Search results for: Experimental Evaluation

Authors: Clement M. Matasane, Mohamed T. Kahn

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Biomass resources such as animal waste, agricultural and acro-industrial residues, forestry and woodland waste, and industrial and municipal solid wastes provide alternative means to utilize its untapped potential for biomass/biofuel renewable energy systems. In addition, crop residues (i.e., grain, starch, and energy crops) are commonly available in the district and play an essential role in community farming activities. The remote sensing technology (mappings) and geographic information systems tool will be used to determine the biomass potential in the Vhembe District Municipality. The detailed assessment, estimation, and modeling in quantifying their distribution, abundance, and quality yield an effective and efficient use of their potential. This paper aims to examine the potential and prospects of deploying bioenergy systems in small or micro-systems in the district for community use and applications. This deployment of the biofuels/biomass systems will help communities for sustainable energy supply from their traditional energy use into innovative and suitable methods that improve their livelihood. The study demonstrates the potential applications of Geographical Information Systems (GIS) in spatial mapping analysis, evaluation, modeling, and decision support for easy access to renewable energy systems.

Keywords: Agricultural crops, waste materials, biomass potentials, bioenergy potentials, GIS mappings, environmental data, renewable energy deployment, sustainable energy supply.

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Authors: K. Okubo, Y. Kurihara, T. Kaburagi, K. Watanabe

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Many of the ever-growing elderly population require exercise, such as running, for health management. One important element of a runner’s training is the choice of shoes for exercise; shoes are important because they provide the interface between the feet and road. When we purchase shoes, we may instinctively choose a pair after trying on many different pairs of shoes. Selecting the shoes instinctively may work, but it does not guarantee a suitable fit for running activities. Therefore, if we could select suitable shoes for each runner from the viewpoint of brain activities, it would be helpful for validating shoe selection. In this paper, we describe how brain activities show different characteristics during particular task, corresponding to different properties of shoes. Using five subjects, we performed a verification experiment, applying weight, softness, and flexibility as shoe properties. In order to affect the shoe property’s differences to the brain, subjects run for 10 min. Before and after running, subjects conducted a paced auditory serial addition task (PASAT) as the particular task; and the subjects’ brain activities during the PASAT are evaluated based on oxyhemoglobin and deoxyhemoglobin relative concentration changes, measured by near-infrared spectroscopy (NIRS). When the brain works actively, oxihemoglobin and deoxyhemoglobin concentration drastically changes; therefore, we calculate the maximum values of concentration changes. In order to normalize relative concentration changes after running, the maximum value are divided by before running maximum value as evaluation parameters. The classification of the groups of shoes is expressed on a self-organizing map (SOM). As a result, deoxyhemoglobin can make clusters for two of the three types of shoes.

Keywords: Brain activities, NIRS, PASAT, running shoes.

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Authors: Yu Shi, Rong Liu, Jingyun Lv

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Compression textiles with ergonomic-fit and controllable pressure performance have demonstrated positive effect on prevention and treatment of chronic venous insufficiency (CVI). Well-designed compression textile products contribute to improving user compliance in their daily application. This study explored the effects of multiple knitting variables (yarn-machinery settings) on the physical-mechanical properties and the produced pressure magnitudes of tubular compression fabrics (TCFs) through experimental testing and multiple regression modeling. The results indicated that fabric physical (stitch densities and circumference) and mechanical (tensile) properties were affected by the linear density of inlay yarns, which, to some extent, influenced pressure magnitudes of the TCFs. Knitting variables (e.g., feeding velocity of inlay yarns and loop size settings) can alter circumferences and tensile properties of tubular fabrics, respectively, and significantly varied pressure values of the TCFs. This study enhanced the understanding of the effects of knitting factors on pressure controlling of TCFs, thus facilitating dimension and pressure design of compression textiles in future development.

Keywords: Laid-in knitted fabric, yarn-machinery settings, pressure magnitudes, quantitative analysis, compression textiles.

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Authors: Aynur Aker, Hasan Kaya

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In recent years, the use of the aluminum based alloys in the industry and technology are increasing. Alloying elements in aluminum have further been improving the strength and stiffness properties that provide superior compared to other metals. In this study, investigation of physical properties (microstructure, microhardness, tensile strength, electrical conductivity and thermal properties) in the Al-12.6wt.%Si-%2wt.Ni ternary alloy were investigated. Al-Si-Ni alloy was prepared in vacuum atmosphere. The samples were directionally solidified upwards with different growth rate V (8.3−165.45 μm/s) at constant temperature gradient G (7.73 K/mm). The flake spacings (λ), microhardness (HV), ultimate tensile strength (σ), electrical resistivity (ρ) and thermal properties (H, Cp, Tm) of the samples were measured. Influence of the growth rate and spacings on microhardness, ultimate tensile strength and electrical resistivity were investigated and relationships between them were obtained. According to results, λ values decrease with increasing V, but HV, σ and ρ values increase with increasing V. Variations of electrical resistivity (ρ) of solidified samples were also measured. The enthalpy of fusion (H) and specific heat (Cp) for the alloy was also determined by differential scanning calorimeter (DSC) from heating trace during the transformation from liquid to solid. The results in this work were compared with the previous similar experimental results.

Keywords: Electrical resistivity, enthalpy, microhardness, solidification, tensile stress.

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Authors: B. Soleimani

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Paleoclimate was reconstructed by the clay mineral assemblages of shale units of Pabdeh (Paleocene- Oligocene), Gurpi (Upper Cretaceous), Kazhdumi (Albian-Cenomanian) and Gadvan (Aptian-Neocomian) formations in the Bangestan anticline. To compare with clay minerals assemblages in these formations, selected samples also taken from available formations in drilled wells in Ahvaz, Marun, Karanj, and Parsi oil fields. Collected samples prepared using standard clay mineral methodology. They were treated as normal, glycolated and heated oriented glass slides. Their identification was made on X-Ray diffractographs. Illite % varies from 8 to 36. Illite quantity increased from Pabdeh to Gurpi Formation. This may be due to dominant dry climate. Kaolinite is in range of 12-49%. Its variation style in different formations could be a marker of climate changes from wet to dry which is supported by the lithological changes. Chlorite (4-28%) can also be detected in those samples without any kaolinite. Mixed layer minerals as the mixture of illite-chlorite and illite-vermiculite-montmorillonite are varied from 6 to 36%, decreased during Kazhdumi deposition from the base to the top. This result may be according to decreasing of illite leaching process. Vermiculite was also determined in very less quantity and found in those units without kaolinite. Montmorillonite varies from 8 to 43%, and its presence is due to terrestrial depositional condition. Stratigraphical documents is also supported this idea that clay mineral distribution is a function of the climate changes. It seems, thus, the present results can be indicated a possible procedure for ancient climate changes evaluation.

Keywords: Clay Minerals, Paleoclimate, XRD, oriented slide

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Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle

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This paper presents a critical study about the application of Neural Networks to ion-exchange process. Ionexchange is a complex non-linear process involving many factors influencing the ions uptake mechanisms from the pregnant solution. The following step includes the elution. Published data presents empirical isotherm equations with definite shortcomings resulting in unreliable predictions. Although Neural Network simulation technique encounters a number of disadvantages including its “black box", and a limited ability to explicitly identify possible causal relationships, it has the advantage to implicitly handle complex nonlinear relationships between dependent and independent variables. In the present paper, the Neural Network model based on the back-propagation algorithm Levenberg-Marquardt was developed using a three layer approach with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and linear transfer function (purelin) at out layer. The above mentioned approach has been used to test the effectiveness in simulating ion exchange processes. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values of copper ions removed from aqueous solutions.

Keywords: Copper, ion-exchange process, neural networks, simulation

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Authors: S. Deswal, M. Pal

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The paper aims to compare the performance of vertical and inclined multiple plunging jets and to model and predict their mass transfer capacity by multi-linear regression based approach. The multiple vertical plunging jets have jet impact angle of θ = 90^O; whereas, multiple inclined plunging jets have jet impact angle of θ = 60^O. The results of the study suggests that mass transfer is higher for multiple jets, and inclined multiple plunging jets have up to 1.6 times higher mass transfer than vertical multiple plunging jets under similar conditions. The derived relationship, based on multi-linear regression approach, has successfully predicted the volumetric mass transfer coefficient (K_La) from operational parameters of multiple plunging jets with a correlation coefficient of 0.973, root mean square error of 0.002 and coefficient of determination of 0.946. The results suggests that predicted overall mass transfer coefficient is in good agreement with actual experimental values; thereby, suggesting the utility of derived relationship based on multi-linear regression based approach and can be successfully employed in modeling mass transfer by multiple plunging jets.

Keywords: Mass transfer, multiple plunging jets, multi-linear regression.

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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: P. Kamphikul, P. Krachodnok, R. Wongsan

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This paper presents the gain improvement of a sector antenna for mobile phone base station by using the new technique to enhance its gain for microstrip antenna (MSA) array without construction enlargement. The curved woodpile Electromagnetic Band Gap (EBG) has been utilized to improve the gain instead. The advantages of this proposed antenna are reducing the length of MSAs array but providing the higher gain and easy fabrication and installation. Moreover, it provides a fan-shaped radiation pattern, wide in the horizontal direction and relatively narrow in the vertical direction, which appropriate for mobile phone base station. The paper also presents the design procedures of a 1x8 MSAs array associated with U-shaped reflector for decreasing their back and side lobes. The fabricated curved woodpile EBG exhibits bandgap characteristics at 2.1 GHz and is utilized for realizing a resonant cavity of MSAs array. This idea has been verified by both the Computer Simulation Technology (CST) software and experimental results. As the results, the fabricated proposed antenna achieves a high gain of 20.3 dB and the half-power beam widths in the E- and H-plane of 36.8 and 8.7 degrees, respectively. Good qualitative agreement between measured and simulated results of the proposed antenna was obtained.

Keywords: Gain Improvement, Microstrip Antenna Array, Electromagnetic Band Gap, Base Station.

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Authors: Khwaja Naweed Seddiqi, Zabihullah Mahdi, Shigeo Honma

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Recently increasing oil production from petroleum reservoirs is one of the most important issues in the global energy sector. So, in this paper, the recovery of oil by the waterflooding technique from petroleum reservoir are considered. To investigate the aforementioned phenomena, the relative permeability of two immiscible fluids in sand is measured in the laboratory based on the steady-state method. Two sorts of oils, kerosene and heavy oil, and water are pumped simultaneously into a vertical sand column with different pumping ratio. From the change in fractional discharge measured at the outlet, a method for determining the relative permeability is developed focusing on the displacement mechanism in sand. Then, displacement mechanism of two immiscible fluids in the sand is investigated under the Buckley-Leveret frontal displacement theory and laboratory experiment. Two sorts of experiments, one is the displacement of pore water by oil, the other is the displacement of pore oil by water, are carried out. It is revealed that the relative permeability curves display tolerably different shape owing to the properties of oils, and produce different amount of residual oils and irreducible water saturation.

Keywords: Petroleum reservoir engineering, relative permeability, two-phase flow, immiscible displacement in porous media, steady-state method, waterflooding.

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Authors: Thirasak Panyaphirawat, Pairoj Sapsmarnwong, Teeratas Pornyungyuen

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This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.

Keywords: Design of Experiment, Taguchi Design, Optimization, Analysis of Variance, Machining Parameters, Horizontal Boring Tool.

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Authors: A. W. J. Wong, I. H. Ibrahim

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Increasing urbanisation has driven building designers to incorporate natural ventilation in the designs of sustainable buildings. This project utilises Computational Fluid Dynamics (CFD) to investigate the natural ventilation of an academic building, SIT@SP, using an assessment criterion based on daily mean temperature and mean velocity. The areas of interest are the pedestrian level of first and fourth levels of the building. A reference case recommended by the Architectural Institute of Japan was used to validate the simulation model. The validated simulation model was then used for coupled simulations on SIT@SP and neighbouring geometries, under two wind speeds. Both steady and transient simulations were used to identify differences in results. Steady and transient results are agreeable with the transient simulation identifying peak velocities during flow development. Under a lower wind speed, the first level was sufficiently ventilated while the fourth level was not. The first level has excessive wind velocities in the higher wind speed and the fourth level was adequately ventilated. Fourth level flow velocity was consistently lower than those of the first level. This is attributed to either simulation model error or poor building design. SIT@SP is concluded to have a sufficiently ventilated first level and insufficiently ventilated fourth level. Future works for this project extend to modifying the urban geometry, simulation model improvements, evaluation using other assessment metrics and extending the area of interest to the entire building.

Keywords: Buildings, CFD simulation, natural ventilation, urban airflow.

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Authors: S. Alrekabi, A. Cundy, A. Lampropoulos, I. Savina

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Due to their remarkable mechanical properties, multi-wall carbon nanotubes (MWCNTs) are considered by many researchers to be a highly promising filler and reinforcement agent for enhanced performance cementitious materials. Currently, however, achieving an effective dispersion of MWCNTs remains a major challenge in developing high performance nano-cementitious composites, since carbon nanotubes tend to form large agglomerates and bundles as a consequence of Van der Waals forces. In this study, effective dispersion of low concentrations of MWCNTs at 0.01%, 0.025%, and 0.05% by weight of cement in the composite was achieved by applying different sonication conditions in combination with the use of polycarboxylate ether as a surfactant. UV-Visible spectroscopy and Transmission electron microscopy (TEM) were used to assess the dispersion of MWCNTs in water, while the dispersion states of MWCNTs within the cement composites and their surface interactions were examined by scanning electron microscopy (SEM). A high sonication intensity applied over a short time period significantly enhanced the dispersion of MWCNTs at initial mixing stages, and 0.025% of MWCNTs wt. of cement, caused 86% and 27% improvement in tensile strength and compressive strength respectively, compared with a plain cement mortar.

Keywords: Dispersion, multiwall carbon nanotubes, mechanical performance, sonication conditions.

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Authors: Ick Hoon Jang, Hoon Jae Lee, Dae Hoon Kwon, Ui Young Pak

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In this paper, we propose a texture feature-based language identification using wavelet-domain BDIP (block difference of inverse probabilities) and BVLC (block variance of local correlation coefficients) features and FFT (fast Fourier transform) feature. In the proposed method, wavelet subbands are first obtained by wavelet transform from a test image and denoised by Donoho-s soft-thresholding. BDIP and BVLC operators are next applied to the wavelet subbands. FFT blocks are also obtained by 2D (twodimensional) FFT from the blocks into which the test image is partitioned. Some significant FFT coefficients in each block are selected and magnitude operator is applied to them. Moments for each subband of BDIP and BVLC and for each magnitude of significant FFT coefficients are then computed and fused into a feature vector. In classification, a stabilized Bayesian classifier, which adopts variance thresholding, searches the training feature vector most similar to the test feature vector. Experimental results show that the proposed method with the three operations yields excellent language identification even with rather low feature dimension.

Keywords: BDIP, BVLC, FFT, language identification, texture feature, wavelet transform.

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Authors: Youngsuck Ji, Youngjoon Han, Hernsoo Hahn

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In this paper, we proposed the robust mobile object detection method for light effect in the night street image block based updating reference background model using block state analysis. Experiment image is acquired sequence color video from steady camera. When suddenly appeared artificial illumination, reference background model update this information such as street light, sign light. Generally natural illumination is change by temporal, but artificial illumination is suddenly appearance. So in this paper for exactly detect artificial illumination have 2 state process. First process is compare difference between current image and reference background by block based, it can know changed blocks. Second process is difference between current image-s edge map and reference background image-s edge map, it possible to estimate illumination at any block. This information is possible to exactly detect object, artificial illumination and it was generating reference background more clearly. Block is classified by block-state analysis. Block-state has a 4 state (i.e. transient, stationary, background, artificial illumination). Fig. 1 is show characteristic of block-state respectively [1]. Experimental results show that the presented approach works well in the presence of illumination variance.

Keywords: Block-state, Edge component, Reference backgroundi, Artificial illumination.

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Authors: Madhujit Deb, G. R. K. Sastry, R. S. Panua, Rahul Banerjee, P. K. Bose

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The present work attempts to investigate the combustion, performance and emission characteristics of an existing single-cylinder four-stroke compression-ignition engine operated in dual-fuel mode with hydrogen as an alternative fuel. Environmental concerns and limited amount of petroleum fuels have caused interests in the development of alternative fuels like hydrogen for internal combustion (IC) engines. In this experimental investigation, a diesel engine is made to run using hydrogen in dual fuel mode with diesel, where hydrogen is introduced into the intake manifold using an LPGCNG injector and pilot diesel is injected using diesel injectors. A Timed Manifold Injection (TMI) system has been developed to vary the injection strategies. The optimized timing for the injection of hydrogen was 10^0 CA after top dead center (ATDC). From the study it was observed that with increasing hydrogen rate, enhancement in brake thermal efficiency (BTHE) of the engine has been observed with reduction in brake specific energy consumption (BSEC). Furthermore, Soot contents decrease with an increase in indicated specific NOx emissions with the enhancement of hydrogen flow rate.

Keywords: Diesel engine, Hydrogen, BTHE, BSEC, Soot, NOx.

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Authors: T. Aldeeb, M. Abduelmula

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This study examines the fatigue life of S275 mild steel at room temperature. Mechanical components can fail under cyclic loading during period of time, known as the fatigue phenomenon. In order to prevent fatigue induced failures, material behavior should be investigated to determine the endurance limit of the material for safe design and infinite life, thus leading to reducing the economic cost and loss in human lives. The fatigue behavior of S275 mild steel was studied and investigated. Specimens were prepared in accordance with ASTM E3-11, and fatigue tests of the specimen were conducted in accordance with ASTM E466-07 on a smooth plate, with a continuous radius between ends (hourglass-shaped plate). The method of fatigue testing was applied with constant load amplitude and constant frequency of 4 Hz with load ratio (Fully Reversal R= -1). Surface fractures of specimens were investigated using Scanning Electron Microscope (SEM). The experimental results were compared with the results of a Finite Element Analysis (FEA), using simulation software. The experiment results indicated that the endurance fatigue limit of S275 mild steel was 195.47 MPa.

Keywords: Fatigue life, fatigue strength, finite element analysis, S275 mild steel, scanning electron microscope.

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Authors: F. Hekmatipour, M. A. Akhavan-Behabadi, B. Sajadi

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In this paper, the combined free and forced convection heat transfer of the Copper Oxide-Heat Transfer Oil (CuO-HTO) nanofluid flow in horizontal and inclined microfin tubes is studied experimentally. The flow regime is laminar, and pipe surface temperature is constant. The effect of nanoparticle and microfin tube on the heat transfer rate is investigated with the Richardson number which is between 0.1 and 0.7. The results show an increasing nanoparticle concentration between 0% and 1.5% leads to enhance the combined free and forced convection heat transfer rate. According to the results, five correlations are proposed to provide estimating the free and forced heat transfer rate as the increasing Richardson number from 0.1 to 0.7. The maximum deviation of both correlations is less than 16%. Moreover, four correlations are suggested to assess the Nusselt number based on the Rayleigh number in inclined tubes from 1800000 to 7000000. The maximum deviation of the correlation is almost 16%. The Darcy friction factor of the nanofluid flow has been investigated. Furthermore, CuO-HTO nanofluid flows in inclined microfin tubes.

Keywords: Nanofluid; heat transfer oil; mixed convection; inclined tube; laminar flow.

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Authors: Muhammad Ashraf Fauzi, Nurhayati Abdul Malek, Jamilah Othman

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The implementations of green roof have been widely used in the developed countries such as Germany, United Kingdom, United States and Canada. Green roof have many benefits such as aesthetic and economic value, ecological gain which are optimization of storm water management, urban heat island mitigation and energy conservation. In term of pollution, green roof can control the air and noise pollution in urban cities. The application of green roof in Malaysian building has been studied with the previous work of green roof either in Malaysia or other Asian region as like Indonesia, Singapore, Thailand, Taiwan and several other countries that have similar climate and environment as in Malaysia. These technologies of adapting green roof have been compared to the Green Building Index (GBI) of Malaysian buildings. The study has concentrated on the technical aspect of green roof system having focused on i) waste & recyclable materials ii) types of plants and method of planting and iii) green roof as tool to reduce storm water runoff. The finding of these areas will be compared to the suitability in achieving good practice of the GBI in Malaysia. Results show that most of the method are based on the countries own climate and environment. This suggests that the method of using green roof must adhere to the tropical climate of Malaysia. Suggestion of this research will be viewed in term of the sustainability of the green roof. Further research can be developed to implement the best method and application in Malaysian climate especially in urban cities and township.

Keywords: Green roofs, vegetation, plants, material, stormwater.

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Authors: Romain Bosquet, Pierre-Olivier Vandanjon, Alex Coiret, Tristan Lorino

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In the hardening energy context, the transport sector which constitutes a large worldwide energy demand has to be improving for decrease energy demand and global warming impacts. In a controversial situation where subsists an increasing demand for long-distance and high-speed travels, high-speed trains offer many advantages, as consuming significantly less energy than road or air transports. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

Keywords: High-speed train, energy, model, track profile, infrastructure

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: Distribution network, machine learning, network topology, phase identification, smart grid.

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Authors: Azian Hariri, M. Z. M Yusof, A. M. Leman

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Experimental study was conducted to assess personal welding fumes exposure toward welders during an aluminum metal inert gas (MIG) process. The welding process was carried out by a welding machine attached to a Computer Numerical Control (CNC) workbench. A dummy welder was used to replicate welder during welding works and was attached with sampling pumps and filter cassettes for welding fumes sampling. Direct reading instruments to measure air velocity, humidity, temperature and particulate matter with diameter size 10µm or less (PM₁₀) were located behind the dummy welder and parallel to the neck collar level to make sure the measured welding fumes exposure were not being influenced by other factors. Welding fumes exposure during standing and sitting position with and without the usage of local exhaust ventilation (LEV) was investigated. Welding fume samples were then digested and analyzed by using inductively coupled plasma mass spectroscopy (ICP-MS) according to ASTM D7439-08 method. The results of the study showed the welding fume exposure during sitting was lower compared to standing position. LEV helped reduce aluminum and lead exposure to acceptable levels during standing position. However during sitting position reduction of exposure was smaller. It can be concluded that welder position and the correct positioning of LEV should be implemented for effective exposure reduction. 

Keywords: ICP-MS, MIG process, personal sampling, welding fumes exposure.

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Authors: Lawrence I. Onyeji, Girish M. Kale, M. Bijan Kermani

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Corrosion problem which exists in every stage of oil and gas production has been a great challenge to the operators in the industry. The conventional carbon steel with all its inherent advantages has been adjudged susceptible to the aggressive corrosion environment of oilfield. This has aroused increased interest in the use of micro alloyed steels for oil and gas production and transportation. The corrosion behavior of three commercially supplied micro alloyed steels designated as A, B, and C have been investigated with API 5L X65 as reference samples. Electrochemical corrosion tests were conducted in an unbuffered 3.5 wt% NaCl solution saturated with CO₂ at 30 ⁰C for 24 hours. Pre-corrosion analyses revealed that samples A, B and X65 consist of ferrite-pearlite microstructures but with different grain sizes, shapes and distribution whereas sample C has bainitic microstructure with dispersed acicular ferrites. The results of the electrochemical corrosion tests showed that within the experimental conditions, the corrosion rate of the samples can be ranked as CR_(A)< CR_(X65)< CR_(B)< CR_(C). These results are attributed to difference in microstructures of the samples as depicted by ASTM grain size number in accordance with ASTM E112-12 Standard and ferrite-pearlite volume fractions determined by ImageJ Fiji grain size analysis software.

Keywords: Carbon dioxide corrosion, corrosion behavior, micro-alloyed steel, microstructures.

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Authors: Jia-Ming Kok, Javaan Chahl

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An optimisation method using both global and local optimisation is implemented to determine the flapping profile which will produce the most lift for an experimental wing-actuation system. The optimisation method is tested using a numerical quasi-steady analysis. Results of an optimised flapping profile show a 20% increase in lift generated as compared to flapping profiles obtained by high speed cinematography of a Sympetrum frequens dragonfly. Initial optimisation procedures showed 3166 objective function evaluations. The global optimisation parameters - initial sample size and stage one sample size, were altered to reduce the number of function evaluations. Altering the stage one sample size had no significant effect. It was found that reducing the initial sample size to 400 would allow a reduction in computational effort to approximately 1500 function evaluations without compromising the global solvers ability to locate potential minima. To further reduce the optimisation effort required, we increase the local solver’s convergence tolerance criterion. An increase in the tolerance from 0.02N to 0.05N decreased the number of function evaluations by another 20%. However, this potentially reduces the maximum obtainable lift by up to 0.025N.

Keywords: Flapping wing, Optimisation, Quasi-steady model.

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Authors: Ramaswamy Palaniappan, Nai-Jen Huan

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Classification of electroencephalogram (EEG) signals extracted during mental tasks is a technique that is actively pursued for Brain Computer Interfaces (BCI) designs. In this paper, we compared the classification performances of univariateautoregressive (AR) and multivariate autoregressive (MAR) models for representing EEG signals that were extracted during different mental tasks. Multilayer Perceptron (MLP) neural network (NN) trained by the backpropagation (BP) algorithm was used to classify these features into the different categories representing the mental tasks. Classification performances were also compared across different mental task combinations and 2 sets of hidden units (HU): 2 to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different mental tasks from 4 subjects were used in the experimental study and combinations of 2 different mental tasks were studied for each subject. Three different feature extraction methods with 6th order were used to extract features from these EEG signals: AR coefficients computed with Burg-s algorithm (ARBG), AR coefficients computed with stepwise least square algorithm (ARLS) and MAR coefficients computed with stepwise least square algorithm. The best results were obtained with 20 to 100 HU using ARBG. It is concluded that i) it is important to choose the suitable mental tasks for different individuals for a successful BCI design, ii) higher HU are more suitable and iii) ARBG is the most suitable feature extraction method.

Keywords: Autoregressive, Brain-Computer Interface, Electroencephalogram, Neural Network.

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Authors: Abbas Alli Taghipoor Bafghi, Hosein Bakhoda, Fateme Khodaei Chegeni

Abstract:

An experimental investigation is carried out to establish the performance characteristics of a compression ignition engine while using cerium oxide nanoparticles as additive in neat diesel and diesel-biodiesel blends. In the first phase of the experiments, stability of neat diesel and diesel-biodiesel fuel blends with the addition of cerium oxide nanoparticles is analyzed. After series of experiments, it is found that the blends subjected to high speed blending followed by ultrasonic bath stabilization improves the stability. In the second phase, performance characteristics are studied using the stable fuel blends in a single cylinder four stroke engine coupled with an electrical dynamometer and a data acquisition system. The cerium oxide acts as an oxygen donating catalyst and provides oxygen for combustion. The activation energy of cerium oxide acts to burn off carbon deposits within the engine cylinder at the wall temperature and prevents the deposition of non-polar compounds on the cylinder wall results reduction in HC emissions. The tests revealed that cerium oxide nanoparticles can be used as additive in diesel and diesel-biodiesel blends to improve complete combustion of the fuel significantly.

Keywords: Diesel engine, cerium oxide, diesel-biodiesel blends, nanoparticles.

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Authors: Andreas Theissler, Ian Dear

Abstract:

In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

Keywords: Anomaly detection, fault detection, test drive analysis, machine learning.

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Authors: H. López-Moreno, A. Rodríguez-Sánchez, C. Viñas-Arrebola, C. Porras-Amores

Abstract:

The ventilated façade has great advantages when compared to traditional façades as it reduces the air conditioning thermal loads due to the stack effect induced by solar radiation in the air chamber. Optimizing energy consumption by using a ventilated façade can be used not only in newly built buildings but also it can be implemented in existing buildings, opening the field of implementation to energy building retrofitting works. In this sense, the following three prototypes of façade where designed, built and further analyzed in this research: non-ventilated façade (NVF); slightly ventilated façade (SLVF) and strongly ventilated façade (STVF). The construction characteristics of the three facades are based on the Spanish regulation of building construction “Technical Building Code”. The façades have been monitored by type-k thermocouples in a representative day of the summer season in Madrid (Spain). Moreover, an analysis of variance (ANOVA) with repeated measures, studying the thermal lag in the ventilated and no-ventilated façades has been designed. Results show that STVF façade presents higher levels of thermal inertia as the thermal lag reduces up to 17% (daily mean) compared to the non-ventilated façade. In addition, the statistical analysis proves that an increase of the ventilation holes size in STVF façades can improve the thermal lag significantly (p >0.05) when compared to the SLVF façade.

Keywords: Energy efficiency, experimental study, statistical analysis, thermal behavior, ventilated façade.

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Authors: S.M. Gupta, V.K. Sehgal, S.K. Kaushik

Abstract:

This paper presents the results of an experimental investigation carried out to evaluate the shrinkage of High Strength Concrete. High Strength Concrete is made by partially replacement of cement by flyash and silica fume. The shrinkage of High Strength Concrete has been studied using the different types of coarse and fine aggregates i.e. Sandstone and Granite of 12.5 mm size and Yamuna and Badarpur Sand. The Mix proportion of concrete is 1:0.8:2.2 with water cement ratio as 0.30. Superplasticizer dose @ of 2% by weight of cement is added to achieve the required degree of workability in terms of compaction factor. From the test results of the above investigation it can be concluded that the shrinkage strain of High Strength Concrete increases with age. The shrinkage strain of concrete with replacement of cement by 10% of Flyash and Silica fume respectively at various ages are more (6 to 10%) than the shrinkage strain of concrete without Flyash and Silica fume. The shrinkage strain of concrete with Badarpur sand as Fine aggregate at 90 days is slightly less (10%) than that of concrete with Yamuna Sand. Further, the shrinkage strain of concrete with Granite as Coarse aggregate at 90 days is slightly less (6 to 7%) than that of concrete with Sand stone as aggregate of same size. The shrinkage strain of High Strength Concrete is also compared with that of normal strength concrete. Test results show that the shrinkage strain of high strength concrete is less than that of normal strength concrete.

Keywords: Shrinkage high strength concrete, fly ash, silica fume& superplastizers.

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Authors: Zhiwen Pan, Jesus Pacheco, Salim Hariri, Yiqiang Chen, Bozhi Liu

Abstract:

The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Keywords: Internet of Things, network security, context awareness, intrusion detection

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