Search results for: thermal cycling machine

Authors: William Sigvardsson, Christoffer Alenius, Jenny Lindblom, Andreas Johansson, Marcus Sandberg

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This article covers a study focusing on a subarctic greenhouse located in Nikkala, Sweden. Through a visit and the creation of a CFD model, the study investigates the differences in energy demand with high pressure sodium (HPS) lights and light emitting diode (LED) lights in combination with an air-carried and water-carried heating system accordingly. Through an IDA ICE model, the impact of insulating the parts of the greenhouse without active cultivation was also investigated. This, with the purpose of comparing the current system in the greenhouse to state-of-the-art alternatives and evaluating if an investment in either a water-carried heating system in combination with LED lights and insulating the non-cultivating parts of the greenhouse could be considered profitable. Operating a greenhouse in the harsh subarctic climate found in the northern parts of Sweden is not an easy task and especially if the operation is year-round. With an average temperature of under -5 °C from November through January, efficient growing techniques are a must to ensure a profitable business. Today the most crucial parts of a greenhouse are the heating system, lighting system, dehumidifying measures, as well as thermal screen, and the impact of a poorly designed system in a sub-arctic could be devastating as the margins are slim. The greenhouse studied uses a pellet burner to power their air- carried heating system which is used. The simulations found the resulting savings amounted to just under 14 800 SEK monthly or 18 % of the total cost of energy by implementing the water-carrying heating system in combination with the LED lamps. Given this, a payback period of 3-9 years could be expected given different scenarios, including specific time periods, financial aids, and the resale price of the current system. The insulation of the non-cultivating parts of the greenhouse was found to have possible savings of 25 300 SEK annually or 46 % of the current heat demand resulting in a payback period of just over 1-2 years. Given the possible energy savings, a reduction in emitted CO2 equivalents of almost 1,9 tonnes could be achieved annually. It was concluded that relatively inexpensive investments in modern greenhouse equipment could make a significant contribution to reducing the energy consumption of the greenhouse resulting in a more competitive business environment for sub-arctic greenhouse owners. New parts of the greenhouse should be built with the water-carried heating system in combination with state-of-the-art LED lights, and all parts which are not housing active cultivation should be insulated. If the greenhouse in Nikkala is eligible for financial aid or finds a resale value in the current system, an investment should be made in a new water-carried heating system in combination with LED lights.

Keywords: energy efficiency, sub-arctic greenhouses, energy measures, greenhouse climate control, greenhouse technology, CFD

Procedia PDF Downloads 69

Authors: D. Falliano, G. Ricciardi, E. Gugliandolo

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Foamed concrete belongs to the category of lightweight concrete. It is characterized by a density which is generally ranging from 200 to 2000 kg/m³ and typically comprises cement, water, preformed foam, fine sand and eventually fine particles such as fly ash or silica fume. The foam component mixed with the cement paste give rise to the development of a system of air-voids in the cementitious matrix. The peculiar characteristics of foamed concrete elements are summarized in the following aspects: 1) lightness which allows reducing the dimensions of the resisting frame structure and is advantageous in the scope of refurbishment or seismic retrofitting in seismically vulnerable areas; 2) thermal insulating properties, especially in the case of low densities; 3) the good resistance against fire as compared to ordinary concrete; 4) the improved workability; 5) cost-effectiveness due to the usage of rather simple constituting elements that are easily available locally. Classic foamed concrete cannot be extruded, as the dimensional stability is not permitted in the green state and this severely limits the possibility of industrializing them through a simple and cost-effective process, characterized by flexibility and high production capacity. In fact, viscosity enhancing agents (VEA) used to extrude traditional concrete, in the case of foamed concrete cause the collapsing of air bubbles, so that it is impossible to extrude a lightweight product. These requirements have suggested the study of a particular additive that modifies the rheology of foamed concrete fresh paste by increasing cohesion and viscosity and, at the same time, stabilizes the bubbles into the cementitious matrix, in order to allow the dimensional stability in the green state and, consequently, the extrusion of a lightweight product. There are plans to submit the additive’s formulation to patent. In addition to the general benefits of using the extrusion process, extrudable foamed concrete allow other limits to be exceeded: elimination of formworks, expanded application spectrum, due to the possibility of extrusion in a range varying between 200 and 2000 kg/m³, which allows the prefabrication of both structural and non-structural constructive elements. Besides, this contribution aims to present the significant differences regarding extrudable and classic foamed concrete fresh properties in terms of slump. Plastic air content, plastic density, hardened density and compressive strength have been also evaluated. The outcomes show that there are no substantial differences between extrudable and classic foamed concrete compression resistances.

Keywords: compressive strength, extrusion, foamed concrete, fresh properties, plastic air content, slump.

Procedia PDF Downloads 170

Authors: Bharatkumar Doshi

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Electro-Magnetic Pulse Welding (EMPW) is a solid state welding process carried out at almost room temperature, in which joining is enabled by high impact velocity deformation. In this process, high voltage capacitor’s stored energy is discharged in an EM coil resulting in a damped, sinusoidal current with an amplitude of several hundred kiloamperes. Due to these transient magnetic fields of few tens of Tesla near the coil is generated. As the conductive (tube) part is positioned in this area, an opposing eddy current is induced in this part. Consequently, high Lorentz forces act on the part, leading to acceleration away from the coil. In case of a tube, it gets compressed under forming velocities of more than 300 meters per second. After passing the joining gap it collides with the second metallic joining rod, leading to the formation of a jet under appropriate collision conditions. Due to the prevailing high pressure, metallurgical bonding takes place. A characteristic feature is the wavy interface resulting from the heavy plastic deformations. In the process, the formation of intermetallic compounds which might deteriorate the weld strength can be avoided, even for metals with dissimilar thermal properties. In order to optimize the process parameters like current, voltage, inductance, coil dimensions, workpiece dimensions, air gap, impact velocity, effective plastic strain, shear stress acting in the welding zone/impact zone etc. are very critical and important to establish. These process parameters could be determined by simulation using Finite Element Methods (FEM) in which electromagnetic –structural couple field analysis is performed. The feasibility of welding could thus be investigated by varying the parameters in the simulation using COMSOL. Simulation results shall be applied in performing the preliminary experiments of welding the different alloy steel tubes and/or alloy steel to other materials. The single turn coil (S.S.304) with field shaper (copper) has been designed and manufactured. The preliminary experiments are performed using existing EMPW facility available Institute for Plasma Research, Gandhinagar, India. The experiments are performed at 22kV charged into 64µF capacitor bank and the energy is discharged into single turn EM coil. Welding of axi-symetric components such as aluminum tube and rod has been proven experimentally using EMPW techniques. In this paper EM coil design, manufacturing, Electromagnetic-structural FEM simulation of Magnetic Pulse Welding and preliminary experiment results is reported.

Keywords: COMSOL, EMPW, FEM, Lorentz force

Procedia PDF Downloads 174

Authors: Mona Mohamed Shawkt Ragab, Heba Mohamed Darwish

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Context: Comfort properties of garments are crucial for the wearer, and with the increasing demand for cotton fabric, there is a need to explore alternative fabrics that can offer similar or superior comfort properties. This study focuses on comparing the comfort properties of tencel/cotton single jersey fabric and cotton single jersey fabric, with the aim of identifying fabrics that are more suitable for summer clothes. Research Aim: The aim of this study is to evaluate the comfort properties of tencel/cotton single jersey fabric and cotton single jersey fabric, with the goal of identifying fabrics that can serve as alternatives to cotton, considering their comfort properties for summer clothing. Methodology: An experimental, analytical approach was employed in this study. Two circular knitting machines were used to produce the fabrics, one with a 24 inches gauge and the other with a 28 inches gauge. Both fabrics were knitted with three different loop lengths (3.05 mm, 2.9 mm, and 2.6 mm) to obtain loose, medium, and tight fabrics for evaluation. Various comfort properties, including air permeability, water vapor permeability, wickability, and thermal resistance, were measured for both fabric types. Findings: The study found a significant difference in comfort properties between tencel/cotton single jersey fabric and cotton single jersey fabric. Tencel/cotton fabric exhibited higher air permeability, water vapor permeability, and wickability compared to cotton fabric. These findings suggest that tencel fabric is more suitable for summer clothes due to its superior ventilation and absorption properties. Theoretical Importance: This study contributes to the exploration of alternative fabrics to cotton by evaluating their comfort properties. By identifying fabrics that offer better comfort properties than cotton, particularly in terms of water usage, the study provides valuable insights into sustainable fabric choices for the fashion industry. Data Collection and Analysis Procedures: The comfort properties of the fabrics were measured using appropriate testing methods. Paired comparison t-tests were conducted to determine the significant differences between tencel/cotton fabric and cotton fabric in the measured properties. Correlation coefficients were also calculated to examine the relationships between the factors under study. Question Addressed: The study addresses the question of whether tencel/cotton single jersey fabric can serve as an alternative to cotton fabric for summer clothes, considering their comfort properties. Conclusion: The study concludes that tencel/cotton single jersey fabric offers superior comfort properties compared to cotton single jersey fabric, making it a suitable alternative for summer clothes. The findings also highlight the importance of considering fabric properties, such as air permeability, water vapor permeability, and wickability, when selecting materials for garments to enhance wearer comfort. This research contributes to the search for sustainable alternatives to cotton and provides valuable insights for the fashion industry in making informed fabric choices.

Keywords: comfort properties, cotton fabric, tencel fabric, single jersey

Procedia PDF Downloads 68

Authors: V. Samulionis, J. Banys, A. Sánchez-Ferrer

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Inorganic nanoparticles are used for fabrication of various composites based on polymer materials because they exhibit a good homogeneity and solubility of the composite material. Multifunctional materials based on composites of a polymer containing inorganic nanotubes are expected to have a great impact on industrial applications in the future. An emerging family of such composites are polyurea elastomers with inorganic MoS2 nanotubes or MoSI nanowires. Polyurea elastomers are a new kind of materials with higher performance than polyurethanes. The improvement of mechanical, chemical and thermal properties is due to the presence of hydrogen bonds between the urea motives which can be erased at high temperature softening the elastomeric network. Such materials are the combination of amorphous polymers above glass transition and crosslinkers which keep the chains into a single macromolecule. Polyurea exhibits a phase separated structure with rigid urea domains (hard domains) embedded in a matrix of flexible polymer chains (soft domains). The elastic properties of polyurea can be tuned over a broad range by varying the molecular weight of the components, the relative amount of hard and soft domains, and concentration of nanoparticles. Ultrasonic methods as non-destructive techniques can be used for elastomer composites characterization. In this manner, we have studied the temperature dependencies of the longitudinal ultrasonic velocity and ultrasonic attenuation of these new polyurea elastomers and composites with inorganic nanoparticles. It was shown that in these polyurea elastomers large ultrasonic attenuation peak and corresponding velocity dispersion exists at 10 MHz frequency below room temperature and this behaviour is related to glass transition Tg of the soft segments in the polymer matrix. The relaxation parameters and Tg depend on the segmental molecular weight of the polymer chains between crosslinking points, the nature of the crosslinkers in the network and content of MoS2 nanotubes or MoSI nanowires. The increase of ultrasonic velocity in composites modified by nanoparticles has been observed, showing the reinforcement of the elastomer. In semicrystalline polyurea elastomer matrices, above glass transition, the first order phase transition from quasi-crystalline to the amorphous state has been observed. In this case, the sharp ultrasonic velocity and attenuation anomalies were observed near the transition temperature TC. Ultrasonic attenuation maximum related to glass transition was reduced in quasicrystalline polyureas indicating less influence of soft domains below TC. The first order phase transition in semicrystalline polyurea elastomer samples has large temperature hysteresis (> 10 K). The impact of inorganic MoS2 nanotubes resulted in the decrease of the first order phase transition temperature in semicrystalline composites.

Keywords: inorganic nanotubes, polyurea elastomer composites, ultrasonic velocity, ultrasonic attenuation

Procedia PDF Downloads 297

Authors: Saman Ahani, Aboozar Dehghan, Roham Vali, Hamid Salehian, Amin Ebrahimi

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Pulsed-wave (PW) doppler ultrasonography is a non-invasive, relatively accurate imaging technique that can measure blood speed. The imaging could be obtained via the common carotid artery, as one of the main vessels supplying the blood of vital organs. In horses, factors such as susceptibility to depression of the cardiovascular system and their large muscular mass have rendered them vulnerable to changes in blood speed. One of the most important factors causing blood velocity changes is the administration of anesthetic drugs, including Ketamine and Acepromazine. Thus, in this study, the Pulsed-wave doppler technique was performed to assess the highest blood velocity in the common carotid artery following administration of Ketamine and Acepromazine. Six male and six female healthy Kurdish horses weighing 351 ± 46 kg (mean ± SD) and aged 9.2 ± 1.7 years (mean ± SD) were housed under animal welfare guidelines. After fasting for six hours, the normal blood flow velocity in the common carotid artery was measured using a Pulsed-wave doppler ultrasonography machine (BK Medical, Denmark), and a high-frequency linear transducer (12 MHz) without applying any sedative drugs as a control group. The same procedure was repeated after each individual received the following medications: 1.1, 2.2 mg/kg Ketamine (Pfizer, USA), and 0.5, 1 mg/kg Acepromizine (RACEHORSE MEDS, Ukraine), with an interval of 21 days between the administration of each dose and/or drug. The ultrasonographic study was done five (T5) and fifteen (T15) minutes after injecting each dose intravenously. Lastly, the statistical analysis was performed using SPSS software version 22 for Windows and a P value less than 0.05 was considered to be statistically significant. Five minutes after administration of Ketamine (1.1, 2.2 mg/kg) in both male and female horses, the blood velocity decreased to 38.44, 34.53 cm/s in males, and 39.06, 34.10 cm/s in females in comparison to the control group (39.59 and 40.39 cm/s in males and females respectively) while administration of 0.5 mg/kg Acepromazine led to a significant rise (73.15 and 55.80 cm/s in males and females respectively) (p<0.05). It means that the most drastic change in blood velocity, regardless of gender, refers to the latter dose/drug. In both medications and both genders, the increase in doses led to a decrease in blood velocity compared to the lower dose of the same drug. In all experiments in this study, the blood velocity approached its normal value at T15. In another study comparing the blood velocity changes affected by Ketamine and Acepromazine through femoral arteries, the most drastic changes were attributed to Ketamine; however, in this experiment, the maximum blood velocity was observed following administration of Acepromazine via the common carotid artery. Therefore, further experiments using the same medications are suggested using Pulsed-wave doppler measuring the blood velocity changes in both femoral and common carotid arteries simultaneously.

Keywords: Acepromazine, common carotid artery, horse, ketamine, pulsed-wave doppler ultrasonography

Procedia PDF Downloads 119

Authors: Domenico Panno, Antonino D’amico, Hamed Jafargholi

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This paper presents an experimental analysis of the performance of a system for freezing fish products equipped with a modulating vapour injection scroll compressor operating with R448A refrigerant. Freezing is a critical process for the preservation of seafood products, as it influences quality, food safety, and environmental sustainability. The use of a modulating scroll compressor with vapour injection, associated with the R448A refrigerant, is proposed as a solution to optimize the performance of the system, reducing energy consumption and mitigating the environmental impact. The stream injection modulating scroll compressor represents an advanced technology that allows you to adjust the compressor capacity based on the actual cooling needs of the system. Vapour injection allows the optimization of the refrigeration cycle, reducing the evaporation temperature and improving the overall efficiency of the system. The use of R448A refrigerant, with a low Global Warming Potential (GWP), is part of an environmental sustainability perspective, helping to reduce the climate impact of the system. The aim of this research was to evaluate the performance of the system through a series of experiments conducted on a pilot plant for the freezing of fish products. Several operational variables were monitored and recorded, including evaporation temperature, condensation temperature, energy consumption, and freezing time of seafood products. The results of the experimental analysis highlighted the benefits deriving from the use of the modulating vapour injection scroll compressor with the R448A refrigerant. In particular, a significant reduction in energy consumption was recorded compared to conventional systems. The modulating capacity of the compressor made it possible to adapt the cold production to variations in the thermal load, ensuring optimal operation of the system and reducing energy waste. Furthermore, the use of an electronic expansion valve highlighted greater precision in the control of the evaporation temperature, with minimal deviation from the desired set point. This helped ensure better quality of the final product, reducing the risk of damage due to temperature changes and ensuring uniform freezing of the fish products. The freezing time of seafood has been significantly reduced thanks to the configuration of the entire system, allowing for faster production and greater production capacity of the plant. In conclusion, the use of a modulating vapour injection scroll compressor operating with R448A has proven effective in improving the performance of a system for freezing fish products. This technology offers an optimal balance between energy efficiency, temperature control, and environmental sustainability, making it an advantageous choice for food industries.

Keywords: scroll compressor, vapor injection, refrigeration system, EER

Procedia PDF Downloads 31

Authors: Anne C. Richer-De-Forges, Dominique Arrouays, Songchao Chen, Mercedes Roman Dobarco

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Most of the digital soil mapping (DSM) products rely on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs. However, many other observations (often qualitative, nominal, or ordinal) could be used as proxies of lab measurements or as input data for ML of PTF predictions. DSM and ML are briefly described with some examples taken from the literature. Then, we explore the potential of an ordinal qualitative variable, i.e., the hand-feel soil texture (HFST) estimating the mineral particle distribution (PSD): % of clay (0-2µm), silt (2-50µm) and sand (50-2000µm) in 15 classes. The PSD can also be measured by lab measurements (LAST) to determine the exact proportion of these particle-sizes. However, due to cost constraints, HFST are much more numerous and spatially dense than LAST. Soil texture (ST) is a very important soil parameter to map as it is controlling many of the soil properties and functions. Therefore, comes an essential question: is it possible to use HFST as a proxy of LAST for calibration and/or validation of DSM predictions of ST? To answer this question, the first step is to compare HFST with LAST on a representative set where both information are available. This comparison was made on ca 17,400 samples representative of a French region (34,000 km2). The accuracy of HFST was assessed, and each HFST class was characterized by a probability distribution function (PDF) of its LAST values. This enables to randomly replace HFST observations by LAST values while respecting the PDF previously calculated and results in a very large increase of observations available for the calibration or validation of PTF and ML predictions. Some preliminary results are shown. First, the comparison between HFST classes and LAST analyses showed that accuracies could be considered very good when compared to other studies. The causes of some inconsistencies were explored and most of them were well explained by other soil characteristics. Then we show some examples applying these relationships and the increase of data to several issues related to DSM. The first issue is: do the PDF functions that were established enable to use HSFT class observations to improve the LAST soil texture prediction? For this objective, we replaced all HFST for topsoil by values from the PDF 100 time replicates). Results were promising for the PTF we tested (a PTF predicting soil water holding capacity). For the question related to the ML prediction of LAST soil texture on the region, we did the same kind of replacement, but we implemented a 10-fold cross-validation using points where we had LAST values. We obtained only preliminary results but they were rather promising. Then we show another example illustrating the potential of using HFST as validation data. As in numerous countries, the HFST observations are very numerous; these promising results pave the way to an important improvement of DSM products in all the countries of the world.

Keywords: digital soil mapping, improvement of digital soil mapping predictions, potential of using hand-feel soil texture, soil texture prediction

Procedia PDF Downloads 215

Authors: Junior Akunzi

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In the matter of patient treatment planning quality assurance in 3D conformational therapy (3D-CRT) and volumetric arc therapy (VMAT or RapidArc), the independent monitor unit verification calculation (MUVC) is an indispensable part of the process. Concerning 3D-CRT treatment planning, the MUVC can be performed manually applying the standard ESTRO formalism. However, due to the complex shape and the amount of beams in advanced treatment planning technic such as RapidArc, the manual independent MUVC is inadequate. Therefore, commercially available software such as RadCalc can be used to perform the MUVC in complex treatment planning been. Indeed, RadCalc (version 6.3 LifeLine Inc.) uses a simplified Clarkson algorithm to compute the dose contribution for individual RapidArc fields to the isocenter. The purpose of this project is the validation of RadCalc in 3D-CRT and RapidArc for treatment planning dosimetry quality assurance at Antoine Lacassagne center (Nice, France). Firstly, the interfaces between RadCalc and our treatment planning systems (TPS) Isogray (version 4.2) and Eclipse (version13.6) were checked for data transfer accuracy. Secondly, we created test plans in both Isogray and Eclipse featuring open fields, wedges fields, and irregular MLC fields. These test plans were transferred from TPSs according to the radiotherapy protocol of DICOM RT to RadCalc and the linac via Mosaiq (version 2.5). Measurements were performed in water phantom using a PTW cylindrical semiflex ionisation chamber (0.3 cm³, 31010) and compared with the TPSs and RadCalc calculation. Finally, 30 3D-CRT plans and 40 RapidArc plans created with patients CT scan were recalculated using the CT scan of a solid PMMA water equivalent phantom for 3D-CRT and the Octavius II phantom (PTW) CT scan for RapidArc. Next, we measure the doses delivered into these phantoms for each plan with a 0.3 cm³ PTW 31010 cylindrical semiflex ionisation chamber (3D-CRT) and 0.015 cm³ PTW PinPoint ionisation chamber (Rapidarc). For our test plans, good agreements were found between calculation (RadCalc and TPSs) and measurement (mean: 1.3%; standard deviation: ± 0.8%). Regarding the patient plans, the measured doses were compared to the calculation in RadCalc and in our TPSs. Moreover, RadCalc calculations were compared to Isogray and Eclispse ones. Agreements better than (2.8%; ± 1.2%) were found between RadCalc and TPSs. As for the comparison between calculation and measurement the agreement for all of our plans was better than (2.3%; ± 1.1%). The independent MU verification calculation software RadCal has been validated for clinical use and for both 3D-CRT and RapidArc techniques. The perspective of this project includes the validation of RadCal for the Tomotherapy machine installed at centre Antoine Lacassagne.

Keywords: 3D conformational radiotherapy, intensity modulated radiotherapy, monitor unit calculation, dosimetry quality assurance

Procedia PDF Downloads 209

Authors: Antoine Lauvray, Fabien Poulhaon, Pierre Michaud, Pierre Joyot, Emmanuel Duc

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Additive Friction Stir Manufacturing (AFSM) is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. Unlike in Friction Stir Welding (FSW) where abundant literature exists and addresses many aspects going from process implementation to characterization and modeling, there are still few research works focusing on AFSM. Therefore, there is still a lack of understanding of the physical phenomena taking place during the process. This research work aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system composed of the tool, the filler material, and the substrate and due to pure friction. Analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes, through numerical modeling followed by experimental validation, to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque, and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, friction, process

Procedia PDF Downloads 141

Authors: Ayla Roberta Galaco, Juliana Fonseca De Lima, Osvaldo Antonio Serra

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Coordination polymers, also known as metal-organic frameworks (MOFs) or lanthanoide organic frameworks (LOFs) have been reported due of their promising applications in gas storage, separation, catalysis, luminescence, magnetism, drug delivery, and so on. As a type of organic–inorganic hybrid materials, the properties of coordination polymers could be chosen by deliberately selecting the organic and inorganic components. LOFs have received considerable attention because of their properties such as porosity, luminescence, and magnetism. Methods such as solvothermal synthesis are important as a strategy to control the structural and morphological properties as well as the composition of the target compounds. In this work the first solvothermal synthesis was employed to obtain the compound [Y0.4,Yb0.4,Er0.2(dmf)(for)(H2O)(tft)], by using terephthalic acid (tft) and oxalic acid, decomposed in formate (for), as ligands; Yttrium, Ytterbium and, Erbium as metal centers, in DMF and water for 4 days under 160 °C. The semi-rigid terephthalic acid (dicarboxylic) coordinates with Ln3+ ions and also is possible to form a polyfunctional bridge. On the other hand, oxalate anion has no high-energy vibrational groups, which benefits the excitation of Yb3+ in upconversion process. It was observed that the compounds with water molecules in the coordination sphere of the lanthanoide ions cause lower crystalline properties and change the structure of the LOF (1D, 2D, 3D). In the FTIR, the bands at 1589 and 1500 cm-1 correspond to the asymmetric stretching vibration of –COO. The band at 1383 cm-1 is assigned to the symmetric stretching vibration of –COO. Single crystal X-ray diffraction study reveals an infinite 3D coordination framework that crystalizes in space group P21/c. The other three products, [TR(chel)(ofd)0,5(H2O)2], where TR= Eu3+, Y3, and Yb3+/Er3+ were obtained by using 1, 2-phenylenedioxydiacetic acid (ofd) and chelidonic acid (chel) as organic ligands. Thermal analysis shows that the lanthanoide organic frameworks do not collapse at temperatures below 250 °C. By the polycrystalline X-ray diffraction patterns (PXRD) it was observed that the compounds with Eu3+, Y3+, and Yb3+/Er3+ ions are isostructural. From PXRD patterns, high crystallinity can be noticed for the complexes. The final products were characterized by single X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), energy dispersive spectroscopy (EDS) and thermogravimetric analysis (TGA). The X-ray diffraction (XRD) is an effective method to investigate crystalline properties of synthesized materials. The solid crystal obtained in the synthesis show peaks at 2θ < 10°, indicating the MOF formation. The chemical composition of LOFs was also confirmed by EDS.

Keywords: isostructural, lanthanoids, lanthanoids organic frameworks (LOFs), metal organic frameworks (MOFs), thermogravimetry, X-Ray diffraction

Procedia PDF Downloads 251

Authors: Dyah Purwaningsih, Roto Roto, Hari Sutrisno

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Manganese dioxide (MnO₂) and its derivatives are among the most widely used materials for the positive electrode in both primary and rechargeable lithium batteries. The MnO₂ derivative compound of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) is one of the leading candidates for positive electrode materials in lithium batteries as it is abundant, low cost and environmentally friendly. Over the years, synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) has been carried out using various methods including sol-gel, gas condensation, spray pyrolysis, and ceramics. Problems with these various methods persist including high cost (so commercially inapplicable) and must be done at high temperature (environmentally unfriendly). This research aims to: (1) synthesize LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) by reflux technique; (2) develop microstructure analysis method from XRD Powder LiMₓMn₂₋ₓO₄ data with the two-stage method; (3) study the electrical conductivity of LiMₓMn₂₋ₓO₄. This research developed the synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) with reflux. The materials consisting of Mn(CH₃COOH)₂. 4H₂O and Na₂S₂O₈ were refluxed for 10 hours at 120°C to form β-MnO₂. The doping of Co, Ni and Cr were carried out using solid-state method with LiOH to form LiMₓMn₂₋ₓO₄. The instruments used included XRD, SEM-EDX, XPS, TEM, SAA, TG/DTA, FTIR, LCR meter and eight-channel battery analyzer. Microstructure analysis of LiMₓMn₂₋ₓO₄ was carried out on XRD powder data by two-stage method using FullProf program integrated into WinPlotR and Oscail Program as well as on binding energy data from XPS. The morphology of LiMₓMn₂₋ₓO₄ was studied with SEM-EDX, TEM, and SAA. The thermal stability test was performed with TG/DTA, the electrical conductivity was studied from the LCR meter data. The specific capacity of LiMₓMn₂₋ₓO₄ as lithium battery cathode was tested using an eight-channel battery analyzer. The results showed that the synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) was successfully carried out by reflux. The optimal temperature of calcination is 750°C. XRD characterization shows that LiMn₂O₄ has a cubic crystal structure with Fd3m space group. By using the CheckCell in the WinPlotr, the increase of Li/Mn mole ratio does not result in changes in the LiMn₂O₄ crystal structure. The doping of Co, Ni and Cr on LiMₓMn₂₋ₓO₄ (x = 0.02; 0.04; 0; 0.6; 0.08; 0.10) does not change the cubic crystal structure of Fd3m. All the formed crystals are polycrystals with the size of 100-450 nm. Characterization of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) microstructure by two-stage method shows the shrinkage of lattice parameter and cell volume. Based on its range of capacitance, the conductivity obtained at LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) is an ionic conductivity with varying capacitance. The specific battery capacity at a voltage of 4799.7 mV for LiMn₂O₄; Li₁.₀₈Mn₁.₉₂O₄; LiCo₀.₁Mn₁.₉O₄; LiNi₀.₁Mn₁.₉O₄ and LiCr₀.₁Mn₁.₉O₄ are 88.62 mAh/g; 2.73 mAh/g; 89.39 mAh/g; 85.15 mAh/g; and 1.48 mAh/g respectively.

Keywords: LiMₓMn₂₋ₓO₄, solid-state, reflux, two-stage method, ionic conductivity, specific capacity

Procedia PDF Downloads 187

Authors: Jacob Schwartz, Maxim Durach, Aniruddha Mitra, Abbas Rashidi, Glen Sage, Atin Adhikari

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NIOSH (National Institute for Occupational Safety and Health) approved N95 respirators are commonly used by workers in construction sites where there is a large amount of dust being produced from sawing, grinding, blasting, welding, etc., both electrostatically charged and not. A significant portion of airborne particles in construction sites could be nanoparticles created beside coarse particles. The penetration of the particles through the masks may differ depending on the size and charge of the individual particle. In field experiments relevant to this current study, we found that nanoparticles of medium size ranges are penetrating more frequently than nanoparticles of smaller and larger sizes. For example, penetration percentages of nanoparticles of 11.5 – 27.4 nm into a sealed N95 respirator on a manikin head ranged from 0.59 to 6.59%, whereas nanoparticles of 36.5 – 86.6 nm ranged from 7.34 to 16.04%. The possible causes behind this increased penetration of mid-size nanoparticles through mask filters are not yet explored. The objective of this study is to identify causes behind this unusual behavior of mid-size nanoparticles. We have considered such physical factors as Boltzmann distribution of the particles in thermal equilibrium with the air, kinetic energy of the particles at impact on the mask, Stoke’s drag force, and electrostatic forces in the mask stopping the particles. When the particles collide with the mask, only the particles that have enough kinetic energy to overcome the energy loss due to the electrostatic forces and the Stokes’ drag in the mask can pass through the mask. To understand this process, the following assumptions were made: (1) the effect of Stoke’s drag depends on the particles’ velocity at entry into the mask; (2) the electrostatic force is proportional to the charge on the particles, which in turn is proportional to the surface area of the particles; (3) the general dependence on electrostatic charge and thickness means that for stronger electrostatic resistance in the masks and thicker the masks’ fiber layers the penetration of particles is reduced, which is a sensible conclusion. In sampling situations where one mask was soaked in alcohol eliminating electrostatic interaction the penetration was much larger in the mid-range than the same mask with electrostatic interaction. The smaller nanoparticles showed almost zero penetration most likely because of the small kinetic energy, while the larger sized nanoparticles showed almost negligible penetration most likely due to the interaction of the particle with its own drag force. If there is no electrostatic force the fraction for larger particles grows. But if the electrostatic force is added the fraction for larger particles goes down, so diminished penetration for larger particles should be due to increased electrostatic repulsion, may be due to increased surface area and therefore larger charge on average. We have also explored the effect of ambient temperature on nanoparticle penetrations and determined that the dependence of the penetration of particles on the temperature is weak in the range of temperatures in the measurements 37-42°C, since the factor changes in the range from 3.17 10-3K-1 to 3.22 10-3K-1.

Keywords: respiratory protection, industrial hygiene, aerosol, electrostatic force

Procedia PDF Downloads 189

Authors: Nkwachukwu Chukwuchekwa, Joy Ulumma Chukwuchekwa

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Magnetic characteristics of grain-oriented electrical steel (GOES) are usually measured at high flux densities suitable for its typical applications in power transformers. There are limited magnetic data at low flux densities which are relevant for the characterization of GOES for applications in metering instrument transformers and low frequency magnetic shielding in magnetic resonance imaging medical scanners. Magnetic properties such as coercivity, B-H loop, AC relative permeability and specific power loss of conventional grain oriented (CGO) and high permeability grain oriented (HGO) electrical steels were measured and compared at high and low flux densities at power magnetising frequency. 40 strips comprising 20 CGO and 20 HGO, 305 mm x 30 mm x 0.27 mm from a supplier were tested. The HGO and CGO strips had average grain sizes of 9 mm and 4 mm respectively. Each strip was singly magnetised under sinusoidal peak flux density from 8.0 mT to 1.5 T at a magnetising frequency of 50 Hz. The novel single sheet tester comprises a personal computer in which LabVIEW version 8.5 from National Instruments (NI) was installed, a NI 4461 data acquisition (DAQ) card, an impedance matching transformer, to match the 600  minimum load impedance of the DAQ card with the 5 to 20  low impedance of the magnetising circuit, and a 4.7 Ω shunt resistor. A double vertical yoke made of GOES which is 290 mm long and 32 mm wide is used. A 500-turn secondary winding, about 80 mm in length, was wound around a plastic former, 270 mm x 40 mm, housing the sample, while a 100-turn primary winding, covering the entire length of the plastic former was wound over the secondary winding. A standard Epstein strip to be tested is placed between the yokes. The magnetising voltage was generated by the LabVIEW program through a voltage output from the DAQ card. The voltage drop across the shunt resistor and the secondary voltage were acquired by the card for calculation of magnetic field strength and flux density respectively. A feedback control system implemented in LabVIEW was used to control the flux density and to make the induced secondary voltage waveforms sinusoidal to have repeatable and comparable measurements. The low noise NI4461 card with 24 bit resolution and a sampling rate of 204.8 KHz and 92 KHz bandwidth were chosen to take the measurements to minimize the influence of thermal noise. In order to reduce environmental noise, the yokes, sample and search coil carrier were placed in a noise shielding chamber. HGO was found to have better magnetic properties at both high and low magnetisation regimes. This is because of the higher grain size of HGO and higher grain-grain misorientation of CGO. HGO is better CGO in both low and high magnetic field applications.

Keywords: flux density, electrical steel, LabVIEW, magnetization

Procedia PDF Downloads 288

Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

Procedia PDF Downloads 120

Authors: Mahshid Arabi

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In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

Procedia PDF Downloads 36

Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

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As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

Procedia PDF Downloads 151

Authors: S. R. Dehghani, Y. S. Muzychka, G. F. Naterer

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The ice accretion of salt water on cold substrates creates brine-spongy ice. This type of ice is a mixture of pure ice and liquid brine. A real case of creation of this type of ice is superstructure icing which occurs on marine vessels and offshore structures in cold and harsh conditions. Transient heat transfer through this medium causes phase changes between brine pockets and pure ice. Salt rejection during the process of transient heat conduction increases the salinity of brine pockets to reach a local equilibrium state. In this process the only effect of passing heat through the medium is not changing the sensible heat of the ice and brine pockets; latent heat plays an important role and affects the mechanism of heat transfer. In this study, a new analytical model for evaluating heat transfer through brine-spongy ice is suggested. This model considers heat transfer and partial solidification and melting together. Properties of brine-spongy ice are obtained using properties of liquid brine and pure ice. A numerical solution using Method of Lines discretizes the medium to reach a set of ordinary differential equations. Boundary conditions are chosen using one of the applicable cases of this type of ice; one side is considered as a thermally isolated surface, and the other side is assumed to be suddenly affected by a constant temperature boundary. All cases are evaluated in temperatures between -20 C and the freezing point of brine-spongy ice. Solutions are conducted using different salinities from 5 to 60 ppt. Time steps and space intervals are chosen properly to maintain the most stable and fast solution. Variation of temperature, volume fraction of brine and brine salinity versus time are the most important outputs of this study. Results show that transient heat conduction through brine-spongy ice can create a various range of salinity of brine pockets from the initial salinity to that of 180 ppt. The rate of variation of temperature is found to be slower for high salinity cases. The maximum rate of heat transfer occurs at the start of the simulation. This rate decreases as time passes. Brine pockets are smaller at portions closer to the colder side than that of the warmer side. A the start of the solution, the numerical solution tends to increase instabilities. This is because of sharp variation of temperature at the start of the process. Changing the intervals improves the unstable situation. The analytical model using a numerical scheme is capable of predicting thermal behavior of brine spongy ice. This model and numerical solutions are important for modeling the process of freezing of salt water and ice accretion on cold structures.

Keywords: method of lines, brine-spongy ice, heat conduction, salt water

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

Procedia PDF Downloads 157

Authors: Wisdom Robert Duruji

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The outbreak of SARS-CoV-2 serotype infection was recorded in January 2020 in Wuhan City, Hubei Province, China. This study examines the concepts of the COVID-19 pandemic and the implications of vaccines for health security in Nigeria and Diasporas. It challenges the widely accepted assumption that the first case of coronavirus infection in Nigeria was recorded on February 27th, 2020, in Lagos. The study utilizes a range of research methods to achieve its objectives. These include the double-layered culture technique, literature review, website knowledge, Google search, news media information, academic journals, fieldwork, and on-site observations. These diverse methods allow for a comprehensive analysis of the concepts and the implications being studied. The study finds that coronavirus infection can be asymptomatic; it may be the antigenicity of the leukocytes (white blood cells), which produce immunogenic hapten or interferons (α, β and γ) that fight infectious parasites, was an immune response that prevented severe virulence in healthy individuals; the reason healthy patients of coronavirus infection in Nigeria naturally recovered after two to three weeks of on-set of infection and test negative. However, the fatality data from the Nigerian Centre for Disease Control (NCDC) is incorrect in this study’s finding; it perused that the fatalities were primarily due to underlying ailments, hunger, and malnutrition in debilitated, comorbid, or compromised patients. This study concluded that the kits and Polymerase Chain Reaction (PCR) machine currently used by the Nigerian Centre for Disease Control (NCDC) in testing and confirming COVID-19 in Nigeria is not ideal; it is programmed and negates separating the strain to its specific serotypes amongst its genera coronavirus, and family Coronaviridae; and might have confirmed patients with the symptoms of febrile caused by cough, catarrh, typhoid and malaria parasites as Covid-19 positive. Therefore, it is recommended that the coronavirus species infected in Nigeria are opportunistic parasites that thrive in human immuno-suppressed conditions like the herpesvirus; it cannot be eradicated by vaccines; the only virucides are interferons, immunoglobulins, and probably synthetic antiviral guanosine drugs like copegus or ribavirin. The findings emphasized that COVID-19 is not the primary pandemic disease in Nigeria; the lockdown was a mirage and not necessary; but rather, pandemic diseases in Nigeria are corruption, nepotism, hunger, and malnutrition caused by ineptitude in governance, religious dichotomy, and ethnic conflicts.

Keywords: coronavirus, corruption, Covid-19 pandemic, lock-down, Nigeria, vaccine

Procedia PDF Downloads 58

Authors: Md. Rafiul Biswas, Uzair Shah, Mohammad Alkayal, Zubair Shah, Othman Althawadi, Kamila Swart

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Background: Social media platforms play a significant role in the mediated consumption of sport, especially so for sport mega-event. The characteristics of Twitter data (e.g., user mentions, retweets, likes, #hashtag) accumulate the users in one ground and spread information widely and quickly. Analysis of Twitter data can reflect the public attitudes, behavior, and sentiment toward a specific event on a larger scale than traditional surveys. Qatar is going to be the first Arab country to host the mega sports event FIFA World Cup 2022 (Q22). Qatar has hosted the FIFA Arab Cup 2021 (FAC21) to serve as a preparation for the mega-event. Objectives: This study investigates public sentiments and experiences about FAC21 and provides an insight to enhance the public experiences for the upcoming Q22. Method: FCA21-related tweets were downloaded using Twitter Academic research API between 01 October 2021 to 18 February 2022. Tweets were divided into three different periods: before T1 (01 Oct 2021 to 29 Nov 2021), during T2 (30 Nov 2021 -18 Dec 2021), and after the FAC21 T3 (19 Dec 2021-18 Feb 2022). The collected tweets were preprocessed in several steps to prepare for analysis; (1) removed duplicate and retweets, (2) removed emojis, punctuation, and stop words (3) normalized tweets using word lemmatization. Then, rule-based classification was applied to remove irrelevant tweets. Next, the twitter-XLM-roBERTa-base model from Huggingface was applied to identify the sentiment in the tweets. Further, state-of-the-art BertTopic modeling will be applied to identify trending topics over different periods. Results: We downloaded 8,669,875 Tweets posted by 2728220 unique users in different languages. Of those, 819,813 unique English tweets were selected in this study. After splitting into three periods, 541630, 138876, and 139307 were from T1, T2, and T3, respectively. Most of the sentiments were neutral, around 60% in different periods. However, the rate of negative sentiment (23%) was high compared to positive sentiment (18%). The analysis indicates negative concerns about FAC21. Therefore, we will apply BerTopic to identify public concerns. This study will permit the investigation of people’s expectations before FAC21 (e.g., stadium, transportation, accommodation, visa, tickets, travel, and other facilities) and ascertain whether these were met. Moreover, it will highlight public expectations and concerns. The findings of this study can assist the event organizers in enhancing implementation plans for Q22. Furthermore, this study can support policymakers with aligning strategies and plans to leverage outstanding outcomes.

Keywords: FIFA Arab Cup, FIFA, Twitter, machine learning

Procedia PDF Downloads 89

Authors: Jaroslaw Gawryluk, Andrzej Teter

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Simply supported angle columns subjected to uniform shortening are tested. The experimental studies are conducted on a testing machine using additional Aramis and the acoustic emission system. The laminate samples are subjected to axial uniform shortening. The tested columns are loaded with the force values from zero to the maximal load destroying the L-shaped column, which allowed one to observe the column post-buckling behavior until its collapse. Laboratory tests are performed at a constant velocity of the cross-bar equal to 1 mm/min. In order to eliminate stress concentrations between sample and support, flexible pads are used. Analyzed samples are made with carbon-epoxy laminate using the autoclave method. The configurations of laminate layers are: [60,0₂,-60₂,60₃,-60₂,0₃,-60₂,0,60₂]T, where direction 0 is along the length of the profile. Material parameters of laminate are: Young’s modulus along the fiber direction - 170GPa, Young’s modulus along the fiber transverse direction - 7.6GPa, shear modulus in-plane - 3.52GPa, Poisson’s ratio in-plane - 0.36. The dimensions of all columns are: length-300 mm, thickness-0.81mm, width of the flanges-40mm. Next, two numerical models of the column with and without flexible pads are developed using the finite element method in Abaqus software. The L-profile laminate column is modeled using the S8R shell elements. The layup-ply technique is used to define the sequence of the laminate layers. However, the model of grips is made of the R3D4 discrete rigid elements. The flexible pad is consists of the C3D20R type solid elements. In order to estimate the moment of the first laminate layer damage, the following initiation criteria were applied: maximum stress criterion, Tsai-Hill, Tsai-Wu, Azzi-Tsai-Hill, and Hashin criteria. The best compliance of results was observed for the Hashin criterion. It was found that the use of the pad in the numerical model significantly influences the damage mechanism. The model without pads characterized a much more stiffness, as evidenced by a greater bifurcation load and damage initiation load in all analyzed criteria, lower shortening, and less deflection of the column in its center than the model with flexible pads. Acknowledgment: The project/research was financed in the framework of the project Lublin University of Technology-Regional Excellence Initiative, funded by the Polish Ministry of Science and Higher Education (contract no. 030/RID/2018/19).

Keywords: angle column, compression, experiment, FEM

Procedia PDF Downloads 204

Authors: Mir Mohammad Badrul Hasan, Anwar Abdkader, Chokri Cherif

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With the increasing demand and use of carbon fibre reinforced composites (CFRC), disposal of the carbon fibres (CF) and end of life composite parts is gaining tremendous importance on the issue especially of sustainability. Furthermore, a number of processes (e. g. pyrolysis, solvolysis, etc.) are available currently to obtain recycled CF (rCF) from end-of-life CFRC. Since the CF waste or rCF are neither allowed to be thermally degraded nor landfilled (EU Directive 1999/31/EC), profitable recycling and re-use concepts are urgently necessary. Currently, the market for materials based on rCF mainly consists of random mats (nonwoven) made from short fibres. The strengths of composites that can be achieved from injection-molded components and from nonwovens are between 200-404 MPa and are characterized by low performance and suitable for non-structural applications such as in aircraft and vehicle interiors. On the contrary, spinning rCF to yarn constructions offers good potential for higher CFRC material properties due to high fibre orientation and compaction of rCF. However, no investigation is reported till yet on the direct comparison of the mechanical properties of thermoplastic CFRC manufactured from virgin CF filament yarn and spun yarns from staple rCF. There is a lack of understanding on the level of performance of the composites that can be achieved from hybrid yarns consisting of rCF and PA6 fibres. In this drop back, extensive research works are being carried out at the Textile Machinery and High-Performance Material Technology (ITM) on the development of new thermoplastic CFRC from hybrid yarns consisting of rCF. For this purpose, a process chain is developed at the ITM starting from fibre preparation to hybrid yarns manufacturing consisting of staple rCF by mixing with thermoplastic fibres. The objective is to apply such hybrid yarns for the manufacturing of load bearing textile reinforced thermoplastic CFRCs. In this paper, the development of innovative multi-component core-sheath hybrid yarn structures consisting of staple rCF and polyamide 6 (PA 6) on a DREF-3000 friction spinning machine is reported. Furthermore, Unidirectional (UD) CFRCs are manufactured from the developed hybrid yarns, and the mechanical properties of the composites such as tensile and flexural properties are analyzed. The results show that the UD composite manufactured from the developed hybrid yarns consisting of staple rCF possesses approximately 80% of the tensile strength and E-module to those produced from virgin CF filament yarn. The results show a huge potential of the DREF-3000 friction spinning process to develop composites from rCF for high-performance applications.

Keywords: recycled carbon fibres, hybrid yarn, friction spinning, thermoplastic composite

Procedia PDF Downloads 251

Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

Procedia PDF Downloads 143

Authors: Franciele L. Bernard, Felipe Dalla Vecchia, Barbara B. Polesso, Jose A. Donato, Marcus Seferin, Rosane Ligabue, Jailton F. do Nascimento, Sandra Einloft

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The increasing level of carbon dioxide concentration in the atmosphere related to fossil fuels processing and utilization are contributing to global warming phenomena considerably. Carbon capture and storage (CCS) technologies appear as one of the key technologies to reduce CO2 emissions mitigating the effects of climate change. Absorption using amines solutions as solvents have been extensively studied and used in industry for decades. However, solvent degradation and equipment corrosion are two of the main problems in this process. Poly (ionic liquid) (PIL) is considered as a promising material for CCS technology, potentially more environmentally friendly and lesser energy demanding than traditional material. PILs possess a unique combination of ionic liquids (ILs) features, such as affinity for CO2, thermal and chemical stability and adjustable properties, coupled with the intrinsic properties of the polymer. This study investigated new Poly (ionic liquid) (PIL) based on polyurethanes with different ionic liquids cations and its potential for CO2 capture. The PILs were synthesized by the addition of diisocyante to a difunctional polyol, followed by an exchange reaction with the ionic Liquids 1-butyl-3-methylimidazolium chloride (BMIM Cl); tetrabutylammonium bromide (TBAB) and tetrabutylphosphonium bromide (TBPB). These materials were characterized by Fourier transform infrared spectroscopy (FTIR), Proton Nuclear Magnetic Resonance (1H-NMR), Atomic force microscopy (AFM), Tensile strength analysis, Field emission scanning electron microscopy (FESEM), Thermogravimetric analysis (TGA), Differential scanning calorimetry (DSC). The PILs CO2 sorption capacity were gravimetrically assessed in a Magnetic Suspension Balance (MSB). It was found that the ionic liquids cation influences in the compounds properties as well as in the CO2 sorption. The best result for CO2 sorption (123 mgCO2/g at 30 bar) was obtained for the PIL (PUPT-TBA). The higher CO2 sorption in PUPT-TBA is probably linked to the fact that the tetraalkylammonium cation having a higher positive density charge can have a stronger interaction with CO2, while the imidazolium charge is delocalized. The comparative CO2 sorption values of the PUPT-TBA with different ionic liquids showed that this material has greater capacity for capturing CO2 when compared to the ILs even at higher temperature. This behavior highlights the importance of this study, as the poly (urethane) based PILs are cheap and versatile materials.

Keywords: capture, CO2, ionic liquids, ionic poly(urethane)

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Authors: Henda Gnakate Biba, Ndassa Mouafon Issa

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Dictionaries modeled on the Western model [tonic accent languages] are not suitable and do not account for tonal languages phonologically, which is why the [prosodic and phonological] ethnographic dictionary was designed. It is a glossary that expresses the tones and the rhythm of words. It recreates exactly the speaking or singing of a tonal language, and allows the non-speaker of this language to pronounce the words as if they were a native. It is a dictionary adapted to tonal languages. It was built from ethnomusicological theorems and phonological processes, according to Jean. J. Rousseau 1776 hypothesis /To say and to sing were once the same thing/. Each word in the French dictionary finds its corresponding language, ekaη. And each word ekaη is written on a musical staff. This ethnographic dictionary is also an inventive, original and innovative research thesis, but it is also an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and, world music or, variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, language, entenglement, science, research

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Authors: James Rigor Camacho, Wansu Lim

Abstract:

Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Dinesh Munjurulimana, Anil Tiwari, Tingwen Li, Carlos Pereira, Sreekanth Pannala, John Waters

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With the rapid transition to electric vehicles (EVs) across the globe, car manufacturers are in need of integrated and lightweight solutions for the battery packs of these vehicles. An integral part of a battery pack is the battery tray, which constitutes a significant portion of the pack’s overall weight. Based on the functional requirements, cost targets, and packaging space available, a range of materials –from metals, composites, and plastics– are often used to develop these battery trays. This paper considers the design and development of integrated thermoplastic-intensive battery trays, using the available packaging space from a representative EV battery pack. Presented as a proposed alternative are multiple concepts to integrate several connected systems such as cooling plates and underbody impact protection parts of a multi-piece incumbent battery pack. The resulting digital prototype was evaluated for several mechanical performance measures such as mechanical shock, drop, crush resistance, modal analysis, and torsional stiffness. The performance of this alternative design is then compared with the incumbent solution. In addition, insights are gleaned into how these novel approaches can be optimized to meet or exceed the performance of incumbent designs. Preliminary manufacturing feasibility of the optimal solution using injection molding and other commonly used manufacturing methods for thermoplastics is briefly explained. Then numerical and analytical evaluations are performed to show a representative Pareto front of cost vs. volume of the production parts. The proposed solution is observed to offer weight savings of up to 40% on a component level and part elimination of up to two systems in the battery pack of a typical battery EV while offering the potential to meet the required performance measures highlighted above. These conceptual solutions are also observed to potentially offer secondary benefits such as improved thermal and electrical isolations and be able to achieve complex geometrical features, thus demonstrating the ability to use the complete packaging space available in the vehicle platform considered. The detailed study presented in this paper serves as a valuable reference for researches across the globe working on the development of EV battery packs – especially those with an interest in the potential of employing alternate solutions as part of a mixed-material system to help capture untapped opportunities to optimize performance and meet critical application requirements.

Keywords: thermoplastics, lightweighting, part integration, electric vehicle battery packs

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Authors: Jiro Takagi

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Approximately 90 percent of the casualties in the near-fault-type Kobe earthquake in 1995 resulted from the collapse of wooden houses, although a limited number of collapses of this type of building were reported in the more recent off-shore-type Tohoku Earthquake in 2011 (excluding direct damage by the Tsunami). Kumamoto earthquake in 2016 also revealed the vulnerability of old wooden houses in Japan. There are approximately 24.5 million wooden houses in Japan and roughly 40 percent of them are considered to have the inadequate seismic-resisting capacity. Therefore, seismic strengthening of these wooden houses is an urgent task. However, it has not been quickly done for various reasons, including cost and inconvenience during the reinforcing work. Residents typically spend their money on improvements that more directly affect their daily housing environment (such as interior renovation, equipment renewal, and placement of thermal insulation) rather than on strengthening against extremely rare events such as large earthquakes. Considering this tendency of residents, a new approach to developing a seismic strengthening method for wooden houses is needed. The seismic reinforcement method developed in this research uses folded galvanized thin steel plates as both shear walls and the new exterior architectural finish. The existing finish is not removed. Because galvanized steel plates are aesthetic and durable, they are commonly used in modern Japanese buildings on roofs and walls. Residents could feel a physical change through the reinforcement, covering existing exterior walls with steel plates. Also, this exterior reinforcement can be installed with only outdoor work, thereby reducing inconvenience for residents since they would not be required to move out temporarily during construction. The Durability of the exterior is enhanced, and the reinforcing work can be done efficiently since perfect water protection is not required for the new finish. In this method, the entire exterior surface would function as shear walls and thus the pull-out force induced by seismic lateral load would be significantly reduced as compared with a typical reinforcement scheme of adding braces in selected frames. Consequently, reinforcing details of anchors to the foundations would be less difficult. In order to attach the exterior galvanized thin steel plates to the houses, new wooden beams are placed next to the existing beams. In this research, steel connections between the existing and new beams are developed, which contain a gap for the existing finish between the two beams. The thin steel plates are screwed to the new beams and the connecting vertical members. The seismic-resisting performance of the shear walls with thin steel plates is experimentally verified both for the frames and connections. It is confirmed that the performance is high enough for bracing general wooden houses.

Keywords: experiment, seismic reinforcement, thin steel plates, wooden houses

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Authors: Armin Solemanifar, Arthur Wilkinson, Kinjalkumar Patel

Abstract:

Carbon fibre (CF) - polymer laminate composites have very low densities (approximately 40% lower than aluminium), high strength and high stiffness but in terms of toughness properties they often require modifications. For example, adding rubbers or thermoplastics toughening agents are common ways of improving the interlaminar fracture toughness of initially brittle thermoset composite matrices. The main aim of this project was to toughen CF-epoxy resin laminate composites using hybrid CF-fabrics incorporating Innegra™ a commercial highly-oriented polypropylene (PP) fibre, in which more than 90% of its crystal orientation is parallel to the fibre axis. In this study, the damage tolerance of hybrid (carbon-Innegra, CI) composites was investigated. Laminate composites were produced by resin-infusion using: pure CF fabric; fabrics with different ratios of commingled CI, and two different types of pure Innegra fabrics (Innegra 1 and Innegra 2). Dynamic mechanical thermal analysis (DMTA) was used to measure the glass transition temperature (Tg) of the composite matrix and values of flexural storage modulus versus temperature. Mechanical testing included drop-weight impact, compression-after-impact (CAI), and interlaminar (short-beam) shear strength (ILSS). Ultrasonic C-Scan imaging was used to determine the impact damage area and scanning electron microscopy (SEM) to observe the fracture mechanisms that occur during failure of the composites. For all composites, 8 layers of fabrics were used with a quasi-isotropic sequence of [-45°, 0°, +45°, 90°]s. DMTA showed the Tg of all composites to be approximately same (123 ±3°C) and that flexural storage modulus (before the onset of Tg) was the highest for the pure CF composite while the lowest were for the Innegra 1 and 2 composites. Short-beam shear strength of the commingled composites was higher than other composites, while for Innegra 1 and 2 composites only inelastic deformation failure was observed during the short-beam test. During impact, the Innegra 1 composite withstood up to 40 J without any perforation while for the CF perforation occurred at 10 J. The rate of reduction in compression strength upon increasing the impact energy was lowest for the Innegra 1 and 2 composites, while CF showed the highest rate. On the other hand, the compressive strength of the CF composite was highest of all the composites at all impacted energy levels. The predominant failure modes for Innegra composites observed in cross-sections of fractured specimens were fibre pull-out, micro-buckling, and fibre plastic deformation; while fibre breakage and matrix delamination were a major failure observed in the commingled composites due to the more brittle behaviour of CF. Thus, Innegra fibres toughened the CF composites but only at the expense of reducing compressive strength.

Keywords: hybrid composite, thermoplastic fibre, compression strength, damage tolerance

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