Search results for: artificial air storage reservoir

Authors: Radovan Čobanović, Milica Rankov Šicar

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The fresh cheese is in the group of perishable food which cannot be kept a long period of time. The study of sustainability have been done in order to extend the shelf-life of the product which was 15 days. According to the plan of sustainability it was defined that 35 samples had to be stored for 30 days at 2°C−6°C and analyzed every 7th day from the day of reception until 30th day. Shelf life of the cheese has expired during the study of sustainability in the period between 15th and 30th day of analyses. Cheese samples were subjected to sensory analysis (appearance, odor, taste, color, aroma) and bacteriological analyzes (Listeria monocytogenes, Salmonella spp., Bacillus cereus, Staphylococcus aureus and total plate count) according to Serbian state regulation. All analyses were tested according to ISO methodology: sensory analysis ISO 6658, Listeria monocytogenes ISO 11 290-1, Salmonella spp ISO 6579, Bacillus cereus ISO 7932, Staphylococcus aureus ISO 6888-1, and total plate count ISO 4833. Analyses showed that after fifteen days of storage at a temperature defined by the manufacturers and within the product's shelf life, the cheese did not have any noticeable changes in sensory characteristics. Smell and taste are unaffected there was no separation of whey and there was not presence of strange smell or taste. As far as microbiological analyses are concerned neither one pathogen was detected and total plate count was at level of 103 cfu/g. After expiry of shelf life in a period of 15th and 30th day of storage, the analysis showed that there was a separation of whey on the surface. Along the edge of the container was present a dried part of cheese and sour-milky smell and taste were very weakly expressed. Concerning the microbiological analyses there still were not positive results for pathogen microorganisms but the total plate count was at a level of 106cfu/g. Based on the obtained results it can be concluded that this product cannot have longer shelf life than shelf life which is already defined because there are a sensory changes that would certainly have influence on decision of customers when purchase of this product is concerned.

Keywords: sustainability, fresh cheese, shelf-life, product

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Authors: Hadi Chahal, Irini Djeran-Maigre

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This paper focuses on the hydro-mechanical behavior of polychlorinated biphenyl (PCB) polluted sediments when stored in landfills and the interaction between PCBs and geosynthetic clay liners (GCL) with respect to hydraulic performance of the liner and the overall performance and stability of landfills. A European decree, adopted in the French regulation forbids the reintroducing of contaminated dredged sediments containing more than 0,64mg/kg Σ 7 PCBs to rivers. At these concentrations, sediments are considered hazardous and a remediation process must be adopted to prevent the release of PCBs into the environment. Dredging and landfilling polluted sediments is considered an eco-environmental remediation solution. French regulations authorize the storage of PCBs contaminated components with less than 50mg/kg in municipal solid waste facilities. Contaminant migration via leachate may be possible. The interactions between PCBs contaminated sediments and the GCL barrier present in the bottom of a landfill for security confinement are not known. Moreover, the hydro-mechanical behavior of stored sediments may affect the performance and the stability of the landfill. In this article, hydro-mechanical characterization of the polluted sediment is presented. This characterization led to predict the behavior of the sediment at the storage site. Chemical testing showed that the concentration of PCBs in sediment samples is between 1.7 and 2,0 mg/kg. Physical characterization showed that the sediment is organic silty sand soil (%Silt=65, %Sand=27, %OM=8) characterized by a high plasticity index (Ip=37%). Permeability tests using permeameter and filter press showed that sediment permeability is in the order of 10-9 m/s. Compressibility tests showed that the sediment is a very compressible soil with Cc=0,53 and Cα =0,0086. In addition, effects of PCB on the swelling behavior of bentonite were studied and the hydraulic performance of the GCL in interaction with PCBs was examined. Swelling tests showed that PCBs don’t affect the swelling behavior of bentonite. Permeability tests were conducted on a 1.0 m pilot scale experiment, simulating a storage facility. PCBs contaminated sediments were directly placed over a passive barrier containing GCL to study the influence of the direct contact of polluted sediment leachate with the GCL. An automatic water system has been designed to simulate precipitation. Effluent quantity and quality have been examined. The sediment settlements and the water level in the sediment have been monitored. The results showed that desiccation affected the behavior of the sediment in the pilot test and that laboratory tests alone are not sufficient to predict the behavior of the sediment in landfill facility. Furthermore, the concentration of PCB in the sediment leachate was very low ( < 0,013 µg/l) and that the permeability of the GCL was affected by other components present in the sediment leachate. Desiccation and cracks were the main parameters that affected the hydro-mechanical behavior of the sediment in the pilot test. In order to reduce these infects, the polluted sediment should be stored at a water content inferior to its shrinkage limit (w=39%). We also propose to conduct other pilot tests with the maximum concentration of PCBs allowed in municipal solid waste facility of 50 mg/kg.

Keywords: geosynthetic clay liners, landfill, polychlorinated biphenyl, polluted dredged materials

Procedia PDF Downloads 123

Authors: Matar Celine, Gaucel Sebastien, Gontard Nathalie, Guilbert Stephane, Guillard Valerie

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To increase the very short shelf life of fresh fruits and vegetable, Modified Atmosphere Packaging (MAP) allows an optimal atmosphere composition to be maintained around the product and thus prevent its decay. This technology relies on the modification of internal packaging atmosphere due to equilibrium between production/consumption of gases by the respiring product and gas permeation through the packaging material. While, to the best of our knowledge, benefit of MAP for fresh fruits and vegetable has been widely demonstrated in the literature, its effect on shelf life increase has never been quantified and formalized in a clear and simple manner leading difficult to anticipate its economic and environmental benefit, notably through the decrease of food losses. Mathematical modelling of mass transfers in the food/packaging system is the basis for a better design and dimensioning of the food packaging system. But up to now, existing models did not permit to estimate food quality nor shelf life gain reached by using MAP. However, shelf life prediction is an indispensable prerequisite for quantifying the effect of MAP on food losses reduction. The objective of this work is to propose an innovative approach to predict shelf life of MAP food product and then to link it to a reduction of food losses and wastes. In this purpose, a ‘Virtual MAP modeling tool’ was developed by coupling a new predictive deterioration model (based on visual surface prediction of deterioration encompassing colour, texture and spoilage development) with models of the literature for respiration and permeation. A major input of this modelling tool is the maximal percentage of deterioration (MAD) which was assessed from dedicated consumers’ studies. Strawberries of the variety Charlotte were selected as the model food for its high perishability, high respiration rate; 50-100 ml CO₂/h/kg produced at 20°C, allowing it to be a good representative of challenging post-harvest storage. A value of 13% was determined as a limit of acceptability for the consumers, permitting to define products’ shelf life. The ‘Virtual MAP modeling tool’ was validated in isothermal conditions (5, 10 and 20°C) and in dynamic temperature conditions mimicking commercial post-harvest storage of strawberries. RMSE values were systematically lower than 3% for respectively, O₂, CO₂ and deterioration profiles as a function of time confirming the goodness of model fitting. For the investigated temperature profile, a shelf life gain of 0.33 days was obtained in MAP compared to the conventional storage situation (no MAP condition). Shelf life gain of more than 1 day could be obtained for optimized post-harvest conditions as numerically investigated. Such shelf life gain permitted to anticipate a significant reduction of food losses at the distribution and consumer steps. This food losses' reduction as a function of shelf life gain has been quantified using a dedicated mathematical equation that has been developed for this purpose.

Keywords: food losses and wastes, modified atmosphere packaging, mathematical modeling, shelf life prediction

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Authors: Humaira Athar, Brajeshwar Singh

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Generally, the brightness of the indoor environment of buildings is entirely maintained by the artificial lighting which has consumed a large amount of resources. It is reported that lighting consumes about 19% of the total generated electricity which accounts for about 30-40% of total energy consumption. One possible way is to reduce the lighting energy by exploiting sunlight either through the use of suitable devices or energy efficient materials like translucent concrete. Translucent concrete is one such architectural concrete which allows the passage of natural light as well as artificial light through it. Several attempts have been made on different aspects of translucent concrete such as light guiding materials (glass fibers, plastic fibers, cylinder etc.), concrete mix design and manufacturing methods for use as building elements. Concerns are, however, raised on various related issues such as poor compatibility between the optical fibers and cement paste, unaesthetic appearance due to disturbance occurred in the arrangement of fibers during vibration and high shrinkage in flowable concrete due to its high water/cement ratio. Need is felt to develop translucent concrete to meet the requirement of structural safety as OPC concrete with the maximized saving in energy towards the power of illumination and thermal load in buildings. Translucent concrete was produced using pre-treated plastic optical fibers (POF, 2mm dia.) and high slump white concrete. The concrete mix was proportioned in the ratio of 1:1.9:2.1 with a w/c ratio of 0.40. The POF was varied from 0.8-9 vol.%. The mechanical properties and light transmission of this concrete were determined. Thermal conductivity of samples was measured by a transient plate source technique. Daylight illumination was measured by a lux grid method as per BIS:SP-41. It was found that the compressive strength of translucent concrete increased with decreasing optical fiber content. An increase of ~28% in the compressive strength of concrete was noticed when fiber was pre-treated. FE-SEM images showed little-debonded zone between the fibers and cement paste which was well supported with pull-out bond strength test results (~187% improvement over untreated). The light transmission of concrete was in the range of 3-7% depending on fiber spacing (5-20 mm). The average daylight illuminance (~75 lux) was nearly equivalent to the criteria specified for illumination for circulation (80 lux). The thermal conductivity of translucent concrete was reduced by 28-40% with respect to plain concrete. The thermal load calculated by heat conduction equation was ~16% more than the plain concrete. Based on Design-Builder software, the total annual illumination energy load of a room using one side translucent concrete was 162.36 kW compared with the energy load of 249.75 kW for a room without concrete. The calculated energy saving on an account of the power of illumination was ~25%. A marginal improvement towards thermal comfort was also noticed. It is concluded that the translucent concrete has the advantages of the existing concrete (load bearing) with translucency and insulation characteristics. It saves a significant amount of energy by providing natural daylight instead of artificial power consumption of illumination.

Keywords: energy saving, light transmission, microstructure, plastic optical fibers, translucent concrete

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Authors: Reza Sadeghi

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Carbon dioxide treatment is one of the new methods for storage pest control. It can be used to replace chemical approaches for postharvest. Hazelnut has a considerable share in the annual exports of Iran. In the present study, hazelnut was studied after being exposed to different CO2 pressures (0.1-0.5bar) within 24 hours. Changes in organoleptic properties (colour, firmness, aroma, crispness, and overall acceptability) during fumigation were studied. The results showed that the sensory evaluation showed that carbon dioxide had no effect on the qualitative characteristics of hazelnut.

Keywords: carbon dioxide, hazelnut, qualitative characteristics, organoleptic

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Authors: Khabat M. Ahmad

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This experiment focuses on the reduction of permeability (formation damage) as a result of fines migration by changing pH and flow rate on core plugs selected from sandstone reservoir of Pannonian basin (Upper Miocene, East Hungary). The main objective of coreflooding experiments was to investigate the influence of both high and low pH fluids and the flow rate on stability of clay minerals. The selected core samples were examined by X-ray powder diffraction (XRD) for bulk mineralogical and clay mineral composition. The shape, position, distribution and type of clay minerals within the core samples were diagnosed by scanning electron microscopy and energy dispersive spectroscopy (SEM- EDS). The basic petrophysical properties such as porosity and initial permeability were determined prior to experiments. The special core analysis (influence of pH and flow rate) on permeability reduction was examined through a series of laboratory coreflooding experiments, testing for acidic (3) and alkaline (11) solutions at different flow rates (50, 100 and 200 ml/h). Permeability in continuously reduced for pH 11 to more than 50 % of initial permeability. However, at pH 3 after a slow decrease, a significant increase is observed, to more than 40 % of initial permeability. The variation is also influenced by flow rate.

Keywords: flow rate, pH, permeability, fine migration, formation damage, XRD, SEM- EDS

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Authors: Khaled Benyounes

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Determination of the rock mechanical properties such as unconfined compressive strength UCS, Young’s modulus E, and tensile strength by the Brazilian test Rtb is considered to be the most important component in drilling and mining engineering project. Research related to establishing correlation between strength and physical parameters of rocks has always been of interest to mining and reservoir engineering. For this, many rock blocks of limestone were collected from the quarry located in Meftah (Algeria), the cores were crafted in the laboratory using a core drill. This work examines the relationships between mechanical properties and some physical properties of limestone. Many empirical equations are established between UCS and physical properties of limestone (such as dry bulk density, velocity of P-waves, dynamic Young’s modulus, alteration index, and total porosity). Other correlations, UCS - tensile strength, dynamic Young’s modulus - static Young’s modulus have been find. Based on the Mohr-Coulomb failure criterion, we were able to establish mathematical relationships that will allow estimating the cohesion and internal friction angle from UCS and indirect tensile strength. Results from this study can be useful for mining industry for resolve range of geomechanical problems such as slope stability.

Keywords: limestone, mechanical strength, Young’s modulus, porosity

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Authors: Apurva Saxena, Sunita Gond

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Demand of computation, data storage in large amount are rapidly increases day by day. Cloud computing technology fulfill the demand of today’s computation but this will lead to high power consumption in cloud data centers. Initiative for Green IT try to reduce power consumption and its adverse environmental impacts. Paper also focus on various green computing techniques, proposed models and efficient way to make cloud greener.

Keywords: virtualization, cloud computing, green computing, data center

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Authors: Mafawez Alharbi, Mahdi Jemmali

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E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: artificial intelligence, architecture, e-learning, software engineering, processing

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Authors: Harald Lang, Michael Bader, A. Buchroithner

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Holistic methods covering the development process as a whole – e.g. systems engineering – have established themselves in product design. However, technical product optimization, representing improvements in efficiency and/or minimization of loss, usually applies to single components of a system. A holistic approach is being defined based on a hierarchical point of view of systems engineering. This is subsequently presented using the example of an electromechanical flywheel energy storage system for automotive applications.

Keywords: design, product development, product optimization, systems engineering

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Authors: Houria Hamitouche, Abdellah Khelifa

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Quaternary ammonium salts (QACs) are the most common cationic surfactants of natural or synthetic origin usually. They possess one or more hydrophobic hydrocarbon chains and hydrophilic cationic group. In fact, the hydrophobic groups are derived from three main sources: petrochemicals, vegetable oils, and animal fats. These QACs have attracted the attention of chemists for a long time, due to their general simple synthesis and their broad application in several fields. They are important as ingredients of cosmetic products and are also used as corrosion inhibitors, in emulsion polymerization and textile processing. Within biological applications, QACs show a good antimicrobial activity and can be used as medicines, gene delivery agents or in DNA extraction methods. The 2004 worldwide annual consumption of QACs was reported as 500,000 tons. The petroleum product is considered a true reservoir of a variety of chemical species, which can be used in the synthesis of quaternary ammonium salts. The purpose of the present contribution is to synthesize the quaternary ammonium salts by Menschutkin reaction, via chloromethylation/quaternization sequences, from Algerian petroleum products namely: reformate, light naphtha and kerosene and characterize.

Keywords: quaternary ammonium salts, reformate, light naphtha, kerosene

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Authors: Meshandren Naidoo, Amy Gooden

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Implantable brain-computer interface (BCI) technologies have developed to the point where brain-computer communication is possible. This has great potential in the medical field, as it allows persons who have lost capacities. However, ethicists and regulators call for a strict approach to these technologies due to the impact on personhood. This research demonstrates that the personhood debate is more nuanced and that where an African approach to personhood is used, it may produce results more favorable to the development and use of this technology.

Keywords: artificial intelligence, law, neuroscience, ethics

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: M. A. Ashour

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As it is known Egypt is one of the countries having oldest sugarcane industry, which goes back to the year 710 AD. Cane plantations are the main agricultural product in five governorates in Upper Egypt (El-Menia, Sohag, Qena, Luxor, and Aswan), producing not less than 16 million tons a year. Eight factories (Abou-korkas, Gena, Nagaa-Hamadi, Deshna, Kous, Armant, Edfuo, and Komombo), located in such upper Egypt governorates generates huge amount of wastes during the manufacturing stage, the so called bagasse which is the fibrous, and cellulosic materials remaining after the era of the sugarcane and the juice extraction, presents about 30% of such wastes. The amount of bagasse generated yearly through the manufacturing stage of the above mentioned 8 factories is approximately about 2.8 million tons, getting red safely of such huge amount, presents a serious environmental problem. Storage of that material openly in the so hot climate in upper Egypt, may cause its self-ignition under air temperature reaches 50 degrees centigrade in summer, due to the remained residual content of sugar. At the same time preparing places for safely storage for such amount is very expensive with respect to the valueless of it. So the best way for getting rid of bagasse is converting it into an added value environmentally friendly material, especially till now the utilization of it is so limited. Since oil pollution became a serious concern, the issue of environmental cleaning arises. With the structure of sugarcane bagasse, which contains fiber and high content of carbon, it can be an adsorbent to adsorb the oil contamination from the water. The present study is a trail to introduce a new material for the purification of water systems to score two goals at once, the first is getting rid of that harmful waste safely, the second is converting it to a commercial valuable material for cleaning, and purifying the water from oil spills, and petroleum pollution. Introduced the new material proved very good performance, and higher efficiency than other similar materials available in the local market, in both closed and open systems. The introduced modified material can absorb 10 times its weight of oil, while don't absorb any water.

Keywords: environment, water resources, agricultural wastes, oil pollution control, sugarcane

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Authors: H. Chenine, D. Ouinas, Z. Bennaceur

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The thin shell structures like metal are particularly susceptible to buckling or geometric instability. Their sizing is performed by resorting to simplified rules, this approach is generally conservative. Indeed, these structures are very sensitive to the slightest imperfection shape (initial geometrical defects). The design is usually based on the knowledge of the real or perceived initial state. Now this configuration evolves over time, there is usually the addition of new deformities due to operation (accidental loads, creep), but also to loss of material located in the corroded areas. Taking into account these various damage generally led to a loss of bearing capacity. In order to preserve the charge potential of the structure, it is then necessary to find a different material. In our study we plan to replace the material used for reservoirs found in the company Sonatrach with a composite material made from carbon fiber or glass. 6 to 12 layers of composite are simply stuck. Research is devoted to the study of the buckling of multilayer shells subjected to an imposed displacement, allowed us to identify the key parameters and those whose effect is less. For all results, we find that the carbon epoxy T700E is the strongest, increasing the number of layers increases the strength of the shell.

Keywords: Finite Element Analysis, circular notches, buckling, tank made composite materials

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Authors: Billy Moore, Izaiah Smith, Dominic Mckinney, Andrew Cisco, Mehdi Kabir

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Phase-change materials (PCMs) are considered one of the most promising substances to be engaged passively in thermal management and storage systems for spacecraft, where it is critical to diminish the overall mass of the onboard thermal storage system while minimizing temperature fluctuations upon drastic changes in the environmental temperature within the orbit stage. This makes the development of effective thermal management systems more challenging since there is no atmosphere in outer space to take advantage of natural and forced convective heat transfer. PCM can store or release a tremendous amount of thermal energy within a small volume in the form of latent heat of fusion in the phase-change processes of melting and solidification from solid to liquid or, conversely, during which temperature remains almost constant. However, the existing PCMs pose very low thermal conductivity, leading to an undesirable increase in total thermal resistance and, consequently, a slow thermal response time. This often turns into a system bottleneck from the thermal performance perspective. To address the above-mentioned drawback, the present study aims to design and develop various heat sinks featured by nano-structured graphitic foams (i.e., carbon foam), expanded graphite (EG), and open-cell copper foam (OCCF) infiltrated with a conventional paraffin wax PCM with a melting temperature of around 35 °C. This study focuses on the use of passive thermal management techniques to develop efficient heat sinks to maintain the electronics circuits’ and battery module’s temperature within the thermal safety limit for small spacecraft and satellites such as the Pumpkin and OPTIMUS battery modules designed for CubeSats with a cross-sectional area of approximately 4˝×4˝. Thermal response times for various heat sinks are assessed in a vacuum chamber to simulate space conditions.

Keywords: heat sink, porous foams, phase-change material (PCM), spacecraft thermal management

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Authors: Amaladhithyan Krishnamoorthy, Ruvaitha Banu

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Vision is considered as the most important sense in humans, without which leading a normal can be often difficult. There are many existing smart canes for visually impaired with obstacle detection using ultrasonic transducer to help them navigate. Though the basic smart cane increases the safety of the users, it does not help in filling the void of visual loss. This paper introduces the concept of Digi-Buddy which is an evolved smart cane for visually impaired. The cane consists for several modules, apart from the basic obstacle detection features; the Digi-Buddy assists the user by capturing video/images and streams them to the server using a wide-angled camera, which then detects the objects using Deep Convolutional Neural Network. In addition to determining what the particular image/object is, the distance of the object is assessed by the ultrasonic transducer. The sound generation application, modelled with the help of Natural Language Processing is used to convert the processed images/object into audio. The object detected is signified by its name which is transmitted to the user with the help of Bluetooth hear phones. The object detection is extended to facial recognition which maps the faces of the person the user meets in the database of face images and alerts the user about the person. One of other crucial function consists of an automatic-intimation-alarm which is triggered when the user is in an emergency. If the user recovers within a set time, a button is provisioned in the cane to stop the alarm. Else an automatic intimation is sent to friends and family about the whereabouts of the user using GPS. In addition to safety and security by the existing smart canes, the proposed concept devices to be implemented as a prototype helping visually-impaired visualize their surroundings through audio more in an amicable way.

Keywords: artificial intelligence, facial recognition, natural language processing, internet of things

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Authors: A. Kavandi, K. Goshtasbi, M. R. Hadei, H. Nejati

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In geothermal energy production, the method of liquid nitrogen (LN₂) fracturing in hot, dry rock is one of the most effective methods to increase the permeability of the reservoir. The geothermal reservoirs mainly consist of hard rocks such as granites and metamorphic rocks like gneiss with high temperatures. Gneiss, as a metamorphic rock, experiences a high level of inherent anisotropy. This type of anisotropy is considered as the nature of rocks, which affects the mechanical behavior of rocks. The aim of this study is to investigate the effects of heating-liquid nitrogen (LN₂) cooling treatment and rock anisotropy on the fracture toughness of gneiss. For this aim, a series of semi-circular bend (SCB) tests were carried out on specimens of gneiss with different anisotropy plane angles (0°, 30°, 60°, and 90°). In this study, gneiss specimens were exposed to heating–cooling treatment through gradual heating to 100°C followed by LN₂ cooling. Results indicate that the fracture toughness of treated samples is lower than that of untreated samples, and with increasing the anisotropy plane angle, the fracture toughness increases. The scanning electron microscope (SEM) technique is also implemented to evaluate the fracture process zone (FPZ) ahead of the crack tip.

Keywords: heating-cooling, anisotropic rock, fracture toughness, liquid nitrogen

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Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

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The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

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Authors: Tatiane Benvenuti, Fernando Hamerski, Alexandre Giacobbo, Andrea M. Bernardes, Marco A. S. Rodrigues

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Population growth in urban areas has caused damages to the environment, a consequence of the uncontrolled dumping of domestic and industrial wastewater. The capacity of some plants to purify domestic and agricultural wastewater has been demonstrated by several studies. Since natural wetlands have the ability to transform, retain and remove nutrients, constructed wetlands have been used for wastewater treatment. They are widely recognized as an economical, efficient and environmentally acceptable means of treating many different types of wastewater. T. domingensis Pers. species have shown a good performance and low deployment cost to extract, detoxify and sequester pollutants. Constructed Floating Wetlands (CFWs) consist of emergent vegetation established upon a buoyant structure, floating on surface waters. The upper parts of the vegetation grow and remain primarily above the water level, while the roots extend down in the water column, developing an extensive under water-level root system. Thus, the vegetation grows hydroponically, performing direct nutrient uptake from the water column. Biofilm is attached on the roots and rhizomes, and as physical and biochemical processes take place, the system functions as a natural filter. The aim of this study is to diagnose the application of macrophytes in artificial floating in the treatment of domestic sewage in south Brazil. The T. domingensis Pers. plants were placed in a flotation system (polymer structure), in full scale, in a sewage treatment plant. The sewage feed rate was 67.4 m³.d⁻¹ ± 8.0, and the hydraulic retention time was 11.5 d ± 1.3. This CFW treat the sewage generated by 600 inhabitants, which corresponds to 12% of the population served by this municipal treatment plant. During 12 months, samples were collected every two weeks, in order to evaluate parameters as chemical oxygen demand (COD), biochemical oxygen demand in 5 days (BOD5), total Kjeldahl nitrogen (TKN), total phosphorus, total solids, and metals. The average removal of organic matter was around 55% for both COD and BOD5. For nutrients, TKN was reduced in 45.9% what was similar to the total phosphorus removal, while for total solids the reduction was 33%. For metals, aluminum, copper, and cadmium, besides in low concentrations, presented the highest percentage reduction, 82.7, 74.4 and 68.8% respectively. Chromium, iron, and manganese removal achieved values around 40-55%. The use of T. domingensis Pers. in artificial floating for sewage treatment is an effective and innovative alternative in Brazilian sewage treatment systems. The evaluation of additional parameters in the treatment system may give useful information in order to improve the removal efficiency and increase the quality of the water bodies.

Keywords: constructed wetland, floating system, sewage treatment, Typha domingensis Pers.

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

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Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

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Authors: Nazmin Akter, Tariqul Islam, Abu Sayed

Abstract:

Food loss and waste have become critical global issues, with approximately one-third of the world's food production being wasted. Among the various food products, horticultural fruits and vegetables are especially susceptible to loss due to their relatively short shelf lives. Litchi (Litchi chinensis) is one of Bangladesh's most important horticultural fruits. But the problem with this fruit is its short shelf life by losing weight faster after harvest. The experiment was carried out at Hajee Mohammad Danesh Science and Technology University, Dinajpur-5200 Bangladesh during 2020-2021. The objective of this experiment was to see the impact of nutrients viz., urea (1%), calcium chloride (1%), borax (1%), and their combinations on fruit quality and shelf life of litchi cv. Bombai. The experiment was laid out in a randomized block design with 7 treatments and 3 replications. Two sprays of each treatment were applied from the last week of May to June (at 20-day intervals). The results indicated that all the treatments significantly improved the quality parameters of litchi fruits as compared to the control. In terms of physicochemical characteristics fruit weight (20.30g), fruit volume (20m ml), and pulp percent (17.14) were found maximum with minimum stone percent (11.09) with the application of urea 1% + borax 1%+ calcium chloride 1%. Maximum TSS (19.62oBrix), TSS/acidity ratio (24.57), maximum ascorbic acid (45.19 mg/100 g pulp), and minimum acidity (0.80%) were reported with the application of T6 (Urea 1% + borax 1%+ calcium chloride 1%) treatments whereas fruits treated with urea 1% + borax 1% gave maximum total sugars (26.64%) and reducing sugars (19.19%) as compared to control. In the case of storage characters, application of Urea 1% + borax 1%+ calcium chloride 1% resulted in a minimum physiological loss in weight (6.11%), (8.41%), and (10.65%) for 2 days, 4 days, and 6 days respectively. In conclusion, to obtain better quality and increased storage period of litchi fruits, two sprays of urea, borax, and calcium chloride (1%) could be used during the fruit growth and development period at fortnightly intervals.

Keywords: litchi chinensis, preharvest, quality, shelf life, postharvest

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Authors: A. Hadjadj, S. Maamir

Abstract:

Since the advent of the law 86/14 concerning the
exploitation of the national territory by foreign companies in
partnership with the Algerian oil and gas company, the problem of
hydrocarbons metering in the sharing production come out.
More generally, good management counting hydrocarbons can
provide data on the production wells, the field and the reservoir for
medium and long term planning, particularly in the context of the
management and field development.
In this work, we are interested in the transactional metering which
is a very delicate and crucial period in the current context of the new
hydrocarbon’s law characterized by assets system between the
various activities of Sonatrach and its foreign partners.
After a state of the art on hydrocarbons metering devices in
Algeria and elsewhere, we will decline the advantages and
disadvantages of each system, and then we describe the problem to
try to reach an optimal solution.

Keywords: transactional metering, flowmeter orifice, heat flow, Sonatrach

Procedia PDF Downloads 362

Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

Abstract:

Arrival of artificial intelligence or smart robots in the modern world put them in charge on pericise and at risk. So acting human activities with robots makes criminal or civil responsibilities for their acts or behavior. The practical usage of smart robots has entered them in to a unique situation when naturalization happens and smart robots are identifies as members of society. There would be some legal situation by adopting these new smart citizens. The first situation is about legal responsibility of robots. Recognizing the naturalization of robot involves some basic right , so humans have the rights of employment, property, housing, using energy and other human rights may be employed for robots. So how would be the practice of these rights in the society and if some problems happens with these rights, how would the civil responsibility and punishment? May we consider them as population and count on the social programs? The second episode is about the criminal responsibility of robots in important activity instead of human that is the aim of inventing robots with handling works in AI technology , but the problem arises when some accidents are happened by robots who are in charge of important activities like army, surgery, transporting, judgement and so on. Moreover, recognizing independent identification for robots in the legal world by register ID cards, naturalization and civilian rights makes and prepare the same rights and obligations of human. So, the civil responsibility is not avoidable and if the robot commit a crime it would have criminal responsibility and have to be punished. The basic component of criminal responsibility may changes in so situation. For example, if designation for criminal responsibility bounds to human by sane, maturity, voluntariness, it would be for robots by being intelligent, good programming, not being hacked and so on. So it is irrational to punish robots by prisoning , execution and other human punishments for body. We may determine to make digital punishments like changing or repairing programs, exchanging some parts of its body or wreck it down completely. Finally the responsibility of the smart robot creators, programmers, the boss in chief, the organization who employed robot, the government which permitted to use robot in important bases and activities , will be analyzing and investigating in their article.

Keywords: robot, artificial intelligence, personality, responsibility

Procedia PDF Downloads 147

Authors: Gordana Ćetković, Sanja Podunavac-Kuzmanović, Jasna Čanadanović-Brunet, Vesna Tumbas Šaponjac, Vanja Šeregelj, Jelena Vulić, Slađana Stajčić

Abstract:

The color of food is one of the decisive factors for consumers. Potential toxicity of artificial food colorants has led to the consumers' preference for natural products over products with artificial colors. Natural pigments have many bioactive functions, such as antioxidant, provitamin and many other. Having this in mind, the acceptability of natural colorants by the consumers is much higher. Being present in all photosynthetic plant tissues carotenoids are probably most widespread pigments in nature. Carrot (Daucus carota) is a good source of functional food components. Carrot is especially rich in carotenoids, mainly α- and β-carotene and lutein. For this study, carrot was extracted using classical extraction with hexane and ethyl acetate, as well as supercritical CO₂ extraction. The extraction efficiency was evaluated by estimation of carotenoid yield determined spectrophotometrically. Classical extraction using hexane (18.27 mg β-carotene/100 g DM) was the most efficient method for isolation of carotenoids, compared to ethyl acetate classical extraction (15.73 mg β-carotene/100 g DM) and supercritical CO₂ extraction (0.19 mg β-carotene/100 g DM). Three carrot extracts were tested in terms of antioxidant activity using DPPH and reducing power assay as well. Surprisingly, ethyl acetate extract had the best antioxidant activity on DPPH radicals (AADPPH=120.07 μmol TE/100 g) while hexane extract showed the best reducing power (RP=1494.97 μmol TE/100 g). Hexane extract was chosen as the most potent source of carotenoids and was encapsulated in whey protein by freeze-drying. Carotenoid encapsulation efficiency was found to be high (89.33%). Based on our results it can be concluded that carotenoids from carrot can be efficiently extracted using hexane and classical extraction method. This extract has the potential to be applied in encapsulated form due to high encapsulation efficiency and coloring capacity. Therefore it can be used for dietary supplements development and food fortification.

Keywords: carotenoids, carrot, extraction, encapsulation

Procedia PDF Downloads 271

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 71

Authors: Manar Y. Abd El-Aziz, Alyaa E. Morgham, Amira A. El-Fallal, Heba Tolla E. Abo El Naga

Abstract:

Different textile materials are usually used in upholstery. However, upholstery parts may become unhealthy when dust accrues and bacteria raise on the surface, which negatively affects the user's health. Also, leather and artificial leather were used in upholstery but, leather has a high cost and artificial leather has a potential chemical risk for users. Researchers have advanced vegie leather made from bacterial cellulose a symbiotic culture of bacteria and yeast (SCOBY). SCOBY remains a gelatinous, cellulose biofilm discovered floating at the air-liquid interface of the container. But this leather still needs some enhancement for its mechanical properties. This study aimed to prepare SCOBY, produce bamboo rib knitted fabrics with two different stitch densities, and cotton woven fabric then laminate these fabrics with the prepared SCOBY film to enhance the mechanical properties of the SCOBY leather at the same time; add anti-microbial function to the prepared fabrics. Laboratory tests were conducted on the produced samples, including tests for function properties; anti-microbial, thermal conductivity and light transparency. Physical properties; thickness and mass per unit. Mechanical properties; elongation, tensile strength, young modulus, and peel force. The results showed that the type of the fabric affected significantly SCOBY properties. According to the test results, the bamboo knitted fabric with higher stitch density laminated with SCOBY was chosen for its tensile strength and elongation as the upholstery of a bed model with antimicrobial properties and comfortability in the headrest design. Also, the single layer of SCOBY was chosen regarding light transparency and lower thermal conductivity for the creation of a lighting unit built into the bed headboard.

Keywords: anti-microbial, bamboo, rib, SCOPY, upholstery

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Authors: Abdelhak Bouchakour, Mustafa Brahami, Layachi Zaghba

Abstract:

The use of photovoltaic energy offers an inexhaustible supply of energy but also a clean and non-polluting energy, which is a definite advantage. The geographical location of Algeria promotes the development of the use of this energy. Indeed, given the importance of the intensity of the radiation received and the duration of sunshine. For this reason, the objective of our work is to develop a data-processing tool (software) of calculation and optimization of dimensioning of the photovoltaic installations. Our approach of optimization is basing on mathematical models, which amongst other things describe the operation of each part of the installation, the energy production, the storage and the consumption of energy.

Keywords: solar panel, solar radiation, inverter, optimization

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Authors: J. D. Marinaccio, I. Mabbett, C. Glover, D. Worsley

Abstract:

Through use of novel modern/rapid processing techniques such as screen printing and Near-Infrared (NIR) radiative curing, process time for the sintering of sintered nickel plaques, applicable to alkaline nickel battery chemistries, has been drastically reduced from in excess of 200 minutes with conventional convection methods to below 2 minutes using NIR curing methods. Steps have also been taken to remove the need for forming gas as a reducing agent by implementing carbon as an in-situ reducing agent, within the ink formulation.

Keywords: batteries, energy, iron, nickel, storage

Procedia PDF Downloads 439