Search results for: Expanding material

Authors: Noor Ul Ain Bhatti, M. Junaid Khan, Javed Ahmad, Murtaza Saleem, Shahid M. Ramay, Saadat A. Siddiqi

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Manganese oxide is being recently used as electrode material for rechargeable batteries. In this study, Al incorporated Mn₂O₃ compositions were synthesized to study the effect of Al doping on electrochemical performance of host material. Structural studies were carried out using X-ray diffraction analysis to confirm the phase stability and explore the lattice parameters, crystallite size, lattice strain, density and cell volume. Morphology and composition were analyzed using field emission scanning electron microscope and energy dispersive X-ray spectroscopy, respectively. Dynamic light scattering analysis was performed to observe the average particle size of the compositions. FTIR measurements exhibit the O-Al-O and O-Mn-O and Al-O bonding and with increasing the concentration of Al, the vibrational peaks of Mn-O become sharper. An enhanced electrochemical performance was observed in compositions with higher Al content.

Keywords: Mn2O3, electrode materials, energy storage and conversion, electrochemical performance.

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Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: Body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech.

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Authors: Jeong-Hyeon Kim, Ki-Yeob Kang, Myung-Hyun Kim, Jae-Myung Lee

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Primary barrier of membrane type LNG containment system consist of corrugated 304L stainless steel. This 304L stainless steel is austenitic stainless steel which shows different material behaviors owing to phase transformation during the plastic work. Even though corrugated primary barriers are subjected to significant amounts of pre-strain due to press working, quantitative mechanical behavior on the effect of pre-straining at cryogenic temperatures are not available. In this study, pre-strain level and pre-strain temperature dependent tensile tests are carried to investigate mechanical behaviors. Also, constitutive equations with material parameters are suggested for a verification study.

Keywords: Constitutive equation, corrugated sheet, pre-strain effect, elasto-visco-plastic-damage model, 304L stainless steel.

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Authors: Yung C. Ho, Hui C. Fang, Ming J. Hsieh

Abstract:

When consistently innovative business-models can give companies a competitive advantage, longitudinal empirical research, which can reflect dynamic business-model changes, has yet to prove a definitive connection. This study consequently employs a dynamic perspective in conjunction with innovation theory to examine the relationship between the types of business-model innovation and firm value. This study tries to examine various types of business-model innovation in high-end and low-end technology industries such as HTC and the 7-Eleven chain stores with research periods of 14 years and 32 years, respectively. The empirical results suggest that adopting radical business-model innovation in addition to expanding new target markets can successfully lead to a competitive advantage. Sustained advanced technological competences and service/product innovation are the key successful factors in high-end and low-end technology industry business-models respectively. In sum up, the business-model innovation can yield a higher market value and financial value in high-end technology industries than low-end ones.

Keywords: Business-model, Dynamic Perspective, Firm Value, Innovation

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Authors: Rafenomananjara Tsinjo Nirina, Tomoo Sekito, Andrianaivoravelona Jaconnet Oliva

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Manufacturing a composite material from post-consumer bottles is an interesting outlet since Madagascar is still facing the challenges of managing plastic waste on the one hand and appropriate waste treatment facilities are not yet developed on the other hand. New waste management options are needed to divert End-Of-Life (EOL) soft plastic wastes from landfills and incineration. Waste polyethylene terephthalate (PET) bottles might be considered as a valuable resource and recovered into polymer concrete. The methodology is easy to implement and appropriate to the local context in Madagascar. This approach will contribute to the production of ecological building materials that might be profitable for the environment and the construction sector. This work aims to study the feasibility of using the post-consumer PET bottles as an alternative binding agent instead of the conventional Portland cement and water. Then, the mechanical and physical properties of the materials were evaluated.

Keywords: PET recycling, polymer concrete, ecological building materials, pollution mitigation.

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Authors: T. Hacib, M. R. Mekideche, N. Ferkha

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This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Keywords: Inverse problem, MLP neural network, parametersidentification, FEM.

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Authors: Yousef Abu Nahleh, Arun Kumar, Fugen Daver

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Facility location is one of the important problems affecting the relief operations. The location model in this paper is motivated by arranging the flow of relief materials from the main warehouse to continent warehouse and further to regional warehouse and from these to the disaster area. This flow makes the relief organization always ready to deal with the disaster situation during shortest possible time. The main purpose of this paper is merge the concept of just in time and the campaign system in emergency supply chain,so that when the disaster happens the affected country can request help from the nearest regional warehouse, which will supply the relief material and the required stuff to support and assist the victims in the disaster area. Furthermore, the regional warehouse places an order to the continent warehouse to replenish the material that is distributed to the disaster area. This way they will always be ready to respond to any type of disaster.

Keywords: Facility location, Center-of-Gravity Technique, Humanitarian relief, emergency supply chain.

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Authors: Xu Tao, Yilun Xu, Dingwei Xiang, Yaofei Sun

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The practice of urban planning and construction based on the concept of the “low carbon eco-city” has been universally accepted by the academic community in response to urban issues such as population, resources, environment, and social development. Based on this, the current article first analyzes the concepts of low carbon eco-city, then builds a complex adaptive system (CAS) theory based on Chinese traditional philosophical thinking, and analyzes the adaptive relationship between material and non-material elements. A three-dimensional evaluation model of natural ecology, economic low carbon, and social harmony was constructed. Finally, the construction of a low carbon eco-city index system in Hexi Newtown of Nanjing was used as an example to verify the effectiveness of the research results; this paradigm provides a new way to achieve a low carbon eco-city system.

Keywords: Complex adaptive system, low carbon ecology, index system, model.

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Authors: Wei-Bo Hua, Zhuo Zheng, Xiao-Dong Guo, Ben-He Zhong

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The layered structure LiNi1/3Co1/3Mn1/3-xAlxO2 (x = 0 ~ 0.04) series cathode materials were synthesized by a carbonate co-precipitation method, followed by a high temperature calcination process. The influence of Al substitution on the microstructure and electrochemical performances of the prepared materials was investigated by X-Ray diffraction (XRD), scanning electron microscopy (SEM), and galvanostatic charge/discharge test. The results show that the LiNi1/3Co1/3Mn1/3-xAlxO2 has a well-ordered hexagonal α-NaFeO2 structure. Although the discharge capacity of Al-doped samples decreases as x increases, LiNi1/3Co1/3Mn1/3-0.02Al0.02O2 exhibits superior capacity retention at high voltage (4.6 V). Therefore, LiNi1/3Co1/3Mn1/3-0.02Al0.02O2 is a promising material for “green” vehicles.

Keywords: Lithium ion battery, carbonate co-precipitation, microstructure, electrochemical properties.

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Authors: Ekachai Phaisangittisagul, Rapeepol Chongprachawat

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Obtaining labeled data in supervised learning is often difficult and expensive, and thus the trained learning algorithm tends to be overfitting due to small number of training data. As a result, some researchers have focused on using unlabeled data which may not necessary to follow the same generative distribution as the labeled data to construct a high-level feature for improving performance on supervised learning tasks. In this paper, we investigate the impact of the relationship between unlabeled and labeled data for classification performance. Specifically, we will apply difference unlabeled data which have different degrees of relation to the labeled data for handwritten digit classification task based on MNIST dataset. Our experimental results show that the higher the degree of relation between unlabeled and labeled data, the better the classification performance. Although the unlabeled data that is completely from different generative distribution to the labeled data provides the lowest classification performance, we still achieve high classification performance. This leads to expanding the applicability of the supervised learning algorithms using unsupervised learning.

Keywords: Autoencoder, high-level feature, MNIST dataset, selftaught learning, supervised learning.

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Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour , Foad Saadi

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In this paper back-propagation artificial neural network (BPANN) is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

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Authors: Shahrazed Medeghri, Saad Hamzaoui, Mokhtar Zerdali

Abstract:

The metallurgical grade silicon (MG-Si) is obtained from the reduction of silica (SiO₂) in an induction furnace or an electric arc furnace. Impurities inherent in reduction process also depend on the quality of the raw material used. Among the applications of the silicon, it is used as a substrate for the photovoltaic conversion of solar energy and this conversion is wider as the purity of the substrate is important. Research is being done where the purpose is looking for new methods of manufacturing and purification of silicon, as well as new materials that can be used as substrates for the photovoltaic conversion of light energy. In this research, the technique of production of silicon in an induction furnace, using a high vacuum for fusion. Diatomaceous Silica (SiO2) used is 99 mass% initial purities, the carbon used is 6N of purity and the particle size of 63μm as starting materials. The final achieved purity of the material was above 50% by mass. These results demonstrate that this method is a technically reliable, and allows obtaining a better return on the amount 50% of silicon.

Keywords: Induction, amorphous silica, carbon microstructure, silicon.

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Authors: Katleho D. Makatjane, Kalebe M. Kalebe

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The present paper used time-varying parameters which are based on the score function of a probability density at time t to model volatility of saving rate. We used a scaled likelihood function to update the parameters of the model overtime. Our results revealed high diligence of time-varying since the location parameter is greater than zero. Furthermore, we discovered a leptokurtic condition on saving rate’s distribution. Kapetanios, Shin-Shell Nonlinear Augmented Dickey-Fuller (KSS-NADF) test showed that the saving rate has a nonlinear unit root; therefore, it can be modeled by a generalised autoregressive score (GAS) model. Additionally, value at risk (VaR) and conditional tail expectation (CTE) indicate that 99% of the time people in Lesotho are saving more than spending. This puts the economy in high risk of not expanding. Therefore, the monetary policy committee (MPC) of Lesotho should revise their monetary policies towards this high saving rates risk.

Keywords: Generalized autoregressive score, time-varying, saving rate, Lesotho.

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Authors: S. Jedari Salami

Abstract:

In this paper the effects of adding an extra layer within a sandwich panel and core- types in top and bottom cores on quasi- static loading are studied experimentally. The panel includes polymer composite laminated sheets for faces and the internal laminated sheet called extra layer sheet, and two types of crushable foams are selected as the core material. Quasi- static tests were done by ZWICK testing machine on fully backed specimens with two foam cores, Poly Urethane Rigid (PUR) and Poly Vinyl Chloride (PVC). It was found that the core material type has made significant role on improving the sandwich panel’s behavior compared with the effect of extra layer location.

Keywords: Multi-layer sandwich structures, Internal sheet, Crushable foam, Top core, Bottom core.

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Authors: Saad Alkhaldi, Fadi Ghammas, Tariq Alghamdi, Stefano Alexandirs

Abstract:

The operating conditions and corrosive nature of the process fluid in the Haradh and Hawiyah areas are subjecting facility piping to undesirable corrosion phenomena. Therefore, production headers inside remote headers have been internally cladded with high alloy material to mitigate the corrosion damage mechanism. Corrosion mitigation in the jump-over lines, constructed between the existing flowlines and the newly constructed facilities to provide operational flexibility, is proposed. This corrosion mitigation system includes the application of fusion bond epoxy (FBE) coating on the internal surface of the pipe and depositing corrosion-resistant alloy (CRA) weld layers at pipe and fittings ends to protect the carbon steel material. In addition, high alloy CRA weld material is used to deposit the girth weld between the 90-degree elbows and mating internally coated segments. A rigorous testing and qualification protocol was established prior to actual adoption at the Haradh and Hawiyah Field Gas Compression Program, currently being executed by Saudi Aramco. The proposed mitigation system, aimed at applying the cladding at the ends of the internally FBE coated pipes/elbows, will resolve field joint coating challenges, eliminate the use of approximately 1700 breakout flanges, and prevent the potential hydrocarbon leaks.

Keywords: Corrosion, FBE coated sour service, cost savings.

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Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

Abstract:

OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

Keywords: Open multimodal emotion corpus, annotated labels.

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Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

Abstract:

OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

Keywords: Open multimodal emotion corpus, annotated labels.

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Authors: M. Ondova, A. Estokova

Abstract:

Rapid industrialization results in increased use of natural resources bring along serious ecological and environmental imbalance due to the dumping of industrial wastes. Principles of sustainable construction have to be accepted with regard to the consumption of natural resources and the production of harmful emissions. Cement is a great importance raw material in the building industry and today is its large amount used in the construction of concrete pavements. Concerning raw materials cost and producing CO₂ emission the replacing of cement in concrete mixtures with more sustainable materials is necessary. To reduce this environmental impact people all over the world are looking for a solution. Over a period of last ten years, the image of fly ash has completely been changed from a polluting waste to resource material and it can solve the major problems of cement use. Fly ash concretes are proposed as a potential approach for achieving substantial reductions in cement. It is known that it improves the workability of concrete, extends the life cycle of concrete roads, and reduces energy use and greenhouse gas as well as amount of coal combustion products that must be disposed in landfills.

Life cycle assessment also proved that a concrete pavement with fly ash cement replacement is considerably more environmentally friendly compared to standard concrete roads. In addition, fly ash is cheap raw material, and the costs saving are guaranteed. The strength properties, resistance to a frost or de-icing salts, which are important characteristics in the construction of concrete pavements, have reached the required standards as well. In terms of human health it can´t be stated that a concrete cover with fly ash could be dangerous compared with a cover without fly ash. Final Multi-criteria analysis also pointed that a concrete with fly ash is a clearly proper solution.

Keywords: Life cycle assessment, fly ash, waste, concrete pavements

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Authors: Mercy M. Ramakokovhu, Henry Kasaini, Richard K.K. Mbaya

Abstract:

The copper flotation tailings from Konkola Copper mine in Nchanga, Zambia were used in the study. The purpose of this study was to determine the leaching characteristics of the tailings material prior and after the physical beneficiation process is employed. The Knelson gravity concentrator (KC-MD3) was used for the beneficiation process. The copper leaching efficiencies and impurity co-extraction percentages in both the upgraded and the raw feed material were determined at different pH levels and temperature. It was observed that the copper extraction increased with an increase in temperature and a decrease in pH levels. In comparison to the raw feed sample, the upgraded sample reported a maximum copper extraction of 69% which was 9%, higher than raw feed % extractions. The impurity carry over was reduced from 18% to 4 % on the upgraded sample. The reduction in impurity co-extraction was as a result of the removal of the reactive gangue elements during the upgrading process, this minimized the number of side reaction occurring during leaching.

Keywords: Atmospheric leaching, Copper, Iron, Knelson concentrator

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Authors: B. S. Sindu, Saptarshi Sasmal, Smitha Gopinath

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Cement, the most widely used construction material is very brittle and characterized by low tensile strength and strain capacity. Macro to nano fibers are added to cement to provide tensile strength and ductility to it. Carbon Nanotube (CNT), one of the nanofibers, has proven to be a promising reinforcing material in the cement composites because of its outstanding mechanical properties and its ability to close cracks at the nano level. The experimental investigations for CNT reinforced cement is costly, time consuming and involves huge number of trials. Mathematical modeling of CNT reinforced cement can be done effectively and efficiently to arrive at the mechanical properties and to reduce the number of trials in the experiments. Hence, an attempt is made to numerically study the effective mechanical properties of CNT reinforced cement numerically using Representative Volume Element (RVE) method. The enhancement in its mechanical properties for different percentage of CNTs is studied in detail.

Keywords: Carbon Nanotubes, Cement composites, Representative Volume Element, Numerical simulation

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Authors: M. K. Pradhan, C. K. Biswas,

Abstract:

In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively

Keywords: Electrical discharge machining, material removal rate, neuro-fuzzy model, regression model, mountain clustering.

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Authors: Young-Jun You, Ki-Tae Park, Kyu-Wan Lee

Abstract:

Since prestressed concrete members rely on the tensile strength of the prestressing strands to resist loads, loss of even few them could result catastrophic. Therefore, it is important to measure present residual prestress force. Although there are some techniques for obtaining present prestress force, some problems still remain. One method is to install load cell in front of anchor head but this may increase cost. Load cell is a transducer using the elastic material property. Anchor head is also an elastic material and this might result in monitoring monitor present prestress force. Features of fiber optic sensor such as small size, great sensitivity, high durability can assign sensing function to anchor head. This paper presents the concept of smart anchor head which acts as load cell and experiment for the applicability of it. Test results showed the smart anchor head worked good and strong linear relationship between load and response.

Keywords: SHM, prestress force, anchor head, fiber optic sensor

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Authors: Carmen E. Zapata, Juan Bautista, Olga Montoya, Claudia Moreno, Marisol Suarez, Alejandra Betancur, Duvan Nanclares, Natalia A. Cano

Abstract:

This study aims to evaluate the diversity of microorganisms in filters PM2.5 and PM10; and determine the genotoxic and cytotoxic activity of the complex mixture present in PM2.5 filters used in the Aburrá Valley Air Quality Monitoring Network (Colombia). The research results indicate that particulate matter PM2.5 of different monitoring stations are bacteria; however, this study of detection of bacteria and their phylogenetic relationship is not complete evidence to connect the microorganisms with pathogenic or degrading activities of compounds present in the air. Additionally, it was demonstrated the damage induced by the particulate material in the cell membrane, lysosomal and endosomal membrane and in the mitochondrial metabolism; this damage was independent of the PM2.5 concentrations in almost all the cases.

Keywords: Cytotoxic, genotoxic, microbiological analysis, PM10, PM2.5.

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Authors: B. Bakken, O. Boe

Abstract:

The Norwegian Military Academy (Army) has initiated a project with the main ambition to explore possible avenues to enhancing operational effectiveness through an increased use of simulation-based training and exercises. Within a cost/benefit framework, we discuss opportunities and limitations of vertical and horizontal integration of the existing tactical training system. Vertical integration implies expanding the existing training system to span the full range of training from tactical level (platoon, company) to command and staff level (battalion, brigade). Horizontal integration means including other domains than army tactics and staff procedures in the training, such as military ethics, foreign languages, leadership and decision making. We discuss each of the integration options with respect to purpose and content of training, "best practice" for organising and conducting simulation-based training, and suggest how to evaluate training procedures and measure learning outcomes. We conclude by giving guidelines towards further explorative work and possible implementation.

Keywords: Effectiveness, integration, simulation, training.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour

Abstract:

In this paper back-propagation artificial neural network (BPANN )with Levenberg–Marquardt algorithm is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

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Authors: A.R.Tahmasebi Birgani, M.Hosseinjani Zamenjani, M.R.Isvandzibaei

Abstract:

In the present work, study of the vibration of thin cylindrical shells made of a functionally gradient material (FGM) composed of stainless steel and nickel is presented. Material properties are graded in the thickness direction of the shell according to volume fraction power law distribution. The objective is to study the natural frequencies, the influence of constituent volume fractions and the effects of boundary conditions on the natural frequencies of the FG cylindrical shell. The study is carried out using third order shear deformation shell theory. The governing equations of motion of FG cylindrical shells are derived based on shear deformation theory. Results are presented on the frequency characteristics, influence of constituent volume fractions and the effects of free-free boundary conditions.

Keywords: Vibration, FGM, Cylindrical shell.

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Authors: Gülşah Kanbur, Veysel Ayhan

Abstract:

Feed oil samples which are used as mixed feed raw material were taken from six different feed factories in March, May and July. All factories make production in Konya, Turkey and all of the samples were crude soybean oils. Physical and chemical analyses, free radical scavenger effect, and total phenol content were determined on these oil samples. Moisture (M) content was found between 0.10-22.23%, saponification number (SF) was determined 143.13 to 167.93 KOH/kg, free fatty acidity (FFA) was varied 0.73 to 35.00%, peroxide value (PV) was found between 1.53 and 28.43 meq/kg, unsaponifiable matter (USM) was determined from 0.40 to 17.10%, viscosity (V) was found between 34.30 and 625.67 mPas, sediment (S) amount was determined between 0.60-18.16%, free radical scavenger effect (FRSE) was varied 20.7 to 43.04% inhibition of the extract and total phenol (TPC) content was found between 1.20 and 2.69mg/L extract. Different results were found between months and factories.

Keywords: Crude soybean oil, Feed oils, mixed feed.

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Authors: M.Z. Islam, C.W. Lim

Abstract:

Based on the standard finite element method, a new finite element method which is known as nonlocal finite element method (NL-FEM) is numerically implemented in this article to study the nonlocal effects for solving 1D nonlocal elastic problem. An Eringen-type nonlocal elastic model is considered. In this model, the constitutive stress-strain law is expressed interms of integral equation which governs the nonlocal material behavior. The new NL-FEM is adopted in such a way that the postulated nonlocal elastic behavior of material is captured by a finite element endowed with a set of (cross-stiffness) element itself by the other elements in mesh. An example with their analytical solutions and the relevant numerical findings for various load and boundary conditions are presented and discussed in details. It is observed from the numerical solutions that the torsional deformation angle decreases with increasing nonlocal nanoscale parameter. It is also noted that the analytical solution fails to capture the nonlocal effect in some cases where numerical solutions handle those situation effectively which prove the reliability and effectiveness of numerical techniques.

Keywords: NL-FEM, nonlocal elasticity, nanoscale, torsion.

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Authors: Md. Z. Alam, Devi R. Asih, Md. N. Salleh

Abstract:

Immobilization of lipase enzyme produced from palm oil mill effluent (POME) by the activated carbon (AC) among the low cost support materials was optimized. The results indicated that immobilization of 94% was achieved by AC as the most suitable support material. A sequential optimization strategy based on a statistical experimental design, including one-factor-at-a-time (OFAT) method was used to determine the equilibrium time. Three components influencing lipase immobilization were optimized by the response surface methodology (RSM) based on the face-centered central composite design (FCCCD). On the statistical analysis of the results, the optimum enzyme concentration loading, agitation rate and carbon active dosage were found to be 30 U/ml, 300 rpm and 8 g/L respectively, with a maximum immobilization activity of 3732.9 U/g-AC after 2 hrs of immobilization. Analysis of variance (ANOVA) showed a high regression coefficient (R²) of 0.999, which indicated a satisfactory fit of the model with the experimental data. The parameters were statistically significant at p<0.05.

Keywords: Activated carbon, adsorption, immobilization, POME based lipase.

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