Search results for: EB thermal processing

Authors: Ahmed Al-Adaileh

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Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Salma Maher, Ahmed Elseragy, Sally Eldeeb

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Nowadays, Urbanism and climate change lead to the rapid growth in energy consumption and the increase of using air-conditioning for cooling. In a hot climate area, there is a need for a new sustainable alternative that is more convenient for an existing situation. The Building envelope controls the heat transfer between the outside and inside the building. While the building façade is the most critical part, types of façade material play a vital role in influences of the energy demand for heating and cooling due to exposure to direct solar radiation throughout the day. Since the beginning of the twentieth century, the use of curtain walls in office buildings façades started to increase rapidly, which lead to more cooling loads in energy consumption. Integrating the living wall system in urban areas as a sustainable renovation and energy-saving method for the built environment will reduce the energy demand of buildings and will also provide environmental benefits. Also, it will balance the urban ecology and enhance urban life quality. The results show that the living wall systems reduce the internal temperature up to 4.0 °C. This research carries on an analytical study by highlighting the different types of living wall systems and verifying their thermal performance, energy-saving, and life potential on the building. These assessing criteria include the reason for using the Living wall systems in the building façade as well as the effect it has upon the surrounding environment. Finally, the paper ends with concluding the effect of using living wall systems on building. And, it suggests a system as long-lasting, and energy-efficient solution to be applied in curtain wall façades in a hot climate area.

Keywords: living wall systems, energy consumption, curtain walls, energy-saving, sustainability, urban life quality

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Authors: А. I. Dovgyalo, S. O. Nekrasova, D. V. Sarmin, A. A. Shimanov, D. A. Uglanov

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Usually liquefied natural gas (LNG) gasification is performed due to atmospheric heat. In order to produce a liquefied gas a sufficient amount of energy is to be consumed (about 1 kW∙h for 1 kg of LNG). This study offers a number of solutions, allowing using a cold energy of LNG. In this paper it is evaluated the application turbines installed behind the evaporator in LNG complex due to its work additional energy can be obtained and then converted into electricity. At the LNG consumption of G=1000kg/h the expansion work capacity of about 10 kW can be reached. Herewith-open Rankine cycle is realized, where a low capacity cryo-pump (about 500W) performs its normal function, providing the cycle pressure. Additionally discussed an application of Stirling engine within the LNG complex also gives a possibility to realize cold energy. Considering the fact, that efficiency coefficient of Stirling engine reaches 50 %, LNG consumption of G=1000 kg/h may result in getting a capacity of about 142 kW of such a thermal machine. The capacity of the pump, required to compensate pressure losses when LNG passes through the hydraulic channel, will make 500 W. Apart from the above-mentioned converters, it can be proposed to use thermoelectric generating packages (TGP), which are widely used now. At present, the modern thermoelectric generator line provides availability of electric capacity with coefficient of efficiency up to 15%. In the proposed complex, it is suggested to install the thermoelectric generator on the evaporator surface is such a way, that the cold end is contacted with the evaporator’s surface, and the hot one – with the atmosphere. At the LNG consumption of G=1000 kgг/h and specified coefficient of efficiency the capacity of the heat flow Qh will make about 32 kW. The derivable net electric power will be P=4,2 kW, and the number of packages will amount to about 104 pieces. The carried out calculations demonstrate the research perceptiveness in this field of propulsion plant development, as well as allow realizing the energy saving potential with the use of liquefied natural gas and other cryogenics technologies.

Keywords: cold energy, gasification, liquefied natural gas, electricity

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Authors: Bryan Christian Baybay, M. Francesca Ronario

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This study is intended to answer the question “What are the communication styles of selected Filipino gays in breaking their silence on their sexual orientation to their parents?” In this regard, six cases of Filipino gay disclosures were examined through in-depth interviews. The participants were selected through purposive sampling and snowball technique. The theories, Rhetorical Sensitivity of Roderick Hart and Communicator Style of Robert Norton were used to analyze the gathered data and to give support to the communication attitudes, message processing, message rendering and communication styles exhibited in each disclosure. As secondary data and validation, parents and experts in the field of communication, sociology, and psychology were also interviewed and consulted. The study found that Filipino gays vary in the communication styles they use during the disclosure with their parents. All communication styles: impression-leaving, contentious, open, dramatic, dominant, precise, relaxed, friendly, animated, and communicator image were observed by the gays depending on their motivation, relationship and thoughts contemplated. These results lend ideas for future researchers to look into the communication patterns and/or styles of lesbians, bisexuals, transgenders and queers or expand researches on the same subject and the utilization of Social Judgment and Relational Dialectics theories in determining and analyzing LGBTQ communication.

Keywords: communication attitudes, communication styles, Filipino gays, self-disclosure, sexual orientation

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Authors: Ziqu Ouyang, Kun Su

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A novel efficient and clean coal combustion system, namely the purification-combustion system, was designed by the Institute of Engineering Thermal Physics, Chinese Academy of Science, in 2022. Among them, the purification system was composed of a mesothermal activating unit and a hyperthermal reductive unit, and the combustion system was composed of a mild combustion system. In the purification-combustion system, the deep in-situ removal of coal-N could be realized by matching the temperature and atmosphere in each unit, and thus the NOx emission was controlled effectively. To acquire the methods for realizing the efficient and clean coal combustion, this study investigated the effect of the activating temperature (including 822 °C, 858 °C, 933 °C, 991 °C), which was the key factor affecting the system operation, on combustion and NOx emission characteristics of pulverized coal in a 30 kW purification-combustion test bench. The research result turned out that the activating temperature affected the combustion and NOx emission characteristics significantly. As the activating temperature increased, the temperature increased first and then decreased in the mild combustion unit, and the temperature change in the lower part was much higher than that in the upper part. Moreover, the main combustion region was always located at the top of the unit under different activating temperatures, and the combustion intensity along the unit was weakened gradually. Increasing the activating temperature excessively could destroy the reductive atmosphere early in the upper part of the unit, which wasn’t conducive to the full removal of coal-N in the reductive coal char. As the activating temperature increased, the combustion efficiency increased first and then decreased, while the NOx emission decreased first and then increased, illustrating that increasing the activating temperature properly promoted the efficient and clean coal combustion, but there was a limit to its growth. In this study, the optimal activating temperature was 858 °C. Hence, this research illustrated that increasing the activating temperature properly could realize the mutual matching of improving the combustion efficiency and reducing the NOx emission, and thus guaranteed the clean and efficient coal combustion well.

Keywords: activating temperature, combustion characteristics, nox emission, purification-combustion system

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Authors: Vishnu V. Pillai, Sunil P. Lonkar, Akhil M. Abraham, Saeed M. Alhassan

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An effectual technology for wastewater treatment is a great demand now in order to encounter the water pollution caused by organic pollutants. Photocatalytic oxidation technology is widely used in removal of such unsafe contaminants. Among the semi-conducting metal oxides, robust and thermally stable TiO2 has emerged as a fascinating material for photocatalysis. Enhanced catalytic activity was observed for nanostructured TiO2 due to its higher surface, chemical stability and higher oxidation ability. However, higher charge carrier recombination and wide band gap of TiO2 limits its use as a photocatalyst in the UV region. It is desirable to develop a photocatalyst that can efficiently absorb the visible light, which occupies the main part of the solar spectrum. Hence, in order to extend its photocatalytic efficiency under visible light, TiO2 nanoparticles are often doped with metallic or non-metallic elements. Non-metallic doping of TiO2 has attracted much attention due to the low thermal stability and enhanced recombination of charge carriers endowed by metallic doping of TiO2. Amongst, sulfur doped TiO2 is most widely used photocatalyst in environmental purification. However, the most of S-TiO2 synthesis technique uses toxic chemicals and complex procedures. Hence, a facile, scalable and environmentally benign preparation process for S-TiO2 is highly desirable. In present work, we have demonstrated new and facile solid-state reaction method for S-TiO2 synthesis that uses abundant elemental sulfur as S source and moderate temperatures. The resulting nano-sized S-TiO2 has been successfully employed as visible light photocatalyst in methylene blue dye removal from aqueous media.

Keywords: ecofriendly, nanomaterials, methylene blue, photocatalysts

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Authors: M. Crozet, D. Roudil, T. Branger, S. Boden, P. Peerani, B. Russell, M. Herranz, L. Aldave de la Heras

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The EURATOM work program project INSIDER (Improved Nuclear Site Characterization for Waste minimization in Decommissioning under Constrained Environment) was launched in June 2017. This 4-year project has 18 partners and aims at improving the management of contaminated materials arising from decommissioning and dismantling (D&D) operations by proposing an integrated methodology of characterization. This methodology is based on advanced statistical processing and modelling, coupled with adapted and innovative analytical and measurement methods, with respect to sustainability and economic objectives. In order to achieve these objectives, the approaches will be then applied to common case studies in the form of Inter-laboratory comparisons on matrix representative reference samples and benchmarking. Work Package 6 (WP6) ‘Performance analysis and overall uncertainty’ is in charge of the analysis of the benchmarking on real samples, the organisation of inter-laboratory comparison on synthetic certified reference materials and the establishment of overall uncertainty budget. Assessment of the outcome will be used for providing recommendations and guidance resulting in pre-standardization tests.

Keywords: decommissioning, sampling strategy, research and development, characterization, European project

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Authors: Layan Kateb, Jawaher Ragban, Rawia Alamri, Rewaa Alhazmi

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This paper evaluates user satisfaction with the AI functionality of Coconote, an innovative app designed to transform raw input -documents, voice recordings, and video recordings- into structured study materials such as flashcards, study guides, and transcripts. Leveraging AI-driven natural language processing and summarization algorithms, Coconote aims to streamline the study process by providing personalized, accessible, and accurate learning tools. To measure user satisfaction, we conducted a survey among 20 participants, including students, educators, and professionals, who tested the app’s core features over a two-week period. The survey assessed criteria such as ease of use, accuracy of generated materials, and perceived value in enhancing productivity. Results indicate high satisfaction levels with the app’s ability to produce coherent and concise outputs, with 83% of respondents reporting improved study efficiency. However, feedback highlighted areas for improvement, including occasional inaccuracies in transcription and customization limitations in flashcard formatting. This study demonstrates the potential of AI to transform learning methods and identifies key areas for refinement in user-centric design. Coconote represents a step forward in leveraging AI to enhance educational technology

Keywords: tools for students, artificial intelligence in education, AI study tool, ethical AI tools

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Authors: Thanusha D. Abeywickrama, Inoka C. Perera, Genji Kurisu

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Tuberculosis, considered being as the ninth leading cause of death worldwide, cause from a single infectious agent M. tuberculosis and the drug resistance nature of this bacterium is a continuing threat to the world. Therefore TB preventing treatment is expanding, where this study designed to analyze the regulatory mechanism of GntR transcriptional regulator gene Rv0792c, which lie between several genes codes for some hypothetical proteins, a monooxygenase and an oxidoreductase. The gene encoding Rv0792c was cloned into pET28a and expressed protein was purified to near homogeneity by Nickel affinity chromatography. It was previously reported that the protein binds within the intergenic region (BS region) between Rv0792c gene and monooxygenase (Rv0793). This resulted in binding of three protein molecules with the BS region suggesting tight control of monooxygenase as well as its own gene. Since monooxygenase plays a key role in metabolism, this gene may have a global regulatory role. The natural ligand for this regulator is still under investigation. In relation to the Rv0792 protein structure, a Circular Dichroism (CD) spectrum was carried out to determine its secondary structure elements. Percentage-wise, 17.4% Helix, 21.8% Antiparallel, 5.1% Parallel, 12.3% turn and 43.5% other were revealed from CD spectrum data under room temperature. Differential Scanning Calorimetry (DSC) was conducted to assess the thermal stability of Rv0792, which the melting temperature of protein is 57.2 ± 0.6 °C. The graph of heat capacity (Cp) versus temperature for the best fit was obtained for non-two-state model, which concludes the folding of Rv0792 protein occurs through stable intermediates. Peak area (∆HCal ) and Peak shape (∆HVant ) was calculated from the graph and ∆HCal / ∆HVant was close to 0.5, suggesting dimeric nature of the protein.

Keywords: CD spectrum, DSC analysis, GntR transcriptional regulator, protein structure

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Authors: Zhiguo Yang, Xiangan Yue, Minglu Shao, Yue Yang, Rongjie Yan

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It is difficult to realize deep profile control because of the small pore-throats and easy water channeling in low-permeability heterogeneous reservoir, and the traditional polymer microspheres have the contradiction between injection and plugging. In order to solve this contradiction, the controllable self-aggregating colloidal particles (CSA) containing amide groups on the surface of microspheres was prepared based on emulsion polymerization of styrene and acrylamide. The dispersed solution of CSA colloidal particles, whose particle size is much smaller than the diameter of pore-throats, was injected into the reservoir. When the microspheres migrated to the deep part of reservoir, , these CSA colloidal particles could automatically self-aggregate into large particle clusters under the action of the shielding agent and the control agent, so as to realize the plugging of the water channels. In this paper, the morphology, temperature resistance and self-aggregation properties of CSA microspheres were studied by transmission electron microscopy (TEM) and bottle test. The results showed that CSA microspheres exhibited heterogeneous core-shell structure, good dispersion, and outstanding thermal stability. The microspheres remain regular and uniform spheres at 100℃ after aging for 35 days. With the increase of the concentration of the cations, the self-aggregation time of CSA was gradually shortened, and the influence of bivalent cations was greater than that of monovalent cations. Core flooding experiments showed that CSA polymer microspheres have good injection properties, CSA particle clusters can effective plug the water channels and migrate to the deep part of the reservoir for profile control.

Keywords: heterogeneous reservoir, deep profile control, emulsion polymerization, colloidal particles, plugging characteristic

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Authors: Foo Shen Hwang, Thomas Confrey, Stephen Scully, Barry Flannery

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Thermal characterization plays an important role in battery pack design. Lithium-ion batteries have to be maintained between 15-35 °C to operate optimally. Heat is generated (Q) internally within the batteries during both the charging and discharging phases. This can be quantified using several standard methods. The most common method of calculating the batteries heat generation is through the addition of both the joule heating effects and the entropic changes across the battery. In addition, such values can be derived by identifying the open-circuit voltage (OCV), nominal voltage (V), operating current (I), battery temperature (T) and the rate of change of the open-circuit voltage in relation to temperature (dOCV/dT). This paper focuses on experimental characterization and comparative modelling of the heat generation rate (Q) across several current discharge rates (0.5C, 1C, and 1.5C) of a 18650 cell. The analysis is conducted utilizing several non-linear mathematical functions methods, including polynomial, exponential, and power models. Parameter fitting is carried out over the respective function orders; polynomial (n = 3~7), exponential (n = 2) and power function. The generated parameter fitting functions are then used as heat source functions in a 3-D computational fluid dynamics (CFD) solver under natural convection conditions. Generated temperature profiles are analyzed for errors based on experimental discharge tests, conducted at standard room temperature (25°C). Initial experimental results display low deviation between both experimental and CFD temperature plots. As such, the heat generation function formulated could be easier utilized for larger battery applications than other methods available.

Keywords: computational fluid dynamics, curve fitting, lithium-ion battery, voltage drop

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Authors: Sreejani Barua, P. P. Srivastav

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Formulation of new functional food products for diabetes patients and obsessed people is a challenge for food industries till date. Starch is a certainly happening, ecological, reasonable and profusely obtainable polysaccharide in plant material. In the present scenario, there is a great interest in modifying starch functional properties without destroying its granular structure using different modification techniques. Resistant starch (RS) contains almost zero calories and can control blood glucose level to prevent diabetes. The current study focused on modification of mung bean starch which is a good source of legumes carbohydrate for the production of functional food. Heat moisture treatment (HMT) of mung starch was conducted at moisture content of 10-30%, temperature of 80-120 °C and time of 8-24 h.The content of resistant starch after modification was significantly increased from native starches containing RS 7.6%. The design combinations of HMT had been completed through Central Composite Rotatable Design (CCRD). The effects of HMT process variables on the yield of resistant starch was studied through Rapid Surface Methodology (RSM). The highest increase of resistant starch was found up to 34.39% when treated the native starch with 30% m.c at 120 °C temperature for 24 h.The functional properties of both native and modified mung bean starches showed that there was a reduction in the swelling power and swelling volume of HMT starches. However, the solubility of the HMT starches was higher than that of untreated native starch and also observed change in structural (scanning electron microscopy), X-Ray diffraction (XRD) pattern, blue value and thermal (differential scanning calorimetry) properties. Therefore, replacing native mung bean starch with heat-moisture treated mung bean starch leads to the development of new products with higher resistant starch levels and functional properties.

Keywords: Mung bean starch, heat moisture treatment, functional properties, resistant starch

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Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

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Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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Authors: Alaa Al Hawari, Mohammad Khader, Wael El Hasan, Mahmoud Alijla, Ammar Manawi, Abdelbaki Benamour

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The production of aluminium alloys and ingots -starting from the processing of alumina to aluminium, and the final cast product- was studied using a Life Cycle Assessment (LCA) approach. The studied aluminium supply chain consisted of a carbon plant, a reduction plant, a casting plant, and a power plant. In the LCA model, the environmental loads of the different plants for the production of 1 ton of aluminium metal were investigated. The impact of the aluminium production was assessed in eight impact categories. The results showed that for all of the impact categories the power plant had the highest impact only in the cases of Human Toxicity Potential (HTP) the reduction plant had the highest impact and in the Marine Aquatic Eco-Toxicity Potential (MAETP) the carbon plant had the highest impact. Furthermore, the impact of the carbon plant and the reduction plant combined was almost the same as the impact of the power plant in the case of the Acidification Potential (AP). The carbon plant had a positive impact on the environment when it comes to the Eutrophication Potential (EP) due to the production of clean water in the process. The natural gas based power plant used in the case study had 8.4 times less negative impact on the environment when compared to the heavy fuel based power plant and 10.7 times less negative impact when compared to the hard coal based power plant.

Keywords: life cycle assessment, aluminium production, supply chain, ecological impacts

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Authors: Abbasali Abouei Mehrizi, Hao Wang

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The thin film region is so important in heat transfer process due to its low thermal resistance. On the other hand, the dynamic contact angle is crucial boundary condition in numerical simulations. While different modeling contains different assumption of the microscopic contact angle, none of them has experimental evidence for their assumption, and the contact line movement mechanism still remains vague. The experimental investigation in complete wetting is more popular than partial wetting, especially in nanoscale resolution when there is sharp variation in thin film profile in partial wetting. In the present study, an experimental investigation of water film morphology near the triple phase contact line during the condensation is performed. The state-of-the-art tapping-mode atomic force microscopy (TM-AFM) was used to get the high-resolution film profile goes down to 2 nm from the contact line. The droplet was put in saturated chamber. The pristine silicon wafer was used as a smooth substrate. The substrate was heated by PI film heater. So the chamber would be over saturated by droplet evaporation. By turning off the heater, water vapor gradually started condensing on the droplet and the droplet advanced. The advancing speed was less than 20 nm/s. The dominant results indicate that in contrast to nonvolatile liquid, the film profile goes down straightly to the surface till 2 nm from the substrate. However, small bending has been observed below 20 nm, occasionally. So, it can be claimed that for the low condensation rate the microscopic contact angle equals to the optically detectable macroscopic contact angle. This result can be used to simplify the heat transfer modeling in partial wetting. The experimental result of the equality of microscopic and macroscopic contact angle can be used as a solid evidence for using this boundary condition in numerical simulation.

Keywords: advancing, condensation, microscopic contact angle, partial wetting

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Authors: Xavier Lorang, Ahmadali Tahmasebimoradi, Chetra Mang, Sylvain Girard

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The additive manufacturing processes (e.g. selective laser melting) allow us to produce lattice structures which have less weight, higher impact absorption capacity, and better thermal exchange property compared to the classical structures. Unfortunately, geometric imperfections (defects) in the lattice structures are by-products results of the manufacturing process. These imperfections decrease the lifetime and the strength of the lattice structures and alternate their mechanical responses. The objective of the paper is to present a simulation strategy which allows us to take into account the effect of the geometric imperfections on the mechanical response of the lattice structure. In the first part, an identification method of geometric imperfection parameters of the lattice structure based on point clouds is presented. These point clouds are based on tomography measurements. The point clouds are fed into the platform LATANA (LATtice ANAlysis) developed by IRT-SystemX to characterize the geometric imperfections. This is done by projecting the point clouds of each microbeam along the beam axis onto a 2D surface. Then, by fitting an ellipse to the 2D projections of the points, the geometric imperfections are characterized by introducing three parameters of an ellipse; semi-major/minor axes and angle of rotation. With regard to the calculated parameters of the microbeam geometric imperfections, a statistical analysis is carried out to determine a probability density law based on a statistical hypothesis. The microbeam samples are randomly drawn from the density law and are used to generate lattice structures. In the second part, a finite element model for the lattice structure with the simplified geometric imperfections (ellipse parameters) is presented. This numerical model is used to simulate the generated lattice structures. The propagation of the uncertainties of geometric imperfections is shown through the distribution of the computed mechanical responses of the lattice structures.

Keywords: additive manufacturing, finite element model, geometric imperfections, lattice structures, propagation of uncertainty

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Authors: D. Miroud, H. Mokaddem, M. Tata, N. Foucha

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The body of PDC (polycrystalline diamond compact) drill bit can be manufactured from two different materials, steel and tungsten carbide matrix. Commonly the steel body is produced by machining, thermal spraying a bonding layer and hardfacing of Ni-based matrix reinforced with fused eutectic tungsten carbide (WC/W2C). The matrix body bit is manufactured by infiltrating tungsten carbide particles, with a Copper binary or ternary alloy. By erosion-corrosion mechanisms, the PDC drill bits matrix undergoes severe damage, occurring particularly around the PDC inserts and near injection nozzles. In this study, we investigated the possibility to repair the damaged matrix regions by hardfacing technic. Ni-based hardfacing alloy reinforced with fused eutectic tungsten carbide is deposited on infiltrated WC-W-Ni substrate by oxyacetylene welding (OAW). The microstructure at the hardfacing / matrix interface is characterized by SEM- EDS, XRD and micro hardness Hv0.1. The hardfacing conditions greatly affect the dilution phenomenon and the distribution of carbides at the interface, without formation of transition zone. During OAW welding deposition, interdiffusion of atoms occurs: Cu and Sn diffuse from infiltrated matrix substrate into hardfacing and simultaneously Cr and Si alloy elements from hardfacing diffuse towards the substrate. The dilution zone consists of a nickel-rich phase with a heterogeneous distribution of eutectic spherical (Ni-based hardfacing alloy) and irregular (matrix) WC/W2C carbides and a secondary phase rich in Cr-W-Si. Hardfacing conditions cause the dissolution of banding around both spherical and irregular carbides. The micro-hardness of interface is significantly improved by the presence of secondary phase in the inter-dendritic structure.

Keywords: dilution, dissolution, hardfacing, infiltrated matrix, PDC drill bits

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Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: Girmaye Abebe, Brook Lemma

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Adsorption of phosphorus (P as PO43-) in filter cake was studied to assess the media's capability in removing phosphorous from wastewaters. The composition of the filter cake that was generated from alum manufacturing process as waste residue has high amount of silicate from the complete silicate analysis of the experiment. Series of batches adsorption experiments were carried out to evaluate parameters that influence the adsorption capacity of PO43-. The factors studied include the effect of contact time, adsorbent dose, thermal pretreatment of the adsorbent, neutralization of the adsorbent, initial PO43- concentration, pH of the solution and effect of co-existing anions. Results showed that adsorption of PO43- is fairly rapid in first 5 min and after that it increases slowly to reach the equilibrium in about 1 h. The treatment efficiency of PO43- was increased with adsorbent extent. About 90% removal efficiency was increased within 1 h at an optimum adsorbent dose of 10 g/L for initial PO43- concentration of 10 mg/L. The amount of PO43- adsorbed increased with increasing initial PO43- concentration. Heat treatment and surface neutralization of the adsorbent did not improve the PO43- removal capacity and efficiency. The percentage of PO43- removal remains nearly constant within the pH range of 3-8. The adsorption data at ambient pH were well fitted to the Langmuir Isotherm and Dubinin–Radushkevick (D–R) isotherm model with a capacity of 25.84 and 157.55 mg/g of the adsorbent respectively. The adsorption kinetic was found to follow a pseudo-second-order rate equation with an average rate constant of 3.76 g.min−1.mg−1. The presence of bicarbonate or carbonate at higher concentrations (10–1000 mg/L) decreased the PO43- removal efficiency slightly while other anions (Cl-, SO42-, and NO3-) have no significant effect within the concentration range tested. The overall result shows that the filter cake is an efficient PO43- removing adsorbent against many parameters.

Keywords: wastewater, filter cake, adsorption capacity, phosphate (PO43-)

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Authors: Alparslan A. Balta, Hilmi Yurdakul, Orkun Tunckan, Servet Turan, Arife Yurdakul

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Si2N2O (Sinoite) is an inorganic-based oxynitride material that reveals promising phosphor candidates for white light-emitting diodes (WLEDs). However, there is now limited knowledge to explain the synthesis of Si2N2O for this purpose. Here, to the best of authors’ knowledge, we report the first time the production of Si2N2O based phosphors by CeO2, SiO2, Si3N4 from main starting powders, and Li2O sintering additive through spark plasma sintering (SPS) route. The processing parameters, e.g., pressure, temperature, and sintering time, were optimized to reach the monophase Si2N2O containing samples. The lattice parameter, crystallite size, and amount of formation phases were characterized in detail by X-ray diffraction (XRD). Grain morphology, particle size, and distribution were analyzed by scanning and transmission electron microscopes (SEM and TEM). Cathodoluminescence (CL) in SEM and photoluminescence (PL) analyses were conducted on the samples to determine the excitation, and emission characteristics of Ce3+ activated Si2N2O. Results showed that the Si2N2O phase in a maximum 90% ratio was obtained by sintering for 15 minutes at 1650oC under 30 MPa pressure. Based on the SEM-CL and PL measurements, Ce3+: Si2N2O phosphor shows a broad emission summit between 400-700 nm that corresponds to white light. The present research was supported by TUBITAK under project number 217M667.

Keywords: cerium, oxynitride, phosphors, sinoite, Si₂N₂O

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

Abstract:

Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Adriana Stefan, Cristina-Elisabeta Pelin, George Pelin, Maria Daniela Stelescu, Elena Manaila

Abstract:

Elastomeric composites have been known for a long time, but, to our knowledge, space and the aeronautic community has been directing a special attention to them only in the last decade. The required properties of advanced elastomeric materials used in space applications (such as O-rings) are sealing, abrasion, low-temperature flexibility, the long-term compression set properties, impact resistance and low-temperature thermal stability in different environments, such as ionized radiations. Basically, the elastomeric nanocomposites are composed of a rubber matrix and a wide and varied range of nanofillers, added with the aim of improving the physico-mechanical and elasticity modulus properties of the materials as well as their stability in different environments. The paper presents a partial synthesis of the research regarding the use of silicon carbide in nanometric form and/or organophylized montmorillonite as fillers in butyl rubber matrix. The need of composite materials arose from the fact that stand-alone polymers are ineffective in providing all the superior properties required by different applications. These drawbacks can be diminished or even eliminated by incorporating a new range of additives into the organic matrix, fillers that have important roles in modifying properties of various polymers. A composite material can provide superior and unique mechanical and physical properties because it combines the most desirable properties of its constituents while suppressing their least desirable properties. The commercial importance of polymers and the continuous increase of their use results in the continuous demand for improvement in their properties to meet the necessary conditions. To study the performance of the elastomeric nanocomposites were mechanically tested, it will be tested the qualities of tensile at low temperatures and RT and the behavior at the compression at cryogenic to room temperatures and under different environments. The morphology of specimens will be investigated by optical and scanning electronic microscopy.

Keywords: elastomeric nanocomposites, O-rings, space applications, mechanical properties

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

Abstract:

Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: Poonam Singh, Surendra Prasad, William Aalbersberg

Abstract:

Iron the most essential trace element in human nutrition. Its deficiency has serious health consequences and is a major public health threat worldwide. The common deficiencies in Fiji population reported are of Fe, Ca and Zn. It has also been reported that 40% of women in Fiji are iron deficient. Therefore, we have been studying the bioavailability of iron in commonly consumed Fiji foods. To study the bioavailability it is essential to assess the iron contents in raw foods. This paper reports the iron contents and its bioavailability in commonly consumed foods by multicultural population of Fiji. The food samples (rice, breads, wheat flour and breakfast cereals) were analyzed by atomic absorption spectrophotometer for total iron and its bioavailability. The white rice had the lowest total iron 0.10±0.03 mg/100g but had high bioavailability of 160.60±0.03%. The brown rice had 0.20±0.03 mg/100g total iron content but 85.00±0.03% bioavailable. The white and brown breads showed the highest iron bioavailability as 428.30±0.11 and 269.35 ±0.02%, respectively. The Weetabix and the rolled oats had the iron contents 2.89±0.27 and 1.24.±0.03 mg/100g with bioavailability of 14.19±0.04 and 12.10±0.03%, respectively. The most commonly consumed normal wheat flour had 0.65±0.00 mg/100g iron while the whole meal and the Roti flours had 2.35±0.20 and 0.62±0.17 mg/100g iron showing bioavailability of 55.38±0.05, 16.67±0.08 and 12.90±0.00%, respectively. The low bioavailability of iron in certain foods may be due to the presence of phytates/oxalates, processing/storage conditions, cooking method or interaction with other minerals present in the food samples.

Keywords: iron, bioavailability, Fiji foods, in vitro technique, human nutrition

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Authors: Abdul Salam Turkmani

Abstract:

Clay of the northern Palmyra region is one of the most important raw materials used in the Syrian ceramics industry. This study is focused on the evaluation of various laboratory analyses such as chemical analysis (XRF), mineral X-ray diffraction analysis (XRD), differential thermal analysis (DTA), and semi-industrial tests carried out on samples collected on two representative locations of the upper Oligocene in AlMkamen valley (MK) and lower Miocene in AlZukara valley (ZR) of the northern part of Palmyra, Syria. Chemical results classify the (MK) and (ZR) clays as semi-plastic red clay slightly carbonate and (eliminate probable) illite-chlorite clays with a very fine particle size distribution. Content of SiO₂ between 46.28-57.66%, Al2O3 13.81-25.2%, Fe₂O₃ 3.47-11.58%, CaO 1.15-7.19%, Na₂O+K₂O varied between 3.34-3.71%. Based on clay chemical composition and iron and carbonate content, these deposits can be considered as red firing clays. Their mineralogical composition is mainly represented by illite, kaolinite and quartz, and accessories minerals such as calcite, feldspar, phillipsite, and goethite. The results of the DTA test confirm the presence of gypsum and quartz phases in (MK) clay. Ceramic testing shows good green and dry bending strength values, which varied between 9-14 kg/cm², at 1160°C to 1180°C. Water absorption moves from 14.6 % at 1120°C to 2.2% at 1180°C to 1.6% at 1200°C. Breaking load after firing changes from 400 to 590 kg/cm². At 1200°C (MK), clay reaches perfect vitrification. After firing, the color of the clay changes from orange-hazel to red-brown at 1180°C. Technological results confirmed the suitability of the studied clays to produce floor and wall ceramic tiles. Using one of the two types of clay into the ceramic body or both types together gave satisfactory industrial results.

Keywords: ceramic, clay, industry , Palmyra

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Authors: Jin Hwa Yang, Hwang Bae, Sung Uk Ryu, Byong Guk Jeon, Sung Jae Yi, Hyun Sik Park

Abstract:

Experimental studies using a large-scale thermal-hydraulic integral test facility, System–integrated Modular Advanced Reactor Integral Test Loop (SMART-ITL), have been carried out to validate the performance of the prototype, SMART. After Fukushima accident, the passive safety systems have been dealt as important designs for retaining of nuclear safety. One of the concerned scenarios for evaluating the passive safety system is a Complete Loss of Coolant Flow (CLOF). The flowrate of coolant in the primary system is maintained by Reactor Coolant Pump (RCP). When the supply of electric power of RCP is shut off, the flowrate of coolant decreases sharply, and the temperature of the coolant increases rapidly. Therefore, the reactor trip signal is activated to prevent the over-heating of the core. In this situation, Passive Residual Heat Removal System (PRHRS) plays a significant role to assure the soundness of the SMART. The PRHRS using a two-phase natural circulation is a passive safety system in the SMART to eliminate the heat of steam generator in the secondary system with heat exchanger submarined in the Emergency Cooling Tank (ECT). As the RCPs continue to coast down, inherent natural circulation in the primary system transfers heat to the secondary system. The transferred heat is removed by PRHRS in the secondary system. In this paper, the progress of the CLOF accident is described with experimental data of transient condition performed by SMART-ITL. Finally, the capability of passive safety system and inherent natural circulation will be evaluated.

Keywords: CLOF, natural circulation, PRHRS, SMART-ITL

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Authors: Changyeop Lee, Sewon Kim, Jongho Lee

Abstract:

Reburning technology has been developed to adopt various commercial combustion systems. Fuel lean reburning is an advanced reburning method to reduce NOx economically without using burnout air, however it is not easy to get high NOx reduction efficiency. In the fuel lean reburning system, the localized fuel rich eddies are used to establish partial fuel rich regions so that the NOx can react with hydrocarbon radical restrictively. In this paper, a new advanced reburning method which supplies reburn fuel with oscillatory motion is introduced to increase NOx reduction rate effectively. To clarify whether forced oscillating injection of reburn fuel can effectively reduce NOx emission, experimental tests were conducted in vertical combustion furnace. Experiments were performed in flames stabilized by a gas burner, which was mounted at the bottom of the furnace. The natural gas is used as both main and reburn fuel and total thermal input is about 40kW. The forced oscillating injection of reburn fuel is realized by electronic solenoid valve, so that fuel rich region and fuel lean region is established alternately. In the fuel rich region, NOx is converted to N2 by reburning reaction, however unburned hydrocarbon and CO is oxidized in fuel lean zone and mixing zone at downstream where slightly fuel lean region is formed by mixing of two regions. This paper reports data on flue gas emissions and temperature distribution in the furnace for a wide range of experimental conditions. All experimental data has been measured at steady state. The NOx reduction rate increases up to 41% by forced oscillating reburn motion. The CO emissions were shown to be kept at very low level. And this paper makes clear that in order to decrease NOx concentration in the exhaust when oscillating reburn fuel injection system is adopted, the control of factors such as frequency and duty ratio is very important.

Keywords: NOx, CO, reburning, pollutant

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Authors: Thomas Wimmer, Bernhard Weigand

Abstract:

The improvement of gas turbine efficiency is one of the main drivers of research and development in the gas turbine market. This has led to elevated gas turbine inlet temperatures beyond the melting point of the utilized materials. The turbine parts need to be actively cooled in order to withstand these harsh environments. However, the usage of compressor air as coolant decreases the overall gas turbine efficiency. Thus, coolant consumption needs to be minimized in order to gain the maximum advantage from higher turbine inlet temperatures. Therefore, sophisticated cooling designs for gas turbine parts aim to minimize coolant mass flow. New design space is accessible as additive manufacturing is maturing to industrial usage for the creation of hot gas flow path parts. By making use of this technology more efficient cooling schemes can be manufacture. In order to find such cooling schemes a generative design method is being developed. It generates cooling schemes randomly which adhere to a set of rules. These assure the sanity of the design. A huge amount of different cooling schemes are generated and implemented in a simulation environment where it is validated. Criteria for the fitness of the cooling schemes are coolant mass flow, maximum temperature and temperature gradients. This way the whole design space is sampled and a Pareto optimum front can be identified. This approach is applied to a flat plate, which resembles a simplified section of a hot gas flow path part. Realistic boundary conditions are applied and thermal barrier coating is accounted for in the simulation environment. The resulting cooling schemes are presented and compared to representative conventional cooling schemes. Further development of this method can give access to cooling schemes with an even better performance having higher complexity, which makes use of the available design space.

Keywords: additive manufacturing, cooling, gas turbine, heat transfer, heat transfer design, optimization

Procedia PDF Downloads 352