Search results for: particle swarm optimization

Authors: A. Aravind, M. Vetrivel, P. Abhimanyu, C. A. Akaash Emmanuel Raj, K. Sundararaj, V. R. S. Kumar

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The choice of high-speed, low budget hatchback car with diversified options is increasing for meeting the new generation buyers trend. This paper is aimed to augment the current speed of the hatchback cars through the aerodynamic drag reduction technique. The inverted airfoils are facilitated at the bottom of the car for generating the downward force for negating the lift while increasing the current speed range for achieving a better road performance. The numerical simulations have been carried out using a 2D steady pressure-based    k-ɛ realizable model with enhanced wall treatment. In our numerical studies, Reynolds-averaged Navier-Stokes model and its code of solution are used. The code is calibrated and validated using the exact solution of the 2D boundary layer displacement thickness at the Sanal flow choking condition for adiabatic flows. We observed through the parametric analytical studies that the inverted airfoil integrated with the bottom surface at various predesigned locations of Hatchback cars can improve its overall aerodynamic efficiency through drag reduction, which obviously decreases the fuel consumption significantly and ensure an optimum road performance lucratively with maximum permissible speed within the framework of the manufactures constraints.

Keywords: aerodynamics of commercial cars, downward force, hatchback car, inverted airfoil

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Authors: Ghada Badr, Manar Hosny, Nuha Bintayyash, Eman Albilali, Souad Larabi Marie-Sainte

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The median problem is significantly applied to derive the most reasonable rearrangement phylogenetic tree for many species. More specifically, the problem is concerned with finding a permutation that minimizes the sum of distances between itself and a set of three signed permutations. Genomes with equal number of genes but different order can be represented as permutations. In this paper, an algorithm, namely BeamGA median, is proposed that combines a heuristic search approach (local beam) as an initialization step to generate a number of solutions, and then a Genetic Algorithm (GA) is applied in order to refine the solutions, aiming to achieve a better median with the smallest possible reversal distance from the three original permutations. In this approach, any genome rearrangement distance can be applied. In this paper, we use the reversal distance. To the best of our knowledge, the proposed approach was not applied before for solving the median problem. Our approach considers true biological evolution scenario by applying the concept of common intervals during the GA optimization process. This allows us to imitate a true biological behavior and enhance genetic approach time convergence. We were able to handle permutations with a large number of genes, within an acceptable time performance and with same or better accuracy as compared to existing algorithms.

Keywords: median problem, phylogenetic tree, permutation, genetic algorithm, beam search, genome rearrangement distance

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Authors: Nabil Mezhoud

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The economic operation of electric energy generating systems is one of the predominant problems in energy systems. Due to the need for better reliability, high energy quality, lower losses, lower cost and a clean environment, the application of renewable and sustainable energy sources, such as wind energy, solar energy, etc., in recent years has become more widespread. In this work, one of a bio-inspired meta-heuristic algorithm inspired by the flashing behavior of fireflies at night called the Firefly Algorithm (FFA) is applied to solve the Optimal Energy Management (OEM) and the environmental index (EI) problems of a micro-grid (MG) operating by Renewable and Sustainable Generation Systems (RSGS). Our main goal is to minimize the nonlinear objective function of an electrical microgrid, taking into account equality and inequality constraints. The FFA approach was examined and tested on a standard MG system composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), and non-renewable energy, such as fuel cells (FC), micro turbine (MT), diesel generator (DEG) and loads with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of the proposed approach to solve the OEM and the EI problems. The results of the proposed method have been compared and validated with those known references published recently.

Keywords: renewable energy sources, energy management, distributed generator, micro-grids, firefly algorithm

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Authors: Vladyslav Povoroznyuk, Oksana Ivanyk, Nataliia Dzerovych

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In the diagnostics of osteoporosis, the gold standard is considered to be bone mineral density; however, X-ray densitometry is not an accurate indicator of osteoporotic fracture risk under all circumstances. In this regard, the search for new methods that could determine the indicators not only of the mineral density, but of the bone tissue quality, is a logical step for diagnostic optimization. One of these methods is the evaluation of trabecular bone quality. The aim of this study was to examine the quality and mineral density of spine bone tissue, femoral neck, and body composition of women depending on the duration of the postmenopausal period, to determine the correlation of body fat with indicators of bone mineral density and quality. The study examined 179 women in premenopausal and postmenopausal periods. The patients were divided into the following groups: Women in the premenopausal period and women in the postmenopausal period at various stages (early, middle, late postmenopause). A general examination and study of the above parameters were conducted with General Electric X-ray densitometer. The results show that bone quality and mineral density probably deteriorate with advancing of postmenopausal period. Total fat and lean mass ratio is not likely to change with age. In the middle and late postmenopausal periods, the bone tissue mineral density of the spine and femoral neck increases along with total fat mass.

Keywords: osteoporosis, bone tissue mineral density, bone quality, fat mass, lean mass, postmenopausal osteoporosis

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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Authors: Mohd. Khaidir Abu Talib, Noriyuki Yasufuku, Ryohei Ishikura

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It is well recognized that peat can impede the proper hydration of cement because of high organic content, presence of humic acid and less solid particles. That means the large amount of cement is required in order to neutralize the acids or otherwise the process of the peat stabilization remains retarded. Nevertheless, adding a great quantity of cement into the peat is absolutely an unfriendly and uneconomical solution. Sugarcane production is world number one commodities and produced a lot of bagasse. Bagasse is burnt to generate power required for diverse activities in the factory and leave bagasse ash as a waste. Increasing concern of disposal of bagasse residual creates interest to explore the potential application of this material. The objective of this study is to develop alternative binders that are environment friendly and contribute towards sustainable management by utilizing sugarcane bagasse ash (SCBA) in the stabilization of peat soil. Alongside SCBA, Ordinary Portland Cement (OPC), calcium chloride (CaCl2) and silica sand (K7) were used as additives to stabilize the peat that sampled from Hokkaido, Japan. In obtaining the optimal mix design, specimens of stabilized peat were tested in unconfined compression. It was found that stabilized peat comprising 20% and 5% (PCB1-20 and PCB2-5) partial replacement of OPC with SCBA 1 and SCBA 2 attain the maximum unconfined compressive strength (UCS) and discovered greater than untreated soil (P) and UCS of peat-cement (PC) specimen. At the optimal mix design, the UCS of the stabilized peat specimens increased with increasing of curing time, preloading during curing, OPC dosage and K7 dosage. For PCB1-20 mixture, inclusion of a minimum OPC dosage of 300 kg/m3 and K7 dosage of 500 kg/m3 along with curing under 20kPa pressure is recommendable for the peat stabilization to be effective. However for PCB2-5 mixture, it suggested to use more OPC and K7 dosage or alternatively increase the preloading during curing to 40kPa in order to achieve minimum strength target. It can be concluded that SCBA 1 has better quality than SCBA 2 in peat stabilization especially the contribution made by its fine particle size.

Keywords: peat stabilization, sugarcane bagasse ash utilization, partial cement replacement, unconfined strength

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Authors: Olivier Mesly

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This research presents a conceptual framework termed “Consumer Financial Spinning” (CFS) to analyze consumer behavior in the financial/economic markets. This phenomenon occurs when consumers of high-stakes financial products accumulate unsustainable debt, leading them to detach from their initial financial hierarchy of needs, wealth-related goals, and preferences regarding their household portfolio of assets. The daring actions of these consumers, forming a dark financial triangle, are characterized by three behaviors: overconfidence, the use of rationed rationality, and deceitfulness. We show that we can incorporate CFS into the traditional CAPM and Markovitz’ portfolio optimization models to create a framework that explains such market phenomena as the global financial crisis, highlighting the antecedents and consequences of ill-conceived speculation. Because this is a conceptual paper, there is no methodology with respect to ground studies. However, we apply modeling principles derived from the data percolation methodology, which contains tenets explicating how to structure concepts. A simulation test of the proposed framework is conducted; it demonstrates the conditions under which the relationship between expected returns and risk may deviate from linearity. The analysis and conceptual findings are particularly relevant both theoretically and pragmatically as they shed light on the psychological conditions that drive intense speculation, which can lead to market turmoil. Armed with such understanding, regulators are better equipped to propose solutions before the economic problems become out of control.

Keywords: consumer financial spinning, rationality, deceitfulness, overconfidence, CAPM

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.

Keywords: injection molding, shrinkage, six sigma, Taguchi parameter design

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Authors: Gargi Ghoshal, Ashay Jain

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Microencapsulation of β-carotene was optimized by complex coacervation technique using casein/gum tragacanth (CAS/GT) coating as a function of pH, initial protein to polysaccharide mixing ratio (Pr:Ps), total biopolymer concentration, core material load, zeta potential, and ionic strength. This study was aimed to understand the influence of experimental parameters on the coacervation kinetics, the coacervate yield, and entrapment efficiency. At a Pr:Ps = 2:1, an optimum pH of complex coacervation was found 4.35, at which the intensity of electrostatic interaction was maximum. At these ratios of coating, the phase separation occurred the fastest and the final coacervate yield and entrapment efficiency was the highest. Varying the Pr: Ps shifted the value of optimum pH. This incident was due to the level of charge compensation of the CAS/GT complexes. Finally, electrostatic interaction and formation of coacervates between CAS and GT were confirmed by Fourier transform infra-red (FTIR) spectra. The size and surface properties of coacervates were studied using scanning electron microscopy (SEM). The resultant formulation (β-carotene loaded microcapsules) was evaluated for in vitro release study and antioxidant activity. Stability of encapsulated β-carotene was also evaluated under three levels of temperature (5, 25 and 40 °C) for 3 months. Encapsulation strongly increased the stability of micronutrients. Our results advocate potential of microcapsules as a novel carrier for the safeguard and sustained release of micronutrient.

Keywords: β-carotene, casein, complex coacervation, controlled release, gum tragacanth, microcapsules

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: Komal Verma, V. S. Moholkar

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This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result is essentially a consequence of synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Microconvection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe₃O₄@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater The Fe₃O₄@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: Fe₃O₄@AC nanocomposite, RSM, COD;, LC-MS, Toxicity

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Authors: Lila Boulekbache-Makhlouf, Kahina Djaoud, Myriam Tazarourte, Samir Hadjal, Khodir Madani

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In Algeria, important quantities of secondary date variety (Phoenix dactylifera L.) are generated in each campaign; their chemical composition is similar to that of commercial dates. The present work aims to valorize this common date variety (Degla-Beida) which is often poorly exploited. In this context, we tried to prepare syrup from the secondary date variety and to evaluate the effect of conventional extraction (CE) or water bath extraction (WBE) and alternative extraction (microwaves assisted extraction (MAE), and ultrasounds assisted extraction (UAE)) on its total sugar content (TSC), using response surface methodology (RSM). Then, the analysis of individual sugars was performed by high-performance liquid chromatography (HPLC). Maximum predicted TSC recoveries under the optimized conditions for MAE, UAE and CE were 233.248 ± 3.594 g/l, 202.889 ± 5.797 g/l, and 233.535 ± 5.412 g/l, respectively, which were close to the experimental values: 233.796 ± 1.898 g/l; 202.037 ± 3.401 g/l and 234.380 ± 2.425 g/l. HPLC analysis revealed high similarity in the sugar composition of date juices obtained by MAE (60.11% sucrose, 16.64% glucose and 23.25% fructose) and CE (50.78% sucrose, 20.67% glucose and 28.55% fructose), although a large difference was detected for that obtained by UAE (0.00% sucrose, 46.94% glucose and 53.06% fructose). Microwave-assisted extraction was the best method for the preparation of date syrup with an optimal recovery of total sugar content. However, ultrasound-assisted extraction was the best one for the preparation of date syrup with high content of reducing sugars.

Keywords: dates, extraction, RSM, sugars, syrup

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Authors: Ganesh Dattatraya Saratale, Min Kyu Oh

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Rice straw is one of the most abundant lignocellulosic waste materials and its annual production is about 731 Mt in the world. This study treats the subject of effective utilization of this waste biomass for biofuels production. We have showed a comparative assessment of numerous pretreatment strategies for rice straw, comprising of major physical, chemical and physicochemical methods. Among the different methods employed for pretreatment alkaline pretreatment in combination with sodium chlorite/acetic acid delignification found efficient pretreatment with significant improvement in the enzymatic digestibility of rice straw. A cellulase dose of 20 filter paper units (FPU) released a maximum 63.21 g/L of reducing sugar with 94.45% hydrolysis yield and 64.64% glucose yield from rice straw, respectively. The effects of different pretreatment methods on biomass structure and complexity were investigated by FTIR, XRD and SEM analytical techniques. Finally the enzymatic hydrolysate of rice straw was used for ethanol production using developed Saccharomyces cerevisiae SR8. The developed yeast strain enabled efficient fermentation of xylose and glucose and produced higher ethanol production. Thus development of bioethanol production from lignocellulosic waste biomass is generic, applicable methodology and have great implication for using ‘green raw materials’ and producing ‘green products’ much needed today.

Keywords: rice straw, pretreatment, enzymatic hydrolysis, FPU, Saccharomyces cerevisiae SR8, ethanol fermentation

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Authors: Hao Qu, Xiang Liu, Michael Crosby, Brian Kozak, Andreas K. Freund

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The outstanding performance of highly oriented pyrolytic graphite (HOPG) as an optical element for neutron beam conditioning is unequaled by any other crystalline material in the applications of monochromator, analyzer, and filter. This superiority stems from the favorable nuclear properties of carbon (small absorption and incoherent scattering cross-sections, big coherent scattering length) and the specific crystalline structure (small thermal diffuse scattering cross-section, layered crystal structure). The real crystal defect structure revealed by imaging techniques is correlated with the parameters used in the mosaic model (mosaic spread, mosaic block size, uniformity). The diffraction properties (rocking curve width as determined by both the intrinsic mosaic spread and the diffraction process, peak and integrated reflectivity, filter transmission) as a function of neutron wavelength or energy can be predicted with high accuracy and reliability by diffraction theory using empirical primary extinction coefficients extracted from a great amount of existing experimental data. The results of these calculations are given as graphs and tables permitting to optimize HOPG characteristics (mosaic spread, thickness, curvature) for any given experimental situation.

Keywords: neutron optics, pyrolytic graphite, mosaic spread, neutron scattering, monochromator, analyzer

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: Gulcin Yildiz, Hao Feng

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Soybean proteins are the most widely used and researched proteins in the food industry. Due to soy allergies among consumers, however, alternative legume proteins having similar functional properties have been studied in recent years. These alternative proteins are also expected to have a price advantage over soy proteins. One such protein that has shown good potential for food applications is pea protein. Besides the favorable functional properties of pea protein, it also contains fewer anti-nutritional substances than soy protein. However, a comparison of the physicochemical properties of pea protein isolate (PPI)-starch nanocomplexes and soy protein isolate (SPI)-starch nanocomplexes treated by ultrasound has not been well documented. This study was undertaken to investigate the effects of ultrasound treatment on the physicochemical properties of PPI-starch and SPI-starch nanocomplexes. Pea protein isolate (85% pea protein) provided by Roquette (Geneva, IL, USA) and soy protein isolate (SPI, Pro-Fam® 955) obtained from the Archer Daniels Midland Company were adjusted to different pH levels (2-12) and treated with 5 minutes of ultrasonication (100% amplitude) to form complexes with starch. The soluble protein content was determined by the Bradford method using BSA as the standard. The turbidity of the samples was measured using a spectrophotometer (Lambda 1050 UV/VIS/NIR Spectrometer, PerkinElmer, Waltham, MA, USA). The volume-weighted mean diameters (D4, 3) of the soluble proteins were determined by dynamic light scattering (DLS). The emulsifying properties of the proteins were evaluated by the emulsion stability index (ESI) and emulsion activity index (EAI). Both the soy and pea protein isolates showed a U-shaped solubility curve as a function of pH, with a high solubility above the isoelectric point and a low one below it. Increasing the pH from 2 to 12 resulted in increased solubility for both the SPI and PPI-starch complexes. The pea nanocomplexes showed greater solubility than the soy ones. The SPI-starch nanocomplexes showed better emulsifying properties determined by the emulsion stability index (ESI) and emulsion activity index (EAI) due to SPI’s high solubility and high protein content. The PPI had similar or better emulsifying properties at certain pH values than the SPI. The ultrasound treatment significantly decreased the particle sizes of both kinds of nanocomplex. For all pH levels with both proteins, the droplet sizes were found to be lower than 300 nm. The present study clearly demonstrated that applying ultrasonication under different pH conditions significantly improved the solubility and emulsify¬ing properties of the SPI and PPI. The PPI exhibited better solubility and emulsifying properties than the SPI at certain pH levels

Keywords: emulsifying properties, pea protein isolate, soy protein isolate, ultrasonication

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Authors: Ogan Karabas, Suleyman Yigit

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Number of blade and blade type of centrifugal fans are the most decisive factor on the field of application, noise level, suction pressure and outlet mass flow rate. Nowadays, in order to determine these effects on centrifugal fans, numerical studies are carried out in addition to experimental studies. In this study, it is aimed to numerically investigate the changes of suction pressure and outlet mass flow rate values of a centrifugal fan according to the number of blade and blade type. Centrifugal fans of the same size with forward, backward and straight blade type were analyzed by using a simulation program and compared with each other. This analysis was carried out under steady state condition by selecting k-Ɛ turbulence model and air is assumed incompressible. Then, 16, 32 and 48 blade centrifugal fans were again analyzed by using same simulation program, and the optimum number of blades was determined for the suction pressure and the outlet mass flow rate. According to the results of the analysis, it was obtained that the suction pressure in the 32 blade fan was twice the value obtained in the 16 blade fan. In addition, the outlet mass flow rate increased by 45% with the increase in the number of blade from 16 to 32. There is no significant change observed on the suction pressure and outlet mass flow rate when the number of blades increased from 32 to 48. In the light of the analysis results, the optimum blade number was determined as 32.

Keywords: blade type, centrifugal fan, cfd, outlet mass flow rate, suction pressure

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Authors: Alvaro Javier Ortega

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A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

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Authors: Juliza Hidayati, Sukardi, Ani Suryani, Sugiharto, Anas M. Fauzi

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The idea of making North Sumatera as a barometer of national oil palm industry requires efforts commodities and agro-industry development of oil palm. One effort that can be done is by successful execution plantation revitalization. The plantation Revitalization is an effort to accelerate the development of smallholder plantations, through expansion and replanting by help of palm Estate Company as business partner and bank financed plantation revitalization fund. Business partner agreement obliged and bound to make at least the same smallholder plantation productivity with business partners, so that the refund rate to banks become larger and prosperous people as a plantation owner. Generally low productivity of smallholder plantations under normal potential caused a lot of old and damaged plants with plant material at random. The purpose of revitalizing oil palm plantations is which are to increase their competitiveness through increased farm productivity. The research aims to identify potential criteria in influencing plantation productivity improvement priorities to be observed and followed up in order to improve the competitiveness of destinations and make North Sumatera barometer of national palm oil can be achieved. Research conducted with Analytical Network Process (ANP), to find the effect of dependency relationships between factors or criteria with the knowledge of the experts in order to produce an objective opinion and relevant depict the actual situation.

Keywords: palm barometer, acceleration of plantation development, productivity, revitalization

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Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad

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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.

Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Zhichao Song, Swanand Vaidya

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Nowadays, most portable (e.g., smartphones) and wearable (e.g., smartwatches and earphones) consumer hardware are designed to be dustproof following IP5 or IP6 ratings to ensure the product is able to handle potentially dusty outdoor environments. On the other hand, the design guideline is relatively vague for indoor devices (e.g., smart displays and speakers). While it is generally believed that the indoor environment is much less dusty, in certain circumstances, dust ingression is still able to cause functional failures, such as microphone frequency response shift and camera black spot, or cosmetic dissatisfaction, mainly the dust build up in visible pockets and gaps which is hard to clean. In this paper, we developed a simulation methodology to analyze dust settlement and ingression into known ports of a device. A closed system is initialized with dust particles whose sizes follow Weibull distribution based on data collected in a user study, and dust particle movement was approximated as a settlement in stationary fluid, which is governed by Stokes’ law. Following this method, we simulated dust ingression into MEMS microphone through the acoustic port and protective mesh. Various design and environmental parameters are evaluated including mesh pore size, acoustic port depth-to-diameter ratio, mass density of dust material and inclined angle of microphone port. Although the dependencies of dust resistance on these parameters are all monotonic, smaller mesh pore size, larger acoustic depth-to-opening ratio and more inclined microphone placement (towards horizontal direction) are preferred for dust resistance; these preferences may represent certain trade-offs in audio performance and compromise in industrial design. The simulation results suggest the quantitative ranges of these parameters, with more pronounced effects in the improvement of dust resistance. Based on the simulation results, we proposed several design guidelines that intend to achieve an overall balanced design from audio performance, dust resistance, and flexibility in industrial design.

Keywords: dust settlement, numerical simulation, microphone design, Weibull distribution, Stoke's equation

Procedia PDF Downloads 102

Authors: Eman M. Sarhan, Doaa A. Ghareeb, Gabriella Ortore, Amr A. Amara, Mohamed M. El-Sayed

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Drug salting and nanoparticle-based drug delivery formulations are considered to be an effective means for rendering the hydrophobic drugs’ nano-scale dispersion in aqueous media, and thus circumventing the pitfalls of their poor solubility as well as enhancing their membrane permeability. The current study aims to increase the bioavailability of quaternary ammonium berberine through acid salting and biodegradable bovine serum albumin (BSA)-based nanoparticulate drug formulation. Berberine hydroxide (BBR-OH) that was chemically synthesized by alkalization of the commercially available berberine hydrochloride (BBR-HCl) was then acidified to get Di-berberine sulfate (BBR)₂SO₄. The purified crystals were spectrally characterized. The desolvation technique was optimized for the preparation of size-controlled BSA-BBR-HCl, BSA-BBR-OH, and BSA-(BBR)₂SO₄ nanoparticles. Particle size, zeta potential, drug release, encapsulation efficiency, Fourier transform infrared spectroscopy (FTIR), tandem MS-MS spectroscopy, energy-dispersive X-ray spectroscopy (EDX), scanning and transmitting electron microscopic examination (SEM, TEM), in vitro bioactivity, and in silico drug-polymer interaction were determined. BSA (PDB ID; 4OR0) protonation state at different pH values was predicted using Amber12 molecular dynamic simulation. Then blind docking was performed using Lamarkian genetic algorithm (LGA) through AutoDock4.2 software. Results proved the purity and the size-controlled synthesis of berberine-BSA-nanoparticles. The possible binding poses, hydrophobic and hydrophilic interactions of berberine on BSA at different pH values were predicted. Antioxidant, anti-hemolytic, and cell differentiated ability of tested drugs and their nano-formulations were evaluated. Thus, drug salting and the potentially effective albumin berberine nanoparticle formulations can be successfully developed using a well-optimized desolvation technique and exhibiting better in vitro cellular bioavailability.

Keywords: berberine, BSA, BBR-OH, BBR-HCl, BSA-BBR-HCl, BSA-BBR-OH, (BBR)₂SO₄, BSA-(BBR)₂SO₄, FTIR, AutoDock4.2 Software, Lamarkian genetic algorithm, SEM, TEM, EDX

Procedia PDF Downloads 165

Authors: Mahdi GoharRokhi, Mohammad H. Ruhipour, Mohammad R. ZamaniZadeh, Mohsen Maleki, Yusef Shamsayi, Mahdi FarhaniNejad, Farzad FarrokhZadeh

Abstract:

Possessing massive resources of natural gas and petroleum, Iran has a special place among all other oil producing countries, according to international institutions of energy. In order to use these resources, development and functioning optimization of refineries and industrial units is mandatory. Heat exchanger is one of the most important and strategic equipment which its key role in the process of production is clear to everyone. For instance, if the temperature of a processing fluid is not set as needed by heat exchangers, the specifications of desired product can change profoundly. Crude oil enters a network of heat exchangers in atmospheric distillation section before getting into the distillation tower; in this case, well-functioning of heat exchangers can significantly affect the operation of distillation tower. In this paper, different scenarios for pre-heating of oil are studied using oil and gas simulation software, and the results are discussed. As we reviewed various scenarios, adding a heat exchanger to pre-heating network is proposed as the most efficient factor in improving all governing parameters of the tower i.e. temperature, pressure, and reflux rate. This exchanger is embedded in crude oil’s path. Crude oil enters the exchanger after E-101 and exchanges heat with discharging kerosene pump around from E-136. As depicted in the results, it will efficiently assist the improvement of process operation and side expenses.

Keywords: atmospheric distillation unit, heat exchanger, preheat, simulation

Procedia PDF Downloads 651

Authors: Anatoly A. Kuznetsov, Pavel G. Berezhko, Sergey M. Kunavin, Eugeny V. Zhilkin, Maxim V. Tsarev, Vyacheslav V. Yaroshenko, Valery V. Mokrushin, Olga Y. Yunchina, Sergey A. Mityashin

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The acoustic emission is caused by short-time propagation of elastic waves that are generated as a result of quick energy release from sources localized inside some material. In particular, the acoustic emission phenomenon lies in the generation of acoustic waves resulted from the reconstruction of material internal structures. This phenomenon is observed at various physicochemical transformations, in particular, at those accompanying hydrogenation processes of metals or intermetallic compounds that make it possible to study parameters of these transformations through recording and analyzing the acoustic signals. It has been known that at the interaction between metals or inter metallides with hydrogen the most intensive acoustic signals are generated as a result of cracking or crumbling of an initial compact powder sample as a result of the change of material crystal structure under hydrogenation. This work is dedicated to the study into changes occurring in metallic titanium samples at their interaction with hydrogen and followed by acoustic emission signals. In this work the subjects for investigation were specimens of metallic titanium in two various initial forms: titanium sponge and fine titanium powder made of this sponge. The kinetic of the interaction of these materials with hydrogen, the acoustic emission signals accompanying hydrogenation processes and the structure of the materials before and after hydrogenation were investigated. It was determined that in both cases interaction of metallic titanium and hydrogen is followed by acoustic emission signals of high amplitude generated on reaching some certain value of the atomic ratio [H]/[Ti] in a solid phase because of metal cracking at a macrolevel. The typical sizes of the cracks are comparable with particle sizes of hydrogenated specimens. The reasons for cracking are internal stresses initiated in a sample due to the increasing volume of a solid phase as a result of changes in a material crystal lattice under hydrogenation. When the titanium powder is used, the atomic ratio [H]/[Ti] in a solid phase corresponding to the maximum amplitude of an acoustic emission signal are, as a rule, higher than when titanium sponge is used.

Keywords: acoustic emission signal, cracking, hydrogenation, titanium specimen

Procedia PDF Downloads 378

Authors: L. Malic, X. Zhang, D. Brassard, L. Clime, J. Daoud, C. Luebbert, V. Barrere, A. Boutin, S. Bidawid, N. Corneau, J. Farber, T. Veres

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The incidence of infections caused by foodborne pathogens such as Listeria monocytogenes (L. monocytogenes) poses a great potential threat to public health and safety. These issues are further exacerbated by legal repercussions due to “zero tolerance” food safety standards adopted in developed countries. Unfortunately, a large number of related disease outbreaks are caused by pathogens present in extremely low counts currently undetectable by available techniques. The development of highly sensitive and rapid detection of foodborne pathogens is therefore crucial, and requires robust and efficient pre-analytical sample preparation. Immunomagnetic separation is a popular approach to sample preparation. Microfluidic chips combined with external magnets have emerged as viable high throughput methods. However, external magnets alone are not suitable for the capture of nanoparticles, as very strong magnetic fields are required. Devices that incorporate externally applied magnetic field and microstructures of a soft magnetic material have thus been used for local field amplification. Unfortunately, very complex and costly fabrication processes used for integration of soft magnetic materials in the reported proof-of-concept devices would prohibit their use as disposable tools for food and water safety or diagnostic applications. We present a sample preparation magnetic microfluidic device implemented in low-cost thermoplastic polymers using fabrication techniques suitable for mass-production. The developed magnetic capture chip (M-chip) was employed for rapid capture and release of L. monocytogenes conjugated to immunomagnetic nanoparticles (IMNs) in buffer and beef filtrate. The M-chip relies on a dense array of Nickel-coated high-aspect ratio pillars for capture with controlled magnetic field distribution and a microfluidic channel network for sample delivery, waste, wash and recovery. The developed Nickel-coating process and passivation allows generation of switchable local perturbations within the uniform magnetic field generated with a pair of permanent magnets placed at the opposite edges of the chip. This leads to strong and reversible trapping force, wherein high local magnetic field gradients allow efficient capture of IMNs conjugated to L. monocytogenes flowing through the microfluidic chamber. The experimental optimization of the M-chip was performed using commercially available magnetic microparticles and fabricated silica-coated iron-oxide nanoparticles. The fabricated nanoparticles were optimized to achieve the desired magnetic moment and surface functionalization was tailored to allow efficient capture antibody immobilization. The integration, validation and further optimization of the capture and release protocol is demonstrated using both, dead and live L. monocytogenes through fluorescence microscopy and plate- culture method. The capture efficiency of the chip was found to vary as function of listeria to nanoparticle concentration ratio. The maximum capture efficiency of 30% was obtained and the 24-hour plate-culture method allowed the detection of initial sample concentration of only 16 cfu/ml. The device was also very efficient in concentrating the sample from a 10 ml initial volume. Specifically, 280% concentration efficiency was achieved in 17 minutes only, demonstrating the suitability of the system for food safety applications. In addition, flexible design and low-cost fabrication process will allow rapid sample preparation for applications beyond food and water safety, including point-of-care diagnosis.

Keywords: array of pillars, bacteria isolation, immunomagnetic sample preparation, polymer microfluidic device

Procedia PDF Downloads 268

Authors: Tanios Saliba, Jad Wakim, Elie Awwad

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Clayey soils exhibit undesirable problems in civil engineering project: poor bearing soil capacity, shrinkage, cracking, …etc. On the other hand, the increasing production of bottom ash and its disposal in an eco-friendly manner is a matter of concern. Soil stabilization using bottom ash is a new technic in the geo-environmental engineering. It can be used wherever a soft clayey soil is encountered in foundations or road subgrade, instead of using old technics such as cement-soil mixing. This new technology can be used for road embankments and clayey foundations platform (shallow or deep foundations) instead of replacing bad soil or using old technics which aren’t eco-friendly. Moreover, applying this new technic in our geotechnical engineering projects can reduce the disposal of the bottom ash problem which is getting bigger day after day. The research consists of mixing clayey soil with different percentages of bottom ash at different values of water content, and evaluates the mechanical properties of every mix: the percentages of bottom ash are 10% 20% 30% 40% and 50% with values of water content of 25% 35% and 45% of the mix’s weight. Before testing the different mixes, clayey soil’s properties were determined: Atterbeg limits, soil’s cohesion and friction angle and particle size distribution. In order to evaluate the mechanical properties and behavior of every mix, different tests are conducted: -Direct shear test in order to determine the cohesion and internal friction angle of every mix. -Unconfined compressive strength (stress strain curve) to determine mix’s elastic modulus and compressive strength. Soil samples are prepared in accordance with the ASTM standards, and tested at different times, in order to be able to emphasize the influence of the curing period on the variation of the mix’s mechanical properties and characteristics. As of today, the results obtained are very promising: the mix’s cohesion and friction angle vary in function of the bottom ash percentage, water content and curing period: the cohesion increases enormously before decreasing for a long curing period (values of mix’s cohesion are larger than intact soil’s cohesion) while internal friction angle keeps on increasing even when the curing period is 28 days (the tests largest curing period), which give us a better soil behavior: less cracks and better soil bearing capacity.

Keywords: bottom ash, Clayey soil, mechanical properties, tests

Procedia PDF Downloads 171

Authors: M. F. Amado, A. Amado, F. Poggi, J. Correia de Freitas

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Today it is widely understood that global energy consumption patterns are directly related to the ongoing urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals. In this paper, a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities, economic development, and the local and global environment while safeguarding fairness in the energy sector.

Keywords: solar urban planning, solar smart city, urban development, energy efficiency

Procedia PDF Downloads 323

Authors: Rohit Shrivastava, Stefan Luding

Abstract:

A mechanical wave is propagation of vibration with transfer of energy and momentum. Studying the energy as well as spectral energy characteristics of a propagating wave through disordered granular media can assist in understanding the overall properties of wave propagation through inhomogeneous materials like soil. The study of these properties is aimed at modeling wave propagation for oil, mineral or gas exploration (seismic prospecting) or non-destructive testing for the study of internal structure of solids. The study of Energy content (Kinetic, Potential and Total Energy) of a pulse propagating through an idealized one-dimensional discrete particle system like a mass disordered granular chain can assist in understanding the energy attenuation due to disorder as a function of propagation distance. The spectral analysis of the energy signal can assist in understanding dispersion as well as attenuation due to scattering in different frequencies (scattering attenuation). The selection of one-dimensional granular chain also helps in studying only the P-wave attributes of the wave and removing the influence of shear or rotational waves. Granular chains with different mass distributions have been studied, by randomly selecting masses from normal, binary and uniform distributions and the standard deviation of the distribution is considered as the disorder parameter, higher standard deviation means higher disorder and lower standard deviation means lower disorder. For obtaining macroscopic/continuum properties, ensemble averaging has been used. Interpreting information from a Total Energy signal turned out to be much easier in comparison to displacement, velocity or acceleration signals of the wave, hence, indicating a better analysis method for wave propagation through granular materials. Increasing disorder leads to faster attenuation of the signal and decreases the Energy of higher frequency signals transmitted, but at the same time the energy of spatially localized high frequencies also increases. An ordered granular chain exhibits ballistic propagation of energy whereas, a disordered granular chain exhibits diffusive like propagation, which eventually becomes localized at long periods of time.

Keywords: discrete elements, energy attenuation, mass disorder, granular chain, spectral energy, wave propagation

Procedia PDF Downloads 281