Search results for: Thermal images.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5818

Search results for: Thermal images.

4138 Reduce the Fire Hazards of Epoxy Resin by a Zinc Stannate and Graphene Hybrids

Authors: Haibo Sheng, Yuan Hu

Abstract:

Spinel structure Zinc stannate (Zn2SnO4, ZS)/Graphene was successfully synthesized by a simple in situ hydrothermal route. Morphological study and structure analysis confirmed the homogenously loading of ZS on the graphene sheets. Then, the resulted ZS/graphene hybrids were incorporated into epoxy resin to form EP/ZS/graphene composites by a solvent dispersion method. Improved thermal stability was investigated by Thermogravimetric Analysis (TGA). Cone calorimeter result showed low peak heat release rate (PHRR). Toxical gases release during combustion was evaluated by a facile device organized in our lab. The results showed that the release of NOx, HCN decrease of about 55%. Also, TG-IR technology was used to investigate the gas release during the EP decomposition process. The CO release had decreased about 80%.The EP/G/ZS showed lowest hazards during combustion (including flame retardancy, thermal stability, lower toxical gases release and so on) than pure EP.

Keywords: fire hazards, zinc stannate, epoxy resin, toxical gas hazards

Procedia PDF Downloads 182
4137 Derivation of Bathymetry Data Using Worldview-2 Multispectral Images in Shallow, Turbid and Saline Lake Acıgöl

Authors: Muhittin Karaman, Murat Budakoglu

Abstract:

In this study, derivation of lake bathymetry was evaluated using the high resolution Worldview-2 multispectral images in the very shallow hypersaline Lake Acıgöl which does not have a stable water table due to the wet-dry season changes and industrial usage. Every year, a great part of the lake water budget has been consumed for the industrial salt production in the evaporation ponds, which are generally located on the south and north shores of Lake Acıgöl. Therefore, determination of the water level changes from a perspective of remote sensing-based lake water by bathymetry studies has a great importance in the sustainability-control of the lake. While the water table interval is around 1 meter between dry and wet season, dissolved ion concentration, salinity and turbidity also show clear differences during these two distinct seasonal periods. At the same time, with the satellite data acquisition (June 9, 2013), a field study was conducted to collect the salinity values, Secchi disk depths and turbidity levels. Max depth, Secchi disk depth and salinity were determined as 1,7 m, 0,9 m and 43,11 ppt, respectively. Eight-band Worldview-2 image was corrected for atmospheric effects by ATCOR technique. For each sampling point in the image, mean reflectance values in 1*1, 3*3, 5*5, 7*7, 9*9, 11*11, 13*13, 15*15, 17*17, 19*19, 21*21, 51*51 pixel reflectance neighborhoods were calculated separately. A unique image has been derivated for each matrix resolution. Spectral values and depth relation were evaluated for these distinct resolution images. Correlation coefficients were determined for the 1x1 matrix: 0,98, 0,96, 0,95 and 0,90 for the 724 nm, 831 nm, 908 nm and 659 nm, respectively. While 15x5 matrix characteristics with 0,98, 0,97 and 0,97 correlation values for the 724 nm, 908 nm and 831 nm, respectively; 51x51 matrix shows 0,98, 0,97 and 0,96 correlation values for the 724 nm, 831 nm and 659 nm, respectively. Comparison of all matrix resolutions indicates that RedEdge band (724 nm) of the Worldview-2 satellite image has the best correlation with the saline shallow lake of Acıgöl in-situ depth.

Keywords: bathymetry, Worldview-2 satellite image, ATCOR technique, Lake Acıgöl, Denizli, Turkey

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4136 Design and Integration of a Renewable Energy Based Polygeneration System with Desalination for an Industrial Plant

Authors: Lucero Luciano, Cesar Celis, Jose Ramos

Abstract:

Polygeneration improves energy efficiency and reduce both energy consumption and pollutant emissions compared to conventional generation technologies. A polygeneration system is a variation of a cogeneration one, in which more than two outputs, i.e., heat, power, cooling, water, energy or fuels, are accounted for. In particular, polygeneration systems integrating solar energy and water desalination represent promising technologies for energy production and water supply. They are therefore interesting options for coastal regions with a high solar potential, such as those located in southern Peru and northern Chile. Notice that most of the Peruvian and Chilean mining industry operations intensive in electricity and water consumption are located in these particular regions. Accordingly, this work focus on the design and integration of a polygeneration system producing industrial heating, cooling, electrical power and water for an industrial plant. The design procedure followed in this work involves integer linear programming modeling (MILP), operational planning and dynamic operating conditions. The technical and economic feasibility of integrating renewable energy technologies (photovoltaic and solar thermal, PV+CPS), thermal energy store, power and thermal exchange, absorption chillers, cogeneration heat engines and desalination technologies is particularly assessed. The polygeneration system integration carried out seek to minimize the system total annual cost subject to CO2 emissions restrictions. Particular economic aspects accounted for include investment, maintenance and operating costs.

Keywords: desalination, design and integration, polygeneration systems, renewable energy

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4135 Wastes of Oil Drilling: Treatment Techniques and Their Effectiveness

Authors: Abbas Hadj Abbas, Hacini Massaoud, Aiad Lahcen

Abstract:

In Hassi-Messoud’s oil industry, the systems which are water based (WBM) are generally used for drilling in the first phase. For the rest of the well, the oil mud systems are employed (OBM). In the field of oil exploration, panoply of chemical products is employed in the drilling fluids formulation. These components of different natures and whose toxicity and biodegradability are of ill-defined parameters are; however, thrown into nature. In addition to the hydrocarbon (HC, such as diesel) which is a major constituent of oil based mud, we also can notice spills as well as a variety of other products and additives on the drilling sites. These wastes are usually stored in places called (crud wastes). These may cause major problems to the ecosystem. To treat these wastes, we have considered two methods which are: solidification/ stabilization (chemical) and thermal. So that we can evaluate the techniques of treatment, a series of analyses are performed on dozens of specimens of wastes before treatment. After that, and on the basis of our analyses of wastes, we opted for diagnostic treatments of pollution before and after solidification and stabilization. Finally, we have done some analyses before and after the thermal treatment to check the efficiency of the methods followed in the study.

Keywords: wastes treatment, the oil pollution, the norms, wastes drilling

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4134 Topographic and Thermal Analysis of Plasma Polymer Coated Hybrid Fibers for Composite Applications

Authors: Hande Yavuz, Grégory Girard, Jinbo Bai

Abstract:

Manufacturing of hybrid composites requires particular attention to overcome various critical weaknesses that are originated from poor interfacial compatibility. A large number of parameters have to be considered to optimize the interfacial bond strength either to avoid flaw sensitivity or delamination that occurs in composites. For this reason, surface characterization of reinforcement phase is needed in order to provide necessary data to drive an assessment of fiber-matrix interfacial compatibility prior to fabrication of composite structures. Compared to conventional plasma polymerization processes such as radiofrequency and microwave, dielectric barrier discharge assisted plasma polymerization is a promising process that can be utilized to modify the surface properties of carbon fibers in a continuous manner. Finding the most suitable conditions (e.g., plasma power, plasma duration, precursor proportion) for plasma polymerization of pyrrole in post-discharge region either in the presence or in the absence of p-toluene sulfonic acid monohydrate as well as the characterization of plasma polypyrrole coated fibers are the important aspects of this work. Throughout the current investigation, atomic force microscopy (AFM) and thermogravimetric analysis (TGA) are used to characterize plasma treated hybrid fibers (CNT-grafted Toray T700-12K carbon fibers, referred as T700/CNT). TGA results show the trend in the change of decomposition process of deposited polymer on fibers as a function of temperature up to 900 °C. Within the same period of time, all plasma pyrrole treated samples began to lose weight with relatively fast rate up to 400 °C which suggests the loss of polymeric structures. The weight loss between 300 and 600 °C is attributed to evolution of CO2 due to decomposition of functional groups (e.g. carboxyl compounds). With keeping in mind the surface chemical structure, the higher the amount of carbonyl, alcohols, and ether compounds, the lower the stability of deposited polymer. Thus, the highest weight loss is observed in 1400 W 45 s pyrrole+pTSA.H2O plasma treated sample probably because of the presence of less stable polymer than that of other plasma treated samples. Comparison of the AFM images for untreated and plasma treated samples shows that the surface topography may change on a microscopic scale. The AFM image of 1800 W 45 s treated T700/CNT fiber possesses the most significant increase in roughening compared to untreated T700/CNT fiber. Namely, the fiber surface became rougher with ~3.6 fold that of the T700/CNT fiber. The increase observed in surface roughness compared to untreated T700/CNT fiber may provide more contact points between fiber and matrix due to increased surface area. It is believed to be beneficial for their application as reinforcement in composites.

Keywords: hybrid fibers, surface characterization, surface roughness, thermal stability

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4133 Relation between Low Thermal Stress and Antioxidant Enzymes Activity in a Sweetening Plant: Stevia Rebaudiana Bert

Authors: T. Bettaieb, S. Soufi, S. Arbaoui

Abstract:

Stevia rebaudiana Bert. is a natural sweet plant. The leaves contain diterpene glycosides stevioside, rebaudiosides A-F, steviolbioside and dulcoside, which are responsible for its sweet taste and have commercial value all over the world as sugar substitute in foods and medicines. Stevia rebaudiana Bert. is sensitive temperature lower than 9°C. The possibility of its outdoor culture in Tunisian conditions demand genotypes tolerant to low temperatures. In order to evaluate the low temperature tolerance of eight genotypes of Stevia rebaudiana, the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalases (CAT) were measured. Before carrying out the analyses, three genotypes of Stevia were exposed for 1 month at a temperature regime of 18°C during the day and 7°C at night similar to winter conditions in Tunisia. In response to the stress generated by low temperature, antioxidant enzymes activity revealed on native gel and quantified by spectrophotometry showed variable levels according to their degree of tolerance to low temperatures.

Keywords: chilling tolerance, enzymatic activity, stevia rebaudiana bert, low thermal stress

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4132 Microstructure, Mechanical, Electrical and Thermal Properties of the Al-Si-Ni Ternary Alloy

Authors: Aynur Aker, Hasan Kaya

Abstract:

In recent years, the use of the aluminum based alloys in the industry and technology are increasing. Alloying elements in aluminum have further been improving the strength and stiffness properties that provide superior compared to other metals. In this study, investigation of physical properties (microstructure, microhardness, tensile strength, electrical conductivity and thermal properties) in the Al-12.6wt.%Si-%2wt.Ni ternary alloy were investigated. Al-Si-Ni alloy was prepared in a graphite crucible under vacuum atmosphere. The samples were directionally solidified upwards with different growth rate (V) at constant temperature gradient G (7.73 K/mm). The microstructures (flake spacings, λ), microhardness (HV), ultimate tensile strength, electrical resistivity and thermal properties enthalpy of fusion and specific heat and melting temperature) of the samples were measured. Influence of the growth rate and flake spacings on microhardness, ultimate tensile strength and electrical resistivity were investigated and relationships between them were experimentally obtained by using regression analysis. According to results, λ values decrease with increasing V, but microhardness, ultimate tensile strength, electrical resistivity values increase with increasing V. Variations of electrical resistivity for cast samples with the temperature in the range of 300-1200 K were also measured by using a standard dc four-point probe technique. The enthalpy of fusion and specific heat for the same alloy was also determined by means of differential scanning calorimeter (DSC) from heating trace during the transformation from liquid to solid. The results obtained in this work were compared with the previous similar experimental results obtained for binary and ternary alloys.

Keywords: electrical resistivity, enthalpy, microhardness, solidification, tensile stress

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4131 Thermodynamically Predicting the Impact of Temperature on the Performance of Drilling Bits as a Function of Time

Authors: Talal Al-Bazali

Abstract:

Air drilling has recently received increasing acceptance by the oil and gas industry due to its unique advantages. The main advantages of air drilling include the higher rate of penetration, less formation damage, lower risk of loss of circulation. However, these advantages cannot be fully realized if thermal effects in air drilling are not well understood and minimized. Due to its high frictional coefficient, low heat conductivity, and high compressibility, air can impact the temperature distribution of bit and thus affect its bit performances. Based on energy and mass balances, a transient thermal model that predicts bit temperature is presented along with numerical solutions in this paper. In addition, several important parameters that influence bit temperature distribution are analyzed. Simulation results show that the bit temperature increases with increasing weight on bit and rotary speed but decreases as the standpipe pressure and flow rate increase. These results can be used to optimize drilling operations and flow parameters for an improved bit performance as shown in this paper.

Keywords: air drilling, rate of penetration, temperature, rotary speed

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4130 Forecasting Thermal Energy Demand in District Heating and Cooling Systems Using Long Short-Term Memory Neural Networks

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

Abstract:

To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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4129 An Analytical and Numerical Solutions for the Thermal Analysis of a Mechanical Draft Wet Cooling Tower

Authors: Hamed Djalal

Abstract:

The thermal analysis of the mechanical draft wet cooling tower is performed in this study by the heat and mass transfer modelization in the packing zone. After combining the heat and mass transfer laws, the mass and energy balances and by involving the Merkel assumptions; firstly, an ordinary differential equations system is derived and solved numerically by the Runge-Kutta method to determine the water and air temperatures, the humidity, and also other properties variation along the packing zone. Secondly, by making some linear assumptions for the air saturation curve, an analytical solution is formed, which is developed for the air washer calculation, but in this study, it is applied for the cooling tower to express also the previous parameters mathematically as a function of the packing height. Finally, a good agreement with experimental data is achieved by both solutions, but the numerical one seems to be the more accurate for modeling the heat and mass transfer process in the wet cooling tower.

Keywords: evaporative cooling, cooling tower, air washer, humidification, moist air, heat, and mass transfer

Procedia PDF Downloads 100
4128 Innovative Fabric Integrated Thermal Storage Systems and Applications

Authors: Ahmed Elsayed, Andrew Shea, Nicolas Kelly, John Allison

Abstract:

In northern European climates, domestic space heating and hot water represents a significant proportion of total primary total primary energy use and meeting these demands from a national electricity grid network supplied by renewable energy sources provides an opportunity for a significant reduction in EU CO2 emissions. However, in order to adapt to the intermittent nature of renewable energy generation and to avoid co-incident peak electricity usage from consumers that may exceed current capacity, the demand for heat must be decoupled from its generation. Storage of heat within the fabric of dwellings for use some hours, or days, later provides a route to complete decoupling of demand from supply and facilitates the greatly increased use of renewable energy generation into a local or national electricity network. The integration of thermal energy storage into the building fabric for retrieval at a later time requires much evaluation of the many competing thermal, physical, and practical considerations such as the profile and magnitude of heat demand, the duration of storage, charging and discharging rate, storage media, space allocation, etc. In this paper, the authors report investigations of thermal storage in building fabric using concrete material and present an evaluation of several factors that impact upon performance including heating pipe layout, heating fluid flow velocity, storage geometry, thermo-physical material properties, and also present an investigation of alternative storage materials and alternative heat transfer fluids. Reducing the heating pipe spacing from 200 mm to 100 mm enhances the stored energy by 25% and high-performance Vacuum Insulation results in heat loss flux of less than 3 W/m2, compared to 22 W/m2 for the more conventional EPS insulation. Dense concrete achieved the greatest storage capacity, relative to medium and light-weight alternatives, although a material thickness of 100 mm required more than 5 hours to charge fully. Layers of 25 mm and 50 mm thickness can be charged in 2 hours, or less, facilitating a fast response that could, aggregated across multiple dwellings, provide significant and valuable reduction in demand from grid-generated electricity in expected periods of high demand and potentially eliminate the need for additional new generating capacity from conventional sources such as gas, coal, or nuclear.

Keywords: fabric integrated thermal storage, FITS, demand side management, energy storage, load shifting, renewable energy integration

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4127 Physicochemical Properties and Thermal Inactivation of Polyphenol Oxidase of African Bush Mango (Irvingia Gabonensis) Fruit

Authors: Catherine Joke Adeseko

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Enzymatic browning is an economically important disorder that degrades organoleptic properties and prevent the consumer from purchasing fresh fruit and vegetables. Prevention and control of enzymatic browning in fruit and its product is imperative. Therefore, this study sought to investigate the catalytic effect of polyphenol oxidase (PPO) in the adverse browning of African bush mango (Irvingia gabonensis) fruit peel and pulp. PPO was isolated and purified, and its physicochemical properties, such as the effect of pH with SDS, temperature, and thermodynamic studies, which invariably led to thermal inactivation of purified PPO at 80 °C, were evaluated. The pH and temperature optima of PPO were found at 7.0 and 50, respectively. There was a gradual increase in the activity of PPO as the pH increases. However, the enzyme exhibited a higher activity at neutral pH 7.0, while enzymatic inhibition was observed at acidic region, pH 2.0. The presence of SDS at pH 5.0 downward was found to inhibit the activity of PPO from the peel and pulp of I. gabonensis. The average value of enthalpy (ΔH), entropy (ΔS), and Gibbs free energy (ΔG) obtained at 20 min of incubation and temperature 30 – 80 °C were respectively 39.93 kJ.mol-1, 431.57 J.mol-1 .K-1 and -107.99 kJ.mol-1 for peel PPO, and 37.92 kJ.mol-1, -442.51J.mol-1.K-1, and -107.22 kJ.mol-1 for pulp PPO. Thermal inactivation of PPO from I. gabonensis exhibited a reduction in catalytic activity as the temperature and duration of heat inactivation increases using catechol, reflected by an increment in k value. The half-life of PPO (t1/2) decreases as the incubation temperature increases due to the instability of the enzyme at high temperatures and was higher in pulp than peel. Both D and Z values decrease with increase in temperature. The information from this study suggests processing parameters for controlling PPO in the potential industrial application of I. gabonensis fruit in order to prolong the shelf-life of this fruit for maximum utilization.

Keywords: enzymatic, browning, characterization, activity

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4126 Improving the Performance of Gas Turbine Power Plant by Modified Axial Turbine

Authors: Hakim T. Kadhim, Faris A. Jabbar, Aldo Rona, Audrius Bagdanaviciu

Abstract:

Computer-based optimization techniques can be employed to improve the efficiency of energy conversions processes, including reducing the aerodynamic loss in a thermal power plant turbomachine. In this paper, towards mitigating secondary flow losses, a design optimization workflow is implemented for the casing geometry of a 1.5 stage axial flow turbine that improves the turbine isentropic efficiency. The improved turbine is used in an open thermodynamic gas cycle with regeneration and cogeneration. Performance estimates are obtained by the commercial software Cycle – Tempo. Design and off design conditions are considered as well as variations in inlet air temperature. Reductions in both the natural gas specific fuel consumption and in CO2 emissions are predicted by using the gas turbine cycle fitted with the new casing design. These gains are attractive towards enhancing the competitiveness and reducing the environmental impact of thermal power plant.

Keywords: axial flow turbine, computational fluid dynamics, gas turbine power plant, optimization

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4125 The Key Role of Yttrium Oxide on Devitrification Resilience of Barium Gallo-germanate Glasses: Physicochemical Properties and Crystallization Study

Authors: Samar Aoujia, Théo Guérineaub, Rayan Zaitera, Evelyne Fargina, Younès Messaddeqb, Thierry Cardinala

Abstract:

Two barium gallo-germanate glass series were elaborated to investigate the effect of the yttrium introduction on the glass physicochemical properties and crystallization behavior. One to twenty mol% of YO3/2 were either added into the glass matrix or substituted for gallium oxide. The glass structure was studied by Raman spectroscopy, and the thermal, optical, thermo-mechanical and physical properties are examined. The introduction of yttrium ions in both glass series increases the glass transition temperature, crystallization temperature, softening temperature, coefficient of linear thermal expansion and density. Through differential scanning calorimetry and X-ray diffraction analyses, it was found that competition occurs between the gallo-germanate zeolite-type phase and the yttrium-containing phase. From 13 mol% of YO3/2, the yttrium introduction impedes the formation of surface crystallization in these glasses.

Keywords: photonic, heavy-metal oxide, glass, crystallization

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4124 Automating 2D CAD to 3D Model Generation Process: Wall pop-ups

Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

Abstract:

In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

Procedia PDF Downloads 144
4123 Comparison between Photogrammetric and Structure from Motion Techniques in Processing Unmanned Aerial Vehicles Imageries

Authors: Ahmed Elaksher

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Over the last few years, significant progresses have been made and new approaches have been proposed for efficient collection of 3D spatial data from Unmanned aerial vehicles (UAVs) with reduced costs compared to imagery from satellite or manned aircraft. In these systems, a low-cost GPS unit provides the position, velocity of the vehicle, a low-quality inertial measurement unit (IMU) determines its orientation, and off-the-shelf cameras capture the images. Structure from Motion (SfM) and photogrammetry are the main tools for 3D surface reconstruction from images collected by these systems. Unlike traditional techniques, SfM allows the computation of calibration parameters using point correspondences across images without performing a rigorous laboratory or field calibration process and it is more flexible in that it does not require consistent image overlap or same rotation angles between successive photos. These benefits make SfM ideal for UAVs aerial mapping. In this paper, a direct comparison between SfM Digital Elevation Models (DEM) and those generated through traditional photogrammetric techniques was performed. Data was collected by a 3DR IRIS+ Quadcopter with a Canon PowerShot S100 digital camera. Twenty ground control points were randomly distributed on the ground and surveyed with a total station in a local coordinate system. Images were collected from an altitude of 30 meters with a ground resolution of nine mm/pixel. Data was processed with PhotoScan, VisualSFM, Imagine Photogrammetry, and a photogrammetric algorithm developed by the author. The algorithm starts with performing a laboratory camera calibration then the acquired imagery undergoes an orientation procedure to determine the cameras’ positions and orientations. After the orientation is attained, correlation based image matching is conducted to automatically generate three-dimensional surface models followed by a refining step using sub-pixel image information for high matching accuracy. Tests with different number and configurations of the control points were conducted. Camera calibration parameters estimated from commercial software and those obtained with laboratory procedures were comparable. Exposure station positions were within less than few centimeters and insignificant differences, within less than three seconds, among orientation angles were found. DEM differencing was performed between generated DEMs and few centimeters vertical shifts were found.

Keywords: UAV, photogrammetry, SfM, DEM

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4122 Electrode Performance of Carbon Coated Nanograined LiFePO4 in Lithium Batteries

Authors: Princess Stephanie P. Llanos, Rinlee Butch M. Cervera

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Lithium iron phosphate (LiFePO4) is a potential cathode material for lithium-ion batteries due to its promising characteristics. In this study, carbon-coated nanograined LiFePO4 is synthesized via wet chemistry method at a low temperature of 400 °C and investigated its performance as a cathode in Lithium battery. The X-ray diffraction pattern of the synthesized samples can be indexed to an orthorhombic LiFePO4 structure. Agglomerated particles that range from 200 nm to 300 nm are observed from scanning electron microscopy images. Transmission electron microscopy images confirm the crystalline structure of LiFePO4 and coating of amorphous carbon layer. Elemental mapping using Energy dispersive spectroscopy analysis revealed the homogeneous dispersion of Fe, P, O, and C elements. On the other hand, the electrochemical performances of the synthesized cathodes were investigated using cyclic voltammetry, galvanostatic charge/discharge tests with different C-rates, and cycling performances. Galvanostatic charge and discharge measurements revealed that the sample sintered at 400 °C for 3 hours with carbon coating demonstrated the highest capacity among the samples which reaches up to 160 mAhg⁻¹ at 0.1C rate.

Keywords: cathode, charge-discharge, electrochemical, lithium batteries

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4121 Thermoelectric Blanket for Aiding the Treatment of Cerebral Hypoxia and Other Related Conditions

Authors: Sarayu Vanga, Jorge Galeano-Cabral, Kaya Wei

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Cerebral hypoxia refers to a condition in which there is a decrease in oxygen supply to the brain. Patients suffering from this condition experience a decrease in their body temperature. While there isn't any cure to treat cerebral hypoxia as of date, certain procedures are utilized to help aid in the treatment of the condition. Regulating the body temperature is an example of one of those procedures. Hypoxia is well known to reduce the body temperature of mammals, although the neural origins of this response remain uncertain. In order to speed recovery from this condition, it is necessary to maintain a stable body temperature. In this study, we present an approach to regulating body temperature for patients who suffer from cerebral hypoxia or other similar conditions. After a thorough literature study, we propose the use of thermoelectric blankets, which are temperature-controlled thermal blankets based on thermoelectric devices. These blankets are capable of heating up and cooling down the patient to stabilize body temperature. This feature is possible through the reversible effect that thermoelectric devices offer while behaving as a thermal sensor, and it is an effective way to stabilize temperature. Thermoelectricity is the direct conversion of thermal to electrical energy and vice versa. This effect is now known as the Seebeck effect, and it is characterized by the Seebeck coefficient. In such a configuration, the device has cooling and heating sides with temperatures that can be interchanged by simply switching the direction of the current input in the system. This design integrates various aspects, including a humidifier, ventilation machine, IV-administered medication, air conditioning, circulation device, and a body temperature regulation system. The proposed design includes thermocouples that will trigger the blanket to increase or decrease a set temperature through a medical temperature sensor. Additionally, the proposed design allows an efficient way to control fluctuations in body temperature while being cost-friendly, with an expected cost of 150 dollars. We are currently working on developing a prototype of the design to collect thermal and electrical data under different conditions and also intend to perform an optimization analysis to improve the design even further. While this proposal was developed for treating cerebral hypoxia, it can also aid in the treatment of other related conditions, as fluctuations in body temperature appear to be a common symptom that patients have for many illnesses.

Keywords: body temperature regulation, cerebral hypoxia, thermoelectric, blanket design

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4120 Automatic Differentiation of Ultrasonic Images of Cystic and Solid Breast Lesions

Authors: Dmitry V. Pasynkov, Ivan A. Egoshin, Alexey A. Kolchev, Ivan V. Kliouchkin

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In most cases, typical cysts are easily recognized at ultrasonography. The specificity of this method for typical cysts reaches 98%, and it is usually considered as gold standard for typical cyst diagnosis. However, it is necessary to have all the following features to conclude the typical cyst: clear margin, the absence of internal echoes and dorsal acoustic enhancement. At the same time, not every breast cyst is typical. It is especially characteristic for protein-contained cysts that may have significant internal echoes. On the other hand, some solid lesions (predominantly malignant) may have cystic appearance and may be falsely accepted as cysts. Therefore we tried to develop the automatic method of cystic and solid breast lesions differentiation. Materials and methods. The input data were the ultrasonography digital images with the 256-gradations of gray color (Medison SA8000SE, Siemens X150, Esaote MyLab C). Identification of the lesion on these images was performed in two steps. On the first one, the region of interest (or contour of lesion) was searched and selected. Selection of such region is carried out using the sigmoid filter where the threshold is calculated according to the empirical distribution function of the image brightness and, if necessary, it was corrected according to the average brightness of the image points which have the highest gradient of brightness. At the second step, the identification of the selected region to one of lesion groups by its statistical characteristics of brightness distribution was made. The following characteristics were used: entropy, coefficients of the linear and polynomial regression, quantiles of different orders, an average gradient of brightness, etc. For determination of decisive criterion of belonging to one of lesion groups (cystic or solid) the training set of these characteristics of brightness distribution separately for benign and malignant lesions were received. To test our approach we used a set of 217 ultrasonic images of 107 cystic (including 53 atypical, difficult for bare eye differentiation) and 110 solid lesions. All lesions were cytologically and/or histologically confirmed. Visual identification was performed by trained specialist in breast ultrasonography. Results. Our system correctly distinguished all (107, 100%) typical cysts, 107 of 110 (97.3%) solid lesions and 50 of 53 (94.3%) atypical cysts. On the contrary, with the bare eye it was possible to identify correctly all (107, 100%) typical cysts, 96 of 110 (87.3%) solid lesions and 32 of 53 (60.4%) atypical cysts. Conclusion. Automatic approach significantly surpasses the visual assessment performed by trained specialist. The difference is especially large for atypical cysts and hypoechoic solid lesions with the clear margin. This data may have a clinical significance.

Keywords: breast cyst, breast solid lesion, differentiation, ultrasonography

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4119 A Simulation Model and Parametric Study of Triple-Effect Desalination Plant

Authors: Maha BenHamad, Ali Snoussi, Ammar Ben Brahim

Abstract:

A steady-state analysis of triple-effect thermal vapor compressor desalination unit was performed. A mathematical model based on mass, salinity and energy balances is developed. The purpose of this paper is to develop a connection between process simulator and process optimizer in order to study the influence of several operating variables on the performance and the produced water cost of the unit. A MATLAB program is used to solve the model equations, and Aspen HYSYS is used to model the plant. The model validity is examined against a commercial plant and showed a good agreement between industrial data and simulations results. Results show that the pressures of the last effect and the compressed vapor have an important influence on the produced cost, and the increase of the difference temperature in the condenser decreases the specific heat area about 22%.

Keywords: steady-state, triple effect, thermal vapor compressor, Matlab, Aspen Hysys

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4118 Development of a CFD Model for PCM Based Energy Storage in a Vertical Triplex Tube Heat Exchanger

Authors: Pratibha Biswal, Suyash Morchhale, Anshuman Singh Yadav, Shubham Sanjay Chobe

Abstract:

Energy demands are increasing whereas energy sources, especially non-renewable sources are limited. Due to the intermittent nature of renewable energy sources, it has become the need of the hour to find new ways to store energy. Out of various energy storage methods, latent heat thermal storage devices are becoming popular due to their high energy density per unit mass and volume at nearly constant temperature. This work presents a computational fluid dynamics (CFD) model using ANSYS FLUENT 19.0 for energy storage characteristics of a phase change material (PCM) filled in a vertical triplex tube thermal energy storage system. A vertical triplex tube heat exchanger, just like its name consists of three concentric tubes (pipe sections) for parting the device into three fluid domains. The PCM is filled in the middle domain with heat transfer fluids flowing in the outer and innermost domains. To enhance the heat transfer inside the PCM, eight fins have been incorporated between the internal and external tubes. These fins run radially outwards from the outer-wall of innermost tube to the inner-wall of the middle tube dividing the middle domain (between innermost and middle tube) into eight sections. These eight sections are then filled with a PCM. The validation is carried with earlier work and a grid independence test is also presented. Further studies on freezing and melting process were carried out. The results are presented in terms of pictorial representation of isotherms and liquid fraction

Keywords: heat exchanger, thermal energy storage, phase change material, CFD, latent heat

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4117 Nanoparticulated (U,Gd)O2 Characterization

Authors: A. Fernandez Zuvich, I. Gana Watkins, H. Zolotucho, H. Troiani, A. Caneiro, M. Prado, A. L. Soldati

Abstract:

The study of actinide nanoparticles (NPs) has attracted the attention of the scientific community not only because the lack of information about their ecotoxicological effects but also because the use of NPs could open a new way in the production of nuclear energy. Indeed, it was recently demonstrated that UO2 NPs sintered pellets exhibit closed porosity with improved fission gas retention and radiation-tolerance , ameliorated mechanical properties, and less detriment of the thermal conductivity upon use, making them an interesting option for new nuclear fuels. In this work, we used a combination of diffraction and microscopy tools to characterize the morphology, the crystalline structure and the composition of UO2 nanoparticles doped with 10%wt Gd2O3. The particles were synthesized by a modified sol-gel method at low temperatures. X-ray Diffraction (XRD) studies determined the presence of a unique phase with the cubic structure and Fm3m spatial group, supporting that Gd atoms substitute U atoms in the fluorite structure of UO2. In addition, Field Emission Gun Scanning (FEG-SEM) and Transmission (FEG-TEM) Electron Microscopy images revealed the presence of micrometric agglomerates of nanoparticles, with rounded morphology and an average crystallite size < 50 nm. Energy Dispersive Spectroscopy (EDS) coupled to TEM determined the presence of Gd in all the analyzed crystallites. Besides, FEG-SEM-EDS showed a homogeneous concentration distribution at the micrometer scale indicating that the small size of the crystallites compensates the variation in composition by averaging a large number of crystallites. These techniques, as combined tools resulted thus essential to find out details of morphology and composition distribution at the sub-micrometer scale, and set a standard for developing and analyzing nanoparticulated nuclear fuels.

Keywords: actinide nanoparticles, burnable poison, nuclear fuel, sol-gel

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4116 Modelling and Assessment of an Off-Grid Biogas Powered Mini-Scale Trigeneration Plant with Prioritized Loads Supported by Photovoltaic and Thermal Panels

Authors: Lorenzo Petrucci

Abstract:

This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

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4115 Biodiesel Synthesis Using Animal Excreta-Based Biochar and Waste Cooking Oil

Authors: Sang-Ryong Lee, Min-Woon Jung, Deugwoo Han, Kiyong Kim

Abstract:

This study laid an emphasis on the possible employment of biochar generated from pyrolysis of animal excreta to establish a green platform for producing biodiesel. To this end, the pseudo-catalytic transesterification reaction using chicken manure biochar and waste cooking oil was investigated. Compared with a commercial porous material (SiO2), chicken manure biochar generated from 350 C showed better performance, resulting in 95.6% of the FAME yield at 350C. The Ca species in chicken manure biochar imparted strong catalytic capability by providing the basicity for transesterification. The identified catalytic effect also led to the thermal cracking of unsaturated FAMEs, which decreased the overall FAME yield. For example, 40–60% of converted FAMEs were thermally degraded. To avoid undesirable thermal cracking arising from the high content of the Ca species in chicken manure biochar, the fabrication of chicken manure biochar at temperatures ≥350C was highly recommended.

Keywords: Trasesterification, Animal excreta, FAME, Biochar, Chicken manure

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4114 Carbon-Doped TiO2 Nanofibers Prepared by Electrospinning

Authors: ChoLiang Chung, YuMin Chen

Abstract:

C-doped TiO2 nanofibers were prepared by electrospinning successfully. Different amounts of carbon were added into the nanofibers by using chitosan, aiming to shift the wave length that is required to excite the photocatalyst from ultraviolet light to visible light. Different amounts of carbon and different atmosphere fibers were calcined at 500oC, and the optical characteristic of C-doped TiO2 nanofibers had been changed. characterizes of nanofibers were identified by X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FE-SEM), UV-vis, Atomic Force Microscope (AFM), and Fourier Transform Infrared Spectroscopy (FTIR). The XRD is used to identify the phase composition of nanofibers. The morphology of nanofibers were explored by FE-SEM and AFM. Optical characteristics of absorption were measured by UV-Vis. Three dimension surface images of C-doped TiO2 nanofibers revealed different effects of processing. The results of XRD showed that the phase of C-doped TiO2 nanofibers transformed to rutile phase and anatase phase successfully. The results of AFM showed that the surface morphology of nanofibers became smooth after high temperature treatment. Images from FE-SEM revealed the average size of nanofibers. UV-vis results showed that the band-gap of TiO2 were reduced. Finally, we found out C-doped TiO2 nanofibers can change countenance of nanofiber and make it smoother.

Keywords: carbon, TiO2, chitosan, electrospinning

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4113 Synthetic Aperture Radar Remote Sensing Classification Using the Bag of Visual Words Model to Land Cover Studies

Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

Abstract:

Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words (BOVW), classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar (PolSAR)

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4112 Ensemble of Deep CNN Architecture for Classifying the Source and Quality of Teff Cereal

Authors: Belayneh Matebie, Michael Melese

Abstract:

The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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4111 From Data Processing to Experimental Design and Back Again: A Parameter Identification Problem Based on FRAP Images

Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

Abstract:

FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

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4110 Dynamic Thermal Modelling of a PEMFC-Type Fuel Cell

Authors: Marco Avila Lopez, Hasnae Ait-Douchi, Silvia De Los Santos, Badr Eddine Lebrouhi, Pamela Ramírez Vidal

Abstract:

In the context of the energy transition, fuel cell technology has emerged as a solution for harnessing hydrogen energy and mitigating greenhouse gas emissions. An in-depth study was conducted on a PEMFC-type fuel cell, with an initiation of an analysis of its operational principles and constituent components. Subsequently, the modelling of the fuel cell was undertaken using the Python programming language, encompassing both steady-state and transient regimes. In the case of the steady-state regime, the physical and electrochemical phenomena occurring within the fuel cell were modelled, with the assumption of uniform temperature throughout all cell compartments. Parametric identification was carried out, resulting in a remarkable mean error of only 1.62% when the model results were compared to experimental data documented in the literature. The dynamic model that was developed enabled the scrutiny of the fuel cell's response in terms of temperature and voltage under varying current conditions.

Keywords: fuel cell, modelling, dynamic, thermal model, PEMFC

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4109 3-D Numerical Simulation of Scraped Surface Heat Exchanger with Helical Screw

Authors: Rabeb Triki, Hassene Djemel, Mounir Baccar

Abstract:

Surface scraping is a passive heat transfer enhancement technique that is directly used in scraped surface heat exchanger (SSHE). The scraping action prevents the accumulation of the product on the inner wall, which intensifies the heat transfer and avoids the formation of dead zones. SSHEs are widely used in industry for several applications such as crystallization, sterilization, freezing, gelatinization, and many other continuous processes. They are designed to deal with products that are viscous, sticky or that contain particulate matter. This research work presents a three-dimensional numerical simulation of the coupled thermal and hydrodynamic behavior within a SSHE which includes Archimedes’ screw instead of scraper blades. The finite volume Fluent 15.0 was used to solve continuity, momentum and energy equations using multiple reference frame formulation. The process fluid investigated under this study is the pure glycerin. Different geometrical parameters were studied in the case of steady, non-isothermal, laminar flow. In particular, attention is focused on the effect of the conicity of the rotor and the pitch of Archimedes’ screw on temperature and velocity distribution and heat transfer rate. Numerical investigations show that the increase of the number of turns in the screw from five to seven turns leads to amelioration of heat transfer coefficient, and the increase of the conicity of the rotor from 0.1 to 0.15 leads to an increase in the rate of heat transfer. Further studies should investigate the effect of different operating parameters (axial and rotational Reynolds number) on the hydrodynamic and thermal behavior of the SSHE.

Keywords: ANSYS-Fluent, hydrodynamic behavior, scraped surface heat exchange, thermal behavior

Procedia PDF Downloads 160