Search results for: satellite thermal images
4590 The Unsteady Non-Equilibrium Distribution Function and Exact Equilibrium Time for a Dilute Gas Affected by Thermal Radiation Field
Authors: Taha Zakaraia Abdel Wahid
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The behavior of the unsteady non-equilibrium distribution function for a dilute gas under the effect of non-linear thermal radiation field is presented. For the best of our knowledge this is done for the first time at all. The distinction and comparisons between the unsteady perturbed and the unsteady equilibrium velocity distribution functions are illustrated. The equilibrium time for the dilute gas is determined for the first time. The non-equilibrium thermodynamic properties of the system (gas+the heated plate) are investigated. The results are applied to the Argon gas, for various values of radiation field intensity. 3D-Graphics illustrating the calculated variables are drawn to predict their behavior. The results are discussed.Keywords: dilute gas, radiation field, exact solutions, travelling wave method, unsteady BGK model, irreversible thermodynamics, unsteady non-equilibrium distribution functions
Procedia PDF Downloads 4954589 Control of Belts for Classification of Geometric Figures by Artificial Vision
Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez
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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB
Procedia PDF Downloads 3784588 Optimal Image Representation for Linear Canonical Transform Multiplexing
Authors: Navdeep Goel, Salvador Gabarda
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Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4x4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4*4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4*4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.Keywords: chirp signals, image multiplexing, image transformation, linear canonical transform, polynomial approximation
Procedia PDF Downloads 4124587 Computer Aided Diagnosis Bringing Changes in Breast Cancer Detection
Authors: Devadrita Dey Sarkar
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Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)
Procedia PDF Downloads 4564586 3D Images Representation to Provide Information on the Type of Castella Beams Hole
Authors: Cut Maisyarah Karyati, Aries Muslim, Sulardi
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Digital image processing techniques to obtain detailed information from an image have been used in various fields, including in civil engineering, where the use of solid beam profiles in buildings and bridges has often been encountered since the early development of beams. Along with this development, the founded castellated beam profiles began to be more diverse in shape, such as the shape of a hexagon, triangle, pentagon, circle, ellipse and oval that could be a practical solution in optimizing a construction because of its characteristics. The purpose of this research is to create a computer application to edge detect the profile of various shapes of the castella beams hole. The digital image segmentation method has been used to obtain the grayscale images and represented in 2D and 3D formats. This application has been successfully made according to the desired function, which is to provide information on the type of castella beam hole.Keywords: digital image, image processing, edge detection, grayscale, castella beams
Procedia PDF Downloads 1414585 Power Grid Line Ampacity Forecasting Based on a Long-Short-Term Memory Neural Network
Authors: Xiang-Yao Zheng, Jen-Cheng Wang, Joe-Air Jiang
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Improving the line ampacity while using existing power grids is an important issue that electricity dispatchers are now facing. Using the information provided by the dynamic thermal rating (DTR) of transmission lines, an overhead power grid can operate safely. However, dispatchers usually lack real-time DTR information. Thus, this study proposes a long-short-term memory (LSTM)-based method, which is one of the neural network models. The LSTM-based method predicts the DTR of lines using the weather data provided by Central Weather Bureau (CWB) of Taiwan. The possible thermal bottlenecks at different locations along the line and the margin of line ampacity can be real-time determined by the proposed LSTM-based prediction method. A case study that targets the 345 kV power grid of TaiPower in Taiwan is utilized to examine the performance of the proposed method. The simulation results show that the proposed method is useful to provide the information for the smart grid application in the future.Keywords: electricity dispatch, line ampacity prediction, dynamic thermal rating, long-short-term memory neural network, smart grid
Procedia PDF Downloads 2834584 Artificial Intelligence-Generated Previews of Hyaluronic Acid-Based Treatments
Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio
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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.Keywords: prediction, hyaluronic acid, treatment, artificial intelligence
Procedia PDF Downloads 1144583 Hygro-Thermal Modelling of Timber Decks
Authors: Stefania Fortino, Petr Hradil, Timo Avikainen
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Timber bridges have an excellent environmental performance, are economical, relatively easy to build and can have a long service life. However, the durability of these bridges is the main problem because of their exposure to outdoor climate conditions. The moisture content accumulated in wood for long periods, in combination with certain temperatures, may cause conditions suitable for timber decay. In addition, moisture content variations affect the structural integrity, serviceability and loading capacity of timber bridges. Therefore, the monitoring of the moisture content in wood is important for the durability of the material but also for the whole superstructure. The measurements obtained by the usual sensor-based techniques provide hygro-thermal data only in specific locations of the wood components. In this context, the monitoring can be assisted by numerical modelling to get more information on the hygro-thermal response of the bridges. This work presents a hygro-thermal model based on a multi-phase moisture transport theory to predict the distribution of moisture content, relative humidity and temperature in wood. Below the fibre saturation point, the multi-phase theory simulates three phenomena in cellular wood during moisture transfer, i.e., the diffusion of water vapour in the pores, the sorption of bound water and the diffusion of bound water in the cell walls. In the multi-phase model, the two water phases are separated, and the coupling between them is defined through a sorption rate. Furthermore, an average between the temperature-dependent adsorption and desorption isotherms is used. In previous works by some of the authors, this approach was found very suitable to study the moisture transport in uncoated and coated stress-laminated timber decks. Compared to previous works, the hygro-thermal fluxes on the external surfaces include the influence of the absorbed solar radiation during the time and consequently, the temperatures on the surfaces exposed to the sun are higher. This affects the whole hygro-thermal response of the timber component. The multi-phase model, implemented in a user subroutine of Abaqus FEM code, provides the distribution of the moisture content, the temperature and the relative humidity in a volume of the timber deck. As a case study, the hygro-thermal data in wood are collected from the ongoing monitoring of the stress-laminated timber deck of Tapiola Bridge in Finland, based on integrated humidity-temperature sensors and the numerical results are found in good agreement with the measurements. The proposed model, used to assist the monitoring, can contribute to reducing the maintenance costs of bridges, as well as the cost of instrumentation, and increase safety.Keywords: moisture content, multi-phase models, solar radiation, timber decks, FEM
Procedia PDF Downloads 1754582 Wear Progress and -Mechanisms in Torpedo Ladles in Steel Industry
Authors: Mattahias Maj, Fabio Tatzgern, Karl Adam, Damir Kahrimanovic, Markus Varga
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Torpedo ladles are necessary transport carriages in steel production to move the molten crude iron from the blast furnace to the steel refining plant. This requires the ladles to be high temperature resistant and insulate well to preserve the temperature and hold the risk of solidification at bay. Therefore, the involved refractories lining the inside of the torpedo ladles are chosen mostly according to their thermal properties, although wear of the materials by the liquid iron is also of major importance. In this work, we combined investigations of the thermal behaviour with wear studies of the lining over the whole lifetime of a torpedo ladle. Additional numerical simulations enabled a detailed model of the mechanical loads and temperature propagation at the various stations (heating, filling, emptying, cooling). The core of the investigation were detailed 3D measurements of the ladle’s cavity and thereby quantitative information of the wear progress at different time intervals during the lifetime of the ladles. The measurements allowed for a separation of different wear zones according to severity, namely the “splash zone” where the melt directly hits the ladle, the “melt zone” where during transport always liquid melt is present, and the “slag zone”, where the slag floats on the melt causing the most severe wear loss. Numerical simulations of the filling process were taken to calculate stress levels and temperature gradients, which led to the different onset of wear on those zones. Thermal imaging and punctual temperature measurements allowed for a study of the thermal consequences entailed by the wear onset. Additional “classical” damage analysis of the worn refractories complete the investigation. Thereby the wear mechanisms leading to the substantial wear loss were disclosed.Keywords: high temperature, tribology, liquid-solid interaction, refractories, thermography
Procedia PDF Downloads 2264581 Assessment of Multi-Domain Energy Systems Modelling Methods
Authors: M. Stewart, Ameer Al-Khaykan, J. M. Counsell
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Emissions are a consequence of electricity generation. A major option for low carbon generation, local energy systems featuring Combined Heat and Power with solar PV (CHPV) has significant potential to increase energy performance, increase resilience, and offer greater control of local energy prices while complementing the UK’s emissions standards and targets. Recent advances in dynamic modelling and simulation of buildings and clusters of buildings using the IDEAS framework have successfully validated a novel multi-vector (simultaneous control of both heat and electricity) approach to integrating the wide range of primary and secondary plant typical of local energy systems designs including CHP, solar PV, gas boilers, absorption chillers and thermal energy storage, and associated electrical and hot water networks, all operating under a single unified control strategy. Results from this work indicate through simulation that integrated control of thermal storage can have a pivotal role in optimizing system performance well beyond the present expectations. Environmental impact analysis and reporting of all energy systems including CHPV LES presently employ a static annual average carbon emissions intensity for grid supplied electricity. This paper focuses on establishing and validating CHPV environmental performance against conventional emissions values and assessment benchmarks to analyze emissions performance without and with an active thermal store in a notional group of non-domestic buildings. Results of this analysis are presented and discussed in context of performance validation and quantifying the reduced environmental impact of CHPV systems with active energy storage in comparison with conventional LES designs.Keywords: CHPV, thermal storage, control, dynamic simulation
Procedia PDF Downloads 2404580 An Improved C-Means Model for MRI Segmentation
Authors: Ying Shen, Weihua Zhu
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Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy
Procedia PDF Downloads 2264579 Efficient Liquid Desiccant Regeneration for Fresh Air Dehumidification Application
Authors: M. V. Rane, Tareke Tekia
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Fresh Air Dehumidifier having a capacity of 1 TR has been developed by Heat Pump Laboratory at IITB. This fresh air dehumidifier is based on potassium formate liquid desiccant. The regeneration of the liquid desiccant can be done in two stages. The first stage of liquid desiccant regeneration involves the boiling of liquid desiccant inside the evacuated glass type solar thermal collectors. Further regeneration of liquid desiccant can be achieved using Low Temperature Regenerator, LTR. The coefficient of performance of the fresh air dehumidifier greatly depends on the performance of the major components such as high temperature regenerator, low temperature regenerator, fresh air dehumidifier, and solution heat exchangers. High effectiveness solution heat exchanger has been developed and tested. The solution heat exchanger is based on a patented aluminium extrusion with special passage geometry to enhance the heat transfer rate. Effectiveness up to 90% was achieved. Before final testing of the dehumidifier, major components have been tested individually. Testing of the solar thermal collector as hot water and steam generator reveals that efficiency up to 55% can be achieved. In this paper, the development of 1 TR fresh air dehumidifier with special focus on solution heat exchangers and solar thermal collector performance is presented.Keywords: solar, liquid desiccant, dehumidification, air conditioning, regeneration, coefficient of performance
Procedia PDF Downloads 1934578 A Thermo-mechanical Finite Element Model to Predict Thermal Cycles and Residual Stresses in Directed Energy Deposition Technology
Authors: Edison A. Bonifaz
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In this work, a numerical procedure is proposed to design dense multi-material structures using the Directed Energy Deposition (DED) process. A thermo-mechanical finite element model to predict thermal cycles and residual stresses is presented. A numerical layer build-up procedure coupled with a moving heat flux was constructed to minimize strains and residual stresses that result in the multi-layer deposition of an AISI 316 austenitic steel on an AISI 304 austenitic steel substrate. To simulate the DED process, the automated interface of the ABAQUS AM module was used to define element activation and heat input event data as a function of time and position. Of this manner, the construction of ABAQUS user-defined subroutines was not necessary. Thermal cycles and thermally induced stresses created during the multi-layer deposition metal AM pool crystallization were predicted and validated. Results were analyzed in three independent metal layers of three different experiments. The one-way heat and material deposition toolpath used in the analysis was created with a MatLab path script. An optimal combination of feedstock and heat input printing parameters suitable for fabricating multi-material dense structures in the directed energy deposition metal AM process was established. At constant power, it can be concluded that the lower the heat input, the lower the peak temperatures and residual stresses. It means that from a design point of view, the one-way heat and material deposition processing toolpath with the higher welding speed should be selected.Keywords: event series, thermal cycles, residual stresses, multi-pass welding, abaqus am modeler
Procedia PDF Downloads 694577 Fabrication Methodologies for Anti-Microbial Polypropylene Surfaces with Leachable and Non-leachable Anti-Microbial Agents
Authors: Saleh Alkarri, Dimple Sharma, Teresa M. Bergholz, Muhammad Rabnawaz
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Aims: Develop a methodology for the fabrication of anti-microbial polypropylene (PP) surfaces with (i) leachable copper, (II) chloride dihydrate (CuCl₂·₂H₂O) and (ii) non-leachable magnesium hydroxide (Mg(OH)₂) biocides. Methods and Results: Two methodologies are used to develop anti-microbial PP surfaces. One method involves melt-blending and subsequent injection molding, where the biocide additives were compounded with PP and subsequently injection-molded. The other method involves the thermal embossing of anti-microbial agents on the surface of a PP substrate. The obtained biocide-bearing PP surfaces were evaluated against E. coli K-12 MG1655 for 0, 4, and 24 h to evaluate their anti-microbial properties. The injection-molded PP bearing 5% CuCl2·₂H₂O showed a 6-log reduction of E. coli K-12 MG1655 after 24 h, while only 1 log reduction was observed for PP bearing 5% Mg(OH)2. The thermally embossed PP surfaces bearing CuCl2·2H2O and Mg(OH)₂ particles (at a concentration of 10 mg/mL) showed 3 log and 4 log reduction, respectively, against E.coli K-12 MG1655 after 24 h. Conclusion: The results clearly demonstrate that CuCl₂·2H₂O conferred anti-microbial properties to PP surfaces that were prepared by both injection molding as well as thermal embossing approaches owing to the presence of leachable copper ions. In contrast, the non-leachable Mg(OH)₂ imparted anti-microbial properties only to the surface prepared via the thermal embossing technique. Significance and Impact of The Study: Plastics with leachable biocides are effective anti-microbial surfaces, but their toxicity is a major concern. This study provides a fabrication methodology for non-leachable PP-based anti-microbial surfaces that are potentially safer. In addition, this strategy can be extended to many other plastics substrates.Keywords: anti-microbial activity, E. coli K-12 MG1655, copper (II) chloride dihydrate, magnesium hydroxide, leachable, non-leachable, compounding, thermal embossing
Procedia PDF Downloads 784576 Fabrication Methodologies for Anti-microbial Polypropylene Surfaces with Leachable and Non-leachable Anti-microbial Agents
Authors: Saleh Alkarri, Dimple Sharma, Teresa M. Bergholz, Muhammad Rabnawa
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Aims: Develop a methodology for the fabrication of anti-microbial polypropylene (PP) surfaces with (i) leachable copper (II) chloride dihydrate (CuCl2·2H2O) and (ii) non-leachable magnesium hydroxide (Mg(OH)2) biocides. Methods and Results: Two methodologies are used to develop anti-microbial PP surfaces. One method involves melt-blending and subsequent injection molding, where the biocide additives were compounded with PP and subsequently injection-molded. The other method involves the thermal embossing of anti-microbial agents on the surface of a PP substrate. The obtained biocide-bearing PP surfaces were evaluated against E. coli K-12 MG1655 for 0, 4, and 24 h to evaluate their anti-microbial properties. The injection-molded PP bearing 5% CuCl2·2H2O showed a 6-log reduction of E. coli K-12 MG1655 after 24 h, while only 1 log reduction was observed for PP bearing 5% Mg(OH)2. The thermally embossed PP surfaces bearing CuCl2·2H2O and Mg(OH)2 particles (at a concentration of 10 mg/mL) showed 3 log and 4 log reduction, respectively, against E.coli K-12 MG1655 after 24 h. Conclusion: The results clearly demonstrate that CuCl2·2H2O conferred anti-microbial properties to PP surfaces that were prepared by both injection molding as well as thermal embossing approaches owing to the presence of leachable copper ions. In contrast, the non-leachable Mg(OH)2 imparted anti-microbial properties only to the surface prepared via the thermal embossing technique. Significance and Impact of The Study: Plastics with leachable biocides are effective anti-microbial surfaces, but their toxicity is a major concern. This study provides a fabrication methodology for non-leachable PP-based anti-microbial surfaces that are potentially safer. In addition, this strategy can be extended to many other plastics substrates.Keywords: anti-microbial activity, E. coli K-12 MG1655, copper (II) chloride dihydrate, magnesium hydroxide, leachable, non-leachable, compounding, thermal embossing
Procedia PDF Downloads 834575 Effect of Synthesis Method on Structural, Morphological Properties of Zr0.8Y0.2-xLax Oxides (x=0, 0.1, 0.2)
Authors: Abdelaziz Ghrib, Samir Hattali, Mouloud Ghrib, Mohamed Lamine Aouissia, David Ruch
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In the present study, the solid solutions with a chemical composition of Zr0.8Y0.2-xLaxO2 (x=0, 0.1, 0.2) were synthesized via two routes, by hydrothermal method using NaOH as precipitating agent at 230°C for 15h and by the sol–gel process using citric acid as complexing agent. Compounds have been characterized by powder X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Thermo gravimetric Analysis (TGA) and Differential Thermal Analysis (DTA) techniques for appropriate characterization of the distinct thermal events occurring during synthesis. All the compounds crystallize in cubic fluorite structure, as indicated by X-ray diffraction studie. The microstructure of oxides synthesized by sol-gel showed porosity that increased with the lanthanum La3+ contents compared to hydrothermal method which gives a single crystal oxide.Keywords: oxide, hydrothermal, rare earth, solubility, sol-gel, ternary mixture
Procedia PDF Downloads 6424574 Natural Frequency Analysis of Spinning Functionally Graded Cylindrical Shells Subjected to Thermal Loads
Authors: Esmaeil Bahmyari
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The natural frequency analysis of the functionally graded (FG) rotating cylindrical shells subjected to thermal loads is studied based on the three-dimensional elasticity theory. The temperature-dependent assumption of the material properties is graded in the thickness direction, which varies based on the simple power law distribution. The governing equations and the appropriate boundary conditions, which include the effects of initial thermal stresses, are derived employing Hamilton’s principle. The initial thermo-mechanical stresses are obtained by the thermo-elastic equilibrium equation’s solution. As an efficient and accurate numerical tool, the differential quadrature method (DQM) is adopted to solve the thermo-elastic equilibrium equations, free vibration equations and natural frequencies are obtained. The high accuracy of the method is demonstrated by comparison studies with those existing solutions in the literature. Ultimately, the parametric studies are performed to demonstrate the effects of boundary conditions, temperature rise, material graded index, the thickness-to-length and the aspect ratios for the rotating cylindrical shells on the natural frequency.Keywords: free vibration, DQM, elasticity theory, FG shell, rotating cylindrical shell
Procedia PDF Downloads 844573 Solutions for Quality Pre-Control of Crimp Contacts
Authors: C. F. Ocoleanu, G. Cividjian, Gh. Manolea
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In this paper, we present two solutions for connections quality pre-control of Crimp Contacts and to identify in the first moments the connections improperly executed, before final assembly of a electrical machines. The first solution supposed experimental determination of specific losses by calculated the initial rate of temperature rise. This can be made drawing the tangent at the origin at heating curve. The method can be used to identify bad connections by passing a current through the winding at ambient temperature and simultaneously record connections temperatures in the first few minutes since the current is setting. The second proposed solution is to apply to each element crimping a thermal indicator one level, and making a test heating with a heating current corresponding to critical temperature indicator.Keywords: temperature, crimp contact, thermal indicator, current distribution, specific losses
Procedia PDF Downloads 4224572 Inclined Convective Instability in a Porous Layer Saturated with Non-Newtonian Fluid
Authors: Rashmi Dubey
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The study aims at investigating the onset of thermal convection in an inclined porous layer saturated with a non-Newtonian fluid. The layer is infinitely extended and has a finite width confined between two boundaries with constant pressure conditions, where the lower one is maintained at a higher temperature. Over the years, this area of research has attracted many scientists and researchers, for it has a plethora of applications in the fields of sciences and engineering, such as in civil engineering, geothermal sites, petroleum industries, etc.Considering the possibilities in a practical scenario, an inclined porous layer is considered, which can be used to develop a generalized model applicable to any inclination. Using the isobaric boundaries, the hydrodynamic boundary conditions are derived for the power-law model and are used to obtain the basic state flow. The convection in the basic state flow is driven by the thermal buoyancy in the flow system and is carried away further due to hydrodynamic boundaries. A linear stability analysis followed by a normal-mode analysis is done to investigate the onset of convection in the buoyancy-driven flow. The analysis shows that the convective instability is always initiated by the non-traveling modes for the Newtonian fluid, but prevails in the form of oscillatory modes, for up to a certain inclination of the porous layer. However, different behavior is observed for the dilatant and pseudoplastic fluids.Keywords: thermal convection, linear stability, porous media flow, Inclined porous layer
Procedia PDF Downloads 1234571 Thermal Effects of Phase Transitions of Cerium and Neodymium
Authors: M. Khundadze, V. Varazashvili, N. Lejava, R. Jorbenadze
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Phase transitions of cerium and neodymium are investigated by using high temperature scanning calorimeter (HT-1500 Seteram). For cerium two types of transformation are detected: at 350-372 K - hexagonal close packing (hcp) - face-centered cubic lattice (fcc) transition, and in 880-960K the face-centered cubic lattice (fcc) transformation into body-centered cubic lattice (bcc). For neodymium changing of hexagonal close packing (hcp) into body-centered cubic lattice (bcc) is detected at 1093-1113K. The thermal characteristics of transitions – enthalpy, entropy, temperature domains – are reported.Keywords: cerium, calorimetry, neodymium, enthalpy of phase transitions, neodymium
Procedia PDF Downloads 3694570 A Novel Hybrid Deep Learning Architecture for Predicting Acute Kidney Injury Using Patient Record Data and Ultrasound Kidney Images
Authors: Sophia Shi
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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG
Procedia PDF Downloads 1314569 Synthesis and Characterization of New Polyesters Based on Diarylidene-1-Methyl-4-Piperidone
Authors: Tareg M. Elsunaki, Suleiman A. Arafa, Mohamed A. Abd-Alla
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New interesting thermal stable polyesters containing 1-methyl-4-piperidone moiety in the main chain have been synthesized. These polyesters were synthesized by interfacial polycondensation technique of 3,5-bis(4-hydroxybenzylidene)-1-methyl-4-piperidone (I) and 3,5-bis(4-hydroxy-3-methoxy benzyli-dene)-1-methyl-4-piperidone (II) with terphthaloyl, isophthaloyl, 4,4'-diphenic, adipoyl and sebacoyl dichlorides. The yield and the values of the reduced viscosity of the produced polyesters were found to be affected by the type of an organic phase. In order to characterize these polymers, the necessary model compounds (A), (B) were prepared from (I), (II) respectively and benzoyl chloride. The structure of monomers (I), (II), model compounds and resulting polyesters were confirmed by IR, elemental analysis and 1HNMR spectroscopy. The various characteristic of the resulting polymers including solubility, thermal properties, viscosity and X-ray analysis were also studied.Keywords: synthesis, characterization, new polyesters, chemistry
Procedia PDF Downloads 4584568 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries
Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi
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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery
Procedia PDF Downloads 5864567 Development of Innovative Nuclear Fuel Pellets Using Additive Manufacturing
Authors: Paul Lemarignier, Olivier Fiquet, Vincent Pateloup
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In line with the strong desire of nuclear energy players to have ever more effective products in terms of safety, research programs on E-ATF (Enhanced-Accident Tolerant Fuels) that are more resilient, particularly to the loss of coolant, have been launched in all countries with nuclear power plants. Among the multitude of solutions being developed internationally, carcinoembryonic antigen (CEA) and its partners are investigating a promising solution, which is the realization of CERMET (CERamic-METal) type fuel pellets made of a matrix of fissile material, uranium dioxide UO2, which has a low thermal conductivity, and a metallic phase with a high thermal conductivity to improve heat evacuation. Work has focused on the development by powder metallurgy of micro-structured CERMETs, characterized by networks of metallic phase embedded in the UO₂ matrix. Other types of macro-structured CERMETs, based on concepts proposed by thermal simulation studies, have been developed with a metallic phase with a specific geometry to optimize heat evacuation. This solution could not be developed using traditional processes, so additive manufacturing, which revolutionizes traditional design principles, is used to produce these innovative prototype concepts. At CEA Cadarache, work is first carried out on a non-radioactive surrogate material, alumina, in order to acquire skills and to develop the equipment, in particular the robocasting machine, an additive manufacturing technique selected for its simplicity and the possibility of optimizing the paste formulations. A manufacturing chain was set up, with the pastes production, the 3D printing of pellets, and the associated thermal post-treatment. The work leading to the first elaborations of macro-structured alumina/molybdenum CERMETs will be presented. This work was carried out with the support of Framatome and EdF.Keywords: additive manufacturing, alumina, CERMET, molybdenum, nuclear safety
Procedia PDF Downloads 774566 Thermal Performance of Hybrid PVT Collector with Natural Circulation
Authors: K. Touafek, A. Khelifa, I. Tabet, H. Haloui, H. Bencheikh El Houcine, M. Adouane
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Hybrid photovoltaic thermal (PVT) collectors allow simultaneous production of electrical energy thus heat energy. There are several configurations of hybrid collectors (to produce water or air). For hybrids water collectors, there are several configurations that differ by the nature of the absorber (serpentine, tubes...). In this paper, an absorber tank is studied. The circulation of the coolant is natural (we do not use the pump). We present the obtained results in our experimental study and we analyzed the data, and then we compare the results with the theory practices. The electrical performances of the hybrid collector are compared with those of conventional photovoltaic module mounted on the same structure and measured under the same conditions. We conducted experiments with natural circulation of the coolant (Thermosyphon), for a flow rate of 0.025kg/m².Keywords: experimental, photovoltaic, solar, temperature, tank
Procedia PDF Downloads 3204565 Exploring the Influence of High-Frequency Acoustic Parameters on Wave Behavior in Porous Bilayer Materials: An Equivalent Fluid Theory Approach
Authors: Mustapha Sadouk
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This study investigates the sensitivity of high-frequency acoustic parameters in a rigid air-saturated porous bilayer material within the framework of the equivalent fluid theory, a specific case of the Biot model. The study specifically focuses on the sensitivity analysis in the frequency domain. The interaction between the fluid and solid phases of the porous medium incorporates visco-inertial and thermal exchange, characterized by two functions: the dynamic tortuosity α(ω) proposed by Johnson et al. and the dynamic compressibility β(ω) proposed by Allard, refined by Sadouki for the low-frequency domain of ultrasound. The parameters under investigation encompass porosity, tortuosity, viscous characteristic length, thermal characteristic length, as well as viscous and thermal shape factors. A +30% variation in these parameters is considered to assess their impact on the transmitted wave amplitudes. By employing this larger variation, a more comprehensive understanding of the sensitivity of these parameters is obtained. The outcomes of this study contribute to a better comprehension of the high-frequency wave behavior in porous bilayer materials, providing valuable insights for the design and optimization of such materials across various applications.Keywords: bilayer materials, ultrasound, sensitivity analysis, equivalent fluid theory, dynamic tortuosity., porous material
Procedia PDF Downloads 864564 Performance Variation of the TEES According to the Changes in Cold-Side Storage Temperature
Authors: Young-Jin Baik, Minsung Kim, Junhyun Cho, Ho-Sang Ra, Young-Soo Lee, Ki-Chang Chang
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Surplus electricity can be converted into potential energy via pumped hydroelectric storage for future usage. Similarly, thermo-electric energy storage (TEES) uses heat pumps equipped with thermal storage to convert electrical energy into thermal energy; the stored energy is then converted back into electrical energy when necessary using a heat engine. The greatest advantage of this method is that, unlike pumped hydroelectric storage and compressed air energy storage, TEES is not restricted by geographical constraints. In this study, performance variation of the TEES according to the changes in cold-side storage temperature was investigated by simulation method.Keywords: energy storage system, heat pump, fluid mechanics, thermodynamics
Procedia PDF Downloads 4824563 Antibacterial Wound Dressing Based on Metal Nanoparticles Containing Cellulose Nanofibers
Authors: Mohamed Gouda
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Antibacterial wound dressings based on cellulose nanofibers containing different metal nanoparticles (CMC-MNPs) were synthesized using an electrospinning technique. First, the composite of carboxymethyl cellulose containing different metal nanoparticles (CMC/MNPs), such as copper nanoparticles (CuNPs), iron nanoparticles (FeNPs), zinc nanoparticles (ZnNPs), cadmium nanoparticles (CdNPs) and cobalt nanoparticles (CoNPs) were synthesized, and finally, these composites were transferred to the electrospinning process. Synthesized CMC-MNPs were characterized using scanning electron microscopy (SEM) coupled with high-energy dispersive X-ray (EDX) and UV-visible spectroscopy used to confirm nanoparticle formation. The SEM images clearly showed regular flat shapes with semi-porous surfaces. All MNPs were well distributed inside the backbone of the cellulose without aggregation. The average particle diameters were 29-39 nm for ZnNPs, 29-33 nm for CdNPs, 25-33 nm for CoNPs, 23-27 nm for CuNPs and 22-26 nm for FeNPs. Surface morphology, water uptake and release of MNPs from the nanofibers in water and antimicrobial efficacy were studied. SEM images revealed that electrospun CMC-MNPs nanofibers are smooth and uniformly distributed without bead formation with average fiber diameters in the range of 300 to 450 nm. Fiber diameters were not affected by the presence of MNPs. TEM images showed that MNPs are present in/on the electrospun CMC-MNPs nanofibers. The diameter of the electrospun nanofibers containing MNPs was in the range of 300–450 nm. The MNPs were observed to be spherical in shape. The CMC-MNPs nanofibers showed good hydrophilic properties and had excellent antibacterial activity against the Gram-negative bacteria Escherichia coli and the Gram-positive bacteria Staphylococcus aureus.Keywords: electrospinning technique, metal nanoparticles, cellulosic nanofibers, wound dressing
Procedia PDF Downloads 3294562 Heat Transfer from Block Heat Sources Mounted on the Wall of a 3-D Cabinet to Ambient Natural Convective Air Stream
Authors: J. C. Cheng, Y. L. Tsay, Z. D. Chan, C. H. Yang
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In this study the physical system under consideration is a three-dimensional (3-D) cabinet with arrays of block heat sources mounted on one of the walls of the cabinet. The block heat sources dissipate heat to the cabinet surrounding through the conjugate conduction and natural convection. The results illustrate that the difference in hot spot temperatures of the system (θH) for the situations with and without consideration of thermal interaction is higher for smaller Rayleigh number (Ra), and can be up to 94.73% as Ra=10^5. In addition, the heat transfer characteristics depends strongly on the dimensionless heat conductivity of cabinet wall (Kwf), heat conductivity of block (Kpf) and length of cabinet (Ax). The maximum reduction in θH is 70.01% when Kwf varies from 10 to 1000, and it is 30.07% for Ax from 0.5 to 1. While the hot spot temperature of system is not sensitive to the cabinet angle (Φ).Keywords: block heat sources, 3-D cabinet, thermal interaction, heat transfer
Procedia PDF Downloads 5554561 A t-SNE and UMAP Based Neural Network Image Classification Algorithm
Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang
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Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.Keywords: t-SNE, UMAP, fashion MNIST, neural networks
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