Search results for: large dams

Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

Procedia PDF Downloads 382

Authors: Sang Guen Kim, Sib Sankar Giri, Jin Woo Jun, Saekil Yun, Hyoun Joong Kim, Sang Wha Kim, Jung Woo Kang, Se Jin Han, Se Chang Park

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Emerging of the super bacteria, bacteriophages are considered to be as an alternative to antibiotics. As the demand of phage increased, economical and large production of phage is becoming one of the critical points. For the therapeutic use, what is important is to eradicate the pathogenic bacteria as fast as possible, so higher concentration of phages is generally needed for effective therapeutic function. On the contrary, for the maximum production, bacteria work as a phage producing factory. As a microbial cell factory, bacteria is needed to last longer producing the phages without eradication. Consequently, killing the bacteria fast has a negative effect on large production. In this study, Multiplicity of Infection (MOI) was manipulated based on initial bacterial inoculation and used phage pAh-6C which has therapeutic effect against Aeromonas hydrophila. 1, 5 and 10 percent of overnight bacterial culture was inoculated and each bacterial culture was co-cultured with the phage of which MOI of 0.01, 0.0001, and 0.000001 respectively. Simply changing the initial MOI as well as bacterial inoculation concentration has regulated the production quantity of the phage without any other changes to culture conditions. It is anticipated that this result can be used as a foundational data for mass production of lytic bacteriophages which can be used as the therapeutic bio-control agent.

Keywords: bacteriophage, multiplicity of infection, optimization, Aeromonas hydrophila

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Authors: Jacques Lamarche, Juhani Dickinson

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This paper introduces a computational model of a Grammar as Logic of Labeling (GLL), where the lexical primitives of morphosyntax are phonological matrixes, the form of words, understood as labels that apply to realities (or targets) assumed to be outside of grammar altogether. The hypothesis is that even though a lexical label relates to its target arbitrarily, this label in a complex (constituent) label is part of a labeling pattern which, depending on its value (i.e., N, V, Adj, etc.), imposes language-specific restrictions on what it targets outside of grammar (in the world/semantics or in cognitive knowledge). Lexical forms categorized as nouns, verbs, adjectives, etc., are effectively targets of labeling patterns in use. The paper illustrates GLL through a computer model of basic patterns in English NPs. A constituent label is a binary object that encodes: i) alignment of input forms so that labels occurring at different points in time are understood as applying at once; ii) endocentric structuring - every grammatical constituent has a head label that determines the target of the constituent, and a limiter label (the non-head) that restricts this target. The N or A values are restricted to limiter label, the two differing in terms of alignment with a head. Consider the head initial DP ‘the dog’: the label ‘dog’ gets an N value because it is a limiter that is evenly aligned with the head ‘the’, restricting application of the DP. Adapting a traditional analysis of ‘the’ to GLL – apply label to something familiar – the DP targets and identifies one reality familiar to participants by applying to it the label ‘dog’ (singular). Consider next the DP ‘the large dog’: ‘large dog’ is nominal by even alignment with ‘the’, as before, and since ‘dog’ is the head of (head final) ‘large dog’, it is also nominal. The label ‘large’, however, is adjectival by narrow alignment with the head ‘dog’: it doesn’t target the head but targets a property of what dog applies to (a property or value of attribute). In other words, the internal composition of constituents determines that a form targets a property or a reality: ‘large’ and ‘dog’ happen to be valid targets to realize this constituent. In the presentation, the computer model of the analysis derives the 8 possible sequences of grammatical values with three labels after the determiner (the x y z): 1- D [ N [ N N ]]; 2- D [ A [ N N ] ]; 3- D [ N [ A N ] ]; 4- D [ A [ A N ] ]; 5- D [ [ N N ] N ]; 5- D [ [ A N ] N ]; 6- D [ [ N A ] N ] 7- [ [ N A ] N ] 8- D [ [ Adv A ] N ]. This approach that suggests that a computer model of these grammatical patterns could be used to construct ontologies/knowledge using speakers’ judgments about the validity of lexical meaning in grammatical patterns.

Keywords: syntactic theory, computational linguistics, logic and grammar, semantics, knowledge and grammar

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Authors: Ayad Salih Sabbar, Amin Chegenizadeh, Hamid Nikraz

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Investigation of liquefaction susceptibility of materials that have been used in embankments, slopes, dams, and foundations is very essential. Many catastrophic geo-hazards such as flow slides, declination of foundations, and damage to earth structure are associated with static liquefaction that may occur during abrupt shearing of these materials. Many artificial backfill materials are mixtures of sand with fines and other composition. In order to provide some clarifications and evaluations on the role of fines in static liquefaction behaviour of sand sandy soils, the effect of fines on the liquefaction susceptibility of sand was experimentally examined in the present work over a range of fines content, relative density, and initial confining pressure. The results of an experimental study on various sand-fines mixtures are presented. Undrained static triaxial compression tests were conducted on saturated Perth sand containing 5% bentonite at three different relative densities (10, 50, and 90%), and saturated Perth sand containing both 5% bentonite and slag (2%, 4%, and 6%) at single relative density 10%. Undrained static triaxial tests were performed at three different initial confining pressures (100, 150, and 200 kPa). The brittleness index was used to quantify the liquefaction potential of sand-bentonite-slag mixtures. The results demonstrated that the liquefaction susceptibility of sand-5% bentonite mixture was more than liquefaction susceptibility of clean sandy soil. However, liquefaction potential decreased when both of two fines (bentonite and slag) were used. Liquefaction susceptibility of all mixtures decreased with increasing relative density and initial confining pressure.  

Keywords: liquefaction, bentonite, slag, brittleness index

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Authors: Mohammed Belloufi, Rachid Benzine, Badreddine Sellami

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Conjugate gradient methods is useful for solving large scale optimization problems in scientific and engineering computation, characterized by the simplicity of their iteration and their low memory requirements. It is well known that the search direction plays a main role in the line search method. In this paper, we propose a search direction with the Wolfe line search technique for solving unconstrained optimization problems. Under the above line searches and some assumptions, the global convergence properties of the given methods are discussed. Numerical results and comparisons with other CG methods are given.

Keywords: unconstrained optimization, conjugate gradient method, strong Wolfe line search, global convergence

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Authors: Agung Budi Muljono, I Made Ginarsa, I Made Ari Nrartha

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A large-scale power system (LSPS) consists of two or more sub-systems connected by inter-connecting transmission. Loading pattern on an LSPS always changes from time to time and varies depend on consumer need. The serious instability problem is appeared in an LSPS due to load fluctuation in all of the bus. Adaptive neuro-fuzzy inference system (ANFIS)-based power system stabilizer (PSS) is presented to cover the stability problem and to enhance the stability of an LSPS. The ANFIS control is presented because the ANFIS control is more effective than Mamdani fuzzy control in the computation aspect. Simulation results show that the presented PSS is able to maintain the stability by decreasing peak overshoot to the value of −2.56 × 10−5 pu for rotor speed deviation Δω2−3. The presented PSS also makes the settling time to achieve at 3.78 s on local mode oscillation. Furthermore, the presented PSS is able to improve the peak overshoot and settling time of Δω3−9 to the value of −0.868 × 10−5 pu and at the time of 3.50 s for inter-area oscillation.

Keywords: ANFIS, large-scale, power system, PSS, stability enhancement

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Authors: S. Apprich, F. Wulle, A. Lechler, A. Pott, A. Verl

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Large-scale machine tools for the manufacturing of large work pieces, e.g. blades, casings or gears for wind turbines, feature pose-dependent dynamic behavior. Small structural damping coefficients lead to long decay times for structural vibrations that have negative impacts on the production process. Typically, these vibrations are handled by increasing the stiffness of the structure by adding mass. That is counterproductive to the needs of sustainable manufacturing as it leads to higher resource consumption both in material and in energy. Recent research activities have led to higher resource efficiency by radical mass reduction that rely on control-integrated active vibration avoidance and damping methods. These control methods depend on information describing the dynamic behavior of the controlled machine tools in order to tune the avoidance or reduction method parameters according to the current state of the machine. The paper presents the appearance, consequences and challenges of the pose-dependent dynamic behavior of lightweight large-scale machine tool structures in production. The paper starts with the theoretical introduction of the challenges of lightweight machine tool structures resulting from reduced stiffness. The statement of the pose-dependent dynamic behavior is corroborated by the results of the experimental modal analysis of a lightweight test structure. Afterwards, the consequences of the pose-dependent dynamic behavior of lightweight machine tool structures for the use of active control and vibration reduction methods are explained. Based on the state of the art on pose-dependent dynamic machine tool models and the modal investigation of an FE-model of the lightweight test structure, the criteria for a pose-dependent model for use in vibration reduction are derived. The description of the approach for a general pose-dependent model of the dynamic behavior of large lightweight machine tools that provides the necessary input to the aforementioned vibration avoidance and reduction methods to properly tackle machine vibrations is the outlook of the paper.

Keywords: dynamic behavior, lightweight, machine tool, pose-dependency

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Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

Procedia PDF Downloads 358

Authors: M. H. A. D. de Silva, R. P. Hewawasam, M. A. G. Iresha

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Macrosomia is common in infants born to not only women diagnosed with gestational diabetes mellitus but also non-diabetic obese women. Maternal Body Mass Index (BMI) correlates with the incidence of large for gestational age infants. Obesity has reached epidemic levels in modern societies. During the past two decades, obesity in children and adolescents has risen significantly in Asian populations including Sri Lanka. There is increasing evidence to believe that infants who are born large for gestational age are more likely to be obese in childhood and adolescence and are at risk of cardiovascular and metabolic complications later in life. It is also established that Asians have lower skeletal muscle mass, low bone mineral content and excess body fat for a given BMI indicating a genetic predisposition in the occurrence of obesity. The objective of this study is to determine the effect of maternal weight, weight gain during pregnancy, c-peptide and insulin concentrations in the cord blood on the birth of appropriate for and large for gestational age infants in a tertiary care center in Southern Sri Lanka. Umbilical cord blood was collected from 90 newborns (Male 40, Female 50; gestational age 35-42 weeks) after double clamping the umbilical cord before separation of the placenta and the concentration of insulin and C-peptide were measured by ELISA technique. Anthropometric parameters of the newborn such as birth weight, length, ponderal index, occipital frontal, chest, hip and calf circumferences were measured, and characteristics of the mother were collected. The relationship between insulin, C-peptide and anthropometrics were assessed by Spearman correlation. The multiple logistic regression analysis examined influences of maternal weight, weight gain during pregnancy, C-peptide and insulin concentrations in cord blood as covariates on the birth of large for gestational age infants. A significant difference (P<0.001) was observed between the insulin levels of infants born large for gestational age (18.73 ± 0.52 µlU/ml) and appropriate for gestational age (13.08 ± 0.56 µlU/ml). Consistently, A significant decrease in concentration (41.68%, P<0.001) was observed between C-peptide levels of infants born large for gestational age and appropriate for gestational age. Cord blood insulin and C-peptide levels had a significant correlation with birth weight (r=0.35, P<0.05) of the newborn at delivery. Maternal weight and BMI which are indicators of maternal nutrition were proven to be directly correlated with birth weight and length. To our knowledge, this relationship was investigated for the first time in a Sri Lankan setting and was also evident in our results. This study confirmed the fact that insulin and C-peptide play a major role in regulating fetal growth. According to the results obtained in this study, we can suggest that the increased BMI of the mother has a direct influence on increased maternal insulin secretion, which may subsequently affect cord insulin and C-peptide levels and also birth weight of the infant.

Keywords: C-peptide, insulin, large for gestational age, maternal weight

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Authors: Du Yanxia, Stephan E. Bansmer, Gui Yewei, Xiao Guangming, Yang Xiaofeng

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The heat and mass transfer characteristics of icing coupled with film flow is studied and the coupled model of the thermal behavior with the flow simulation by single-step method is developed. The behavior of ice and water was analyzed. The results show that under supercooled large droplet (SLD) icing conditions, the film flow is an important phonomena in icing accretion process. The pressure gradient, gravity and shear stress are the main factors affecting the film flow on icing surface, which has important influence on the shape and rate of icing. To predict SLD ice accretion accurately, the heat and mass transfer of ice and film flow should be taken into account.

Keywords: SLD, aircraft, icing, heat and mass transfer

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Authors: Lilian Kishimbo

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This study aims to examine Corporate Social Responsibility (CSR) practices of local large firms of East Africa region. In this study CSR is defined as all actions that go beyond obeying minimum legal requirements as espoused by other authors. Despite the increase of CSR literature empirical evidence clearly demonstrate an imbalance of CSR studies in the developing countries . Moreover, it is evident that most of the research on CSR in developing economies emerges from large fast-growing economies or BRICS members (i.e. Brazil, India, China and South Africa), and Indonesia and Malaysia and a further call for more research in Africa is particularly advocated. Taking Africa as an example, there are scanty researches on CSR practices, and the few available studies are mainly from Nigeria and South Africa leaving other parts of Africa for example East Africa underrepresented. Furthermore, in the face of globalization, experience shows that literature has focused mostly on multinational companies (MNCs) operating in either North-North or North-South and less on South-South indigenous local firms. Thus the existing literature in Africa shows more studies of MNCs and little is known about CSR of local indigenous firms operating in the South particularly in the East Africa region. Accordingly, this paper explores CSR practices of indigenous local large firms of East Africa region particularly Kenya and Tanzania with the aim of testing the hypothesis that do local firms of East Africa region engage in similar CSR practices as firms in other parts of the world?. To answer this question only listed local large firms were considered based on the assumption that they are large enough to engage. Newspapers were the main source of data and information collected was supplemented by business Annual Reports for the period 2010-2012. The research finding revealed that local firms of East Africa engage in CSR practices. However, there are some differences in the set of activities these firms prefers to engage in compared to findings from previous studies. As such some CSR that were given priority by firms in East Africa were less prioritized in the other part of the world including Indonesia. This paper will add knowledge to the body of CSR and experience of CSR practices of South-South indigenous firms where is evidenced to have a relative dearth of literature on CSR. Finally, the paper concludes that local firms of East Africa region engage in similar activities like other firms globally. But firms give more priority to some activities such education and health related activities. Finally, the study intends to assist policy makers at firm’s levels to plan for long lasting projects related to CSR for their stakeholders.

Keywords: Africa, corporate social responsibility, developing countries, indigenous firms, Kenya, Tanzania

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Authors: Wenjuan Du, Jingtian Bi, Tong Wang, Haifeng Wang

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Grid connection of a large-scale wind farm affects power system small-signal angular stability in two aspects. Firstly, connection of the wind farm brings about the change of load flow and configuration of a power system. Secondly, the dynamic interaction is introduced by the wind farm with the synchronous generators (SGs) in the power system. This paper proposes a method to assess the two aspects of the effect of the wind farm on power system small-signal angular stability. The effect of the change of load flow/system configuration brought about by the wind farm can be examined separately by displacing wind farms with constant power sources, then the effect of the dynamic interaction of the wind farm with the SGs can be also computed individually. Thus, a clearer picture and better understanding on the power system small-signal angular stability as affected by grid connection of the large-scale wind farm are provided. In the paper, an example power system with grid connection of a wind farm is presented to demonstrate the proposed approach.

Keywords: power system small-signal angular stability, power system low-frequency oscillations, electromechanical oscillation modes, wind farms, double fed induction generator (DFIG)

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Authors: Hafiz Md. Hasan Babu, Khandaker Mohammad Mohi Uddin, Nitish Biswas, Sarreha Tasmin Rikta, Nuzmul Hossain Nahid

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Nanomedicine and bioengineering use biological systems that can perform computing operations. In a biocomputational circuit, different types of biomolecules and DNA (Deoxyribose Nucleic Acid) are used as active components. DNA computing has the capability of performing parallel processing and a large storage capacity that makes it diverse from other computing systems. In most processors, the multiplier is treated as a core hardware block, and multiplication is one of the time-consuming and lengthy tasks. In this paper, cost-effective DNA multipliers are designed using algorithms of molecular DNA operations with respect to conventional ones. The speed and storage capacity of a DNA multiplier are also much higher than a traditional silicon-based multiplier.

Keywords: biological systems, DNA multiplier, large storage, parallel processing

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Authors: Zhiyan Meng, Dan Liu, Jintao Meng

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Dependable encrypted traffic classification is crucial for improving cybersecurity and handling the growing amount of data. Large language models have shown that learning from large datasets can be effective, making pre-trained methods for encrypted traffic classification popular. However, attention-based pre-trained methods face two main issues: their large neural parameters are not suitable for low-computation environments like mobile devices and real-time applications, and they often overfit by getting stuck in local minima. To address these issues, we developed a lightweight transformer model, which reduces the computational parameters through lightweight vocabulary construction and Squeeze-and-Excitation Block. We use sharpness-aware optimization to avoid local minima during pre-training and capture temporal features with relative positional embeddings. Our approach keeps the model's classification accuracy high for downstream tasks. We conducted experiments on four datasets -USTC-TFC2016, VPN 2016, Tor 2016, and CICIOT 2022. Even with fewer than 18 million parameters, our method achieves classification results similar to methods with ten times as many parameters.

Keywords: sharpness-aware optimization, encrypted traffic classification, squeeze-and-excitation block, pretrained model

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Authors: M. Babul Hasan

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Management sciences (MS), big group of companies and industries or government policies (GP) is affiliated with a huge number of decision ingredients and complicated restrictions. Every factor in MS, every product in Industries or decision in GP is not always bankable in practice. After formulating these models there arises large-scale mixed integer programming (MIP) problem. In this paper, we developed decomposition-based pricing procedure to filter the unnecessary decision ingredients from MIP where the variables in huge number will be abated and the complicacy of restrictions will be elementary. A real life numerical example has been illustrated to demonstrate the methods. We develop the computer techniques for these methods by using a mathematical programming language (AMPL).

Keywords: Lagrangian relaxation, decomposition, sub-problem, master-problem, pricing, mixed IP, AMPL

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Authors: Nicholas Aerne, John P. Parmigiani

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There is an increasing desire for renewable and sustainable energy sources to replace fossil fuels. This desire is the result of several factors. First, is the role of fossil fuels in climate change. Scientific data clearly shows that global warming is occurring. It has also been concluded that it is highly likely human activity; specifically, the combustion of fossil fuels, is a major cause of this warming. Second, despite the current surplus of petroleum, fossil fuels are a finite resource and will eventually become scarce and alternatives, such as clean or renewable energy will be needed. Third, operations to obtain fossil fuels such as fracking, off-shore oil drilling, and strip mining are expensive and harmful to the environment. Given these environmental impacts, there is a need to replace fossil fuels with renewable energy sources as a primary energy source. Various sources of renewable energy exist. Many familiar sources obtain renewable energy from the sun and natural environments of the earth. Common examples include solar, hydropower, geothermal heat, ocean waves and tides, and wind energy. Often obtaining significant energy from these sources requires physically-large, sophisticated, and expensive equipment (e.g., wind turbines, dams, solar panels, etc.). Other sources of renewable energy are from the man-made environment. An example is municipal water distribution systems. The movement of water through the pipelines of these systems typically requires the reduction of hydraulic pressure through the use of pressure reducing valves. These valves are needed to reduce upstream supply-line pressures to levels suitable downstream users. The energy associated with this reduction of pressure is significant but is currently not harvested and is simply lost. While the integrity of municipal water supplies is of paramount importance, one can certainly envision means by which this lost energy source could be safely accessed. This paper provides a technical description and analysis of one such means by the technology company InPipe Energy to generate hydroelectricity by harvesting energy from municipal water distribution pressure reducing valve stations. Specifically, InPipe Energy proposes to install hydropower turbines in parallel with existing pressure reducing valves in municipal water distribution systems. InPipe Energy in partnership with Oregon State University has evaluated this approach and built a prototype system at the O. H. Hinsdale Wave Research Lab. The Oregon State University evaluation showed that the prototype system rapidly and safely initiates, maintains, and ceases power production as directed. The outgoing water pressure remained constant at the specified set point throughout all testing. The system replicates the functionality of the pressure reducing valve and ensures accurate control of down-stream pressure. At a typical water-distribution-system pressure drop of 60 psi the prototype, operating at an efficiency 64%, produced approximately 5 kW of electricity. Based on the results of this study, this proposed method appears to offer a viable means of producing significant amounts of clean renewable energy from existing pressure reducing valves.

Keywords: pressure reducing valve, renewable energy, sustainable energy, water supply

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Authors: Linyue Jia, Wenbo Du, Zhaohui Wang, Ke Liu, Shubo Li

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Due to the great potential for weight reduction in aerospace and automotive industries, magnesium-rare earth (Mg-RE) based alloys with outstanding mechanical performance have been widely investigated for decades. However, magnesium alloys are still restricted in engineering applications because of their lower strength and ductility. Hence, there are large spaces and challenges in achieving high-performance Mg alloys. This work reports an Mg-Gd-Er-Zn-Zr alloy with ultrahigh strength and good ductility developed via hot extrusion, pre-deformation, and two-stage aging. The extruded alloy comprises fine dynamically recrystallized (DRXed) grains and coarse worked grains with a large aspect ratio. Pre-deformation has little effect on the microstructure and macro-texture and serves primarily to introduce a large number of dislocations, resulting in strain hardening and higher precipitation strengthening during subsequent aging due to more nucleation sites. As a result, the alloy exhibits a yield strength (YS) of 506 MPa, an ultimate tensile strength (UTS) of 549 MPa, and elongation (EL) of 8.2% at room temperature, showing superior strength-ductility balance than the other wrought Mg-RE alloys previously reported. The current study proposes a combination of pre-deformation and two-stage aging to further improve the mechanical properties of wrought Mg alloys for engineering applications.

Keywords: magnesium alloys, mechanical properties, microstructure, pre-deformation, two-stage aging

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Tassili, occupying a large area of Algeria, is characterized by a rich vegetative biodiversity to be preserved and managed both in time and space. The management of a large area (case of Tassili), by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information etc.), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Multispectral imaging sensors have been very useful in the last decade in very interesting applications of remote sensing. They can aid in several domains such as the de¬tection and identification of diverse surface targets, topographical details, and geological features. In this work, we try to extract vegetative areas using fusion techniques between data acquired from sensor on-board the Earth Observing 1 (EO-1) satellite and Landsat ETM+ and TM sensors. We have used images acquired over the Oasis of Djanet in the National Park of Tassili in the south of Algeria. Fusion technqiues were applied on the obtained image to extract the vegetative fraction of the different classes of land use. We compare the obtained results in vegetation end member extraction with vegetation indices calculated from both Hyperion and other multispectral sensors.

Keywords: Landsat ETM+, EO1, data fusion, vegetation, Tassili, Algeria

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Authors: Patricia Sanz-Cordoba, Bernd Theilen

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This article analyzes the conditions where decentralization and partial tax harmonization in a coalition of asymmetric jurisdictions plays a role in the fight of fiscal competition (i.e. the race to bottom). Starting from a centralized economies, we use the ZM-W model to analyze the fiscal competition and coordination among three countries. We find that the asymmetry of jurisdictions facilitates partial tax harmonization between jurisdictions when these asymmetries are not too large. Furthermore, when the asymmetries are large enough, the level of labor tax plays an important role in the decision of decentralize capital tax. Accordingly, decentralization is achievable when labor tax is low. This result indicates that decentralization and partial tax harmonization between jurisdictions can be possible results in order to fight the negative externalities from fiscal competition, and more in the European Union countries where the asymmetries are substantial.

Keywords: centralization, decentralization, fiscal competition, partial tax harmonization

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Authors: Timir Baran Roy, Luis Guerreiro, Ashutosh Bagchi

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Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as bridges, dams, high-rise buildings etc. There had been a substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as natural frequency, modal damping, and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototypes of such walls have been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated, and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

Keywords: frequency domain decomposition (fdd), modal parameters, signal processing, stochastic subspace identification (ssi), time domain decomposition

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Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Maria Magdy Danial Riad

Abstract:

The objective of this study was to investigate the effect of different protein sources with different degradability ratios during late gestation of ewes on colostrum composition and its IgG concentration, body weight change of dams, and birth weight of their lambs. Objectives: 35 multiparous native crossbred ewes (BW= 59±2.5kg) were randomly allocated to five dietary treatments (7 ewes / treatment) for 2 months prior to lambing. Methods: Experimental diets were isonitrogenous (12.27% CP) and isocaloric (2.22 Mcal ME/kg DM). In diet I (the control), solvent extract soybeans (SESM 33% RUP of CP), II feed grade urea (FGU 31% RUP), III slow release urea (SRU 31% RUP). As sources of undegradable protein, extruded expeller SBM-EESM 40 (37% RUP) and extruded expeller SBM-EESM 60 (41% RUP) were used in groups IV and V, respectively. Results showed no significant effect on feed intake, crude protein (CP), metabolizable energy (ME), and body condition score (BCS). Ewes fed the 37% RUP diet gained more (p<0.05) weight compared with ewes fed the 31% RUP diet (5.62 vs. 2.5kg). Ewes in EESM 60 had the highest levels of fat, protein, total solid, solid not fat, and immunoglobulin and the lowest in urea N content (P< 0.05) in colostrum during the first 24hrs after lambing. Conclusions: Protein source and RUP levels in ewes’ diets had no significant effect (P< 0.05) on lambs’ birth weight and ewes' blood biochemical parameters. Increasing the RUP content of diet during late gestation resulted in an increase in colostrum constituents and its IgG level but had no effect on ewes’ performance and their lambs’ outcome.

Keywords: colostrum, ewes, lambs output, pregnancy, undegradable protein

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Authors: M. Abbasi

Abstract:

A spillway structure is used to pass excess water and floods from upstream or upstream to downstream or tributary. The spillway is considered one of the most key members of the dam, and the failure of many dams is attributed to the inefficiency of their spillway. Weirs should be selected as strong, reliable and high-performance structures, and weirs should be ready for use in all conditions and able to drain the flood so that we do not witness many casualties and financial losses when a flood occurs. The purpose of this study is to simulate the flow pattern passing over the peak spillway in order to optimize and adjust the height of the spillway walls. In this research, the effect of the shape of the side wings on the flow pattern over the peak spillways of the Gotvand reservoir dam was simulated and modelled using Flow3D software. In this research, side wings with rounded walls with six different approach angles were used. In addition, the different value of H/Hd was used to check the effect of the tank head. The results showed that with the constant H/Hd ratio and the increase of the approach angle of the side wing, the flow depth first decreases and then increases. These changes were the opposite regarding the depth average speed of the flow and the depth average concentration of the air entering the flow. At the same time, with the constant angle of approach of the side wing and with the increase of H/Hd ratio, the flow depth increases. In general, a correct understanding of the operation of overflows and a correct design can significantly reduce construction costs and solve flooding problems.

Keywords: effect of the shape, gotvand reservoir dam, narrowing coefficients, supports of the gates

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Authors: G. Ravindranath, S. Savitha

Abstract:

This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

Procedia PDF Downloads 365

Authors: Fatma Soltani

Abstract:

In power electronics the DC-DC converters or choppers are now employed in large areas, particularly in the field of electricity generation by wind and solar energy conversion. Photovoltaic generators (GPV) can deliver maximum power for a point on the characteristic P = f (Vpv), called maximum power point (MPP), or climatic variations, entraiment fluctuation PPM. To remedy this problem is interposed between the generator and receiver a DC-DC converter. The converter is usually used a simple MOSFET chopper. However, the MOSFET can be applied in the field of low power when you need a high switching frequency but becomes highly dissipative when should block large voltages For PV generators medium and high power, the use of IGBT chopper is by far the most recommended. To reduce stress on semiconductor components using several choppers series connected in parallel is known as interleaved chopper. These choppers lead to rotas.

Keywords: converter DC-DC entrelaced

, photovoltaic generators, IGBT, optimisation

Procedia PDF Downloads 539

Authors: D. C. Soares, J. T. S. Santos, D. G. Costa, A. K. S. Abud, T. P. Nunes, A. V. D. Figueiredo, A. M. de Oliveira Junior

Abstract:

Mangabeira (Hancornia speciosa Gomes), a native plant in Brazil, is found growing spontaneously in various regions of the country. The high perishability of tropical fruits such as mangaba, causes it to be necessary to use technologies that promote conservation, aiming to increase the shelf life of this fruit and add value. The objective of this study was to compare the mangabas lyophilisation curves behaviours with different sizes and maturation stages. The fruits were freeze-dried for a period of approximately 45 hours at lyophilizer Liotop brand, model L -108. It has been considered large the fruits between 38 and 58 mm diameter and small, between 23 and 28 mm diameter and the two states of maturation, intermediate and mature. Large size mangabas drying curves in both states of maturation were linear behaviour at all process, while the kinetic drying curves related to small fruits, independent of maturation state, had a typical behaviour of drying, with all the well-defined steps. With these results it was noted that the time of lyophilisation was suitable for small mangabas, a fact that did not happen with the larger one. This may indicate that the large mangabas require a longer time to freeze until reaches the equilibrium level, as it happens with the small fruits, going to have constant moisture at the end of the process. For both types of fruit were analysed water activity, acidity, protein, lipid, and vitamin C before and after the process.

Keywords: freeze dryer, mangaba, conservation, chemical characteristics

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Authors: F. Calderón-Vega, A. D. García-Soto, C. Mösso

Abstract:

Recorded significant wave heights sometimes exhibit large uncommon values (outliers) that can be associated with extreme phenomena such as hurricanes and cold fronts. In this study, some extremely large wave heights recorded in NOAA buoys (National Data Buoy Center, noaa.gov) are used to investigate their effect in the prediction of future wave heights associated with given return periods. Extreme waves are predicted through a time-dependent model based on the so-called generalized extreme value distribution. It is found that the outliers do affect the estimated wave heights. It is concluded that a detailed inspection of outliers is envisaged to determine whether they are real recorded values since this will impact defining design wave heights for coastal protection purposes.

Keywords: GEV model, non-stationary, seasonality, outliers

Procedia PDF Downloads 195

Authors: Sakshi Gupta, Kavita Sardana

Abstract:

Management of a forest catchment involves diverse dimensions, multiple stakeholders, and conflicting interests, primarily due to the wide variety of valuable ecosystem services offered by it. Often, the coordination among different levels of formal institutions governing the catchment, local communities, as well as societal norms, taboos, customs and practices, happens to be amiss, leading to conflicting policy interventions which prove detrimental for such resources. In the case of Ala Catchment, which is a protected forest located at a distance of 9 km North-East of the town of Dalhousie, within district Chamba of Himachal Pradesh, India, and serves as one of the primary sources of public water supply for the downstream town of Dalhousie and nearby areas, several policy measures have been adopted for the restoration of the forest catchment, as well as for the improvement of public water supply. These catchment forest restoration measures include; the installation of a fence along the perimeter of the catchment, plantation of trees in the empty patches of the forest, construction of check dams, contour trenches, contour bunds, issuance of grazing permits, and installation of check posts to keep track of trespassers. While the measures adopted to address the acute shortage of public water supply in the Dalhousie region include; building and maintenance of large capacity water storage tanks, laying of pipelines, expanding public water distribution infrastructure to include water sources other than Ala Catchment Forest and introducing of five new water supply schemes for drinking water as well as irrigation. However, despite these policy measures, the degradation of the Ala catchment and acute shortage of water supply continue to distress the region. This study attempts to conduct an institutional analysis to assess the impact of policy measures for the restoration of the Ala Catchment in the Chamba district of Himachal Pradesh in India. For this purpose, the theoretical framework of Ostrom’s Institutional Assessment and Development (IAD) Framework was used. Snowball sampling was used to conduct private interviews and focused group discussions. A semi-structured questionnaire was administered to interview a total of 184 respondents across stakeholders from both formal and informal institutions. The central hypothesis of the study is that the interplay of formal and informal institutions facilitates the implementation of policy measures for ameliorating Ala Catchment, in turn improving the livelihood of people depending on this forest catchment for direct and indirect benefits. The findings of the study suggest that leakages in the successful implementation of policy measures occur at several nodes of decision-making, which adversely impact the catchment and the ecosystem services provided by it. Some of the key reasons diagnosed by the immediate analysis include; ad-hoc assignment of property rights, rise in tourist inflow increasing the pressures on water demand, illegal trespassing by local and nomadic pastoral communities for grazing and unlawful extraction of forest products, and rent-seeking by a few influential formal institutions. Consequently, it is indicated that the interplay of formal and informal institutions may be obscuring the consequentiality of the policy measures on the restoration of the catchment.

Keywords: catchment forest restoration, institutional analysis and development framework, institutional interplay, protected forest, water supply management

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Authors: Dezhi Li, Peng Cui, Bo Zhang, Tengyuan Chang

Abstract:

In order to solve the housing problem for the low-income families, the construction of affordable housing is booming in China. However, due to various reasons, the service facilities and systems in the indemnificatory residential community meet many problems. This article established a Satisfaction Evaluation System of the Fundamental Public Services for Large-scale Indemnificatory Residential Community based on the national standards and local criteria and developed evaluation methods and processes. At last, in the case of Huagang project in Nanjing, the satisfaction of basic public service is calculated according to a survey of local residents.

Keywords: indemnificatory residential community, public services, satisfaction evaluation, structural equation modeling

Procedia PDF Downloads 362