Search results for: hybrid nanostructures

Authors: Gondrexon, Gonon, Mendil-Jakani, Mareau

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Proton Exchange Membrane Fuel Cells (PEMFCs) seems to be a promising device used for converting hydrogen into electricity. PEMFC is made of a Membrane Electrode Assembly (MEA) composed of a Proton Exchange Membrane (PEM) sandwiched by two catalytic layers. Nowadays, specific performances are targeted in order to ensure the long-term expansion of this technology. Current polymers used (perfluorinated as Nafion®) are unsuitable (loss of mechanical properties) for the high-temperature range. To overcome this issue, sulfonated polyaromatic polymers appear to be a good alternative since it has very good thermomechanical properties. However, their proton conductivity and chemical stability (oxidative resistance to H2O2 formed during fuel cell (FC) operating) are very low. In our team, we patented an original concept of hybrid membranes able to fulfill the specific requirements for PEMFC. This idea is based on the improvement of commercialized polymer membrane via an easy and processable stabilization thanks to sol-gel (SG) chemistry with judicious embeded chemical functions. This strategy is thus breaking up with traditional approaches (design of new copolymers, use of inorganic charges/additives). In 2020, we presented the elaboration and functional properties of a 1st generation of hybrid membranes with promising performances and durability. The latter was made by self-condensing a SG phase with 3(mercaptopropyl)trimethoxysilane (MPTMS) inside a commercial sPEEK host membrane. The successful in-situ condensation reactions of the MPTMS was demonstrated by measures of mass uptakes, FTIR spectroscopy (presence of C-Haliphatics) and solid state NMR 29Si (T2 & T3 signals of self-condensation products). The ability of the SG phase to prevent the oxidative degradation of the sPEEK phase (thanks to thiol chemical functions) was then proved with H2O2 accelerating tests and FC operating tests. A 2nd generation made of thiourea functionalized SG precursors (named HTU & TTU) was made after. By analysing in depth the morphologies of these different hybrids by direct space analysis (AFM/SEM/TEM) and reciprocal space analysis (SANS/SAXS/WAXS), we highlighted that both SG phase morphology and its localisation into the host has a huge impact on the PEM functional properties observed. This relationship is also dependent on the chemical function embedded. The hybrids obtained have shown very good chemical resistance during aging test (exposed to H2O2) compared to the commercial sPEEK. But the chemical function used is considered as “sacrificial” and cannot react indefinitely with H2O2. Thus, we are now working on a 3rd generation made of both sacrificial/regenerative chemical functions which are expected to inhibit the chemical aging of sPEEK more efficiently. With this work, we are confident to reach a predictive approach of the key parameters governing the final properties.

Keywords: fuel cells, ionomers, membranes, sPEEK, chemical stability

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Authors: Faris A. Uriayer, Mehtab Alam

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The concept of using a hybrid composite by combining two or more different materials to produce bilinear stress–strain behaviour has become a subject of interest. Having studied the mechanical properties of steel-CFRP specimens (CFRP Laminate Sandwiched between Mild Steel Strips), full size steel-CFRP composite reinforcement were fabricated and used as a new reinforcing material inside beams in lieu of traditional steel bars. Four beams, three beams reinforced with steel-CFRP composite reinforcement and one beam reinforced with traditional steel bars were cast, cured and tested under quasi-static loading. The flexural test results of the beams reinforced with this composite reinforcement showed that the beams with steel-CFRP composite reinforcement had comparable flexural strength and flexural ductility with beams reinforced with traditional steel bars.

Keywords: CFRP laminate, steel strip, flexural behaviour, modified model, concrete beam

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Authors: Lucille Lok-Sun Ngan

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There are significant gaps in both the migration and family literatures regarding the gendered parenting of Chinese migrants. Evidence from the literature informs us that the child-focused parenting style of the West has altered, with positive consequences, parent–child relationships in migrant families. In particular, second-generation migrants have developed hybrid identities distinct from those of their overseas-born parents and the locals. On returning to their place of origin, they may undergo yet another process of change in values, and in behaviour, in order to adapt to the local culture. As migration changes values, personality and practice at personal, interpersonal and familial levels, the cross-cultural experiences of returnees inevitably affect their own fatherhood journeys in their country of origin. This paper reviews current literature on fatherhood and migration and identifies the gaps and limitations that pertain to understanding the paternal experiences of Chinese return migrants.

Keywords: Chinese returnees, cross-cultural experiences, fatherhood, hybridity, migration

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Authors: Makhan Maharjan, Mani Ulaganathan, Vanchiappan Aravindan, Srinivasan Madhavi, Jing-Yuan Wang, Tuti Mariana Lim

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There is great interest to exploit sustainable, low-cost, renewable resources as carbon precursors for energy storage applications. Research on development of energy storage devices has been growing rapidly due to mismatch in power supply and demand from renewable energy sources This paper reported the synthesis of porous activated carbon from biomass waste and evaluated its performance in supercapicators. In this work, we employed orange peel (waste material) as the starting material and synthesized activated carbon by pyrolysis of KOH impregnated orange peel char at 800 °C in argon atmosphere. The resultant orange peel-derived activated carbon (OP-AC) exhibited a high BET surface area of 1,901 m2 g-1, which is the highest surface area so far reported for the orange peel. The pore size distribution (PSD) curve exhibits the pores centered at 11.26 Å pore width, suggesting dominant microporosity. The OP-AC was studied as positive electrode in combination with different negative electrode materials, such as pre-lithiated graphite (LiC6) and Li4Ti5O12 for making different hybrid capacitors. The lithium ion capacitor (LIC) fabricated using OP-AC with pre-lithiated graphite delivered a high energy density of ~106 Wh kg–1. The energy density for OP-AC||Li4Ti5O12 capacitor was ~35 Wh kg–1. For comparison purpose, configuration of OP-AC||OP-AC capacitors were studied in both aqueous (1M H2SO4) and organic (1M LiPF6 in EC-DMC) electrolytes, which delivered the energy density of 6.6 Wh kg-1 and 16.3 Wh kg-1, respectively. The cycling retentions obtained at current density of 1 A g–1 were ~85.8, ~87.0 ~82.2 and ~58.8% after 2500 cycles for OP-AC||OP-AC (aqueous), OP-AC||OP-AC (organic), OP-AC||Li4Ti5O12 and OP-AC||LiC6 configurations, respectively. In addition, characterization studies were performed by elemental and proximate composition, thermogravimetry, field emission-scanning electron microscopy, Raman spectra, X-ray diffraction (XRD) pattern, Fourier transform-infrared, X-ray photoelectron spectroscopy (XPS) and N2 sorption isotherms. The morphological features from FE-SEM exhibited well-developed porous structures. Two typical broad peaks observed in the XRD framework of the synthesized carbon implies amorphous graphitic structure. The ratio of 0.86 for ID/IG in Raman spectra infers high degree of graphitization in the sample. The band spectra of C 1s in XPS display the well resolved peaks related to carbon atoms in various chemical environments; for instances, the characteristics binding energies appeared at ~283.83, ~284.83, ~286.13, ~288.56, and ~290.70 eV which correspond to sp2 -graphitic C, sp3 -graphitic C, C-O, C=O and π-π*, respectively. Characterization studies revealed the synthesized carbon to be promising electrode material towards the application for energy storage devices. The findings opened up the possibility of developing high energy LICs from abundant, low-cost, renewable biomass waste.

Keywords: lithium-ion capacitors, orange peel, pre-lithiated graphite, supercapacitors

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Authors: Yingxin Hui

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Understanding seismic response feature of the bridges crossing fault is the basis of the seismic fortification. Taking a multi-span bridge crossing active fault under construction as an example, the seismic ground motions at bridge site were generated following hybrid simulation methodology. Multi-support excitations displacement input models and nonlinear time history analysis was used to calculate seismic response of structures, and the results were compared with bridge in the near-fault region. The results showed that the seismic response features of bridges crossing fault were different from the bridges in the near-fault region. The design according to the bridge in near-fault region would cause the calculation results with insecurity and non-reasonable if the effect of cross the fault was ignored. The design of seismic fortification should be based on seismic response feature, which could reduce the adverse effect caused by the structure damage.

Keywords: bridge engineering, seismic response feature, across faults, rupture directivity effect, fling step

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Authors: Brandtner-Hafner Martin

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Adhesives have established themselves as an innovative joining technology in the industry. Their strengths lie in joining different materials, avoiding structural weakening as in welding or screwing, and enabling lightweight construction methods. Now there are a variety of ways to improve the efficiency and effectiveness of bonded joints. One way is to add fiber fillers. This leads to an improvement in adhesion and cohesion (structural integrity). In this study, the effectiveness of fiber-modified adhesives for bonding different construction materials is reviewed. A series of experimental tests were performed using the fracture analytical GF principle to study the adhesive bonding safety and performance of the joint. Three different structural adhesive systems based on epoxy, CA/A hybrid, and PUR were modified with different fiber materials on different substrates. The results show that significant performance improvements can be achieved and that bonding reliability can be sustainably increased.

Keywords: fiber-modified adhesives, bonding safety, GF-principle, fracture analysis

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Authors: Rashid Mahmood, Muhammad Sufyan, Nasir Ahmed

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The MANETs have lessened transportation and decentralized network. There are numerous basis of routing protocols. We derived the MANETs protocol into three major categories like Reactive, Proactive and hybrid. In these protocols, we discussed only some protocols like Distance Sequenced Distance Vector (DSDV), Ad hoc on Demand Distance Vector (AODV) and Dynamic Source Routing (DSR). The AODV and DSR are both reactive type of protocols. On the other hand, DSDV is proactive type protocol here. We compare these routing protocols for network security estimated by network simulator (NS-2). In this dissertation some parameters discussed such as simulation time, packet size, number of node, packet delivery fraction, push time and speed etc. We will construct all these parameters on routing protocols under suitable conditions for network security measures.

Keywords: DSDV, AODV, DSR NS-2, PDF, push time

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: S. A. Naeini, A. Khalili

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Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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Authors: Robin Molinier

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Industrial symbiosis (I.S) deals with the exchange of waste materials, fatal energy and utilities as resources for production. While it brings environmental benefits from resource conservation its economic profitability is one of the main barriers to its implementation. I.S involves several actors with their own objectives and resources so that each actor must be satisfied by ex-ante arrangements to commit toward investments and transactions. Regarding I.S Transaction cost economics helps to identify hybrid forms of governance for transactions governance due to I.S projects specificities induced by the need for customization (asset specificity, non-homogeneity). Thus we propose a framework to analyze the best contractual practices tailored to address I.S specific risks that we identified as threefold (load profiles and quality mismatch, value fluctuations). Schemes from cooperative game theory and contracting management are integrated to analyze value flows between actors. Contractual guidelines are then proposed to address the identified risks and to split the value for a set of I.S archetypes drawn from actual experiences.

Keywords: contracts, economics, industrial symbiosis, risks

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Authors: Lee Artz

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This presentation outlines US media frames of recent interventions in Iraq, Afghanistan, and Syria and their impact on global media and public discourse. A content analysis of sources, descriptors, and contexts of leading US media (AP, New York Times, Fox News) finds that news coverage highlights terrorism, justifies military action, and downplays the human costs. These media frames that normalize intervention also omit coverage of the environmental consequences of war, with scant or no reporting on pollution, destruction and contamination of agricultural infrastructures and the difficulty of any environmentally sustainable recovery. A content analysis of leading European and Middle East media (Daily Mail, Le Monde, Deutsch Welle, Al Jazeera) indicates that they have adopted the same reporting practices, frames, and techniques resulting in a hybrid, yet homogeneous, increasingly global news environment that does a disservice to the public interest and democracy.

Keywords: conflict, environment, media framing, public interest

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Authors: M. A. Badr, A. N. Mohib, M. M. Ibrahim

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The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) system supplying a remote small gathering of six families using HOMER software package. The electrical energy is to cater for the basic needs for which the daily load pattern is estimated. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites as the price of generated electricity is about 0.308 $/kWh, without taking external benefits into considerations. W/D/B systems are more economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.

Keywords: optimum energy systems, remote electrification, renewable energy, wind turbine systems

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Authors: T. Parhizkar, H. Jafarian, F. Aramoun, Y. Saboohi

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Applying motorized shades have substantial effect on reducing energy consumption in building sector. Moreover, the combination of motorized shades with lighting systems and PV panels can lead to considerable reduction in the energy demand of buildings. In this paper, a model is developed to assess and find an optimum combination from shade designs, lighting control systems (dimming and on/off) and implementing PV panels in shades point of view. It is worth mentioning that annual saving for all designs is obtained during hourly simulation of lighting, solar heat flux and electricity generation with the use of PV panel. From 12 designs in general, three designs, two lighting control systems and PV panel option is implemented for a case study. The results illustrate that the optimum combination causes a saving potential of 792kW.hr per year.

Keywords: motorized shades, daylight, cooling load, shade control, hourly simulation

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Authors: Mehrnaz Mostafavi, Jalaledin Ghanavi

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This research investigates the production of nanoring structures through a chemical reduction approach, exploring gradual reduction processes assisted by reductant agents, leading to the formation of these specialized nanorings. The study focuses on the controlled reduction of metal atoms within these agents, crucial for shaping these nanoring structures over time. The paper commences by highlighting the wide-ranging applications of metal nanostructures across fields like Nanomedicine, Nanobiotechnology, and advanced spectroscopy methods such as Surface Enhanced Raman Spectroscopy (SERS) and Surface Enhanced Infrared Absorption Spectroscopy (SEIRA). Particularly, gold nanoparticles, especially in the nanoring configuration, have gained significant attention due to their distinctive properties, offering accessible spaces suitable for sensing and spectroscopic applications. The methodology involves utilizing human serum albumin as a reducing agent to create gold nanoparticles through a chemical reduction process. This process involves the transfer of electrons from albumin's carboxylic groups, converting them into carbonyl, while AuCl4− acquires electrons to form gold nanoparticles. Various characterization techniques like Ultraviolet–visible spectroscopy (UV-Vis), Atomic-force microscopy (AFM), and Transmission electron microscopy (TEM) were employed to examine and validate the creation and properties of the gold nanoparticles and nanorings. The findings suggest that precise and gradual reduction processes, in conjunction with optimal pH conditions, play a pivotal role in generating nanoring structures. Experiments manipulating optical properties revealed distinct responses in the visible and infrared spectrums, demonstrating the tunability of these nanorings. Detailed examinations of the morphology confirmed the formation of gold nanorings, elucidating their size, distribution, and structural characteristics. These nanorings, characterized by an empty volume enclosed by uniform walls, exhibit promising potential in the realms of Nanomedicine and Nanobiotechnology. In summary, this study presents a chemical synthesis approach using organic reducing agents to produce gold nanorings. The results underscore the significance of controlled and gradual reduction processes in crafting nanoring structures with unique optical traits, offering considerable value across diverse nanotechnological applications.

Keywords: nanoring structures, chemical reduction approach, gold nanoparticles, spectroscopy methods, nano medicine applications

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Authors: N. Jinesh, K. Shankar

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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: inverse problem, particle swarm optimization, PZT patches, structural identification

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Authors: Yixun Shi

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Many interior point methods for convex programming solve an (n+m)x(n+m)linear system in each iteration. Many implementations solve this system in each iteration by considering an equivalent mXm system (4) as listed in the paper, and thus the job is reduced into solving the system (4). However, the system(4) has to be solved exactly since otherwise the error would be entirely passed onto the last m equations of the original system. Often the Cholesky factorization is computed to obtain the exact solution of (4). One Cholesky factorization is to be done in every iteration, resulting in higher computational costs. In this paper, two iterative methods for solving linear systems using vector division are combined together and embedded into interior point methods. Instead of computing one Cholesky factorization in each iteration, it requires only one Cholesky factorization in the entire procedure, thus significantly reduces the amount of computation needed for solving the problem. Based on that, a hybrid algorithm for solving convex programming problems is proposed.

Keywords: convex programming, interior point method, linear systems, vector division

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Authors: Sanjay Agrawal, Trapti Varshney, G. N. Tiwari

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In this paper, thermal modeling has been developed for photovoltaic PV modules, namely; Case A: semitransparent PV module without duct, Case B: semitransparent PV module with duct, Case C: opaque PV module without duct, Case D: opaque PV module with duct for Delhi, India climatic condition. MATLAB 7.0 software has been used to solve mathematical models of the proposed system. For validation of proposed system, the experimental study has also been carried out for all above four cases, and then comparative analysis of all different type of PV module has been presented. The hybrid PVT module air collectors presented in this study are self sustaining the system and can be used for the electricity generation in remote areas where access of electricity is not economical due to high transmission and distribution losses. It has been found that overall annual thermal energy and exergy gain of semitransparent PV module is higher by 11.6% and7.32% in summer condition and 16.39% and 18% in winter condition respectively as compared to opaque PV module considering same area (0.61 m2) of PV module.

Keywords: semitransparent PV module, overall exergy, overall thermal energy, opaque

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Authors: Peyman Honarmandi, Mazen Alhirsh

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Banner towing is a major form of advertisement. It consists of a banner showing a logo or a selection of words or letters being towed by an aircraft. Traditionally bush planes have been used to tow banners given their high thrust capabilities; however, with the development of remote-controlled (RC) aircraft, they could be a good replacement as RC planes mitigate the risk of human life and can be easier to operate. This paper studies the best banner design to be towed by an RC aircraft. This is done by conducting wind tunnel testing on an array of banners with different materials and designs. A pull gauge is used to record the drag force during testing, which is then used to calculate the coefficient of drag, Cd. The testing results show that the best banner design would be a hybrid design with a solid and mesh material. The design with the lowest Cd of 0.082 was a half ripstop nylon half polyester mesh design. On the other hand, the design with the highest Cd of 0.305 involved incorporating a tail chute to decrease fluttering.

Keywords: aerodynamics of banner, banner design, banner towing, drag coefficients of banner, RC aircraft banner

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Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir

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NSGA-II is one of the most well-known and most widely used evolutionary algorithms. In addition to its new versions, such as NSGA-III, there are several modified types of this algorithm in the literature. In this paper, a hybrid NSGA-II algorithm has been suggested for solving the multi-objective flexible job shop scheduling problem. For a better search, new neighborhood-based crossover and mutation operators are defined. To create new generations, the neighbors of the selected individuals by the tournament selection are constructed. Also, at the end of each iteration, before sorting, neighbors of a certain number of good solutions are derived, except for solutions protected by elitism. The neighbors are generated using a constraint-based neural network that uses various constructs. The non-dominated sorting and crowding distance operators are same as the classic NSGA-II. A comparison based on some multi-objective benchmarks from the literature shows the efficiency of the algorithm.

Keywords: flexible job shop scheduling problem, multi-objective optimization, NSGA-II algorithm, neighborhood structures

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Authors: Sultan Noman Qasem

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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

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Authors: Jens Hagman, Jenny Janhager Stier, Ellen Olausson, Anne Y. Faxer, Ana Magazinius

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Sweden has the second highest electric vehicle (plug-in hybrid and battery electric vehicle) sales per capita in Europe but in relation to sales of internal combustion engine electric vehicles sales are still minuscular (< 4%). Much research effort has been placed on various technical and user focused barriers and enablers for adoption of electric vehicles. Less effort has been placed on investigating the retail (dealership-customer) sales process of vehicles in general and electric vehicles in particular. Arguably, no one ought to be better informed about needs and desires of potential electric vehicle buyers than car salesmen, originating from their daily encounters with customers at the dealership. The aim of this paper is to explore the conditions of selling electric vehicle from a car salesmen’s perspective. This includes identifying barriers and enablers for electric vehicle sales originating from internal (dealership and brand) and external (customer, government) sources. In this interview study five car brands (manufacturers) that sell both electric and internal combustion engine vehicles have been investigated. A total of 15 semi-structured interviews have been conducted (three per brand, in rural and urban settings and at different dealerships). Initial analysis reveals several barriers and enablers, experienced by car salesmen, which influence electric vehicle sales. Examples of as reported by car salesmen identified barriers are: -Electric vehicles earn car salesmen less commission on average compared to internal combustion engine vehicles. -It takes more time to sell and deliver an electric vehicle than an internal combustion engine vehicle. -Current leasing contracts entails relatively low second-hand value estimations for electric vehicles and thus a high leasing fee, which negatively affects the attractiveness of electric vehicles for private consumers in particular. -High purchasing price discourages many consumers from considering electric vehicles. -The education and knowledge level of electric vehicles differs between car salesmen, which could affect their self-confidence in meeting well prepared and question prone electric vehicle buyers. Examples of identified enablers are: -Company car tax regulation promotes sales of electric vehicles; in particular, plug-in hybrid electric vehicles are sold extensively to companies (up to 95 % of sales). -Low operating cost of electric vehicles such as fuel and service is an advantage when understood by consumers. -The drive performance of electric vehicles (quick, silent and fun to drive) is attractive to consumers. -Environmental aspects are considered important for certain consumer groups. -Fast technological improvements, such as increased range are opening up a wider market for electric vehicles. -For one of the brands; attractive private lease campaigns have proved effective to promote sales. This paper gives insights of an important but often overlooked aspect for the diffusion of electric vehicles (and durable products in general); the interaction between car salesmen and customers at the critical acquiring moment. Extracted through interviews with multiple car salesmen. The results illuminate untapped potential for sellers (salesmen, dealerships and brands) to mitigating sales barriers and strengthening sales enablers and thus becoming a more important actor in the electric vehicle diffusion process.

Keywords: customer barriers, electric vehicle promotion, sales of electric vehicles, interviews with car salesmen

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Authors: Abdulaziz Alageel, Martino Luis, Shuya Zhong

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The main focus of this research study is on the challenges faced in decision-making in a supply chain network regarding the facility location while considering carbon emissions. The study aims (i) to locate facilities (i.e., distribution centeres) in a continuous space considering limitations of capacity and the costs associated with opening and (ii) to reduce the cost of carbon emissions by selecting the mode of transportation. The problem is formulated as mixed-integer linear programming. This study hybridised a greedy randomised adaptive search (GRASP) and variable neighborhood search (VNS) to deal with the problem. Well-known datasets from the literature (Brimberg et al. 2001) are used and adapted in order to assess the performance of the proposed method. The proposed hybrid method produces encouraging results based on computational analysis. The study also highlights some research avenues for future recommendations.

Keywords: supply chain, facility location, weber problem, sustainability

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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

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Authors: (Ted) Edward Holmberg, Mahdi Abdelguerfi, Elias Ioup

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This research details a coverage measure for evaluating the effectiveness of observer node placements in a spatial bipartite network. This coverage measure can be used to optimize the configuration of stationary or mobile spatially oriented observer nodes, or a hybrid of the two, over time in order to fully utilize their capabilities. To demonstrate the practical application of this approach, we construct a SpatioTemporal Bipartite Network (STBN) using real-time crime center (RTCC) camera nodes and NOPD calls for service (CFS) event nodes from New Orleans, La (NOLA). We use the coverage measure to identify optimal placements for moving mobile RTCC camera vans to improve coverage of vulnerable areas based on temporal patterns.

Keywords: coverage measure, mobile node dynamics, Monte Carlo simulation, observer nodes, observable nodes, spatiotemporal bipartite knowledge graph, temporal spatial analysis

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Authors: S. Cichosz, A. Masek

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A new cellulose hybrid modification approach, which is undoubtedly a scientific novelty, is introduced. The study reports the properties of cellulose (Arbocel UFC100 – Ultra Fine Cellulose) and characterizes cellulose filled polymer composites based on an ethylene-norbornene copolymer (TOPAS Elastomer E-140). Moreover, the approach of physicochemical two-stage cellulose treatment is introduced: solvent exchange (to ethanol or hexane) and further chemical modification with maleic anhydride (MA). Furthermore, the impact of the drying process on cellulose properties was investigated. Suitable measurements were carried out to characterize cellulose fibers: spectroscopic investigation (Fourier Transform Infrared Spektrofotometer-FTIR, Near InfraRed spectroscopy-NIR), thermal analysis (Differential scanning calorimetry, Thermal gravimetric analysis ) and Karl Fischer titration. It should be emphasized that for all UFC100 treatments carried out, a decrease in moisture content was evidenced. FT-IR reveals a drop in absorption band intensity at 3334 cm-1, the peak is associated with both –OH moieties and water. Similar results were obtained with Karl Fischer titration. Based on the results obtained, it may be claimed that the employment of ethanol contributes greatly to the lowering of cellulose water absorption ability (decrease of moisture content to approximately 1.65%). Additionally, regarding polymer composite properties, crucial data has been obtained from the mechanical and thermal analysis. The highest material performance was noted in the case of the composite sample that contained cellulose modified with MA after a solvent exchange with ethanol. This specimen exhibited sufficient tensile strength, which is almost the same as that of the neat polymer matrix – in the region of 40 MPa. Moreover, both the Payne effect and filler efficiency factor, calculated based on dynamic mechanical analysis (DMA), reveal the possibility of the filler having a reinforcing nature. What is also interesting is that, according to the Payne effect results, fibers dried before the further chemical modification are assumed to allow more regular filler structure development in the polymer matrix (Payne effect maximum at 1.60 MPa), compared with those not dried (Payne effect in the range 0.84-1.26 MPa). Furthermore, taking into consideration the data gathered from DSC and TGA, higher thermal stability is obtained in case of the materials filled with fibers that were dried before the carried out treatments (degradation activation energy in the region of 195 kJ/mol) in comparison with the polymer composite samples filled with unmodified cellulose (degradation activation energy of approximately 180 kJ/mol). To author’s best knowledge this work results in the introduction of a novel, new filler hybrid treatment approach. Moreover, valuable data regarding the properties of composites filled with cellulose fibers of various moisture contents have been provided. It should be emphasized that plant fiber-based polymer bio-materials described in this research might contribute significantly to polymer waste minimization because they are more readily degraded.

Keywords: cellulose fibers, solvent exchange, moisture content, ethylene-norbornene copolymer

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Authors: Kumar Sankaran, Santanu Chattopadhyay, Golok Behari Nando, Sujith Nair, Sreejesh Arayambath, Unnikrishnan Govindan

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Rubber nanocomposites based on Bromobutyl rubber (BIIR), Polyepichlorohydrin rubber (CO), Carbon black (CB) and organically modified montmorillonite clay (NC) were prepared via melt compounding technique. The developed quaternary nanocomposites were characterized analytically and their properties were compared against the standard BIIR compound. BIIR-CO nanocomposites showed improved physico-mechanical properties as compared to that of the standard BIIR compound. Hybrid microstructure (NC-CB) development, clay exfoliation and better filler dispersion in the quaternary nanocomposite significantly contributed to the overall enhancement of properties. Introduction of CO in the system increased the specific gravity and hardness of the compound as compared to that of the standard compound. XRD analysis, AFM imaging and HR-TEM measurements confirmed exfoliation and a good level of dispersion of the NC in the composites. Permeability of developed BIIR-CO nanocomposites decreases significantly as compared to that of the standard BIIR compound.

Keywords: rubber nanocomposites, morphology, permeability, BIIR

Procedia PDF Downloads 436

Authors: S. P. Koko, K. Kusakana, H. J. Vermaak

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Standalone micro-hydrokinetic river (MHR) system is one of the promising technologies to be used for remote rural electrification. It simply requires the flow of water instead of elevation or head, leading to expensive civil works. This paper demonstrates an economic benefit offered by a standalone MHR system when compared to the commonly used standalone systems such as solar, wind and diesel generator (DG) at the selected study site in Kwazulu Natal. Wind speed and solar radiation data of the selected rural site have been taken from national aeronautics and space administration (NASA) surface meteorology database. The hybrid optimization model for electric renewable (HOMER) software was used to determine the most feasible solution when using MHR, solar, wind or DG system to supply 5 rural houses. MHR system proved to be the best cost-effective option to consider at the study site due to its low cost of energy (COE) and low net present cost (NPC).

Keywords: economic analysis, micro-hydrokinetic, rural-electrification, cost of energy (COE), net present cost (NPC)

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Authors: Anjali Vanpariya, Priyanka Marathey, Sakshum Khanna, Roma Patel, Indrajit Mukhopadhyay

Abstract:

Silicon (Si) is a promising negative electrode material for lithium-ion batteries (LiBs) due to its low cost, non-toxicity, and a high theoretical capacity of 4200 mAhg⁻¹. The primary challenge of the application of Si-based LiBs is large volume expansion (~ 300%) during the charge-discharge process. Incorporation of graphene, carbon nanotubes (CNTs), morphological control, and nanoparticles was utilized as effective strategies to tackle volume expansion issues. However, molten salt methods can resolve the issue, but high-temperature requirement limits its application. For sustainable and practical approach, room temperature (RT) based methods are essentially required. Use of ionic liquids (ILs) for electrodeposition of Si nanostructures can possibly resolve the issue of temperature as well as greener media. In this work, electrodeposition of Si nanoparticles on gold substrate was successfully carried out in the presence of ILs media, 1-butyl-3-methylimidazolium-bis (trifluoromethyl sulfonyl) imide (BMImTf₂N) at room temperature. Cyclic voltammetry (CV) suggests the sequential reduction of Si⁴⁺ to Si²⁺ and then Si nanoparticles (SiNs). The structure and morphology of the electrodeposited SiNs were investigated by FE-SEM and observed interconnected Si nanoparticles of average particle size ⁓100-200 nm. XRD and XPS data confirm the deposition of Si on Au (111). The first discharge-charge capacity of Si anode material has been found to be 1857 and 422 mAhg⁻¹, respectively, at current density 7.8 Ag⁻¹. The irreversible capacity of the first discharge-charge process can be attributed to the solid electrolyte interface (SEI) formation via electrolyte decomposition, and trapped Li⁺ inserted into the inner pores of Si. Pulverization of SiNs results in the creation of a new active site, which facilitates the formation of new SEI in the subsequent cycles leading to fading in a specific capacity. After 20 cycles, charge-discharge profiles have been stabilized, and a reversible capacity of 150 mAhg⁻¹ is retained. Electrochemical impedance spectroscopy (EIS) data shows the decrease in Rct value from 94.7 to 47.6 kΩ after 50 cycles of charge-discharge, which demonstrates the improvements of the interfacial charge transfer kinetics. The decrease in the Warburg impedance after 50 cycles of charge-discharge measurements indicates facile diffusion in fragmented and smaller Si nanoparticles. In summary, Si nanoparticles deposited on gold substrate using ILs as media and characterized well with different analytical techniques. Synthesized material was successfully utilized for LiBs application, which is well supported by CV and EIS data.

Keywords: silicon nanoparticles, ionic liquid, electrodeposition, cyclic voltammetry, Li-ion battery

Procedia PDF Downloads 125

Authors: Hamza A. A. Al-Sewadi, Adnan H. M. Al-Helali, Samaa A. K. Khamis

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Ownership proofs of multimedia such as text, image, audio or video files can be achieved by the burial of watermark is them. It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications would be in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.

Keywords: authentication, copyright protection, information hiding, ownership, watermarking

Procedia PDF Downloads 565