Search results for: clean sport behavior

Authors: Jhansi Rani Boda, G. Sunitha

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Worldwide, the financial markets are influenced by several factors such as the changes in economic and political processes that occur in the country and the globe, information diffusion and approachability and so on. Yet, the foremost important factor is the investor’s reaction and perception. For an individual investor, decision-making process can be perceived as a continuous process that has significant impact of their psychology while making investment decisions. Behavioral finance relies on research of human and social recognition and emotional tolerance studies to identify and understand the investment decisions. This article aims to report the research of individual investor’s financial behavior in a historical perspective. This article uncovers the investor’s psychology in investment decision making focusing on the investor’s rationality with an explanation of psychological and emotional factors that affect investing. The results of the study are revealed by means of Graphical visualization.

Keywords: behavioral finance, psychology, investor’s behavior, psychological and emotional factors

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Authors: Nor Asrina Binti Ramlee

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Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: power quality, voltage sag, voltage swell, wavelet transform

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Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

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The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of the Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling human behavior. However, the exclusive use of this technology still seems insufficient to control vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: accuracy assessment, AI-driven mobility, artificial intelligence, automated vehicles

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Authors: Mafel Obhuo, Dodeye I. Igbong, Duabari S. Aziaka, Pericles Pilidis

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An important feature of the exploitation of associated gas as fuel for gas turbine engines is a declining supply. So when exploiting this resource, the divestment of prime movers is very important as the fuel supply diminishes with time. This paper explores the influence of engine degradation on the timing of divestments. Hypothetical but realistic gas turbine engines were modelled with Turbomatch, the Cranfield University gas turbine performance simulation tool. The results were deployed in three degradation scenarios within the TERA (Techno-economic and environmental risk analysis) framework to develop economic models. An optimisation with Genetic Algorithms was carried out to maximize the economic benefit. The results show that degradation will have a significant impact. It will delay the divestment of power plants, while they are running less efficiently. Over a 20 year investment, a decrease of $0.11bn, $0.26bn and $0.45bn (billion US dollars) were observed for the three degradation scenarios as against the clean case.

Keywords: economic return, flared associated gas, net present value, optimization

Procedia PDF Downloads 134

Authors: William Albeiro Alvarez, Gloria Patricia Jaramillo, Ivan Reinaldo Sarmiento

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Understanding the behavior of individuals and the different human factors that influence the choice when faced with a complex system such as transportation is one of the most complicated aspects of measuring in the components that constitute the modeling of route choice due to that various behaviors and driving mode directly or indirectly affect the choice. During the last two decades, with the development of information and communications technologies, new data collection techniques have emerged such as GPS, geolocation with mobile phones, apps for choosing the route between origin and destination, individual service transport applications among others, where an interest has been generated to improve discrete choice models when considering the incorporation of these developments as well as psychological factors that affect decision making. This paper implements a discrete choice model that proposes and estimates a hybrid model that integrates route choice models and latent variables based on the observation on the route of a sample of public taxi drivers from the city of Medellín, Colombia in relation to its behavior, personality, socioeconomic characteristics, and driving mode. The set of choice options includes the routes generated by the individual service transport applications versus the driver's choice. The hybrid model consists of measurement equations that relate latent variables with measurement indicators and utilities with choice indicators along with structural equations that link the observable characteristics of drivers with latent variables and explanatory variables with utilities.

Keywords: behavior choice model, human factors, hybrid model, real time data

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Authors: Milad Abbasi

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Carbon fiber-reinforced polymer (CFRP) composite structures are increasingly being utilized in the automotive industry due to their lightweight and specific energy absorption capabilities. Although it is impossible to predict composite mechanical properties directly using theoretical methods, various research has been conducted so far in the literature for accurate simulation of CFRP structures' energy-absorbing behavior. In this research, axial compression experiments were carried out on hand lay-up unidirectional CFRP composite tubes. The fabrication method allowed the authors to extract the material properties of the CFRPs using ASTM D3039, D3410, and D3518 standards. A neural network machine learning algorithm was then utilized to build a robust prediction model to forecast the axial compressive properties of CFRP tubes while reducing high-cost experimental efforts. The predicted results have been compared with the experimental outcomes in terms of load-carrying capacity and energy absorption capability. The results showed high accuracy and precision in the prediction of the energy-absorption capacity of the CFRP tubes. This research also demonstrates the effectiveness and challenges of machine learning techniques in the robust simulation of composites' energy-absorption behavior. Interestingly, the proposed method considerably condensed numerical and experimental efforts in the simulation and calibration of CFRP composite tubes subjected to compressive loading.

Keywords: CFRP composite tubes, energy absorption, crushing behavior, machine learning, neural network

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Authors: Kristina Pflug, Markus Busch

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

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

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Authors: Igor Svishchev, Kashif Choudhry

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Progress in advanced energy technologies is not feasible without understanding how engineering materials perform under extreme environmental conditions. The corrosion behaviour of Fe-Ni-Cr and Zr alloys has been systematically examined under high-temperature and supercritical water flow conditions. The changes in elemental release rate and dissolved gas concentration provide valuable insights into the mechanism of passivation by forming oxide films. A non-intrusive method for monitoring the extent of surface oxidation based on hydrogen release rate has been developed. This approach can be used for the on-line monitoring corrosion behavior of reactor materials without the need to interrupt the flow and remove corrosion coupons. Surface catalysed thermochemical reactions may generate sufficient hydrogen to have an effect on the accumulation of oxidizing species generated by radiolytic processes in the heat transport systems of the supercritical water cooled nuclear reactor.

Keywords: high-temperature corrosion, non-intrusive monitoring, reactor materials, supercritical water

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Authors: Vaibhav Rana, Nicholas Balaresque

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The 3-cup anemometer is the most commonly used instrument for wind speed measurement and, consequently, for the wind resource assessment. Though the cup anemometer shows accurate measurement under quasi-static conditions, there is uncertainty in the measurement when subjected to field measurement. Sensitivity to the angle of attacks with respect to horizontal plane, dynamic response, and non-linear behavior in calibration due to friction. The presented work aimed to identify the sensitivity of anemometer to non-horizontal flow. The cup anemometer was investigated under low wind speed wind tunnel, first under the static flow direction changes and second under the dynamic direction changes, at a different angle of attacks, under the similar conditions of reference wind tunnel speeds. The cup anemometer response under both conditions was evaluated and compared. The results showed the anemometer under dynamic wind direction changes is highly sensitive compared to static conditions.

Keywords: wind energy, cup anemometer, directional sensitivity, dynamic behavior, wind tunnel

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Authors: Rabindranath Jana, Biswajit Maity, Keka Rana

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The most promising clean energy source is the fuel cell, since it does not generate toxic gases and other hazardous compounds. Again the direct methanol fuel cell (DMFC) is more user-friendly as it is easy to be miniaturized and suited as energy source for automobiles as well as domestic applications and portable devices. And unlike the hydrogen used for some fuel cells, methanol is a liquid that is easy to store and transport in conventional tanks. The most important part of a fuel cell is its membrane. Till now, an overall efficiency for a methanol fuel cell is reported to be about 20 ~ 25%. The lower efficiency of the cell may be due to the critical factors, e.g. slow reaction kinetics at the anode and methanol crossover. The oxidation of methanol is composed of a series of successive reactions creating formaldehyde and formic acid as intermediates that contribute to slow reaction rates and decreased cell voltage. Currently, the investigation of new anode catalysts to improve oxidation reaction rates is an active area of research as it applies to the methanol fuel cell. Surprisingly, there are very limited reports on nanostructured membranes, which are rather simple to manufacture with different tuneable compositions and are expected to allow only the proton permeation but not the methanol due to their molecular sizing effects and affinity to the membrane surface. We have developed a nanostructured fuel cell membrane from polydimethyl siloxane rubber (PDMS), ethylene methyl co-acrylate (EMA) and multi-walled carbon nanotubes (MWNTs). The effect of incorporating different proportions of f-MWNTs in polymer membrane has been studied. The introduction of f-MWNTs in polymer matrix modified the polymer structure, and therefore the properties of the device. The proton conductivity, measured by an AC impedance technique using open-frame and two-electrode cell and methanol permeability of the membranes was found to be dependent on the f-MWNTs loading. The proton conductivity of the membranes increases with increase in concentration of f-MWNTs concentration due to increased content of conductive materials. Measured methanol permeabilities at 60oC were found to be dependant on loading of f-MWNTs. The methanol permeability decreased from 1.5 x 10-6 cm²/s for pure film to 0.8 x 10-7 cm²/s for a membrane containing 0.5wt % f-MWNTs. This is due to increasing proportion of f-MWNTs, the matrix becomes more compact. From DSC melting curves it is clear that the polymer matrix with f-MWNTs is thermally stable. FT-IR studies show good interaction between EMA and f-MWNTs. XRD analysis shows good crystalline behavior of the prepared membranes. Significant cost savings can be achieved when using the blended films which contain less expensive polymers.

Keywords: fuel cell membrane, polydimethyl siloxane rubber, carbon nanotubes, proton conductivity, methanol permeability

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Authors: Areeg Shermaddo, Abedulgader Baktheer

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Solar updraft power plants (SUPPs) made from reinforced concrete (RC) are an innovative technology to generate solar electricity. An up to 1000 m high chimney represents the major part of each SUPP ensuring the updraft of the warmed air from the ground. Numerical simulation of nonlinear behavior of such large mega shell concrete structures is a challenging task, and computationally expensive. A general finite element approach to simulate reinforced concrete bearing behavior is presented and verified on a simply supported beam, as well as the technique of submodeling. The verified numerical approach is extended and consecutively transferred to a more complex chimney structure of a SUPP. The obtained results proved the reliability of submodeling technique in analyzing critical regions of simple and complex mega concrete structures with high accuracy and dramatic decrease in the computation time.

Keywords: ABAQUS, nonlinear analysis, submodeling, SUPP

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Authors: N. Hammouda, K. Belmokre

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The paints are used extensively today in the industry to protect the metallic structures of the aggressive environments. This work is devoted to the study of corrosion resistance and aging behavior of a paint coating providing external protection for oil tankers. To avoid problems related to corrosion of these vessels, two protection modes are provided: An electro chemical active protection (cathodic protection of the hull). A passive protection by external painting. Investigations are conducted using stationary and non-stationary electro chemical tools such as electro chemical impedance spectroscopy has allowed us to characterize the protective qualities of these films. The application of the EIS on our damaged in-situ painting shows the existence of several capacitive loops which is an indicator of the failure of our tested paint. Microscopic analysis (micrograph) helped bring essential elements in understanding the degradation of our paint condition and immersion training corrosion products.

Keywords: epoxy paints, electrochemical impedance spectroscopy, corrosion mechanisms, seawater

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Authors: Chanida Tangjai Benchalak Muangmeesri, Dechrit Maneetham

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Collection of marine garbage in the modern world, where technology is vital to existence. Consequently, technology can assist in reducing the duplicate labor in the subject of collecting trash in the water that must be done the same way repeatedly owing to the consequence of suffering an emerging disease or COVID-19. This is due to the rapid advancement of technology. As a result, solid trash and plastic garbage are increasing. Agricultural gardens, canals, ponds, and water basins are all sources of water. Building boat-like instruments for rubbish collection in the water will be done this time. It has two control options, boat control via remote control and boat control via an Internet of Things system. A solar panel with a power output of 40 watts powers the system being able to store so accurate and precise waste collection, allowing for thorough water cleaning. The primary goals are to keep the water's surface clean and assess its quality to support the aquatic ecology.

Keywords: automatic boat, water treatment, cleaning machine, iot

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Authors: M. H. Arslan, U. K. Sahin, H. Acikgoz-Tufan, I. Gocek, I. Erdem

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Various exterior factors have perpetual effects on textile materials during wear, use and laundering in everyday life. In accordance with their frequency of use, textile materials are required to be laundered at certain intervals. The medium in which the laundering process takes place have inevitable detrimental physical and chemical effects on textile materials caused by the unique parameters of the process inherently existing. Connatural structures of various textile materials result in many different physical, chemical and mechanical characteristics. Because of their specific structures, these materials have different behaviors against several exterior factors. By modeling the behavior of commercial and test textiles as group-wise against laundering process, it is possible to disclose the relation in between these two groups of materials, which will lead to better understanding of their behaviors in terms of similarities and differences against the washing parameters of the laundering. Thus, the goal of the current research is to examine the behavior of two groups of textile materials as commercial textiles and as test textiles towards the main washing machine parameters during laundering process such as temperature, load quantity, mechanical action and level of water amount by concentrating on shrinkage, pilling, sewing defects, collar abrasion, the other defects other than sewing, whitening and overall properties of textiles. In this study, cotton fabrics were preferred as commercial textiles due to the fact that garments made of cotton are the most demanded products in the market by the textile consumers in daily life. Full factorial experimental set-up was used to design the experimental procedure. All profiles always including all of the commercial and the test textiles were laundered for 20 cycles by commercial home laundering machine to investigate the effects of the chosen parameters. For the laundering process, a modified version of ‘‘IEC 60456 Test Method’’ was utilized. The amount of detergent was altered as 0.5% gram per liter depending on varying load quantity levels. Datacolor 650®, EMPA Photographic Standards for Pilling Test and visual examination were utilized to test and characterize the textiles. Furthermore, in the current study the relation in between commercial and test textiles in terms of their performance was deeply investigated by the help of statistical analysis performed by MINITAB® package program modeling their behavior against the parameters of the laundering process. In the experimental work, the behaviors of both groups of textiles towards washing machine parameters were visually and quantitatively assessed in dry state.

Keywords: behavior against washing machine parameters, performance evaluation of textiles, statistical analysis, commercial and test textiles

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Authors: B. K. Sahoo

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Superior thermoelectric (TE) efficiency of AlₓIn₁₋ₓN /GaN heterostructure (HS) requires a minimum value of thermal conductivity (k). A smaller k would lead to even further increase of TE figure of merit (ZT). The built-in polarization (BIP) electric field of AlₓIn₁₋ₓN /GaN HS enhances S, and σ of the HS, however, the effect of BIP field on k of the HS has not been explored. Study of thermal conductivities (k: without BIP and kp: including BIP) vs temperature predicts pyroelectric behavior of HS. Both k and kp show crossover at a temperature Tp. The result shows that below Tp, kp < k due to negative thermal expansion coefficient (TEC). However, above Tp, kp > k. Above Tp, piezoelectric polarization dominates over spontaneous polarization due to positive TEC. This generates more lattice mismatch resulting in the significant contribution of BIP field to thermal conductivity. Thus, Tp can be considered as primary pyroelectric transition temperature of the material as above Tp thermal expansion takes place which is the reason for the secondary pyroelectric effect. It is found that below Tp, kp is decreased; thus enhancing TE efficiency. For x=0.1, 0.2 and 0.3; Tp are close to 200, 210 and 260 K, respectively. Thus, k of the HS can be modified as per requirement by tailoring the Al composition; making it suitable simultaneously for the design of high-temperature pyroelectric sensors and TE module for maximum power production.

Keywords: AlₓIn₁₋ₓN/GaN heterostructure, built in polarization, pyroelectric behavior, thermoelectric efficiency

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Authors: Maarten J. Van der Burgt

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A universe containing matter and antimatter can only exist when matter and antimatter repel each other. Such a system, where like attracts like and like repels unlike, will always expand. Calculations made for such a symmetric universe demonstrate that the expansion is consistent with Hubble’s law, the observed increase in the expansion velocity with time, the initial high acceleration and the foam structure of the universe. Conversely, these observations can be considered as proof for a symmetrical universe and for antimatter possessing a negative gravitational mass. A second proof can be found by reinterpreting the behavior of relativistic moving charged particles. Attributing their behavior to a charge defect of √(1-v2/c2) instead of to a mass defect of 1/√(1-v2/c2) makes it plausible that gravitation is an electromagnetic force, as already suggested by Feynman. This would automatically imply that antimatter has a negative gravitational mass. These proofs underpin the untenability of the Weak Equivalence Principle which states that in a gravitational field all structure less point-like particles follow the same path.

Keywords: celestial mechanics, cosmology, gravitation astrophysics, origin of structure, miscellaneous (matter and antimatter)

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Authors: Nur Hidayah Kaz Abdul Aziz, Norhalida Hashim, Zurina Hassan

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Peripartum period is a time where women are vulnerable to depression, and stress may further increase the risk of its occurrence. Use of selective serotonin reuptake inhibitors (SSRI) in the treatment of postpartum depression is a common practice. Comparison of antidepressant treatment, however, is rarely studied between gestated and nulliparous animals exposed to stress. This study was aimed to investigate the effect of parity and stress, as well as fluoxetine (an SSRI) treatment after stress exposure on the behavior of rats. Gestating and nulliparous Sprague Dawley rats were either subjected to chronic stressors or left undisturbed throughout the gestation period. After parturition, all stressors were stopped and some of the stressed rats were treated with fluoxetine (10mg/kg). Hence, the final groups formed were: 1. Non-stressed nulliparous rats, 2. Non-stressed dams, 3. Stressed nulliparous rats, 4. Stressed dams, 5. Fluoxetine-treated stressed nulliparous rats, and 6. Fluoxetine-treated stressed dams. Rats were tested in open field test (OFT), novel object recognition test (NOR) and forced swim test (FST) after weaning of pups. Gestational stress significantly reduced the locomotor activity of rats in OFT (p<0.05), while fluoxetine significantly increased the activity in nulliparous rats (p<0.001) but not the dams. While no differences were observed in NOR, stress and parity inhibited the rats from performing swimming behavior in FST. However, climbing and immobile behaviors in FST were found to have no significant differences, although there is a tendency of effect of treatment for immobility parameter (p=0.06) where fluoxetine-treated stressed dams were being the least immobile. In conclusion, the effects of parity and stress, as well as fluoxetine treatment, depended on the type of behavioral test performed.

Keywords: stress, parity, SSRI, behavioral tests

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Authors: Meng-Cong Zheng, Yu-Sheng Chen

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The meeting behavior is a pervasive kind of interaction, which often occurs between the passenger and the shuttle. However, the meeting point set up at the Taoyuan International Airport is too far from the entry-exit, often causing passengers to stop searching near the entry-exit. When the number of people waiting for the rush hour increases, it often results in chaos in the waiting area. This study tried to find out what is the key factor to promote the rapid finding of each other between the passengers and the pick-ups. Then we implemented several design proposals to improve the meeting behavior of passengers and pick-ups based on behavior mapping and post-occupancy evaluation to enhance their meeting efficiency in unfamiliar environments. The research base is the reception hall of the second terminal of Taoyuan International Airport. Behavioral observation and mapping are implemented on the entry of inbound passengers into the welcome space, including the crowd distribution of the people who rely on the separation wall in the waiting area, the behavior of meeting and the interaction between the inbound passengers and the pick-ups. Then we redesign the space planning and signage design based on post-occupancy evaluation to verify the effectiveness of space plan and signage design. This study found that passengers ignore existing meeting-point designs which are placed on distant pillars at both ends. The position of the screen affects the area where the receiver is stranded, causing the pick-ups to block the passenger's moving line. The pick-ups prefer to wait where it is easy to watch incoming passengers and where it is closest to the mode of transport they take when leaving. Large visitors tend to gather next to landmarks, and smaller groups have a wide waiting area in the lobby. The location of the meeting point chosen by the pick-ups is related to the view of the incoming passenger. Finally, this study proposes an improved design of the meeting point, setting the traffic information in it, so that most passengers can see the traffic information when they enter the country. At the same time, we also redesigned the pick-ups desk to improve the efficiency of passenger meeting.

Keywords: meeting point design, post-occupancy evaluation, behavioral mapping, international airport

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Authors: Shih-Ching Wang, Mark Lang

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This paper examines the secondary effects and consequences of special displays on subsequent shopping behavior. Special displays are studied as a prominent form of in-store or shopper marketing activity. Two experiments are performed using special value and special quality-oriented displays in an online simulated store environment. The impact of exposure to special displays on mindsets and resulting product choices are tested in a shopping task. Impact on store image is also tested. The experiments find that special displays do trigger shopping mindsets that affect product choices and shopping basket composition and value. There are intended and unintended positive and negative effects found. Special value displays improve store price image but trigger a price sensitive shopping mindset that causes more lower-priced items to be purchased, lowering total basket dollar value. Special natural food displays improve store quality image and trigger a quality-oriented mindset that causes fewer lower-priced items to be purchased, increasing total basket dollar value. These findings extend the theories of product categorization, mind-sets, and price sensitivity found in communication research into the retail store environment. Findings also warn retailers to consider the total effects and consequences of special displays when designing and executing in-store or shopper marketing activity.

Keywords: special displays, mindset, shopping behavior, price consciousness, product categorization, store image

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Authors: Nikhil Jain, Yang Xu, Bin Yu

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The material behavior of graphene, a single layer of carbon lattice, is extremely sensitive to its dielectric environment. We demonstrate improvement in electronic performance of graphene nanowire interconnects with full encapsulation by lattice-matching, chemically inert, 2D layered insulator hexagonal boron nitride (h- BN). A novel layer-based transfer technique is developed to construct the h-BN/MLG/h-BN heterostructures. The encapsulated graphene wires are characterized and compared with that on SiO2 or h-BN substrate without passivating h-BN layer. Significant improvements in maximum current-carrying density, breakdown threshold, and power density in encapsulated graphene wires are observed. These critical improvements are achieved without compromising the carrier transport characteristics in graphene. Furthermore, graphene wires exhibit electrical behavior less insensitive to ambient conditions, as compared with the non-passivated ones. Overall, h-BN/graphene/h- BN heterostructure presents a robust material platform towards the implementation of high-speed carbon-based interconnects.

Keywords: two-dimensional nanosheet, graphene, hexagonal boron nitride, heterostructure, interconnects

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Authors: Jo Kwang-Won, Lee Ho-Jun, Choi In-Rak, Park Hong-Gun

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Prefabricated angle truss composited beam is a kind of concrete encased composite beam. It is prefabricated at factory as Pratt truss with steel members. Double angle is used for top, bottom chords and vertical web member. Moreover, diagonal web member is steel plate. Its sectional shape looks like I-shape. This beam system has two stages. The first is construction stage in which the beam is directly connected to the column for resist construction load. This stage beam consists of Pratt truss and precast concrete. The stability of the beam is verified. The second is service stage. After the connection, cast-in-place concrete is used for composite action. Ultimate flexural capacity is verified and show advantage than RC and steel. In this paper, the beam flexural capacity is verified in both stages. And examined the flexural behavior of the beam.

Keywords: composite beam, prefabrication, angle, precast concrete, pratt truss

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Authors: Antoni Grau, Yolanda Bolea, Alberto Sanfeliu

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Mobile robots can be used in many different applications, including mapping, search, rescue, reconnaissance, hazard detection, and carpet cleaning, exploration, etc. However, they are limited due to their reliance on traditional energy sources such as electricity and oil which cannot always provide a convenient energy source in all situations. In an ever more eco-conscious world, solar energy offers the most environmentally clean option of all energy sources. Electricity presents threats of pollution resulting from its production process, and oil poses a huge threat to the environment. Not only does it pose harm by the toxic emissions (for instance CO2 emissions), it produces the combustion process necessary to produce energy, but there is the ever present risk of oil spillages and damages to ecosystems. Solar energy can help to mitigate carbon emissions by replacing more carbon intensive sources of heat and power. The challenge of this work is to propose the design and the implementation of electric battery recharge stations. Those recharge docks are based on the use of renewable energy such as solar energy (with photovoltaic panels) with the object to reduce the CO2 emissions. In this paper, a comparative study of the CO2 emission productions (from the use of different energy sources: natural gas, gas oil, fuel and solar panels) in the charging process of the Segway PT batteries is carried out. To make the study with solar energy, a photovoltaic panel, and a Buck-Boost DC/DC block has been used. Specifically, the STP005S-12/Db solar panel has been used to carry out our experiments. This module is a 5Wp-photovoltaic (PV) module, configured with 36 monocrystalline cells serially connected. With those elements, a battery recharge station is made to recharge the robot batteries. For the energy storage DC/DC block, a series of ultracapacitors have been used. Due to the variation of the PV panel with the temperature and irradiation, and the non-integer behavior of the ultracapacitors as well as the non-linearities of the whole system, authors have been used a fractional control method to achieve that solar panels supply the maximum allowed power to recharge the robots in the lesser time. Greenhouse gas emissions for production of electricity vary due to regional differences in source fuel. The impact of an energy technology on the climate can be characterised by its carbon emission intensity, a measure of the amount of CO2, or CO2 equivalent emitted by unit of energy generated. In our work, the coal is the fossil energy more hazardous, providing a 53% more of gas emissions than natural gas and a 30% more than fuel. Moreover, it is remarkable that existing fossil fuel technologies produce high carbon emission intensity through the combustion of carbon-rich fuels, whilst renewable technologies such as solar produce little or no emissions during operation, but may incur emissions during manufacture. The solar energy thus can help to mitigate carbon emissions.

Keywords: autonomous robots, CO2 emissions, DC/DC buck-boost, solar energy

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Authors: Nadia Hammouda, Kamel Belmokre

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Organic coatings are widely employed in the corrosion protection of most metal surfaces, particularly steel. They provide a barrier against corrosive species present in the environment, due to their high resistance to oxygen, water and ions transport. This study focuses on the evaluation of corrosion protection performance of epoxy paint on the carbon steel surface in sea water by Electrochemical Impedance Spectroscopy (EIS). The electrochemical behavior of painted surface was estimated by EIS parameters that contained paint film resistance, paint film capacitance and double layer capacitance. On the basis of calculation using EIS spectrums it was observed that pore resistance (Rpore) decreased with the appearance of doubled layer capacitance (Cdl) due to the electrolyte penetration through the film. This was further confirmed by the decrease of diffusion resistance (Rd) which was also the indicator of the deterioration of paint film protectiveness.

Keywords: epoxy paints, carbon steel, electrochemical impedance spectroscopy, corrosion mechanisms, sea water

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Authors: Mohd. Ashik Shahrier, Hiromi Wada

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Prenatal ethanol exposure has potential to induce difficulties in the social behavior of rats and can alter pup-dam communication suggesting that deficits in pups could result in altered dam behavior, which in turn could result in more aberrant behavior in the pup. Ultrasonic vocalization (USV) is a sensitive tool for investigating social behavior between rat pups and their dam. Rat pups produce USVs on separation from their dam. This signals the dam to locate her pups and retrieve them back to the nest. In this study, it was predicted that prenatal ethanol exposure cause alterations on the acoustic characteristics of USVs in rat pups. Thirteen pregnant rats were purchased and randomly assigned into three groups: high-ethanol (n = 4), low-ethanol (n = 5), and control (n = 4) groups. Laboratory ethanol (purity = 99.5%) was dissolved in tap water and administered to the high- and low-ethanol groups as drinking water from gestational days (GD) 8-20. Ethanol-containing water was administered to the animals in three stages by gradually increasing the concentration between GDs 8–20. From GDs 8–10, 10% and 5%, from GDs 11–13, 20% and 10%, and from GDs 14–20, 30% and 15% ethanol-containing water (v/v) was administered to the high- and low-ethanol groups, respectively. Tap water without ethanol was given to the control group throughout the experiment. The day of birth of the pups was designated as postnatal day (PND) 0. On PND 4, each litter was culled to four male and four female pups. For the present study, two male and two female pups were randomly sampled from each litter as subjects. Thus, eight male and eight female pups from the high-ethanol and control groups and another 10 male and 10 female pups from the low-ethanol group, were sampled. An ultrasonic microphone and the Sonotrack system version 2.4.0 (Metris, Hoofddorp, The Netherlands) were used to record and analyze USVs of the pups. On postnatal days 4, 8, 12 and 16, the resultant pups were individually isolated from their dams and littermates, and USVs were recorded for 5 min in a sound-proof box. Pups in the high-ethanol group produced greater number of USVs compared with that in both low-ethanol and control groups on PND 12. Rat pups in the high-ethanol group also produced higher mean, minimum, and maximum fundamental frequencies of USVs compared with that in both low-ethanol and control groups. Male pups in the high-ethanol group had higher USV amplitudes than in those in low-ethanol and control groups on PND 12. These results suggest that pups in the high-ethanol group relatively experienced more negative emotionality due to the ethanol-induced neuronal activation in the core limbic system and tegmental structures and accordingly, produced altered USVs as distress calls.

Keywords: emotionality, ethanol, maternal separation, ultrasonic vocalization

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: Carlos M. Parra, Matthew Sutherland, Ranjita Poudel

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Reduced mental-bandwidth related to low socioeconomic status (low-SES) might lead to impulsivity and risk-taking behavior, which poses as a major hurdle towards asset building (savings) behavior. Understanding the relationship between risk-related personality metrics as well as laboratory risk behavior and real-life savings behavior can help facilitate the development of effective asset building programs, which are vital for mitigating financial vulnerability and income inequality. As such, this study explored the relationship between personality metrics, laboratory behavior in a risky decision-making task and real-life asset building (savings) behaviors among individuals with low-SES from Miami, Florida (FL). Study participants (12 male, 15 female) included racially and ethnically diverse adults (mean age 41.22 ± 12.65 years), with incomplete higher education (18% had High School Diploma, 30% Associates, and 52% Some College), and low annual income (mean $13,872 ± $8020.43). Participants completed eight self-report surveys and played a widely used risky decision-making paradigm called the Balloon Analogue Risk Task (BART). Specifically, participants played three runs of BART (20 trials in each run; total 60 trials). In addition, asset building behavior data was collected for 24 participants who opened and used savings accounts and completed a 6-month savings program that involved monthly matches, and a final reward for completing the savings program without any interim withdrawals. Each participant’s total savings at the end of this program was the main asset building indicator considered. In addition, a new effective use of average pump bet (EUAPB) indicator was developed to characterize each participant’s ability to place winning bets. This indicator takes the ratio of each participant’s total BART earnings to average pump bet (APB) in all 60 trials. Our findings indicated that EUAPB explained more than a third of the variation in total savings among participants. Moreover, participants who managed to obtain BART earnings of at least 30 cents out of their APB, also tended to exhibit better asset building (savings) behavior. In particular, using this criterion to separate participants into high and low EUAPB groups, the nine participants with high EUAPB (mean BART earnings of 35.64 cents per APB) ended up with higher mean total savings ($255.11), while the 15 participants with low EUAPB (mean BART earnings of 22.50 cents per APB) obtained lower mean total savings ($40.01). All mean differences are statistically significant (2-tailed p  .0001) indicating that the relation between higher EUAPB and higher total savings is robust. Overall, these findings can help refine asset building interventions implemented by policy makers and practitioners interested in reducing financial vulnerability among low-SES population. Specifically, by helping identify individuals who are likely to readily take advantage of savings opportunities (such as matched savings programs) and avoiding the stipulation of unnecessary and expensive financial coaching programs to these individuals. This study was funded by J.P. Morgan Chase (JPMC) and carried out by scientists from Florida International University (FIU) in partnership with Catalyst Miami.

Keywords: balloon analogue risk task (BART), matched savings programs, asset building capability, low-SES participants

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Authors: Mohamed M. El Gendy, Ibrahim A. El Arabi, Rafeek W. Abdel-Missih, Omar A. Kandil

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Nonlinear analysis is one of the most important design and safety tools in structural engineering. Based on the finite-element method, a geometrical and material nonlinear analysis of large span reinforced concrete arches is carried out considering soil-structure interaction. The concrete section details and reinforcement distribution are taken into account. The behavior of soil is considered via Winkler's and continuum models. A computer program (NARC II) is specially developed in order to follow the structural behavior of large span reinforced concrete arches up to failure. The results obtained by the proposed model are compared with available literature for verification. This work confirmed that the geometrical and material nonlinearities, as well as soil structure interaction, have considerable influence on the structural response of reinforced concrete arches.

Keywords: nonlinear analysis, reinforced concrete arched structure, soil-structure interaction, geotechnical engineering

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Authors: Tithdanin Chav, Phichhang Ou

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The study is about the e-banking consumer behavior of five major banks in Cambodia. This work aims to examine the relationships among job relevance, trust, mobility, perceived ease of use, perceived usefulness, attitude toward using, and intention to use of internet banking and apps. Also, the research develops and tests a conceptual model of intention to use internet banking by integrating the Technology Acceptance Model (TAM) and job relevance, trust, and mobility which were supported by Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB). The proposed model was tested using Structural Equation Modeling (SEM), which was processed by using SPSS and AMOS with a sample size of 250 e-banking users. The results showed that there is a significant positive relationship among variables and attitudes toward using internet banking, and apps are the most factor influencing consumers’ intention to use internet banking and apps with the importance level in SEM 0.82 accounted by 82%. Significantly, all six hypotheses were accepted.

Keywords: bank apps, consumer intention, internet banking, technology acceptance model, TAM

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Authors: Juan C. Sanchez, Jose L. Endrino, Alejandro Toro, Hugo A. Estupinan, Glenn Leighton

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For years, the reduction of friction and wear has been a matter of interest in the engineering field. Several solutions have been proposed to address this issue, including the use of lubricants and coatings to reduce the frictional forces and to increase the surface wear resistance. Alternatively, texturing processes have been used in a wide variety of materials, in many cases inspired in natural surfaces. Nature has shown how species adapt to the environment and the engineers try to understand natural surfaces for particular applications by analyzing outstanding species such as gecko for high adhesion, lotus leaves for hydrophobicity, sharks for reduced flow resistance and snakes for optimized frictional response. Texturized surfaces have shown a superior performance in terms of the frictional response in many situations, and the control of its behavior greatly depends on the manufacturing process. The focus of this work is to evaluate the tribological behavior of AISI 52100 steel samples texturized by Photochemical Machining (PCM). The surface texture was inspired by several features of the snakeskin such as aspect ratio of fibrils and mean fibril spacing. Two coatings were applied on the texturized surface, namely Diamond-like Carbon (DLC) and Molybdenum Disulphide (MoS₂), and their tribological behavior after pin-on-disk tests were compared with that of the non-texturized and uncovered surfaces. The samples were characterised through Stereoscopic Microscope (SM), Scanning Electron Microscope (SEM), Optical Microscope (OM), Profilometer, Raman Spectrometer (RS) and X-Ray Diffractometer (XRD). The Coefficient of Friction (COF) measured in pin-on-disk tests showed correlations with the sliding direction (relative to the texture features) and the aspect ratio of the texture features. Regarding the coated surfaces, the DLC and MoS₂ coating had a good performance in terms of wear rate and coefficient of friction compared with the uncoated and non-texturized surfaces. On the other hand, for the uncoated surfaces, the texture showed an influence in the tribological performance with respect to the non-texturized surface.

Keywords: coating, coefficient of friction, deterministic surface, photochemical machining

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Authors: Ahmed I. Osman, Jehad K. Abu-Dahrieh, David W. Rooney, Jillian Thompson

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The effect of loading of copper on the catalytic performance of different alumina support during the dehydration of methanol to dimethyl ether (DME) was performed in a fixed bed reactor. There are two levels of loading; low loading (1, 2, 4 and 6% Cu wt/wt) and high loading (10 and 15% Cu wt/wt) on both AC350 (alumina catalyst calcined at 350) and AC550 (alumina catalyst calcined at 550), to study the effect of loading and the effect of the support during methanol dehydration to DME (MTD). The catalysts were characterized by TGA, XRD, BET, TPD-NH3, TEM and DRIFT-Pyridine. Under reaction conditions where the temperature ranged from 180-300˚C with a WHSV= 12.1 h-1 it was found that all the catalysts calcined at 550˚C showed higher activity than those calcined at 350˚C. In this study, the optimum catalyst was 6% Cu/AC550. This catalyst showed a high degree of stability, had one half activity of the pure catalyst (AC550) and double the activity of the optimum catalyst calcined at 350˚C (6% Cu/AC350). So, we recommended 6% Cu/AC550 for the production of DME from methanol.

Keywords: bio-fuel, nano composite catalyst, DME, Cu-Al2O3

Procedia PDF Downloads 296