Search results for: particle matter (PM)

Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution

Keywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution

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Authors: E. Keramaris

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In this study, laboratory experiments in open channel flows over a sand bed were conducted. A porous bed (sand bed) with porosity of ε=0.70 and porous thickness of s΄=3 cm was tested. Vertical distributions of velocity were evaluated by using a two-dimensional (2D) Particle Image Velocimetry (PIV). Velocity profiles are measured above the impermeable bed and above the sand bed for the same different total water heights (h= 6, 8, 10 and 12 cm) and for the same slope S=1.5. Measurements of mean velocity indicate the effects of the bed material used (sand bed) on the flow characteristics (Velocity distribution and Reynolds number) in comparison with those above the impermeable bed.

Keywords: particle image velocimetry, sand bed, velocity distribution, Reynolds number

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Authors: Mutaz Dwairy

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Solid tumors have high interstitial fluid pressure (IFP), high mechanical stress, and low oxygen levels. Solid stresses may induce apoptosis, stimulate the invasiveness and metastasis of cancer cells, and lower their proliferation rate, while oxygen concentration may affect the response of cancer cells to treatment. Although tumors grow in a nonhomogeneous environment, many existing theoretical models assume homogeneous growth and tissue has uniform mechanical properties. For example, the brain consists of three primary materials: white matter, gray matter, and cerebrospinal fluid (CSF). Therefore, tissue inhomogeneity should be considered in the analysis. This study established a physical model based on convection-diffusion equations and continuum mechanics principles. The model considers the geometrical inhomogeneity of the brain by including the three different matters in the analysis: white matter, gray matter, and CSF. The model also considers fluid-solid interaction and explicitly describes the effect of mechanical factors, e.g., solid stresses and IFP, chemical factors, e.g., oxygen concentration, and biological factors, e.g., cancer cell concentration, on growing tumors. In this article, we applied the model on a brain tumor positioned within the white matter, considering the brain inhomogeneity to estimate solid stresses, IFP, the cancer cell concentration, oxygen concentration, and the deformation of the tissues within the neoplasm and the surrounding. Tumor size was estimated at different time points. This model might be clinically crucial for cancer detection and treatment planning by measuring mechanical stresses, IFP, and oxygen levels in the tissue.

Keywords: biomechanical model, interstitial fluid pressure, solid stress, tumor microenvironment

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Authors: A. Hamidi, S. Khelladi, L. Illoul, A. Tcharkhtchi

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Reactive rotational molding (RRM) is a process to manufacture hollow plastic parts with reactive material has several advantages compared to conventional roto molding of thermoplastic powders: process cycle time is shorter; raw material is less expensive because polymerization occurs during processing and high-performance polymers may be used such as thermosets, thermoplastics or blends. However, several phenomena occur during this process which makes the optimization of the process quite complex. In this study, we have used a mixture of isocyanate and polyol as a reactive system. The chemical transformation of this system to polyurethane has been studied by thermal analysis and rheology tests. Thanks to these results of the curing process and rheological measurements, the kinetic and rheokinetik of polyurethane was identified. Smoothed Particle Hydrodynamics, a Lagrangian meshless method, was chosen to simulate reactive fluid flow in 2 and 3D configurations of the polyurethane during the process taking into account the chemical, and chemiorehological results obtained experimentally in this study.

Keywords: reactive rotational molding, simulation, smoothed particle hydrodynamics, surface tension, rheology, free surface flows, viscoelastic, interpolation

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Authors: Suzannah Sharif, Aznie Aida Ahmad, Maznah Ismail

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Cocoa bean is the raw material for products such as cocoa powder and chocolate. Cocoa bean contains polyphenol which has been shown in several clinical studies to confer beneficial health effects. However studies showed that cocoa polyphenol absorption in the human intestinal tracts are very low. Therefore nanoemulsion may be one way to increase the bioavailability of cocoa polyphenol. This study aim to characterize nanoemulsion incorporating crude cocoa polyphenol produced using high energy technique. Cocoa polyphenol was extracted from fresh freeze-dried cocoa beans from Malaysia. The particle distribution, particle size, and zeta potential were determined. The emulsion was also analysed using transmission electron microscope to visualize the particles. Solubilization study was conducted by titrating the nanoemulsion into distilled water or 1% surfactant solution. Result showed that the nanoemulsion contains particle which have narrow size distribution. The particles size average at 112nm with zeta potential of -45mV. The nanoemulsions behave differently in distilled water and surfactant solution.

Keywords: cocoa, nanoemulsion, cocoa polyphenol, solubilisation study

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Authors: Hossein Arfaeinia, Azam Nadali, Zahra Asadgol, Mohammad Fahiminia

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Indoor and outdoor particulate matters (PM) were monitored in 20 residential buildings in a two-part study. In part I, the levels of indoor and outdoor PM₁₀, PM₂.₅ and PM₁ was measured using real time GRIMM dust monitors. In part II, the effect of negative air ions (NAIs) method was investigated on the reduction of indoor concentration of PM in these residential buildings. Hourly average concentration and standard deviation (SD) of PM₁₀ in indoor and outdoor at residential buildings were 90.1 ± 33.5 and 63.5 ± 27.4 µg/ m3, respectively. Indoor and outdoor concentrations of PM₂.₅ in residential buildings were 49.5 ± 18.2 and 39.4± 18.1 µg/ m3 and for PM₁ the concentrations were 6.5 ± 10.1and 4.3 ± 7.7 µg/ m3, respectively. Indoor/outdoor (I/O) ratios and concentrations of all size fractions of PM were strongly correlated with wind speed and temperature whereas a good relationship was not observed between humidity and I/O ratios of PM. We estimated that nearly 71.47 % of PM₁₀, 79.86 % of PM₂.₅ and of 61.25 % of PM₁ in indoor of residential buildings can be removed by negative air ions.

Keywords: particle matter (PM), indoor air, negative air ions (NAIs), residential building

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Authors: Shane Theunissen, Rob Grandy

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Historically and we would fairly conventionally within our formal schooling systems, we have convergent testing where all the students are expected to converge on the same answer, and that answer has been determined by an external authority that is reproducing knowledge of the hegemon. Many youths may not embody the cultural capital that's rewarded in formal schooling contexts as they aren't able to converge on the required answer that's being determined by the classroom teacher or the administrators. In this paper, we explore divergent processes that promote creative problem-solving. We embody this divergent process in our measurement of fundamental growth needs. To this end, we utilize the Mosaic Approach as a method for implementing the Outcomes That Matter framework. Outcomes That Matter is the name of the measurement tool built around the Circle of Courage framework, which is a way of identifying fundamental growth needs for young people. The Circle of Courage was developed by Martin-Broken-Leg and colleagues as a way to connect indigenous child-rearing philosophies with contemporary resilience and positive psychology research. The Outcomes that Matter framework puts forward four categories of growth needs for young people. These are: Belonging, which on a macro scale is acceptance into the greater community of practice, Mastery which includes a constellation of concepts including confidence, motivation, self-actualization, and self-determination, Independence refers to a sense of personal power into autonomy within a context where creativity and problem solving, and a personal voice can begin to emerge, and finally Generosity which includes interpersonal things like conflict resolution and teamwork. Outcomes of Matter puts these four domains into a measurement tool that facilitates collaborative assessment between the youth, teachers, and recreation therapists that allows for youth-led narratives pertaining to their fundamental growth outcomes. This application of the Outcomes That Matter framework is unique as it may be the first application of this framework in an educational boatbuilding context.

Keywords: collaboration, empowerment, outcomes that matter, mosaic approach, boat building

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Authors: Benoit Rougier, Alexandre Lefrancois, Herve Aubert

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Microwave interrogation in the range 10-100 GHz is identified as an advanced technique to investigate simultaneously shock and particle velocity measurements. However, it requires the understanding of electromagnetic wave propagation in a multi-layered moving media. The existing models limit their approach to wave guides or evaluate the velocities with a fitting method, restricting therefore the domain of validity and the precision of the results. Moreover, few data of permittivity on high explosives at these frequencies under dynamic compression have been reported. In this paper, shock and particle velocities are computed concurrently for steady and unsteady shocks for various inert and reactive materials, via a propagation model based on Doppler shifts and signal amplitude. Refractive index of the material under compression is also calculated. From experimental data processing, it is demonstrated that Hugoniot curve can be evaluated. The comparison with published results proves the accuracy of the proposed method. This microwave interrogation technique seems promising for shock and detonation waves studies.

Keywords: electromagnetic propagation, experimental setup, Hugoniot measurement, shock propagation

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Authors: Saadelnour Abdueljabbar Adam

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Wastes from slaughterhouses in most towns in Sudan are often poorly managed and sometimes discharged into adjoining streams due to poor implementation of standards, thus causing environmental and public health hazards and also there is a large amount of manure from dairy farms. This paper presents a solution of organic waste from cow dairy farms and slaughterhouse. We present the findings of experimental investigation of biogas production using cow manure, blood and rumen content were mixed at three proportions :72.3%, 61%, 39% manure, 6%, 8.5%, 22% blood; and 21.7%, 30.5%, 39% rumen content in volume for bio-digester 1,2,3 respectively. This paper analyses the quantitative and qualitative composition of biogas: gas content, and the concentration of methane. The highest biogas output 0.116L/g dry matter from bio-digester1 together with a high-quality biogas of 85% methane Was from the mixture of cow manure with blood and rumen content were mixed at 72.3%manure, 6%blood and 21.7%rumen content which is useful for combustion and energy production. While bio-digester 2 and 3 gave 0.012L/g dry matter and 0.013L/g dry matter respectively with the weak concentration of methane (50%).

Keywords: anaerobic digestion, bio-digester, blood, cow manure, rumen content

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Authors: Saeed Ur Rahman, Naveed Ullah, Muhammad Irshad Khan, Quensheng Cao, Niaz Muhammad Khan

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In this paper the optimization performance of non-uniform linear antenna array is presented. The Particle Swarm Optimization (PSO) algorithm is presented to minimize Side Lobe Level (SLL) and Half Power Beamwidth (HPBW). The purpose of using the PSO algorithm is to get the optimum values for inter-element spacing and excitation amplitude of linear antenna array that provides a radiation pattern with minimum SLL and HPBW. Various design examples are considered and the obtain results using PSO are confirmed by comparing with results achieved using other nature inspired metaheuristic algorithms such as real coded genetic algorithm (RGA) and biogeography (BBO) algorithm. The comparative results show that optimization of linear antenna array using the PSO provides considerable enhancement in the SLL and HPBW.

Keywords: linear antenna array, minimum side lobe level, narrow half power beamwidth, particle swarm optimization

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Authors: Yagya Sharma, Basanta K. Rana, Arup K. Das

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Rotary entrainment is a phenomenon in which the interfaces of two immiscible fluids are subjected to external flux in the form of rotation. Present work reports the experimental study on rotary motion of a horizontal cylinder between the interface of air and water to observe the penetration of gas inside the liquid. Experiments have been performed to establish entrainment of air mass in water alongside the cylindrical surface. The movement of tracer and seeded particles have been tracked to calculate the speed and path of the entrained air inside water. Simplified particle image velocimetry technique has been used to trace the movement of particles/tracers at the moment they are injected inside the entrainment zone and suspended beads have been used to replicate the particle movement with respect to time in order to determine the flow dynamics of the fluid along the cylinder. Present paper establishes a thorough experimental analysis of the rotary entrainment phenomenon between air and water keeping in interest the extent to which we can intermix the two and also to study its entrainment trajectories.

Keywords: entrainment, gas-liquid flow, particle image velocimetry, stratified layer mixing

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Authors: Mohanad Al-Behadili, Djamila Ouelhadj

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In this paper, a specific type of vehicle routing problem under stochastic demand (SVRP) is considered. This problem is of great importance because it models for many of the real world vehicle routing applications. This paper used a robust optimisation model to solve the problem along with the novel Simulation-Particle Swarm Optimisation (Sim-PSO) approach. The proposed Sim-PSO approach is based on the hybridization of the Monte Carlo simulation technique with the PSO algorithm. A comparative study between the proposed model and the Sim-PSO approach against other solution methods in the literature has been given in this paper. This comparison including the Analysis of Variance (ANOVA) to show the ability of the model and solution method in solving the complicated SVRP. The experimental results show that the proposed model and Sim-PSO approach has a significant impact on the obtained solution by providing better quality solutions comparing with well-known algorithms in the literature.

Keywords: stochastic vehicle routing problem, robust optimisation model, Monte Carlo simulation, particle swarm optimisation

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Authors: W. Benstaali, A. Belasri

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In this work we study a planar lamp filled with neon-xenon gas. We use a one-dimensional particle in a cell with Monte Carlo simulation (PIC-MCC) to investigate the effect xenon concentration on the energy deposited on excitation, ionization and ions. A Xe-Ne discharge is studied for a gas pressure of 400 torr. The results show an efficient Xe20-Ne mixture with an applied voltage of 1.2KV; the xenon excitation energy represents 65% form total energy dissipated in the discharge. We have also studied electrical properties and the energy balance a discharge for Xe50-Ne which needs a voltage of 2kv; the xenon energy is than more important.

Keywords: dielectric barrier discharge, efficiency, excitation, lamps

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Authors: Raj Banerjee, Y. M. Parulekar, Aniruddha Sengupta, J. Chattopadhyay

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This study proposes a Discrete Element Method (DEM) simulation using a commercial software PFC 2D (2019) for quantitatively simulating the monotonic and cyclic behaviour of sand using irregular shapes of sand grains. A preliminary analysis of the number of particles for optimal Representative Element Volume (REV) simulation of dimension 35mm x 35mm x 70mm using the scaled Grain Size Distribution (GSD) of sand is carried out. Subsequently, the effect of particle shape on the performance of sand during monotonic and cyclic bi-axial tests is assessed using numerical simulation. The validation of the numerical simulation for one case is carried out using the test results from the literature. Further numerical studies are performed in which the particles in REV are simulated by mixing round discs with irregular clumps (100% round disc, 75% round disc 25% irregular clump, 50% round disc 50% irregular clump, 25% round disc 75% irregular clump, 100% irregular clump) in different proportions using Dry Deposition (DD) method. The macro response for monotonic loading shows that irregular sand has a higher strength than round particles and that the Mohr-Coulomb failure envelope depends on the shape of the grains. During cyclic loading, it is observed that the liquefaction resistance curve (Cyclic Stress Ratio (CSR)-Number of cycles (N)) of sand is dependent on the combination of particle shapes with different proportions.

Keywords: biaxial test, particle shape, monotonic, cyclic

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Authors: Prakriti Diwan, S. Saraf

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The present study involves preparation and evaluation of microparticles of diclofenac sodium. The microparticles were prepared by the emulsion solvent evaporation techniques using ethylcellulose polymer. Four different batches of microspheres were prepared by varying the concentration of polymer from 50% to 80% w/w. The microspheres were characterized for drug content, percentage yield and encapsulation efficiency, particle size analysis and surface morphology. Microsphere prepared with high drug content produces higher percentage yield and encapsulation efficiency values. It was observed the increase in concentration of the polymer, increases the mean particle size of the microspheres. The effect of polymer concentration on the in vitro release of diclofenac from the microspheres was also studied. The production microparticles yield showed 98.74%, mean particle size 956.32µm and loading efficiency 97.15%. The results were found that microparticles prepared had slower release than microparticles (p>0.05). Therefore, it may be concluded that drug loaded microparticles are suitable delivery systems for diclofenac sodium.

Keywords: diclofenac sodium, emulsion solvent evaporation, ethylcellulose, microparticles

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Authors: Susanta Kumar Gachhayat, S. K. Dash

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Multi objective non-convex economic dispatch problems of a thermal power plant are of grave concern for deciding the cost of generation and reduction of emission level for diminishing the global warming level for improving green-house effect. This paper deals with ramp rate constraints for achieving better inequality constraints so as to incorporate valve point loading for cost of generation in thermal power plant through ramp rate biogeography based optimization involving mutation and migration. Through 50 out of 100 trials, the cost function and emission objective function were found to have outperformed other classical methods such as lambda iteration method, quadratic programming method and many heuristic methods like particle swarm optimization method, weight improved particle swarm optimization method, constriction factor based particle swarm optimization method, moderate random particle swarm optimization method etc. Ramp rate biogeography based optimization applications prove quite advantageous in solving non convex multi objective economic dispatch problems subjected to nonlinear loads that pollute the source giving rise to third harmonic distortions and other such disturbances.

Keywords: economic load dispatch, ELD, biogeography-based optimization, BBO, ramp rate biogeography-based optimization, RRBBO, valve-point loading, VPL

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Authors: Vadood Mobini, Mansoreh Agazadeh Shahrivar, Parvin Hashemi Gelenjkhanlo, Hassan Vazifah

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Seed number is a function of dry matter accumulation, crop growth rate (CGR), photothermal quotient (PTQ) and temperature during a critical developmental period, which is around flowering in canola (Brassica napus L.). The objective of this experiment was to determine factors such as dry matter, CGR, temperature, and PTQ around flowering which affect seed number. The experiment was conducted at Agricultural Research Station of Gonbad, Iran, between 2005 and 2007. Two cultivars of canola (Hyola401 and RGS003), as subplots were grown at 5 sowing dates as main plots, spaced approximately 30 days apart, to obtain different environmental conditions during flowering. The experiment was arranged in two conditions, i.e., supplemental irrigation and rainfed. Seed number per unit area was a key factor for increasing seed yield. Late sowing dates made the critical period of flowering coincide with high temperatures, decreased days to the flowering, seed number per unit area and seed yield. Seed number was driven by the availability of carbohydrates around flowering. Seed number per unit area was maximized for the cultivars when exposed to the highest PTQ, and to the lowest temperature between the beginning of flowering to that of seed filling. The relationship of seed number with aboveground dry matter, CGR, temperature, and PTQ around flowering, over different environmental conditions, showed these variables were generally applicable to seed number determination.

Keywords: flowering, cultivar, seed filling, environmental conditions, seed yield

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Authors: H. Kazemi Esfeh, V. Akbari, M. Ehdaei, T. N. G. Borhani, A. Shamiri, M. Najafi

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In an industrial fluidized bed polymerization reactor, particle size distribution (PSD) plays a significant role in the reactor efficiency evaluation. The computational fluid dynamic (CFD) models coupled with population balance equation (CFD-PBM) have been extensively employed to investigate the flow behavior in the poly-disperse multiphase fluidized bed reactors (FBRs) utilizing ANSYS Fluent code. In this study, an existing CFD-PBM/ DQMOM coupled modeling framework has been used to highlight its potential to analyze the industrial-scale gas phase polymerization reactor. The predicted results reveal an acceptable agreement with the observed industrial data in terms of pressure drop and bed height. The simulated results also indicate that the higher particle growth rate can be achieved for bigger particles. Hence, the 2D CFD-PBM/DQMOM coupled model can be used as a reliable tool for analyzing and improving the design and operation of the gas phase polymerization FBRs.

Keywords: computational fluid dynamics, population balance equation, fluidized bed polymerization reactor, direct quadrature method of moments

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Authors: Tooran Tavangar, Masoud Hosseinpoor, Jeffrey S. Marshall, Ammar Yahia, Kamal Henri Khayat

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In this study, a four-way coupled CFD-DEM methodology was used to simulate the behavior of concrete pipe flow. Fresh concrete, characterized as a biphasic suspension, features aggregates comprising the solid-suspended phase with diverse particle-size distributions (PSD) within a non-Newtonian cement paste/mortar matrix forming the liquid phase. The fluid phase was simulated using CFD, while the aggregates were modeled using DEM. Interaction forces between the fluid and solid particles were considered through CFD-DEM computations. To capture the viscoelastic characteristics of the suspending fluid, a bi-viscous approach was adopted, incorporating a critical shear rate proportional to the yield stress of the mortar. In total, three diphasic suspensions were simulated, each featuring distinct particle size distributions and a concentration of 10% for five subclasses of spherical particles ranging from 1 to 17 mm in a suspending fluid. The adopted bi-viscous approach successfully simulated both un-sheared (plug flow) and sheared zones. Furthermore, shear-induced particle migration (SIPM) was assessed by examining coefficients of variation in particle concentration across the pipe. These SIPM values were then compared with results obtained using CFD-DEM under the Newtonian assumption. The study highlighted the crucial role of yield stress in the mortar phase, revealing that lower yield stress values can lead to increased flow rates and higher SIPM across the pipe.

Keywords: computational fluid dynamics, concrete pumping, coupled CFD-DEM, discrete element method, plug flow, shear-induced particle migration.

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Authors: Seyed Mohammad Ali Zahedi

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This field experiment was conducted in Isfahan in 2011 in order to study the effect of plant density and planting pattern on growth, yield and quality of silage corn (SC 704) using a randomized complete block design with split plot layout and four replications. The main plot consisted of three planting patterns (60 and 75 cm single planting row and 75 cm double planting row referred to as 60S, 75S and 75T, respectively). The subplots consisted of four levels of plant densities (65000, 80000, 95000 and 110000 plants per hectare). Each subplot consisted of 7 rows, each with 10m length. Vegetative and reproductive characteristics of plants at silking and hard dough stages (when the plants were harvested for silage) were evaluated. Results of variance analysis showed that the effects of planting pattern and plant density were significant on leaf area per plant, leaf area index (at silking), plant height, stem diameter, dry weights of leaf, stem and ear in silking and harvest stages and on fresh and dry yield, dry matter percentage and crude protein percentage at harvest. There was no planting pattern × plant density interaction for these parameters. As row space increased from 60 cm with single planting to 75 cm with single planting, leaf area index and plant height increased, but leaf area per plant, stem diameter, dry weight of leaf, stem and ear, dry matter percentage, dry matter yield and crude protein percentage decreased. Dry matter yield reduced from 24.9 to 18.5 t/ha and crude protein percentage decreased from 6.11 to 5.60 percent. When the plant density increased from 65000 to 110000 plant per hectare, leaf area index, plant height, dry weight of leaf, stem and ear and dry matter yield increased from 19.2 to 23.3 t/ha, whereas leaf area per plant, stem diameter, dry matter percentage and crude protein percentage decreased from 6.30 to 5.25. The best results were obtained with 60 cm row distance with single planting and 110000 plants per hectare.

Keywords: silage corn, plant density, planting pattern, yield

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Authors: Brad Fox

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Between something and nothing, a bit of both, neither/nor, a figment of the imagination, the womb of the universe - questions of what matter is, where it exists and what it means continue to surge up from the bottom of our concepts and theories. This paper looks at divergences and convergences, intimations and mistranslations, in a lineage of thought that begins with Plato’s Timaeus, travels through Arabic Spain and Syria, finally to end up in the language of science. Up to the 13th century, philosophers in Christian France based such inquiries on a questionable and fragmented translation of the Timaeus by Calcidius, with a commentary that conflated the Platonic concept of khora (‘space’ or ‘void’) with Aristotle’s hyle (‘primal matter’ as derived from ‘wood’ as a building material). Both terms were translated by Calcidius as silva. For 700 years, this was the only source for philosophers of matter in the Latin-speaking world. Bernard Silvestris, in his Cosmographia, exemplifies the concepts developed before new translations from Arabic began to pour into the Latin world from such centers as the court of Toledo. Unlike their counterparts across the Pyrenees, 13th century philosophers in Muslim Spain had access to a broad vocabulary for notions of primal matter. The prolific and visionary theologian, philosopher, and poet Muhyiddin Ibn Arabi could draw on the Ikhwan Al-Safa’s 10th Century renderings of Aristotle, which translated the Greek hyle as the everyday Arabic word maddah, still used for building materials today. He also often used the simple transliteration of hyle as hayula, probably taken from Ibn Sina. The prophet’s son-in-law Ali talked of dust in the air, invisible until it is struck by sunlight. Ibn Arabi adopted this dust - haba - as an expression for an original metaphysical substance, nonexistent but susceptible to manifesting forms. Ibn Arabi compares the dust to a phoenix, because we have heard about it and can conceive of it, but it has no existence unto itself and can be described only in similes. Elsewhere he refers to it as quwwa wa salahiyya - pure potentiality and readiness. The final portion of the paper will compare Bernard and Ibn Arabi’s notions of matter to the recent ontology developed by theoretical physicist and philosopher Karen Barad. Looking at Barad’s work with the work of Nils Bohr, it will argue that there is a rich resonance between Ibn Arabi’s paradoxical conceptions of matter and the quantum vacuum fluctuations verified by recent lab experiments. The inseparability of matter and meaning in Barad recall Ibn Arabi’s original response to Ibn Rushd’s question: Does revelation offer the same knowledge as rationality? ‘Yes and No,’ Ibn Arabi said, ‘and between the yes and no spirit is divided from matter and heads are separated from bodies.’ Ibn Arabi’s double affirmation continues to offer insight into our relationship to momentary experience at its most fundamental level.

Keywords: Karen Barad, Muhyiddin Ibn Arabi, primal matter, Bernard Silvestris

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Authors: Sait Ali Uymaz, Gülay Tezel

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This paper presents the comparison results on the performance of the Cuckoo Search (CS) algorithm for constrained optimization problems. For constraint handling, CS algorithm uses penalty method. CS algorithm is tested on thirteen well-known test problems and the results obtained are compared to Particle Swarm Optimization (PSO) algorithm. Mean, best, median and worst values were employed for the analyses of performance.

Keywords: cuckoo search, particle swarm optimization, constrained optimization problems, penalty method

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Authors: Varvara Roubtsova, Mohamed Chekired

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Recent studies on the numerical simulation of geotechnical problems show the importance of considering the soil micro-structure. At this scale, soil is a discrete particle medium where the particles can interact with each other and with water flow under external forces, structure loads or natural events. This paper presents research conducted in a virtual laboratory named SiGran, developed at IREQ (Institut de recherche d’Hydro-Quebec) for the purpose of investigating a broad range of problems encountered in geotechnics. Using Discrete Element Method (DEM), SiGran simulated granular materials directly by applying Newton’s laws to each particle. The water flow was simulated by using Marker and Cell method (MAC) to solve the full form of Navier-Stokes’s equation for non-compressible viscous liquid. In this paper, examples of numerical simulation and their comparisons with real experiments have been selected to show the complexity of geotechnical research at the micro level. These examples describe transient flows into a porous medium, interaction of particles in a viscous flow, compacting of saturated and unsaturated soils and the phenomenon of liquefaction under seismic load. They also provide an opportunity to present SiGran’s capacity to compute the distribution and evolution of energy by type (particle kinetic energy, particle internal elastic energy, energy dissipated by friction or as a result of viscous interaction into flow, and so on). This work also includes the first attempts to apply micro discrete results on a macro continuum level where the Smoothed Particle Hydrodynamics (SPH) method was used to resolve the system of governing equations. The material behavior equation is based on the results of simulations carried out at a micro level. The possibility of combining three methods (DEM, MAC and SPH) is discussed.

Keywords: discrete element method, marker and cell method, numerical simulation, multi-scale simulations, smoothed particle hydrodynamics

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Authors: Ananya Das, Arun Kumar, Gazala Habib, Vivekanandan Perumal

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Regulatory bodies has proposed limits on Particulate Matter (PM) concentration in air; however, it does not explicitly indicate the incorporation of effects of toxicities of constituents of PM in developing regulatory limits. This study aimed to provide a structured approach to incorporate toxic effects of components in developing regulatory limits on PM. A four-step human health risk assessment framework consists of - (1) hazard identification (parameters: PM and its constituents and their associated toxic effects on health), (2) exposure assessment (parameters: concentrations of PM and constituents, information on size and shape of PM; fate and transport of PM and constituents in respiratory system), (3) dose-response assessment (parameters: reference dose or target toxicity dose of PM and its constituents), and (4) risk estimation (metric: hazard quotient and/or lifetime incremental risk of cancer as applicable). Then parameters required at every step were obtained from literature. Using this information, an attempt has been made to determine limits on PM using component-specific information. An example calculation was conducted for exposures of PM_2.5 and its metal constituents from Indian ambient environment to determine limit on PM values. Identified data gaps were: (1) concentrations of PM and its constituents and their relationship with sampling regions, (2) relationship of toxicity of PM with its components.

Keywords: air, component-specific toxicity, human health risks, particulate matter

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Authors: Miroslava Zelinkova, Marcela Ondova

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Fly ash (FA) thanks to the significant presence of SiO2 and Al2O3 as the main components is a potential raw material for geopolymers production. Mechanical activation is a method for improving FA reactivity and also the porosity of final mixture; those parameters can be analysed through sorption properties. They have direct impact on the durability of fly ash based geopolymer mortars. In the paper, effect of FA fineness on sorption properties of geopolymers based on sodium silicate, as well as relationship between fly ash fineness and apparent density, compressive and flexural strength of geopolymers are presented. The best results in the evaluated area reached the sample H1, which contents the highest portion of particle under 20μm (100% of GFA). The interdependence of individual tested properties was confirmed for geopolymer mixtures corresponding to those in the cement based mixtures: higher is portion of fine particles < 20μm, higher is strength, density and lower are sorption properties. The compressive strength as well as sorption parameters of the geopolymer can be reasonably controlled by grinding process and also ensured by the higher share of fine particle (to 20μm) in total mass of the material.

Keywords: alkali activation, geopolymers, fly ash, particle fineness

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Authors: Esam I. Jassim

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The main aim of this paper is to demonstrate the prediction of the model capability of predicting the nucleation process, the growth rate, and the deposition potential of second phase particles in gas flowlines. The primary objective of the research is to predict the risk hazards involved in the marine transportation of compressed natural gas. However, the proposed model can be equally used for other applications including production and transportation of natural gas in any high-pressure flow-line. The proposed model employs the following three main components to approach the problem: computational fluid dynamics (CFD) technique is used to configure the flow field; the nucleation model is developed and incorporated in the simulation to predict the incipient hydrate particles size and growth rate; and the deposition of the gas/particle flow is proposed using the concept of the particle deposition velocity. These components are integrated in a comprehended model to locate the hydrate deposition in natural gas flowlines. The present research is prepared to foresee the deposition location of solid particles that could occur in a real application in Compressed Natural Gas loading and offloading. A pipeline with 120 m length and different sizes carried a natural gas is taken in the study. The location of particle deposition formed as a result of restriction is determined based on the procedure mentioned earlier and the effect of water content and downstream pressure is studied. The critical flow speed that prevents such particle to accumulate in the certain pipe length is also addressed.

Keywords: hydrate deposition, compressed natural gas, marine transportation, oceanography

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Authors: G. Ravindranath, S. Savitha

Abstract:

This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

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Authors: Jayotpaul Chaudhuri, Lutz Goedeke, Torsten Hallenga, Peter Ehrhard

Abstract:

Purification of gases from aerosols or airborne particles via filters is widely applied in the industry and in our daily lives. This separation especially in the micron and submicron size range is a necessary step to protect the environment and human health. Fibrous filters are often employed due to their low cost and high efficiency. For designing any filter the two most important performance parameters are capture efficiency and pressure drop. Since the capture efficiency is directly proportional to the pressure drop which leads to higher operating costs, a detailed investigation of the separation mechanism is required to optimize the filter designing, i.e., to have a high capture efficiency with a lower pressure drop. Therefore a two-dimensional flow simulation around a single fiber using Ansys CFX and Matlab is used to get insight into the separation process. Instead of simulating a solid fiber, the present Ansys CFX model uses a fictitious domain approach for the fiber by implementing a momentum loss model. This approach has been chosen to avoid creating a new mesh for different fiber sizes, thereby saving time and effort for re-meshing. In a first step, only the flow of the continuous fluid around the fiber is simulated in Ansys CFX and the flow field data is extracted and imported into Matlab and the particle trajectory is calculated in a Matlab routine. This calculation is a Lagrangian, one way coupled approach for particles with all relevant forces acting on it. The key parameters for the simulation in both Ansys CFX and Matlab are the porosity ε, the diameter ratio of particle and fiber D, the fluid Reynolds number Re, the Reynolds particle number Rep, the Stokes number St, the Froude number Fr and the density ratio of fluid and particle ρf/ρp. The simulation results were then compared to the single fiber theory from the literature.

Keywords: BBO-equation, capture efficiency, CFX, Matlab, fibrous filter, particle trajectory

Procedia PDF Downloads 181

Authors: Phawichsak Prapassornpitaya, Wanida Jinsart

Abstract:

Daily monitoring PM₁₀ and PM₂.₅ data from 2007 to 2017 were analyzed to provide baseline data for prediction of the air pollution in Bangkok in the period of 2018 -2020. Two statistical models, Autoregressive Integrated Moving Average model (ARIMA) were used to evaluate the trends of pollutions. The prediction concentrations were tested by root means square error (RMSE) and index of agreement (IOA). This evaluation of the traffic PM₂.₅ and PM₁₀ were studied in association with the regulatory control and emission standard changes. The emission factors of particulate matter from diesel vehicles were decreased when applied higher number of euro standard. The trends of ambient air pollutions were expected to decrease. However, the Bangkok smog episode in February 2018 with temperature inversion caused high concentration of PM₂.₅ in the air environment of Bangkok. The impact of traffic pollutants was depended upon the emission sources, temperature variations, and metrological conditions.

Keywords: fine particulate matter, ARIMA, RMSE, Bangkok

Procedia PDF Downloads 247

Authors: Seungyeong Choi, Namkyu Lee, Dong Il Shim, Young Mun Lee, Yong-Ki Park, Hyung Hee Cho

Abstract:

Effect of the cross-sectional geometry on heat transfer and particle motion of circulating fluidized bed riser for CO₂ capture was investigated. Numerical simulation using Eulerian-eulerian method with kinetic theory of granular flow was adopted to analyze gas-solid flow consisting in circulating fluidized bed riser. Circular, square, and rectangular cross-sectional geometry cases of the same area were carried out. Rectangular cross-sectional geometries were analyzed having aspect ratios of 1: 2, 1: 4, 1: 8, and 1:16. The cross-sectional geometry significantly influenced the particle motion and heat transfer. The downward flow pattern of solid particles near the wall was changed. The gas-solid mixing degree of the riser with the rectangular cross section of the high aspect ratio was the lowest. There were differences in bed-to-wall heat transfer coefficient according to rectangular geometry with different aspect ratios.

Keywords: bed geometry, computational fluid dynamics, circulating fluidized bed riser, heat transfer

Procedia PDF Downloads 234