loss, sparse, kernels, shrinkage functions

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Authors: Hyun-Woo Cho

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Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.

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Authors: D. Gazdič, I. Hájková, M. Fridrichová

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This paper involved the performance of a hightemperature X-Ray powder diffraction analysis (XRD) of a sample of chemical gypsum generated in the production of titanium white; this gypsum originates by neutralizing highly acidic water with limestone suspension. Specifically, it was gypsum formed in the first stage of neutralization when the resulting material contains, apart from gypsum, a number of waste products resulting from the decomposition of ilmenite by sulphuric acid. So it can be described as red titanogypsum. By conducting the experiment using XRD apparatus Bruker D8 Advance with a Cu anode (λkα=1.54184 Å) equipped with high-temperature chamber Anton Paar HTK 16, it was possible to identify clearly in the sample each phase transition in the system of CaSO4·xH2O.

Keywords: Anhydrite, Gypsum, Bassanite, Hematite, XRD, Powder, High-Temperature.

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Authors: Refaat M Mohamed, Ayman El-Baz, Aly A. Farag

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This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.

Keywords: Density Estimation, SVM, Learning Algorithms, Parameters Estimation.

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Authors: Abdullah Yassin, Takashi Ueda, Syed Tarmizi Syed Shazali

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This paper presents an experimental investigation on the machinability of laser-sintered material using small ball end mill focusing on wear mechanisms. Laser-sintered material was produced by irradiating a laser beam on a layer of loose fine SCM-Ni-Cu powder. Bulk carbon steel JIS S55C was selected as a reference steel. The effects of powder consolidation mechanisms and unsintered powder on the tool life and wear mechanisms were carried out. Results indicated that tool life in cutting laser-sintered material is lower than that in cutting JIS S55C. Adhesion of the work material and chipping were the main wear mechanisms of the ball end mill in cutting laser-sintered material. Cutting with the unsintered powder surrounding the tool and laser-sintered material had caused major fracture on the cutting edge.

Keywords: Laser-sintered material, tool life, wear mechanism.

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Authors: Naveen Beri, S. Maheshwari, C. Sharma, Anil Kumar

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In this paper an attempt has been made to correlate the usefulness of electrodes made through powder metallurgy (PM) in comparison with conventional copper electrode during electric discharge machining. Experimental results are presented on electric discharge machining of AISI D2 steel in kerosene with copper tungsten (30% Cu and 70% W) tool electrode made through powder metallurgy (PM) technique and Cu electrode. An L18 (21 37) orthogonal array of Taguchi methodology was used to identify the effect of process input factors (viz. current, duty cycle and flushing pressure) on the output factors {viz. material removal rate (MRR) and surface roughness (SR)}. It was found that CuW electrode (made through PM) gives high surface finish where as the Cu electrode is better for higher material removal rate.

Keywords: Electrical discharge machining (EDM), Powder Metallurgy (PM), Taguchi method, Material Removal Rate (MRR), Surface Roughness (SR).

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Authors: M. Ghobeiti-Hasab

Abstract:

Magnetic powder of Sr-ferrite was prepared by conventional and sol-gel auto-combustion methods. In conventional method, strontium carbonate and ferric oxide powders were mixed together and then mixture was calcined. In sol-gel auto-combustion method, a solution containing strontium nitrate, ferric nitrate and citric acid was heated until the combustion took place automatically; then, as-burnt powder was calcined. Thermal behavior, phase identification, morphology and magnetic properties of powders obtained by these two methods were compared by DTA, XRD, SEM and VSM techniques. According to the results of DTA analysis, formation temperature of Sr-ferrite obtained by conventional and solgel auto-combustion methods were 1300°C and 1000°C, respectively. XRD results confirmed the formation of pure Sr-ferrite at the mentioned temperatures. Plate and hexagonal-shape particles of Srferrite were observed using SEM. The Sr-ferrite powder obtained by sol-gel auto-combustion method had saturation magnetization of 66.03 emu/g and coercivity of 5731 Oe in comparison with values of 58.20 emu/g and 4378 Oe obtained by conventional method.

Keywords: Sr-ferrite, Sol-gel, Magnetic properties, Calcination.

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Authors: Abhishek Neogi, Jayesh Verma, Pinaki Pratim Acharjya

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Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.

Keywords: Image segmentation, edge Detection, noisy images, spatialfilters, stochastic gradient kernel.

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Authors: E. Abustam, M. I. Said, M. Yusuf, H. M. Ali

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This study aims to examine the sensory quality of meatballs made from Balinese beef and buffalo meat after the addition of smoke powder prior to storage at the temperatures of 2- 5°C for 7 days. This study used meat from Longissimus dorsi muscle of male Balinese cattle aged 3 years and of male buffalo aged 5 years as the main raw materials, and smoke powder as a binder and preservative in making meatballs. The study was based on completely randomized design (CRD) of factorial pattern of 2 x 3 x 2 where factors 1, 2 and 3 included the types of meat (cattle and buffalo), types of smoke powder (oven dried, freeze dried and spray dried) with a level of 2% of the weight of the meat (w/w), and storage duration (0 and 7 days) with three replications, respectively. The parameters measured were the meatball sensory quality (scores of tenderness, firmness, chewing residue, and intensity of flavor). The results of this study show that each type of meat has produced different sensory characteristics. The meatballs made from buffalo meat have higher tenderness and elasticity scores than the Balinese beef. Meanwhile, the buffalo meatballs have a lower residue mastication score than the Balinese beef. Each type of smoke powders has produced a relatively similar sensory quality of meatballs. It can be concluded that the smoke powder of 2% of the weight of the meat (w/w) could maintain the sensory quality of the meatballs for 7 days of storage.

Keywords: Balinese beef meatballs, buffalo meatballs, sensory quality, smoke powder.

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Authors: Rallapalli Revanth, Shivakumar Bhavi, Vijay Kumar Turaga

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Dispensing powders manually can be difficult as it requires to gradually pour and check the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and is user dependent and it is also difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various powder dispensing mechanisms are being designed to overcome these challenges. Battery operated screw conveyor mechanism is being innovated to overcome above problems faced. These inventions are numerically evaluated at concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in the development of such devices, saving time and money by reducing the number of prototypes and testing. In this study, powder dispensation from the trocar's end is simulated by using the Dense Discrete Phase Model technique along with Kinetic Theory of Granular Flow. The powder is viewed as a secondary flow in air (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation side is done by rotation of the screw conveyor. The performance is calculated for 1 sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and the effective area within a quick turnaround time frame.

Keywords: Multiphase flow, screw conveyor, transient, DDPM - KTGF.

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Authors: Mahidin, Yanna Syamsuddin, Samsul Rizal

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In order to fulfill world energy demand, several efforts have been done to look for new and renewable energy candidates to substitute oil and gas. Biomass is one of new and renewable energy sources, which is abundant in Indonesia. Palm kernel shell is a kind of biomass discharge from palm oil industries as a waste. On the other hand, Jatropha curcas that is easy to grow in Indonesia is also a typical energy source either for bio-diesel or biomass. In this study, biomass was used as co-fuel in briquetting of low-rank coal to suppress the release of emission (such as CO, NO_x and SO_x) during coal combustion. Desulfurizer, CaO-base, was also added to ensure the SO_x capture is effectively occurred. Ratio of coal to palm kernel shell (w/w) in the bio-briquette were 50:50, 60:40, 70:30, 80:20 and 90:10, while ratio of calcium to sulfur (Ca/S) in mole/mole were 1:1; 1.25:1; 1.5:1; 1.75:1 and 2:1. The bio-briquette then subjected to physical characterization and combustion test. The results show that the maximum weight loss in the durability measurement was ±6%. In addition, the highest stove efficiency for each desulfurizer was observed at the coal/PKS ratio of 90:10 and Ca/S ratio of 1:1 (except for the scallop shell desulfurizer that appeared at two Ca/S ratios; 1.25:1 and 1.5:1, respectively), i.e. 13.8% for the lime; 15.86% for the oyster shell; 14.54% for the scallop shell and 15.84% for the green mussel shell desulfurizers.

Keywords: Biomass, low-rank coal, bio-briquette, new and renewable energy, palm kernel shell.

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Authors: Serge B. Provost, Min Jiang

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The density estimates considered in this paper comprise a base density and an adjustment component consisting of a linear combination of orthogonal polynomials. It is shown that, in the context of density approximation, the coefficients of the linear combination can be determined either from a moment-matching technique or a weighted least-squares approach. A kernel representation of the corresponding density estimates is obtained. Additionally, two refinements of the Kronmal-Tarter stopping criterion are proposed for determining the degree of the polynomial adjustment. By way of illustration, the density estimation methodology advocated herein is applied to two data sets.

Keywords: kernel density estimation, orthogonal polynomials, moment-based methodologies, density approximation.

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Authors: A. A. Samat, N. A. Abdullah, M. A. M. Ishak, N. Osman

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Powder of La0.6Sr0.4CoO3-α (LSCO) was synthesized by a combined citrate-EDTA method. The as-synthesized LSCO powder was calcined, respectively at temperatures of 800, 900 and 1000 °C with different heating/cooling rates which are 2, 5, 10 and 15 °C min-1. The effects of heat treatments on the phase formation of perovskite phase of LSCO were investigated by powder X-ray diffraction (XRD). The XRD patterns revealed that the rate of 5 °C min-1 is the optimum heating/cooling rate to obtain a single perovskite phase of LSCO with calcination temperature of 800 °C. This result was confirmed by a thermogravimetric analysis (TGA) as it showed a complete decomposition of intermediate compounds to form oxide material was also observed at 800 °C.

Keywords: La0.6Sr0.4CoO3-α, heat treatment, perovskite-type oxide, XRD.

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Authors: Benjamin Gorry, Zezhi Chen, Kevin Hammond, Andy Wallace, Greg Michaelson

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This paper describes new computer vision algorithms that have been developed to track moving objects as part of a long-term study into the design of (semi-)autonomous vehicles. We present the results of a study to exploit variable kernels for tracking in video sequences. The basis of our work is the mean shift object-tracking algorithm; for a moving target, it is usual to define a rectangular target window in an initial frame, and then process the data within that window to separate the tracked object from the background by the mean shift segmentation algorithm. Rather than use the standard, Epanechnikov kernel, we have used a kernel weighted by the Chamfer distance transform to improve the accuracy of target representation and localization, minimising the distance between the two distributions in RGB color space using the Bhattacharyya coefficient. Experimental results show the improved tracking capability and versatility of the algorithm in comparison with results using the standard kernel. These algorithms are incorporated as part of a robot test-bed architecture which has been used to demonstrate their effectiveness.

Keywords: Hume, functional programming, autonomous vehicle, pioneer robot, vision.

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Authors: Hossein Kabir, Mojtaba Sadeghi

Abstract:

Nowadays, high-strength concrete is an integral element of a variety of high-rise buildings. On the other hand, finding a suitable aggregate size distribution is a great concern; hence, the concrete mix proportion is presented that has no coarse aggregate, which still withstands enough desirable strength. Nano Reactive Silica sand powder concrete (NRSSPC) is a type of concrete with no coarse material in its own composition. In this concrete, the only aggregate found in the mix design is silica sand powder with a size less than 150 mm that is infinitesimally small regarding the normal concrete. The research aim is to find the compressive strength of this particular concrete under the applied different conditions of curing and consolidation to compare the approaches. In this study, the young concrete specimens were compacted with a pressing or vibrating process. It is worthwhile to mention that in order to show the influence of temperature in the curing process, the concrete specimen was cured either in 20 ⁰C lime water or autoclaved in 90 ⁰C oven.

Keywords: Nano reactive silica sand powder concrete, consolidation, compressive strength, normal curing, thermal accelerated curing.

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Authors: Sung-Hae Jun, Kyung-Whan Oh

Abstract:

Statistical learning theory was developed by Vapnik. It is a learning theory based on Vapnik-Chervonenkis dimension. It also has been used in learning models as good analytical tools. In general, a learning theory has had several problems. Some of them are local optima and over-fitting problems. As well, statistical learning theory has same problems because the kernel type, kernel parameters, and regularization constant C are determined subjectively by the art of researchers. So, we propose an evolutionary statistical learning theory to settle the problems of original statistical learning theory. Combining evolutionary computing into statistical learning theory, our theory is constructed. We verify improved performances of an evolutionary statistical learning theory using data sets from KDD cup.

Keywords: Evolutionary computing, Local optima, Over-fitting, Statistical learning theory

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Authors: R. Bures, M. Streckova, M. Faberova, P. Kurek

Abstract:

Composite material based on Fe3Si micro-particles and Mn-Zn nano-ferrite was prepared using powder metallurgy technology. The sol-gel followed by autocombustion process was used for synthesis of Mn0.8Zn0.2Fe2O4 ferrite. 3 wt.% of mechanically milled ferrite was mixed with Fe3Si powder alloy. Mixed micro-nano powder system was homogenized by the Resonant Acoustic Mixing using ResodynLabRAM Mixer. This non-invasive homogenization technique was used to preserve spherical morphology of Fe3Si powder particles. Uniaxial cold pressing in the closed die at pressure 600 MPa was applied to obtain a compact sample. Microwave sintering of green compact was realized at 800°C, 20 minutes, in air. Density of the powders and composite was measured by Hepycnometry. Impulse excitation method was used to measure elastic properties of sintered composite. Mechanical properties were evaluated by measurement of transverse rupture strength (TRS) and Vickers hardness (HV). Resistivity was measured by 4 point probe method. Ferrite phase distribution in volume of the composite was documented by metallographic analysis. It has been found that nano-ferrite particle distributed among micro- particles of Fe3Si powder alloy led to high relative density (~93%) and suitable mechanical properties (TRS >100 MPa, HV ~1GPa, E-modulus ~140 GPa) of the composite. High electric resistivity (R~6.7 ohm.cm) of prepared composite indicate their potential application as soft magnetic material at medium and high frequencies.

Keywords: Micro- and nano-composite, soft magnetic materials, microwave sintering, mechanical and electric properties.

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Authors: P. Ninduangdee, V. I. Kuprianov

Abstract:

Palm kernel shell is an important bioenergy resource in Thailand. However, due to elevated alkali content in biomass ash, this oil palm residue shows high tendency to bed agglomeration in a fluidized-bed combustion system using conventional bed material (silica sand). In this study, palm kernel shell was burned in the conical fluidized-bed combustor (FBC) using alumina and dolomite as alternative bed materials to prevent bed agglomeration. For each bed material, the combustion tests were performed at 45kg/h fuel feed rate with excess air within 20–80%. Experimental results revealed rather weak effects of the bed material type but substantial influence of excess air on the behavior of temperature, O2, CO, CxHy, and NO inside the reactor, as well as on the combustion efficiency and major gaseous emissions of the conical FBC. The optimal level of excess air ensuring high combustion efficiency (about 98.5%) and acceptable level of the emissions was found to be about 40% when using alumina and 60% with dolomite. By using these alternative bed materials, bed agglomeration can be prevented when burning the shell in the proposed conical FBC. However, both bed materials exhibited significant changes in their morphological, physical and chemical properties in the course of the time.

Keywords: Palm kernel shell, fluidized-bed combustion, alternative bed materials, combustion and emission performance, bed agglomeration prevention.

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Authors: M. Bahgat, F. M. Awan, H. A. Hanafy

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The conventional ceramic route was utilized to prepare a hard magnetic powder (M-type strontium ferrite, SrFe12O19). The stoichiometric mixture of iron oxide and strontium carbonate were calcined at 1000oC and then fired at various temperatures. The influence of various reaction parameters such as mixing ratio, calcination temperature, firing temperature and firing time on the magnetic behaviors of the synthesized magnetic powder were investigated. The magnetic properties including Coercivity (Hc), Magnetic saturation (Ms), and Magnetic remnance (Mr) were measured by vibrating sample magnetometer. Morphologically the produced magnetic powder has a dense hexagonal grain shape structure.

Keywords: Hard magnetic materials, ceramic route, strontium ferrite, magnetic properties.

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Authors: Farhad Kolahan, Mohammad Bironro

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This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.

Keywords: Regression modeling, PMEDM, GeneticAlgorithm, Optimization.

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