Search results for: discrete particle modelling

Authors: Johannes Mertl

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Our surrounding air contains various particles. Besides typical representatives of inorganic dust, such as soot and ash, also particles originating from animals, microorganisms or plants are floating through the air, so-called bioaerosols. The group of bioaerosols consists of a broad spectrum of particles of different size, including fungi, bacteria, viruses, spores, or tree, flower and grass pollen that are of high relevance for allergy sufferers. In dependence of the environmental climate and the actual season, these allergenic particles can be found in enormous numbers in the air and are inhaled by humans via the respiration tract, with a potential for inflammatory diseases of the airways, such as asthma or allergic rhinitis. As a consequence air filter systems of ventilation and air conditioning devices are required to meet very high standards to prevent, or at least lower the number of allergens and airborne germs entering the indoor air. Still, filter systems are merely classified for their separation rates using well-defined mineral test dust, while no appropriate sufficiently standardized test methods for bioaerosols exist. However, determined separation rates for mineral test particles of a certain size cannot simply be transferred to bioaerosols, as separation efficiency of particularly fine and respirable particles (< 10 microns) is dependent not only on their shape and particle diameter, but also defined by their density and physicochemical properties. For this reason, the OFI developed a test method, which directly enables a testing of filters and filter media for their separation rates on bioaerosols, as well as a classification of filters. Besides allergens from an intact or fractured tree or grass pollen, allergenic proteins bound to particulates, as well as allergenic fungal spores (e.g. Cladosporium cladosporioides), or bacteria can be used to classify filters regarding their separation rates. Allergens passing through the filter can then be detected by highly sensitive immunological assays (ELISA) or in the case of fungal spores by microbiological methods, which allow for the detection of even one single spore passing the filter. The test procedure, which is carried out in laboratory scale, was furthermore validated regarding its sufficiency to cover real life situations by upscaling using air conditioning devices showing great conformity in terms of separation rates. Additionally, a clinical study with allergy sufferers was performed to verify analytical results. Several different air conditioning filters from the car industry have been tested, showing significant differences in their separation rates.

Keywords: airborne germs, allergens, classification of filters, fine dust

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Authors: Fatima Zahra Mahjoubi, Abderrahim Khalidi, Mohamed Abdennouri, Omar Cherkaoui, Noureddine Barka

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Industrial effluents are one of the major causes of environmental pollution, especially effluents discharged from various dyestuff manufactures, plastic, and paper making industries. These effluents can give rise to certain hazards and environmental problems for their highly colored suspended organic solid. Dye effluents are not only aesthetic pollutants, but coloration of water by the dyes may affect photochemical activities in aquatic systems by reducing light penetration. It has been also reported that several commonly used dyes are carcinogenic and mutagenic for aquatic organisms. Therefore, removing dyes from effluents is of significant importance. Many adsorbent materials have been prepared in the removal of dyes from wastewater, including anionic clay or layered double hydroxyde. The zinc/aluminium (Zn-AlNO₃), magnesium/aluminium (Mg-AlNO₃) and nickel/aluminium (Ni-AlNO₃) layered double hydroxides (LDHs) were successfully synthesized via coprecipitation method. Samples were characterized by XRD, FTIR, TGA/DTA, TEM and pHPZC analysis. XRD patterns showed a basal spacing increase in the order of Zn-AlNO₃ (8.85Å)> Mg-AlNO₃ (7.95Å)> Ni-AlNO₃ (7.82Å). FTIR spectrum confirmed the presence of nitrate anions in the LDHs interlayer. The TEM images indicated that the Zn-AlNO3 presents circular to shaped particles with an average particle size of approximately 30 to 40 nm. Small plates assigned to sheets with hexagonal form were observed in the case of Mg-AlNO₃. Ni-AlNO₃ display nanostructured sphere in diameter between 5 and 10 nm. The LDHs were used as adsorbents for the removal of methyl orange (MO), as a model dye and for the treatment of an effluent generated by a textile factory. Adsorption experiments for MO were carried out as function of solution pH, contact time and initial dye concentration. Maximum adsorption was occurred at acidic solution pH. Kinetic data were tested using pseudo-first-order and pseudo-second-order kinetic models. The best fit was obtained with the pseudo-second-order kinetic model. Equilibrium data were correlated to Langmuir and Freundlich isotherm models. The best conditions for color and COD removal from textile effluent sample were obtained at lower values of pH. Total color removal was obtained with Mg-AlNO₃ and Ni-AlNO₃ LDHs. Reduction of COD to limits authorized by Moroccan standards was obtained with 0.5g/l LDHs dose.

Keywords: chemical oxygen demand, color removal, layered double hydroxides, textile wastewater treatment

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Authors: Protik Basu, Indranil Ghosh, Pranab K. Dan

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Lean management is an integrated socio-technical system to bring about a competitive state in an organization. The purpose of this paper is to explore and integrate the role of customers and suppliers with the internal practices of the Indian manufacturing industries towards successful implementation of lean manufacturing (LM). An extensive literature survey is carried out. An attempt is made to build an exhaustive list of all the input manifests related to customers, suppliers and internal practices necessary for LM implementation, coupled with a similar exhaustive list of the benefits accrued from its successful implementation. A structural model is thus conceptualized, which is empirically validated based on the data from the Indian manufacturing sector. With the current impetus on developing the industrial sector, the Government of India recently introduced the Lean Manufacturing Competitiveness Scheme that aims to increase competitiveness with the help of lean concepts. There is a huge scope to enrich the Indian industries with the lean benefits, the implementation status being quite low. Hardly any survey-based empirical study in India has been found to integrate customers and suppliers with the internal processes towards successful LM implementation. This empirical research is thus carried out in the Indian manufacturing industries. The basic steps of the research methodology followed in this research are the identification of input and output manifest variables and latent constructs, model proposition and hypotheses development, development of survey instrument, sampling and data collection and model validation (exploratory factor analysis, confirmatory factor analysis, and structural equation modeling). The analysis reveals six key input constructs and three output constructs, indicating that these constructs should act in unison to maximize the benefits of implementing lean. The structural model presented in this paper may be treated as a guide to integrating customers and suppliers with internal practices to successfully implement lean. Integrating customers and suppliers with internal practices into a unified, coherent manufacturing system will lead to an optimum utilization of resources. This work is one of the very first researches to have a survey-based empirical analysis of the role of customers, suppliers and internal practices of the Indian manufacturing sector towards an effective lean implementation.

Keywords: customer management, internal manufacturing practices, lean benefits, lean implementation, lean manufacturing, structural model, supplier management

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Authors: Abraham Castellanos, Christophe Durville, Sophie Echenim

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In this article, a portfolio optimization problem is performed in a Solvency II context: it illustrates how advanced optimization techniques can help to tackle complex operational pain points around the monitoring, control, and stability of Solvency Capital Requirement (SCR). The market SCR of a portfolio is calculated as a combination of SCR sub-modules. These sub-modules are the results of stress-tests on interest rate, equity, property, credit and FX factors, as well as concentration on counter-parties. The market SCR is non convex and non differentiable, which does not make it a natural optimization criteria candidate. In the SCR formulation, correlations between sub-modules are fixed, whereas risk-driven portfolio allocation is usually driven by the dynamics of the actual correlations. Implementing a portfolio construction approach that is efficient on both a regulatory and economic standpoint is not straightforward. Moreover, the challenge for insurance portfolio managers is not only to achieve a minimal SCR to reduce non-invested capital but also to ensure stability of the SCR. Some optimizations have already been performed in the literature, simplifying the standard formula into a quadratic function. But to our knowledge, it is the first time that the standard formula of the market SCR is used in an optimization problem. Two solvers are combined: a bundle algorithm for convex non- differentiable problems, and a BFGS (Broyden-Fletcher-Goldfarb- Shanno)-SQP (Sequential Quadratic Programming) algorithm, to cope with non-convex cases. A market SCR minimization is then performed with historical data. This approach results in significant reduction of the capital requirement, compared to a classical Markowitz approach based on the historical volatility. A comparative analysis of different optimization models (equi-risk-contribution portfolio, minimizing volatility portfolio and minimizing value-at-risk portfolio) is performed and the impact of these strategies on risk measures including market SCR and its sub-modules is evaluated. A lack of diversification of market SCR is observed, specially for equities. This was expected since the market SCR strongly penalizes this type of financial instrument. It was shown that this direct effect of the regulation can be attenuated by implementing constraints in the optimization process or minimizing the market SCR together with the historical volatility, proving the interest of having a portfolio construction approach that can incorporate such features. The present results are further explained by the Market SCR modelling.

Keywords: financial risk, numerical optimization, portfolio management, solvency capital requirement

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Authors: Subhankar Karmakar, Madhan Kumar Vasudevan, Manivannan Muniyandi

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Thermal Grill Illusion (TGI) elicits a strong and often painful sensation of burn when interlacing warm and cold stimuli that are individually non-painful, excites thermoreceptors beneath the skin. Among several theories of TGI, the “disinhibition” theory is the most widely accepted in the literature. According to this theory, TGI is the result of the disinhibition or unmasking of the pain-sensitive HPC (Heat-Pinch-Cold) nerve fibers due to the inhibition of cold-sensitive nerve fibers that are responsible for masking HPC nerve fibers. Although researchers focused on understanding TGI throughexperiments and models, none of them investigated the prediction of TGI pain intensity through a computational model. Furthermore, the comparison of psychophysically perceived TGI intensity with neurophysiological models has not yet been studied. The prediction of pain intensity through a computational model of TGI can help inoptimizing thermal displays and understanding pathological conditions related to temperature perception. The current studyfocuses on developing a computational model to predict the intensity of TGI pain and experimentally observe the perceived TGI pain. The computational model is developed based on the disinhibition theory and by utilizing the existing popular models of warm and cold receptors in the skin. The model aims to predict the neuronal activity of the HPC nerve fibers. With a temperature-controlled thermal grill setup, fifteen participants (ten males and five females) were presented with five temperature differences between warm and cold grills (each repeated three times). All the participants rated the perceived TGI pain sensation on a scale of one to ten. For the range of temperature differences, the experimentally observed perceived intensity of TGI is compared with the neuronal activity of pain-sensitive HPC nerve fibers. The simulation results show a monotonically increasing relationship between the temperature differences and the neuronal activity of the HPC nerve fibers. Moreover, a similar monotonically increasing relationship is experimentally observed between temperature differences and the perceived TGI intensity. This shows the potential comparison of TGI pain intensity observed through the experimental study with the neuronal activity predicted through the model. The proposed model intends to bridge the theoretical understanding of the TGI and the experimental results obtained through psychophysics. Further studies in pain perception are needed to develop a more accurate version of the current model.

Keywords: thermal grill Illusion, computational modelling, simulation, psychophysics, haptics

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Authors: Tomilola J. Ajayi

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A category of nanovalves system containing the α-cyclodextrin (α-CD) ring on a stalk tethered to the pores of mesoporous silica nanoparticles (MSN) is theoretically and computationally modelled. This functions to control opening and blocking of the MSN pores for efficient targeted drug release system. Modeling of the nanovalves is based on the interaction between α-CD and the stalk (p-anisidine) in relation to pH variation. Conformational analysis was carried out prior to the formation of the inclusion complex, to find the global minimum of both neutral and protonated stalk. B3LYP/6-311G**(d, p) basis set was employed to attain all theoretically possible conformers of the stalk. Six conformers were taken into considerations, and the dihedral angle (θ) around the reference atom (N17) of the p-anisidine stalk was scanned from 0° to 360° at 5° intervals. The most stable conformer was obtained at a dihedral angle of 85.3° and was fully optimized at B3LYP/6-311G**(d, p) level of theory. The most stable conformer obtained from conformational analysis was used as the starting structure to create the inclusion complexes. 9 complexes were formed by moving the neutral guest into the α-CD cavity along the Z-axis in 1 Å stepwise while keeping the distance between dummy atom and OMe oxygen atom on the stalk restricted. The dummy atom and the carbon atoms on α-CD structure were equally restricted for orientation A (see Scheme 1). The generated structures at each step were optimized with B3LYP/6-311G**(d, p) methods to determine their energy minima. Protonation of the nitrogen atom on the stalk occurs at acidic pH, leading to unsatisfactory host-guest interaction in the nanogate; hence there is dethreading. High required interaction energy and conformational change are theoretically established to drive the release of α-CD at a certain pH. The release was found to occur between pH 5-7 which agreed with reported experimental results. In this study, we applied the theoretical model for the prediction of the experimentally observed pH-responsive nanovalves which enables blocking, and opening of mesoporous silica nanoparticles pores for targeted drug release system. Our results show that two major factors are responsible for the cargo release at acidic pH. The higher interaction energy needed for the complex/nanovalve formation to exist after protonation as well as conformational change upon protonation are driving the release due to slight pH change from 5 to 7.

Keywords: nanovalves, nanogate, mesoporous silica nanoparticles, cargo

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Authors: Jyh Sheen, Yong-Lin Wang

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This research dedicates to find a different measurement procedure of microwave dielectric properties of ceramic materials with high dielectric constants. For the composite of ceramic dispersed in the polymer matrix, the dielectric constants of the composites with different concentrations can be obtained by various mixture equations. The other development of mixture rule is to calculate the permittivity of ceramic from measurements on composite. To do this, the analysis method and theoretical accuracy on six basic mixture laws derived from three basic particle shapes of ceramic fillers have been reported for dielectric constants of ceramic less than 40 at microwave frequency. Similar researches have been done for other well-known mixture rules. They have shown that both the physical curve matching with experimental results and low potential theory error are important to promote the calculation accuracy. Recently, a modified of mixture equation for high dielectric constant ceramics at microwave frequency has also been presented for strontium titanate (SrTiO3) which was selected from five more well known mixing rules and has shown a good accuracy for high dielectric constant measurements. However, it is still not clear the accuracy of this modified equation for other high dielectric constant materials. Therefore, the five more well known mixing rules are selected again to understand their application to other high dielectric constant ceramics. The other high dielectric constant ceramic, TiO2 with dielectric constant 100, was then chosen for this research. Their theoretical error equations are derived. In addition to the theoretical research, experimental measurements are always required. Titanium dioxide is an interesting ceramic for microwave applications. In this research, its powder is adopted as the filler material and polyethylene powder is like the matrix material. The dielectric constants of those ceramic-polyethylene composites with various compositions were measured at 10 GHz. The theoretical curves of the five published mixture equations are shown together with the measured results to understand the curve matching condition of each rule. Finally, based on the experimental observation and theoretical analysis, one of the five rules was selected and modified to a new powder mixture equation. This modified rule has show very good curve matching with the measurement data and low theoretical error. We can then calculate the dielectric constant of pure filler medium (titanium dioxide) by those mixing equations from the measured dielectric constants of composites. The accuracy on the estimating dielectric constant of pure ceramic by various mixture rules will be compared. This modified mixture rule has also shown good measurement accuracy on the dielectric constant of titanium dioxide ceramic. This study can be applied to the microwave dielectric properties measurements of other high dielectric constant ceramic materials in the future.

Keywords: microwave measurement, dielectric constant, mixture rules, composites

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Authors: É. Vincze

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Demand on plant oils has increased to an enormous extent that is due to the change of human nutrition habits on the one hand, while on the other hand to the increase of raw material demand of some industrial sectors, just as to the increase of biofuel production. Besides the determining importance of sunflower in Hungary the production area, just as in part the average yield amount of rapeseed has increased among the produced oil crops. The variety/hybrid palette has changed significantly during the past decade. The available varieties’/hybrids’ palette has been extended to a significant extent. It is agreed that rapeseed production demands professionalism and local experience. Technological elements are successive; high yield amounts cannot be produced without system-based approach. The aim of the present work was to execute the complex study of one of the most critical production technology element of rapeseed production, that was sowing technology. Several sowing technology elements are studied in this research project that are the following: biological basis (the hybrid Arkaso is studied in this regard), sowing time (sowing time treatments were set so that they represent the wide period used in industrial practice: early, optimal and late sowing time) plant density (in this regard reaction of rare, optimal and too dense populations) were modelled. The multifactorial experimental system enables the single and complex evaluation of rapeseed sowing technology elements, just as their modelling using experimental result data. Yield quality and quantity have been determined as well in the present experiment, just as the interactions between these factors. The experiment was set up in four replications at the Látókép Plant Production Research Site of the University of Debrecen. Two different sowing times were sown in the first experimental year (2014), while three in the second (2015). Three different plant densities were set in both years: 200, 350 and 500 thousand plants ha-1. Uniform nutrient supply and a row spacing of 45 cm were applied. Winter wheat was used as pre-crop. Plant physiological measurements were executed in the populations of the Arkaso rapeseed hybrid that were: relative chlorophyll content analysis (SPAD) and leaf area index (LAI) measurement. Relative chlorophyll content (SPAD) and leaf area index (LAI) were monitored in 7 different measurement times.

Keywords: inner quality, plant density, rapeseed, sowing time

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Authors: Thayalan Nall, Andreas Putra

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A major offshore reclamation work is currently underway in Southeast Asia for a container terminal. The total extent of the reclamation extent is 2600m x 800m and the seabed level is around -5mRL below mean sea level. Subsoil profile below seabed comprises soft marine clays of thickness varying from 8m to 15m. To contain the dredging spoil within the reclamation area, perimeter bunds have been constructed to +2.5mRL. They include breakwaters of trapezoidal geometry, made of boulder size rock along the northern, eastern and western perimeters, with a sand bund along the southern perimeter. Breakwaters were constructed on a composite bamboo pile and raft foundation system. Bamboo clusters 8m long, with 7 individual Bamboos bundled together as one, have been installed within the footprint of the breakwater below seabed in soft marine clay. To facilitate drainage two prefabricated vertical drains (PVD) have been attached to each cluster. Once the cluster piles were installed, a bamboo raft was placed as a load transfer platform. Rafts were made up of 5 layers of bamboo mattress, and in each layer bamboos were spaced at 200mm centres. The rafts wouldn’t sink under their own weight, and hence, they were sunk by loading quarry run rock onto them. Bamboo is a building material available in abundance in Indonesia and obtained at a relatively low cost. They are commonly used as semi-rigid inclusions to improve compressibility and stability of soft soils. Although bamboo is widely used in soft soil engineering design, no local design guides are available and the designs are carried out based on local experience. In June 2015, when the 1st load of sand was pumped by a dredging vessel next to the breakwater, a 150m long section of the breakwater underwent failure and displaced the breakwater between 1.2m to 4.0m. The cause of the failure was investigated to implement remedial measures to reduce the risk of further failures. Analyses using both limit equilibrium approach and finite element modelling revealed two plausible modes of breakwater failure. This paper outlines: 1) Developed Geology and the ground model, 2) The techniques used for the installation of bamboo piles, 3) Details of the analyses including modes and mechanism of failure and 4) Design changes incorporated to reduce the risk of failure.

Keywords: bamboo piles, ground improvement, reclamation, breakwater failure

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Authors: Ramon Omar Rosales-Espinoza

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Pile-to-pile mechanical connections are used if the depth of the soil layers with sufficient bearing strength exceeds the original (“leading”) pile length, with the additional pile segment being termed “extension” pile. Mechanical connectors permit a safe transmission of forces from leading to extension pile while meeting strength and serviceability requirements. Common types of connectors consist of an assembly of sleeve-type external couplers, bolts, pins, and other mechanical interlock devices that ensure the transmission of compressive, tensile, torsional and bending stresses between leading and extension pile segments. While welded connections allow for a relatively simple structural design, mechanical connections are advantageous over welded connections because they lead to shorter installation times and significant cost reductions since specialized workmanship and inspection activities are not required. However, common practices followed to design mechanical connectors neglect important aspects of the assembly response, such as stress concentration around pin/bolt holes, torsional stresses from the installation process, and interaction between the forces at the installation (torsion), service (compression/tension-bending), and removal stages (torsion). This translates into potentially unsatisfactory designs in terms of the ultimate and service limit states, exhibiting either reduced strength or excessive deformations. In this study, the experimental response under compressive forces of a type of mechanical connector is presented, in terms of strength, deformation and failure modes. The tests revealed that the type of connector used can safely transmit forces from pile to pile. Using the results from the compressive tests, an analysis model was developed using the finite element (FE) method to study the interaction of forces under installation and service stages of a typical mechanical connector. The response of the analysis model is used to identify potential areas for design optimization, including size, gap between leading and extension piles, number of pin/bolts, hole sizes, and material properties. The results show the design of mechanical connectors should take into account the interaction of forces present at every stage of their life cycle, and that the torsional stresses occurring during installation are critical for the safety of the assembly.

Keywords: piles, FEA, steel, mechanical connector

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Authors: Marcin Szlachetka, Rafal Sochaczewski, Lukasz Grabowski

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This paper presents the results of the load simulations of main bearings in a two-stroke Diesel engine. A model of an engine lubrication system with connections of its main lubrication nodes, i.e., a connection of its main bearings in the engine block with the crankshaft, a connection of its crankpins with its connecting rod and a connection of its pin and its piston has been created for our calculations performed using the AVL EXCITE Designer. The analysis covers the loads given as a pressure distribution in a hydrodynamic oil film, a temperature distribution on the main bush surfaces for the specified radial clearance values as well as the impact of the force of gas on the minimum oil film thickness in the main bearings depending on crankshaft rotational speeds and temperatures of oil in the bearings. One of the main goals of the research has been to determine whether the minimum thickness of the oil film at which fluid friction occurs can be achieved for each value of crankshaft speed. Our model calculates different oil film parameters, i.e., its thickness, a pressure distribution there, the change in oil temperature. Additional enables an analysis of an oil temperature distribution on the surfaces of the bearing seats. It allows verifying the selected clearances in the bearings of the main engine under normal operation conditions and extremal ones that show a significant increase in temperature above the limit value. The research has been conducted for several engine crankshaft speeds ranging from 1000 rpm to 4000 rpm. The oil pressure in the bearings has ranged 2-5 bar according to engine speeds and the oil temperature has ranged 90-120 °C. The main bearing clearance has been adopted for the calculation and analysis as 0.025 mm. The oil classified as SAE 5W-30 has been used for the simulations. The paper discusses the selected research results referring to several specific operating points and different temperatures of the lubricating oil in the bearings. The received research results show that for the investigated main bearing bushes of the shaft, the results fall within the ranges of the limit values despite the increase in the oil temperature of the bearings reaching 120˚C. The fact that the bearings are loaded with the maximum pressure makes no excessive temperature rise on the bush surfaces. The oil temperature increases by 17˚C, reaching 137˚C at a speed of 4000 rpm. The minimum film thickness at which fluid friction occurs has been achieved for each of the operating points at each of the engine crankshaft speeds. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A.’ and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: diesel engine, main bearings, opposing pistons, two-stroke

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Authors: E. G. Karvelas, C. Liosis, A. Theodorakakos, T. E. Karakasidis

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Magnetic navigation of the drug inside the human vessels is a very important concept since the drug is delivered to the desired area. Consequently, the quantity of the drug required to reach therapeutic levels is being reduced while the drug concentration at targeted sites is increased. Magnetic navigation of drug agents can be achieved with the use of magnetic nanoparticles where anti-tumor agents are loaded on the surface of the nanoparticles. The magnetic field that is required to navigate the particles inside the human arteries is produced by a magnetic resonance imaging (MRI) device. The main factors which influence the efficiency of the usage of magnetic nanoparticles for biomedical applications in magnetic driving are the size and the magnetization of the biocompatible nanoparticles. In this study, a computational platform for the simulation of the optimal gradient magnetic fields for the navigation of magnetic nanoparticles inside a carotid artery is presented. For the propulsion model of the particles, seven major forces are considered, i.e., the magnetic force from MRIs main magnet static field as well as the magnetic field gradient force from the special propulsion gradient coils. The static field is responsible for the aggregation of nanoparticles, while the magnetic gradient contributes to the navigation of the agglomerates that are formed. Moreover, the contact forces among the aggregated nanoparticles and the wall and the Stokes drag force for each particle are considered, while only spherical particles are used in this study. In addition, gravitational forces due to gravity and the force due to buoyancy are included. Finally, Van der Walls force and Brownian motion are taken into account in the simulation. The OpenFoam platform is used for the calculation of the flow field and the uncoupled equations of particles' motion. To verify the optimal gradient magnetic fields, a covariance matrix adaptation evolution strategy (CMAES) is used in order to navigate the particles into the desired area. A desired trajectory is inserted into the computational geometry, which the particles are going to be navigated in. Initially, the CMAES optimization strategy provides the OpenFOAM program with random values of the gradient magnetic field. At the end of each simulation, the computational platform evaluates the distance between the particles and the desired trajectory. The present model can simulate the motion of particles when they are navigated by the magnetic field that is produced by the MRI device. Under the influence of fluid flow, the model investigates the effect of different gradient magnetic fields in order to minimize the distance of particles from the desired trajectory. In addition, the platform can navigate the particles into the desired trajectory with an efficiency between 80-90%. On the other hand, a small number of particles are stuck to the walls and remains there for the rest of the simulation.

Keywords: artery, drug, nanoparticles, navigation

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Authors: Sahar El Kasmi, Ayoub Aziz, Saadia Lharti, Mohammed El Janati, Boubker Boukili, Nacer El Motawakil, Mayom Chol Luka Awan

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Two types of geomaterials (Red Triassic clay from the Maaziz region and Yellow Pliocene clay from the Akrach region) were used to create different mixtures for the fabrication of ceramic bricks. This study investigated the influence of the Pliocene clay on the overall composition and mechanical properties of the Triassic clay. The red Triassic clay, sourced from Maaziz, underwent various mechanical processes and treatments to facilitate its transformation into ceramic bricks for construction. The triassic clay was subjected to a drying chamber and a heating chamber at 100°C to remove moisture. Subsequently, the dried clay samples were processed using a Planetary Babs ll Mill to reduce particle size and improve homogeneity. The resulting clay material was sieved, and the fine particles below 100 mm were collected for further analysis. In parallel, the Miocene marl obtained from the Akrach region was fragmented into finer particles and subjected to similar drying, grinding, and sieving procedures as the triassic clay. The two clay samples are then amalgamated and homogenized in different proportions. Precise measurements were taken using a weighing balance, and mixtures of 90%, 80%, and 70% Triassic clay with 10%, 20%, and 30% yellow clay were prepared, respectively. To evaluate the impact of Pliocene marl on the composition, the prepared clay mixtures were spread evenly and treated with a water modifier to enhance plasticity. The clay was then molded using a brick-making machine, and the initial manipulation process was observed. Additional batches were prepared with incremental amounts of Pliocene marl to further investigate its effect on the fracture behavior of the clay, specifically their resistance. The molded clay bricks were subjected to compression tests to measure their strength and resistance to deformation. Additional tests, such as water absorption tests, were also conducted to assess the overall performance of the ceramic bricks fabricated from the different clay mixtures. The results were analyzed to determine the influence of the Pliocene marl on the strength and durability of the Triassic clay bricks. The results indicated that the incorporation of Pliocene clay reduced the fracture of the triassic clay, with a noticeable reduction observed at 10% addition. No fractures were observed when 20% and 30% of yellow clay are added. These findings suggested that yellow clay can enhance the mechanical properties and structural integrity of red clay-based products.

Keywords: triassic clay, pliocene clay, mineralogical composition, geo-materials, ceramics, akach region, maaziz region, morocco.

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Authors: Piotr J. Skusiewicz, Johnathan Saul, Ijhar Rusli, Svetlana Aleksandrova, Stephen. F. Benjamin, Miroslaw Gall, Steve Pierson, Carol A. Roberts

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The application of turbocharging in automotive engines leads to swirling flow entering the catalyst. The behaviour of this type of flow within the catalyst has yet to be adequately documented. This work discusses the effect of swirling flow on the flow distribution in automotive exhaust catalysts. Compressed air supplied to a moving-block swirl generator allowed for swirling flow with variable intensities to be generated. Swirl intensities were measured at the swirl generator outlet using single-sensor hot-wire probes. The swirling flow was fed into diffusers with total angles of 10°, 30° and 180°. Downstream of the diffusers, a wash-coated diesel oxidation catalyst (DOC) of length 143.8 mm, diameter 76.2 mm and nominal cell density of 400 cpsi was fitted. Velocity profiles were measured at the outlet sleeve about 30 mm downstream of the monolith outlet using single-sensor hot-wire probes. Wall static pressure was recorded using a multi-tube manometer connected to pressure taps positioned along the diffuser walls. The results show that as swirl is increased, more of the flow is directed towards the diffuser walls. The velocity decreases around the centre-line and maximum velocities are observed close to the outer radius of the monolith for all flow rates. At the maximum swirl intensity, reversed flow was recorded near the centre of the monolith. Wall static pressure measurements in the 180° diffuser indicated no pressure recovery as the flow enters the diffuser. This is indicative of flow separation at the inlet to the diffuser. To gain insight into the flow structure, CFD simulations have been performed for the 180° diffuser for a flow rate of 63 g/s. The geometry of the model consists of the complete assembly from the upstream swirl generator to the outlet sleeve. Modelling of the flow in the monolith was achieved using the porous medium approach, where the monolith with parallel flow channels is modelled as a porous medium that resists the flow. A reasonably good agreement was achieved between the experimental and CFD results downstream of the monolith. The CFD simulations allowed visualisation of the separation zones and central toroidal recirculation zones that occur within the expansion region at certain swirl intensities which are highlighted.

Keywords: catalyst, computational fluid dynamics, diffuser, hot-wire anemometry, swirling flow

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Authors: Bryan Clark B. Hernandez, Eugene C. Herrera, Kazuo Nadaoka

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Mangrove forests thriving in intertidal zones in tropical and subtropical regions of the world offer a range of ecosystem services including carbon storage and sequestration. They can regulate the detrimental effects of climate change due to carbon releases two to four times greater than that of mature tropical rainforests. Moreover, they are effective natural defenses against storm surges and tsunamis. However, their proliferation depends significantly on the prevailing hydroperiod at the coast. In the Philippines, these coastal ecosystems have been severely threatened with a 50% decline in areal extent observed from 1918 to 2010. The highest decline occurred in 1950 - 1972 when national policies encouraged the development of fisheries and aquaculture. With the intensive land use conversion upstream, changes in the freshwater-saltwater envelope at the coast may considerably impact mangrove growth conditions. This study investigates a developing urban watershed in Kalibo, Aklan province with a 220-hectare mangrove forest replanted for over 30 years from coastal mudflats. Since then, the mangrove forest was sustainably conserved and declared as protected areas. Hybrid land cover classification technique was used to classify Landsat images for years, 1990, 2010, and 2017. Digital elevation model utilized was Interferometric Synthetic Aperture Radar (IFSAR) with a 5-meter resolution to delineate the watersheds. Using numerical modelling techniques, the hydrologic and hydraulic analysis of the influence of land cover change to flow and sediment dynamics was simulated. While significant land cover change occurred upland, thereby increasing runoff and sediment loads, the mangrove forests abundance adjacent to the coasts for the urban watershed, was somehow sustained. However, significant alteration of the coastline was observed in Kalibo through the years, probably due to the massive land-use conversion upstream and significant replanting of mangroves downstream. Understanding the hydrologic-hydraulic response of these watersheds to change land cover is essential to helping local government and stakeholders facilitate better management of these mangrove ecosystems.

Keywords: coastal mangroves, hydrologic model, land cover change, Philippines

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Authors: Yuguang Gao, Mingtao Deng

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The integration of independently operating hospitals into a unified healthcare service system has become a strategic imperative in the pursuit of hospitals’ high-quality development. Central to the concept of group governance over such transformation, exemplified by a collaborative medical alliance, is the delineation of shared value, vision, and goals. Given the inherent disparity in capabilities among hospitals within the alliance, particularly in the treatment of different diseases characterized by Disease Related Groups (DRG) in terms of effectiveness, efficiency and resource utilization, this study aims to address the centralized decision-making of intra-hospital patient referral within the medical alliance to enhance the overall production and quality of service provided. We first introduce the notion of production utility, where a higher production utility for a hospital implies better performance in treating patients diagnosed with that specific DRG group of diseases. Then, a Discrete-Event Simulation (DES) framework is established for patient referral among hospitals, where patient flow modeling incorporates a queueing system with fixed capacities for each hospital. The simulation study begins with a two-member alliance. The pivotal strategy examined is a "whether-to-refer" decision triggered when the bed usage rate surpasses a predefined threshold for either hospital. Then, the decision encompasses referring patients to the other hospital based on DRG groups’ production utility differentials as well as bed availability. The objective is to maximize the total production utility of the alliance while minimizing patients’ average length of stay and turnover rate. Thus the parameter under scrutiny is the bed usage rate threshold, influencing the efficacy of the referral strategy. Extending the study to a three-member alliance, which could readily be generalized to multi-member alliances, we maintain the core setup while introducing an additional “which-to-refer" decision that involves referring patients with specific DRG groups to the member hospital according to their respective production utility rankings. The overarching goal remains consistent, for which the bed usage rate threshold is once again a focal point for analysis. For the two-member alliance scenario, our simulation results indicate that the optimal bed usage rate threshold hinges on the discrepancy in the number of beds between member hospitals, the distribution of DRG groups among incoming patients, and variations in production utilities across hospitals. Transitioning to the three-member alliance, we observe similar dependencies on these parameters. Additionally, it becomes evident that an imbalanced distribution of DRG diagnoses and further disparity in production utilities among member hospitals may lead to an increase in the turnover rate. In general, it was found that the intra-hospital referral mechanism enhances the overall production utility of the medical alliance compared to individual hospitals without partnership. Patients’ average length of stay is also reduced, showcasing the positive impact of the collaborative approach. However, the turnover rate exhibits variability based on parameter setups, particularly when patients are redirected within the alliance. In conclusion, the re-structuring of diagnostic disease groups within the medical alliance proves instrumental in improving overall healthcare service outcomes, providing a compelling rationale for the government's promotion of patient referrals within collaborative medical alliances.

Keywords: collaborative medical alliance, disease related group, patient referral, simulation

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Authors: Xu Zhang

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This article unveils an indicator of language contact between English and Cantonese in one of the Outer Circle Englishes, Hong Kong (HK) English, through an empirical investigation into 1000 tokens from the Global Web-based English (GloWbE) corpus, employing frequency analysis and logistic regression analysis. It is perceived that Cantonese and general Chinese are contextually marked by an integral underlying thinking pattern. Chinese speakers exhibit a reliance on semantic context over syntactic rules and lexical forms. This linguistic trait carries over to their use of English, affording greater flexibility to formal elements in constructing English sentences. The study focuses on the syntactic positioning of the focusing subjunct ‘also’, a linguistic element used to add new or contrasting prominence to specific sentence constituents. The English language generally allows flexibility in the relative position of 'also’, while there is a preference for close marking relationships. This article shifts attention to Hong Kong, where Cantonese and English converge, and 'also' finds counterparts in Cantonese ‘jaa’ and Mandarin ‘ye’. Employing a corpus-based data-driven method, we investigate the syntactic position of 'also' in both HK and GB English. The study aims to ascertain whether HK English exhibits a greater 'syntactic freedom,' allowing for a more distant marking relationship with 'also' compared to GB English. The analysis involves a random extraction of 500 samples from both HK and GB English from the GloWbE corpus, forming a dataset (N=1000). Exclusions are made for cases where 'also' functions as an additive conjunct or serves as a copulative adverb, as well as sentences lacking sufficient indication that 'also' functions as a focusing particle. The final dataset comprises 820 tokens, with 416 for GB and 404 for HK, annotated according to the focused constituent and the relative position of ‘also’. Frequency analysis reveals significant differences in the relative position of 'also' and marking relationships between HK and GB English. Regression analysis indicates a preference in HK English for a distant marking relationship between 'also' and its focused constituent. Notably, the subject and other constituents emerge as significant predictors of a distant position for 'also.' Together, these findings underscore the nuanced linguistic dynamics in HK English and contribute to our understanding of language contact. It suggests that future pedagogical practice should consider incorporating the syntactic variation within English varieties, facilitating leaners’ effective communication in diverse English-speaking environments and enhancing their intercultural communication competence.

Keywords: also, Cantonese, English, focus marker, frequency analysis, language contact, logistic regression analysis

Procedia PDF Downloads 32

Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

Procedia PDF Downloads 210

Authors: M. Khorshed Alam, H. Takaba

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The catalytic properties of metal usually change by intermixturing with another metal in polymer electrolyte fuel cells. Pt-Ru alloy is one of the much-talked used alloy to enhance the CO oxidation. In this work, we have investigated the CO coverage on the Pt2Ru3 nanoparticle with different atomic conformation of Pt and Ru using a combination of material informatics with computational chemistry. Density functional theory (DFT) calculations used to describe the adsorption strength of CO and H with different conformation of Pt Ru ratio in the Pt2Ru3 slab surface. Then through the Monte Carlo (MC) simulations we examined the segregation behaviour of Pt as a function of surface atom ratio, subsurface atom ratio, particle size of the Pt2Ru3 nanoparticle. We have constructed a regression equation so as to reproduce the results of DFT only from the structural descriptors. Descriptors were selected for the regression equation; xa-b indicates the number of bonds between targeted atom a and neighboring atom b in the same layer (a,b = Pt or Ru). Terms of xa-H2 and xa-CO represent the number of atoms a binding H2 and CO molecules, respectively. xa-S is the number of atom a on the surface. xa-b- is the number of bonds between atom a and neighboring atom b located outside the layer. The surface segregation in the alloying nanoparticles is influenced by their component elements, composition, crystal lattice, shape, size, nature of the adsorbents and its pressure, temperature etc. Simulations were performed on different size (2.0 nm, 3.0 nm) of nanoparticle that were mixing of Pt and Ru atoms in different conformation considering of temperature range 333K. In addition to the Pt2Ru3 alloy we also considered pure Pt and Ru nanoparticle to make comparison of surface coverage by adsorbates (H2, CO). Hence, we assumed the pure and Pt-Ru alloy nanoparticles have an fcc crystal structures as well as a cubo-octahedron shape, which is bounded by (111) and (100) facets. Simulations were performed up to 50 million MC steps. From the results of MC, in the presence of gases (H2, CO), the surfaces are occupied by the gas molecules. In the equilibrium structure the coverage of H and CO as a function of the nature of surface atoms. In the initial structure, the Pt/Ru ratios on the surfaces for different cluster sizes were in range of 0.50 - 0.95. MC simulation was employed when the partial pressure of H2 (PH2) and CO (PCO) were 70 kPa and 100-500 ppm, respectively. The Pt/Ru ratios decrease as the increase in the CO concentration, without little exception only for small nanoparticle. The adsorption strength of CO on the Ru site is higher than the Pt site that would be one of the reason for decreasing the Pt/Ru ratio on the surface. Therefore, our study identifies that controlling the nanoparticle size, composition, conformation of alloying atoms, concentration and chemical potential of adsorbates have impact on the steadiness of nanoparticle alloys which ultimately and also overall catalytic performance during the operations.

Keywords: anode catalysts, fuel cells, material informatics, Monte Carlo

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

Procedia PDF Downloads 84

Authors: Benoît Mary, Thibaut Gras, Gaëtan Fagot, Yvon Goth, Ilyes Mnassri-Cetim

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A Gerotor pump is composed of an external and internal gear with conjugate cycloidal profiles. From suction to delivery ports, the fluid is transported inside cavities formed by teeth and driven by the shaft. From a geometric and conceptional side it is worth to note that the internal gear has one tooth less than the external one. Simcenter Amesim v.16 includes a new submodel for modelling the hydraulic Gerotor pumps behavior (THCDGP0). This submodel considers leakages between teeth tips using Poiseuille and Couette flows contributions. From the 3D CAD model of the studied pump, the “CAD import” tool takes out the main geometrical characteristics and the submodel THCDGP0 computes the evolution of each cavity volume and their relative position according to the suction or delivery areas. This module, based on international publications, presents robust results up to 6 000 rpm for pressure greater than atmospheric level. For higher rotational speeds or lower pressures, oil aeration and cavitation effects are significant and highly drop the pump’s performance. The liquid used in hydraulic systems always contains some gas, which is dissolved in the liquid at high pressure and tends to be released in a free form (i.e. undissolved as bubbles) when pressure drops. In addition to gas release and dissolution, the liquid itself may vaporize due to cavitation. To model the relative density of the equivalent fluid, modified Henry’s law is applied in Simcenter Amesim v.16 to predict the fraction of undissolved gas or vapor. Three parietal pressure sensors have been set up upstream from the pump to estimate the sound speed in the oil. Analytical models have been compared with the experimental sound speed to estimate the occluded gas content. Simcenter Amesim v.16 model was supplied by these previous analyses marks which have successfully improved the simulations results up to 14 000 rpm. This work provides a sound foundation for designing the next Gerotor pump generation reaching high rotation range more than 25 000 rpm. This improved module results will be compared to tests on this new pump demonstrator.

Keywords: gerotor pump, high speed, numerical simulations, aeronautic, aeration, cavitation

Procedia PDF Downloads 117

Authors: Anjali Vanpariya, Priyanka Marathey, Sakshum Khanna, Roma Patel, Indrajit Mukhopadhyay

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Silicon (Si) is a promising negative electrode material for lithium-ion batteries (LiBs) due to its low cost, non-toxicity, and a high theoretical capacity of 4200 mAhg⁻¹. The primary challenge of the application of Si-based LiBs is large volume expansion (~ 300%) during the charge-discharge process. Incorporation of graphene, carbon nanotubes (CNTs), morphological control, and nanoparticles was utilized as effective strategies to tackle volume expansion issues. However, molten salt methods can resolve the issue, but high-temperature requirement limits its application. For sustainable and practical approach, room temperature (RT) based methods are essentially required. Use of ionic liquids (ILs) for electrodeposition of Si nanostructures can possibly resolve the issue of temperature as well as greener media. In this work, electrodeposition of Si nanoparticles on gold substrate was successfully carried out in the presence of ILs media, 1-butyl-3-methylimidazolium-bis (trifluoromethyl sulfonyl) imide (BMImTf₂N) at room temperature. Cyclic voltammetry (CV) suggests the sequential reduction of Si⁴⁺ to Si²⁺ and then Si nanoparticles (SiNs). The structure and morphology of the electrodeposited SiNs were investigated by FE-SEM and observed interconnected Si nanoparticles of average particle size ⁓100-200 nm. XRD and XPS data confirm the deposition of Si on Au (111). The first discharge-charge capacity of Si anode material has been found to be 1857 and 422 mAhg⁻¹, respectively, at current density 7.8 Ag⁻¹. The irreversible capacity of the first discharge-charge process can be attributed to the solid electrolyte interface (SEI) formation via electrolyte decomposition, and trapped Li⁺ inserted into the inner pores of Si. Pulverization of SiNs results in the creation of a new active site, which facilitates the formation of new SEI in the subsequent cycles leading to fading in a specific capacity. After 20 cycles, charge-discharge profiles have been stabilized, and a reversible capacity of 150 mAhg⁻¹ is retained. Electrochemical impedance spectroscopy (EIS) data shows the decrease in Rct value from 94.7 to 47.6 kΩ after 50 cycles of charge-discharge, which demonstrates the improvements of the interfacial charge transfer kinetics. The decrease in the Warburg impedance after 50 cycles of charge-discharge measurements indicates facile diffusion in fragmented and smaller Si nanoparticles. In summary, Si nanoparticles deposited on gold substrate using ILs as media and characterized well with different analytical techniques. Synthesized material was successfully utilized for LiBs application, which is well supported by CV and EIS data.

Keywords: silicon nanoparticles, ionic liquid, electrodeposition, cyclic voltammetry, Li-ion battery

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Authors: Derek Wardle, Tarik Al-Shemmeri, Neil Packer

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This paper presents a small tube/wire type electrostatic precipitator (ESP). In the ESPs present form, particle charging and collecting voltages and airflow rates were individually varied throughout 200 ambient temperature test runs ranging from 10 to 30 kV in increments on 5 kV and 0.5 m/s to 1.5 m/s, respectively. It was repeatedly observed that, at input air velocities of between 0.5 and 0.9 m/s and voltage settings of 20 kV to 30 kV, the collection efficiency remained above 95%. The outcomes of preliminary tests at combustion flue temperatures are, at present, inconclusive although indications are that there is little or no drop in comparable performance during ideal test conditions. A limited set of similar tests was carried out during which the collecting electrode was grounded, having been disconnected from the static generator. The collecting efficiency fell significantly, and for that reason, this approach was not pursued further. The collecting efficiencies during ambient temperature tests were determined by mass balance between incoming and outgoing dry PM. The efficiencies of combustion temperature runs are determined by analysing the difference in opacity of the flue gas at inlet and outlet compared to a reference light source. In addition, an array of Leit tabs (carbon coated, electrically conductive adhesive discs) was placed at inlet and outlet for a number of four-day continuous ambient temperature runs. Analysis of the discs’ contamination was carried out using scanning electron microscopy and ImageJ computer software that confirmed collection efficiencies of over 99% which gave unequivocal support to all the previous tests. The average efficiency for these runs was 99.409%. Emissions collected from a woody biomass combustion unit, classified to a diameter of 100 µm, were used in all ambient temperature trials test runs apart from two which collected airborne dust from within the laboratory. Sawdust and wood pellets were chosen for laboratory and field combustion trials. Video recordings were made of three ambient temperature test runs in which the smoke from a wood smoke generator was drawn through the precipitator. Although these runs were visual indicators only, with no objective other than to display, they provided a strong argument for the device’s claimed efficiency, as no emissions were visible at exit when energised.  The theoretical performance of ESPs, when applied to the geometry and configuration of the tested model, was compared to the actual performance and was shown to be in good agreement with it.

Keywords: electrostatic precipitators, air quality, particulates emissions, electron microscopy, image j

Procedia PDF Downloads 235

Authors: Thabo M. Bafitlhile, Adewole Oladele

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Botswana has been affected by floods since long ago and is still experiencing this tragic event. Flooding occurs mostly in the North-West, North-East, and parts of Central district due to heavy rainfalls experienced in these areas. The torrential rains destroyed homes, roads, flooded dams, fields and destroyed livestock and livelihoods. Palapye is one area in the central district that has been experiencing floods ever since 1995 when its greatest flood on record occurred. Heavy storms result in floods and inundation; this has been exacerbated by poor and absence of drainage structures. Since floods are a part of nature, they have existed and will to continue to exist, hence more destruction. Furthermore floods and highway plays major role in erosion and destruction of roads structures. Already today, many culverts, trenches, and other drainage facilities lack the capacity to deal with current frequency for extreme flows. Future changes in the pattern of hydro climatic events will have implications for the design and maintenance costs of roads. Increase in rainfall and severe weather events can affect the demand for emergent responses. Therefore flood forecasting and warning is a prerequisite for successful mitigation of flood damage. In flood prone areas like Palapye, preventive measures should be taken to reduce possible adverse effects of floods on the environment including road structures. Therefore this paper attempts to estimate return periods associated with huge storms of different magnitude from recorded historical rainfall depth using statistical method. The method of annual maxima was used to select data sets for the rainfall analysis. In the statistical method, the Type 1 extreme value (Gumbel), Log Normal, Log Pearson 3 distributions were all applied to the annual maximum series for Palapye area to produce IDF curves. The Kolmogorov-Smirnov test and Chi Squared were used to confirm the appropriateness of fitted distributions for the location and the data do fit the distributions used to predict expected frequencies. This will be a beneficial tool for urgent flood forecasting and water resource administration as proper drainage design will be design based on the estimated flood events and will help to reclaim and protect the road structures from adverse impacts of flood.

Keywords: drainage, estimate, evaluation, floods, flood forecasting

Procedia PDF Downloads 348

Authors: Emiliano Matta

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Passive resonant vibration absorbers are among the most widely used dynamic control systems in civil engineering. They typically consist in a single-degree-of-freedom mechanical appendage of the main structure, tuned to one structural target mode through frequency and damping optimization. One classical scheme is the pendulum absorber, whose mass is constrained to move along a curved trajectory and is damped by viscous dashpots. Even though the principle is well known, the search for improved arrangements is still under way. In recent years this investigation inspired a type of bidirectional pendulum absorber (BPA), consisting of a mass constrained to move along an optimal three-dimensional (3D) concave surface. For such a BPA, the surface principal curvatures are designed to ensure a bidirectional tuning of the absorber to both principal modes of the main structure, while damping is produced either by horizontal viscous dashpots or by vertical friction dashpots, connecting the BPA to the main structure. In this paper, a variant of BPA is proposed, where damping originates from the variable tangential friction force which develops between the pendulum mass and the 3D surface as a result of a spatially-varying friction coefficient pattern. Namely, a friction coefficient is proposed that varies along the pendulum surface in proportion to the modulus of the 3D surface gradient. With such an assumption, the dissipative model of the absorber can be proven to be nonlinear homogeneous in the small displacement domain. The resulting homogeneous BPA (HBPA) has a fundamental advantage over conventional friction-type absorbers, because its equivalent damping ratio results independent on the amplitude of oscillations, and therefore its optimal performance does not depend on the excitation level. On the other hand, the HBPA is more compact than viscously damped BPAs because it does not need the installation of dampers. This paper presents the analytical model of the HBPA and an optimal methodology for its design. Numerical simulations of single- and multi-story building structures under wind and earthquake loads are presented to compare the HBPA with classical viscously damped BPAs. It is shown that the HBPA is a promising alternative to existing BPA types and that homogeneous tangential friction is an effective means to realize systems provided with amplitude-independent damping.

Keywords: amplitude-independent damping, homogeneous friction, pendulum nonlinear dynamics, structural control, vibration resonant absorbers

Procedia PDF Downloads 127

Authors: Calister Wingang Makebe, Wilson Agwanande Ambindei, Zangue Steve Carly Desobgo, Abraham Billu, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1, as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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Authors: Nidhi Sharotri, Dhiraj Sud

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Water pollution by pesticides constitutes a serious ecological problem due to their potential toxicity and bioaccumulation. The widespread use of pesticides in industry and agriculture along with their resistance to natural decomposition, biodegradation, chemical and photochemical degradation under typical environmental conditions has resulted in the emergence of these chemicals and their transformed products in natural water. Among AOP’s, heterogeneous photocatalysis using TiO2 as photocatalyst appears as the most emerging destructive technology for mineralization of the pollutant in aquatic streams. Among the various semiconductors (TiO2, ZnO, CdS, FeTiO3, MnTiO3, SrTiO2 and SnO2), TiO2 has proven to be the most efficient photocatalyst for environmental applications due to its biological and chemical inertness, high photo reactivity, non-toxicity, and photo stability. Semiconductor photocatalysts are characterized by an electronic band structure in which valence band and conduction band are separated by a band gap, i.e. a region of forbidden energy. Semiconductor based photocatalysts produces e-/h+ pairs which have been employed for degradation of organic pollutants. The present paper focuses on modification of TiO2 photocatalyst in order to shift its absorption edge towards longer wavelength to make it active under natural light. Semiconductor TiO2 photocatalysts was prepared by doping with anion (N), cation (Mn) and double doped (Mn, N) using greener approach. Titanium isopropoxide is used as titania precursor and ethanedithiol, hydroxyl amine hydrochloride, manganous chloride as sulphur, nitrogen and manganese precursors respectively. Synthesized doped TiO2 nanomaterials are characterized for surface morphology (SEM, TEM), crystallinity (XRD) and optical properties (absorption spectra and band gap). EPR data confirms the substitutional incorporation of Mn2+ in TiO2 lattice. The doping influences the phase transformation of rutile and anatase phase crystal and thereby the absorption spectrum changes were observed. The effect of variation of reaction parameters such as solvent, reaction time and calcination temperature on the yield, surface morphology and optical properties was also investigated. The TEM studies show the particle size of nanomaterials varies from 10-50 nm. The calculated band gap of nanomaterials varies from 2.30-2.60 eV. The photocatalytic degradation of organic pollutant organophosphate pesticide (Quinalphos) has been investigated by studying the changes in UV absorption spectrum and the promising results were obtained under visible light. The complete mineralization of quinalphos has occurred as no intermediates were recorded after 8 hrs of degradation confirmed from the HPLC studies.

Keywords: quinalphos, doped-TiO2, mineralization, EPR

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Authors: Ariyan S. Araghi, Guy C. Jackson, Stephen J. Bonsor

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Materials & Methods: A systematic literature search was undertaken using pre-determined inclusion and exclusion criteria. This review followed the Preferred Reporting Items for Systemic Reviews and Meta-Analysis (PRISMA) statement. Several databases were used to search for randomised control trials and longitudinal cohort studies, which were published less than thirty years ago. A total of 54 studies met the predefined inclusion criteria. Four studies reviewed the success, survival, and failure characteristics of zirconia framework resin retained bridges, whilst two reviewed non-precious metal resin retained bridges. Results: The analysis of the studies revealed an overall survival rate of 95.9% for zirconia-based restorations compared to 90.7% for non-precious metal frameworks. Non-precious metal resin retained bridges displayed a higher overall failure rate of 11.9% compared to 4.6% for zirconia-based restorations in the analysed papers. The most frequent complications were wing debonding for the non-precious metal wing group, whereas substructure fracture and veneering ceramic fracture were more prevalent for the zirconia arm of the study. Conclusion: Both types of resin retained bridges provide effective medium to long-term survival. Zirconia-based frameworks will provide marginally increased success and survival and greatly improved aesthetics. However, catastrophic failure is more likely with zirconia-based restorations. Non-precious metal is time tested but performs worse than its zirconia counterpart with regards to longevity; it does not exhibit the same framework fractures as zirconia. Cement choice and attention to the adhesive bonding systems used appear to be paramount to restoration longevity with both restoration subtypes. Furthermore, improved longevity can be seen when air particle abrasion is incorporated into the adhesive protocol. Within the limitations of this study, it has been determined that zirconia-based resin retained bridges can be effectively used in anterior cantilever bridges. Clinical Significance: Zirconia-based resin retained bridges have been demonstrating promising results in terms of improved success and survival characteristics, together with improved aesthetics when compared to non-precious metal winged resin retained bridges. Their popularity is increasing in the age of digital dentistry as many restorations are manufactured using such technology. It is essential that clinicians understand the limitations of each material type and principles of adhesion to ensure restoration longevity.

Keywords: resin retained bridge, fixed partial denture, zirconia bridge, adhesive bridge

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Authors: Imed Feki, Faouzi Msahli

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Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevant fabric physical parameters for each sensory quality feature. The proposed relevancy criterion has been developed using two approaches. The first utilizes a fuzzy sensitivity criterion by exploiting from experimental data the relationship between physical parameters and all the sensory quality features for each evaluator. Next an OWA aggregation procedure is applied to aggregate the ranking lists provided by different evaluators. In the second approach, another panel of experts provides their ranking lists of physical features according to their professional knowledge. Also by applying OWA and a fuzzy aggregation model, the data sensitivity-based ranking list and the knowledge-based ranking list are combined using our proposed percolation technique, to determine the final ranking list. The key issue of the proposed percolation technique is to filter automatically and objectively the relevant features by creating a gap between scores of relevant and irrelevant parameters. It permits to automatically generate threshold that can effectively reduce human subjectivity and arbitrariness when manually choosing thresholds. For a specific sensory descriptor, the threshold is defined systematically by iteratively aggregating (n times) the ranking lists generated by OWA and fuzzy models, according to a specific algorithm. Having applied the percolation technique on a real example, of a well known finished textile product especially the stonewashed denims, usually considered as the most important quality criteria in jeans’ evaluation, we separate the relevant physical features from irrelevant ones for each sensory descriptor. The originality and performance of the proposed relevant feature selection method can be shown by the variability in the number of physical features in the set of selected relevant parameters. Instead of selecting identical numbers of features with a predefined threshold, the proposed method can be adapted to the specific natures of the complex relations between sensory descriptors and physical features, in order to propose lists of relevant features of different sizes for different descriptors. In order to obtain more reliable results for selection of relevant physical features, the percolation technique has been applied for combining the fuzzy global relevancy and OWA global relevancy criteria in order to clearly distinguish scores of the relevant physical features from those of irrelevant ones.

Keywords: data sensitivity, feature selection, fuzzy logic, OWA operators, percolation technique

Procedia PDF Downloads 584

Authors: Marita Heyns

Abstract:

Job insecurity is a distressing phenomenon which has far reaching consequences for both employees and their organizations. Previously, much attention has been given to the link between job insecurity and individual level performance outcomes, while less is known about how subjectively perceived job insecurity might transfer beyond the individual level to affect performance of the organization on an aggregated level. Research focusing on how employees’ fear of job loss might affect the organization’s ability to respond proactively to volatility and drastic change through applying its capabilities of sensing, seizing, and reconfiguring, appears to be practically non-existent. Equally little is known about the potential underlying mechanisms through which job insecurity might affect the dynamic capabilities of an organization. This study examines how job insecurity might affect dynamic organizational capability through trust as an underling process. More specifically, it considered the simultaneous roles of trust at an impersonal (organizational) level as well as trust at an interpersonal level (in leaders and co-workers) as potential underlying mechanisms through which job insecurity might affect the organization’s dynamic capability to respond to opportunities and imminent, drastic change. A quantitative research approach and a stratified random sampling technique enabled the collection of data among 314 managers at four different plant sites of a large South African steel manufacturing organization undergoing dramatic changes. To assess the study hypotheses, the following statistical procedures were employed: Structural equation modelling was performed in Mplus to evaluate the measurement and structural models. The Chi-square values test for absolute fit as well as alternative fit indexes such as the Comparative Fit Index and the Tucker-Lewis Index, the Root Mean Square Error of Approximation and the Standardized Root Mean Square Residual were used as indicators of model fit. Composite reliabilities were calculated to evaluate the reliability of the factors. Finally, interaction effects were tested by using PROCESS and the construction of two-sided 95% confidence intervals. The findings indicate that job insecurity had a lower-than-expected detrimental effect on evaluations of the organization’s dynamic capability through the conducive buffering effects of trust in the organization and in its leaders respectively. In contrast, trust in colleagues did not seem to have any noticeable facilitative effect. The study proposes that both job insecurity and dynamic capability can be managed more effectively by also paying attention to factors that could promote trust in the organization and its leaders; some practical recommendations are given in this regard.

Keywords: dynamic organizational capability, impersonal trust, interpersonal trust, job insecurity

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