Search results for: transient propagation

Authors: Kullanart Obsuwan, Chockpisit Thepsithar

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This study aimed to investigate effect of different organic supplements on growth of Vanda and Mokara seedlings. Vanda and Mokara seedlings approximately 0.2 and 0.3 cm. in height were sub-cultured onto VW supplemented with 150 ml/L coconut water, 100 g/L potato extract, 100 g/L ‘Gros Michel’ banana (AAA group) and 100 g/L ‘Namwa’ banana (ABB group). The explants were sub-cultured onto the same medium every month for 3 months. The best medium increased stem height to 0.52 and 0.44 Cm. in Vanda and Mokara respectively was supplemented with coconut water. The maximum fresh weight of Vanda (0.59 g) was found on medium supplemented with ‘Gros Michel’ banana while Mokara cultured on medium supplemented with Potato extract had the maximum fresh weight (0.27 g) and number of roots (5.20 roots/shoot) statistically different (p≤ 0.05) to other treatments. However, Vanda cultured on medium supplemented with ‘Namwa’ banana had the maximum number of roots (3.80 roots/shoot). Our results suggested that growth of different orchid genera was responded diversely to different organic supplements. 

 

Keywords: Fresh weight, in vitro propagation, orchid, plant height.

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Authors: Worachat Wannawong, Usa W. Humphries, Prungchan Wongwises, Suphat Vongvisessomjai

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The three steps of the standard one-way nested grid for a regional scale of the third generation WAve Model Cycle 4 (WAMC4) is scrutinized. The model application is enabled to solve the energy balance equation on a coarse resolution grid in order to produce boundary conditions for a smaller area by the nested grid technique. In the present study, the model takes a full advantage of the fine resolution of wind fields in space and time produced by the available U.S. Navy Global Atmospheric Prediction System (NOGAPS) model with 1 degree resolution. The nested grid application of the model is developed in order to gradually increase the resolution from the open ocean towards the South China Sea (SCS) and the Gulf of Thailand (GoT) respectively. The model results were compared with buoy observations at Ko Chang, Rayong and Huahin locations which were obtained from the Seawatch project. In addition, the results were also compared with Satun based weather station which was provided from Department of Meteorology, Thailand. The data collected from this station presented the significant wave height (Hs) reached 12.85 m. The results indicated that the tendency of the Hs from the model in the spherical coordinate propagation with deep water condition in the fine grid domain agreed well with the Hs from the observations.

Keywords: energy balance equation, Gulf of Thailand, nested gridapplication, South China Sea, wave model.

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: Lateral bearing capacity, short pile, clayey soil, artificial neural network, Imperialist competition algorithm.

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Authors: Tai Yuan Yu, Pei-Jen Wang

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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings (GFBs) are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional (3D) fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: Fluid structure interaction multi-physics simulations, gas foil bearing, oil-free, transient thermohydrodynamic.

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Authors: Mohammad Reza Zamani Kouhpanji

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Characterizing the fatigue and fracture properties of nanostructures is one of the most challenging tasks in nanoscience and nanotechnology due to lack of a MEMS/NEMS device for generating uniform cyclic loadings at high frequencies. Here, the dynamic response of a recently proposed MEMS/NEMS device under different inputs signals is completely investigated. This MEMS/NEMS device is designed and modeled based on the electromagnetic force induced between paired parallel wires carrying electrical currents, known as Ampere’s Force Law (AFL). Since this MEMS/NEMS device only uses two paired wires for actuation part and sensing part, it represents highly sensitive and linear response for nanostructures with any stiffness and shapes (single or arrays of nanowires, nanotubes, nanosheets or nanowalls). In addition to studying the maximum gains at different resonance frequencies of the MEMS/NEMS device, its dynamical responses are investigated for different inputs and nanostructure properties to demonstrate the capability, usability, and reliability of the device for wide range of nanostructures. This MEMS/NEMS device can be readily integrated into SEM/TEM instruments to provide real time study of the fatigue and fracture properties of nanostructures as well as their softening or hardening behaviors, and initiation and/or propagation of nanocracks in them.

Keywords: Ampere’s force law, dynamical response, fatigue and fracture characterization, paired wire actuators and sensors, MEMS/NEMS devices.

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Authors: Sotirios Raptis

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Linking social needs to social classes using different criteria may lead to social services misuse. The paper discusses using ML and Neural Networks (NNs) in linking public services in Scotland in the long term and advocates, this can result in a reduction of the services cost connecting resources needed in groups for similar services. The paper combines typical regression models with clustering and cross-correlation as complementary constituents to predict the demand. Insurance companies and public policymakers can pack linked services such as those offered to the elderly or to low-income people in the longer term. The work is based on public data from 22 services offered by Public Health Services (PHS) Scotland and from the Scottish Government (SG) from 1981 to 2019 that are broken into 110 years series called factors and uses Linear Regression (LR), Autoregression (ARMA) and 3 types of back-propagation (BP) Neural Networks (BPNN) to link them under specific conditions. Relationships found were between smoking related healthcare provision, mental health-related health services, and epidemiological weight in Primary 1(Education) Body Mass Index (BMI) in children. Primary component analysis (PCA) found 11 significant factors while C-Means (CM) clustering gave 5 major factors clusters.

Keywords: Probability, cohorts, data frames, services, prediction.

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Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: Neural network, gravitational resistance, pattern recognition, non-linear.

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Authors: Rihab Hamdi, Amel Hadri Hamida, Fatiha Khelili, Sakina Zerouali, Ouafae Bennis

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This paper features a comparative study performance of sliding mode controller (SMC) for closed-loop voltage control of direct current to direct current (DC-DC) three-cells buck converter connected in parallel, operating in continuous conduction mode (CCM), based on pulse-width modulation (PWM) with SMC based on hysteresis modulation (HM) where an adaptive feedforward technique is adopted. On one hand, for the PWM-based SM, the approach is to incorporate a fixed-frequency PWM scheme which is effectively a variant of SM control. On the other hand, for the HM-based SM, oncoming an adaptive feedforward control that makes the hysteresis band variable in the hysteresis modulator of the SM controller in the aim to restrict the switching frequency variation in the case of any change of the line input voltage or output load variation are introduced. The results obtained under load change, input change and reference change clearly demonstrates a similar dynamic response of both proposed techniques, their effectiveness is fast and smooth tracking of the desired output voltage. The PWM-based SM technique has greatly improved the dynamic behavior with a bit advantageous compared to the HM-based SM technique, as well as provide stability in any operating conditions. Simulation studies in MATLAB/Simulink environment have been performed to verify the concept.

Keywords: Sliding mode control, pulse-width modulation, hysteresis modulation, DC-DC converter, parallel multi-cells converter, robustness.

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD, as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches, such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: Autism spectrum disorder, clustering, optimization, unsupervised machine learning.

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Authors: R. A. Shahmiri, O. C. Standard, J. N. Hart, C. C. Sorrell

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The ceramic yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) has been used as a dental biomaterial for several decades. The strength and toughness of this material can be accounted for by its toughening mechanisms, which include transformation toughening, crack deflection, zone shielding, contact shielding, and crack bridging. Prevention of crack propagation is of critical importance in high-fatigue situations, such as those encountered in mastication and para-function. However, the poor translucence of Y-TZP in polycrystalline form is such that it may not meet the aesthetic requirements due to its white/grey appearance. To improve the optical properties of Y-TZP, more detailed study of the optical properties is required; in particular, precise evaluation of the refractive index, absorption coefficient, and scattering coefficient are necessary. The measurement of the optical parameters has been based on the assumption that light scattered from biological media is isotropically distributed over all angles. In fact, the optical behavior of real biological materials depends on the angular scattering of light due to the anisotropic nature of the materials. The purpose of the present work is to evaluate the optical properties (including color, opacity/translucence, scattering, and fluorescence) of zirconia dental ceramics and their control through modification of the chemical composition, phase composition, and surface microstructure.

Keywords: Optical properties, opacity/translucence, scattering, fluorescence, chemical composition, phase composition, surface microstructure.

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Authors: Mohammad Heidari

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Horizontal wells are proven to be better producers because they can be extended for a long distance in the pay zone. Engineers have the technical means to forecast the well productivity for a given horizontal length. However, experiences have shown that the actual production rate is often significantly less than that of forecasted. It is a difficult task, if not impossible to identify the real reason why a horizontal well is not producing what was forecasted. Often the source of problem lies in the drilling of horizontal section such as permeability reduction in the pay zone due to mud invasion or snaky well patterns created during drilling. Although drillers aim to drill a constant inclination hole in the pay zone, the more frequent outcome is a sinusoidal wellbore trajectory. The two factors, which play an important role in wellbore tortuosity, are the inclination and side force at bit. A constant inclination horizontal well can only be drilled if the bit face is maintained perpendicular to longitudinal axis of bottom hole assembly (BHA) while keeping the side force nil at the bit. This approach assumes that there exists no formation force at bit. Hence, an appropriate BHA can be designed if bit side force and bit tilt are determined accurately. The Artificial Neural Network (ANN) is superior to existing analytical techniques. In this study, the neural networks have been employed as a general approximation tool for estimation of the bit side forces. A number of samples are analyzed with ANN for parameters of bit side force and the results are compared with exact analysis. Back Propagation Neural network (BPN) is used to approximation of bit side forces. Resultant low relative error value of the test indicates the usability of the BPN in this area.

Keywords: Artificial Neural Network, BHA, Horizontal Well, Stabilizer.

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Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

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Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.

Keywords: Satellite, neural network, MATLAB, power system.

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Authors: Leila Rashidian, Abbas Ebrahimi

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The development of industrial activities, increase in fossil fuel consumption, vehicles, destruction of forests and grasslands, changes in land use, and population growth have caused to increase the amount of greenhouse gases especially CO₂ in the atmosphere in recent decades. This has led to global warming and climate change. In the present paper, we have investigated the trend of climate change according to the data simulation during the time interval of 2010-2030 in the Fars province. In this research, the daily climatic parameters such as maximum and minimum temperature, precipitation and number of sunny hours during the 1977-2008 time interval for synoptic stations of Shiraz and Abadeh and during 1995-2008 for Lar stations and also the output of HADCM₃ model in 2010-2030 time interval have been used based on the A₂ propagation scenario. The results of the model show that the average temperature will increase by about 1 degree centigrade and the amount of precipitation will increase by 23.9% compared to the observational data. In conclusion, according to the temperature increase in this province, the amount of precipitation in the form of snow will be reduced and precipitations often will occur in the form of rain. This 1-degree centigrade increase during the season will reduce production by 6 to 10% because of shortening the growing period of wheat.

Keywords: Climate change, Lars.WG, HADCM3 model, Fars province, climatic parameters, A2 scenario.

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Authors: S. I. V. Sousa, F.G. Martins, M. C. Pereira, M. C. M. Alvim-Ferraz, H. Ribeiro, M. Oliveira, I. Abreu

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Exposure to ambient air pollution has been linked to a number of health outcomes, starting from modest transient changes in the respiratory tract and impaired pulmonary function, continuing to restrict activity/reduce performance and to the increase emergency rooms visits, hospital admissions or mortality. The increase of allergenic symptoms has been associated with air contaminants such as ozone, particulate matter, fungal spores and pollen. Considering the potential relevance of crossed effects of nonbiological pollutants and airborne pollens and fungal spores on allergy worsening, the aim of this work was to evaluate the influence of non-biological pollutants (O3 and PM10) and meteorological parameters on the concentrations of pollen and fungal spores using multiple linear regressions. The data considered in this study were collected in Oporto which is the second largest Portuguese city, located in the North. Daily mean of O3, PM10, pollen and fungal spore concentrations, temperature, relative humidity, precipitation, wind velocity, pollen and fungal spore concentrations, for 2003, 2004 and 2005 were considered. Results showed that the 90th percentile of the adjusted coefficient of determination, P90 (R2aj), of the multiple regressions varied from 0.613 to 0.916 for pollen and from 0.275 to 0.512 for fungal spores. O3 and PM10 showed to have some influence on the biological pollutants. Among the meteorological parameters analysed, temperature was the one that most influenced the pollen and fungal spores airborne concentrations. Relative humidity also showed to have some influence on the fungal spore dispersion. Nevertheless, the models for each pollen and fungal spore were different depending on the analysed period, which means that the correlations identified as statistically significant can not be, even so, consistent enough.

Keywords: Air pollutants, meteorological parameters, biologicalpollutants, multiple linear correlations.

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Authors: Jehnming Lin

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The effects of the contact ball-lens on the soda lime glass in laser thermal cleavage with a cw Nd-YAG laser were investigated in this study. A contact ball-lens was adopted to generate a bending force on the crack formation of the soda-lime glass in the laser cutting process. The Nd-YAG laser beam (wavelength of 1064 nm) was focused through the ball-lens and transmitted to the soda-lime glass, which was coated with a carbon film on the surface with a bending force from a ball-lens to generate a tensile stress state on the surface cracking. The fracture was controlled by the contact ball-lens and a straight cutting was tested to demonstrate the feasibility. Experimental observations on the crack propagation from the leading edge, main section and trailing edge of the glass sheet were compared with various mechanical and thermal loadings. Further analyses on the stress under various laser powers and contact ball loadings were made to characterize the innovative technology. The results show that the distributions of the side crack at the leading and trailing edges are mainly dependent on the boundary condition, contact force, cutting speed and laser power. With the increase of the mechanical and thermal loadings, the region of the side cracks might be dramatically reduced with proper selection of the geometrical constrains. Therefore the application of the contact ball-lens is a possible way to control the fracture in laser cleavage with improved cutting qualities.

Keywords: Laser cleavage, controlled fracture, contact ball lens.

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Authors: Shih-Bin Wang, Ping Yuan, Syu-Fang Liu, Ming-Jun Kuo

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By the application of an improved back-propagation neural network (BPNN), a model of current densities for a solid oxide fuel cell (SOFC) with 10 layers is established in this study. To build the learning data of BPNN, Taguchi orthogonal array is applied to arrange the conditions of operating parameters, which totally 7 factors act as the inputs of BPNN. Also, the average current densities achieved by numerical method acts as the outputs of BPNN. Comparing with the direct solution, the learning errors for all learning data are smaller than 0.117%, and the predicting errors for 27 forecasting cases are less than 0.231%. The results show that the presented model effectively builds a mathematical algorithm to predict performance of a SOFC stack immediately in real time. Also, the calculating algorithms are applied to proceed with the optimization of the average current density for a SOFC stack. The operating performance window of a SOFC stack is found to be between 41137.11 and 53907.89. Furthermore, an inverse predicting model of operating parameters of a SOFC stack is developed here by the calculating algorithms of the improved BPNN, which is proved to effectively predict operating parameters to achieve a desired performance output of a SOFC stack.

Keywords: a SOFC stack, BPNN, inverse predicting model of operating parameters, optimization of the average current density

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Authors: Nuri Yucel, Muhammed Ilter Berberoglu, Salih Karaaslan, Nureddin Dinler

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The objective of this study is to investigate fire behaviors, experimentally and numerically, in a scaled version of an underground station. The effect of ventilation velocity on the fire is examined. Fire experiments are simulated by burning 10 ml isopropyl alcohol fuel in a fire pool with dimensions 5cm x 10cm x 4 mm at the center of 1/100 scaled underground station model. A commercial CFD program FLUENT was used in numerical simulations. For air flow simulations, k-ω SST turbulence model and for combustion simulation, non-premixed combustion model are used. This study showed that, the ventilation velocity is increased from 1 m/s to 3 m/s the maximum temperature in the station is found to be less for ventilation velocity of 1 m/s. The reason for these experimental result lies on the relative dominance of oxygen supply effect on cooling effect. Without piston effect, maximum temperature occurs above the fuel pool. However, when the ventilation velocity increased the flame was tilted in the direction of ventilation and the location of maximum temperature moves along the flow direction. The velocities measured experimentally in the station at different locations are well matched by the CFD simulation results. The prediction of general flow pattern is satisfactory with the smoke visualization tests. The backlayering in velocity is well predicted by CFD simulation. However, all over the station, the CFD simulations predicted higher temperatures compared to experimental measurements.

Keywords: Fire, underground station, flame propagation, CFDsimulation, k-ω SST turbulence model, non-premixed combustionmodel.

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Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: Structural health monitoring, bridge health monitoring, sensor-based methods, machine-learning algorithms, model-based techniques, sensor placement, data acquisition, data analysis.

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Authors: M. Ferguson, T. Konkova, I. Violatos

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Microstructure analysis of additively manufactured (AM) materials is an important step in understanding the interrelationship between mechanical properties and materials performance. Literature on the effect of a laser-based AM process parameters on the microstructure in the substrate-deposit interface is limited. The interface region, the adjoining area of substrate and deposit, is characterized by the presence of the fusion zone (FZ) and heat affected zone (HAZ) experiencing rapid thermal gyrations resulting in thermal induced transformations. Inconel 718 was utilized as a work material for both the substrate and deposit. Three blocks of Inconel 718 material were deposited by Direct Energy Deposition (DED) using three different laser powers, 550W, 750W and 950W, respectively. A coupled thermo-mechanical transient approach was utilized to correlate temperature history to the evolution of microstructure. Thermal history of the deposition process was monitored with the thermocouples installed inside the substrate material. Interface region of the blocks were analysed with Optical Microscopy (OM) and Scanning Electron Microscopy (SEM) including electron back-scattered diffraction (EBSD) technique. Laser power was found to influence the dissolution of intermetallic precipitated phases in the substrate and grain growth in the interface region. Microstructure and thermal history data were utilized to draw conclusive comparisons between the investigated process parameters.

Keywords: Additive manufacturing, direct energy deposition, electron back-scatter diffraction, finite element analysis, Inconel 718, microstructure, optical microscopy, scanning electron microscopy, substrate-deposit interface region.

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Authors: Z. Gholamzadeh, A. Zali, S. A. H. Feghhi, C. Tenreiro, Y. Kadi, M. Rezazadeh, M. Aref

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Most HWRs currently use natural uranium fuel. Using enriched uranium fuel results in a significant improvement in fuel cycle costs and uranium utilization. On the other hand, reactivity changes of HWRs over the full range of operating conditions from cold shutdown to full power are small. This reduces the required reactivity worth of control devices and minimizes local flux distribution perturbations, minimizing potential problems due to transient local overheating of fuel. Analyzing heavy water effectiveness on neutronic parameters such as enrichment requirements, peaking factor and reactivity is important and should pay attention as primary concepts of a HWR core designing. Two nuclear nuclear reactors of CANDU-type and hexagonal-type reactor cores of 33 fuel assemblies and 19 assemblies in 1.04 P/D have been respectively simulated using MCNP-4C code. Using heavy water and light water as moderator have been compared for achieving less reactivity insertion and enrichment requirements. Two fuel matrixes of (232Th/235U)O2 and (238/235U)O2 have been compared to achieve more economical and safe design. Heavy water not only decreased enrichment needs, but it concluded in negative reactivity insertions during moderator density variations. Thorium oxide fuel assemblies of 2.3% enrichment loaded into the core of heavy water moderator resulted in 0.751 fission to absorption ratio and peaking factor of 1.7 using. Heavy water not only provides negative reactivity insertion during temperature raises which changes moderator density but concluded in 2 to 10 kg reduction of enrichment requirements, depend on geometry type.

Keywords: MCNP-4C, Reactor core, Multiplication factor, Reactivity, Peaking factor.

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Authors: Bijit Kalita, K. V. N. Surendra

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Rotating disk is one of the most indispensable parts of a rotating machine. Rotating disk has found many applications in the diverging field of science and technology. In this paper, we have taken into consideration the problem of a heavy spinning disk mounted on a rotor system acted upon by boundary traction. Finite element modelling is used at various loading condition to determine the mixed mode stress intensity factors. The effect of combined shear and normal traction on the boundary is incorporated in the analysis under the action of gravity. The variation near the crack tip is characterized in terms of the stress intensity factor (SIF) with an aim to find the SIF for a wide range of parameters. The results of the finite element analyses carried out on the compressed disk of a belt pulley arrangement using fracture mechanics concepts are shown. A total of hundred cases of the problem are solved for each of the variations in loading arc parameter and crack orientation using finite element models of the disc under compression. All models were prepared and analyzed for the uncracked disk, disk with a single crack at different orientation emanating from shaft hole as well as for a disc with pair of cracks emerging from the same center hole. Curves are plotted for various loading conditions. Finally, crack propagation paths are determined using kink angle concepts.

Keywords: Crack-tip deformations, static loading, stress concentration, stress intensity factor.

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Authors: S. Sundaravalli, M. C. Majumder, G. K. Vijayaraghavan

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The study focuses to investigate the thermal response of delaminations and develop mathematical models using numerical results to obtain the optimum heat requirement and time to identify delaminations in GLARE type of Fibre Metal Laminates (FML) in both reflection mode and through-transmission (TT) mode of step pulsed active thermography (SPAT) method in the type of nondestructive testing and evaluation (NDTE) technique. The influence of applied heat flux and time on various sizes and depth of delaminations in FML is analyzed to investigate the thermal response through numerical simulations. A finite element method (FEM) is applied to simulate SPAT through ANSYS software based on 3D transient heat transfer principle with the assumption of reflection mode and TT mode of observation individually.

The results conclude that the numerical approach based on SPAT in reflection mode is more suitable for analysing smaller size of near-surface delaminations located at the thermal stimulator side and TT mode is more suitable for analysing smaller size of deeper delaminations located far from thermal stimulator side or near thermal detector/Infrared camera side. The mathematical models provide the optimum q and T at the required MRTD to identify unidentified delamination 7 with 25015.0022W/m2 at 2.531sec and delamination 8 with 16663.3356 W/m2 at 1.37857sec in reflection mode. In TT mode, the delamination 1 with 34954W/m2 at 13.0399sec, delamination 2 with 20002.67W/m2 at 1.998sec and delamination 7 with 20010.87 W/m2 at 0.6171sec could be identified.

Keywords: Step pulsed active thermography (SPAT), NDTE, FML, Delaminations, Finite element method.

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Authors: Hsien-Chou Liao, Yu-Shiang Wang

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Surveillance system is widely used in the traffic monitoring. The deployment of cameras is moving toward a ubiquitous camera (UbiCam) environment. In our previous study, a novel service, called GPS-VT, was firstly proposed by incorporating global positioning system (GPS) and visual tracking techniques for the UbiCam environment. The first prototype is called GODTA (GPS-based Moving Object Detection and Tracking Approach). For a moving person carried GPS-enabled mobile device, he can be tracking when he enters the field-of-view (FOV) of a camera according to his real-time GPS coordinate. In this paper, GPS-VT service is applied to the tracking of vehicles. The moving speed of a vehicle is much faster than a person. It means that the time passing through the FOV is much shorter than that of a person. Besides, the update interval of GPS coordinate is once per second, it is asynchronous with the frame rate of the real-time image. The above asynchronous is worsen by the network transmission delay. These factors are the main challenging to fulfill GPS-VT service on a vehicle.In order to overcome the influence of the above factors, a back-propagation neural network (BPNN) is used to predict the possible lane before the vehicle enters the FOV of a camera. Then, a template matching technique is used for the visual tracking of a target vehicle. The experimental result shows that the target vehicle can be located and tracking successfully. The success location rate of the implemented prototype is higher than that of the previous GODTA.

Keywords: visual surveillance, visual tracking, globalpositioning system, intelligent transportation system

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Authors: Farah Haroon, Haroon Rasheed, Kazi M Ahmed

Abstract:

IEEE 802.15.4a impulse radio-time hopping ultra wide band (IR-TH UWB) physical layer, due to small duty cycle and very short pulse widths is robust against multipath propagation. However, scattering and reflections with the large number of obstacles in indoor channel environments, give rise to dense multipath fading. It imposes serious problem to optimum Rake receiver architectures, for which very large number of fingers are needed. Presence of strong noise also affects the reception of fine pulses having extremely low power spectral density. A robust SRake receiver for IEEE 802.15.4a IRTH UWB in dense multipath and additive white Gaussian noise (AWGN) is proposed to efficiently recover the weak signals with much reduced complexity. It adaptively increases the signal to noise (SNR) by decreasing noise through a recursive least square (RLS) algorithm. For simulation, dense multipath environment of IEEE 802.15.4a industrial non line of sight (NLOS) is employed. The power delay profile (PDF) and the cumulative distribution function (CDF) for the respective channel environment are found. Moreover, the error performance of the proposed architecture is evaluated in comparison with conventional SRake and AWGN correlation receivers. The simulation results indicate a substantial performance improvement with very less number of Rake fingers.

Keywords: Adaptive noise cancellation, dense multipath propoagation, IEEE 802.15.4a, IR-TH UWB, industrial NLOS environment, SRake receiver

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Authors: Sunthari Tharapan, Chockpisit Thepsithar, Kullanart Obsuwan

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This study was aimed to investigate the effect of various organic supplements on growth and development of Dendrobium discolor’s protocorms and seedlings growth of Dendrobium Judy Rutz. Protocorms of Dendrobium discolor with 2.0 cm. in diameter and seedlings of Dendrobium Judy Rutz at the same size (0.5 cm. height) were sub-cultured on Hyponex medium supplemented with cow milk (CM), soy milk (SM), potato extract (PE) and peptone (P) for 2 months. The protocorms were developed to seedlings in all treatments after cultured for 2 months. However, the best results were found on Hyponex medium supplemented with P was the best in which the maximum fresh and dry weight and maximum shoot height were obtained in this treatment statistically different (p ≤ 0.05) to other treatments. Moreover, Hyponex medium supplemented with P also stimulated the maximum mean number of 5.7 shoots per explant which also showed statistically different (p ≤ 0.05) when compared to other treatments. The results of growth of Dendrobium Judy Rutz seedlings indicated the medium supplemented with 100 mL/L PE enhanced the maximum fresh and dry weigh per explants with significantly different (p ≤ 0.05) in fresh weight from other treatments including the control medium without any organic supplementation. However, the dry weight was not significantly different (p ≤ 0.05) from medium supplemented with SM and P. There was multiple shoots induction in all media with or without organic supplementation ranging from 2.6 to 3 shoots per explants. The maximum shoot height was also obtained in the seedlings cultured on medium supplemented with PE while the longest root length was found in medium supplemented with SM.

Keywords: Fresh weight, in vitro propagation, orchid, plant height.

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Authors: S. M. Abdul Khader, Anurag Ayachit, Raghuvir Pai, K. A. Ahmed, V. R. K. Rao, S. Ganesh Kamath

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The numerical simulation has made tremendous advances in investigating the blood flow phenomenon through elastic arteries. Such study can be useful in demonstrating the disease progression and hemodynamics of cardiovascular diseases such as atherosclerosis. In the present study, patient specific case diagnosed with partially stenosed complete right ICA and normal left carotid bifurcation without any atherosclerotic plaque formation is considered. 3D patient specific carotid bifurcation model is generated based on CT scan data using MIMICS-4.0 and numerical analysis is performed using FSI solver in ANSYS-14.5. The blood flow is assumed to be incompressible, homogenous and Newtonian, while the artery wall is assumed to be linearly elastic. The two-way sequentially coupled transient FSI analysis is performed using FSI solver for three pulse cycles. The hemodynamic parameters such as flow pattern, Wall Shear Stress, pressure contours and arterial wall deformation are studied at the bifurcation and critical zones such as stenosis. The variation in flow behavior is studied throughout the pulse cycle. Also, the simulation results reveal that there is a considerable increase in the flow behavior in stenosed carotid in contrast to the normal carotid bifurcation system. The investigation also demonstrates the disturbed flow pattern especially at the bifurcation and stenosed zone elevating the hemodynamics, particularly during peak systole and later part of the pulse cycle. The results obtained agree well with the clinical observation and demonstrates the potential of patient specific numerical studies in prognosis of disease progression and plaque rupture.

Keywords: Fluid-Structure Interaction, arterial stenosis, Wall Shear Stress, Carotid Artery Bifurcation.

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Authors: K. Uma Maheswari, S. Sathiyamoorthy, G. Lakshmi

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Diffuse Optical Tomography (DOT) is a non-invasive imaging modality used in clinical diagnosis for earlier detection of carcinoma cells in brain tissue. It is a form of optical tomography which produces gives the reconstructed image of a human soft tissue with by using near-infra-red light. It comprises of two steps called forward model and inverse model. The forward model provides the light propagation in a biological medium. The inverse model uses the scattered light to collect the optical parameters of human tissue. DOT suffers from severe ill-posedness due to its incomplete measurement data. So the accurate analysis of this modality is very complicated. To overcome this problem, optical properties of the soft tissue such as absorption coefficient, scattering coefficient, optical flux are processed by the standard regularization technique called Levenberg - Marquardt regularization. The reconstruction algorithms such as Split Bregman and Gradient projection for sparse reconstruction (GPSR) methods are used to reconstruct the image of a human soft tissue for tumour detection. Among these algorithms, Split Bregman method provides better performance than GPSR algorithm. The parameters such as signal to noise ratio (SNR), contrast to noise ratio (CNR), relative error (RE) and CPU time for reconstructing images are analyzed to get a better performance.

Keywords: Diffuse optical tomography, ill-posedness, Levenberg Marquardt method, Split Bregman, the Gradient projection for sparse reconstruction.

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Authors: Ahmed. S. Alasmari, M. S. Soliman, Magdy M. El-Rayes

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This study focuses on the effect of the addition of magnesium (Mg) and silver (Ag) on the mechanical properties of aluminum based alloys. The alloying elements will be added at different levels using the factorial design of experiments of 2²; the two factors are Mg and Ag at two levels of concentration. The superior mechanical properties of the produced Al-Cu-Mg-Ag alloys after aging will be resulted from a unique type of precipitation named as Ω-phase. The formed precipitate enhanced the tensile strength and thermal stability. This paper further investigated the microstructure and mechanical properties of as cast Al–Cu–Mg–Ag alloys after being complete homogenized treatment at 520 °C for 8 hours followed by isothermally age hardening process at 190 °C for different periods of time. The homogenization at 520 °C for 8 hours was selected based on homogenization study at various temperatures and times. The alloys’ microstructures were studied by using optical microscopy (OM). In addition to that, the fracture surface investigation was performed using a scanning electronic microscope (SEM). Studying the microstructure of aged Al-Cu-Mg-Ag alloys reveal that the grains are equiaxed with an average grain size of about 50 µm. A detailed fractography study for fractured surface of the aged alloys exhibited a mixed fracture whereby the random fracture suggested crack propagation along the grain boundaries while the dimples indicated that the fracture was ductile. The present result has shown that alloy 5 has the highest hardness values and the best mechanical behaviors.

Keywords: Precipitation hardening, aluminum alloys, aging, design of experiments, analysis of variance, heat treatments.

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Authors: Zahra Ghadampour, Gholamreza Rakhshandehroo

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A concern that researchers usually face in different applications of Artificial Neural Network (ANN) is determination of the size of effective domain in time series. In this paper, trial and error method was used on groundwater depth time series to determine the size of effective domain in the series in an observation well in Union County, New Jersey, U.S. different domains of 20, 40, 60, 80, 100, and 120 preceding day were examined and the 80 days was considered as effective length of the domain. Data sets in different domains were fed to a Feed Forward Back Propagation ANN with one hidden layer and the groundwater depths were forecasted. Root Mean Square Error (RMSE) and the correlation factor (R2) of estimated and observed groundwater depths for all domains were determined. In general, groundwater depth forecast improved, as evidenced by lower RMSEs and higher R2s, when the domain length increased from 20 to 120. However, 80 days was selected as the effective domain because the improvement was less than 1% beyond that. Forecasted ground water depths utilizing measured daily data (set #1) and data averaged over the effective domain (set #2) were compared. It was postulated that more accurate nature of measured daily data was the reason for a better forecast with lower RMSE (0.1027 m compared to 0.255 m) in set #1. However, the size of input data in this set was 80 times the size of input data in set #2; a factor that may increase the computational effort unpredictably. It was concluded that 80 daily data may be successfully utilized to lower the size of input data sets considerably, while maintaining the effective information in the data set.

Keywords: Neural networks, groundwater depth, forecast.

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Authors: Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin

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Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Keywords: Computer vision, image acquisition device, machine vision, multi-layer neural networks.

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