Search results for: CO₂ Phase transition

Authors: Aminu J. A. Koguna, Aliyu M. Aliyu, Olawale T. Fajemidupe, Yahaya D. Baba

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Production fluids are transported from the platform to tankers or process facilities through transfer pipelines. Water being one of the heavier phases tends to settle at the bottom of pipelines especially at low flow velocities and this has adverse consequences for pipeline integrity. On restart after a shutdown this could result in corrosion and issues for process equipment, thus the need to have the heavier liquid dispersed into the flowing lighter fluid. This study looked at the flow regime of low water cut and low flow velocity oil and water flow using conductive film thickness probes in a large diameter 4-inch pipe to obtain oil and water interface height and the interface structural velocity. A wide range of 0.1–1.0 m/s oil and water mixture velocities was investigated for 0.5–5% water cut. Two fluid model predictions were used to compare with the experimental results.

Keywords: interface height, liquid, velocity, flow regime, dispersed, water cut

Procedia PDF Downloads 383

Authors: S. Rawashdi, D. Bshouty

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This paper aimed at discussing how to urge middle and high school Arab students in Israel to be aware of the importance of and investing in learning mathematics. In the first phase of the study, three questionnaires were passed to two nine-grade classes, one on Awareness, one on Awakeness and one on Learning. One of the two classes was an outstanding class from a public school (PUBS) of 31 students, and the other a heterogeneous class from a private school (PRIS) with 31 students. The Learning questionnaire which was administrated to the Awareness and Awareness topics was passed to PRIS and the Awareness and Awareness Questionnaires were passed to the PUBS class After two months we passed the post-questionnaire to both classes to validate the long-term impact of the study. The findings of the study show that awakeness and awareness processes have an effect on the math learning process, on its context in students' daily lives and their growing interest in learning math.

Keywords: awakeness, awareness, learning mathematics, pupils

Procedia PDF Downloads 135

Authors: M. Asato, C. Liu, N. Fujima, T. Hoshino, Y. Chen, T. Mohri

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We study the temperature dependence of the interaction energies (IEs) of X (=Ru, Rh) impurities in Pd, due to the Fermi-Dirac (FD) distribution and the thermal vibration effect by the Debye-Grüneisen model. The n-body (n=2~4) IEs among X impurities in Pd, being used to calculate the internal energies in the free energies of the Pd-rich PdX alloys, are determined uniquely and successively from the lower-order to higher-order, by the full-potential Korringa-Kohn-Rostoker Green’s function method (FPKKR), combined with the generalized gradient approximation in the density functional theory. We found that the temperature dependence of IEs due to the FD distribution, being usually neglected, is very important to reproduce the X-concentration dependence of the observed solvus temperatures of the Pd-rich PdX (X=Ru, Rh) alloys.

Keywords: full-potential KKR-green’s function method, Fermi-Dirac distribution, GGA, phase diagram of Pd-rich PdX (X=Ru, Rh) alloys, thermal vibration effect

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Authors: F. Zouai, F. Z. Benabid, S. Bouhelal, D. Benachour

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Reinforced plastics or nanocomposites have attracted considerable attention in scientific and industrial fields because a very small amount of clay can significantly improve the properties of the polymer. The polymeric matrices used in this work are two saturated polyesters, i.e., polyethylene terephthalate (PET) and polyethylene naphthalate (PEN). The success of processing compatible blends, based on poly(ethylene terephthalate) (PET)/poly(ethylene naphthalene) (PEN)/clay nanocomposites in one step by reactive melt extrusion is described. Untreated clay was first purified and functionalized ‘in situ’ with a compound based on an organic peroxide/ sulfur mixture and (tetramethylthiuram disulfide) as the activator for sulfur. The PET and PEN materials were first separately mixed in the molten state with functionalized clay. The PET/4 wt% clay and PEN/7.5 wt% clay compositions showed total exfoliation. These compositions, denoted nPET and nPEN, respectively, were used to prepare new n(PET/PEN) nanoblends in the same mixing batch. The n(PET/PEN) nanoblends were compared to neat PET/PEN blends. The blends and nanocomposites were characterized using various techniques. Microstructural and nanostructural properties were investigated. Fourier transform infrared spectroscopy (FTIR) results showed that the exfoliation of tetrahedral clay nanolayers is complete, and the octahedral structure totally disappears. It was shown that total exfoliation, confirmed by wide-angle X-ray scattering (WAXS) measurements, contributes to the enhancement of impact strength and tensile modulus. In addition, WAXS results indicated that all samples are amorphous. The differential scanning calorimetry (DSC) study indicated the occurrence of one glass transition temperature Tg, one crystallization temperature Tc and one melting temperature Tm for every composition.

Keywords: exfoliation, DRX, DSC, montmorillonite, nanocomposites, PEN, PET, plastograph, reactive melt-mixing

Procedia PDF Downloads 322

Authors: A. A. Abid

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Wave-particle interactions are considered to be the paramount in the transmission of energy in collisionless space plasmas, where electromagnetic fields confined the charged particles movement. One of the distinct features of energy transfer in collisionless plasma is wave-particle interaction which is ubiquitous in space plasmas. The three essential populations of the inner magnetosphere are cold plasmaspheric plasmas, ring-currents, and radiation belts high energy particles. The transition region amid such populations initiates wave-particle interactions among distinct plasmas and the wave mode perceived in the magnetosphere is the electromagnetic ion cyclotron (EMIC) wave. These waves can interact with numerous particle species resonantly, accompanied by plasma particle heating is still in debate. In this work we paid particular attention to how EMIC waves impact plasma species, specifically how they affect the heating of electrons and ions during storm and substorm in the Magnetosphere. Using Magnetospheric Multiscale (MMS) mission and electromagnetic hybrid simulation, this project will investigate the energy transfer mechanism (e.g., Landau interactions, bounce resonance interaction, cyclotron resonance interaction, etc.) between EMIC waves and cold-warm plasma populations. Other features such as the production of EMIC waves and the importance of cold plasma particles in EMIC wave-particle interactions will also be worth exploring. Wave particle interactions, electromagnetic hybrid simulation, electromagnetic ion cyclotron (EMIC) waves, Magnetospheric Multiscale (MMS) mission, space plasmas, inner magnetosphere

Keywords: MMS, magnetosphere, wave particle interraction, non-maxwellian distribution

Procedia PDF Downloads 56

Authors: Hamadi Cherif, Christophe Coquelet, Paolo Stringari, Denis Clodic, Laura Pellegrini, Stefania Moioli, Stefano Langè

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Biogas is a promising technology which can be used as a vehicle fuel, for heat and electricity production, or injected in the national gas grid. It is storable, transportable, not intermittent and substitutable for fossil fuels. This gas produced from the wastewater treatment by degradation of organic matter under anaerobic conditions is mainly composed of methane and carbon dioxide. To be used as a renewable fuel, biogas, whose energy comes only from methane, must be purified from carbon dioxide and other impurities such as water vapor, siloxanes and hydrogen sulfide. Purification of biogas for this application particularly requires the removal of hydrogen sulfide, which negatively affects the operation and viability of equipment especially pumps, heat exchangers and pipes, causing their corrosion. Several methods are available to eliminate hydrogen sulfide from biogas. Herein, reactive absorption in structured packed column by means of chemical absorption in aqueous sodium hydroxide solutions is considered. This study is based on simulations using Aspen Plus™ V8.0, and comparisons are done with data from an industrial pilot plant treating 85 Nm3/h of biogas which contains about 30 ppm of hydrogen sulfide. The rate-based model approach has been used for simulations in order to determine the efficiencies of separation for different operating conditions. To describe vapor-liquid equilibrium, a γ/ϕ approach has been considered: the Electrolyte NRTL model has been adopted to represent non-idealities in the liquid phase, while the Redlich-Kwong equation of state has been used for the vapor phase. In order to validate the thermodynamic model, Henry’s law constants of each compound in water have been verified against experimental data. Default values available in Aspen Plus™ V8.0 for the properties of pure components properties as heat capacity, density, viscosity and surface tension have also been verified. The obtained results for physical and chemical properties are in a good agreement with experimental data. Reactions involved in the process have been studied rigorously. Equilibrium constants for equilibrium reactions and the reaction rate constant for the kinetically controlled reaction between carbon dioxide and the hydroxide ion have been checked. Results of simulations of the pilot plant purification section show the influence of low temperatures, concentration of sodium hydroxide and hydrodynamic parameters on the selective absorption of hydrogen sulfide. These results show an acceptable degree of accuracy when compared with the experimental data obtained from the pilot plant. Results show also the great efficiency of sodium hydroxide for the removal of hydrogen sulfide. The content of this compound in the gas leaving the column is under 1 ppm.

Keywords: biogas, hydrogen sulfide, reactive absorption, sodium hydroxide, structured packed column

Procedia PDF Downloads 349

Authors: Rabah Haoui

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Hypersonic flows around spatial vehicles during their reentry phase in planetary atmospheres are characterized by intense aerothermodynamics phenomena. The aim of this work is to analyze high temperature flows around an axisymmetric blunt body taking into account chemical and vibrational non-equilibrium for air mixture species and the no slip condition at the wall. For this purpose, the Navier-Stokes equations system is resolved by the finite volume methodology to determine the flow parameters around the axisymmetric blunt body especially at the stagnation point and in the boundary layer along the wall of the blunt body. The code allows the capture of shock wave before a blunt body placed in hypersonic free stream. The numerical technique uses the Flux Vector Splitting method of Van Leer. CFL coefficient and mesh size level are selected to ensure the numerical convergence.

Keywords: hypersonic flow, viscous flow, chemical kinetic, dissociation, finite volumes, frozen and non-equilibrium flow

Procedia PDF Downloads 459

Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad

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Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.

Keywords: face labeling, semantic segmentation, classification, face segmentation

Procedia PDF Downloads 251

Authors: Shamsulhaq Amin

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Unbound granular materials (UGMs) are pivotal in ensuring long-term quality, especially in the layers under the surface of flexible pavements and other constructions. This study seeks to better understand the behavior of the UGMs by looking at popular models for predicting lasting deformation under various levels of stresses and load cycles. These models focus on variables such as the number of load cycles, stress levels, and features specific to materials and were evaluated on the basis of their ability to accurately predict outcomes. The study showed that these factors play a crucial role in how well the models work. Therefore, the research highlights the need to look at a wide range of stress situations to more accurately predict how much the UGMs bend or shift. The research looked at important factors, like how permanent deformation relates to the number of times a load is applied, how quickly this phenomenon happens, and the shakedown effect, in two different types of UGMs: granite and limestone. A detailed study was done over 100,000 load cycles, which provided deep insights into how these materials behave. In this study, a number of factors, such as the level of stress applied, the number of load cycles, the density of the material, and the moisture present were seen as the main factors affecting permanent deformation. It is vital to fully understand these elements for better designing pavements that last long and handle wear and tear. A series of laboratory tests were performed to evaluate the mechanical properties of materials and acquire model parameters. The testing included gradation tests, CBR tests, and Repeated load triaxial tests. The repeated load triaxial tests were crucial for studying the significant components that affect deformation. This test involved applying various stress levels to estimate model parameters. In addition, certain model parameters were established by regression analysis, and optimization was conducted to improve outcomes. Afterward, the material parameters that were acquired were used to construct graphs for each model. The graphs were subsequently compared to the outcomes obtained from the repeated load triaxial testing. Additionally, the models were evaluated to determine if they demonstrated the two inherent deformation behaviors of materials when subjected to repetitive load: the initial phase, post-compaction, and the second phase volumetric changes. In this study, using log-log graphs was key to making the complex data easier to understand. This method made the analysis clearer and helped make the findings easier to interpret, adding both precision and depth to the research. This research provides important insight into picking the right models for predicting how these materials will act under expected stress and load conditions. Moreover, it offers crucial information regarding the effect of load cycle and permanent deformation as well as the shakedown effect on granite and limestone UGMs.

Keywords: permanent deformation, unbound granular materials, load cycles, stress level

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Authors: Ivan Balachin, Geanette Polanco, Jiang Xingliang, Hu Qin

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The problem of global warming raised up interest towards renewable energy sources. To reduce cost of wind energy is a challenge. Before building of wind park conditions such as: average wind speed, direction, time for each wind, probability of icing, must be considered in the design phase. Operation values used on the setting of control systems also will depend on mentioned variables. Here it is proposed a procedure to be include in the evaluation of the performance of a wind turbine, based on the amplitude of wind changes, the number of changes and their duration. A generic study case based on actual data is presented. Data analysing techniques were applied to model the power required for yaw system based on amplitude and data amount of wind changes. A theoretical model between time, amplitude of wind changes and angular speed of nacelle rotation was identified.

Keywords: field data processing, regression determination, wind turbine performance, wind turbine placing, yaw system losses

Procedia PDF Downloads 387

Authors: Zeki Oralhan, Mahmut Tokmakçı

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SSVEP based brain computer interface (BCI) systems have been preferred, because of high information transfer rate (ITR) and practical use. ITR is the parameter of BCI overall performance. For high ITR value, one of specification BCI system is that has high accuracy. In this study, we investigated to recognize SSVEP with shorter time and lower error rate. In the experiment, there were 8 flickers on light crystal display (LCD). Participants gazed to flicker which had 12 Hz frequency and 50% duty cycle ratio on the LCD during 10 seconds. During the experiment, EEG signals were acquired via EEG device. The EEG data was filtered in preprocessing session. After that Canonical Correlation Analysis (CCA), Multiset CCA (MsetCCA), phase constrained CCA (PCCA), and Multiway CCA (MwayCCA) methods were applied on data. The highest average accuracy value was reached when MsetCCA was applied.

Keywords: brain computer interface, canonical correlation analysis, human computer interaction, SSVEP

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Authors: Mauricio Gómez, Esmeralda López, Ian Becar, Jaime Pizarro, Paula A. Zapata

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A biodegradable material is developed with adsorptive capacity for metals ion for intended use in mining tailings mitigating the environmental impact with economic retribution, two types of fibers were elaborated by electrospinning: (1) a cellulose acetate (CA) matrix and (2) a cellulose acetate (CA)/chitosan (CH) matrix evaluating the effect of CH in CA on its physicochemical properties. Through diffuse reflectance infrared fourier transform spectroscopy (DRIFTS) the incorporation of chitosan in the matrix was identified, observing the band of the amino group at 1500 - 1600 [cm-1]. By scanning electron microscopy (SEM), Hg porosimetry, and CO2 isotherm at 273 [K], the intrafiber microporosity and interfiber macroporosity were identified, with an increase in the distribution of macropores for CA/CH fibers. In the tensile test, CH into the matrix produces a more ductile and tenacious behavior, where the % elongation at break increased by 33% with the other parameters constant. Thermal analysis by differential scanning calorimetry (DSC) and Thermogravimetric Analysis (TGA) showed that the incorporation of chitosan produces higher retention of water molecules due to the functional groups (amino groups (- NH3)), but there is a decrease in the specific heat and thermoplastic properties of the matrix since the glass transition temperature and softening temperature disappear. The effect of the optimum pH for CA and CA/CH fibers were studied in a batch system. In the adsorption kinetic study, the best isotherm model adapted to the experimental results corresponds to the Sips model and the kinetics corresponds to pseudo-second order

Keywords: environmental materials, wastewater treatment, electrospun fibers, biopolymers (cellulose acetate/chitosan), metals recovery

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Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

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The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

Procedia PDF Downloads 210

Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

Procedia PDF Downloads 274

Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

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Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, material recycling, optimization modeling

Procedia PDF Downloads 53

Authors: Hao Xiaohong, Wu Zongxiang, Chen Xuefeng

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With the high power density and high integration of electronic devices, their heat flux has been increasing rapidly. Therefore, an effective cooling technology is essential for the reliability and efficient operation of electronic devices. Liquid cooling is studied increasingly widely for its higher heat transfer efficiency. Serpentine channels are superior in the augmentation of single-phase convective heat transfer because of their better channel velocity distribution. In this paper, eight different frame sizes water-cooled serpentine channel heat sinks are designed to study the heat transfer and pressure drop characteristics. With water as the working fluid, experiment setup is established and the results showed the effect of different channel width, fin thickness and number of channels on thermal resistance and pressure drop.

Keywords: heat transfer, experiment, serpentine heat sink, pressure drop

Procedia PDF Downloads 450

Authors: Yuxi Zhu, Zhenqian Chen

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It is of great interest to investigate the thermal properties of non-precious metal catalysts for Proton exchange membrane fuel cell (PEMFC) based on the thermal management requirements. Due to the low symmetry of materials, to accurately obtain the thermal conductivity of materials, it is necessary to obtain the second and third order force constants by combining density functional theory and machine learning interatomic potential. To be specific, the interatomic force constants are obtained by moment tensor potential (MTP), which is trained by the computational trajectory of Ab initio molecular dynamics (AIMD) at 50, 300, 600, and 900 K for 1 ps each, with a time step of 1 fs in the AIMD computation. And then the thermal conductivity can be obtained by solving the Boltzmann transport equation. In this paper, the thermal transport properties of single metal atom catalysts are studied for the first time to our best knowledge by machine-learning interatomic potential (MLIP). Results show that the single metal atom catalysts exhibit anisotropic thermal conductivities and partially exhibit good thermal conductivity. The average lattice thermal conductivities of G-FeN₄, G-CoN₄ and G-NiN₄ at 300 K are 88.61 W/mK, 205.32 W/mK and 210.57 W/mK, respectively. While other single metal atom catalysts show low thermal conductivity due to their low phonon lifetime. The results also show that low-frequency phonons (0-10 THz) dominate thermal transport properties. The results provide theoretical insights into the application of single metal atom catalysts in thermal management.

Keywords: proton exchange membrane fuel cell, single metal atom catalysts, density functional theory, thermal conductivity, machine-learning interatomic potential

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Authors: Gábor Kovács

Abstract:

Requirement for pole-changing motors emerged at the very early times of asynchronous motor design. Different solutions have been elaborated and some of them are generally used. An alternative is the so called 3 Y/3 Y pole-changing winding. This paper deals with high power application of this solution. A complete and comprehensive study is introduced, including features and design guidelines. The method presented in this paper is especially suitable for pole numbers being close to each other. The study also reveals that the method is more advantageous then the existing solutions for high power motors with 1:3 pole ratio. Using this motor, a new and complete drive supply system has been proposed as most appropriate arrangement of high power main naval propulsion drive. Further, the method makes possible to extend the pole ratio to 1:6, 1:9, 1:12, etc. At the end, the proposal is further extended to the here so far missing 1:4, 1:5, 1:7 etc. pole ratios. A complete proposal for the theoretically infinite range has been given in this way.

Keywords: induction motor, pole changing 3Y/3Y, pole phase modulation, pole changing 1:3, 1:6

Procedia PDF Downloads 164

Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

Abstract:

Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, life cycle assessment, material recycling

Procedia PDF Downloads 70

Authors: Naveed Ejaz, Liaqat Ali, Amer Nusair

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Thermal barrier coatings (TBCs) serve as thermal barriers against the high temperature of the hot regions of the aircraft turbine engines keeping the surface of the turbine blades, vanes and combustion chamber at comparatively lower temperature. The life of these coatings depends on many in-service environmental factors. Among these factors, the behavior of the bond coat as well as the top coat at high temperature aggravated by the corrosive environments having S, V, Na and Cl plays a key role. The incorporation of the 5-15% CaZrO3 in YSZ coatings was studied after hot corrosion in vanadium oxide environment. It was observed that the reactivity of the V gradually switched from Y to Ca making CaV2O4 instead of YVO4; the percentage of CaV2O4 increased with the increase of CaZrO3 in YSZ. It eventually prevented leaching out of the Y from YSZ leaving the YSZ without any harmful phase change. The thermal insulation was found to be improved in case of CaZrO3 incorporated YSZ coatings as compared to only YSZ coating.

Keywords: hot corrosion, thermal barrier coatings, yttria stabilized zirconia, calcium zirconate

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Authors: Liang Zhao, Chong-quan Zhong

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In order to improve the control performance of vector inverter, an improved parameter identification solution for induction motor is proposed in this paper. Dc or AC voltage is applied to the induction motor using the SVPWM through the inverter. Then stator resistance, stator leakage inductance, rotor resistance, rotor leakage inductance and mutual inductance are obtained according to the signal response. The discrete Fourier transform (DFT) is used to deal with the noise and harmonic. The impact on parameter identification caused by delays in the inverter switch tube, tube voltage drop and dead-time is avoided by effective compensation measures. Finally, the parameter identification experiment is conducted based on the vector inverter which using TMS320F2808 DSP as the core processor and results show that the strategy is verified.

Keywords: vector inverter, parameter identification, SVPWM; DFT, dead-time compensation

Procedia PDF Downloads 456

Authors: Karima Megdouli, Bourhan tachtouch

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Ejector refrigeration cycles offer an alternative to conventional systems for producing cold from low-temperature heat. In this article, a thermodynamic model is presented. This model has the advantage of simplifying the calculation algorithm and describes the complex double-throttling mechanism that occurs in the ejector. The model assumption and calculation algorithm are presented first. The impact of each efficiency is evaluated. Validation is performed on several data sets. The ejector model is then used to simulate a RES (refrigeration ejector system), to validate its robustness and suitability for use in predicting thermodynamic cycle performance. A Taguchi and ANOVA optimization is carried out on a RES. TOPSIS analysis was applied to decide the optimum refrigerants with cost, safety, environmental and enviro economic concerns along with thermophysical properties.

Keywords: ejector, velocity distribution, shock circle, Taguchi and ANOVA optimization, TOPSIS analysis

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Authors: Onkar Nath Verma, Nitish Kumar Singh, Raghvendra, Pravin Kumar, Prabhakar Singh

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The perovskite type electrolyte material LaAlO3 was prepared by solution based auto-combustion method using Al (NO3)3.6H2O, La2O3 with dilute nitrate acid (HNO3) as precursors and citric acid (C6H8O7.H2O) as a fuel. The synthesis protocol gave an easy processing of the LaAlO3 nano-particles. The XRD measurement revealed that the material has single phase with space group R-3c (rhombohedral). Thermal behavior was measured by simultaneous differential thermal analysis and thermo gravimetric analysis (DTA-TGA). The compact pellet density was determined. Also, the surface morphology was studied using scanning electron microscopy (SEM). The conductivity of LaAlO3 was measured employing LCR meter and found to increase with increasing temperature. This increase in conductivity may be attributed to increased mobility of oxide ion.

Keywords: perovskite, LaAlO3, XRD, SEM, DTA-TGA, SOFC

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Authors: Niraimathi Kesavan, Sangeeta Sharma, Deepa Jagan, Sridhar Sukumar, Mohan Ramachandran, Vidhubala Elangovan

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Background: Childhood is a dynamic period for growth and development. Optimum nutrition during this period forms a strong foundation for growth, development, resistance to infections, long-term good health, cognition, educational achievements, and work productivity in a later phase of life. Underprivileged children living in a resource constraint settings like shelter homes are at high risk of malnutrition due to poor quality diet and nutritional inadequacy. In low-income countries, underprivileged children are vulnerable to being deprived of nutritious food, which stands as a major challenge in the health sector. The present aims to assess the dietary intake, nutritional status, and nutritional inadequacy and their association with malnutrition among children residing in shelter homes in rural Tamil Nadu. Methods: The study was a descriptive survey conducted among all the children aged between 8-18 years residing in two selected shelter homes (Anbu illam, a home for female children, and Amaidhi illam, a home for male children), rural Tirunelveli, Tamil Nadu, India. A total of 57 children were recruited, including 18 boys and 39 girls, for the study. Dietary intake was measured using seven days 24 hours recall. The average nutrient intake was considered for further analysis. Results: Of the 57 children, about 60% (n=35) were undernutrition. The mean daily energy intake was 1298 (SD 180) kcal for boys and 952 (SD155) kcal for girls. The total calorie intake was 55-60% below the estimated average requirement (EAR) for adolescent boys and girls in the age group 13-15 years and 16-18 years. Carbohydrates were the major source of energy (boys 53% and girls 51%), followed by fat (boys 31.5% and girls 34.5%) and protein (boys 14% and girls 12.9%). Dairy intake (<200ml/day) was less than the recommendation (500ml/day). Micro-nutrient-rich foods such as fruits, vegetables, and green leafy vegetables in the diet were <200g/day, which was far less than the recommended dietary guidelines of 400g- 600g/day for the age group of 7-18 years. Nearly 26% of girls reported experiencing menstrual problems. The majority (76.9%) of the children exhibited nutrient deficiency-related signs and symptoms. Conclusion: The total energy, minerals, and micro-nutrient intake were inadequate and below the Recommended Dietary Allowance for children and adolescents. The diet predominantly consists of refined cereals, rice, semolina, and vermicelli. Consumption of whole grains, milk, fruits, vegetables, and leafy vegetables was far below the recommended dietary guidelines. Dietary inadequacies among these children pose a serious concern for their overall health status and its consequences in the later phase of life.

Keywords: adolescents, children, dietary intake, malnutrition, nutritional inadequacy, shelter home

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Authors: R. F. Louh, Cathy Chou, Victor Wang, Howard Yan

Abstract:

The aim of this study is to manufacture titania and reduced graphene oxide (TiO2/rGO) composite nanofibers via electrospinning (ESP) of precursor fluid consisted of titania sol containing polyvinylpyrrolidone (PVP) and titanium isopropoxide (TTIP) and GO solution. The GO nanoparticles were derived from Hummers’ method. A metal grid ring was used to provide the bias voltage to reach higher ESP yield and nonwoven fabric with dense network of TiO2/GO composite nanofibers. The ESP product was heat treated at 500°C for 2 h in nitrogen atmosphere to acquire TiO2/rGO nanofibers by thermal reduction of GO and phase transformation into anatase TiO2. The TiO2/rGO nanofibers made from various volume fractions of GO solution by ESP were analyzed by FE-SEM, TEM, XRD, EDS, BET and FTIR. Such TiO2/rGO fibers having photocatalytic property, high specific surface area and electrical conductivity can be used for photovoltaics and chemical sensing applications.

Keywords: electrospinning process, titanium oxide, thermally reduced graphene oxide, composite nanofibers

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Authors: Ali Asmari, Alex Symington, Htaik Than, Austin Caradonna, John Senft

Abstract:

This paper presents the collaborative effort between ULC Technologies and Con Edison in developing a groundbreaking robotic cable splicing machine. The focus is on the machine's design, which integrates advanced robotics and automation to enhance safety and efficiency in power network maintenance. The paper details the operational steps of the machine, including cable grounding, cutting, and removal of different insulation layers, and discusses its novel technological approach. The significant benefits over traditional methods, such as improved worker safety and reduced outage times, are highlighted based on the field data collected during the validation phase of the project. The paper also explores the future potential and scalability of this technology, emphasizing its role in transforming the landscape of power network maintenance.

Keywords: cable splicing machine, power network maintenance, electric distribution, electric transmission, medium voltage cable

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Authors: Kamel Belammi, Houria Fatrim

Abstract:

imbalanced data set, a problem often found in real world application, can cause seriously negative effect on classification performance of machine learning algorithms. There have been many attempts at dealing with classification of imbalanced data sets. In medical diagnosis classification, we often face the imbalanced number of data samples between the classes in which there are not enough samples in rare classes. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weight and some rules of thumb to determine those weights. After the balancing phase, we applythe different classifiers (support vector machine (SVM), k- nearest neighbor (KNN) and multilayer neuronal networks (MNN)) for balanced data set. We have also compared the obtained results before and after balancing method.

Keywords: multilayer neural networks, k- nearest neighbor, support vector machine, imbalanced medical data, least mean square algorithm, diabetes

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Authors: Nguyen Van Que, Nguyen Huy The

Abstract:

This paper presents combined natural and forced convection of humid air flow. The film condensation of water vapour on a cold floor was investigated using ANSYS Fluent software. User-defined Functions(UDFs) were developed and added to address the issue of film condensation at the surface of the floor. Those UDFs were validated by analytical results on a flat plate. The film condensation model based on mass transfer was used to solve phase change. On the floor, condensation rate was obtained by mass fraction change near the floor. The study investigated effects of inlet velocity, inlet relative humidity and cold floor temperature on the condensation rate. The simulations were done in both 2D and 3D models to show the difference and need for 3D modeling of condensation.

Keywords: heat and mass transfer, convection, condensation, relative humidity, user-defined functions

Procedia PDF Downloads 324

Authors: Coriolano Salvini

Abstract:

The increasing utilization of renewable energy sources for electric power production calls for the introduction of energy storage systems to match the electric demand along the time. Although many countries are pursuing as a final goal a “decarbonized” electrical system, in the next decades the traditional fossil fuel fed power plant still will play a relevant role in fulfilling the electric demand. Presently, such plants provide grid ancillary services (frequency control, grid balance, reserve, etc.) by adapting the output power to the grid requirements. An interesting option is represented by the possibility to use traditional plants to improve the grid storage capabilities. The present paper is addressed to small-medium size systems suited for distributed energy storage. The proposed Energy Storage System (ESS) is based on a Compressed Air Energy Storage (CAES) integrated into a Gas-Steam Combined Cycle (GSCC) or a Gas Turbine based CHP plants. The systems can be incorporated in an ex novo built plant or added to an already existing one. To avoid any geological restriction related to the availability of natural compressed air reservoirs, artificial storage is addressed. During the charging phase, electric power is absorbed from the grid by an electric driven intercooled/aftercooled compressor. In the course of the discharge phase, the compressed stored air is sent to a heat transfer device fed by hot gas taken upstream the Heat Recovery Steam Generator (HRSG) and subsequently expanded for power production. To maximize the output power, a staged reheated expansion process is adopted. The specific power production related to the kilogram per second of exhaust gas used to heat the stored air is two/three times larger than that achieved if the gas were used to produce steam in the HRSG. As a result, a relevant power augmentation is attained with respect to normal GSCC plant operations without additional use of fuel. Therefore, the excess of output power can be considered “fuel free” and the storage system can be compared to “pure” ESSs such as electrochemical, pumped hydro or adiabatic CAES. Representative cases featured by different power absorption, production capability, and storage capacity have been taken into consideration. For each case, a technical optimization aimed at maximizing the storage efficiency has been carried out. On the basis of the resulting storage pressure and volume, number of compression and expansion stages, air heater arrangement and process quantities found for each case, a cost estimation of the storage systems has been performed. Storage efficiencies from 0.6 to 0.7 have been assessed. Capital costs in the range of 400-800 €/kW and 500-1000 €/kWh have been estimated. Such figures are similar or lower to those featuring alternative storage technologies.

Keywords: artificial air storage reservoir, compressed air energy storage (CAES), gas steam combined cycle (GSCC), techno-economic analysis

Procedia PDF Downloads 209

Authors: Elisa Boatti, Ulisse Stefanelli, Alessandro Reali, Ferdinando Auricchio

Abstract:

Thanks to their unusual properties, shape memory alloys (SMAs) are good candidates for advanced applications in a wide range of engineering fields, such as automotive, robotics, civil, biomedical, aerospace. In the last decades, the ever-growing interest for such materials has boosted several research studies aimed at modeling their complex nonlinear behavior in an effective and robust way. Since the constitutive response of SMAs is strongly thermomechanically coupled, the investigation of the non-isothermal evolution of the material must be taken into consideration. The present study considers an existing three-dimensional phenomenological model for SMAs, able to reproduce the main SMA properties while maintaining a simple user-friendly structure, and proposes a variational reformulation of the full non-isothermal version of the model. While the considered model has been thoroughly assessed in an isothermal setting, the proposed formulation allows to take into account the full nonisothermal problem. In particular, the reformulation is inspired to the GENERIC (General Equations for Non-Equilibrium Reversible-Irreversible Coupling) formalism, and is based on a generalized gradient flow of the total entropy, related to thermal and mechanical variables. Such phrasing of the model is new and allows for a discussion of the model from both a theoretical and a numerical point of view. Moreover, it directly implies the dissipativity of the flow. A semi-implicit time-discrete scheme is also presented for the fully coupled thermomechanical system, and is proven unconditionally stable and convergent. The correspondent algorithm is then implemented, under a space-homogeneous temperature field assumption, and tested under different conditions. The core of the algorithm is composed of a mechanical subproblem and a thermal subproblem. The iterative scheme is solved by a generalized Newton method. Numerous uniaxial and biaxial tests are reported to assess the performance of the model and algorithm, including variable imposed strain, strain rate, heat exchange properties, and external temperature. In particular, the heat exchange with the environment is the only source of rate-dependency in the model. The reported curves clearly display the interdependence between phase transformation strain and material temperature. The full thermomechanical coupling allows to reproduce the exothermic and endothermic effects during respectively forward and backward phase transformation. The numerical tests have thus demonstrated that the model can appropriately reproduce the coupled SMA behavior in different loading conditions and rates. Moreover, the algorithm has proved effective and robust. Further developments are being considered, such as the extension of the formulation to the finite-strain setting and the study of the boundary value problem.

Keywords: generalized gradient flow, GENERIC formalism, shape memory alloys, thermomechanical coupling

Procedia PDF Downloads 220