Search results for: precision feed

Authors: Petros Gkotsis, Anastasios Zouboulis, Manasis Mitrakas, Dimitrios Zamboulis, E. Peleka

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The most serious drawback in wastewater treatment using membrane bioreactors (MBRs) is membrane fouling which gradually leads to membrane permeability decrease and efficiency deterioration. This work is part of a research project that aims to develop an integrated methodology for membrane fouling control, using specific chemicals which will enhance the coagulation and flocculation of compounds responsible for fouling, hence reducing biofilm formation on the membrane surface and limiting the fouling rate acting as a pre-treatment step. For this purpose, a pilot-scale plant with fully automatic operation achieved by means of programmable logic controller (PLC) has been constructed and tested. The experimental set-up consists of four units: wastewater feed unit, bioreactor, membrane (side-stream) filtration unit and permeate collection unit. Synthetic wastewater was fed as the substrate for the activated sludge. The dissolved oxygen (DO) concentration of the aerobic tank was maintained in the range of 2-3 mg/L during the entire operation by using an aerator below the membrane module. The membranes were operated at a flux of 18 LMH while membrane relaxation steps of 1 min were performed every 10 min. Both commercial and composite coagulants are added in different concentrations in the pilot-scale plant and their effect on the overall performance of the ΜΒR system is presented. Membrane fouling was assessed in terms of TMP, membrane permeability, sludge filterability tests, total resistance and the unified modified fouling index (UMFI). Preliminary tests showed that particular attention should be paid to the addition of the coagulant solution, indicating that pipe flocculation effectively increases hydraulic retention time and leads to voluminous sludge flocs. The most serious drawback in wastewater treatment using MBRs is membrane fouling, which gradually leads to membrane permeability decrease and efficiency deterioration. This results in increased treatment cost, due to high energy consumption and the need for frequent membrane cleaning and replacement. Due to the widespread application of MBR technology over the past few years, it becomes clear that the development of a methodology to mitigate membrane fouling is of paramount importance. The present work aims to develop an integrated technique for membrane fouling control in MBR systems and, thus, contribute to sustainable wastewater treatment.

Keywords: coagulation, membrane bioreactor, membrane fouling, pilot plant

Procedia PDF Downloads 303

Authors: G. Battistoni, F. Collamati, E. De Lucia, R. Faccini, C. Mancini-Terracciano, M. Marafini, I. Mattei, S. Muraro, V. Patera, A. Sarti, A. Sciubba, E. Solfaroli Camillocci, M. Toppi, G. Traini, S. M. Valle, C. Voena

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Accelerated charged particles, mainly protons and carbon ions, are presently used in Particle Therapy (PT) to treat solid tumors. The precision of PT exploiting the charged particle high localized dose deposition in tissues and biological effectiveness in killing cancer cells demands for an online dose monitoring technique, crucial to improve the quality assurance of treatments: possible patient mis-positionings and biological changes with respect to the CT scan could negatively affect the therapy outcome. In PT the beam range confined in the irradiated target can be monitored thanks to the secondary radiation produced by the interaction of the projectiles with the patient tissue. The Dose Profiler (DP) is a novel device designed to track charged secondary particles and reconstruct their longitudinal emission distribution, correlated to the Bragg peak position. The feasibility of this approach has been demonstrated by dedicated experimental measurements. The DP has been developed in the framework of the INSIDE project, MIUR, INFN and Centro Fermi, Museo Storico della Fisica e Centro Studi e Ricerche 'E. Fermi', Roma, Italy and will be tested at the Proton Therapy center of Trento (Italy) within the end of 2017. The DP combines a tracker, made of six layers of two-view scintillating fibers with square cross section (0.5 x 0.5 mm2) with two layers of two-view scintillating bars (section 12.0 x 0.6 mm2). The electronic readout is performed by silicon photomultipliers. The sensitive area of the tracking planes is 20 x 20 cm2. To optimize the detector layout, a Monte Carlo (MC) simulation based on the FLUKA code has been developed. The complete DP geometry and the track reconstruction code have been fully implemented in the MC. In this contribution, the DP hardware will be described. The expected detector performance computed using a dedicated simulation of a 220 MeV/u carbon ion beam impinging on a PMMA target will be presented, and the result will be discussed in the standard clinical application framework. A possible procedure for real-time beam range monitoring is proposed, following the expectations in actual clinical operation.

Keywords: online range monitoring, particle therapy, quality assurance, tracking detector

Procedia PDF Downloads 237

Authors: Hany Elsaid Fawaz Abdallah

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This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

Procedia PDF Downloads 84

Authors: Hendrick Maxil Zárate Rocha, Ricardo da Silva Pereira, Manoel Fernandes Martins Nogueira, Carlos R. Pereira Belchior, Maria Emilia de Lima Tostes

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This study investigates experimentally the effects of hydrogen addition in the intake manifold of a diesel generator operating with a 7% biodiesel-diesel oil blend (B7). An experimental apparatus setup was used to conduct performance and emissions tests in a single cylinder, air cooled diesel engine. This setup consisted of a generator set connected to a wirewound resistor load bank that was used to vary engine load. In addition, a flowmeter was used to determine hydrogen volumetric flowrate and a digital anemometer coupled with an air box to measure air flowrate. Furthermore, a digital precision electronic scale was used to measure engine fuel consumption and a gas analyzer was used to determine exhaust gas composition and exhaust gas temperature. A thermopar was installed near the exhaust collection to measure cylinder temperature. In-cylinder pressure was measured using an AVL Indumicro data acquisition system with a piezoelectric pressure sensor. An AVL optical encoder was installed in the crankshaft and synchronized with in-cylinder pressure in real time. The experimental procedure consisted of injecting hydrogen into the engine intake manifold at different mass concentrations of 2,6,8 and 10% of total fuel mass (B7 + hydrogen), which represented energy fractions of 5,15, 20 and 24% of total fuel energy respectively. Due to hydrogen addition, the total amount of fuel energy introduced increased and the generators fuel injection governor prevented any increases of engine speed. Several conclusions can be stated from the test results. A reduction in specific fuel consumption as a function of hydrogen concentration increase was noted. Likewise, carbon dioxide emissions (CO2), carbon monoxide (CO) and unburned hydrocarbons (HC) decreased as hydrogen concentration increased. On the other hand, nitrogen oxides emissions (NOx) increased due to average temperatures inside the cylinder being higher. There was also an increase in peak cylinder pressure and heat release rate inside the cylinder, since the fuel ignition delay was smaller due to hydrogen content increase. All this indicates that hydrogen promotes faster combustion and higher heat release rates and can be an important additive to all kind of fuels used in diesel generators.

Keywords: diesel engine, hydrogen, dual fuel, combustion analysis, performance, emissions

Procedia PDF Downloads 347

Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

Procedia PDF Downloads 168

Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

Procedia PDF Downloads 183

Authors: Nayeli Camacho, Fernanda Lara-Perez, Carolina Ortega-Portilla, Diego G. Espinosa-Arbelaez, Juan M. Alvarado-Orozco, Guillermo C. Mondragon-Rodriguez

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Ultra-high molecular weight polyethylene (UHMWPE) has been the gold standard material for total knee replacements for almost five decades. Wear damage to UHMWPE articulating surface is inevitable due to the natural sliding and rolling movements of the knee. This generates a considerable amount of wear debris, which results in mechanical instability of the joint, reduces joint mobility, increases pain with detrimental biologic responses, and causes component loosening. The presence of wear particles has been closely related to adverse reactions in the knee joint surrounding tissue, especially for particles in the range of 0.3 to 2 μm. Carbon-based materials possess excellent mechanical properties and have shown great promise in tribological applications. In this study, diamond-like carbon coatings (DLC) and carbon nanotubes (CNTs) were used to decrease the wear rate of ultra-high molecular weight polyethylene. A titanium doped DLC (Ti-DLC) was deposited by magnetron sputtering on stainless steel precision spheres while CNTs were used as a second phase reinforcement in UHMWPE at a concentration of 1.25 wt.%. A comparative tribological analysis of the wear of UHMWPE and UHMWPE-CNTs with a stainless steel counterpart with and without Ti-DLC coating is presented. The experimental wear testing was performed on a pin-on-disc tribometer under dry conditions, using a reciprocating movement with a load of 1 N at a frequency of 2 Hz for 100,000 and 200,000 cycles. The wear tracks were analyzed with high-resolution scanning electron microscopy to determine wear modes and observe the size and shape of the wear debris. Furthermore, profilometry was used to study the depth of the wear tracks and to map the wear of the articulating surface. The wear tracks at 100,000 and 200,000 cycles on all samples were relatively shallow, and they were in the range of average roughness. It was observed that the Ti-DLC coating decreases the mass loss in the UHMWPE and the depth of the wear track. The combination of both carbon-based materials decreased the material loss compared to the system of stainless steel and UHMWPE. Burnishing of the surface was the predominant wear mode observed with all the systems, more subtle for the systems with Ti-DLC coatings. Meanwhile, in the system composed of stainless steel-UHMWPE, the intrinsic surface roughness of the material was completely replaced by the wear tracks.

Keywords: CNT reinforcement, self-lubricating materials, Ti-DLC, UHMWPE tribological performance

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Authors: Surinder Pal, Ajay Gupta, Johny Khajuria

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Casting simulation helps visualize mold filling and casting solidification; predict related defects like cold shut, shrinkage porosity and hard spots; and optimize the casting design to achieve the desired quality with high yield. Flow and solidification of molten metals are, however, a very complex phenomenon that is difficult to simulate correctly by conventional computational techniques, especially when the part geometry is intricate and the required inputs (like thermo-physical properties and heat transfer coefficients) are not available. Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mockup of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome. The all casting simulation software has own requirements, like magma cast has only best for crack simulation. The latest generation software Auto CAST developed at IIT Bombay provides a host of functions to support method engineers, including part thickness visualization, core design, multi-cavity mold design with common gating and feeding, application of various feed aids (feeder sleeves, chills, padding, etc.), simulation of mold filling and casting solidification, automatic optimization of feeders and gating driven by the desired quality level, and what-if cost analysis. IIT Bombay has developed a set of applications for the foundry industry to improve casting yield and quality. Casting simulation is a fast and efficient solution for process for advanced tool which is the result of more than 20 years of collaboration with major industrial partners and academic institutions around the world. In this paper the process of casting simulation is studied.

Keywords: casting simulation software’s, simulation technique’s, casting simulation, processes

Procedia PDF Downloads 474

Authors: Oğuz Taşbozan, Celal Erbaş, Şefik Surhan Tabakoğlu, Mahmut Ali Gökçe

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Polyunsaturated fatty acids (PUFAs) and particularly the levels and ratios of ω-3 and ω-6 fatty acids are important for biological functions in humans and recognized as essential components of human diet. According to the terms of many different points of view, the nutritional composition of fish in culture conditions and caught from wild are wondered by the consumers. Therefore the aim of this study was to investigate the chemical composition of cage-cultured and wild sharpsnout seabream which has been preferred by the consumers as an economical important fish species in Turkey. The fish were caught from wild and obtained from cage-cultured commercial companies. Eight fish were obtained for each group, and their average weights of the samples were 245.8±13.5 g for cultured, 149.4±13.3 g for wild samples. All samples were stored in freezer (-18 °C) and analyses were carried out in triplicates, using homogenized boneless fish fillets. Proximate compositions (protein, ash, moisture and lipid) were determined. The fatty acid composition was analyzed by a GC Clarous 500 with auto sampler (Perkin–Elmer, USA). Proximate compositions of cage-cultured and wild samples of sharpsnout seabream were found statistical differences in terms of proximate composition between the groups. The saturated fatty acid (SFA), monounsaturated fatty acid (MUFA) and PUFA amounts of cultured and wild sharpsnout seabream were significantly different. ω3/ω6 ratio was higher in the cultured group. Especially in protein level and lipid level of cultured samples was significantly higher than wild counterparts. One of the reasons for this, cultured species exposed to continuous feeding. This situation had a direct effect on their body lipid content. The fatty acid composition of fish differs depending on a variety of factors including species, diet, environmental factors and whether they are farmed or wild. The higher levels of MUFA in the cultured fish may be explained with the high content of monoenoic fatty acids in the feed of cultured fish as in some other species. The ω3/ω6 ratio is a good index for comparing the relative nutritional value of fish oils. In our study, the cultured sharpsnout seabream appears to be better nutritious in terms of ω3/ω6. Acknowledgement: This work was supported by the Scientific Research Project Unit of the University of Cukurova, Turkey under grant no FBA-2016-5780.

Keywords: Diplodus puntazo, cage cultured, PUFA, fatty acid

Procedia PDF Downloads 261

Authors: Prince Vivek, Vijay Kumar Bharti, Deepak Kumar, Rohit Kumar, Kapil Nehra, Dhananjay Singh, Om Prakash Chaurasia, Bhuvnesh Kumar

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High altitude native people still rely heavily on animal transport for logistic support at eastern and northern Himalayas regions. The prevalent mountainous terrains and rugged region are not suitable for the motorized vehicle to use in logistic transport. Therefore, people required high endurance pack animals for load carrying and riding. So far to the best of our knowledge, no studies have been taken to evaluate the effect of loads on the physiology of ponies in high altitude region. So, in this view, we evaluated variation in physiological, hematological, biochemical, and cytokines indices of Zanskar ponies during load carrying at high altitude. Total twelve (12) of Zanskar ponies, mare, age 4-6 years selected for this study, Feed was offered at 2% of body weight, and water ad libitum. Ponies were divided into three groups; group-A (without load), group-B (60 kg), and group-C (80 kg) of backpack loads. The track was very narrow and slippery with gravel, uneven with a rocky surface and has a steep gradient of 4 km uphill at altitude 3291 to 3500m. When we evaluate these parameters, it is understood that the heart rate, pulse rate, and respiration rate was significantly increased in 80 kg group among the three groups. The hematology parameters viz. hemoglobin significantly increased in 80 kg group on 1st day after load carrying among the three groups which was followed by control and 60 kg whereas, PCV, lymphocytes, monocytes percentage significantly increased however, ESR and eosinophil % significantly decreased in 80 kg group after load carrying on 7th day after load carrying among the three groups which were followed by control and 60 kg group. In biochemical parameters viz. LA, LDH, TP, hexokinase (HK), cortisol (CORT), T3, GPx, FRAP and IL-6 significantly increased in 80 kg group on the 7th day after load carrying among the three groups which were followed by control and 60 kg group. The ALT, ALB, GLB, UR, and UA significantly increased in 80 kg group on the 7th day before and after load carrying among the three groups which were followed by control and 60 kg group. The CRT, AST, and CK-MB were significantly increased in 80 kg group on the 1st and 7th day after load carrying among the three groups which were followed by control and 60 kg group. It has been concluded that, heart rate, respiration rate, hematological indices like PCV, lymphocytes, monocytes, Hb and ESR, biochemical indices like lactic acid, LDH, TP, HK, CORT, T3, ALT, AST and CRT, ALB, GLB, UR, UA, GPx, FRAP and IL-6 are important biomarkers to assess effect of load on animal physiology and endurance. Further, this result has revealed the strong correlation of change in biomarkers level with performance in ponies during load carry. Hence, these parameters might be used for the performance of endurance of Zanskar ponies in the high mountain region.

Keywords: biochemical, endurance, high altitude, load, ponies

Procedia PDF Downloads 277

Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

Procedia PDF Downloads 37

Authors: Alexandra C. Blaga, Dan Caşcaval, Alexandra Tucaliuc, Madalina Poştaru, Anca I. Galaction

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Amino acids are valuable chemical products used in in human foods, in animal feed additives and in the pharmaceutical field. Recently, there has been a noticeable rise of amino acids utilization throughout the world to include their use as raw materials in the production of various industrial chemicals: oil gelating agents (amino acid-based surfactants) to recover effluent oil in seas and rivers and poly(amino acids), which are attracting attention for biodegradable plastics manufacture. The amino acids can be obtained by biosynthesis or from protein hydrolysis, but their separation from the obtained mixtures can be challenging. In the last decades there has been a continuous interest in developing processes that will improve the selectivity and yield of downstream processing steps. The liquid-liquid extraction of amino acids (dissociated at any pH-value of the aqueous solutions) is possible only by using the reactive extraction technique, mainly with extractants of organophosphoric acid derivatives, high molecular weight amines and crown-ethers. The purpose of this study was to analyse the separation of nine amino acids of acidic character (l-aspartic acid, l-glutamic acid), basic character (l-histidine, l-lysine, l-arginine) and neutral character (l-glycine, l-tryptophan, l-cysteine, l-alanine) by reactive extraction with di-(2-ethylhexyl)phosphoric acid (D2EHPA) dissolved in butyl acetate. The results showed that the separation yield is controlled by the pH value of the aqueous phase: the reactive extraction of amino acids with D2EHPA is possible only if the amino acids exist in aqueous solution in their cationic forms (pH of aqueous phase below the isoeletric point). The studies for individual amino acids indicated the possibility of selectively separate different groups of amino acids with similar acidic properties as a function of aqueous solution pH-value: the maximum yields are reached for a pH domain of 2–3, then strongly decreasing with the pH increase. Thus, for acidic and neutral amino acids, the extraction becomes impossible at the isolelectric point (pHi) and for basic amino acids at a pH value lower than pHi, as a result of the carboxylic group dissociation. From the results obtained for the separation from the mixture of the nine amino acids, at different pH, it can be observed that all amino acids are extracted with different yields, for a pH domain of 1.5–3. Over this interval, the extract contains only the amino acids with neutral and basic character. For pH 5–6, only the neutral amino acids are extracted and for pH > 6 the extraction becomes impossible. Using this technique, the total separation of the following amino acids groups has been performed: neutral amino acids at pH 5–5.5, basic amino acids and l-cysteine at pH 4–4.5, l-histidine at pH 3–3.5 and acidic amino acids at pH 2–2.5.

Keywords: amino acids, di-(2-ethylhexyl) phosphoric acid, reactive extraction, selective extraction

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Authors: Prudhvinath Reddy Ankireddy, Narasimha Mangadoddy

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Spiral concentrators are commonly used in various industries, including mineral and coal processing, to efficiently separate materials based on their density and size. In these concentrators, a mixture of solid particles and fluid (usually water) is introduced as feed at the top of a spiral channel. As the mixture flows down the spiral, centrifugal and gravitational forces act on the particles, causing them to stratify based on their density and size. Spiral flows exhibit complex fluid dynamics, and interactions involve multiple phases and components in the process. Understanding the behavior of these phases within the spiral concentrator is crucial for achieving efficient separation. An experimental bi-component particle interaction study is conducted in this work utilizing magnetite (heavier density) and silica (lighter density) with different proportions processed in the spiral concentrator. The observation separation reveals that denser particles accumulate towards the inner region of the spiral trough, while a significant concentration of lighter particles are found close to the outer edge. The 5th turn of the spiral trough is partitioned into five zones to achieve a comprehensive distribution analysis of bicomponent particle segregation. Samples are then gathered from these individual streams using an in-house sample collector, and subsequent analysis is conducted to assess component segregation. Along the trough, there was a decline in the concentration of coarser particles, accompanied by an increase in the concentration of lighter particles. The segregation pattern indicates that the heavier coarse component accumulates in the inner zone, whereas the lighter fine component collects in the outer zone. The middle zone primarily consists of heavier fine particles and lighter coarse particles. The zone-wise results reveal that there is a significant fraction of segregation occurs in inner and middle zones. Finer magnetite and silica particles predominantly accumulate in outer zones with the smallest fraction of segregation. Additionally, numerical simulations are also carried out using the computational fluid dynamics (CFD) model based on the volume of fluid (VOF) approach incorporating the RSM turbulence model. The discrete phase model (DPM) is employed for particle tracking, thereby understanding the particle segregation of magnetite and silica along the spiral trough.

Keywords: spiral concentrator, bi-component particle segregation, computational fluid dynamics, discrete phase model

Procedia PDF Downloads 62

Authors: Lubna M. Al-Otaibi

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Mucocele is a common benign neoplasm of the oral cavity and the most common after fibroma. The lesion develops as a result of retention or extravasation of mucous material from minor salivary glands. Extravasation type of mucocele results from trauma and mostly occurs in the lower lip of young patients. The various treatment options available for the treatment of mucocele are associated with a relatively high incidence of recurrence making surgical intervention necessary for a permanent cure. The conventional surgical procedure, however, arouses apprehension in the patient and is associated with bleeding and postoperative pain. Recently, treatment of mucocele with lasers has become a viable treatment option. Various types of lasers are being used and are preferable over the conventional surgical procedure as they provide good hemostasis, reduced postoperative swelling and pain, reduced bacterial population, lesser need for suturing, faster healing and low recurrence rates. Er,Cr:YSGG is a solid-state laser with great affinity to water molecule. Its hydrokinetic cutting action allows it to work effectively on hydrated tissues without any thermal damage. However, up to date, only a few studies have reported its use in the removal of lip mucocele, especially in children. In this case, a 6 year old female patient with history of trauma to the lower lip presented with a soft, sessile, whitish-bluish 4 mm papule. The lesion was present for approximately four months and was fluctuant in size. The child developed a habit of biting the lesion causing injury, bleeding and discomfort. Surgical excision under local anaesthesia was performed using 2780 nm Er,Cr:YSGG Laser (WaterLase iPlus, Irvine, CA) with a Gold handpiece and MZ6 tip (3.5w, 50 Hz, 20% H2O, 20% Air, S mode). The tip was first applied in contact mode with focused beam using the Circumferential Incision Technique (CIT) to excise the tissue followed by the removal of the underlying causative minor salivary gland. Bleeding was stopped using Laser Dry Bandage setting (0.5w, 50 Hz, 1% H2O, 20% Air, S mode) and no suturing was needed. Safety goggles were worn and high-speed suction was used for smoke evacuation. Mucocele excision using 2780 nm Er,Cr:YSGG laser was rapid, easy to perform with excellent precision and allowed for histopathological examination of the excised tissue. The patient was comfortable and there were minimum bleeding and no sutures, postoperative pain, scarring or recurrence. Laser assisted mucocele excision appears to have efficient and reliable benefits in young patients and should be considered as an alternative to conventional surgical and non-surgical techniques.

Keywords: Erbium, excision, laser, lip, mucocele

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Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

Procedia PDF Downloads 120

Authors: Jose A. Diaz-Olivares, Nafise Mahdavian, Farhad Abtahi, Kaj Lindecrantz, Abdelakram Hafid, Fernando Seoane

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Despite new recommendations and guidelines for the evaluation of occupational risk assessments and their prevention, work-related musculoskeletal disorders are still one of the biggest causes of work activity disruption, productivity loss, sick leave and chronic work disability. It affects millions of workers throughout Europe, with a large-scale economic and social burden. These specific efforts have failed to produce significant results yet, probably due to the limited availability and high costs of occupational risk assessment at work, especially when the methods are complex, consume excessive resources or depend on self-evaluations and observations of poor accuracy. To overcome these limitations, a pervasive system of risk assessment tools in real time has been developed, which has the characteristics of a systematic approach, with good precision, usability and resource efficiency, essential to facilitate the prevention of musculoskeletal disorders in the long term. The system allows the combination of different wearable sensors, placed on different limbs, to be used for data collection and evaluation by a software solution, according to the needs and requirements in each individual working environment. This is done in a non-disruptive manner for both the occupational health expert and the workers. The creation of this solution allows us to attend different research activities that require, as an essential starting point, the recording of data with ergonomic value of very diverse origin, especially in real work environments. The software platform is here presented with a complimentary smart clothing system for data acquisition, comprised of a T-shirt containing inertial measurement units (IMU), a vest sensorized with textile electronics, a wireless electrocardiogram (ECG) and thoracic electrical bio-impedance (TEB) recorder and a glove sensorized with variable resistors, dependent on the angular position of the wrist. The collected data is processed in real-time through a mobile application software solution, implemented in commercially available Android-based smartphones and tablet platforms. Based on the collection of this information and its analysis, real-time risk assessment and feedback about postural improvement is possible, adapted to different contexts. The result is a tool which provides added value to ergonomists and occupational health agents, as in situ analysis of postural behavior can assist in a quantitative manner in the evaluation of work techniques and the occupational environment.

Keywords: ergonomics, mobile technologies, risk assessment, smart textiles

Procedia PDF Downloads 115

Authors: Abdul Haq

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The goal of this research is to better understand how wind loads affect bridges and develop strategies for designing bridges that are more stable and resistant to wind. The effect of wind on bridges is essential to their safety and functionality, especially in areas that are prone to high wind speeds or violent wind conditions. The study looks at the aerodynamic forces and vibrations caused by wind and how they affect bridge construction. Part of the research method involves first understanding the underlying ideas influencing wind flow near bridges. Computational fluid dynamics (CFD) simulations are used to model and forecast the aerodynamic behaviour of bridges under different wind conditions. These models incorporate several factors, such as wind directionality, wind speed, turbulence intensity, and the influence of nearby structures or topography. The results provide significant new insights into the loads and pressures that wind places on different bridge elements, such as decks, pylons, and connections. Following the determination of the wind loads, the structural response of bridges is assessed. By simulating their dynamic behavior under wind-induced forces, Finite Element Analysis (FEA) is used to model the bridge's component parts. This work contributes to the understanding of which areas are at risk of experiencing excessive stresses, vibrations, or oscillations due to wind excitations. Because the bridge has inherent modes and frequencies, the study considers both static and dynamic responses. Various strategies are examined to maximize the design of bridges to withstand wind. It is possible to alter the bridge's geometry, add aerodynamic components, add dampers or tuned mass dampers to lessen vibrations, and boost structural rigidity. Through an analysis of several design modifications and their effectiveness, the study aims to offer guidelines and recommendations for wind-resistant bridge design. In addition to the numerical simulations and analyses, there are experimental studies. In order to assess the computational models and validate the practicality of proposed design strategies, scaled bridge models are tested in a wind tunnel. These investigations help to improve numerical models and prediction precision by providing valuable information on wind-induced forces, pressures, and flow patterns. Using a combination of numerical models, actual testing, and long-term performance evaluation, the project aims to offer practical insights and recommendations for building wind-resistant bridges that are secure, long-lasting, and comfortable for users.

Keywords: wind effects, aerodynamic forces, computational fluid dynamics, finite element analysis

Procedia PDF Downloads 61

Authors: Michal Brazda, Miroslav Urbanek, Martina Koukolikova

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This work focuses on the development of functional surfaces and edges for cutting and forming tools created through the Directed Energy Deposition (DED) technology. In the context of growing challenges in modern engineering, additive technologies, especially DED, present an innovative approach to manufacturing tools for forming and cutting. One of the key features of DED is its ability to precisely and efficiently deposit Fully dense metals from powder feedstock, enabling the creation of complex geometries and optimized designs. Gradually, it becomes an increasingly attractive choice for tool production due to its ability to achieve high precision while simultaneously minimizing waste and material costs. Tools created using DED technology gain significant durability through the utilization of high-performance materials such as nickel alloys and tool steels. For high-temperature applications, Nimonic 80A alloy is applied, while for cold applications, M2 tool steel is used. The addition of ceramic materials, such as tungsten carbide, can significantly increase the tool's resistance. The introduction of functionally graded materials is a significant contribution, opening up new possibilities for gradual changes in the mechanical properties of the tool and optimizing its performance in different sections according to specific requirements. In this work, you will find an overview of individual applications and their utilization in the industry. Microstructural analyses have been conducted, providing detailed insights into the structure of individual components alongside examinations of the mechanical properties and tool life. These analyses offer a deeper understanding of the efficiency and reliability of the created tools, which is a key element for successful development in the field of cutting and forming tools. The production of functional surfaces and edges using DED technology can result in financial savings, as the entire tool doesn't have to be manufactured from expensive special alloys. The tool can be made from common steel, onto which a functional surface from special materials can be applied. Additionally, it allows for tool repairs after wear and tear, eliminating the need for producing a new part and contributing to an overall cost while reducing the environmental footprint. Overall, the combination of DED technology, functionally graded materials, and verified technologies collectively set a new standard for innovative and efficient development of cutting and forming tools in the modern industrial environment.

Keywords: additive manufacturing, directed energy deposition, DED, laser, cutting tools, forming tools, steel, nickel alloy

Procedia PDF Downloads 44

Authors: Mohammad Ali Al Qatawneh, Bespalchuk Pavel Ivanovich

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Computer navigation has been introduced in total knee arthroplasty to improve the accuracy of the procedure. Computer navigation improves the accuracy of bone resection in the coronal and sagittal planes. It was also noted that it normalizes the rotational alignment of the femoral component and fully assesses and balances the deformation of soft tissues in the coronal plane. The work is devoted to the advantages of using computer navigation technology in total knee arthroplasty in 62 patients (11 men and 51 women) suffering from gonarthrosis, aged 51 to 83 years, operated using a computer navigation system, followed up to 3 years from the moment of surgery. During the examination, the deformity variant was determined, and radiometric parameters of the knee joints were measured using the Knee Society Score (KSS), Functional Knee Society Score (FKSS), and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) scales. Also, functional stress tests were performed to assess the stability of the knee joint in the frontal plane and functional indicators of the range of motion. After surgery, improvement was observed in all scales; firstly, the WOMAC values decreased by 5.90 times, and the median value to 11 points (p < 0.001), secondly KSS increased by 3.91 times and reached 86 points (p < 0.001), and the third one is that FKSS data increased by 2.08 times and reached 94 points (p < 0.001). After TKA, the axis deviation of the lower limbs of more than 3 degrees was observed in 4 patients at 6.5% and frontal instability of the knee joint just in 2 cases at 3.2%., The lower incidence of sagittal instability of the knee joint after the operation was 9.6%. The range of motion increased by 1.25 times; the volume of movement averaged 125 degrees (p < 0.001). Computer navigation increases the accuracy of the spatial orientation of the endoprosthesis components in all planes, reduces the variability of the axis of the lower limbs within ± 3 °, allows you to achieve the best results of surgical interventions, and can be used to solve most basic tasks, allowing you to achieve excellent and good outcomes of operations in 100% of cases according to the WOMAC scale. With diaphyseal deformities of the femur and/or tibia, as well as with obstruction of their medullary canal, the use of computer navigation is the method of choice. The use of computer navigation prevents the occurrence of flexion contracture and hyperextension of the knee joint during the distal sawing of the femur. Using the navigation system achieves high-precision implantation for the endoprosthesis; in addition, it achieves an adequate balance of the ligaments, which contributes to the stability of the joint, reduces pain, and allows for the achievement of a good functional result of the treatment.

Keywords: knee joint, arthroplasty, computer navigation, advantages

Procedia PDF Downloads 86

Authors: Muhammad Farhan Saeed, Waheed Aslam Khan, Muhammad Nadeem, Iftikhar Ahmad, Zakir Ali

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Milk is an important and fundamental nutrition source of human diet. In Pakistan, the milk used by the consumer is of low quality and is often contaminated due to the lack of quality controls. Mycotoxins produced from molds which contaminate the agriculture commodities of animal feed. Mycotoxins are poisons which affect the animals when they consume contaminated feeds. Aflatoxin AFM1 is naturally occurring form of mycotoxins in milk which is carcinogenic. To assess public awareness regarding milk Aflatoxin contamination, a population-based survey using a questionnaire was carried out from general public and from farmers of both rural and urban areas. It was revealed from the data that people of rural area were more satisfied about quality of available milk but the awareness level about milk contamination was found lower in both areas. Total 297 samples of milk were collected from rural (n=156) and urban (n=141) areas of district Vehari during June-July 2015. Milk samples were collected from three different point sources; farmer, milkman and milkshop. These point sources had three types of dairy milk including cow milk, buffalo milk and mixed milk. After performing ELISA test 18 samples with positive ELISA results were maintain per source for further analysis for aflatoxin M1 (AFM1) by High Performance Liquid Chromatography (HPLC). Higher percentages of samples were found exceeding the permissible limit for urban area. In rural area about 15% samples and from urban area about 35% samples were exceeded the permissible limit of AFM1 with 0.05µg/kg set by European Union. From urban areas about 55% of buffalo, 33% of cows and 17% of mixed milk samples were exceeded the permissible AFM1 level as compared with 17%, 11% and 17% for milk samples from rural areas respectively. Samples from urban areas 33%, 44% and 28% were exceeded the permissible AFM1 level for farmer, milkman and of milk shop respectively as compared with 28% and 17% of farmer and milkman’s samples from rural areas respectively. The presence of AFM1 in milk samples demands the implementation of strict regulations and also urges the need for continuous monitoring of milk and milk products in order to minimize the health hazards. Regulations regarding aflatoxins contamination and adulteration should be strictly imposed to prevent health problems related to milk quality. Permissible limits for aflatoxin should be enforced strongly in Pakistan so that economic loss due to aflatoxin contamination can be reduced.

Keywords: Vehari, aflatoxins AFM1, milk, HPLC

Procedia PDF Downloads 365

Authors: Ming-Hsiang Shih, Wen-Pei Sung, Shih-Heng Tung

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Semi-active control system for structure under excitation of earthquake provides with the characteristics of being adaptable and requiring low energy. DSHD (Displacement Semi-Active Hydraulic Damper) was developed by our research team. Shake table test results of this DSHD installed in full scale test structure demonstrated that this device brought its energy-dissipating performance into full play for test structure under excitation of earthquake. The objective of this research is to develop a new AIC (Active Interaction Control Device) and apply shake table test to perform its dissipation of energy capability. This new proposed AIC is converting an improved DSHD (Displacement Semi-Active Hydraulic Damper) to AIC with the addition of an accumulator. The main concept of this energy-dissipating AIC is to apply the interaction function of affiliated structure (sub-structure) and protected structure (main structure) to transfer the input seismic force into sub-structure to reduce the structural deformation of main structure. This concept is tested using full-scale multi-degree of freedoms test structure, installed with this proposed AIC subjected to external forces of various magnitudes, for examining the shock absorption influence of predictive control, stiffness of sub-structure, synchronous control, non-synchronous control and insufficient control position. The test results confirm: (1) this developed device is capable of diminishing the structural displacement and acceleration response effectively; (2) the shock absorption of low precision of semi-active control method did twice as much seismic proof efficacy as that of passive control method; (3) active control method may not exert a negative influence of amplifying acceleration response of structure; (4) this AIC comes into being time-delay problem. It is the same problem of ordinary active control method. The proposed predictive control method can overcome this defect; (5) condition switch is an important characteristics of control type. The test results show that synchronism control is very easy to control and avoid stirring high frequency response. This laboratory results confirm that the device developed in this research is capable of applying the mutual interaction between the subordinate structure and the main structure to be protected is capable of transforming the quake energy applied to the main structure to the subordinate structure so that the objective of minimizing the deformation of main structural can be achieved.

Keywords: DSHD (Displacement Semi-Active Hydraulic Damper), AIC (Active Interaction Control Device), shake table test, full scale structure test, sub-structure, main-structure

Procedia PDF Downloads 514

Authors: M. El-haj, Z. Olama, H. Holail

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Single cell oils (SCOs) accumulated by oleaginous fungi have emerged as a potential alternative feedstock for biodiesel production. Five fungal strains were isolated from the Lebanese environment namely Fusarium oxysporum, Mucor hiemalis, Penicillium citrinum, Aspergillus tamari, and Aspergillus niger that have been selected among 39 oleaginous strains for their potential ability to accumulate lipids (lipid content was more than 40% on dry weight basis). Wide variations were recorded in the environmental factors that lead to maximum lipid production by fungi under test and were cultivated under submerged fermentation on medium containing glucose as a carbon source. The maximum lipid production was attained within 6-8 days, at pH range 6-7, 24 to 48 hours age of seed culture, 4 to 6.107 spores/ml inoculum level and 100 ml culture volume. Eleven culture conditions were examined for their significance on lipid production using Plackett-Burman factorial design. Reducing sugars and nitrogen source were the most significant factors affecting lipid production process. Maximum lipid yield was noticed with 15.62, 14.48, 12.75, 13.68 and 20.41g/l for Fusarium oxysporum, Mucor hiemalis, Penicillium citrinum, Aspergillus tamari, and Aspergillus niger respectively. A verification experiment was carried out to examine model validation and revealed more than 94% validity. The profile of extracted lipids from each fungal isolate was studied using thin layer chromatography (TLC) indicating the presence of monoacylglycerols, diaacylglycerols, free fatty acids, triacylglycerols and sterol esters. The fatty acids profiles were also determined by gas-chromatography coupled with flame ionization detector (GC-FID). Data revealed the presence of significant amount of oleic acid (29-36%), palmitic acid (18-24%), linoleic acid (26.8-35%), and low amount of other fatty acids in the extracted fungal oils which indicate that the fatty acid profiles were quite similar to that of conventional vegetable oil. The cost of lipid production could be further reduced with acid-pretreated lignocellulotic corncob waste, whey and date molasses to be utilized as the raw material for the oleaginous fungi. The results showed that the microbial lipid from the studied fungi was a potential alternative resource for biodiesel production.

Keywords: agro-industrial waste products, biodiesel, fatty acid, single cell oil, Lebanese environment, oleaginous fungi

Procedia PDF Downloads 402

Authors: Jason Gica, Yi-Hsieng Samuel Wu, Deng-Jye Yang, Yi-Chen Chen

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Mycotoxins, harmful secondary metabolites produced by certain fungi species, pose significant risks to animals and humans worldwide. Their stable properties lead to contamination during grain harvesting, transportation, and storage, as well as in processed food products. The prevalence of mycotoxin contamination has attracted significant attention due to its adverse impact on food safety and global trade. The secondary contamination pathway from animal products has been identified as an important route of exposure, posing health risks for livestock and humans consuming contaminated products. Pork, one of the highly consumed meat products in Taiwan according to the National Food Consumption Database, plays a critical role in the nation's diet and economy. Given its substantial consumption, pork processing products are a significant component of the food supply chain and a potential source of mycotoxin contamination. This study is paramount for formulating effective regulations and strategies to mitigate mycotoxin-related risks in the food supply chain. By establishing a reliable analytical method, this research contributes to safeguarding public health and enhancing the quality of pork processing products. The findings will serve as valuable guidance for policymakers, food industries, and consumers to ensure a safer food supply chain in the face of emerging mycotoxin challenges. An innovative and efficient analytical approach is proposed using Ultra-High Performance Liquid Chromatography coupled with Temperature Control Fluorescence Detector Light (UHPLC-TCFLD) to determine multiple mycotoxins in pork meat samples due to its exceptional capacity to detect multiple mycotoxins at the lowest levels of concentration, making it highly sensitive and reliable for comprehensive mycotoxin analysis. Additionally, its ability to simultaneously detect multiple mycotoxins in a single run significantly reduces the time and resources required for analysis, making it a cost-effective solution for monitoring mycotoxin contamination in pork processing products. The research aims to optimize the efficient mycotoxin QuEChERs extraction method and rigorously validate its accuracy and precision. The results will provide crucial insights into mycotoxin levels in pork processing products.

Keywords: multiple-mycotoxin analysis, pork processing products, QuEChERs, UHPLC-TCFLD, validation

Procedia PDF Downloads 62

Authors: B. Gepts, E. Meex, E. Nuyts, E. Knaepen, G. Verbeeck

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The importance of resource efficiency and environmental impact assessment has raised the interest in knowing the amount of materials used in buildings. If no BIM model or energy performance certificate is available, material quantities can be obtained through an estimation or time-consuming calculation. For the interior wall area, no validated estimation method exists. However, in the case of environmental impact assessment or evaluating the existing building stock as future material banks, knowledge of the material quantities used in interior walls is indispensable. This paper presents a validated method for the estimation of the interior wall area for dwellings based on easy-to-collect building characteristics. A database of 4963 residential buildings spread all over Belgium is used. The data are collected through onsite measurements of the buildings during the construction phase (between mid-2010 and mid-2017). The interior wall area refers to the area of all interior walls in the building, including the inner leaf of exterior (party) walls, minus the area of windows and doors, unless mentioned otherwise. The two predictive modelling techniques used are 1) a (stepwise) linear regression and 2) a decision tree. The best estimation method is selected based on the best R² k-fold (5) fit. The research shows that the building volume is by far the most important variable to estimate the interior wall area. A stepwise regression based on building volume per building, building typology, and type of house provides the best fit, with R² k-fold (5) = 0.88. Although the best R² k-fold value is obtained when the other parameters ‘building typology’ and ‘type of house’ are included, the contribution of these variables can be seen as statistically significant but practically irrelevant. Thus, if these parameters are not available, a simplified estimation method based on only the volume of the building can also be applied (R² k-fold = 0.87). The robustness and precision of the method (output) are validated three times. Firstly, the prediction of the interior wall area is checked by means of alternative calculations of the building volume and of the interior wall area; thus, other definitions are applied to the same data. Secondly, the output is tested on an extension of the database, so it has the same definitions but on other data. Thirdly, the output is checked on an unrelated database with other definitions and other data. The validation of the estimation methods demonstrates that the methods remain accurate when underlying data are changed. The method can support environmental as well as economic dimensions of impact assessment, as it can be used in early design. As it allows the prediction of the amount of interior wall materials to be produced in the future or that might become available after demolition, the presented estimation method can be part of material flow analyses on input and on output.

Keywords: buildings as material banks, building stock, estimation method, interior wall area

Procedia PDF Downloads 23

Authors: Ricardo Torcato, Helder Morais

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The manufacture of crystal glass parts is based on obtaining the rough geometry by blowing and/or injection, generally followed by a set of manual finishing operations using cutting and grinding tools. The forming techniques used do not allow the obtainment, with repeatability, of parts with complex shapes and the finishing operations use intensive specialized labor resulting in high cycle times and production costs. This work aims to explore the digital manufacture of crystal glass parts by investigating new subtractive techniques for the automated, flexible finishing of these parts. Finishing operations are essential to respond to customer demands in terms of crystal feel and shine. It is intended to investigate the applicability of different computerized finishing technologies, namely milling and grinding in a CNC machining center with or without ultrasonic assistance, to crystal processing. Research in the field of grinding hard and brittle materials, despite not being extensive, has increased in recent years, and scientific knowledge about the machinability of crystal glass is still very limited. However, it can be said that the unique properties of glass, such as high hardness and very low toughness, make any glass machining technology a very challenging process. This work will measure the performance improvement brought about by the use of ultrasound compared to conventional crystal grinding. This presentation is focused on the mechanical characterization and analysis of the cutting forces in CNC machining of superior crystal glass (Pb ≥ 30%). For the mechanical characterization, the Vickers hardness test provides an estimate of the material hardness (Hv) and the fracture toughness based on cracks that appear in the indentation. Mechanical impulse excitation test estimates the Young’s Modulus, shear modulus and Poisson ratio of the material. For the cutting forces, it a dynamometer was used to measure the forces in the face grinding process. The tests were made based on the Taguchi method to correlate the input parameters (feed rate, tool rotation speed and depth of cut) with the output parameters (surface roughness and cutting forces) to optimize the process (better roughness using the cutting forces that do not compromise the material structure and the tool life) using ANOVA. This study was conducted for conventional grinding and for the ultrasonic grinding process with the same cutting tools. It was possible to determine the optimum cutting parameters for minimum cutting forces and for minimum surface roughness in both grinding processes. Ultrasonic-assisted grinding provides a better surface roughness than conventional grinding.

Keywords: CNC machining, crystal glass, cutting forces, hardness

Procedia PDF Downloads 152

Authors: Ayodeji Fasuyi

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Telfairia occidentalis is a leafy vegetable commonly grown in the tropics for nutritional benefits. The use of enzymes and probiotics is becoming prominent due to the ban on antibiotics as growth promoters in many parts of the world. It is conceived that with enzymes and probiotics additives, fibrous leafy vegetables can be incorporated into poultry feeds as protein source. However, certain antinutrients were also found in the leaves of Telfairia occidentalis. Four broiler starter and finisher diets were formulated for the two phases of the broiler experiments. A mixture of fiber degrading enzymes, Roxazyme G2 (combination of cellulase, glucanase and xylanase) and probiotics (Turbotox), a growth promoter, were used in broiler diets at 1:1. The Roxazyme G2/Turbotox mixtures were used in diets containing four varying levels of Telfairia occidentalis leaf meal (TOLM) at 0, 10, 20 and 30%. Diets 1 were standard broiler diets without TOLM and Roxazyme G2 and Turbotox additives. Diets 2, 3 and 4 had enzymes and probiotics additives. Certain mineral elements such as Ca, P, K, Na, Mg, Fe, Mn, Cu and Zn were found in notable quantities viz. 2.6 g/100 g, 1.2 g/100 g, 6.2 g/100 g, 5.1 g/100 g, 4.7 g/100 g, 5875 ppm, 182 ppm, 136 ppm and 1036 ppm, respectively. Phytin, phytin-P, oxalate, tannin and HCN were also found in ample quantities viz. 189.2 mg/100 g, 120.1 mg/100 g, 80.7 mg/100 g, 43.1 mg/100 g and 61.2 mg/100 g, respectively. The average weight gain was highest at 46.3 g/bird/day for birds on 10% TOLM diet but similar (P > 0.05) to 46.2 g/bird/day for birds on 20% TOLM. The feed conversion ratio (FCR) of 2.27 was the lowest and optimum for birds on 10% TOLM although similar (P > 0.05) to 2.29 obtained for birds on 20% TOLM. FCR of 2.61 was the highest at 2.61 for birds on 30% TOLM diet. The lowest FCR of 2.27 was obtained for birds on 10% TOLM diet although similar (P > 0.05) to 2.29 for birds on 20% TOLM diet. Most carcass characteristics and organ weights were similar (P > 0.05) for the experimental birds on the different diets except for kidney, gizzard and intestinal length. The values for kidney, gizzard and intestinal length were significantly higher (P < 0.05) for birds on the TOLM diets. The nitrogen retention had the highest value of 72.37 ± 0.10% for birds on 10% TOLM diet although similar (P > 0.05) to 71.54 ± 1.89 obtained for birds on the control diet without TOLM and enzymes/probiotics mixture. There was evidence of a better utilization of TOLM as a plant protein source. The carcass characteristics and organ weights all showed evidence of uniform tissue buildup and muscles development particularly in diets containing 10% of TOLM level. There was also better nitrogen utilization in birds on the 10% TOLM diet. Considering the cheap cost of TOLM, it is envisaged that its introduction into poultry feeds as a plant protein source will ultimately reduce the cost of poultry feeds.

Keywords: Telfairia occidentalis leaf meal, enzymes, probiotics, additives

Procedia PDF Downloads 131

Authors: Anderson Braga Mendes

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Itaipu Hydroelectric Power Plant is settled on the Paraná River, which is a natural boundary between Brazil and Paraguay; thus, the facility is shared by both countries. Itaipu Power Plant is the biggest hydroelectric generator in the world, and provides clean and renewable electrical energy supply for 17% and 76% of Brazil and Paraguay, respectively. The plant started its generation in 1984. It counts on 20 Francis turbines and has installed capacity of 14,000 MWh. Its historic generation record occurred in 2016 (103,098,366 MWh), and since the beginning of its operation until the last day of 2016 the plant has achieved the sum of 2,415,789,823 MWh. The distinct sedimentologic aspects of the drainage area of Itaipu Power Plant, from its stretch upstream (Porto Primavera and Rosana dams) to downstream (Itaipu dam itself), were taken into account in order to best estimate the increase/decrease in the sediment yield by using data from 2001 to 2016. Such data are collected through a network of 14 automatic sedimentometric stations managed by the company itself and operating in an hourly basis, covering an area of around 136,000 km² (92% of the incremental drainage area of the undertaking). Since 1972, a series of lifespan studies for the Itaipu Power Plant have been made, being first assessed by Sir Hans Albert Einstein, at the time of the feasibility studies for the enterprise. From that date onwards, eight further studies were made through the last 44 years aiming to confer more precision upon the estimates based on more updated data sets. From the analysis of each monitoring station, it was clearly noticed strong increase tendencies in the sediment yield through the last 14 years, mainly in the Iguatemi, Ivaí, São Francisco Falso and Carapá Rivers, the latter situated in Paraguay, whereas the others are utterly in Brazilian territory. Five lifespan scenarios considering different sediment yield tendencies were simulated with the aid of the softwares SEDIMENT and DPOSIT, both developed by the author of the present work. Such softwares thoroughly follow the Borland & Miller methodology (empirical method of area-reduction). The soundest scenario out of the five ones under analysis indicated a lifespan foresight of 168 years, being the reservoir only 1.8% silted by the end of 2016, after 32 years of operation. Besides, the mass balance in the reservoir (water inflows minus outflows) between 1986 and 2016 shows that 2% of the whole Itaipu lake is silted nowadays. Owing to the convergence of both results, which were acquired by using different methodologies and independent input data, it is worth concluding that the mathematical modeling is satisfactory and calibrated, thus assigning credibility to this most recent lifespan estimate.

Keywords: Borland and Miller method, hydroelectricity, Itaipu Power Plant, lifespan, mass balance

Procedia PDF Downloads 273

Authors: Peyman Mosberian-Tanha, Mona Rezaei

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Aquaculture sector is the fastest growing food sector with annual growth rate of about 10%. The sustainability of aquaculture production, however, has been debated mainly in relation to the feed ingredients used for farmed fish. The industry has been able to decrease its dependency on marine-based ingredients in line with policies for more sustainable production. As a result, plant-based ingredients have increasingly been incorporated in aquaculture feeds, especially in feeds for popular carnivorous species, salmonids. The effect of these ingredients on salmonids’ health and performance has been widely studied. In most cases, plant-based diets are associated with varying degrees of health and performance issues across salmonids, partly depending on inclusion levels of plant ingredients and the species in question. However, aquaculture sector is facing another challenge of concern. Environmental challenges in association with climate change is another issue the aquaculture sector must deal with. Data from trials in salmonids subjected to environmental challenges of various types show adverse physiological responses, partly in relation to stress. To date, there are only a limited number of studies reporting the interactive effects of adverse environmental conditions and dietary regimens on salmonids. These studies have shown that adverse environmental conditions exacerbate the detrimental effect of plant-based diets on digestive function and health in salmonids. This indicates an additional challenge for the aquaculture sector to grow in a sustainable manner. The adverse environmental conditions often studied in farmed fish is the change in certain water quality parameters such as oxygen and/or temperature that are typically altered in response to climate change and, more specifically, global warming. In a challenge study, we observed that the in the fish fed a plant-based diet, the fish’s ability to absorb dietary energy was further reduced when reared under low oxygen level. In addition, gut health in these fish was severely impaired. Some other studies also confirm the adverse effect of environmental challenge on fish’s gut health. These effects on the digestive function and gut health of salmonids may result in less resistance to diseases and weaker performance with significant economic and ethical implications. Overall, various findings indicate the multidimensional negative effects of climate change, as a major environmental issue, in different sectors, including aquaculture production. Therefore, a comprehensive evaluation of different ways to cope with climate change is essential for planning more sustainable strategies in aquaculture sector.

Keywords: aquaculture, climate change, sustainability, salmonids

Procedia PDF Downloads 183

Authors: Suruchi Saini, Hitender Kumar Tyagi

Abstract:

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 58

Authors: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong

Abstract:

Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.

Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale

Procedia PDF Downloads 63