Search results for: slope stability analysis

Authors: B. E. Tarazona-Romero, J. G. Ascanio-Villabona, O. Lengerke-Perez, A. D. Rincon-Quintero, C. L. Sandoval-Rodriguez

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Desalination offers solutions for the shortage of water in the world, however, the process of eliminating salts generates a by-product known as brine, generally eliminated in the environment through techniques that mitigate its impact. Brine treatment techniques are vital to developing an environmentally sustainable desalination process. Consequently, this document evaluates three different geometric configurations of solar stills as an alternative for brine treatment to be integrated into a low-scale desalination process. The geometric scenarios to be studied were selected because they have characteristics that adapt to the concept of appropriate technology; low cost, intensive labor and material resources for local manufacturing, modularity, and simplicity in construction. Additionally, the conceptual design of the collectors was carried out, and the ray tracing methodology was applied through the open access software SolTrace and Tonatiuh. The simulation process used 600.00 rays and modified two input parameters; direct normal radiation (DNI) and reflectance. In summary, for the scenarios evaluated, the ladder-type distiller presented higher efficiency values compared to the pyramid-type and single-slope collectors. Finally, the efficiency of the collectors studied was directly related to their geometry, that is, large geometries allow them to receive a greater number of solar rays in various paths, affecting the efficiency of the device.

Keywords: appropriate technology, brine treatment techniques, desalination, monte carlo ray tracing

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Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

Procedia PDF Downloads 511

Authors: Minhyuk Heo, Jihwan Yun, Seonghun Park

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It has been reported that intervertebral fusion surgery, which removes most of the ligaments and muscles of the spine, increases the degenerative disease in adjacent spinal segments. Therefore, it is required to develop a lumbar interspinous process fixation device that minimizes the risks and side effects from the surgery. The objective of the current study is to design an interspinous process fixation device with simple structures in order to minimize soft tissue removal and operation time during intervertebral fusion surgery. For the design concepts of a lumbar fixation device, the principle of the ratchet was first applied on the joining parts of the device in order to shorten the operation time. The coil spring structure was selected for connecting parts between the spinous processes so that a normal range of motion in spinal segments is preserved and degenerative spinal diseases are not developed in the adjacent spinal segments. The stiffness of the spring was determined not to interrupt the motion of a lumbar spine. The designed value of the spring stiffness allows the upper part of the spring to move ~10° which is higher than the range of flexion and extension for normal lumbar spine (6°-8°), when a moment of 10Nm is applied on the upper face of L1. A finite element (FE) model composed of L1 to L5 lumbar spines was generated to verify the mechanical integrity and the dynamic stability of the designed lumbar fixation device and to further optimize the lumbar fixation device. The FE model generated above produced the same pressure value on intervertebral disc and dynamic behavior as the normal intact model reported in the literature. The consistent results from this comparison validates the accuracy in the modeling of the current FE model. Currently, we are trying to generate an abnormal model with defects in one or more components of the normal FE model above. Then, the mechanical integrity and the dynamic stability of the designed lumbar fixation device will be analyzed after being installed in the abnormal model and then the lumbar fixation device will be further optimized.

Keywords: lumbar interspinous process fixation device, finite element method, lumbar spine, kinematics

Procedia PDF Downloads 217

Authors: Sayali Vyas, Atharva Desai, Shreyas Badave, Apurv Kulkarni, B. Rajiv

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The Failure Modes and Effect Analysis (FMEA) is an efficient evaluation technique to identify potential failures in products, processes, and services. FMEA is designed to identify and prioritize failure modes. It proves to be a useful method for identifying and correcting possible failures at its earliest possible level so that one can avoid consequences of poor performance. In this paper, FMEA tool is used in detection of failures of various components of heat exchanger cycle and to identify critical failures of the components which may hamper the system’s performance. Further, a detailed Pareto analysis is done to find out the most critical components of the cycle, the causes of its failures, and possible recommended actions. This paper can be used as a checklist which will help in maintainability of the system.

Keywords: FMEA, heat exchanger cycle, Ishikawa diagram, pareto analysis, RPN (Risk Priority Number)

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Authors: N. F. Hanna, A. M. Haridy

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One of the main drawbacks of the Modal Pushover Analysis (MPA) is the need to perform nonlinear time-history analysis, which complicates the analysis method and time. A simplified version of the MPA has been proposed based on the concept of the inelastic deformation ratio. Furthermore, the effect of the higher modes of vibration is considered by assuming linearly-elastic responses, which enables the use of standard elastic response spectrum analysis. In this thesis, the simplified MPA (SMPA) method is applied to determine the target global drift and the inter-story drifts of steel frame building. The effect of the higher vibration modes is considered within the framework of the SMPA. A comprehensive survey about the inelastic deformation ratio is presented. After that, a suitable expression from literature is selected for the inelastic deformation ratio and then implemented in the SMPA. The estimated seismic demands using the SMPA, such as target drift, base shear, and the inter-story drifts, are compared with the seismic responses determined by applying the standard MPA. The accuracy of the estimated seismic demands is validated by comparing with the results obtained by the nonlinear time-history analysis using real earthquake records.

Keywords: modal analysis, pushover analysis, seismic performance, target displacement

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Authors: Harsh Agarwal, Pratikkumar Patel, Maharshi Pathak

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Recently the low prices of Crude oil and increase in strict environmental regulations limit limits the use of diesel based muds as these muds are relatively costlier and toxic, as a result disposal of cuttings into the eco-system is a major issue faced by the drilling industries. To overcome these issues faced by the Oil Industry, an attempt has been made to develop oil-in-water emulsion mud system using nettlespurge oil. Nettlespurge oil could be easily available and its cost is around ₹30/litre which is about half the price of diesel in India. Oil-based mud (OBM) was formulated with Nettlespurge oil extracted from Nettlespurge seeds using the Soxhlet extraction method. The formulated nettlespurge oil mud properties were analysed with diesel oil mud properties. The compared properties were rheological properties, yield point and gel strength, and mud density and filtration loss properties, fluid loss and filter cake. The mud density measurement showed that nettlespurge OBM was slightly higher than diesel OBM with mud density values of 9.175 lb/gal and 8.5 lb/gal, respectively, at barite content of 70 g. Thus it has a higher lubricating property. Additionally, the filtration loss test results showed that nettlespurge mud fluid loss volumes, oil was 11 ml, compared to diesel oil mud volume of 15 ml. The filtration loss test indicated that the nettlespurge oil mud with filter cake thickness of 2.2 mm had a cake characteristic of thin and squashy while the diesel oil mud resulted in filter cake thickness of 2.7 mm with cake characteristic of tenacious, rubbery and resilient. The filtration loss test results showed that nettlespurge oil mud fluid loss volumes was much less than the diesel based oil mud. The filtration loss test indicated that the nettlespurge oil mud filter cake thickness less than the diesel oil mud filter cake thickness. So Low formation damage and the emulsion stability effect was analysed with this experiment. The nettlespurge oil-in-water mud system had lower coefficient of friction than the diesel oil based mud system. All the rheological properties have shown better results relative to the diesel based oil mud. Therefore, with all the above mentioned factors and with the data of the conducted experiment we could conclude that the Nettlespurge oil based mud is economically and well as eco-logically much more feasible than the worn out and shabby diesel-based oil mud in the Drilling Industry.

Keywords: economical feasible, ecological feasible, emulsion stability, nettle spurge oil, rheological properties, soxhlet extraction method

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Authors: Wassima El Mofid, Svetlozar Ivanov, Andreas Bund

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The increasing requirements for high power and energy lithium ion batteries have led to the development of several classes of positive electrode materials. Among those one promising material is LiNixMnyCo1−x−yO2 due to its high reversible capacity and remarkable cycling performance. Further structural stabilization and improved electrochemical performance of this class of cathode materials can be achieved by cationic substitution to a transition metal such as Al, Mg, Cr, etc. The current study discusses a novel NMC type material obtained by simultaneous cationic substitution of the cobalt which is a toxic element, with aluminum and iron. A compound with the composition LiNi0.6Mn0.2Co0.15Al0.025Fe0.025O2 (NMCAF) was synthesized by the self-combustion method using sucrose as fuel. The material has a layered α-NaFeO2 type structure with a good hexagonal ordering. Rietveld refinement analysis of the XRD patterns revealed a very low cationic mixing compared to the non-substituted material LiNi0.6Mn0,2Co0.2O2 suggesting a structural stabilization. Galvanostatic cycling measurements indicate improved electrochemical performance after the metal substitution. An initial discharge capacity of about 190 mAh.g−1 at slow rate (C/20), and a good cycling stability even at moderately faster rates (C/5 and C) have been observed. The long term cycling displayed a capacity retention of about 90% after 10 cycles.

Keywords: cationic substitution, lithium ion batteries, positive electrode material, self-combustion synthesis method

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Authors: B. Engel, Sara Salman Hassan Al-Maeeni

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Human consumption of the Earth's resources increases the need for a sustainable development as an important ecological, social, and economic theme. Re-engineering of machine tools, in terms of design and failure analysis, is defined as steps performed on an obsolete machine to return it to a new machine with the warranty that matches the customer requirement. To understand the future fatigue behavior of the used machine components, it is important to investigate the possible causes of machine parts failure through design, surface, and material inspections. In this study, the failure modes of the shaft of the rotary draw bending machine are inspected. Furthermore, stress and deflection analysis of the shaft subjected to combined torsion and bending loads are carried out by an analytical method and compared with a finite element analysis method. The theoretical fatigue strength, correction factors, and fatigue life sustained by the shaft before damaged are estimated by creating a stress-cycle (S-N) diagram. In conclusion, it is seen that the shaft can work in the second life, but it needs some surface treatments to increase the reliability and fatigue life.

Keywords: failure analysis, fatigue life, FEM analysis, shaft, stress analysis

Procedia PDF Downloads 277

Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Document Analysis is an important research field that aims to gather the information by analyzing the data in documents. As one of the important targets for many fields is to understand what people actually want, sentimental analysis field has been one of the vital fields that are tightly related to the document analysis. This research focuses on analyzing text documents to classify each document according to its opinion. The aim of this research is to detect the emotions from text documents based on enriching the lexicon with adapting their content based on semantic patterns extraction. The proposed approach has been presented, and different experiments are applied by different perspectives to reveal the positive impact of the proposed approach on the classification results.

Keywords: document analysis, sentimental analysis, emotion detection, WEKA tool, NRC lexicon

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Authors: Maged El Osta, Milad Masoud

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Al Jabal Al Akhdar in the north-eastern part of Libya represents a region with promising ecological underpinning for grazing and other agricultural developments. The groundwater potential of both Upper Cretaceous and Eocene aquifers was studied based the available literature and a complete database for about 112 water wells drilled in the period 2003-2009. In this research, the hydrogeological methods will be integrated with the Geographic Information System (GIS) that played a main role in highlighting the spatial characteristics of the groundwater system. The results indicate that the depth to water for the Upper Cretaceous aquifer ranges from 150 to 458 m, and the piezometric surface decreases from over 500 m (m.s.l) in the northern parts to -20 m (m.s.l) in southeastern part. Salinity ranges between 303 and 1329 mg/l indicating that groundwater belongs to the slightly fresh water class. In the Eocene aquifer, the depth to groundwater ranges from 120 to 290.5 m and the potentiometric level decreases gradually southwards from 220 to -51 m (m.s.l) and characterized by steep slope in the southeastern part of the study area, where the aquifer characterized by relatively high productivity (specific capacity ranges between 10.08 and 332.3 m2/day). The groundwater salinity within this aquifer ranges between 198 and 2800 mg/l (fresh to brackish water class). The annual average rainfall (from 280 to 500 mm) plays a significant role in the recharge of the two aquifers. The priority of groundwater quality and potentiality increases towards the central and northern portions of the concerned area.

Keywords: Eocene and Upper Cretaceous aquifers, rainfall, potentiality, Geographic Information System (GIS)

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Jisun Lee, Jay Hyoun Kwon

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As an alternative way to compensate the INS (inertial navigation system) error in non-GNSS (Global Navigation Satellite System) environment, geophysical database referenced navigation is being studied. In this study, both gravity gradient and terrain data were combined to complement the weakness of sole geophysical data as well as to improve the stability of the positioning. The main process to compensate the INS error using geophysical database was constructed on the basis of the EKF (Extended Kalman Filter). In detail, two type of combination method, centralized and decentralized filter, were applied to check the pros and cons of its algorithm and to find more robust results. The performance of each navigation algorithm was evaluated based on the simulation by supposing that the aircraft flies with precise geophysical DB and sensors above nine different trajectories. Especially, the results were compared to the ones from sole geophysical database referenced navigation to check the improvement due to a combination of the heterogeneous geophysical database. It was found that the overall navigation performance was improved, but not all trajectories generated better navigation result by the combination of gravity gradient with terrain data. Also, it was found that the centralized filter generally showed more stable results. It is because that the way to allocate the weight for the decentralized filter could not be optimized due to the local inconsistency of geophysical data. In the future, switching of geophysical data or combining different navigation algorithm are necessary to obtain more robust navigation results.

Keywords: Extended Kalman Filter, geophysical database referenced navigation, gravity gradient, terrain

Procedia PDF Downloads 333

Authors: Noor S. Nasri, Eric C. A. Tatt, Usman D. Hamza, Jibril Mohammed, Husna M. Zain

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Climate change has becoming a global environmental issue that may trigger irreversible changes in the environment with catastrophic consequences for human, animals and plants on our planet. Methane, carbon dioxide and nitrous oxide are the greenhouse gases (GHG) and as the main factor that significantly contributes to the global warming. Mainly carbon dioxide be produced and released to atmosphere by thermal industrial and power generation sectors. Methane is dominant component of natural gas releases significant of thermal heat, and the gaseous pollutants when homogeneous thermal combustion takes place at high temperature. Heterogeneous catalytic Combustion (HCC) principle is promising technologies towards environmental friendly energy production should be developed to ensure higher yields with lower pollutants gaseous emissions and perform complete combustion oxidation at moderate temperature condition as comparing to homogeneous high thermal combustion. Hence the principle has become a very interesting alternative total oxidation for the treatment of pollutants gaseous emission especially NOX product formation. Noble metals are dispersed on a support-porous HCC such as γ- Al2O3, TiO2 and ThO2 to increase thermal stability of catalyst and to increase to effectiveness of catalytic combustion. Support-porous HCC material to be selected based on factors of the surface area, porosity, thermal stability, thermal conductivity, reactivity with reactants or products, chemical stability, catalytic activity, and catalyst life. γ- Al2O3 with high catalytic activity and can last longer life of catalyst, is commonly used as the support for Pd catalyst at low temperatures. Sustainable and renewable support-material of bio-mass char was derived from agro-industrial waste material and used to compare with those the conventional support-porous material. The abundant of biomass wastes generated in palm oil industries is one potential source to convert the wastes into sustainable material as replacement of support material for catalysts. Objective of this study was to compare the kinetic rate of reaction the combustion of methane on Palladium (Pd) based catalyst with Al2O3 support and bio-char (Bc) support derived from shell kernel. The 2wt% Pd was prepared using incipient wetness impregnation method and the HCC performance was accomplished using tubular quartz reactor with gas mixture ratio of 3% methane and 97% air. Material characterization was determined using TGA, SEM, and BET surface area. The methane porous-HCC conversion was carried out by online gas analyzer connected to the reactor that performed porous-HCC. BET surface area for prepared 2 wt% Pd/Bc is smaller than prepared 2wt% Pd/ Al2O3 due to its low porosity between particles. The order of catalyst activity based on kinetic rate on reaction of catalysts in low temperature is prepared 2wt% Pd/Bc > calcined 2wt% Pd/ Al2O3 > prepared 2wt% Pd/ Al2O3 > calcined 2wt% Pd/Bc. Hence the usage of agro-industrial bio-mass waste material can enhance the sustainability principle.

Keywords: catalytic-combustion, environmental, support-bio-char material, sustainable and renewable material

Procedia PDF Downloads 380

Authors: Gulcin Yildiz, Hao Feng

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Soybean proteins are the most widely used and researched proteins in the food industry. Due to soy allergies among consumers, however, alternative legume proteins having similar functional properties have been studied in recent years. These alternative proteins are also expected to have a price advantage over soy proteins. One such protein that has shown good potential for food applications is pea protein. Besides the favorable functional properties of pea protein, it also contains fewer anti-nutritional substances than soy protein. However, a comparison of the physicochemical properties of pea protein isolate (PPI)-starch nanocomplexes and soy protein isolate (SPI)-starch nanocomplexes treated by ultrasound has not been well documented. This study was undertaken to investigate the effects of ultrasound treatment on the physicochemical properties of PPI-starch and SPI-starch nanocomplexes. Pea protein isolate (85% pea protein) provided by Roquette (Geneva, IL, USA) and soy protein isolate (SPI, Pro-Fam® 955) obtained from the Archer Daniels Midland Company were adjusted to different pH levels (2-12) and treated with 5 minutes of ultrasonication (100% amplitude) to form complexes with starch. The soluble protein content was determined by the Bradford method using BSA as the standard. The turbidity of the samples was measured using a spectrophotometer (Lambda 1050 UV/VIS/NIR Spectrometer, PerkinElmer, Waltham, MA, USA). The volume-weighted mean diameters (D4, 3) of the soluble proteins were determined by dynamic light scattering (DLS). The emulsifying properties of the proteins were evaluated by the emulsion stability index (ESI) and emulsion activity index (EAI). Both the soy and pea protein isolates showed a U-shaped solubility curve as a function of pH, with a high solubility above the isoelectric point and a low one below it. Increasing the pH from 2 to 12 resulted in increased solubility for both the SPI and PPI-starch complexes. The pea nanocomplexes showed greater solubility than the soy ones. The SPI-starch nanocomplexes showed better emulsifying properties determined by the emulsion stability index (ESI) and emulsion activity index (EAI) due to SPI’s high solubility and high protein content. The PPI had similar or better emulsifying properties at certain pH values than the SPI. The ultrasound treatment significantly decreased the particle sizes of both kinds of nanocomplex. For all pH levels with both proteins, the droplet sizes were found to be lower than 300 nm. The present study clearly demonstrated that applying ultrasonication under different pH conditions significantly improved the solubility and emulsify¬ing properties of the SPI and PPI. The PPI exhibited better solubility and emulsifying properties than the SPI at certain pH levels

Keywords: emulsifying properties, pea protein isolate, soy protein isolate, ultrasonication

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Authors: E. Arcos, E. Bautista, F. Méndez

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In this work, a scaling analysis of the liquefaction phenomena is presented. The characteristic scales are obtained by balancing term by term of the well-known partial dynamics governing equations, (U − P). From the above, the order of magnitude of the horizontal displacement is very smaller compared with the vertical displacement and therefore the governing equation is only a function of the dependent vertical variables. The U − P approximation is reduced and presented in its dimensionless version. This scaling analysis can be used to obtain analytical solutions of the liquefaction phenomena under the action of the water waves.

Keywords: approximation U-P, porous seabed, scaling analysis, water waves

Procedia PDF Downloads 335

Authors: Fernando Martinez Soto, Gaetano Di Mino

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The application of rubber into bituminous mixtures requires attention and care during mixing and compaction. Rubber modifies the properties because it reacts in the internal structure of bitumen at high temperatures changing the performance of the mixture (interaction process of solvents with binder-rubber aggregate). The main change is the increasing of the viscosity and elasticity of the binder due to the larger sizes of the rubber particles by dry process but, this positive effect is counteracted by short mixing times, compared to wet technology, and due to the transport processes, curing time and post-compaction of the mixtures. Therefore, negative effects as swelling of rubber particles, rebounding effect of the specimens and thermal changes by different expansion of the structure inside the mixtures, can change the mechanical properties of the rubberized blends. Based on the dry technology, different asphalt-rubber binders using devulcanized or natural rubber (truck and bus tread rubber), have served to demonstrate these effects and how to solve them into two dense-gap graded rubber modified asphalt concrete mixes (RUMAC) to enhance the stability, workability and durability of the compacted samples by Superpave gyratory compactor method. This paper specifies the procedures developed in the Department of Civil Engineering of the University of Palermo during September 2016 to March 2017, for characterizing the post-compaction and mix-stability of the one conventional mixture (hot mix asphalt without rubber) and two gap-graded rubberized asphalt mixes according granulometry for rail sub-ballast layers with nominal size of Ø22.4mm of aggregates according European standard. Thus, the main purpose of this laboratory research is the application of ambient ground rubber from scrap tires processed at conventional temperature (20ºC) inside hot bituminous mixtures (160-220ºC) as a substitute for 1.5%, 2% and 3% by weight of the total aggregates (3.2%, 4.2% and, 6.2% respectively by volumetric part of the limestone aggregates of bulk density equal to 2.81g/cm³) considered, not as a part of the asphalt binder. The reference bituminous mixture was designed with 4% of binder and ± 3% of air voids, manufactured for a conventional bitumen B50/70 at 160ºC-145ºC mix-compaction temperatures to guarantee the workability of the mixes. The proportions of rubber proposed are #60-40% for mixtures with 1.5 to 2% of rubber and, #20-80% for mixture with 3% of rubber (as example, a 60% of Ø0.4-2mm and 40% of Ø2-4mm). The temperature of the asphalt cement is between 160-180 ºC for mixing and 145-160 ºC for compaction, according to the optimal values for viscosity using Brookfield viscometer and 'ring and ball' - penetration tests. These crumb rubber particles act as a rubber-aggregate into the mixture, varying sizes between 0.4mm to 2mm in a first fraction, and 2-4mm as second proportion. Ambient ground rubber with a specific gravity of 1.154g/cm³ is used. The rubber is free of loose fabric, wire, and other contaminants. It was found optimal results in real beams and cylindrical specimens with each HMA mixture reducing the swelling effect. Different factors as temperature, particle sizes of rubber, number of cycles and pressures of compaction that affect the interaction process are explained.

Keywords: crumb-rubber, gyratory compactor, rebounding effect, superpave mix-design, swelling, sub-ballast railway

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Authors: Zety Shakila Binti Mohd Yusof, Muhammad Adib Bin Ishak, Hajah Fatimah Binti Hussein

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The international shipping business is related to numerous controls or regulations of export and import shipments. It is costly and time consuming, and when something goes wrong or when the buyer or seller fails to comply with the regulations, it can result in penalties, delays, and unexpected costs etc. For the focus of this study, the researchers have selected a local forwarder that provides forwarding and clearance services, Nexus Zone Logistics. It was identified that this company currently has many extra costs to be paid including local and detention charges, which negatively impacts the flow of income and reduces overall stability. Two variables have been identified as factors of extra charges; loaded containers entering the port by exceeded closing time and late delivery of empty containers to the container yard. This study is a qualitative in nature and the secondary data collected was analyzed using self-administered observation. The findings of this study were covered by one selected case for each export and import shipment between July and December 2014. The data were analyzed using frequency analysis based on tables and graphs. The researcher recommends Nexus Zone Logistics impose a 1% deposit payment per container for each shipment (export and import) to its customers.

Keywords: international shipping, export and import, detention charges, container shipment

Procedia PDF Downloads 367

Authors: M. S. Abd El-Sadek, M. A. Omar, Gharib M. Taha

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In recent years, photocatalytic degradation of various kinds of organic and inorganic pollutants using semiconductor powders as photocatalysts has been extensively studied. Owing to its relatively high photocatalytic activity, biological and chemical stability, low cost, nonpoisonous and long stable life, Tin oxide materials have been widely used as catalysts in chemical reactions, including synthesis of vinyl ketone, oxidation of methanol and so on. Tin oxide (SnO₂), with a rutile-type crystalline structure, is an n-type wide band gap (3.6 eV) semiconductor that presents a proper combination of chemical, electronic and optical properties that make it advantageous in several applications. In the present work, SnO₂ nanoparticles were synthesized at room temperature by the sol-gel process and thermohydrolysis of SnCl₂ in isopropanol by controlling the crystallite size through calculations. The synthesized nanoparticles were identified by using XRD analysis, TEM, FT-IR, and Uv-Visible spectroscopic techniques. The crystalline structure and grain size of the synthesized samples were analyzed by X-Ray diffraction analysis (XRD) and the XRD patterns confirmed the presence of tetragonal phase SnO₂. In this study, Methylene blue degradation was tested by using SnO₂ nanoparticles (at different calculations temperatures) as a photocatalyst under sunlight as a source of irradiation. The results showed that the highest percentage of degradation of Methylene blue dye was obtained by using SnO₂ photocatalyst at calculations temperature 800 ᵒC. The operational parameters were investigated to be optimized to the best conditions which result in complete removal of organic pollutants from aqueous solution. It was found that the degradation of dyes depends on several parameters such as irradiation time, initial dye concentration, the dose of the catalyst and the presence of metals such as silver as a dopant and its concentration. Percent degradation was increased with irradiation time. The degradation efficiency decreased as the initial concentration of the dye increased. The degradation efficiency increased as the dose of the catalyst increased to a certain level and by further increasing the SnO₂ photocatalyst dose, the degradation efficiency is decreased. The best degradation efficiency on which obtained from pure SnO₂ compared with SnO₂ which doped by different percentage of Ag.

Keywords: SnO₂ nanoparticles, a sol-gel method, photocatalytic applications, methylene blue, degradation efficiency

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Khaled Harrar, Rachid Jennane

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The purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an age-matched control group of 28 women using texture analysis based on fractals. Two pre-processing approaches are applied on radiographic images; these techniques are compared to highlight the choice of the pre-processing method. Furthermore, the values of the fractal dimension are compared to those of the fractal signature in terms of the classification of the two populations. In a second analysis, the BMD measure at proximal femur was compared to the fractal analysis, the latter, which is a non-invasive technique, allowed a better discrimination; the results confirm that the fractal analysis of texture on calcaneus radiographs is able to discriminate osteoporotic patients with femoral fracture from controls. This discrimination was efficient compared to that obtained by BMD alone. It was also present in comparing subgroups with overlapping values of BMD.

Keywords: osteoporosis, fractal dimension, fractal signature, bone mineral density

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Authors: Alina P. Colling, Robert G. Hekkenberg

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Recent years have seen extensive technological advancement in truck platooning, as reflected in the literature. Its main benefits are the improvement of traffic stability and the reduction of air drag, resulting in less fuel consumption, in comparison to using individual trucks. Platooning is now being adapted to the waterborne transport sector in the NOVIMAR project through the development of a Vessel Train (VT) concept. The main focus of VT’s, as opposed to the truck platoons, is the decrease in manning on board, ultimately working towards autonomous vessel operations. This crew reduction can prove to be an important selling point in achieving economic competitiveness of the waterborne approach when compared to alternative modes of transport. This paper discusses the expected benefits and drawbacks of the VT concept, in terms of the technical logistic performance and generalized costs. More specifically, VT’s can provide flexibility in destination choices for shippers but also add complexity when performing special manoeuvres in VT formation. In order to quantify the cost and performances, a model is developed and simulations are carried out for various case studies. These compare the application of VT’s in the short sea and inland water transport, with specific sailing regimes and technologies installed on board to allow different levels of autonomy. The results enable the identification of the most important boundary conditions for the successful operation of the waterborne platooning concept. These findings serve as a framework for future business applications of the VT.

Keywords: autonomous vessels, NOVIMAR, vessel trains, waterborne platooning

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Authors: Maassoumeh Bemani Naeini

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Studies on interlanguage have long been engaged in describing the phenomenon of variation in SLA. Pursuing the same goal and particularly addressing the role of linguistic features, this study describes the use of Persian morphology in the interlanguage of two adult English-speaking learners of Persian L2. Taking the general approach of a combination of contrastive analysis, error analysis and interlanguage analysis, this study focuses on the identification and prediction of some possible instances of transfer from English L1 to Persian L2 across six elicitation tasks aiming to investigate whether any of contextual features may variably influence the learners’ order of morpheme accuracy in the areas of copula, possessives, articles, demonstratives, plural form, personal pronouns, and genitive cases.  Results describe the existence of task variation in the interlanguage system of Persian L2 learners.

Keywords: English L1, Interlanguage Analysis, Persian L2, SLA variation

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Asli Beyler Çi̇ği̇l, Memet Vezi̇r Kahraman

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Organic–inorganic hybrids have become an effective source of advanced materials because they combine the advantages of both the organic moiety such as flexibility, low dielectric constant, and processability, and inorganic moiety as rigidity, strength, durability, and thermal stability. By incorporating cross-linkable side chains, the hybrid materials can be made photosensitive and UV curable, which offers many advantages including low processing temperature, low equipment cost and compatibility. In this study, uv-curable organic-inorganic hybrid material, which was contained surface modified polyaniline particles (PANI), was prepared. PANI surface photografted with hydroxy ethyl methacrylate (HEMA) to produce hydroxyl groups. Hydroxyl functionalized PANI/HEMA was acrylated using isocyanato ethyl methacrylate (IEM) in order to improve the dispersion and interfacial interaction in composites. UV-curable formulation was prepared by mixing the surface modified PANI, polyethylene glycol diacrylate (PEGDA), trimethylolpropane triacrylate (TMPTA), hydrolized 3- methacryloxypropyltrimethoxysilane (hyd. MEMO) and photoinitiator. Chemical structure of nano-hybrid material was characterized by FTIR. FTIR spectra showed that the photografting of PANI was prepared successfully. Thermal properties of the nano-hybrid material were determined by thermogravimetric analysis (TGA). The morphology of the nano-hybrid material was performed by scanning electron microscopy (SEM).

Keywords: polyaniline, photograft, sol-gel, uv-curable polymer

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Authors: Marziyeh Yousefi, Hossein Nassaji

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This paper reports the results of a meta-analysis of studies on the effects of instruction mode on learning second language pragmatics during the last decade (from 2006 to 2016). After establishing related inclusion/ exclusion criteria, 39 published studies were retrieved and included in the present meta-analysis. Studies were later coded for face-to-face and computer-assisted mode of instruction. Statistical procedures were applied to obtain effect sizes. It was found that Computer-Assisted-Language-Learning studies generated larger effects than Face-to-Face instruction.

Keywords: meta-analysis, effect size, L2 pragmatics, comprehensive meta-analysis, face-to-face, computer-assisted language learning

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Authors: Safak Baykal

Abstract:

The purpose of this study is analyzing the relationship between self leadership and social capital of people with using Social Network Analysis. In this study, two aspects of social capital will be focused: bonding, homophilous social capital (BoSC) which implies better, strong, dense or closed network ties, and bridging, heterophilous social capital (BrSC) which implies weak ties, bridging the structural holes. The other concept of the study is Trust (Tr), namely interpersonal trust, willingness to ascribe good intentions to and have confidence in the words and actions of other people. In this study, the sample group, 61 people, was selected from a private firm from the defense industry. The relation between BoSC/BrSC and Tr is shown by using Social Network Analysis (SNA) and statistical analysis with Likert type-questionnaire. The results of the analysis show the Cronbach’s alpha value is 0.73 and social capital values (BoSC/BrSC) is highly correlated with Tr values of the people.

Keywords: bonding social capital, bridging social capital, trust, social network analysis (SNA)

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Authors: Hema V. Vanar, R. K. Soni, N. D. Shah

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Slabs supported directly on columns without beams are known as Flat slabs. Flat slabs are highly versatile elements widely used in construction, providing minimum depth, fast construction and allowing flexible column grids. The main objective of this thesis is comparison of analytical method and soft ware for analysis of flat slab subjected to various parametric loadings. Study presents analysis of flat slab is performed under different types of gravity.

Keywords: fat slab, parametric load, analysis, software

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Authors: Hyungoo Kang, Minsung Kim, Jinkoo Kim

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This study investigates the performance of a 2D and 3D steel moment frame subjected to vehicle collision at a first story column using LS-DYNA. The finite element models of vehicles provided by the National Crash Analysis Center (NCAC) are used for numerical analysis. Nonlinear dynamic time history analysis of the 2D and 3D model structures are carried out based on the arbitrary column removal scenario, and the vertical displacement of the damaged structures are compared with that obtained from collision analysis. The analysis results show that the model structure remains stable when the speed of the vehicle is 40km/h. However, at the speed of 80 and 120km/h both the 2D and 3D structures collapse by progressive collapse. The vertical displacement of the damaged joint obtained from collision analysis is significantly larger than the displacement computed based on the arbitrary column removal scenario.

Keywords: vehicle collision, progressive collapse, FEM, LS-DYNA

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Authors: Marziyeh Khavari

Abstract:

In recent decades, climate change, global warming, and the growing population worldwide face some challenges, such as increasing food consumption and shortage of resources. Assessing how climate change could disturb crops, especially hazelnut production, seems crucial for sustainable agriculture production. For hazelnut cultivation in the mid-warm condition, such as in Iran, here we present an investigation of climate parameters and how much they are effective on fertility and nut production of hazelnut trees. Therefore, the climate change of the northern zones in Iran has investigated (1960-2017) and was reached an uptrend in temperature. Furthermore, the descriptive analysis performed on six cultivars during seven years shows how this small-scale survey could demonstrate the effects of climate change on hazelnut production and stability. Results showed that some climate parameters are more significant on nut production, such as solar radiation, soil temperature, relative humidity, and precipitation. Moreover, some cultivars have produced more stable production, for instance, Negret and Segorbe, while the Mervill de Boliver recorded the most variation during the study. Another aspect that needs to be met is training and predicting an actual model to simulate nut production through a neural network and linear regression simulation. The study developed and estimated the ANN model's generalization capability with different criteria such as RMSE, SSE, and accuracy factors for dependent and independent variables (environmental and yield traits). The models were trained and tested while the accuracy of the model is proper to predict hazelnut production under fluctuations in weather parameters.

Keywords: climate change, neural network, hazelnut, global warming

Procedia PDF Downloads 116

Authors: Keisuke Takahata, Hiroshi Suetsugu

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Forest height is an important parameter for forest biomass estimation, and precise elevation data is essential for accurate forest height estimation. There are several globally or nationally available digital elevation models (DEMs) like SRTM and ASTER. However, its accuracy is reported to be low particularly in mountainous areas where there are closed canopy or steep slope. Recently, space-borne LiDAR, such as the Global Ecosystem Dynamics Investigation (GEDI), have started to provide sparse but accurate ground elevation and canopy height estimates. Several studies have reported the high degree of accuracy in their elevation products on their exact footprints, while it is not clear how this sparse information can be used for wider area. In this study, we developed a digital terrain model correction algorithm by spatially interpolating the difference between existing DEMs and GEDI elevation products by using Gaussian Process (GP) regression model. The result shows that our GP-based methodology can reduce the mean bias of the elevation data from 3.7m to 0.3m when we use airborne LiDAR-derived elevation information as ground truth. Our algorithm is also capable of quantifying the elevation data uncertainty, which is critical requirement for biomass inventory. Upcoming satellite-LiDAR missions, like MOLI (Multi-footprint Observation Lidar and Imager), are expected to contribute to the more accurate digital terrain model generation.

Keywords: digital terrain model, satellite LiDAR, gaussian processes, uncertainty quantification

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