Search results for: nonlinear equations

Authors: Juan S. Vera, Miguel A. Gomez, Omar Gelvez

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Water is Earth's most valuable resource, and the lack of it is currently a critical problem in today’s society. Non-treated wastewaters contribute to this situation, especially those coming from industrial activities, as they reduce the quality of the water bodies, annihilating all kind of life and bringing disease to people in contact with them. An effective solution for this problem is distillation, which removes most contaminants. However, this approach must also be energetically efficient in order to appeal to the industry. In this endeavour, most water distillation treatments fail, with the exception of the Mechanical Vapor Compression (MVC) distillation system, which has a great efficiency due to energy input by a compressor and the latent heat exchange. This paper presents the process of design, construction, and evaluation of a Mechanical Vapor Compression (MVC) distillation system for the main Colombian poultry company Avidesa Macpollo SA. The system will be located in the principal slaughterhouse in the state of Santander, and it will work along with the Gas Energy Mixing system (GEM) to treat the wastewaters from the plant. The main goal of the MVC distiller, rarely used in this type of application, is to reduce the chlorides, Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD) levels according to the state regulations since the GEM cannot decrease them enough. The MVC distillation system works with three components, the evaporator/condenser heat exchanger where the distillation takes place, a low-pressure compressor which gives the energy to create the temperature differential between the evaporator and condenser cavities and a preheater to save the remaining energy in the distillate. The model equations used to describe how the compressor power consumption, heat exchange area and distilled water are related is based on a thermodynamic balance and heat transfer analysis, with correlations taken from the literature. Finally, the design calculations and the measurements of the installation are compared, showing accordance with the predictions in distillate production and power consumption, changing the temperature difference of the evaporator/condenser.

Keywords: mechanical vapor compression, distillation, wastewater, design, construction, evaluation

Procedia PDF Downloads 136

Authors: Sarath Chandran Nair S, Srinivas Kodati, Vasudevan R, Asraff A. K

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Spacecrafts generally employ liquid propulsion for their attitude and orbital maneuvers or raising it from geo-transfer orbit to geosynchronous orbit. Liquid propulsion systems use either mono-propellant or bi-propellants for generating thrust. These propellants are generally stored in either spherical tanks or cylindrical tanks with spherical end domes. The propellant tanks are provided with a propellant acquisition system/propellant management device along with vanes and their conical mounting structure to ensure propellant availability in the outlet for thrust generation even under a low/zero-gravity environment. Slosh is the free surface oscillations in partially filled containers under external disturbances. In a spacecraft, these can be due to control forces and due to varying acceleration. Knowledge of slosh and its effect due to internals is essential for understanding its stability through control stability studies. It is mathematically represented by a pendulum-mass model. It requires parameters such as slosh frequency, damping, sloshes mass and its location, etc. This paper enumerates various numerical and experimental methods used for evaluating the slosh parameters required for representing slosh. Numerical methods like finite element methods based on linear velocity potential theory and computational fluid dynamics based on Reynolds Averaged Navier Stokes equations are used for the detailed evaluation of slosh behavior in one of the spacecraft propellant tanks used in an Indian space mission. Experimental studies carried out on a scaled-down model are also discussed. Slosh parameters evaluated by different methods matched very well and finalized their dispersion bands based on experimental studies. It is observed that the presence of internals such as propellant management devices, including conical support structure, alters slosh parameters. These internals also offers one order higher damping compared to viscous/ smooth wall damping. It is an advantage factor for the stability of slosh. These slosh parameters are given for establishing slosh margins through control stability studies and finalize the spacecraft control system design.

Keywords: control stability, propellant tanks, slosh, spacecraft, slosh spacecraft

Procedia PDF Downloads 204

Authors: Geetanjali Yadav, Arpit Mishra, Parthsarathi Ghosh, Ramkrishna Sen

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The world is facing problems of increasing global CO2 emissions, climate change and fuel crisis. Therefore, several renewable and sustainable energy alternatives should be investigated to replace non-renewable fuels in future. Algae presents itself a versatile feedstock for the production of variety of fuels (biodiesel, bioethanol, bio-hydrogen etc.) and high value compounds for food, fodder, cosmetics and pharmaceuticals. Microalgae are simple microorganisms that require water, light, CO2 and nutrients for growth by the process of photosynthesis and can grow in extreme environments, utilize waste gas (flue gas) and waste waters. Mixing, however, is a crucial parameter within the culture system for the uniform distribution of light, nutrients and gaseous exchange in addition to preventing settling/sedimentation, creation of dark zones etc. The overarching goal of the present study is to improve photobioreactor (PBR) design for enhancing dissolution of CO2 from ambient air (0.039%, v/v), pure CO2 and coal-fired flue gas (10 ± 2%) into microalgal PBRs. Computational fluid dynamics (CFD), a state-of-the-art technique has been used to solve partial differential equations with turbulence closure which represents the dynamics of fluid in a photobioreactor. In this paper, the hydrodynamic performance of the PBR has been characterized and compared with that of the conventional bubble column PBR using CFD. Parameters such as flow rate (Q), mean velocity (u), mean turbulent kinetic energy (TKE) were characterized for each experiment that was tested across different aeration schemes. The results showed that the modified PBR design had superior liquid circulation properties and gas-liquid transfer that resulted in creation of uniform environment inside PBR as compared to conventional bubble column PBR. The CFD technique has shown to be promising to successfully design and paves path for a future research in order to develop PBRs which can be commercially available for scale-up microalgal production.

Keywords: computational fluid dynamics, microalgae, bubble column photbioreactor, flue gas, simulation

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Authors: V. Batishchev, V. Getman

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We study the self-similar fluid flows in the Marangoni layers with the axial symmetry. Such flows are induced by the radial gradients of the temperatures whose distributions along the free boundary obey some power law. The self-similar solutions describe thermo-capillar flows both in the thin layers and in the case of infinite thickness. We consider both positive and negative temperature gradients. In the former case the cooling of free boundary nearby the axis of symmetry gives rise to the rotation of fluid. The rotating flow concentrates itself inside the Marangoni layer while outside of it the fluid does not revolve. In the latter case we observe no rotating flows at all. In the layers of infinite thickness the separation of the rotating flow creates two zones where the flows are directed oppositely. Both the longitudinal velocity and the temperature have exactly one critical point inside the boundary layer. It is worth to note that the profiles are monotonic in the case of non-swirling flows. We describe the flow outside the boundary layer with the use of self-similar solution of the Euler equations. This flow is slow and non-swirling. The introducing of an outer flow gives rise to the branching of swirling flows from the non-swirling ones. There is such the critical velocity of the outer flow that a non-swirling flow exists for supercritical velocities and cannot be extended to the sub-critical velocities. For the positive temperature gradients there are two non-swirling flows. For the negative temperature gradients the non-swirling flow is unique. We determine the critical velocity of the outer flow for which the branching of the swirling flows happens. In the case of a thin layer confined within free boundaries we show that the cooling of the free boundaries near the axis of symmetry leads to the separating of the layer and creates two sub-layers with opposite rotations inside. This makes sharp contrast with the case of infinite thickness. We show that such rotation arises provided the thickness of the layer exceed some critical value. In the case of a thin layer confined within free and rigid boundaries we construct the branching equation and the asymptotic approximation for the secondary swirling flows near the bifurcation point. It turns out that the bifurcation gives rise to one pair of the secondary swirling flows with different directions of swirl.

Keywords: free surface, rotation, fluid flow, bifurcation, boundary layer, Marangoni layer

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Authors: Abbas Kamalibandpey, Alain Beland, Joseph Mukendi Kabuya

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Since a rock mass is a discontinuum medium, its behaviour is governed by discontinuities such as faults, joint sets, lithologic contact, and bedding planes. Thus, rock slope stability analysis in jointed rock masses is largely dependent upon discontinuities constitutive equations. This paper studies the difference between the Mohr-Coulomb (MC) and the Barton-Bandis (BB) joint constitutive numerical models for lithological contacts and joint sets. For the rock in these models, generalized Hoek-Brown criteria have been considered. The joint roughness coefficient (JRC) and the joint wall compressive strength (JCS) are vital parameters in the BB model. The numerical models are applied to the rock slope stability analysis in the Mont-Wright (MW) mine. The Mont-Wright mine is owned and operated by ArcelorMittal Mining Canada (AMMC), one of the largest iron-ore open pit operations in Canada. In this regard, one of the high walls of the mine has been selected to undergo slope stability analysis with RS2D software, finite element method. Three piezometers have been installed in this zone to record pore water pressure and it is monitored by radar. In this zone, the AMP-IF and QRMS-IF contacts and very persistent and altered joint sets in IF control the rock slope behaviour. The height of the slope is more than 250 m and consists of different lithologies such as AMP, IF, GN, QRMS, and QR. To apply the B-B model, the joint sets and geological contacts have been scanned by Maptek, and their JRC has been calculated by different methods. The numerical studies reveal that the JRC of geological contacts, AMP-IF and QRMS-IF, and joint sets in IF had a significant influence on the safety factor. After evaluating the results of rock slope stability analysis and the radar data, the B-B constitutive equation for discontinuities has shown acceptable results to the real condition in the mine. It should be noted that the difference in safety factors in MC and BB joint constitutive models in some cases is more than 30%.

Keywords: barton-Bandis criterion, Hoek-brown and Mohr-Coulomb criteria, open pit, slope stability

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Authors: Subrat Partha Sarathi Pattnaik, Rajan N.K.S.

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Integrated rocket ramjet engines are highly suitable for long range missile applications. Designing the fixed geometry intakes for such missiles that can operate efficiently over a range of operating conditions is a highly challenging task. Hence, the present study aims to evaluate the effect of throat design on the performance of a rectangular mixed compression intake for operation in the Mach number range of 1.8 – 2.5. The analysis has been carried out at four different Mach numbers of 1.8, 2, 2.2, 2.5 and two angle-of-attacks of +5 and +10 degrees. For the throat design, three different throat heights have been considered, one corresponding to a 3- external shock design and two heights corresponding to a 2-external shock design leading to different internal contraction ratios. The on-design Mach number for the study is M 2.2. To obtain the viscous flow field in the intake, the theoretical designs have been considered for computational fluid dynamic analysis. For which Favre averaged Navier- Stokes (FANS) equations with two equation SST k-w model have been solved. The analysis shows that for zero angle of attack at on-design and high off-design Mach number operations the three-ramp design leads to a higher total pressure recovery (TPR) compared to the two-ramp design at both contraction ratios maintaining same mass flow ratio (MFR). But at low off-design Mach numbers the total pressure shows an opposite trend that is maximum for the two-ramp low contraction ratio design due to lower shock loss across the external shocks similarly the MFR is higher for low contraction ratio design as the external ramp shocks move closer to the cowl. At both the angle of attack conditions and complete range of Mach numbers the total pressure recovery and mass flow ratios are highest for two ramp low contraction design due to lower stagnation pressure loss across the detached bow shock formed at the ramp and lower mass spillage. Hence, low contraction design is found to be suitable for higher off-design performance.

Keywords: internal contraction ratio, mass flow ratio, mixed compression intake, performance, supersonic flows

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Authors: Jiradeach Kalayaruan, Tosawat Seetawan

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This paper studied the energy of the nature systems by looking at the overall image throughout the universe. The energy of the nature systems was developed from the Einstein’s energy equation. The researcher used the new ideas called even 2n and odd 3n light dimension energy states systems, which were developed from Einstein’s relativity energy theory equation. In this study, the major methodology the researchers used was the basic principle ideas or beliefs of some religions such as Buddhism, Christianity, Hinduism, Islam, or Tao in order to get new discoveries. The basic beliefs of each religion - Nivara, God, Ether, Atman, and Tao respectively, were great influential ideas on the researchers to use them greatly in the study to form new ideas from philosophy. Since the philosophy of each religion was alive with deep insight of the physical nature relative energy, it connected the basic beliefs to light dimension energy states systems. Unfortunately, Einstein’s original relative energy equation showed only even 2n light dimension energy states systems (if n = 1,…,∞). But in advance ideas, the researchers multiplied light dimension energy by Einstein’s original relative energy equation and get new idea of theoritical physics in odd 3n light dimension energy states systems (if n = 1,…,∞). Because from basic principle ideas or beliefs of some religions philosophy of each religion, you had to add the media light dimension energy into Einstein’s original relative energy equation. Consequently, the simple meaning picture in deep insight showed that you could touch light dimension energy of Nivara, God, Ether, Atman, and Tao by light dimension energy. Since light dimension energy was transferred by Nivara, God, Ether, Atman and Tao, the researchers got the new equation of odd 3n light dimension energy states systems. Moreover, the researchers expected to be able to solve overview problems of all light dimension energy in all nature relative energy, which are developed from Eistein’s relative energy equation.The finding of the study was called 'super nature relative energy' ( in odd 3n light dimension energy states systems (if n = 1,…,∞)). From the new ideas above you could do the summation of even 2n and odd 3n light dimension energy states systems in all of nature light dimension energy states systems. In the future time, the researchers will expect the new idea to be used in insight theoretical physics, which is very useful to the development of quantum mechanics, all engineering, medical profession, transportation, communication, scientific inventions, and technology, etc.

Keywords: 2n light dimension energy states systems effect, Ether, even 2n light dimension energy states systems, nature relativity, Nivara, odd 3n light dimension energy states systems, perturbation points energy, relax point energy states systems, stress perturbation energy states systems effect, super relative energy

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

Procedia PDF Downloads 280

Authors: Teris Cheung, Joyce Yuen Ting Lam, Kwan Hin Fong, Yuen Shan Ho, Tim Man Ho Li, Andy Choi-Yeung Tse, Cheng-Ta Li, Calvin Pak-Wing Cheng, Roland Beisteiner

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Transcranial pulse stimulation (TPS) is a non-intrusive brain stimulation technology that has been proven effective in older adults with mild neurocognitive disorders and adults with major depressive disorder. Given these robust evidences, TPS might be an adjunct treatment options in neuropsychiatric disorders, for example, autism spectrum disorder (ASD) – which is a common neurodevelopmental disorder in children. This trial aimed to investigate the effects of TPS on right temporoparietal junction, a key node for social cognition for Autism Spectrum Disorder (ASD), and to examine the association between TPS, executive functions and social functions. Design: This trial adopted a two-armed (verum TPS group vs. sham TPS group), double-blinded, randomized, sham-controlled design. Sampling: 32 subjects aged between 12 and 17, diagnosed with ASD were recruited. All subjects were computerized randomized into either verum TPS group or the sham TPS group on a 1:1 ratio. All subjects undertook functional MRI before and after the TPS interventions. Intervention: Six 30-min TPS sessions were administered to subjects in 2 weeks’ time on alternate days assessing neural connectivity changes. Baseline measurements and post-TPS evaluation of the ASD symptoms, executive functions, and social functions were conducted. Participants were followed up at 2-weeks, at 1-month and 3-month, assessing the short-and long-term sustainability of the TPS intervention. Data analysis: Generalized Estimating Equations with repeated measures were used to analyze the group and time difference. Missing data were managed by multiple imputations. The level of significance was set at p < 0.05. To our best knowledge, this is the first study evaluating the efficacy and safety of TPS among adolescents with ASD in Hong Kong and nationwide. Results emerging from this study will develop insight on whether TPS can be used as an adjunct treatment on ASD in neuroscience and clinical psychiatry. Clinical Trial Registration: ClinicalTrials.gov, identifier: NCT05408793.

Keywords: adolescents, autism spectrum disorder, neuromodulation, rct, transcranial pulse stimulation

Procedia PDF Downloads 45

Authors: A. Rezaei, M. Huisman, W. Van Paepegem

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Atomic interactions in molecular systems are mainly studied by particle mechanics. Nevertheless, researches have also put on considerable effort to simulate them using continuum methods. In early 2000, simple equivalent finite element models have been developed to study the mechanical properties of carbon nanotubes and graphene in composite materials. Afterward, many researchers have employed similar structural simulation approaches to obtain mechanical properties of nanostructured materials, to simplify interface behavior of fiber-reinforced composites, and to simulate defects in carbon nanotubes or graphene sheets, etc. These structural approaches, however, are limited to small deformations due to complicated local rotational coordinates. This article proposes a method for the finite element simulation of molecular mechanics. For ease in addressing the approach, here it is called Structural Finite Element Molecular Modeling (SFEMM). SFEMM method improves the available structural approaches for large deformations, without using any rotational degrees of freedom. Moreover, the method simulates molecular conformation, which is a big advantage over the previous approaches. Technically, this method uses nonlinear multipoint constraints to simulate kinematics of the atomic multibody interactions. Only truss elements are employed, and the bond potentials are implemented through constitutive material models. Because the equilibrium bond- length, bond angles, and bond-torsion potential energies are intrinsic material parameters, the model is independent of initial strains or stresses. In this paper, the SFEMM method has been implemented in ABAQUS finite element software. The constraints and material behaviors are modeled through two Fortran subroutines. The method is verified for the bond-stretch, bond-angle and bond-torsion of carbon atoms. Furthermore, the capability of the method in the conformation simulation of molecular structures is demonstrated via a case study of a graphene sheet. Briefly, SFEMM builds up a framework that offers more flexible features over the conventional molecular finite element models, serving the structural relaxation modeling and large deformations without incorporating local rotational degrees of freedom. Potentially, the method is a big step towards comprehensive molecular modeling with finite element technique, and thereby concurrently coupling an atomistic domain to a solid continuum domain within a single finite element platform.

Keywords: finite element, large deformation, molecular mechanics, structural method

Procedia PDF Downloads 128

Authors: O. Ojeda Mena, Y. Cressault, P. Teulet, J. P. Gonnet, D. F. N. Santos, MD. Cunha, M. S. Benilov

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The assumption of plasma in local thermal equilibrium (LTE) is commonly used to perform electric arc simulations for industrial applications. This assumption allows to model the arc using a set of magneto-hydromagnetic equations that can be solved with a computational fluid dynamic code. However, the LTE description is only valid in the arc column, whereas in the regions close to the electrodes the plasma deviates from the LTE state. The importance of these near-electrode regions is non-trivial since they define the energy and current transfer between the arc and the electrodes. Therefore, any accurate modelling of the arc must include a good description of the arc-electrode phenomena. Due to the modelling complexity and computational cost of solving the near-electrode layers, a simplified description of the arc-electrode interaction was developed in a previous work to study a steady high-pressure arc discharge, where the near-electrode regions are introduced at the interface between arc and electrode as boundary conditions. The present work proposes a similar approach to simulate the arc ignition in a free-burning arc configuration following an LTE description of the plasma. To obtain the transient evolution of the arc characteristics, appropriate boundary conditions for both the near-cathode and the near-anode regions are used based on recent publications. The arc-cathode interaction is modeled using a non-linear surface heating approach considering the secondary electron emission. On the other hand, the interaction between the arc and the anode is taken into account by means of the heating voltage approach. From the numerical modelling, three main stages can be identified during the arc ignition. Initially, a glow discharge is observed, where the cold non-thermionic cathode is uniformly heated at its surface and the near-cathode voltage drop is in the order of a few hundred volts. Next, a spot with high temperature is formed at the cathode tip followed by a sudden decrease of the near-cathode voltage drop, marking the glow-to-arc discharge transition. During this stage, the LTE plasma also presents an important increase of the temperature in the region adjacent to the hot spot. Finally, the near-cathode voltage drop stabilizes at a few volts and both the electrode and plasma temperatures reach the steady solution. The results after some seconds are similar to those presented for thermionic cathodes.

Keywords: arc-electrode interaction, thermal plasmas, electric arc simulation, cold electrodes

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Authors: K. Khouzami, J. Brassinne, C. Branca, E. Van Ruymbeke, B. Nysten, G. D’Angelo

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The development of hybrid organic-inorganic nanocomposites has recently attracted great interest. Typically, polymer silicates represent an emerging class of polymeric nanocomposites that offer superior material properties compared to each compound alone. Among these materials, complexes based on silicate clay and polysaccharides are one of the most promising nanocomposites. The strong electrostatic interaction between chitosan and montmorillonite can induce what is called physical hydrogel, where the coordination bonds or physical crosslinks may associate and dissociate reversibly and in a short time. These mechanisms could be the main origin of the uniqueness of their rheological behavior. However, owing to their structure intrinsically heterogeneous and/or the lack of dissipated energy, they are usually brittle, possess a poor toughness and may not have sufficient mechanical strength. Consequently, the properties of these nanocomposites cannot respond to some requirements of many applications in several fields. To address the issue of weak mechanical properties, covalent chemical crosslink bonds can be introduced to the physical hydrogel. In this way, quite homogeneous dually crosslinked microstructures with high dissipated energy and enhanced mechanical strength can be engineered. In this work, we have prepared a series of chitosan-montmorillonite nanocomposites chemically crosslinked by addition of poly (ethylene glycol) diglycidyl ether. This study aims to provide a better understanding of the mechanical behavior of dually crosslinked chitosan-based nanocomposites by relating it to their microstructures. In these systems, the variety of microstructures is obtained by modifying the number of cross-links. Subsequently, a superior uniqueness of the rheological properties of chemically crosslinked chitosan-montmorillonite nanocomposites is achieved, especially at the highest percentage of clay. Their rheological behaviors depend on the clay/chitosan ratio and the crosslinking. All specimens exhibit a viscous rheological behavior over the frequency range investigated. The flow curves of the nanocomposites show a Newtonian plateau at very low shear rates accompanied by a quite complicated nonlinear decrease with increasing the shear rate. Crosslinking induces a shear thinning behavior revealing the formation of network-like structures. Fitting shear viscosity curves via Ostward-De Waele equation disclosed that crosslinking and clay addition strongly affect the pseudoplasticity of the nanocomposites for shear rates γ ̇>20.

Keywords: chitosan, crossliking, nanocomposites, rheological properties

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Authors: P. Mounnarath, U. Schmitz, Ch. Zhang

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Fragility analysis is an effective tool for the seismic vulnerability assessment of civil structures in the last several years. The design of the expansion joints according to various bridge design codes is almost inconsistent, and only a few studies have focused on this problem so far. In this study, the influence of the expansion joint clearances between the girder ends and the abutment backwalls on the seismic fragility assessment of continuous integral bridge frames is investigated. The gaps (ranging from 60 mm, 150 mm, 250 mm and 350 mm) are designed by following two different bridge design code specifications, namely, Caltrans and Eurocode 8-2. Five bridge models are analyzed and compared. The first bridge model serves as a reference. This model uses three-dimensional reinforced concrete fiber beam-column elements with simplified supports at both ends of the girder. The other four models also employ reinforced concrete fiber beam-column elements but include the abutment backfill stiffness and four different gap values. The nonlinear time history analysis is performed. The artificial ground motion sets, which have the peak ground accelerations (PGAs) ranging from 0.1 g to 1.0 g with an increment of 0.05 g, are taken as input. The soil-structure interaction and the P-Δ effects are also included in the analysis. The component fragility curves in terms of the curvature ductility demand to the capacity ratio of the piers and the displacement demand to the capacity ratio of the abutment sliding bearings are established and compared. The system fragility curves are then obtained by combining the component fragility curves. Our results show that in the component fragility analysis, the reference bridge model exhibits a severe vulnerability compared to that of other sophisticated bridge models for all damage states. In the system fragility analysis, the reference curves illustrate a smaller damage probability in the earlier PGA ranges for the first three damage states, they then show a higher fragility compared to other curves in the larger PGA levels. In the fourth damage state, the reference curve has the smallest vulnerability. In both the component and the system fragility analysis, the same trend is found that the bridge models with smaller clearances exhibit a smaller fragility compared to that with larger openings. However, the bridge model with a maximum clearance still induces a minimum pounding force effect.

Keywords: expansion joint clearance, fiber beam-column element, fragility assessment, time history analysis

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Authors: Laura Salvia Diaz Silvarrey, Anh Phan

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Municipal Plastic Waste (MPW) comprises a mixture of thermoplastics such as high and low density polyethylene (HDPE and LDPE), polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET). Recycling rate of these plastics is low, e.g. only 27% in 2013. The remains were incinerated or disposed in landfills. As MPW generation increases approximately 5% per annum, MPW management technologies have to be developed to comply with legislation . Pyrolysis, thermochemical decomposition, provides an excellent alternative to convert MPW into valuable resources like fuels and chemicals. Most studies on waste plastic kinetics only focused on HDPE and LDPE with a simple assumption of first order decomposition, which is not the real reaction mechanism. The aim of this study was to develop a kinetic study for each of the polymers in the MPW mixture using thermogravimetric analysis (TGA) over a range of heating rates (5, 10, 20 and 40°C/min) in N2 atmosphere and sample size of 1 – 4mm. A model-free kinetic method was applied to quantify the activation energy at each level of conversion. Kissinger–Akahira–Sunose (KAS) and Flynn–Wall–Ozawa (FWO) equations jointly with Master Plots confirmed that the activation energy was not constant along all the reaction for all the five plastic studied, showing that MPW decomposed through a complex mechanism and not by first-order kinetics. Master plots confirmed that MPW decomposed following a random scission mechanism at conversions above 40%. According to the random scission mechanism, different radicals are formed along the backbone producing the cleavage of bonds by chain scission into molecules of different lengths. The cleavage of bonds during random scission follows first-order kinetics and it is related with the conversion. When a bond is broken one part of the initial molecule becomes an unsaturated one and the other a terminal free radical. The latter can react with hydrogen from and adjacent carbon releasing another free radical and a saturated molecule or reacting with another free radical and forming an alkane. Not every time a bonds is broken a molecule is evaporated. At early stages of the reaction (conversion and temperature below 40% and 300°C), most products are not short enough to evaporate. Only at higher degrees of conversion most of cleavage of bonds releases molecules small enough to evaporate.

Keywords: kinetic, municipal plastic waste, pyrolysis, random scission

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Mitchell J. Baum, Badin Gibbes, Greg Collecutt

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This study details a three-dimensional field-scale numerical investigation conducted for the Gold Coast Desalination Plant (GCDP) offshore multiport brine diffuser. Quantitative assessment of diffuser performance with regard to trajectory, dilution and mapping of seafloor concentration distributions was conducted for 100% plant operation. The quasi-steady Computational Fluid Dynamics (CFD) simulations were performed using the Reynolds averaged Navier-Stokes equations with a k-ω shear stress transport turbulence closure scheme. The study compliments a field investigation, which measured brine plume characteristics under similar conditions. CFD models used an iterative mesh in a domain with dimensions 400 m long, 200 m wide and an average depth of 24.2 m. Acoustic Doppler current profiler measurements conducted in the companion field study exhibited considerable variability over the water column. The effect of this vertical variability on simulated discharge outcomes was examined. Seafloor slope was also accommodated into the model. Ambient currents varied predominantly in the longshore direction – perpendicular to the diffuser structure. Under these conditions, the alternating port orientation of the GCDP diffuser resulted in simultaneous subjection to co-propagating and counter-propagating ambient regimes. Results from quiescent ambient simulations suggest broad agreement with empirical scaling arguments traditionally employed in design and regulatory assessments. Simulated dynamic ambient regimes showed the influence of ambient crossflow upon jet trajectory, dilution and seafloor concentration is significant. The effect of ambient flow structure and the subsequent influence on jet dynamics is discussed, along with the implications for using these different simulation approaches to inform regulatory decisions.

Keywords: computational fluid dynamics, desalination, field-scale simulation, multiport brine diffuser, negatively buoyant jet

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Rafal Bryk, Holger Schmidt, Thomas Mull, Ingo Ganzmann, Oliver Herbst

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Prediction of the two-phase water mixture level during fast depressurization of the Reactor Pressure Vessel (RPV) resulting from an accident scenario is an important issue from the view point of the reactor safety. Since the level swell may influence the behavior of some passive safety systems, it has been recognized that an assumption which at the beginning may be considered as a conservative one, not necessary leads to a conservative result. This paper discusses outcomes obtained during simulations of the water dynamics and heat transfer during sudden depressurization of a vessel filled up to a certain level with liquid water under saturation conditions and with the rest of the vessel occupied by saturated steam. In case of the pressure decrease e.g. due to the main steam line break, the liquid water evaporates abruptly, being a reason thereby, of strong transients in the vessel. These transients and the sudden emergence of void in the region occupied at the beginning by liquid, cause elevation of the two-phase mixture. In this work, several models calculating the water collapse and swell levels are presented and validated against experimental data. Each of the models uses different approach to calculate void fraction. The object-oriented models were developed with the Modelica modelling language and the OpenModelica environment. The models represent the RPV of the Integral Test Facility Karlstein (INKA) – a dedicated test rig for simulation of KERENA – a new Boiling Water Reactor design of Framatome. The models are based on dynamic mass and energy equations. They are divided into several dynamic volumes in each of which, the fluid may be single-phase liquid, steam or a two-phase mixture. The heat transfer between the wall of the vessel and the fluid is taken into account. Additional heat flow rate may be applied to the first volume of the vessel in order to simulate the decay heat of the reactor core in a similar manner as it is simulated at INKA. The comparison of the simulations results against the reference data shows a good agreement.

Keywords: boiling water reactor, level swell, Modelica, RPV depressurization, thermal-hydraulics

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Authors: Kateriina Rannula, Elle Sõrmus, Siret Piirsalu

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Mixed generation classroom is a phenomenon that current higher education establishments are faced with daily trying to meet the needs of modern labor market with its emphasis on lifelong learning and retraining. Representatives of mainly X and Y generations in one classroom acquiring higher education is a challenge to lecturers considering all the characteristics that differ one generation from another. The importance of outlining different strategies and considering the needs of the students lies in the necessity for everyone to acquire the maximum of the provided knowledge as well as to understand each other to study together in one classroom and successfully cooperate in future workplaces. In addition to different generations, there are also learners with different native languages which have an impact on reading and understanding texts in third languages, including possible translation. Current research aims to investigate, describe and compare reading strategies among the representatives of generation X and Y. Hypotheses were formulated - representatives of generation X and Y use different reading strategies which is also different among first and third year students of the before mentioned generations. Current study is an empirical, qualitative study. To achieve the aim of the research, relevant literature was analyzed and a semi-structured questionnaire conducted among the first and third year students of Tallinn Health Care College. Questionnaire consisted of 25 statements on the text reading strategies, 3 multiple choice questions on preferences considering the design and medium of the text, and three open questions on the translation process when working with a text in student’s third language. The results of the questionnaire were categorized, analyzed and compared. Both, generation X and Y described their reading strategies to be 'scanning' and 'surfing'. Compared to generation X, first year generation Y learners valued interactivity and nonlinear texts. Students frequently used strategies of skimming, scanning, translating and highlighting together with relevant-thinking and assistance-seeking. Meanwhile, the third-year generation Y students no longer frequently used translating, resourcing and highlighting while Generation X learners still incorporated these strategies. Knowing about different needs of the generations currently inside the classrooms and on the labor market enables us with tools to provide sustainable education and grants the society a work force that is more flexible and able to move between professions. Future research should be conducted in order to investigate the amount of learning and strategy- adoption between generations. As for reading, main suggestions arising from the research are as follows: make a variety of materials available to students; allow them to select what they want to read and try to make those materials visually attractive, relevant, and appropriately challenging for learners considering the differences of generations.

Keywords: generation X, generation Y, learning strategies, reading strategies

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Authors: Zachary Huffman, Joana Rocha

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Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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Authors: Poonam Mishra, Shiv Kumar Sharma, Sanjeev Swami

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Purpose: The Purpose of this paper is to investigate the relationship of percieved organizational politics with three levels of antecedents (i.e., organizational level, work environment level and individual level)and its consequents simultaneously. The study addresses antecedents and consequents of percieved political behavior in the higher education sector of India with specific reference to a central university. Design/ Methodology/ Approach: A conceptual framework and hypotheses were first developed on the basis of review of previous studies on organizational politics. A questionnaire was then developed carrying 66 items related to 8-constructs and demographic characteristics of respondents. Jundegemental sampling was used to select respondents. Primary data is collected through structured questionnaire from 45 faculty members of a central university. The sample constitutes Professors, Associate Professors and Assistant Professors from various departments of the University. To test hypotheses data was analyzed statistically using partial least square-structural equations modeling (PLS-SEM). Findings: Results indicated a strong support for OP’s relationship with three of the four proposed antecedents that are, workforce diversity, relationship conflict and need for power with relationship conflict having the strongest impact. No significant relationship was found between role conflict and perception of organizational politics. The three consequences that is, intention to turnover, job anxiety, and organizational commitment are significantly impacted by perception of organizational politics. Practical Implications– This study will be helpful in motivating future research for improving the quality of higher education in India by reducing the level of antecedents that adds to the level of perception of organizational politics, ultimately resulting in unfavorable outcomes. Originality/value: Although a large number of studies on atecedents and consequents of percieved organizational politics have been reported, little attention has been paid to test all the separate but interdependent relationships simultaneously; in this paper organizational politics will be simultaneously treated as a dependent variable and same will be treated as independent variable in subsequent relationships.

Keywords: organizational politics, workforce diversity, relationship conflict, role conflict, need for power, intention to turnover, job anxiety, organizational commitment

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Authors: Eun Mi Ryu, Ah Young An, Ji Yeon Kang, Yeong Soo Shin, Hee Sun Kim

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As the number of fire incidents has been increased, fire incidents significantly damage economy and human lives. Especially when high strength reinforced concrete is exposed to high temperature due to a fire, deterioration occurs such as loss in strength and elastic modulus, cracking, and spalling of the concrete. Therefore, it is important to understand risk of structural safety in building structures by studying structural behaviors and rehabilitation of fire damaged high strength concrete structures. This paper aims at investigating rehabilitation effect on fire damaged high strength concrete beams using experimental and analytical methods. In the experiments, flexural specimens with high strength concrete are exposed to high temperatures according to ISO 834 standard time temperature curve. After heated, the fire damaged reinforced concrete (RC) beams having different cover thicknesses and fire exposure time periods are rehabilitated by removing damaged part of cover thickness and filling polymeric mortar into the removed part. From four-point loading test, results show that maximum loads of the rehabilitated RC beams are 1.8~20.9% higher than those of the non-fire damaged RC beam. On the other hand, ductility ratios of the rehabilitated RC beams are decreased than that of the non-fire damaged RC beam. In addition, structural analyses are performed using ABAQUS 6.10-3 with same conditions as experiments to provide accurate predictions on structural and mechanical behaviors of rehabilitated RC beams. For the rehabilitated RC beam models, integrated temperature–structural analyses are performed in advance to obtain geometries of the fire damaged RC beams. After spalled and damaged parts are removed, rehabilitated part is added to the damaged model with material properties of polymeric mortar. Three dimensional continuum brick elements are used for both temperature and structural analyses. The same loading and boundary conditions as experiments are implemented to the rehabilitated beam models and nonlinear geometrical analyses are performed. Structural analytical results show good rehabilitation effects, when the result predicted from the rehabilitated models are compared to structural behaviors of the non-damaged RC beams. In this study, fire damaged high strength concrete beams are rehabilitated using polymeric mortar. From four point loading tests, it is found that such rehabilitation is able to make the structural performance of fire damaged beams similar to non-damaged RC beams. The predictions from the finite element models show good agreements with the experimental results and the modeling approaches can be used to investigate applicability of various rehabilitation methods for further study.

Keywords: fire, high strength concrete, rehabilitation, reinforced concrete beam

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Authors: Ajith Kumar S., Sankaran Namboothiri, Sankrish J., SarathKumar S., S. Anil Lal

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A numerical analysis of flow over a heated circular cylinder is done in this paper. The governing equations, Navier-Stokes, and energy equation within the Boussinesq approximation along with continuity equation are solved using hybrid FEM-FVM technique. The density gradient created due to the heating of the cylinder will induce buoyancy force, opposite to the direction of action of acceleration due to gravity, g. In the present work, the flow direction and the direction of buoyancy force are taken as same (vertical flow configuration), so that the buoyancy force accelerates the mean flow past the cylinder. The relative dominance of the buoyancy force over the inertia force is characterized by the Richardson number (Ri), which is one of the parameter that governs the flow dynamics and heat transfer in this analysis. It is well known that above a certain value of Reynolds number, Re (ratio of inertia force over the viscous forces), the unsteady Von Karman vortices can be seen shedding behind the cylinder. The shedding wake patterns could be seriously altered by heating/cooling the cylinder. The non-dimensional shedding frequency called the Strouhal number is found to be increasing as Ri increases. The aerodynamic force coefficients CL and CD are observed to change its value. In the present vertical configuration of flow over the cylinder, as Ri increases, shedding frequency gets increased and suddenly drops down to zero at a critical value of Richardson number. The unsteady vortices turn to steady standing recirculation bubbles behind the cylinder after this critical Richardson number. This phenomenon is well known in literature as "Breakdown of the Karman Vortex Street". It is interesting to see the flow structures on further increase in the Richardson number. On further heating of the cylinder surface, the size of the recirculation bubble decreases without loosing its symmetry about the horizontal axis passing through the center of the cylinder. The separation angle is found to be decreasing with Ri. Finally, we observed a second critical Richardson number, after which the the flow will be attached to the cylinder surface without any wake behind it. The flow structures will be symmetrical not only about the horizontal axis, but also with the vertical axis passing through the center of the cylinder. At this stage, there will be a "single plume" emanating from the rear stagnation point of the cylinder. We also observed the transition of the plume is a strong function of the Richardson number.

Keywords: drag reduction, flow over circular cylinder, flow control, mixed convection flow, vortex shedding, vortex breakdown

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Authors: Priyanka Chaudhary, M. Rizwan

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This paper presents a grid synchronization technique based on adaptive notch filter for SPV (Solar Photovoltaic) system along with MPPT (Maximum Power Point Tracking) techniques. An efficient grid synchronization technique offers proficient detection of various components of grid signal like phase and frequency. It also acts as a barrier for harmonics and other disturbances in grid signal. A reference phase signal synchronized with the grid voltage is provided by the grid synchronization technique to standardize the system with grid codes and power quality standards. Hence, grid synchronization unit plays important role for grid connected SPV systems. As the output of the PV array is fluctuating in nature with the meteorological parameters like irradiance, temperature, wind etc. In order to maintain a constant DC voltage at VSC (Voltage Source Converter) input, MPPT control is required to track the maximum power point from PV array. In this work, a variable step size P & O (Perturb and Observe) MPPT technique with DC/DC boost converter has been used at first stage of the system. This algorithm divides the dPpv/dVpv curve of PV panel into three separate zones i.e. zone 0, zone 1 and zone 2. A fine value of tracking step size is used in zone 0 while zone 1 and zone 2 requires a large value of step size in order to obtain a high tracking speed. Further, adaptive notch filter based control technique is proposed for VSC in PV generation system. Adaptive notch filter (ANF) approach is used to synchronize the interfaced PV system with grid to maintain the amplitude, phase and frequency parameters as well as power quality improvement. This technique offers the compensation of harmonics current and reactive power with both linear and nonlinear loads. To maintain constant DC link voltage a PI controller is also implemented and presented in this paper. The complete system has been designed, developed and simulated using SimPower System and Simulink toolbox of MATLAB. The performance analysis of three phase grid connected solar photovoltaic system has been carried out on the basis of various parameters like PV output power, PV voltage, PV current, DC link voltage, PCC (Point of Common Coupling) voltage, grid voltage, grid current, voltage source converter current, power supplied by the voltage source converter etc. The results obtained from the proposed system are found satisfactory.

Keywords: solar photovoltaic systems, MPPT, voltage source converter, grid synchronization technique

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Authors: Carla Idely Palencia-Aguilar

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Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

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Authors: Shuang Chen, Zongqian Shi, Jiajia Sun, Mingjia Li

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Microfluidics is a technology that small amounts of fluids are manipulated using channels with dimensions of tens to hundreds of micrometers. At present, this significant technology is required for several applications in some fields, including disease diagnostics, genetic engineering, and environmental monitoring, etc. Among these fields, manipulation of microparticles and cells in microfluidic device, especially separation, have aroused general concern. In magnetic field, the separation methods include positive and negative magnetophoresis. By comparison, negative magnetophoresis is a label-free technology. It has many advantages, e.g., easy operation, low cost, and simple design. Before the separation of particles or cells, focusing them into a single tight stream is usually a necessary upstream operation. In this work, the focusing of diamagnetic particles in ferrofluid microflows with a single set of overhead permanent magnets is investigated numerically. The geometric model of the simulation is based on the configuration of previous experiments. The straight microchannel is 24mm long and has a rectangular cross-section of 100μm in width and 50μm in depth. The spherical diamagnetic particles of 10μm in diameter are suspended into ferrofluid. The initial concentration of the ferrofluid c₀ is 0.096%, and the flow rate of the ferrofluid is 1.8mL/h. The magnetic field is induced by five identical rectangular neodymium−iron− boron permanent magnets (1/8 × 1/8 × 1/8 in.), and it is calculated by equivalent charge source (ECS) method. The flow of the ferrofluid is governed by the Navier–Stokes equations. The trajectories of particles are solved by the discrete phase model (DPM) in the ANSYS FLUENT program. The positions of diamagnetic particles are recorded by transient simulation. Compared with the results of the mentioned experiments, our simulation shows consistent results that diamagnetic particles are gradually focused in ferrofluid under magnetic field. Besides, the diamagnetic particle focusing is studied by varying the flow rate of the ferrofluid. It is in agreement with the experiment that the diamagnetic particle focusing is better with the increase of the flow rate. Furthermore, it is investigated that the diamagnetic particle focusing is affected by other factors, e.g., the width and depth of the microchannel, the concentration of the ferrofluid and the diameter of diamagnetic particles.

Keywords: diamagnetic particle, focusing, microfluidics, permanent magnet

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Authors: Shin Yoneda, Mikiya Kato, Kosuke Murate, Kodo Kawase

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In recent years, there have been numerous attempts to smuggle narcotic drugs and chemicals by concealing them in international mail. Combatting this requires a non-destructive technique that can identify such illicit substances in mail. Terahertz (THz) waves can pass through a wide variety of materials, and many chemicals show specific frequency-dependent absorption, known as a spectral fingerprint, in the THz range. Therefore, it is reasonable to investigate non-destructive mail inspection techniques that use THz waves. For this reason, in this work, we tried to identify reagents under high attenuation shielding materials using injection-seeded THz-wave parametric generator (is-TPG). Our THz spectroscopic imaging system using is-TPG consisted of two non-linear crystals for emission and detection of THz waves. A micro-chip Nd:YAG laser and a continuous wave tunable external cavity diode laser were used as the pump and seed source, respectively. The pump beam and seed beam were injected to the LiNbO₃ crystal satisfying the noncollinear phase matching condition in order to generate high power THz-wave. The emitted THz wave was irradiated to the sample which was raster scanned by the x-z stage while changing the frequencies, and we obtained multispectral images. Then the transmitted THz wave was focused onto another crystal for detection and up-converted to the near infrared detection beam based on nonlinear optical parametric effects, wherein the detection beam intensity was measured using an infrared pyroelectric detector. It was difficult to identify reagents in a cardboard box because of high noise levels. In this work, we introduce improvements for noise reduction and image clarification, and the intensity of the near infrared detection beam was converted correctly to the intensity of the THz wave. A Gaussian spatial filter is also introduced for a clearer THz image. Through these improvements, we succeeded in identification of reagents hidden in a 42-mm thick cardboard box filled with several obstacles, which attenuate 56 dB at 1.3 THz, by improving analysis methods. Using this system, THz spectroscopic imaging was possible for saccharides and may also be applied to cases where illicit drugs are hidden in the box, and multiple reagents are mixed together. Moreover, THz spectroscopic imaging can be achieved through even thicker obstacles by introducing an NIR detector with higher sensitivity.

Keywords: nondestructive inspection, principal component analysis, terahertz parametric source, THz spectroscopic imaging

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Authors: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Feng Wang, Vladislav Vasilyev

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Ferrocene (Fe(C5H5)2, i.e., di-cyclopentadienyle iron (FeCp2) or Fc) is a unique example of ‘wrong but seminal’ in chemistry history. It has significant applications in a number of areas such as homogeneous catalysis, polymer chemistry, molecular sensing, and nonlinear optical materials. However, the ‘molecular carousel’ has been a ‘notoriously difficult example’ and subject to long debate for its conformation and properties. Ferrocene is a dynamic molecule. As a result, understanding of the dynamical properties of ferrocene is very important to understand the conformational properties of Fc. In the present study, molecular dynamic (MD) simulations are performed. In the simulation, we use 5 geometrical parameters to define the overall conformation of Fc and all the rest is a thermal noise. The five parameters are defined as: three parameters d---the distance between two Cp planes, α and δ to define the relative positions of the Cp planes, in which α is the angle of the Cp tilt and δ the angle the two Cp plane rotation like a carousel. Two parameters to position the Fe atom between two Cps, i.e., d1 for Fe-Cp1 and d2 for Fe-Cp2 distances. Our preliminary MD simulation discovered the five parameters behave differently. Distances of Fe to the Cp planes show that they are independent, practically identical without correlation. The relative position of two Cp rings, α, indicates that the two Cp planes are most likely not in a parallel position, rather, they tilt in a small angle α≠ 0°. The mean plane dihedral angle δ ≠ 0°. Moreover, δ is neither 0° nor 36°, indicating under those conditions, Fc is neither in a perfect eclipsed structure nor a perfect staggered structure. The simulations show that when the temperature is above 80K, the conformers are virtually in free rotations, A very interesting result from the MD simulation is the five C-Fe bond distances from the same Cp ring. They are surprisingly not identical but in three groups of 2, 2 and 1. We describe the pentagon formed by five carbon atoms as ‘turtle swimming’ for the motion of the Cp rings of Fc as shown in their dynamical animation video. The Fe- C(1) and Fe-C(2) which are identical as ‘the turtle back legs’, Fe-C(3) and Fe-C(4) which are also identical as turtle front paws’, and Fe-C(5) ---’the turtle head’. Such as ‘turtle swimming’ analog may be able to explain the single substituted derivatives of Fc. Again, the mean Fe-C distance obtained from MD simulation is larger than the quantum mechanically calculated Fe-C distances for eclipsed and staggered Fc, with larger deviation with respect to the eclipsed Fc than the staggered Fc. The same trend is obtained for the five Fe-C-H angles from same Cp ring of Fc. The simulated mean IR spectrum at 7K shows split spectral peaks at approximately 470 cm-1 and 488 cm-1, in excellent agreement with quantum mechanically calculated gas phase IR spectrum for eclipsed Fc. As the temperature increases over 80K, the clearly splitting IR spectrum become a very board single peak. Preliminary MD results will be presented.

Keywords: ferrocene conformation, molecular dynamics simulation, conformer orientation, eclipsed and staggered ferrocene

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