Search results for: sharpness-aware optimization

Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Szymon Kuczynski

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Poland is characterized by the presence of numerous sedimentary basins and hydrocarbon provinces. Since 2006 exploration for hydrocarbons in Poland become gradually more focus on new unconventional targets, particularly on the shale gas potential of the Upper Ordovician and Lower Silurian in the Baltic-Podlasie-Lublin Basin. The first forecast prepared by US Energy Information Administration in 2011 indicated to 5.3 Tcm of natural gas. In 2012, Polish Geological Institute presented its own forecast which estimated maximum reserves on 1.92 Tcm. The difference in the estimates was caused by problems with calculations of the initial amount of adsorbed, as well as free, gas trapped in shale rocks (GIIP - Gas Initially in Place). This value is dependent from sorption capacity, gas saturation and mutual interactions between gas, water, and rock. Determination of the reservoir type in the initial exploration phase brings essential knowledge, which has an impact on decisions related to the production. The study of porosity impact for phase envelope shift eliminates errors and improves production profitability. Confinement phenomenon affects flow characteristics, fluid properties, and phase equilibrium. The thermodynamic behavior of confined fluids in porous media is subject to the basic considerations for industrial applications such as hydrocarbons production. In particular the knowledge of the phase equilibrium and the critical properties of the contained fluid is essential for the design and optimization of such process. In pores with a small diameter (nanopores), the effect of the wall interaction with the fluid particles becomes significant and occurs in shale formations. Nano pore size is similar to the fluid particles’ diameter and the area of particles which flow without interaction with pore wall is almost equal to the area where this phenomenon occurs. The molecular simulation studies have shown an effect of confinement to the pseudo critical properties. Therefore, the critical parameters pressure and temperature and the flow characteristics of hydrocarbons in terms of nano-scale are under the strong influence of fluid particles with the pore wall. It can be concluded that the impact of a single pore size is crucial when it comes to the nanoscale because there is possible the above-described effect. Nano- porosity makes it difficult to predict the flow of reservoir fluid. Research are conducted to explain the mechanisms of fluid flow in the nanopores and gas extraction from porous media by desorption.

Keywords: adsorption, capillary condensation, phase envelope, nanopores, unconventional natural gas

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

Procedia PDF Downloads 125

Authors: T. Sadunishvili, L. Kutateladze, T. Urushadze, R. Khvedelidze, N. Zakariashvili, M. Jobava, G. Kvesitadze

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Multiple repeated soil-climatic zones in Georgia determines the diversity of microorganisms. Hundreds of microscopic fungi of different genera have been isolated from different ecological niches, including some extreme environments. Biosynthetic ability of microscopic fungi has been studied. Trichoderma ressei, representative of the Ascomycetes secrete cellulolytic and xylanolytic enzymes that act in synergy to hydrolyze polysaccharide polymers to glucose, xylose and arabinose, which can be fermented to biofuels. The other mesophilic strains producing cellulases are Allesheria terrestris, Chaetomium thermophile, Fusarium oxysporium, Piptoporus betulinus, Penicillium echinulatum, P. purpurogenum, Aspergillus niger, A. wentii, A. versicolor, A. fumigatus etc. In the majority of the cases the cellulases produced by strains of genus Aspergillus usually have high β-glucosidase activity and average endoglucanases levels (with some exceptions), whereas strains representing Trichoderma have high endo enzyme and low β-glucosidase, and hence has limited efficiency in cellulose hydrolysis. Six producers of stable cellulases and xylanases from mesophilic and thermophilic fungi have been selected. By optimization of submerged cultivation conditions, high activities of cellulases and xylanases were obtained. For enzymes purification, their sedimentation by organic solvents such as ethyl alcohol, acetone, isopropanol and by ammonium sulphate in different ratios have been carried out. Best results were obtained with precipitation by ethyl alcohol (1:3.5) and ammonium sulphate. The yields of enzyme according to cellulase activities were 80-85% in both cases. Cellulase activity of enzyme preparation obtained from the strain Trichoderma viride X 33 is 126 U/g, from the strain Penicillium canescence D 85–185U/g and from the strain Sporotrichum pulverulentum T 5-0 110 U/g. Cellulase activity of enzyme preparation obtained from the strain Aspergillus sp. Av10 is 120 U/g, xylanase activity of enzyme preparation obtained from the strain Aspergillus niger A 7-5–1155U/g and from the strain Aspergillus niger Aj 38-1250 U/g. Optimum pH and temperature of operation and thermostability, of the enzyme preparations, were established. The efficiency of hydrolyses of different agricultural residues by the microscopic fungi cellulases has been studied. The glucose yield from the residues as a result of enzymatic hydrolysis is highly determined by the ratio of enzyme to substrate, pH, temperature, and duration of the process. Hydrolysis efficiency was significantly increased as a result of different pretreatment of the residues by different methods. Acknowledgement: The Study was supported by the ISTC project G-2117, funded by Korea.

Keywords: cellulase, xylanase, microscopic fungi, enzymatic hydrolysis

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Authors: Minal Jain, Vinayak Malhotra

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Solid Propellant ignition consists of rapid and complex events comprising of heat generation and transfer of heat with spreading of flames over the entire burning surface area. Proper combustion and thus propulsion depends heavily on the modes of heat transfer characteristics and cavity volume. Fire safety is an integral component of a successful rocket flight failing to which may lead to overall failure of the rocket. This leads to enormous forfeiture in resources viz., money, time, and labor involved. When the propellant is ignited, thrust is generated and the casing gets heated up. This heat adds on to the propellant heat and the casing, if not at proper orientation starts burning as well, leading to the whole rocket being completely destroyed. This has necessitated active research efforts emphasizing a comprehensive study on the inter-energy relations involved for effective utilization of the solid rocket motors for better space missions. Present work is focused on one of the major influential aspects of this detrimental burning which is the presence of an external heat source, in addition to a potential heat source which is already ignited. The study is motivated by the need to ensure better combustion and fire safety presented experimentally as a simplified small-scale mode of a rocket carrying a solid propellant inside a cavity. The experimental setup comprises of a paraffin wax candle as the pilot fuel and incense stick as the external heat source. The candle is fixed and the incense stick position and location is varied to investigate the find the influence of the pilot heat source. Different configurations of the external heat source presence with separation distance are tested upon. Regression rates of the pilot thin solid fuel are noted to fundamentally understand the non-linear heat and mass transfer which is the governing phenomenon. An attempt is made to understand the phenomenon fundamentally and the mechanism governing it. Results till now indicate non-linear heat transfer assisted with the occurrence of flaming transition at selected critical distances. With an increase in separation distance, the effect is noted to drop in a non-monotonic trend. The parametric study results are likely to provide useful physical insight about the governing physics and utilization in proper testing, validation, material selection, and designing of solid rocket motors with enhanced safety.

Keywords: combustion, propellant, regression, safety

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Authors: Guerich Mohamed, Assaf Samir

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The application of viscoelastic materials in the form of constrained layers in mechanical structures is an efficient and cost-effective technique for solving noise and vibration problems. This technique requires a design tool to select the best location, type, and thickness of the damping treatment. This paper presents a finite element model for the vibration of beams partially or fully covered with a constrained viscoelastic damping material. The model is based on Bernoulli-Euler theory for the faces and Timoshenko beam theory for the core. It uses four variables: the through-thickness constant deflection, the axial displacements of the faces, and the bending rotation of the beam. The sandwich beam finite element is compatible with the conventional C1 finite element for homogenous beams. To validate the proposed model, several free vibration analyses of fully or partially covered beams, with different locations of the damping patches and different percent coverage, are studied. The results show that the proposed approach can be used as an effective tool to study the influence of the location and treatment size on the natural frequencies and the associated modal loss factors. Then, a parametric study regarding the variation in the damping characteristics of partially covered beams has been conducted. In these studies, the effect of core shear modulus value, the effect of patch size variation, the thickness of constraining layer, and the core and the locations of the patches are considered. In partial coverage, the spatial distribution of additive damping by using viscoelastic material is as important as the thickness and material properties of the viscoelastic layer and the constraining layer. Indeed, to limit added mass and to attain maximum damping, the damping patches should be placed at optimum locations. These locations are often selected using the modal strain energy indicator. Following this approach, the damping patches are applied over regions of the base structure with the highest modal strain energy to target specific modes of vibration. In the present study, a more efficient indicator is proposed, which consists of placing the damping patches over regions of high energy dissipation through the viscoelastic layer of the fully covered sandwich beam. The presented approach is used in an optimization method to select the best location for the damping patches as well as the material thicknesses and material properties of the layers that will yield optimal damping with the minimum area of coverage.

Keywords: finite element model, damping treatment, viscoelastic materials, sandwich beam

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Authors: masmoudi Jabri Khaoula, Zitouni Hana, Bousselmi Latifa, Akrout Hanen

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Mathematical modeling has become an essential tool for sustainable wastewater management, particularly for the simulation and the optimization of complex processes involved in activated sludge systems. In this context, the activated sludge model (ASM3h) was used for the simulation of a Biological Membrane Reactor (MBR) as it includes the integration of biological wastewater treatment and physical separation by membrane filtration. In this study, the MBR with a useful volume of 12.5 L was fed continuously with poultry slaughterhouse wastewater (PSWW) for 50 days at a feed rate of 2 L/h and for a hydraulic retention time (HRT) of 6.25h. Throughout its operation, High removal efficiency was observed for the removal of organic pollutants in terms of COD with 84% of efficiency. Moreover, the MBR has generated a treated effluent which fits with the limits of discharge into the public sewer according to the Tunisian standards which were set in March 2018. In fact, for the nitrogenous compounds, average concentrations of nitrate and nitrite in the permeat reached 0.26±0.3 mg. L-1 and 2.2±2.53 mg. L-1, respectively. The simulation of the MBR process was performed using SIMBA software v 5.0. The state variables employed in the steady state calibration of the ASM3h were determined using physical and respirometric methods. The model calibration was performed using experimental data obtained during the first 20 days of the MBR operation. Afterwards, kinetic parameters of the model were adjusted and the simulated values of COD, N-NH4+and N- NOx were compared with those reported from the experiment. A good prediction was observed for the COD, N-NH4+and N- NOx concentrations with 467 g COD/m³, 110.2 g N/m³, 3.2 g N/m³ compared to the experimental data which were 436.4 g COD/m³, 114.7 g N/m³ and 3 g N/m³, respectively. For the validation of the model under dynamic simulation, the results of the experiments obtained during the second treatment phase of 30 days were used. It was demonstrated that the model simulated the conditions accurately by yielding a similar pattern on the variation of the COD concentration. On the other hand, an underestimation of the N-NH4+ concentration was observed during the simulation compared to the experimental results and the measured N-NO3 concentrations were lower than the predicted ones, this difference could be explained by the fact that the ASM models were mainly designed for the simulation of biological processes in the activated sludge systems. In addition, more treatment time could be required by the autotrophic bacteria to achieve a complete and stable nitrification. Overall, this study demonstrated the effectiveness of mathematical modeling in the prediction of the performance of the MBR systems with respect to organic pollution, the model can be further improved for the simulation of nutrients removal for a longer treatment period.

Keywords: activated sludge model (ASM3h), membrane bioreactor (MBR), poultry slaughter wastewater (PSWW), reuse

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Authors: Cheng-Chi Yu, Yu-Shiue Wang, Kei-Lin Kuo

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Active Independent Front Steering system is a steering system which can according to vehicle driving situation adjusts the relation of steering angle between inner wheel and outer wheel. In low-speed cornering, AIFS sets the steering angles of inner and outer wheel into Ackerman steering geometry to make vehicle has less cornering radius. Besides, AIFS changes the steering geometry to parallel or even anti-Ackerman steering geometry to keep vehicle stability in high-speed cornering. Therefore, based on the analysis of the vehicle steering behavior from different steering geometries, this study develops a new screw type of active independent front steering system to make vehicles best cornering performance at any speeds. The screw type of active independent front steering system keeps the pinion and separates the rack into main rack and second rack. Two racks connect by a screw. Extra screw rotated motion powered by assistant motor through coupler makes second rack move relative to main rack, which can adjust both steering ratio and steering geometry. First of all, this study distinguishes the steering geometry by using Ackerman percentage and utilizes the software of ADAMS/Car to construct diverse steering geometry models. The different steering geometries are compared at low-speed and high-speed cornering, and then control strategies of the active independent front steering systems could be formulated. Secondly, this study applies closed loop equation to analyze tire steering angles and carries out optimization calculations to make the steering geometry from traditional rack and pinion steering system near to Ackerman steering geometry. Steering characteristics of the optimum steering mechanism and motion characteristics of vehicle installed the steering mechanism are verified by ADAMS/Car models of front suspension and full vehicle respectively. By adding dual auxiliary rack and dual motor to the optimum steering mechanism, the active independent front steering system could be developed to achieve the functions of variable steering ratio and variable steering geometry. At last, this study uses ADAMS/Car and Matlab/Simulink to co-simulate the cornering motion of vehicles confirms the vehicle installed the Active Independent Front Steering (AIFS) system has better handling performance than that with Active Independent Steering (AFS) system or with Electric Power Steering (EPS) system. At low-speed cornering, the vehicles with AIFS system and with AFS system have better maneuverability, less cornering radius, than the traditional vehicle with EPS system because that AIFS and AFS systems both provide function of variable steering ratio. However, there is a slight penalty in the motor(s) power consumption. In addition, because of the capability of variable steering geometry, the vehicle with AIFS system has better high-speed cornering stability, trajectory keeping, and even less motor(s) power consumption than that with EPS system and also with AFS system.

Keywords: active front steering system, active independent front steering system, steering geometry, steering ratio

Procedia PDF Downloads 190

Authors: África Vicario, Fernando J. Álvarez, Felipe Parralejo, Fernando Aranda

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The irrigation systems of traditional agriculture, such as gravity-fed irrigation, produce a great waste of water because, generally, there is no control over the amount of water supplied in relation to the water needed. The AIRON Project tries to solve this problem by implementing an IoT-based system to sensor the irrigation plots so that the state of the crops and the amount of water used for irrigation can be known remotely. The IoT system consists of a sensor network that measures the humidity of the soil, the weather conditions (temperature, relative humidity, wind and solar radiation) and the irrigation water flow. The communication between this network and a central gateway is conducted by means of long-range wireless communication that depends on the characteristics of the irrigation plot. The main objective of the AIRON project is to deploy an IoT sensor network in two different plots of the irrigation community of Aranjuez in the Spanish region of Madrid. The first plot is 2 km away from the central gateway, so LoRa has been used as the base communication technology. The problem with this plot is the absence of mains electric power, so devices with energy-saving modes have had to be used to maximize the external batteries' use time. An ESP32 SOC board with a LoRa module is employed in this case to gather data from the sensor network and send them to a gateway consisting of a Raspberry Pi with a LoRa hat. The second plot is located 18 km away from the gateway, a range that hampers the use of LoRa technology. In order to establish reliable communication in this case, the long-term evolution (LTE) standard is used, which makes it possible to reach much greater distances by using the cellular network. As mains electric power is available in this plot, a Raspberry Pi has been used instead of the ESP32 board to collect sensor data. All data received from the two plots are stored on a proprietary server located at the irrigation management company's headquarters. The analysis of these data by means of machine learning algorithms that are currently under development should allow a short-term prediction of the irrigation water demand that would significantly reduce the waste of this increasingly valuable natural resource. The major finding of this work is the real possibility of deploying a remote sensing system for irrigated plots by using Commercial-Off-The-Shelf (COTS) devices, easily scalable and adaptable to design requirements such as the distance to the control center or the availability of mains electrical power at the site.

Keywords: internet of things, irrigation water control, LoRa, LTE, smart farming

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Authors: Peter. M. Kusen, Georg Wandrey, Christopher Probst, Dietrich Kohlheyer, Jochen Buchs, Jorg Pietruszkau

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Light as a stimulus provides the capability to develop regulation techniques for customizable gene expression. A great advantage is the extremely flexible and accurate dosing that can be performed in a non invasive and sterile manner even for high throughput technologies. Therefore, light regulation in a multiwell microbioreactor system was realized providing the opportunity to control gene expression with outstanding complexity. A light-regulated gene expression system in Saccharomyces cerevisiae was designed applying the strategy of caged compounds. These compounds are photo-labile protected and therefore biologically inactive regulator molecules which can be reactivated by irradiation with certain light conditions. The “caging” of a repressor molecule which is consumed after deprotection was essential to create a flexible expression system. Thereby, gene expression could be temporally repressed by irradiation and subsequent release of the active repressor molecule. Afterwards, the repressor molecule is consumed by the yeast cells leading to reactivation of gene expression. A yeast strain harboring a construct with the corresponding repressible promoter in combination with a fluorescent marker protein was applied in a Photo-BioLector platform which allows individual irradiation as well as online fluorescence and growth detection. This device was used to precisely control the repression duration by adjusting the amount of released repressor via different irradiation times. With the presented screening platform the regulation of complex expression procedures was achieved by combination of several repression/derepression intervals. In particular, a stepwise increase of temporally-constant expression levels was demonstrated which could be used to study concentration dependent effects on cell functions. Also linear expression rates with variable slopes could be shown representing a possible solution for challenging protein productions, whereby excessive production rates lead to misfolding or intoxication. Finally, the very flexible regulation enabled accurate control over the expression induction, although we used a repressible promoter. Summing up, the continuous online regulation of gene expression has the potential to synchronize gene expression levels to optimize metabolic flux, artificial enzyme cascades, growth rates for co cultivations and many other applications addicted to complex expression regulation. The developed light-regulated expression platform represents an innovative screening approach to find optimization potential for production processes.

Keywords: caged-compounds, gene expression regulation, optogenetics, photo-labile protecting group

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Authors: Chinedu F. Anochie

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The presence of gangue particles in recovered metal concentrates has been a serious challenge to ore dressing engineers. Middlings lower the quality of concentrates, and in most cases, drastically affect the smelter terms, owing to exorbitant amounts paid by Mineral Processing industries as treatment charge. Models which encourage optimization of liberation operations have been utilized in most ore beneficiation industries to reduce the presence of locked particles in valuable concentrates. Moreover, methods such as incorporation of regrind mills, scavenger, rougher and cleaner cells, to the milling and flotation plants has been widely employed to tackle these concerns, and to optimize the grade–recovery relationship of metal concentrates. This work compared the crushing and grinding method of liberation, to the mine to mill route, by evaluating the proportion of middlings present in selectively processed complex Pb-Zn ore samples. To establish the effect of size reduction operations on the percentage of locked particles present in recovered concentrates, two similar samples of complex Pb- Zn ores were processed. Following blasting operation, the first ore sample was ground directly in a ball mill (Mine to Mill Route of Comminution), while the other sample was manually crushed, and subsequently ground in the ball mill (Crushing and Grinding Route of Comminution). The two samples were separately sieved in a mesh to obtain the desired representative particle sizes. An equal amount of each sample that would be processed in the flotation circuit was then obtained with the aid of a weighing balance. These weighed fine particles were simultaneously processed in the flotation circuit using the selective flotation technique. Sodium cyanide, Methyl isobutyl carbinol, Sodium ethyl xanthate, Copper sulphate, Sodium hydroxide, Lime and Isopropyl xanthate, were the reagents used to effect differential flotation of the two ore samples. Analysis and calculations showed that the degree of liberation obtained for the ore sample which went through the conventional crushing and grinding route of comminution, was higher than that of the directly milled run off mine (ROM) ore. Similarly, the proportion of middlings obtained from the separated galena (PbS) and sphalerite (ZnS) concentrates, were lower for the crushed and ground ore sample. A concise data which proved that the mine to mill method of size reduction is not the most ideal technique for the recovery of quality metal concentrates has been established.

Keywords: comminution, degree of liberation, middlings, mine to mill

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Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

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The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

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Authors: A. Poukens, I. Sluyts, A. Krings, J. Swartenbroekx, D. Geeroms, J. Poukens

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Introduction and Objectives: It has been known for many years that with the administration of intravenous medication, a rather significant part of the planned to be administered infusion solution, the residual volume ( the volume that remains in the IV line and or infusion bag), does not reach the patient and is wasted. This could possibly result in under dosage and diminished therapeutic effect. Despite the important impact on the patient, the reduction of residual volume lacks attention. An optimized and clearly stated protocol concerning the reduction of residual volume in an IV line is necessary for each hospital. As described in my Master’s thesis, acquiring the degree of Master in Hospital Pharmacy, administration of intravenous medication can be optimized by reduction of the residual volume. Herewith effectiveness, user-friendliness, cost efficiency and safety were taken into account. Material and Methods: By usage of a literature study and an online questionnaire sent out to all Flemish hospitals and hospitals in the Netherlands (province Limburg), current flush methods could be mapped out. In laboratory research, possible flush methods aiming to reduce the residual volume were measured. Furthermore, a self-developed experimental method to reduce the residual volume was added to the study. The current flush methods and the self-developed experimental method were compared to each other based on cost efficiency, user-friendliness and safety. Results: There is a major difference between the Flemish and the hospitals in the Netherlands (Province Limburg) concerning the approach and method of flushing IV lines after administration of intravenous medication. The residual volumes were measured and laboratory research showed that if flushing was done minimally 1-time equivalent to the residual volume, 95 percent of glucose would be flushed through. Based on the comparison, it became clear that flushing by use of a pre-filled syringe would be the most cost-efficient, user-friendly and safest method. According to laboratory research, the self-developed experimental method is feasible and has the advantage that the remaining fraction of the medication can be administered to the patient in unchanged concentration without dilution. Furthermore, this technique can be applied regardless of the level of the residual volume. Conclusion and Recommendations: It is recommendable to revise the current infusion systems and flushing methods in most hospitals. Aside from education of the hospital staff and alignment on a uniform substantiated protocol, an optimized and clear policy on the reduction of residual volume is necessary for each hospital. It is recommended to flush all IV lines with rinsing fluid with at least the equivalent volume of the residual volume. Further laboratory and clinical research for the self-developed experimental method are needed before this method can be implemented clinically in a broader setting.

Keywords: intravenous medication, infusion therapy, IV flushing, residual volume

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Authors: Paula Quiterio, Arlete Apolinario, Celia T. Sousa, Joao Azevedo, Paula Dias, Adelio Mendes, Joao P. Araujo

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Nowadays one of the mankind's greatest challenges has been the supply of low-cost and environmentally friendly energy sources as an alternative to non-renewable fossil fuels. Hydrogen has been considered a promising solution, representing a clean and low-cost fuel. It can be produced directly from clean and abundant resources, such as sunlight and water, using photoelectrochemical cells (PECs), in a process that mimics the nature´s photosynthesis. Hematite (alpha-Fe2O3) has attracted considerable attention as a promising photoanode for solar water splitting, due to its high chemical stability, nontoxicity, availability and low band gap (2.2 eV), which allows reaching a high thermodynamic solar-to-hydrogen efficiency of 16.8 %. However, the main drawbacks of hematite such as the short hole diffusion length and the poor conductivity that lead to high electron-hole recombination result in significant PEC efficiency losses. One strategy to overcome these limitations and to increase the PEC efficiency is to use 1D nanostructures, such as nanotubes (NTs) and nanowires (NWs), which present high aspect ratios and large surface areas providing direct pathways for electron transport up to the charge collector and minimizing the recombination losses. In particular, due to the ultrathin walls of the NTs, the holes can reach the surface faster than in other nanostructures, representing a key factor for the NTs photoresponse. In this work, we prepared hematite NWs and NTs, respectively by hydrothermal process and electrochemical anodization. For hematite NWs growing, we studied the effect of variable hydrothermal conditions, different annealing temperatures and time, and the use of Ti and Sn dopants on the morphology and PEC performance. The crystalline phase characterization by X-ray diffraction was crucial to distinguish the formation of hematite and other iron oxide phases, alongside its effect on the photoanodes conductivity and consequent PEC efficiency. The conductivity of the as-prepared NWs is very low, in the order of 10-5 S cm-1, but after doping and annealing optimization it increased by a factor of 105. A high photocurrent density of 1.02 mA cm-2 at 1.45 VRHE was obtained under simulated sunlight, which is a very promising value for this kind of hematite nanostructures. The stability of the photoelectrodes was also tested, presenting good stability after several J-V measurements over time. The NTs, synthesized by fast anodizations with potentials ranging from 20-100 V, presented a linear growth of the NTs pore walls, with very low thicknesses from 10 - 18 nm. These preliminary results are also very promising for the use of hematite photoelectrodes on PEC hydrogen applications.

Keywords: hematite, nanotubes, nanowires, photoelectrochemical cells

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Authors: Philip Semaha, Zhongfang Lei, Ziwen Zhao, Sen Liu, Zhenya Zhang, Kazuya Shimizu

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The increasing generation of saline wastewater through various industrial activities is becoming a global concern for activated sludge (AS) based biological treatment which is widely applied in wastewater treatment plants (WWTPs). As for the AS process, an increase in wastewater salinity has negative impact on its overall performance. The advent of conventional aerobic granular sludge (AGS) or bacterial AGS biotechnology has gained much attention because of its superior performance. The development of algal-bacterial AGS could enhance better nutrients removal, potentially reduce aeration cost through symbiotic algae-bacterial activity, and thus, can also reduce overall treatment cost. Nonetheless, the potential of salt stress to decrease biomass growth, microbial activity and nutrient removal exist. Up to the present, little information is available on saline wastewater treatment by algal-bacterial AGS. To the authors’ best knowledge, a comparison of the two AGS systems has not been done to evaluate nutrients removal capacity in the context of salinity increase. This study sought to figure out the impact of salinity on the algal-bacterial AGS system in comparison to bacterial AGS one, contributing to the application of AGS technology in the real world of saline wastewater treatment. In this study, the salt concentrations tested were 0 g/L, 1 g/L, 5 g/L, 10 g/L and 15 g/L of NaCl with 24-hr artificial illuminance of approximately 97.2 µmol m¯²s¯¹, and mature bacterial and algal-bacterial AGS were used for the operation of two identical sequencing batch reactors (SBRs) with a working volume of 0.9 L each, respectively. The results showed that salinity increase caused no apparent change in the color of bacterial AGS; while for algal-bacterial AGS, its color was progressively changed from green to dark green. A consequent increase in granule diameter and fluffiness was observed in the bacterial AGS reactor with the increase of salinity in comparison to a decrease in algal-bacterial AGS diameter. However, nitrite accumulation peaked from 1.0 mg/L and 0.4 mg/L at 1 g/L NaCl in the bacterial and algal-bacterial AGS systems, respectively to 9.8 mg/L in both systems when NaCl concentration varied from 5 g/L to 15 g/L. Almost no ammonia nitrogen was detected in the effluent except at 10 g/L NaCl concentration, where it averaged 4.2 mg/L and 2.4 mg/L, respectively, in the bacterial and algal-bacterial AGS systems. Nutrients removal in the algal-bacterial system was relatively higher than the bacterial AGS in terms of nitrogen and phosphorus removals. Nonetheless, the nutrient removal rate was almost 50% or lower. Results show that algal-bacterial AGS is more adaptable to salinity increase and could be more suitable for saline wastewater treatment. Optimization of operation conditions for algal-bacterial AGS system would be important to ensure its stably high efficiency in practice.

Keywords: algal-bacterial aerobic granular sludge, bacterial aerobic granular sludge, Nutrients removal, saline wastewater, sequencing batch reactor

Procedia PDF Downloads 148

Authors: Muhammad Ather Nadeem, Bilal Ahmad Khan, Hussam F. Najeeb Alawadi, Athar Mahmood, Aneela Nijabat, Tasawer Abbas, Muhammad Habib, Abdullah

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The global prevalence of Avena fatua infestation poses a significant challenge to wheat sustainability. While chemical control stands out as an efficient and rapid way to control weeds, concerns over developing resistance in weeds and environmental pollution have led to criticisms of herbicide use. Consequently, this study was designed to address these challenges through the chemical synthesis, characterization, and optimization of chitosan-based nanoparticles containing clodinofop Propargyl and fenoxaprop-P-ethyl for the effective management of A. fatua. Utilizing the ionic gelification technique, chitosan-based nanoparticles of clodinofop Propargyl and fenoxaprop-P-ethyl were prepared. These nanoparticles were applied at the 3-4 leaf stage of Phalaris minor weed, applying seven altered doses. These nanoparticles were applied at the 3-4 leaf stage of Phalaris minor weed, applying seven altered doses (D0 (Check weeds), D1 (Recommended dose of traditional-herbicide (TH), D2 (Recommended dose of Nano-herbicide (NPs-H)), D3 (NPs-H with 05-fold lower dose), D4 ((NPs-H) with 10-fold lower dose), D5 (NPs-H with 15-fold lower dose), and D6 (NPs-H with 20-fold lower dose)). Characterization of the chitosan-containing herbicide nanoparticles (CHT-NPs) was conducted using FT-IR analysis, demonstrating a perfect match with standard parameters. UV–visible spectrum further revealed absorption peaks at 310 nm for NPs of clodinofop propargyl and at 330 nm for NPs of fenoxaprop-p-ethyl. This research aims to contribute to sustainable weed management practices by addressing the challenges associated with chemical herbicide use. The application of chitosan-based nanoparticles (CHT-NPs) containing fenoxaprop-P-ethyl and clodinofop-propargyl at the recommended dose of the standard herbicide resulted in 100% mortality and visible injury to weeds. Surprisingly, when applied at a lower dose with 5-folds, these chitosan-containing nanoparticles of clodinofop Propargyl and fenoxaprop-P-ethyl demonstrated extreme control efficacy. Furthermore, at a 10-fold lower dose compared to standard herbicides and the recommended dose of clodinofop-propargyl and fenoxaprop-P-ethyl, the chitosan-based nanoparticles exhibited comparable effects on chlorophyll content, visual injury (%), mortality (%), plant height (cm), fresh weight (g), and dry weight (g) of A. fatua. This study indicates that chitosan/tripolyphosphate-loaded nanoparticles containing clodinofop-propargyl and fenoxaprop-P-ethyl can be effectively utilized for the management of A. fatua at a 10-fold lower dose, highlighting their potential for sustainable and efficient weed control.

Keywords: mortality, chitosan-based nanoparticles, visual injury, chlorophyl contents, 5-fold lower dose.

Procedia PDF Downloads 56

Authors: Olga Maksakova

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A work with unconscious patients after acute brain damages besides special knowledge and practical skills of all the participants requires a very specific organization. A lot of said about team approach in neurorehabilitation, usually as for outpatient mode. Rehabilitologists deal with fixed patient problems or deficits (motion, speech, cognitive or emotional disorder). Team-building means superficial paradigm of management psychology. Linear mode of teamwork fits casual relationships there. Cases with deep altered states of consciousness (vegetative states, coma, and confusion) require non-linear mode of teamwork: recovery of consciousness might not be the goal due to phenomenon uncertainty. Rehabilitation team as Semi-open Complex System includes the patient as a part. Patient's response pattern becomes formed not only with brain deficits but questions-stimuli, context, and inquiring person. Teamwork is sourcing of phenomenology knowledge of patient's processes as Third-person approach is replaced with Second- and after First-person approaches. Here is a chance for real-time change. Patient’s contacts with his own body and outward things create a basement for restoration of consciousness. The most important condition is systematic feedbacks to any minimal movement or vegetative signal of the patient. Up to now, recovery work with the most severe contingent is carried out in the mode of passive physical interventions, while an effective rehabilitation team should include specially trained psychologists and psychotherapists. It is they who are able to create a network of feedbacks with the patient and inter-professional ones building up the team. Characteristics of ‘Team-Patient’ system (TPS) are energy, entropy, and complexity. Impairment of consciousness as the absence of linear contact appears together with a loss of essential functions (low energy), vegetative-visceral fits (excessive energy and low order), motor agitation (excessive energy and excessive order), etc. Techniques of teamwork are different in these cases for resulting optimization of the system condition. Directed regulation of the system complexity is one of the recovery tools. Different signs of awareness appear as a result of system self-organization. Joint meetings are an important part of teamwork. Regular or event-related discussions form the language of inter-professional communication, as well as the patient's shared mental model. Analysis of complex communication process in TPS may be useful for creation of the general theory of consciousness.

Keywords: rehabilitation team, urgent rehabilitation, severe brain damage, consciousness disorders, complex system theory

Procedia PDF Downloads 147

Authors: Naser Zouri

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Purpose: Measures of formulate and implementation strategy shows amount of product rate-market based strategic management category such as courtesy, competence, and compliance to reach the high loyalty of financial ecosystem. Despite, it solves the market place error intention to fair trade organization. Finding: Finding shows the ability of executives’ level of management to motivate and better decision-making to solve the treatments in business organization. However, it made ideal level of each interposition policy for a hypothetical household. Methodology/design. Style of questionnaire about the data collection was selected to survey of both pilot test and real research. Also, divide of questionnaire and using of Free Scale Semiconductor`s between the finance employee was famous of this instrument. Respondent`s nominated basic on non-probability sampling such as convenience sampling to answer the questionnaire. The way of realization costs to performed the questionnaire divide among the respondent`s approximately was suitable as a spend the expenditure to reach the answer but very difficult to collect data from hospital. However, items of research survey was formed of implement strategy, environment, supply chain, employee from impact of implementation strategy on reach to better financial consequences and also formulate strategy, comprehensiveness strategic design, organization performance from impression on formulate strategy and financial consequences. Practical Implication: Dynamic capability approach of formulate and implement strategy focuses on the firm-specific processes through which firms integrate, build, or reconfigure resources valuable for making a theoretical contribution. Originality/ value of research: Going beyond the current discussion, we show that case studies have the potential to extend and refine theory. We present new light on how dynamic capabilities can benefit from case study research by discovering the qualifications that shape the development of capabilities and determining the boundary conditions of the dynamic capabilities approach. Limitation of the study :Present study also relies on survey of methodology for data collection and the response perhaps connection by financial employee was difficult to responds the question because of limitation work place.

Keywords: financial ecosystem, loyalty, Malaysian market error, dynamic capability approach, rate-market, optimization intelligence strategy, courtesy, competence, compliance

Procedia PDF Downloads 307

Authors: Suruchi Saini, Hitender Kumar Tyagi

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With the rapid progress of the nanotechnology industry, it is becoming increasingly important to have compact semiconductor devices to function and offer the best results at various technology nodes. While performing the scaling of the device, several short-channel effects occur. To minimize these scaling limitations, some device architectures have been developed in the semiconductor industry. FinFET is one of the most promising structures. Also, the double-gate 2D Fin field effect transistor has the benefit of suppressing short channel effects (SCE) and functioning well for less than 14 nm technology nodes. In the present research, the MuGFET simulation tool is used to analyze and explain the electrical behaviour of a double-gate 2D Fin field effect transistor. The drift-diffusion and Poisson equations are solved self-consistently. Various models, such as Fermi-Dirac distribution, bandgap narrowing, carrier scattering, and concentration-dependent mobility models, are used for device simulation. The transfer and output characteristics of the double-gate 2D Fin field effect transistor are determined at 10 nm technology node. The performance parameters are extracted in terms of threshold voltage, trans-conductance, leakage current and current on-off ratio. In this paper, the device performance is analyzed at different structure parameters. The utilization of the Id-Vg curve is a robust technique that holds significant importance in the modeling of transistors, circuit design, optimization of performance, and quality control in electronic devices and integrated circuits for comprehending field-effect transistors. The FinFET structure is optimized to increase the current on-off ratio and transconductance. Through this analysis, the impact of different channel widths, source and drain lengths on the Id-Vg and transconductance is examined. Device performance was affected by the difficulty of maintaining effective gate control over the channel at decreasing feature sizes. For every set of simulations, the device's features are simulated at two different drain voltages, 50 mV and 0.7 V. In low-power and precision applications, the off-state current is a significant factor to consider. Therefore, it is crucial to minimize the off-state current to maximize circuit performance and efficiency. The findings demonstrate that the performance of the current on-off ratio is maximum with the channel width of 3 nm for a gate length of 10 nm, but there is no significant effect of source and drain length on the current on-off ratio. The transconductance value plays a pivotal role in various electronic applications and should be considered carefully. In this research, it is also concluded that the transconductance value of 340 S/m is achieved with the fin width of 3 nm at a gate length of 10 nm and 2380 S/m for the source and drain extension length of 5 nm, respectively.

Keywords: current on-off ratio, FinFET, short-channel effects, transconductance

Procedia PDF Downloads 61

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

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

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

Procedia PDF Downloads 48

Authors: Thelma Maria Melo Pinheiro, Guilherme Raposo Diniz Vieira, Sidney Matos da Silva, Leonardo Mendonça de Oliveira Queiroz, Mateus Sousa Pinheiro, Danyllo Wenceslau de Oliveira Lopes

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The present article has the objective to describe the regulatory impact analysis (RIA) of the contracting efficiency of the Brazilian transmission system usage. This contracting is made by users connected to the main transmission network and is used to guide necessary investments to supply the electrical energy demand. Therefore, an inefficient contracting of this energy amount distorts the real need for grid capacity, affecting the sector planning accuracy and resources optimization. In order to provide this efficiency, the Brazilian Electricity Regulatory Agency (ANEEL) homologated the Normative Resolution (NR) No. 666, from July 23th of 2015, which consolidated the procedures for the contracting of transmission system usage and the contracting efficiency verification. Aiming for a more efficient and rational transmission system contracting, the resolution established economic incentives denominated as Inefficiency installment for excess (IIE) and inefficiency installment for over-contracting (IIOC). The first one, IIE, is verified when the contracted demand exceeds the established regulatory limit; it is applied to consumer units, generators, and distribution companies. The second one, IIOC, is verified when the distributors over-contract their demand. Thus, the establishment of the inefficiency installments IIE and IIOC intends to avoid the agent contract less energy than necessary or more than it is needed. Knowing that RIA evaluates a regulatory intervention to verify if its goals were achieved, the results from the application of the above-mentioned normative resolution to the Brazilian transmission sector were analyzed through indicators that were created for this RIA to evaluate the contracting efficiency transmission system usage, using real data from before and after the homologation of the normative resolution in 2015. For this, indicators were used as the efficiency contracting indicator (ECI), excess of demand indicator (EDI), and over-contracting of demand indicator (ODI). The results demonstrated, through the ECI analysis, a decrease of the contracting efficiency, a behaviour that was happening even before the normative resolution of 2015. On the other side, the EDI showed a considerable decrease in the amount of excess for the distributors and a small reduction for the generators; moreover, the ODI notable decreased, which optimizes the usage of the transmission installations. Hence, with the complete evaluation from the data and indicators, it was possible to conclude that IIE is a relevant incentive for a more efficient contracting, indicating to the agents that their contracting values are not adequate to keep their service provisions for their users. The IIOC also has its relevance, to the point that it shows to the distributors that their contracting values are overestimated.

Keywords: contracting, electricity regulation, evaluation, regulatory impact analysis, transmission power system

Procedia PDF Downloads 121

Authors: J. Van Engeland, C. Lavigne, S. De Jaeger

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In the light of the transition towards a more circular economy, recovery of products, parts or materials will gain in importance. Additionally, the EU proximity principle related to waste management and emissions generated by transporting large amounts of end-of-life products, shift attention to local recovery networks. The Flemish inter-communal cooperation for municipal solid waste management Meetjesland (IVM) is currently investigating the set-up of such a network. More specifically, the network encompasses the recycling of polyvinyl chloride (PVC), which is collected in separate containers. When these containers are full, a truck should transport them to the processor which can recycle the PVC into new products. This paper proposes a model to optimize the container collection. The containers are located at different Civic Amenity sites (CA sites) in a certain region. Since people can drop off their waste at these CA sites, the containers will gradually fill up during a planning horizon. If a certain container is full, it has to be collected and replaced by an empty container. The collected waste is then transported to a single processor. To perform this collection and transportation of containers, the responsible firm has a set of vehicles stationed at a single depot and different personnel crews. A vehicle can load exactly one container. If a trailer is attached to the vehicle, it can load an additional container. Each day of the planning horizon, the different crews and vehicles leave the depot to collect containers at the different sites. After loading one or two containers, the crew has to drive to the processor for unloading the waste and to pick up empty containers. Afterwards, the crew can again visit sites or it can return to the depot to end its collection work for that day. All along the collection process, the crew has to respect the opening hours of the sites. In order to allow for some flexibility, a crew is allowed to wait a certain amount of time at the gate of a site until it opens. The problem described can be modelled as a variant to the PVRP-TW (Periodic Vehicle Routing Problem with Time Windows). However, a vehicle can at maximum load two containers, hence only two subsequent site visits are possible. For that reason, we will refer to the model as a model for building tactical waste collection schemes. The goal is to a find a schedule describing which crew should visit which CA site on which day to minimize the number of trucks and the routing costs. The model was coded in IBM CPLEX Optimization studio and applied to a number of test instances. Good results were obtained, and specific suggestions concerning route and truck costs could be made. For a large range of input parameters, collection schemes using two trucks are obtained.

Keywords: container collection, crew scheduling, mixed integer linear programming, waste management

Procedia PDF Downloads 136

Authors: I. Berger, N. Machour, F. Portet-Koltalo

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Polycyclic aromatic hydrocarbons (PAHs) are toxic and carcinogenic pollutants produced in majority by incomplete combustion processes in industrialized and urbanized areas. After being emitted in atmosphere, these persistent contaminants are deposited to soils or sediments. Even if persistent, some can be partially degraded (photodegradation, biodegradation, chemical oxidation) and they lead to oxygenated metabolites (oxy-PAHs) which can be more toxic than their parent PAH. Oxy-PAHs are less measured than PAHs in sediments and this study aims to compare different analytical tools in order to extract and quantify a mixture of four hydroxylated PAHs (OH-PAHs) and four carbonyl PAHs (quinones) in sediments. Methodologies: Two analytical systems – HPLC with on-line UV and fluorescence detectors (HPLC-UV-FLD) and GC coupled to a mass spectrometer (GC-MS) – were compared to separate and quantify oxy-PAHs. Microwave assisted extraction (MAE) was optimized to extract oxy-PAHs from sediments. Results: First OH-PAHs and quinones were analyzed in HPLC with on-line UV and fluorimetric detectors. OH-PAHs were detected with the sensitive FLD, but the non-fluorescent quinones were detected with UV. The limits of detection (LOD)s obtained were in the range (2-3)×10-4 mg/L for OH-PAHs and (2-3)×10-3 mg/L for quinones. Second, even if GC-MS is not well adapted to the analysis of the thermodegradable OH-PAHs and quinones without any derivatization step, it was used because of the advantages of the detector in terms of identification and of GC in terms of efficiency. Without derivatization, only two of the four quinones were detected in the range 1-10 mg/L (LODs=0.3-1.2 mg/L) and LODs were neither very satisfying for the four OH-PAHs (0.18-0.6 mg/L). So two derivatization processes were optimized, comparing to literature: one for silylation of OH-PAHs, one for acetylation of quinones. Silylation using BSTFA/TCMS 99/1 was enhanced using a mixture of catalyst solvents (pyridine/ethyle acetate) and finding the appropriate reaction duration (5-60 minutes). Acetylation was optimized at different steps of the process, including the initial volume of compounds to derivatize, the added amounts of Zn (0.1-0.25 g), the nature of the derivatization product (acetic anhydride, heptafluorobutyric acid…) and the liquid/liquid extraction at the end of the process. After derivatization, LODs were decreased by a factor 3 for OH-PAHs and by a factor 4 for quinones, all the quinones being now detected. Thereafter, quinones and OH-PAHs were extracted from spiked sediments using microwave assisted extraction (MAE) followed by GC-MS analysis. Several mixtures of solvents of different volumes (10-25 mL) and using different extraction temperatures (80-120°C) were tested to obtain the best recovery yields. Satisfactory recoveries could be obtained for quinones (70-96%) and for OH-PAHs (70-104%). Temperature was a critical factor which had to be controlled to avoid oxy-PAHs degradation during the MAE extraction process. Conclusion: Even if MAE-GC-MS was satisfactory to analyze these oxy-PAHs, MAE optimization has to be carried on to obtain a most appropriate extraction solvent mixture, allowing a direct injection in the HPLC-UV-FLD system, which is more sensitive than GC-MS and does not necessitate a previous long derivatization step.

Keywords: derivatizations for GC-MS, microwave assisted extraction, on-line HPLC-UV-FLD, oxygenated PAHs, polluted sediments

Procedia PDF Downloads 287

Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

Procedia PDF Downloads 128

Authors: Nabil Al-Zaqri

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Semiconductor photocatalysts with surface defects display incredible light absorption bandwidth, and these defects function as highly active sites for oxidation processes by interacting with the surface band structure. Accordingly, engineering the photocatalyst with surface oxygen vacancies will enhance the semiconductor nanostructure's photocatalytic efficiency. Herein, a CeO2₋ₓ nanostructure is designed under the influence of low-frequency ultrasonic waves to create surface oxygen vacancies. This approach enhances the photocatalytic efficiency compared to many heterostructures while keeping the intrinsiccrystal structure intact. Ultrasonic waves induce the acoustic cavitation effect leading to the dissemination of active elements on the surface, which results in vacancy formation in conjunction with larger surface area and smaller particle size. The structural analysis of CeO₂₋ₓ revealed higher crystallinity, as well as morphological optimization, and the presence of oxygen vacancies is verified through Raman, X-rayphotoelectron spectroscopy, temperature-programmed reduction, photoluminescence, and electron spinresonance analyses. Oxygen vacancies accelerate the redox cycle between Ce₄+ and Ce₃+ by prolongingphotogenerated charge recombination. The ultrasound-treated pristine CeO₂ sample achieved excellenthydrogen production showing a quantum efficiency of 1.125% and efficient organic degradation. Ourpromising findings demonstrated that ultrasonic treatment causes the formation of surface oxygenvacancies and improves photocatalytic hydrogen evolution and pollution degradation. Conclusion: Defect engineering of the ceria nanoparticles with oxygen vacancies was achieved for the first time using low-frequency ultrasound treatment. The U-CeO₂₋ₓsample showed high crystallinity, and morphological changes were observed. Due to the acoustic cavitation effect, a larger surface area and small particle size were observed. The ultrasound treatment causes particle aggregation and surface defects leading to oxygen vacancy formation. The XPS, Raman spectroscopy, PL spectroscopy, and ESR results confirm the presence of oxygen vacancies. The ultrasound-treated sample was also examined for pollutant degradation, where 1O₂was found to be the major active species. Hence, the ultrasound treatment influences efficient photocatalysts for superior hydrogen evolution and an excellent photocatalytic degradation of contaminants. The prepared nanostructure showed excellent stability and recyclability. This work could pave the way for a unique post-synthesis strategy intended for efficient photocatalytic nanostructures.

Keywords: surface defect, CeO₂₋ₓ, photocatalytic, water treatment, H₂ production

Procedia PDF Downloads 141

Authors: Benjamin Blat Belmonte, Stephan Rinderknecht

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The transition to electric vehicles (EVs) stands at the forefront of innovative strategies designed to address environmental concerns and reduce fossil fuel dependency. As the number of EVs on the roads increases, so too does the potential for their integration into energy markets. This research dives deep into the transformative possibilities of using electric vehicle fleets, specifically electric bus fleets, not just as consumers but as active participants in the energy market. This paper investigates the feasibility and grid effects of electric vehicle fleet operators in the energy market. Our objective centers around a comprehensive exploration of the sector coupling domain, with an emphasis on the economic potential in both electricity and balancing markets. Methodologically, our approach combines data mining techniques with thorough pre-processing, pulling from a rich repository of electricity and balancing market data. Our findings are grounded in the actual operational realities of the bus fleet operator in Darmstadt, Germany. We employ a Mixed Integer Linear Programming (MILP) approach, with the bulk of the computations being processed on the High-Performance Computing (HPC) platform ‘Lichtenbergcluster’. Our findings underscore the compelling economic potential of EV fleets in the energy market. With electric buses becoming more prevalent, the considerable size of these fleets, paired with their substantial battery capacity, opens up new horizons for energy market participation. Notably, our research reveals that economic viability is not the sole advantage. Participating actively in the energy market also translates into pronounced positive effects on grid stabilization. Essentially, EV fleet operators can serve a dual purpose: facilitating transport while simultaneously playing an instrumental role in enhancing grid reliability and resilience. This research highlights the symbiotic relationship between the growth of EV fleets and the stabilization of the energy grid. Such systems could lead to both commercial and ecological advantages, reinforcing the value of electric bus fleets in the broader landscape of sustainable energy solutions. In conclusion, the electrification of transport offers more than just a means to reduce local greenhouse gas emissions. By positioning electric vehicle fleet operators as active participants in the energy market, there lies a powerful opportunity to drive forward the energy transition. This study serves as a testament to the synergistic potential of EV fleets in bolstering both economic viability and grid stabilization, signaling a promising trajectory for future sector coupling endeavors.

Keywords: electric vehicle fleet, sector coupling, optimization, electricity market, balancing market

Procedia PDF Downloads 76

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

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

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

Procedia PDF Downloads 161

Authors: Funda Erdem Şahnali, Ş. Özgür Atayılmaz, Tolga N. Aynur

Abstract:

Almost all of the domestic refrigerators operate on the principle of the vapor compression refrigeration cycle and removal of heat from the refrigerator cabinets is done via one of the two methods: natural convection or forced convection. In this study, airflow and temperature distributions inside a 375L no-frost type larder cabinet, in which cooling is provided by forced convection, are evaluated both experimentally and numerically. Airflow rate, compressor capacity and temperature distribution in the cooling chamber are known to be some of the most important factors that affect the cooling performance and energy consumption of a refrigerator. The objective of this study is to evaluate the original temperature distribution in the larder cabinet, and investigate for better temperature distribution solutions throughout the refrigerator domain via system optimizations that could provide uniform temperature distribution. The flow visualization and airflow velocity measurements inside the original refrigerator are performed via Stereoscopic Particle Image Velocimetry (SPIV). In addition, airflow and temperature distributions are investigated numerically with Ansys Fluent. In order to study the heat transfer inside the aforementioned refrigerator, forced convection theories covering the following cases are applied: closed rectangular cavity representing heat transfer inside the refrigerating compartment. The cavity volume has been represented with finite volume elements and is solved computationally with appropriate momentum and energy equations (Navier-Stokes equations). The 3D model is analyzed as transient, with k-ε turbulence model and SIMPLE pressure-velocity coupling for turbulent flow situation. The results obtained with the 3D numerical simulations are in quite good agreement with the experimental airflow measurements using the SPIV technique. After Computational Fluid Dynamics (CFD) analysis of the baseline case, the effects of three parameters: compressor capacity, fan rotational speed and type of shelf (glass or wire) are studied on the energy consumption; pull down time, temperature distributions in the cabinet. For each case, energy consumption based on experimental results is calculated. After the analysis, the main effective parameters for temperature distribution inside a cabin and energy consumption based on CFD simulation are determined and simulation results are supplied for Design of Experiments (DOE) as input data for optimization. The best configuration with minimum energy consumption that provides minimum temperature difference between the shelves inside the cabinet is determined.

Keywords: air distribution, CFD, DOE, energy consumption, experimental, larder cabinet, refrigeration, uniform temperature

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Authors: Vlad Andrei Raducanu, Mariana Lucia Angelescu, Ion Cinca, Vasile Danut Cojocaru, Doina Raducanu

Abstract:

By using smart digital tools, such as generative design (GD) and digital fabrication (DF), problems of high actuality concerning resources optimization (materials, energy, time) can be solved and applications or products of free-form type can be created. In the new digital technology materials are active, designed in response to a set of performance requirements, which impose a total rethinking of old material practices. The article presents the design procedure key steps of a free-form architectural object - a column type one with connections to get an adaptive 3D surface, by using the parametric design methodology and by exploiting the properties of conventional metallic materials. In parametric design the form of the created object or space is shaped by varying the parameters values and relationships between the forms are described by mathematical equations. Digital parametric design is based on specific procedures, as shape grammars, Lindenmayer - systems, cellular automata, genetic algorithms or swarm intelligence, each of these procedures having limitations which make them applicable only in certain cases. In the paper the design process stages and the shape grammar type algorithm are presented. The generative design process relies on two basic principles: the modeling principle and the generative principle. The generative method is based on a form finding process, by creating many 3D spatial forms, using an algorithm conceived in order to apply its generating logic onto different input geometry. Once the algorithm is realized, it can be applied repeatedly to generate the geometry for a number of different input surfaces. The generated configurations are then analyzed through a technical or aesthetic selection criterion and finally the optimal solution is selected. Endless range of generative capacity of codes and algorithms used in digital design offers various conceptual possibilities and optimal solutions for both technical and environmental increasing demands of building industry and architecture. Constructions or spaces generated by parametric design can be specifically tuned, in order to meet certain technical or aesthetical requirements. The proposed approach has direct applicability in sustainable architecture, offering important potential economic advantages, a flexible design (which can be changed until the end of the design process) and unique geometric models of high performance.

Keywords: parametric design, algorithmic procedures, free-form architectural object, sustainable architecture

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Authors: Mahamad Yousif, Eoin Cunningham, Beatrice Smyth

Abstract:

Every year ~6 million tonnes of feathers are produced globally. Due to feathers’ low density and possible contamination with pathogens, their disposal causes health and environmental problems. The extraction of keratin, which represents >90% of feathers’ dry weight, could offer a solution due to its wide range of applications in the food, medical, cosmetics, and biopolymer industries. One of these applications is the production of biofilms which can be used for packaging, edible films, drug delivery, wound healing etc. Several studies in the last two decades investigated keratin film production and its properties. However, the effects of many parameters on the properties of the films remain to be investigated including the extraction method, crosslinker type and concentration, and the film production method. These parameters were investigated in this study. Keratin was extracted from chicken feathers using two methods, alkaline extraction with 0.5 M NaOH at 80 °C or sulphitolysis extraction with 0.5 M sodium sulphite, 8 M urea, and 0.25-1 g sodium dodecyl sulphate (SDS) at 100 °C. The extracted keratin was mixed with different types and concentrations of plasticizers (glycerol and polyethylene glycol) and crosslinkers (formaldehyde (FA), glutaraldehyde, cinnamaldehyde, glyoxal, and 1,4-Butanediol diglycidyl ether (BDE)). The mixtures were either cast in a mould or compression moulded to produce films. For casting, keratin powder was initially dissolved in water to form a 5% keratin solution and the mixture was dried in an oven at 60 °C. For compression moulding, 10% water was added and the compression moulding temperature and pressure were in the range of 60-120 °C and 10-30 bar. Finally, the tensile properties, solubility, and transparency of the films were analysed. The films prepared using the sulphitolysis keratin had superior tensile properties to the alkaline keratin and formed successfully with lower plasticizer concentrations. Lowering the SDS concentration from 1 to 0.25 g/g feathers improved all the tensile properties. All the films prepared without crosslinkers were 100% water soluble but adding crosslinkers reduced solubility to as low as 21%. FA and BDE were found to be the best crosslinkers increasing the tensile strength and elongation at break of the films. Higher compression moulding temperature and pressure lowered the tensile properties of the films; therefore, 80 °C and 10 bar were considered to be the optimal compression moulding temperature and pressure. Nevertheless, the films prepared by casting had higher tensile properties than compression moulding but were less transparent. Two optimal films, prepared by film casting, were identified and their compositions were: (a) Sulphitolysis keratin, 20% glycerol, 10% FA, and 10% BDE. (b) Sulphitolysis keratin, 20% glycerol, and 10% BDE. Their tensile strength, elongation at break, Young’s modulus, solubility, and transparency were: (a) 4.275±0.467 MPa, 86.12±4.24%, 22.227±2.711 MPa, 21.34±1.11%, and 8.57±0.94* respectively. (b) 3.024±0.231 MPa, 113.65±14.61%, 10±1.948 MPa, 25.03±5.3%, and 4.8±0.15 respectively. A higher value indicates that the film is less transparent. The extraction method, film composition, and production method had significant influence on the properties of keratin films and should therefore be tailored to meet the desired properties and applications.

Keywords: compression moulding, crosslinker, film casting, keratin, plasticizer, solubility, tensile properties, transparency

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