Search results for: Atmospheric Boundary Layer

Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra

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Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I₁, I₂, … I_n at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.

Keywords: multi-temporal satellite image, urban growth, non-stationary, stochastic model

Procedia PDF Downloads 419

Authors: Ibrahim Ozkan

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In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

Procedia PDF Downloads 130

Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

Procedia PDF Downloads 124

Authors: Muhammad Tarmidzi, Reza M. G. Gani, Andri Luthfi

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The purpose of this study is to identify rock zone containing hydrocarbons with calculating rock property includes volume shale, total porosity, effective porosity and water saturation. Identification method rock property based on GR log, resistivity log, neutron log and density rock. Zoning is based on sequence stratigraphic markers that are sequence boundary (SB), transgressive surface (TS) and flooding surface (FS) which correlating ten well log in blok “M”. The results of sequence stratigraphic correlation consist of eight zone that are two LST zone, three TST zone and three HST zone. The result of rock property calculation in each zone is showing two LST zone containing hydrocarbons. LST-1 zone has average volume shale (Vsh) 25%, average total porosity (PHIT) 14%, average effective porosity (PHIE) 11% and average water saturation 0,83. LST-2 zone has average volume shale (Vsh) 19%, average total porosity (PHIT) 21%, average effective porosity (PHIE) 17% and average water saturation 0,82.

Keywords: hydrocarbons zone, petrophysic, rock property, sequence stratigraphic

Procedia PDF Downloads 305

Authors: Tosin Ige

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Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

Procedia PDF Downloads 153

Authors: Mace Bentley, Zhuojun Duan, Tobias Gerken, Dudley Bonsal, Henry Way, Endre Szakal, Mia Pham, Hunter Donaldson, Chelsea Lang, Hayden Abbott, Leah Wilcynzski

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Air pollution has the potential to modify the lifespan and intensity of thunderstorms and the properties of lightning. Using data mining and geovisualization, we investigate how background climate and weather conditions shape variability in urban air pollution and how this, in turn, shapes thunderstorms as measured by the intensity, distribution, and frequency of cloud-to-ground lightning. A spatiotemporal analysis was conducted in order to identify thunderstorms using high-resolution lightning detection network data. Over seven million lightning flashes were used to identify more than 196,000 thunderstorms that occurred between 2006 - 2020 in the Washington, DC Metropolitan Region. Each lightning flash in the dataset was grouped into thunderstorm events by means of a temporal and spatial clustering algorithm. Once the thunderstorm event database was constructed, hourly wind direction, wind speed, and atmospheric thermodynamic data were added to the initiation and dissipation times and locations for the 196,000 identified thunderstorms. Hourly aerosol and air quality data for the thunderstorm initiation times and locations were also incorporated into the dataset. Developing thunderstorm climatologies using a lightning tracking algorithm and lightning detection network data was found to be useful for visualizing the spatial and temporal distribution of urban augmented thunderstorms in the region.

Keywords: lightning, urbanization, thunderstorms, climatology

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Authors: William Middleton, Nodumo Zulu, Sue Harrison

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Open raceway ponds are currently the most used system for the commercial cultivation of algal biomass, as it is a cost-effective means of production. However, raceway ponds suffer from lower algal productivity when compared to closed photobioreactors. This is due to poor gas exchange between the fluid and the atmosphere. Carbon dioxide (CO₂) mass transfer is a large concern in the production of algae in raceway pond systems. The utilization of atmospheric CO₂ does not support maximal growth; however, CO₂ supplementation in the form of flue gas or concentrated CO₂ is not cost-effective. The introduction of slopes into the raceway system presents a possible improvement to the mass transfer from the air, as seen in previous work conducted at CeBER. Slopes improve turbulence (decreasing the concentration gradient of dissolved CO₂) and can cause air entrainment (allowing for greater surface area and contact time between the air and water). This project tests the findings of previous studies conducted in an indoor lab-scale raceway on a larger scale under outdoor conditions. The addition of slopes resulted in slightly increased CO₂ mass transfer as well as algal growth rate and productivity. However, there were reductions in energy consumption and average fluid velocity in the system. These results indicate a potential to improve the economic feasibility of algal biomass production, but further economic assessment would need to be carried out.

Keywords: algae, raceway ponds, mass transfer, algal culture, biotechnology, reactor design

Procedia PDF Downloads 84

Authors: H. Medoukali, B. Zegnini

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Insulation techniques in high-voltage cables rely heavily on chemically synapsed polyethylene. The latter may contain manufacturing defects such as small cavities, for example. The presence of the cavity affects the distribution of the electric field at the level of the insulating layer; this change in the electric field is affected by the presence of different space charge densities within the insulating material. This study is carried out by performing simulations to determine the distribution of the electric field inside the insulator. The simulations are based on the creation of a two-dimensional model of a high-voltage cable of 154 kV using the COMSOL Multiphysics software. Each time we study the effect of changing the space charge density of on the electromechanical Constraints.

Keywords: COMSOL multiphysics, electric field, HVDC, microcavities, space charges, XLPE

Procedia PDF Downloads 118

Authors: Raouf Mbarki, Fadi Al Khatib, Malek Adouni

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Knee collateral ligaments play a significant role in restraining excessive frontal motion (varus/valgus rotations). In this investigation, a multiscale frame was developed based on structural hierarchies of the collateral ligaments starting from the bottom (tropocollagen molecule) to up where the fibred reinforced structure established. Experimental data of failure tensile test were considered as the principal driver of the developed model. This model was calibrated statistically using Bayesian calibration due to the high number of unknown parameters. Then the model is scaled up to fit the real structure of the collateral ligaments and simulated under realistic boundary conditions. Predications have been successful in describing the observed transient response of the collateral ligaments during tensile test under pre- and post-damage loading conditions. Collateral ligaments maximum stresses and strengths were observed near to the femoral insertions, a results that is in good agreement with experimental investigations. Also for the first time, damage initiation and propagation were documented with this model as a function of the cross-link density between tropocollagen molecules.

Keywords: multiscale model, tropocollagen, fibrils, ligaments commas

Procedia PDF Downloads 148

Authors: Janneke K. Oostrom, Richard Ronay

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The so called “red sneakers effect” refers to people’s inclination to infer status and competence from signals of nonconformity. In the current research, we explore an untested possible boundary condition to the red sneakers effect within the context of personnel selection. In two experimental studies (total N = 156), we examined how (non)conforming dress style interacts with the quality of a job applicant’s resume to determine hirability perceptions. We found that dress style indeed impacts hirability perceptions, but that the exact impact depends on the quality of the applicant’s resume. Results revealed that applicants with a low quality resume were punished for behaving in a nonconforming way, whereas applicants with a high quality resume appeared to have the leeway to dress as they please. Importantly, the observed interaction effect was mediated by perceptions of power. These findings suggest that nonconforming dress acts as a power-signaling mechanism in the context of personnel selection. However, the signaling effects of non-conforming dress style can backfire when accompanied by evidence that such posturing is not matched by cues of actual competence.

Keywords: clothing, hirability, nonconformity, personnel selection, power

Procedia PDF Downloads 166

Authors: Sowntharya L.

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Aerodynamics is the most important factor when it comes to resistive forces such as lift, drag and side forces acting on the vehicle. In passenger vehicles, reducing the drag will not only unlock the door for higher achievable speed but will also reduce the fuel consumption of the vehicle. Generally, tyre contributes significantly to the overall aerodynamics of the vehicle. Hence, understanding the air-flow behaviour around the tyre is vital to optimize the aerodynamic performance in the early stage of design process. Nowadays, aerodynamic simulation employing Computational Fluid Dynamics (CFD) is gaining more importance as it reduces the number of physical wind-tunnel experiments during vehicle development process. This research develops a methodology to predict aerodynamic drag of a standalone tyre using Numerical CFD Solver and to validate the same using a wind tunnel experiment. A parametric study was carried out on different tread pattern tyres such as slick, circumferential groove & patterned tyre in stationary and rotating boundary conditions. In order to represent wheel rotation contact with the ground, moving reference frame (MRF) approach was used in this study. Aerodynamic parameters such as drag lift & air flow behaviour around the tire were simulated and compared with experimental results.

Keywords: aerodynamics, CFD, drag, MRF, wind-tunnel

Procedia PDF Downloads 185

Authors: Abdelhak-Djamel Seriai, Selim Kebir, Allaoua Chaoui

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During the last decades, object oriented program- ming has been massively used to build large-scale systems. However, evolution and maintenance of such systems become a laborious task because of the lack of object oriented programming to offer a precise view of the functional building blocks of the system. This lack is caused by the fine granularity of classes and objects. In this paper, we use a post object-oriented technology namely software components, to propose an approach based on the identification of the functional building blocks of an object oriented system by analyzing its source code. These functional blocks are specified as software components and the result is a multi-layer component based software architecture.

Keywords: software comprehension, software component, object oriented, software architecture, reverse engineering

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Authors: Aipeng Zhu, Yun Zhang

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The growing grievous environment problems together with the exhaustion of energy resources put urgent demands for developing high energy density. Considering the factors including capacity, resource and environment, Manganese-based lithium-rich layer-structured cathode materials xLi₂MnO₃⋅(1-x)LiMO₂ (M = Ni, Co, Mn, and other metals) are drawing increasing attention due to their high reversible capacities, high discharge potentials, and low cost. They are expected to be one type of the most promising cathode materials for the next-generation Li-ion batteries (LIBs) with higher energy densities. Unfortunately, their commercial applications are hindered with crucial drawbacks such as poor rate performance, limited cycle life and continuous falling of the discharge potential. With decades of extensive studies, significant achievements have been obtained in improving their cyclability and rate performances, but they cannot meet the requirement of commercial utilization till now. One major problem for lithium-rich layer-structured cathode materials (LLOs) is the side reaction during cycling, which leads to severe surface degradation. In this process, the metal ions can dissolve in the electrolyte, and the surface phase change can hinder the intercalation/deintercalation of Li ions and resulting in low capacity retention and low working voltage. To optimize the LLOs cathode material, the surface coating is an efficient method. Considering the price and stability, Al₂O₃ was used as a coating material in the research. Meanwhile, due to the low initial Coulombic efficiency (ICE), the pristine LLOs was pretreated by KMnO₄ to increase the ICE. The precursor was prepared by a facile coprecipitation method. The as-prepared precursor was then thoroughly mixed with Li₂CO₃ and calcined in air at 500℃ for 5h and 900℃ for 12h to produce Li₁.₂[Ni₀.₂Mn₀.₆]O₂ (LNMO). The LNMO was then put into 0.1ml/g KMnO₄ solution stirring for 3h. The resultant was filtered and washed with water, and dried in an oven. The LLOs obtained was dispersed in Al(NO₃)₃ solution. The mixture was lyophilized to confer the Al(NO₃)₃ was uniformly coated on LLOs. After lyophilization, the LLOs was calcined at 500℃ for 3h to obtain LNMO@LMO@ALO. The working electrodes were prepared by casting the mixture of active material, acetylene black, and binder (polyvinglidene fluoride) dissolved in N-methyl-2-pyrrolidone with a mass ratio of 80: 15: 5 onto an aluminum foil. The electrochemical performance tests showed that the multiple surface modified materials had a higher initial Coulombic efficiency (84%) and better capacity retention (91% after 100 cycles) compared with that of pristine LNMO (76% and 80%, respectively). The modified material suggests that the KMnO₄ pretreat and Al₂O₃ coating can increase the ICE and cycling stability.

Keywords: Li-rich materials, surface coating, lithium ion batteries, Al₂O₃

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Authors: Gilbert O. Osayemwenre, Meyer L. Edson

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Ethylene vinyl acetate (EVA) encapsulation degradation affects the performance of photovoltaic (PV) module. Hotspot formation causes the EVA encapsulation to undergo photothermal deterioration and molecular breakdown by UV radiation. This leads to diffusion of chemical particles into other layers. During outdoor deployment, the EVA encapsulation in the affect region loses its adhesive strength, when this happen the affected region layer undergoes rapid delamination. The presence of photo-thermal degradation is detrimental to PV modules as it causes both optical and thermal degradation. Also, it enables the encapsulant to be more susceptible to chemicals substance and moisture. Our findings show a high concentration of Sodium, Phosphorus and Aluminium which originate from the glass substrate, cell emitter and back contact respectively.

Keywords: ethylene vinyl acetate (EVA), encapsulation, photo-thermal degradation, thermogravimetric analysis (TGA), scanning probe microscope (SPM)

Procedia PDF Downloads 292

Authors: Saman Ghaffarian, Ilgin Gökaşar

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This paper presents a new automatic vehicle detection method from very high resolution aerial images to measure traffic density. The proposed method starts by extracting road regions from image using road vector data. Then, the road image is divided into equal sections considering resolution of the images. Gradient vectors of the road image are computed from edge map of the corresponding image. Gradient vectors on the each boundary of the sections are divided where the gradient vectors significantly change their directions. Finally, number of vehicles in each section is carried out by calculating the standard deviation of the gradient vectors in each group and accepting the group as vehicle that has standard deviation above predefined threshold value. The proposed method was tested in four very high resolution aerial images acquired from Istanbul, Turkey which illustrate roads and vehicles with diverse characteristics. The results show the reliability of the proposed method in detecting vehicles by producing 86% overall F1 accuracy value.

Keywords: aerial images, intelligent transportation systems, traffic density measurement, vehicle detection

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Authors: Stephane Laussac, Jacques Piazzola, Gilles Tedeschi

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Estimation of the impact of atmospheric aerosols on the climate evolution is an important scientific challenge. One of a major source of particles is constituted by the oceans through the generation of sea-spray aerosols. In coastal areas, marine aerosols can affect air quality through their ability to interact chemically and physically with other aerosol species and gases. The integration of accurate sea-spray emission terms in modeling studies is then required. However, it was found that sea-spray concentrations are not represented with the necessary accuracy in some situations, more particularly at short fetch. In this study, the WRF-Chem model was implemented on a North-Western Mediterranean coastal region. WRF-Chem is the Weather Research and Forecasting (WRF) model online-coupled with chemistry for investigation of regional-scale air quality which simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. One of the objectives was to test the ability of the WRF-Chem model to represent the fine details of the coastal geography to provide accurate predictions of sea spray evolution for different fetches and the anthropogenic aerosols. To assess the performance of the model, a comparison between the model predictions using a local emission inventory and the physicochemical analysis of aerosol concentrations measured for different wind direction on the island of Porquerolles located 10 km south of the French Riviera is proposed.

Keywords: sea-spray aerosols, coastal areas, sea-spray concentrations, short fetch, WRF-Chem model

Procedia PDF Downloads 182

Authors: Chih-Fong Tsai, Ya-Han Hu

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The aim of feature selection (or dimensionality reduction) is to filter out unrepresentative features (or variables) making the classifier perform better than the one without feature selection. Since there are many well-known feature selection algorithms, and different classifiers based on different selection results may perform differently, very few studies consider examining the effect of performing different feature selection algorithms on the classification performances by different classifiers over different types of datasets. In this paper, two widely used algorithms, which are the genetic algorithm (GA) and information gain (IG), are used to perform feature selection. On the other hand, three well-known classifiers are constructed, which are the CART decision tree (DT), multi-layer perceptron (MLP) neural network, and support vector machine (SVM). Based on 14 different types of datasets, the experimental results show that in most cases IG is a better feature selection algorithm than GA. In addition, the combinations of IG with DT and IG with SVM perform best and second best for small and large scale datasets.

Keywords: data mining, feature selection, pattern classification, dimensionality reduction

Procedia PDF Downloads 657

Authors: Arber Sejdiji, Jan Schmitz-Huebsch, Christian Mittelstedt

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Due to its use in a broad range of temperatures, the prediction of elastic properties of fiber composite materials under thermal load is significant. Especially the transversal stiffness dominates the potential of use for fiber-reinforced composites (FRC). A numerical study on the influence of thermal stress on transversal stiffness of fiber-reinforced composites is presented. In the numerical study, a representative volume element (RVE) is used to estimate the elastic properties of a unidirectional ply with finite element method (FEM). For the investigation, periodic boundary conditions are applied to the RVE. Firstly, the elastic properties under pure mechanical load are derived numerically and compared to results, which are obtained by analytical methods. Thereupon thermo-mechanical load is implemented into the model to investigate the influence of temperature change with low temperature as a key aspect. Regarding low temperatures, the transversal stiffness increases intensely, especially when thermal stress is dominant over mechanical stress. This paper outlines the employed numerical methods as well as the derived results.

Keywords: elastic properties, micromechanics, thermal stress, representative volume element

Procedia PDF Downloads 95

Authors: Naresh Radaliyagoda, Nigel M. Jennett, Rong Lan, David Parfitt

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A series of length scale engineered multilayer material with temperature robust mechanical properties has been suggested. A range of polycrystalline copper sub-layers with the thickness varying from 1 to 25μm and buried in between two nickel layers was produced using electrodeposition dual bath technique. The structure of the multilayers was characterized using Electron Backscatter Diffraction and Scanning Electron Microscope. The interface effect on the hardness and elastic modulus was tested using Nano-indentation. Results of the grain size and layer thickness measurements, and indentation hardness have been compared. It is found that there is a combined length scale effect that improves mechanical properties in Ni/Cu multilayer structures.

Keywords: nano-indentation, size effect, multilayers, electrodeposition

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Authors: S. Nandal, R. Bhargava

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The paper contains a numerical study of the unsteady magneto-hydrodynamic natural convection flow of nanofluids within a symmetrical wavy walled trapezoidal enclosure. The length and height of enclosure are both considered equal to L. Two-phase nanofluid model is employed. The governing equations of nanofluid flow along with boundary conditions are non-dimensionalized and are solved using one of Meshfree technique (EFGM method). Meshfree numerical technique does not require a predefined mesh for discretization purpose. The bottom wavy wall of the enclosure is defined using a cosine function. Element free Galerkin method (EFGM) does not require the domain. The effects of various parameters namely time t, amplitude of bottom wavy wall a, Brownian motion parameter Nb and thermophoresis parameter Nt is examined on rate of heat and mass transfer to get a visualization of cooling and heating effects. Such problems have important applications in heat exchangers or solar collectors, as wavy walled enclosures enhance heat transfer in comparison to flat walled enclosures.

Keywords: heat transfer, meshfree methods, nanofluid, trapezoidal enclosure

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Authors: Ramovatar, Neeraj Panwar

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Lead free Ba₀.₉₈Ca₀.₀₂SnxTi₁₋ₓO₃ (x = 0.01 and 0.05 mole %) ferroelectric ceramics have been synthesized by the solid-state reaction method with sintering at 1400 °C for 2 h. The room temperature x-ray diffraction (XRD) patterns identified the tetragonal phase for x = 0.01 composition whereas co-existence of tetragonal and orthorhombic phases for x =0.05 composition. Raman spectroscopy results corroborated with the XRD results at room temperature. The maximum dielectric properties (ɛm ~ 8591, tanδ ~ 0.018) were obtained for the compound with x = 0.01 at 5 kHz. Further, the tetragonal to cubic (TC) transition temperature was observed at 122 °C and 102 °C for the ceramics with x =0.01 and x = 0.05, respectively. The temperature dependent P-E loops also revealed the existence of TC at these particular temperature values. The energy storage density (Ed) of both compounds was calculated from room temperature P – E loops at an applied electric field of 20 kV/cm. The maximum Ed ~ 224 kJ/m³ was achieved for the sample with x = 0.01 as compared to 164 kJ/m³ for the x =0.05 composition. The value of Ed is comparable to other BaTiO₃ based lead free ferroelectric systems. Impedance spectroscopy analysis exhibited the bulk and grain boundary contributions above 300 °C under the frequency range 100 Hz to 1 MHz. The above properties make these ceramics suitable for energy storage devices.

Keywords: dielectric properties, energy storage properties, impedance spectroscopy, lead free ceramics

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Authors: Siyu Wang, Anthony Ward

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Emotional intelligence (EI) is a well-established personal characteristic. It has been viewed as a critical factor which can influence an individual's academic achievement, ability to work and potential to succeed. When working in a group, EI is fundamentally connected to the group members' interaction and ability to work as a team. The ability of a group member to intelligently perceive and understand own emotions (Intrapersonal EI), to intelligently perceive and understand other members' emotions (Interpersonal EI), and to intelligently perceive and understand emotions between different groups (Cross-boundary EI) can be considered as Group emotional intelligence (Group EI). In this research, a more representative Group EI measurement approach, which incorporates the information of the composition of a group and an individual’s role in that group, is proposed. To demonstrate the claim of being more representative Group EI measurement approach, this study adopts a multi-method research design, involving a combination of both qualitative and quantitative techniques to establish a metric of Group EI. From the results, it can be concluded that by introducing the weight coefficient of each group member on group work into the measurement of Group EI, Group EI will be more representative and more capable of understanding what happens during teamwork than previous approaches.

Keywords: case study, emotional intelligence, group EI, multi-method research

Procedia PDF Downloads 116

Authors: H. Ben Khlifa, W. Cheikhrouhou, R. M'nassri

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The Orthorhombic Pr0.8Na0.2MnO3 ceramic was prepared in Polycrystalline form by a Pechini sol–gel method and its structural, magnetic, electrical, and dielectric properties were investigated experimentally. A structural study confirms that the sample is a single phase. Magnetic measurements show that the sample is a charge ordered Manganite. The sample undergoes two successive magnetic phase transitions with the variation of temperature: a charge ordering transition occurred at TCO = 212 K followed by a Paramagnetic (PM) to ferromagnetic (FM) transition around TC = 115 K. From an electrical point of view, a saturation region was marked in the conductivity as a function of Temperature s(T) curves at a specific temperature. The dc-conductivity (sdc) reaches a maximum value at 240 K. The obtained results are in good agreement with the temperature dependence of the average normalized change (ANC). We found that the conduction mechanism was governed by small polaron hopping (SPH) in the high-temperature region and by variable range hopping (VRH) in the low-temperature region. Complex impedance analysis indicates the presence of a non-Debye relaxation phenomenon in the system. Also, the compound was modeled by an electrical equivalent circuit. Then, the contribution of the grain boundary in the transport properties was confirmed.

Keywords: manganites, preparation methods, magnetization, magnetocaloric effect, electrical and dielectric

Procedia PDF Downloads 153

Authors: Hamed Khosravi, Reza Eslami-Farsani

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Increased interest in lightweight and efficient structural components has created the need for selecting materials with improved mechanical properties. To do so, composite materials are being widely used in many applications, due to durability, high strength and modulus, and low weight. Among the various composite structures, grid-stiffened structures are extensively considered in various aerospace and aircraft applications, because of higher specific strength and stiffness, higher impact resistance, superior load-bearing capacity, easy to repair, and excellent energy absorption capability. Although there are a good number of publications on the design aspects and fabrication of grid structures, little systematic work has been reported on their material modification to improve their properties, to our knowledge. Therefore, the aim of this research is to study the reinforcing effect of silica nanoparticles on the flexural properties of epoxy/E-glass isogrid panels under three-point bending test. Samples containing 0, 1, 3, and 5 wt.% of the silica nanoparticles, with 44 and 48 vol.% of the glass fibers in the ribs and skin components respectively, were fabricated by using a manual filament winding method. Ultrasonic and mechanical routes were employed to disperse the nanoparticles within the epoxy resin. To fabricate the ribs, the unidirectional fiber rovings were impregnated with the matrix mixture (epoxy + nanoparticles) and then laid up into the grooves of a silicone mold layer-by-layer. At once, four plies of woven fabrics, after impregnating into the same matrix mixture, were layered on the top of the ribs to produce the skin part. In order to conduct the ultimate curing and to achieve the maximum strength, the samples were tested after 7 days of holding at room temperature. According to load-displacement graphs, the bellow trend was observed for all of the samples when loaded from the skin side; following an initial linear region and reaching a load peak, the curve was abruptly dropped and then showed a typical absorbed energy region. It would be worth mentioning that in these structures, a considerable energy absorption was observed after the primary failure related to the load peak. The results showed that the flexural properties of the nanocomposite samples were always higher than those of the nanoparticle-free sample. The maximum enhancement in flexural maximum load and energy absorption was found to be for the incorporation of 3 wt.% of the nanoparticles. Furthermore, the flexural stiffness was continually increased by increasing the silica loading. In conclusion, this study suggested that the addition of nanoparticles is a promising method to improve the flexural properties of grid-stiffened fibrous composite structures.

Keywords: grid-stiffened composite structures, nanocomposite, three point flexural test , energy absorption

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Authors: Richard Colwell, Thomas Englert

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In cryogenic liquefaction processes, brazed aluminum core heat exchangers are used to minimize surface area/volume of the exchanger. Aluminum alloy (5083-H321; UNS A95083) piping must transition to higher melting point 304L stainless steel piping outside of the heat exchanger kettle or cold box for safety reasons. Since aluminum alloys and austenitic stainless steel cannot be directly welded to together, a transition joint consisting of 5 layers of different metals explosively bonded are used. Failures of two of these joints resulted in process shut-down and loss of revenue. Failure analyses, FEA analysis, and mock-up testing were performed by multiple teams to gain a further understanding into the failure mechanisms involved.

Keywords: explosion bonding, intermetallic compound, thermal strain, titanium-nickel Interface

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Authors: Kai Chun Yang, Shao-Wen Chen, Jong-Rong Wang, Chunkuan Shih, Jung-Hua Yang, Hsiung-Chih Chen, Wen-Sheng Hsu

Abstract:

In this study, we build RADionuclide Transport, Removal And Dose Estimation/Symbolic Nuclear Analysis Package (SNAP/RADTRAD) model of Kuosheng Nuclear Power Plant which is based on the Final Safety Evaluation Report (FSAR) and other data of Kuosheng Nuclear Power Plant. It is used to estimate the radiation dose of the Exclusion Area Boundary (EAB), the Low Population Zone (LPZ), and the control room following ‘release from the containment’ case in Loss Of Coolant Accident (LOCA). The RADTRAD analysis result shows that the evaluation dose at EAB, LPZ, and the control room are close to the FSAR data, and all of the doses are lower than the regulatory limits. At last, we do a sensitivity analysis and observe that the evaluation doses increase as the intake rate of the control room increases.

Keywords: RADTRAD, radionuclide transport, removal and dose estimation, snap, symbolic nuclear analysis package, boiling water reactor, NPP, kuosheng

Procedia PDF Downloads 327

Authors: Xia Fang

Abstract:

Arid and semiarid areas of China (ASAC) have experienced significant land-use/cover changes (LUCC), along with intensified climate change. However, LUCC and climate changes and their individual and interactive effects on carbon stocks have not yet been fully understood in the ASAC. This study analyses the carbon stocks in the ASAC during 1980 - 2020 using the specific arid ecosystem model (AEM), and investigates the effects of LUCC and climate change on carbon stock trends. The results indicate that in the past 41 years, the ASAC carbon pool experienced an overall growth trend, with an increase of 182.03 g C/m2. Climatic factors (+291.99 g C/m2), especially the increase in precipitation, were the main drivers of the carbon pool increase. LUCC decreased the carbon pool (-112.27 g C/m2), mainly due to the decrease in grassland area (-2.77%). The climate-induced carbon sinks were distributed in northern Xinjiang, on the Ordos Plateau, and in Northeast China, while the LUCC-induced carbon sinks mainly occurred on the Ordos Plateau and the North China Plain, resulting in a net decrease in carbon sequestration in these regions according to carbon pool measurements. The study revealed that the combination of climate variability, LUCC, and increasing atmospheric CO2 concentration resulted in an increase of approximately 182.03 g C/m2, which was mainly distributed in eastern Inner Mongolia and the western Qinghai-Tibet Plateau. Our findings are essential for improving theoretical guidance to protect the ecological environment, rationally plan land use, and understand the sustainable development of arid and semiarid zones.

Keywords: AEM, climate change, LUCC, carbon stocks

Procedia PDF Downloads 65

Authors: Qiong Rao, Xiongqi Peng

Abstract:

In this work, multi-walled carbon nanotubes (MWCNTs) and graphene nanoplates (GNPs) were dispersed into epoxy adhesive to investigate their synergy effects on the shear properties, mode I and mode II fracture toughness of unidirectional composite bonded joints. Testing results showed that the incorporation of MWCNTs and GNPs significantly improved the shear strength, the mode I and mode II fracture toughness by 36.6%, 45% and 286%, respectively. In addition, the fracture surfaces of the bonding area as well as the toughening mechanism of nanofillers were analyzed. Finally, a nonlinear cohesive/friction coupled model for delamination analysis of adhesive layer under shear and normal compression loadings was proposed and implemented in ABAQUS/Explicit via user subroutine VUMAT.

Keywords: nanofillers, adhesive joints, fracture toughness, cohesive zone model

Procedia PDF Downloads 125

Authors: H. Fazlinejad, A. Halvaee

Abstract:

In this study, characteristics of ATIG welds using ZnO flux on aluminum was investigated and compared with TIG welds. Autogenously AC-ATIG bead on plate welding was applied on Al1050 plate with a coating of ZnO as the flux. Different levels of welding current and flux layer thickness was considered to study the effect of heat input and flux quantity on ATIG welds and was compared with those of TIG welds. Geometrical investigation of the weld cross sections revealed that penetration depth of the ATIG welds with ZnO flux, was increased up to 2 times in some samples compared to the TIG welds. Optical metallographic and Scanning Electron Microscopy (SEM) observations revealed similar microstructures in TIG and ATIG welds. Composition of the ATIG welds slag was also analyzed using X-ray diffraction. In both TIG and ATIG samples, the lowest values of microhardness were observed in the HAZ.

Keywords: ATIG, active flux, weld penetration, Al 1050, ZnO

Procedia PDF Downloads 153

Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

Abstract:

Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

Procedia PDF Downloads 81