Search results for: linear density of reinforcement
Commenced in January 2007
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Edition: International
Paper Count: 7265

Search results for: linear density of reinforcement

6125 Bone Mineral Density in Egyptian Children with Familial Mediterranean Fever

Authors: S. Salah, S. A. El-Masry, H. F. Sheba, R. A. El-Banna, W. Saad

Abstract:

Background: Familial Mediterranean fever (FMF) has episodic or subclinical inflammation that may lead to a decrease in bone mineral density (BMD). Objective: To assess BMD in Egyptian children with FMF on genetic basis. Subjects and Methods: A cross sectional study included 45 FMF patients and 25 control children of both sexes, with age range between 3-16 years old. The patients were reclassified into 2 groups: Group I (A) 23 cases used colchicines for 1 month or less, and Group I (B) 22 cases used colchicines for more than 6 months. For both patients and control, MEFV mutations were defined using molecular genetics technique and BMD was measured by DXA at 2 sites: proximal femur and the lumber spines. Results: four frequent gene mutations were found in the patient group: E148Q (35.6%), V726A (33.3%), M680I (28.9.0%) and M694V (2.2%). There were also 4 heterozygous gene mutations in 40% of control children. Patients received colchicines treatment for less than 1 month had highly significant lower values of BMD at femur and lumber spines than control children (p<0.05). Patients received colchicines treatment for more than 6 months had improved values of BMD at femur compared to control, but there were still significant differences between them at lumbar spine (p>0.05). There are insignificant effect of type of gene mutation on BMD and the risk of osteopenia among the patients. Conclusion: FMF had significant effect on BMD. However, regular use of colchicines treatment improves this effect mainly at femur.

Keywords: familial mediterranean fever, bone mineral density, genes, children

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6124 Analytical and Numerical Study of Formation of Sporadic E Layer with Taking into Account Horizontal and Vertical In-Homogeneity of the Horizontal Wind

Authors: Giorgi Dalakishvili, Goderdzi G. Didebulidze, Maya Todua

Abstract:

The possibility of sporadic E (Es) layer formation in the mid-latitude nighttime lower thermosphere by horizontal homogeneous and inhomogeneous (vertically and horizontally changing) winds is investigated in 3D by analytical and numerical solutions of continuity equation for dominant heavy metallic ions Fe+. The theory of influence of wind velocity direction, value, and its shear on formation of sporadic E is developed in case of presence the effect of horizontally changing wind (the effect of horizontal convergence). In this case, the horizontal wind with horizontal shear, characterized by compressibility and/or vortices, can provide an additional influence on heavy metallic ions Fe+ horizontal convergence and Es layers density, which can be formed by their vertical convergence caused as by wind direction and values and by its horizontal shear as well. The horizontal wind value and direction have significant influence on ion vertical drift velocity and its minimal negative values of divergence necessary for development of ion vertical convergence into sporadic E type layer. The horizontal wind horizontal shear, in addition to its vertical shear, also influences the ion drift velocity value and its vertical changes and correspondingly on formation of sporadic E layer and its density. The atmospheric gravity waves (AGWs), with relatively smaller horizontal wave length than planetary waves and tidal motion, can significantly influence location of ion vertical drift velocity nodes (where Es layers formation expectable) and its vertical and horizontal shear providing ion vertical convergence into thin layer. Horizontal shear can cause additional influence in the Es layers density than in the case of only wind value and vertical shear only. In this case, depending on wind direction and value in the height region of the lower thermosphere about 90-150 km occurs heavy metallic ions (Fe+) vertical convergence into thin sporadic E type layer. The horizontal wind horizontal shear also can influence on ions horizontal convergence and density and location Es layers. The AGWs modulate the horizontal wind direction and values and causes ion additional horizontal convergence, while the vertical changes (shear) causes additional vertical convergence than in the case without vertical shear. Influence of horizontal shear on sporadic E density and the importance of vertical compressibility of the lower thermosphere, which also can be influenced by AGWs, is demonstrated numerically. For the given wavelength and background wind, the predictability of formation Es layers and its possible location regions are shown. Acknowledgements: This study was funded by Georgian Shota Rustaveli National Science Foundation Grant no. FR17-357.

Keywords: in-homogeneous, sporadic E, thermosphere, wind

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6123 A Compact Standing-Wave Thermoacoustic Refrigerator Driven by a Rotary Drive Mechanism

Authors: Kareem Abdelwahed, Ahmed Salama, Ahmed Rabie, Ahmed Hamdy, Waleed Abdelfattah, Ahmed Abd El-Rahman

Abstract:

Conventional vapor-compression refrigeration systems rely on typical refrigerants, such as CFC, HCFC and ammonia. Despite of their suitable thermodynamic properties and their stability in the atmosphere, their corresponding global warming potential and ozone depletion potential raise concerns about their usage. Thus, the need for new refrigeration systems, which are environment-friendly, inexpensive and simple in construction, has strongly motivated the development of thermoacoustic energy conversion systems. A thermoacoustic refrigerator (TAR) is a device that is mainly consisting of a resonator, a stack and two heat exchangers. Typically, the resonator is a long circular tube, made of copper or steel and filled with Helium as a the working gas, while the stack has short and relatively low thermal conductivity ceramic parallel plates aligned with the direction of the prevailing resonant wave. Typically, the resonator of a standing-wave refrigerator has one end closed and is bounded by the acoustic driver at the other end enabling the propagation of half-wavelength acoustic excitation. The hot and cold heat exchangers are made of copper to allow for efficient heat transfer between the working gas and the external heat source and sink respectively. TARs are interesting because they have no moving parts, unlike conventional refrigerators, and almost no environmental impact exists as they rely on the conversion of acoustic and heat energies. Their fabrication process is rather simpler and sizes span wide variety of length scales. The viscous and thermal interactions between the stack plates, heat exchangers' plates and the working gas significantly affect the flow field within the plates' channels, and the energy flux density at the plates' surfaces, respectively. Here, the design, the manufacture and the testing of a compact refrigeration system that is based on the thermoacoustic energy-conversion technology is reported. A 1-D linear acoustic model is carefully and specifically developed, which is followed by building the hardware and testing procedures. The system consists of two harmonically-oscillating pistons driven by a simple 1-HP rotary drive mechanism operating at a frequency of 42Hz -hereby, replacing typical expensive linear motors and loudspeakers-, and a thermoacoustic stack within which the energy conversion of sound into heat is taken place. Air at ambient conditions is used as the working gas while the amplitude of the driver's displacement reaches 19 mm. The 30-cm-long stack is a simple porous ceramic material having 100 square channels per square inch. During operation, both oscillating-gas pressure and solid-stack temperature are recorded for further analysis. Measurements show a maximum temperature difference of about 27 degrees between the stack hot and cold ends with a Carnot coefficient of performance of 11 and estimated cooling capacity of five Watts, when operating at ambient conditions. A dynamic pressure of 7-kPa-amplitude is recorded, yielding a drive ratio of 7% approximately, and found in a good agreement with theoretical prediction. The system behavior is clearly non-linear and significant non-linear loss mechanisms are evident. This work helps understanding the operation principles of thermoacoustic refrigerators and presents a keystone towards developing commercial thermoacoustic refrigerator units.

Keywords: refrigeration system, rotary drive mechanism, standing-wave, thermoacoustic refrigerator

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6122 Soil Reinforcement by Stone Columns

Authors: Saou Mohamed Amine

Abstract:

The construction industry has been identified as a user of substantial amount of materials and energy resources that has an enormous impact on environment. The energy efficient in refurbishment project is being considered as one of the approaches to achieve sustainability in construction industry. The increasing concern for environment has made building owners and designers to incorporate the energy efficiency features into their building projects.

Keywords: construction industry, design team attributes, energy efficient performance, refurbishment projects characteristics

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6121 A Dislocation-Based Explanation to Quasi-Elastic Release in Shock Loaded Aluminum

Authors: Song L. Yao, Ji D. Yu, Xiao Y. Pei

Abstract:

An explanation is introduced to study the quasi-elastic release phenomenon in shock compressed aluminum. A dislocation-based model, taking into account of dislocation substructures and evolutions, is applied to simulate the elastic-plastic response of both single crystal and polycrystalline aluminum. Simulated results indicate that dislocation immobilization during dynamic deformation results in a smooth increase of yield stress, which leads to the quasi-elastic release. While the generation of dislocations caused by plastic release wave results in the appearance of transition point between the quasi-elastic release and the plastic release in the profile. The quantities of calculated shear strength and dislocation density are in accordance with experimental result, which demonstrates the accuracy of our simulations.

Keywords: dislocation density, quasi-elastic release, wave profile, shock wave

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6120 Derivatives Balance Method for Linear and Nonlinear Control Systems

Authors: Musaab Mohammed Ahmed Ali, Vladimir Vodichev

Abstract:

work deals with an universal control technique or single controller for linear and nonlinear stabilization and tracing control systems. These systems may be structured as SISO and MIMO. Parameters of controlled plants can vary over a wide range. Introduced a novel control systems design method, construction of stable platform orbits using derivative balance, solved transfer function stability preservation problem of linear system under partial substitution of a rational function. Universal controller is proposed as a polar system with the multiple orbits to simplify design procedure, where each orbit represent single order of controller transfer function. Designed controller consist of proportional, integral, derivative terms and multiple feedback and feedforward loops. The controller parameters synthesis method is presented. In generally, controller parameters depend on new polynomial equation where all parameters have a relationship with each other and have fixed values without requirements of retuning. The simulation results show that the proposed universal controller can stabilize infinity number of linear and nonlinear plants and shaping desired previously ordered performance. It has been proven that sensor errors and poor performance will be completely compensated and cannot affect system performance. Disturbances and noises effect on the controller loop will be fully rejected. Technical and economic effect of using proposed controller has been investigated and compared to adaptive, predictive, and robust controllers. The economic analysis shows the advantage of single controller with fixed parameters to drive infinity numbers of plants compared to above mentioned control techniques.

Keywords: derivative balance, fixed parameters, stable platform, universal control

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6119 Exact Solutions of a Nonlinear Schrodinger Equation with Kerr Law Nonlinearity

Authors: Muna Alghabshi, Edmana Krishnan

Abstract:

A nonlinear Schrodinger equation has been considered for solving by mapping methods in terms of Jacobi elliptic functions (JEFs). The equation under consideration has a linear evolution term, linear and nonlinear dispersion terms, the Kerr law nonlinearity term and three terms representing the contribution of meta materials. This equation which has applications in optical fibers is found to have soliton solutions, shock wave solutions, and singular wave solutions when the modulus of the JEFs approach 1 which is the infinite period limit. The equation with special values of the parameters has also been solved using the tanh method.

Keywords: Jacobi elliptic function, mapping methods, nonlinear Schrodinger Equation, tanh method

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6118 Spectroscopic Characterization of Indium-Tin Laser Ablated Plasma

Authors: Muhammad Hanif, Muhammad Salik

Abstract:

In the present research work we present the optical emission studies of the Indium (In)-Tin (Sn) plasma produced by the first (1064 nm) harmonic of an Nd: YAG nanosecond pulsed laser. The experimentally observed line profiles of neutral Indium (InI) and Tin (SnI) are used to extract the electron temperature (Te) using the Boltzmann plot method. Whereas, the electron number density (Ne) has been determined from the Stark broadening line profile method. The Te is calculated by varying the distance from the target surface along the line of propagation of plasma plume and also by varying the laser irradiance. Beside we have studied the variation of Ne as a function of laser irradiance as well as its variation with distance from the target surface.

Keywords: indium-tin plasma, laser ablation, optical emission spectroscopy, electron temperature, electron number density

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6117 Influence of P-Y Curves on Buckling Capacity of Pile Foundation

Authors: Praveen Huded, Suresh Dash

Abstract:

Pile foundations are one of the most preferred deep foundation system for high rise or heavily loaded structures. In many instances, the failure of the pile founded structures in liquefiable soils had been observed even in many recent earthquakes. Recent centrifuge and shake table experiments on two layered soil system have credibly shown that failure of pile foundation can occur because of buckling, as the pile behaves as an unsupported slender structural element once the surrounding soil liquefies. However the buckling capacity depends on largely on the depth of soil liquefied and its residual strength. Hence it is essential to check the pile against the possible buckling failure. Beam on non-linear Winkler Foundation is one of the efficient method to model the pile-soil behavior in liquefiable soil. The pile-soil interaction is modelled through p-y springs, different author have proposed different types of p-y curves for the liquefiable soil. In the present paper the influence two such p-y curves on the buckling capacity of pile foundation is studied considering initial geometric and non-linear behavior of pile foundation. The proposed method is validated against experimental results. Significant difference in the buckling capacity is observed for the two p-y curves used in the analysis. A parametric study is conducted to understand the influence of pile diameter, pile flexural rigidity, different initial geometric imperfections, and different soil relative densities on buckling capacity of pile foundation.

Keywords: Pile foundation , Liquefaction, Buckling load, non-linear py curve, Opensees

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6116 Chemometric Analysis of Raw Milk Quality Originating from Conventional and Organic Dairy Farming in AP Vojvodina, Serbia

Authors: Sanja Podunavac-Kuzmanović, Denis Kučević, Strahinja Kovačević, Milica Karadžić, Lidija Jevrić

Abstract:

The present study describes the application of chemometric methods in analysis of milk samples which were collected in a conventional dairy farm and an organic dairy farm in AP Vojvodina, Republic of Serbia. The chemometric analysis included the application of univariate regression modeling and Analysis of Variance (ANOVA) method. The ANOVA was used in order to determine the differences in fatty acids content in the milk samples from conventional and organic farm. The results of the ANOVA testing indicate that there is a highly statistically significant difference between the content of fatty acid (saturated fatty acid vs. unsaturated fatty acids) in different dairy farming. Besides, the linear univariate models have been obtained as a result of modeling the linear relationships between the milk fat content and saturated fatty acids content, and the linear relationships between the milk fat content and unsaturated fatty acids content. The models obtained on the basis of the milk samples which originate from the organic farming are statistically better than the models based on the milk samples from conventional farming.

Keywords: hemometrics, milk, organic farming, quality control

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6115 Microgrid Design Under Optimal Control With Batch Reinforcement Learning

Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

Abstract:

Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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6114 Estimates of Freshwater Content from ICESat-2 Derived Dynamic Ocean Topography

Authors: Adan Valdez, Shawn Gallaher, James Morison, Jordan Aragon

Abstract:

Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport and modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116 km3/year. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff. The total climatological freshwater content is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity driven pycnocline as opposed to the temperature driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and remotely sensed dynamic ocean topography (DOT). In-situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time consuming. NASA’s Advanced Topographic Laser Altimeter System (ATLAS) derived dynamic ocean topography (DOT), and Air Expendable CTD (AXCTD) derived Freshwater Content are used to develop a linear regression model. In-situ data for the regression model is collected across the 150° West meridian, which typically defines the centerline of the Beaufort Gyre. Two freshwater content models are determined by integrating the freshwater volume between the surface and an isopycnal corresponding to reference salinities of 28.7 and 34.8. These salinities correspond to those of the winter pycnocline and total climatological freshwater content, respectively. Using each model, we determine the strength of the linear relationship between freshwater content and satellite derived DOT. The result of this modeling study could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non in-situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: ICESat-2, dynamic ocean topography, freshwater content, beaufort gyre

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6113 Identification of Cocoa-Based Agroforestry Systems in Northern Madagascar: Pillar of Sustainable Management

Authors: Marizia Roberta Rasoanandrasana, Hery Lisy Tiana. Ranarijaona, Herintsitohaina Razakamanarivo, Eric Delaitre, Nandrianina Ramifehiarivo

Abstract:

Madagascar is one of the producer’s countries of world's fine cocoa. Cocoa-based agroforestry systems (CBAS) plays a very important economic role for over 75% of the population in the north of Madagascar, the island's main cocoa-producing area. It is also viewed as a key factor in the deforestation of local protected areas. It is therefore urgent to establish a compromise between cocoa production and forest conservation in this region which is difficult due to a lack of accurate cocoa agro-systems data. In order to fill these gaps and to response to these socio-economic and environmental concerns, this study aims to describe CBAS by providing precise data on their characteristics and to establish a typology. To achieve this, 150 farms were surveyed and observed to characterize CBAS based on 11 agronomic and 6 socio-economic data. Also, 30 representative plots of CBAS among the 150 farms were inventoried for providing accurate ecological data (6 variables) as an additional data for the typology determination. The results showed that Madagascar’s CBAS systems are generally extensive and practiced by smallholders. Four types of cocoa-based agroforestry system were identified, with significant differences between the following variables: yield, planting age, cocoa density, density of associated trees, preceding crop, associated crops, Shannon-Wiener indices and species richness in the upper stratum. Type 1 is characterized by old systems (>45 years) with low crop density (425 cocoa trees/ha), installed after conversion of crops other than coffee (> 50%) and giving low yields (427 kg/ha/year). Type 2 consists of simple agroforestry systems (no associated crop 0%), fairly young (20 years) with low density of associated trees (77 trees/ha) and low species diversity (H'=1.17). Type 3 is characterized by high crop density (778 trees/ha and 175 trees/ha for cocoa and associated trees respectively) and a medium level of species diversity (H'=1.74, 8 species). Type 4 is particularly characterized by orchard regeneration method involving replanting and tree lopping (100%). Analysis of the potential of these four types has identified Type 4 as a promising practice for sustainable agriculture.

Keywords: conservation, practices, productivity, protect areas, smallholder, trade-off, typology

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6112 Convergence of Generalized Jacobi, Gauss-Seidel and Successive Overrelaxation Methods for Various Classes of Matrices

Authors: Manideepa Saha, Jahnavi Chakrabarty

Abstract:

Generalized Jacobi (GJ) and Generalized Gauss-Seidel (GGS) methods are most effective than conventional Jacobi and Gauss-Seidel methods for solving linear system of equations. It is known that GJ and GGS methods converge for strictly diagonally dominant (SDD) and for M-matrices. In this paper, we study the convergence of GJ and GGS converge for symmetric positive definite (SPD) matrices, L-matrices and H-matrices. We introduce a generalization of successive overrelaxation (SOR) method for solving linear systems and discuss its convergence for the classes of SDD matrices, SPD matrices, M-matrices, L-matrices and for H-matrices. Advantages of generalized SOR method are established through numerical experiments over GJ, GGS, and SOR methods.

Keywords: convergence, Gauss-Seidel, iterative method, Jacobi, SOR

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6111 Inventory Management System of Seasonal Raw Materials of Feeds at San Jose Batangas through Integer Linear Programming and VBA

Authors: Glenda Marie D. Balitaan

Abstract:

The branch of business management that deals with inventory planning and control is known as inventory management. It comprises keeping track of supply levels and forecasting demand, as well as scheduling when and how to plan. Keeping excess inventory results in a loss of money, takes up physical space, and raises the risk of damage, spoilage, and loss. On the other hand, too little inventory frequently causes operations to be disrupted and raises the possibility of low customer satisfaction, both of which can be detrimental to a company's reputation. The United Victorious Feed mill Corporation's present inventory management practices were assessed in terms of inventory level, warehouse allocation, ordering frequency, shelf life, and production requirement. To help the company achieve their optimal level of inventory, a mathematical model was created using Integer Linear Programming. Due to the season, the goal function was to reduce the cost of purchasing US Soya and Yellow Corn. Warehouse space, annual production requirements, and shelf life were all considered. To ensure that the user only uses one application to record all relevant information, like production output and delivery, the researcher built a Visual Basic system. Additionally, the technology allows management to change the model's parameters.

Keywords: inventory management, integer linear programming, inventory management system, feed mill

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6110 Parametric Analysis of Solid Oxide Fuel Cell Using Lattice Boltzmann Method

Authors: Abir Yahya, Hacen Dhahri, Khalifa Slimi

Abstract:

The present paper deals with a numerical simulation of temperature field inside a solid oxide fuel cell (SOFC) components. The temperature distribution is investigated using a co-flow planar SOFC comprising the air and fuel channel and two-ceramic electrodes, anode and cathode, separated by a dense ceramic electrolyte. The Lattice Boltzmann method (LBM) is used for the numerical simulation of the physical problem. The effects of inlet temperature, anode thermal conductivity and current density on temperature distribution are discussed. It was found that temperature distribution is very sensitive to the inlet temperature and the current density.

Keywords: heat sources, Lattice Boltzmann method, solid oxide fuel cell, temperature

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6109 Proposed Algorithms to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis

Authors: Rami Hashish, Manon Limousis-Gayda, Caitlin McCleery

Abstract:

Introduction: Mild traumatic brain injuries, also referred to as concussions, represent an increasing burden to society. Due to limited objective diagnostic measures, concussions are diagnosed by assessing subjective symptoms, often leading to disputes to their presence. Common biomechanical measures associated with concussion are high linear and/or angular acceleration to the head. With regards to linear acceleration, approximately 80g’s has previously been shown to equate with a 50% probability of concussion. Motor vehicle collisions (MVCs) are a leading cause of concussion, due to high head accelerations experienced. The change in velocity (delta-V) of a vehicle in an MVC is an established metric for impact severity. As acceleration is the rate of delta-V with respect to time, the purpose of this paper is to determine the relation between delta-V (and occupant parameters) with linear head acceleration. Methods: A meta-analysis was conducted for manuscripts collected using the following keywords: head acceleration, concussion, brain injury, head kinematics, delta-V, change in velocity, motor vehicle collision, and rear-end. Ultimately, 280 studies were surveyed, 14 of which fulfilled the inclusion criteria as studies investigating the human response to impacts, reporting head acceleration, and delta-V of the occupant’s vehicle. Statistical analysis was conducted with SPSS and R. The best fit line analysis allowed for an initial understanding of the relation between head acceleration and delta-V. To further investigate the effect of occupant parameters on head acceleration, a quadratic model and a full linear mixed model was developed. Results: From the 14 selected studies, 139 crashes were analyzed with head accelerations and delta-V values ranging from 0.6 to 17.2g and 1.3 to 11.1 km/h, respectively. Initial analysis indicated that the best line of fit (Model 1) was defined as Head Acceleration = 0.465

Keywords: acceleration, brain injury, change in velocity, Delta-V, TBI

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6108 Production of Chromium Matrix Composite Reinforced by WC by Powder Metallurgy

Authors: Ahmet Yonetken, Ayhan Erol

Abstract:

Intermetallic materials advanced technology materials that have outstanding mechanical and physical properties for high temperature applications. Especially creep resistance, low density and high hardness properties stand out in such intermetallics. The microstructure, mechanical properties of %80Cr-%10Ti and %10WC powders were investigated using specimens produced by tube furnace sintering at 1000-1400°C temperature. A composite consisting of ternary additions, a metallic phase, Ti,Cr and WC have been prepared under Ar shroud and then tube furnace sintered. XRD, SEM (Scanning Electron Microscope), were investigated to characterize the properties of the specimens. Experimental results carried out for composition %80Cr-%10Ti and %10WC at 1400°C suggest that the best properties as 292HV and 5,34g/cm3 density were obtained at 1400°C.

Keywords: ceramic-metal, composites, powder metallurgy, sintering

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6107 DeepLig: A de-novo Computational Drug Design Approach to Generate Multi-Targeted Drugs

Authors: Anika Chebrolu

Abstract:

Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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6106 Sound Analysis of Young Broilers Reared under Different Stocking Densities in Intensive Poultry Farming

Authors: Xiaoyang Zhao, Kaiying Wang

Abstract:

The choice of stocking density in poultry farming is a potential way for determining welfare level of poultry. However, it is difficult to measure stocking densities in poultry farming because of a lot of variables such as species, age and weight, feeding way, house structure and geographical location in different broiler houses. A method was proposed in this paper to measure the differences of young broilers reared under different stocking densities by sound analysis. Vocalisations of broilers were recorded and analysed under different stocking densities to identify the relationship between sounds and stocking densities. Recordings were made continuously for three-week-old chickens in order to evaluate the variation of sounds emitted by the animals at the beginning. The experimental trial was carried out in an indoor reared broiler farm; the audio recording procedures lasted for 5 days. Broilers were divided into 5 groups, stocking density treatments were 8/m², 10/m², 12/m² (96birds/pen), 14/m² and 16/m², all conditions including ventilation and feed conditions were kept same except from stocking densities in every group. The recordings and analysis of sounds of chickens were made noninvasively. Sound recordings were manually analysed and labelled using sound analysis software: GoldWave Digital Audio Editor. After sound acquisition process, the Mel Frequency Cepstrum Coefficients (MFCC) was extracted from sound data, and the Support Vector Machine (SVM) was used as an early detector and classifier. This preliminary study, conducted in an indoor reared broiler farm shows that this method can be used to classify sounds of chickens under different densities economically (only a cheap microphone and recorder can be used), the classification accuracy is 85.7%. This method can predict the optimum stocking density of broilers with the complement of animal welfare indicators, animal productive indicators and so on.

Keywords: broiler, stocking density, poultry farming, sound monitoring, Mel Frequency Cepstrum Coefficients (MFCC), Support Vector Machine (SVM)

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6105 Detecting Earnings Management via Statistical and Neural Networks Techniques

Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

Abstract:

Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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6104 Effect of Hydrostatic Stress on Yield Behavior of the High Density Polyethylene

Authors: Kamel Hachour, Lydia Sadeg, Djamel Sersab, Tassadit Bellahcen

Abstract:

The hydrostatic stress is, for polymers, a significant parameter which affects the yield behavior of these materials. In this work, we investigate the influence of this parameter on yield behavior of the high density polyethylene (hdpe). Some tests on specimens with diverse geometries are described in this paper. Uniaxial tests: tensile on notched round bar specimens with different curvature radii, compression on cylindrical specimens and simple shear on parallelepiped specimens were performed. Biaxial tests with various combinations of tensile/compressive and shear loading on butterfly specimens were also realized in order to determine the hydrostatic stress for different states of solicitation. The experimental results show that the yield stress is very affected by the hydrostatic stress developed in the material during solicitations.

Keywords: biaxial tests, hdpe, Hydrostatic stress, yield behavior

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6103 Treatment of Leather Industry Wastewater with Advance Treatment Methods

Authors: Seval Yilmaz, Filiz Bayrakci Karel, Ali Savas Koparal

Abstract:

Textile products produced by leather have been indispensable for human consumption. Various chemicals are used to enhance the durability of end-products in the processing of leather products. The wastewaters from the leather industry which contain these chemicals exhibit toxic effects on the receiving environment and threaten the natural ecosystem. In this study, leather industry wastewater (LIW), which has high loads of contaminants, was treated using advanced treatment techniques instead of conventional methods. During the experiments, the performance of electrochemical methods was investigated. During the electrochemical experiments, the performance of batch electrooxidation (EO) using boron-doped diamond (BDD) electrodes with monopolar configuration for removal of chemical oxygen demand (COD) from LIW were investigated. The influences of electrolysis time, current density (which varies as 5 mA/cm², 10 mA/cm², 20 mA/cm², 30 mA/cm², 50 mA/cm²) and initial pH (which varies as 3,80 (natural pH of LIW), 7, 9) on removal efficiency were investigated in a batch stirred cell to determine the best treatment conditions. The current density applied to the electrochemical reactors is directly proportional to the consumption of electric energy, so electrical energy consumption was monitored during the experiment. The best experimental conditions obtained in electrochemical studies were as follows: electrolysis time = 60 min, current density = 30.0 mA/cm², pH 7. Using these parameters, 53.59% COD removal rates for LIW was achieved and total energy consumption was obtained as 13.03 kWh/m³. It is concluded that electrooxidation process constitutes a plausible and developable method for the treatment of LIW.

Keywords: BDD electrodes, COD removal, electrochemical treatment, leather industry wastewater

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6102 Predicting Radioactive Waste Glass Viscosity, Density and Dissolution with Machine Learning

Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

Abstract:

The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

Procedia PDF Downloads 117
6101 Unbalanced Cylindrical Magnetron for Accelerating Cavities Coating

Authors: G. Rosaz, V. Semblanet, S. Calatroni, A. Sublet, M. Taborelli

Abstract:

We report in this paper the design and qualification of a cylindrical unbalanced magnetron source. The dedicated magnetic assemblies were simulated using a finite element model. A hall-effect magnetic probe was then used to characterize those assemblies and compared to the theoretical magnetic profiles. These show a good agreement between the expected and actual values. The qualification of the different magnetic assemblies was then performed by measuring the ion flux density reaching the surface of the sample to be coated using a commercial retarding field energy analyzer. The strongest unbalanced configuration shows an increase from 0.016 A.cm-2 to 0.074 A.cm-2 of the ion flux density reaching the sample surface compared to the standard balanced configuration for a pressure 5.10-3 mbar and a plasma source power of 300 W.

Keywords: ion energy distribution function, magnetron sputtering, niobium, unbalanced, SRF cavities, thin film

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6100 Smart Energy Storage: W₁₈O₄₉ NW/Ti₃C₂Tₓ Composite-Enabled All Solid State Flexible Electrochromic Supercapacitors

Authors: Muhammad Hassan, Kemal Celebi

Abstract:

Developing a highly efficient electrochromic energy storage device with sufficient color fluctuation and significant electrochemical performance is highly desirable for practical energy-saving applications. Here, to achieve a highly stable material with a large electrochemical storage capacity, a W₁₈O₄₉ NW/Ti₃C₂Tₓ composite has been fabricated and deposited on a pre-assembled Ag and W₁₈O₄₉ NW conductive network by Langmuir-Blodgett technique. The resulting hybrid electrode composed of 15 layers of W₁₈O₄₉ NW/Ti₃C₂Tₓ exhibits an areal capacitance of 125 mF/cm², with a fast and reversible switching response. An optical modulation of 98.2% can be maintained at a current density of 5 mAcm⁻². Using this electrode, we fabricated a bifunctional symmetric electrochromic supercapacitor device having an energy density of 10.26 μWh/cm² and a power density of 0.605 mW/cm², with high capacity retention and full columbic efficiency over 4000 charge-discharge cycles. Meanwhile, the device displays remarkable electrochromic characteristics, including fast switching time (5 s for coloring and 7 s for bleaching) and a significant coloration efficiency of 116 cm²/C with good optical modulation stability. In addition, the device exhibits remarkable mechanical flexibility and fast switching while being stable over 100 bending cycles, which is promising for real-world applications.

Keywords: MXene, nanowires, supercapacitor, ion diffusion, electrochromic, coloration efficiency

Procedia PDF Downloads 80
6099 Reinforcement of Calcium Phosphate Cement with E-Glass Fibre

Authors: Kanchan Maji, Debasmita Pani, Sudip Dasgupta

Abstract:

Calcium phosphate cement (CPC) due to its high bioactivity and optimum bioresorbability shows excellent bone regeneration capability. Despite it has limited applications as bone implant due to its macro-porous microstructure causing its poor mechanical strength. The reinforcement of apatitic CPCs with biocompatible fibre glass phase is an attractive area of research to improve its mechanical strength. Here we study the setting behaviour of Si-doped and un-doped alpha tri-calcium phosphate (α-TCP) based CPC and its reinforcement with the addition of E-glass fibre. Alpha tri-calcium phosphate powders were prepared by solid state sintering of CaCO3, CaHPO4 and tetra ethyl ortho silicate (TEOS) was used as silicon source to synthesise Si doped α-TCP powders. Alpha tri-calcium phosphate based CPC hydrolyzes to form hydroxyapatite (HA) crystals having excellent osteoconductivity and bone-replacement capability thus self-hardens through the entanglement of HA crystals. Setting time, phase composition, hydrolysis conversion rate, microstructure, and diametral tensile strength (DTS) of un-doped CPC and Si-doped CPC were studied and compared. Both initial and final setting time of the developed cement was delayed because of Si addition. Crystalline phases of HA (JCPDS 9-432), α-TCP (JCPDS 29-359) and β-TCP (JCPDS 9-169) were detected in the X-ray diffraction (XRD) pattern after immersion of CPC in simulated body fluid (SBF) for 0 hours to 10 days. The intensities of the α-TCP peaks of (201) and (161) at 2θ of 22.2°and 24.1° decreased when the time of immersion of CPC in SBF increased from 0 hours to 10 days, due to its transformation into HA. As Si incorporation in the crystal lattice stabilised the TCP phase, Si doped CPC showed a little slower rate of conversion into HA phase as compared to un-doped CPC. The SEM image of the microstructure of hardened CPC showed lower grain size of HA in un-doped CPC because of premature setting and faster hydrolysis of un-doped CPC in SBF as compared that in Si-doped CPC. Premature setting caused generation of micro and macro porosity in un-doped CPC structure which resulted in its lower mechanical strength as compared to that in Si-doped CPC. This lower porosity and greater compactness in the microstructure attributes to greater DTS values observed in Si-doped CPC. E-glass fibres of the average diameter of 12 μm were cut into approximately 1 mm in length and immersed in SBF to deposit carbonated apatite on its surface. This was performed to promote HA crystal growth and entanglement along the fibre surface to promote stronger interface between dispersed E-glass fibre and CPC matrix. It was found that addition of 10 wt% of E-glass fibre into Si-doped α-TCP increased the average DTS of CPC from 8 MPa to 15 MPa as the fibres could resist the propagation of crack by deflecting the crack tip. Our study shows that biocompatible E-glass fibre in optimum proportion in CPC matrix can enhance the mechanical strength of CPC without affecting its bioactivity.

Keywords: Calcium phosphate cement, biocompatibility, e-glass fibre, diametral tensile strength

Procedia PDF Downloads 346
6098 On the Representation of Actuator Faults Diagnosis and Systems Invertibility

Authors: F. Sallem, B. Dahhou, A. Kamoun

Abstract:

In this work, the main problem considered is the detection and the isolation of the actuator fault. A new formulation of the linear system is generated to obtain the conditions of the actuator fault diagnosis. The proposed method is based on the representation of the actuator as a subsystem connected with the process system in cascade manner. The designed formulation is generated to obtain the conditions of the actuator fault detection and isolation. Detectability conditions are expressed in terms of the invertibility notions. An example and a comparative analysis with the classic formulation illustrate the performances of such approach for simple actuator fault diagnosis by using the linear model of nuclear reactor.

Keywords: actuator fault, Fault detection, left invertibility, nuclear reactor, observability, parameter intervals, system inversion

Procedia PDF Downloads 406
6097 Numerical Investigation of the Performance of a Vorsyl Separator Using a Euler-Lagrange Approach

Authors: Guozhen Li, Philip Hall, Nick Miles, Tao Wu, Jie Dong

Abstract:

This paper presents a Euler-Lagrange model of the water-particles multiphase flows in a Vorsyl separator where particles with different densities are separated. A series of particles with their densities ranging from 760 kg/m3 to 1380 kg/m3 were fed into the Vorsyl separator with water by means of tangential inlet. The simulation showed that the feed materials acquired centrifugal force which allows most portion of the particles with a density less than water to move to the center of the separator, enter the vortex finder and leave the separator through the bottom outlet. While the particles heavier than water move to the wall, reach the throat area and leave the separator through the side outlet. The particles were thus separated and particles collected at the bottom outlet are pure and clean. The influence of particle density on separation efficiency was investigated which demonstrated a positive correlation of the separation efficiency with increasing density difference between medium liquid and the particle. In addition, the influence of the split ratio on the performance was studied which showed that the separation efficiency of the Vorsyl separator can be improved by the increase of split ratio. The simulation also suggested that the Vorsyl separator may not function when the feeding velocity is smaller than a certain critical feeding in velocity. In addition, an increasing feeding velocity gives rise to increased pressure drop, however does not necessarily increase the separation efficiency.

Keywords: Vorsyl separator, separation efficiency, CFD, split ratio

Procedia PDF Downloads 354
6096 Processing and Evaluation of Jute Fiber Reinforced Hybrid Composites

Authors: Mohammad W. Dewan, Jahangir Alam, Khurshida Sharmin

Abstract:

Synthetic fibers (carbon, glass, aramid, etc.) are generally utilized to make composite materials for better mechanical and thermal properties. However, they are expensive and non-biodegradable. In the perspective of Bangladesh, jute fibers are available, inexpensive, and comprising good mechanical properties. The improved properties (i.e., low cost, low density, eco-friendly) of natural fibers have made them a promising reinforcement in hybrid composites without sacrificing mechanical properties. In this study, jute and e-glass fiber reinforced hybrid composite materials are fabricated utilizing hand lay-up followed by a compression molding technique. Room temperature cured two-part epoxy resin is used as a matrix. Approximate 6-7 mm thick composite panels are fabricated utilizing 17 layers of woven glass and jute fibers with different fiber layering sequences- only jute, only glass, glass, and jute alternatively (g/j/g/j---) and 4 glass - 9 jute – 4 glass (4g-9j-4g). The fabricated composite panels are analyzed through fiber volume calculation, tensile test, bending test, and water absorption test. The hybridization of jute and glass fiber results in better tensile, bending, and water absorption properties than only jute fiber-reinforced composites, but inferior properties as compared to only glass fiber reinforced composites. Among different fiber layering sequences, 4g-9j-4g fibers layering sequence resulted in better tensile, bending, and water absorption properties. The effect of chemical treatment on the woven jute fiber and chopped glass microfiber infusion are also investigated in this study. Chemically treated jute fiber and 2 wt. % chopped glass microfiber infused hybrid composite shows about 12% improvements in flexural strength as compared to untreated and no micro-fiber infused hybrid composite panel. However, fiber chemical treatment and micro-filler do not have a significant effect on tensile strength.

Keywords: compression molding, chemical treatment, hybrid composites, mechanical properties

Procedia PDF Downloads 159