Search results for: whale optimization algorithm

Authors: A. Hamidi, S. Khelladi, L. Illoul, A. Tcharkhtchi

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Reactive rotational molding (RRM) is a process to manufacture hollow plastic parts with reactive material has several advantages compared to conventional roto molding of thermoplastic powders: process cycle time is shorter; raw material is less expensive because polymerization occurs during processing and high-performance polymers may be used such as thermosets, thermoplastics or blends. However, several phenomena occur during this process which makes the optimization of the process quite complex. In this study, we have used a mixture of isocyanate and polyol as a reactive system. The chemical transformation of this system to polyurethane has been studied by thermal analysis and rheology tests. Thanks to these results of the curing process and rheological measurements, the kinetic and rheokinetik of polyurethane was identified. Smoothed Particle Hydrodynamics, a Lagrangian meshless method, was chosen to simulate reactive fluid flow in 2 and 3D configurations of the polyurethane during the process taking into account the chemical, and chemiorehological results obtained experimentally in this study.

Keywords: reactive rotational molding, simulation, smoothed particle hydrodynamics, surface tension, rheology, free surface flows, viscoelastic, interpolation

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Authors: K. Roushanger, A. Soleymanzadeh

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Weirs are structures often used in irrigation techniques, sewer networks and flood protection. However, the hydraulic behavior of this type of weir is complex and difficult to predict accurately. An accurate flow prediction over a weir mainly depends on the proper estimation of discharge coefficient. In this study, the Genetic Expression Programming (GEP) approach was used for predicting trapezoidal and rectangular sharp-crested side weirs discharge coefficient. Three different performance indexes are used as comparing criteria for the evaluation of the model’s performances. The obtained results approved capability of GEP in prediction of trapezoidal and rectangular side weirs discharge coefficient. The results also revealed the influence of downstream Froude number for trapezoidal weir and upstream Froude number for rectangular weir in prediction of the discharge coefficient for both of side weirs.

Keywords: discharge coefficient, genetic expression programming, trapezoidal weir

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Authors: Ahmed Aisa, Tariq Iqbal

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This letter talks about the ready-to-use design of a solar water heating system because, in Canada, the average consumption of hot water per person is approximately 50 to 75 L per day and the average Canadian household uses 225 L. Therefore, this paper will demonstrate the method of designing a solar water heating system with thermal storage. It highlights the renewable hybrid power system, allowing you to obtain a reliable, independent system with the optimization of the ingredient size and at an improved capital cost. The system can provide hot water for a big building. The main power for the system comes from solar panels. Solar Advisory Model (SAM) and HOMER are used. HOMER and SAM are design models that calculate the consumption of hot water and cost for a house. Some results, obtained through simulation, were for monthly energy production, annual energy production, after tax cash flow, the lifetime of the system and monthly energy usage represented by three types of energy. These are system energy, electricity load electricity and net metering credit.

Keywords: water heating, thermal storage, capital cost solar, consumption

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

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In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador

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Authors: Boukhris Lahouari, Bouchetara Mostefa

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The active safety of a vehicle is mainly influenced by the properties of the installed braking system. With the increase in road traffic density and travel speeds, increasingly stringent requirements are placed on the vehicle's behaviour during braking. The achievable decelerations are limited by the physical aspect characterized by the coefficient of friction between the tires and the ground. As a result, it follows that an optimized distribution of braking forces becomes necessary for a better use of friction coefficients. This objective could only be achieved if sufficient knowledge is available on the theory of vehicle dynamics during braking and on current standards for the approval of braking systems. This will facilitate the development of a braking force calculation algorithm that will enable an optimized distribution of braking forces to be achieved. Operating safety is conditioned by the requirements of efficiency, progressiveness, regularity or fidelity of a braking system without obviously neglecting the recommendations imposed by the legislator.

Keywords: brake force distribution, distribution diagram, friction coefficient, brake by wire

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Authors: F. Karim

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In this paper, triangular lattice index-guiding photonic crystal fibers (PCFs) are synthesized to compensate the chromatic dispersion of a single mode fiber (SMF-28) for an 80 km optical link operating at 1.55 µm, by using the directed tabu search algorithm. Hole-to-hole distance, circular air-hole diameter, solid-core diameter, ring number and PCF length parameters are optimized for this purpose. Three Synthesized PCFs with different physical parameters are compared in terms of their objective functions values, residual dispersions and compensation ratios.

Keywords: triangular lattice index-guiding photonic crystal fiber, dispersion compensation, directed tabu search, synthesis

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Authors: I. Bentchikou, A. Tlemcani, F. Boudjema, D. Boukhetala, N. Ould Cherchali

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In this paper, hybrid approach is proposed to regulate the voltages of the floating capacitor multicell inverter and the current in the load. This structure makes it possible to ensure the distribution of the voltage stresses on the various low-voltage semiconductor components connected in series. And as the problem and to keep a constant voltage across the capacitors. Thus, it is necessary to ensure a distribution balanced voltages at the terminals of floating capacitors thanks to Algorithm develop for this, using the Petri nets. So we consider a three-cell converter represented as a hybrid system with eight modes of operation. The operating modes of the system are governed by the control reference voltage and a reference current. Finally, we present the results of the simulation with MATLAB/SIMULINK to illustrate the performances of this approach.

Keywords: hybrid control, floating condensers, multicellular converter, petri nets

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Authors: Rupu Yang, Cong Toan Tran, Assaad Zoughaib

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The work provides an iterative nonlinear programming method to synthesize a heat exchanger network by manipulating the trade-offs between the heat load of process heat exchangers (HEs) and utilities. We consider for the synthesis problem two cases, the first one without fixed cost for HEs, and the second one with fixed cost. For the no fixed cost problem, the nonlinear programming (NLP) model with all the potential HEs is optimized to obtain the global optimum. For the case with fixed cost, the NLP model is iterated through adding/removing HEs. The method was applied in five case studies and illustrated quite well effectiveness. Among which, the approach reaches the lowest TAC (2,904,026$/year) compared with the best record for the famous Aromatic plants problem. It also locates a slightly better design than records in literature for a 10 streams case without fixed cost with only 1/9 computational time. Moreover, compared to the traditional mixed-integer nonlinear programming approach, the iterative NLP method opens a possibility to consider constraints (such as controllability or dynamic performances) that require knowing the structure of the network to be calculated.

Keywords: heat exchanger network, synthesis, NLP, optimization

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Authors: Kelaiaia Mounia Samira, Labar Hocine, Mesbah Tarek, Kelaiaia samia

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The photovoltaic panel produces green power, and because of its availability across the globe, it can supply isolated loads (site away of the electrical network or difficult of access). Unfortunately this energy remains very expensive. The most application of these types of power needs storage devices, the Lithium batteries are commonly used because of its powerful storage capability. Using a solar panel or an array of panels without a controller that can perform MPPT will often result in wasted power, which results in the need to install more panels for the same power requirement. For devices that have the battery connected directly to the panel, this will also result in premature battery failure or capacity loss. In this paper it is proposed a modified P&O algorithm for the MPPT which takes in account the battery’s internal resistance vs temperature and stage of charging. Of course the temperature variation and irradiation of the PV panel are also introduced.

Keywords: modeling, battery, MPPT, charging, PV Panel

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Authors: A. W. Zularisam, Sveta Thakur, Lakhveer Singh, Mimi Sakinah Abdul Munaim

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Clostridium sp. LS2 was immobilised by entrapment in polyethylene glycol (PEG) gel beads to improve the biohydrogen production rate from palm oil mill effluent (POME). We sought to explore and optimise the hydrogen production capability of the immobilised cells by studying the conditions for cell immobilisation, including PEG concentration, cell loading and curing times, as well as the effects of temperature and K2HPO4 (500–2000 mg/L), NiCl2 (0.1–5.0 mg/L), FeCl2 (100–400 mg/L) MgSO4 (50–200 mg/L) concentrations on hydrogen production rate. The results showed that by optimising the PEG concentration (10% w/v), initial biomass (2.2 g dry weight), curing time (80 min) and temperature (37 °C), as well as the concentrations of K2HPO4 (2000 mg/L), NiCl2 (1 mg/L), FeCl2 (300 mg/L) and MgSO4 (100 mg/L), a maximum hydrogen production rate of 7.3 L/L-POME/day and a yield of 0.31 L H2/g chemical oxygen demand were obtained during continuous operation. We believe that this process may be potentially expanded for sustained and large-scale hydrogen production.

Keywords: hydrogen, polyethylene glycol, immobilised cell, fermentation, palm oil mill effluent

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Kumar N., Verma S., Park J., Srivastava V. C.

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Organic carbonates have the potential to be used as fuels and because of this, their production through non-phosgene routes is a thrust area of research. Di-ethyl carbonate (DEC) synthesis from propylene carbonate (PC) in the presence of alcohol is a green route. In this study, the use of reduced graphene oxide (rGO) based metal oxide catalysts [rGO-MO, where M = Ce] with different amounts of graphene oxide (0.2%, 0.5%, 1%, and 2%) has been investigated for the synthesis of DEC by using PC and ethanol as reactants. The GO sheets were synthesized by an electrochemical process and the catalysts were synthesized using an in-situ method. A theoretical study of the thermodynamics of the reaction was done, which revealed that the reaction is mildly endothermic. The theoretical value of optimum temperature was found to be 420 K. The synthesized catalysts were characterized for their morphological, structural and textural properties using field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), N2 adsorption/desorption, thermogravimetric analysis (TGA), and Raman spectroscopy. Optimization studies were carried out to study the effect of different reaction conditions like temperature (140 °C to 180 °C) and catalyst dosage (0.102 g to 0.255 g) on the yield of DEC. Amongst the various synthesized catalysts, 1% rGO-CeO2 gave the maximum yield of DEC.

Keywords: GO, DEC, propylene carbonate, transesterification, thermodynamics

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Authors: Zongjie Wang, Zhizhong Guo

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While the regular optimal power flow model focuses on a single time scan, the optimization of power systems is typically intended for a time duration with respect to a desired objective function. In this paper, a temporal optimal power flow model for a time period is proposed. To reduce the computation burden needed for calculating temporal optimal power flow, a characteristic optimal power flow model is proposed, which employs different characteristic load patterns to represent the objective function and security constraints. A numerical method based on the interior point method is also proposed for solving the characteristic optimal power flow model. Both the temporal optimal power flow model and characteristic optimal power flow model can improve the systems’ desired objective function for the entire time period. Numerical studies are conducted on the IEEE 14 and 118-bus test systems to demonstrate the effectiveness of the proposed characteristic optimal power flow model.

Keywords: optimal power flow, time period, security, economy

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Authors: Charalampos Saridakis, Stelios Tsafarakis

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Although environmental concern is on the rise across Europe, current market data indicate that adoption rates of environmentally friendly vehicles remain extremely low. Against this background, the aim of this paper is to a) assess preferences of European consumers for clean-fuel cars and their characteristics and b) design car lines that optimize the combination of fuel types among models in the line-up. In this direction, the authors introduce a new evolutionary mechanism and implement it to stated-preference data derived from a large-scale choice-based conjoint experiment that measures consumer preferences for various factors affecting clean-fuel vehicle (CFV) adoption. The proposed two-step methodology provides interesting insights into how new and existing fuel-types can be combined in a car line that maximizes customer satisfaction.

Keywords: clean-fuel vehicles, product line design, conjoint analysis, choice experiment, differential evolution

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Authors: Jessica A. Soto-Bear, Virginia González-Vélez, Norma Castañeda-Villa, Amparo Gil

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Glutamate release of the cochlear inner hair cell (IHC) ribbon synapse is a fundamental step in transferring sound information in the auditory pathway. Otoferlin is the calcium sensor in the IHC and its activity has been related to many auditory disorders. In order to simulate secretion dynamics occurring in the IHC in a few milliseconds timescale and with high spatial resolution, we proposed an active-zone model solved with Monte Carlo algorithms. We included models for calcium buffered diffusion, calcium-binding schemes for vesicle fusion, and L-type voltage-gated calcium channels. Our results indicate that calcium influx and calcium binding is managing IHC secretion as a function of voltage depolarization, which in turn mean that IHC response depends on sound intensity.

Keywords: inner hair cells, Monte Carlo algorithm, Otoferlin, secretion

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Authors: Jatinder Kumar, Ajay Bansal

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Simulation of a photocatalytic reactor helps in understanding the complex behavior of the photocatalytic degradation. Simulation also aids the designing and optimization of the photocatalytic reactor. Lack of simulation strategies is a huge hindrance in the commercialization of the photocatalytic technology. With the increased performance of computational resources, and development of simulation software, computational fluid dynamics (CFD) is becoming an affordable engineering tool to simulate and optimize reactor designs. In the present paper, a CFD (Computational fluid dynamics) model for simulating the performance of an immobilized-titanium dioxide based annular photocatalytic reactor was developed. The computational model integrates hydrodynamics, species mass transport, and chemical reaction kinetics using a commercial CFD code Fluent 6.3.26. The CFD model was based on the intrinsic kinetic parameters determined experimentally in a perfectly mixed batch reactor. Rhodamine B, a complex organic compound, was selected as a test pollutant for photocatalytic degradation. It was observed that CFD could become a valuable tool to understand and improve the photocatalytic systems.

Keywords: simulation, computational fluid dynamics (CFD), annular photocatalytic reactor, titanium dioxide

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Authors: Li Hui, Riyadh Hindi

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Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

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Authors: Richard Tanaka, Ying Zhu

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This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

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Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Due to the competitive market in which companies are currently engaged, the constant changes require companies to react quickly regarding the variability of demand and process. The changes are caused by customers, or by demand fluctuations or variations of products, or the need to serve customers within agreed delivery taking into account the continuous search for quality and competitive prices in products. These changes end up influencing directly or indirectly the activities of the Planning and Production Control (PPC), which does business in strategic, tactical and operational levels of production systems. One area of concern for organizations is in the short term (operational level), because this planning stage any error or divergence will cause waste and impact on the delivery of products on time to customers. Thus, this study aims to optimize the efficiency of production scheduling, using different sequencing strategies in an automotive company. Seeking to aim the proposed objective, we used the computer simulation in conjunction with lean manufacturing to build and validate the current model, and subsequently the creation of future scenarios.

Keywords: computational simulation, lean manufacturing, production scheduling, sequencing strategies

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Authors: Khaled A. Madi, Rema A. Mousbahi, Mostafa B. Abuitbel, Abdualhakim O. Nagi

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Antenna perhaps is the most important part of any communication system, it determines the overall efficiency and the direction of radiation of the system. Antennas vary in shape and size on a very wide range. For fast moving vehicles, the antenna should offer as litter aerodynamic resistance as possible. Slot antenna is best suited for this purpose. It offers very little aerodynamic resistance, compact, easy to feed and fabricate. This work presented in this paper deals with the investigation of a half wave slot antenna. The antenna has been studied, analyzed, designed, simulated, fabrication, and tested at the X-band. The field of antenna study is an extremely vast one, and to grasp the fundamentals, two pronged approaches have been used, and the focus was on the fabrication and testing of a slot waveguide directional antenna. Focuses on the design and simulation of slot antennas with an emphasis on optimization of a 9.1 GHz a rectangular waveguide have been used to feed slot antenna. A microwave fed slot antenna used in the communication lab was also simulated. The results have been presented and compared with the expected values, where a good agreement was achieved between the simulation and experimental results.

Keywords: microwave, slot antenna, simulation, fabrication

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Authors: S. Ghorbani, N. I. Polushin

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Vibration during machining process is crucial since it affects cutting tool, machine, and workpiece leading to a tool wear, tool breakage, and an unacceptable surface roughness. This paper applies a nonparametric statistical method, single decision tree (SDT), to identify factors affecting on vibration in machining process. Workpiece material (AISI 1045 Steel, AA2024 Aluminum alloy, A48-class30 Gray Cast Iron), cutting tool (conventional, cutting tool with holes in toolholder, cutting tool filled up with epoxy-granite), tool overhang (41-65 mm), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev) and depth of cut (0.05-0.15 mm) were used as input variables, while vibration was the output parameter. It is concluded that workpiece material is the most important parameters for natural frequency followed by cutting tool and overhang.

Keywords: cutting condition, vibration, natural frequency, decision tree, CART algorithm

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Authors: Yi F. Wu, Ai Q. Li, Hao Wang

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Taking a novel type of bridge bearings with the diameter being 100mm as an example, the theoretical analysis, the experimental research as well as the numerical simulation of the bearing were conducted. Since the normal compression-shear machines cannot be applied to the small-size bearing, an improved device to test the properties of the bearing was proposed and fabricated. Besides, the simulation of the bearing was conducted on the basis of the explicit finite element software ANSYS/LS-DYNA, and some parameters of the bearing are modified in the finite element model to effectively reduce the computation cost. Results show that all the research methods are capable of revealing the fundamental properties of the small-size bearings, and a combined use of these methods can better catch both the integral properties and the inner detailed mechanical behaviors of the bearing.

Keywords: ANSYS/LS-DYNA, compression shear, contact analysis, explicit algorithm, small-size

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Authors: S. Toufigh Bararpour, Davood Karami, Nader Mahinpey

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Dependence of global economics on fossil fuels has led to a large growth in the emission of greenhouse gases (GHGs). Among the various GHGs, carbon dioxide is the main contributor to the greenhouse effect due to its huge emission amount. To mitigate the threatening effect of CO₂, carbon capture and sequestration (CCS) technologies have been studied widely in recent years. For the combustion processes, three main CO₂ capture techniques have been proposed such as post-combustion, pre-combustion and oxyfuel combustion. Post-combustion is the most commonly used CO₂ capture process as it can be readily retrofit into the existing power plants. Multiple advantages have been reported for the post-combustion by solid sorbents such as high CO₂ selectivity, high adsorption capacity, and low required regeneration energy. Chemical adsorption of CO₂ over alkali-metal-based solid sorbents such as K₂CO₃ is a promising method for the selective capture of diluted CO₂ from the huge amount of nitrogen existing in the flue gas. To improve the CO₂ capture performance, K₂CO₃ is supported by a stable and porous material. Al₂O₃ has been employed commonly as the support and enhanced the cyclic CO₂ capture efficiency of K₂CO₃. Different phases of alumina can be obtained by setting the calcination temperature of boehmite at 300, 600 (γ-alumina), 950 (δ-alumina) and 1200 °C (α-alumina). By increasing the calcination temperature, the regeneration capacity of alumina increases, while the surface area reduces. However, sorbents with lower surface areas have lower CO₂ capture capacity as well (except for the sorbents prepared by hydrophilic support materials). To resolve this issue, a highly efficient alumina-aerogel support was synthesized with a BET surface area of over 2000 m²/g and then calcined at a high temperature. The synthesized alumina-aerogel was impregnated on K₂CO₃ based on 50 wt% support/K₂CO₃, which resulted in the preparation of a sorbent with remarkable CO₂ capture performance. The effect of synthesis conditions such as types of alcohols, solvent-to-co-solvent ratios, and aging times was investigated on the performance of the support. The best support was synthesized using methanol as the solvent, after five days of aging time, and at a solvent-to-co-solvent (methanol-to-toluene) ratio (v/v) of 1/5. Response surface methodology was used to investigate the effect of operating parameters such as carbonation temperature and H₂O-to-CO₂ flowrate ratio on the CO₂ capture capacity. The maximum CO₂ capture capacity, at the optimum amounts of operating parameters, was 7.2 mmol CO₂ per gram K₂CO₃. Cyclic behavior of the sorbent was examined over 20 carbonation and regenerations cycles. The alumina-aerogel-supported K₂CO₃ showed a great performance compared to unsupported K₂CO₃ and γ-alumina-supported K₂CO₃. Fundamental performance analyses and long-term thermal and chemical stability test will be performed on the sorbent in the future. The applicability of the sorbent for a bench-scale process will be evaluated, and a corresponding process model will be established. The fundamental material knowledge and respective process development will be delivered to industrial partners for the design of a pilot-scale testing unit, thereby facilitating the industrial application of alumina-aerogel.

Keywords: alumina-aerogel, CO₂ capture, K₂CO₃, optimization

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Authors: Caroline Atef Shoukry Tadros

Abstract:

Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

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Authors: Danilo López, Edwin Rivas, Fernando Pedraza

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Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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Authors: Sanjoy Mukherjee

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Discussions on concepts of Single Axis Tracker (SAT) are becoming more and more apt for developing countries like India not just as an advancement in racking technology but due to the utmost necessity of reaching at the lowest Levelized Cost of Energy (LCOE) targets. With this increasing competition and significant fall in feed-in tariffs of solar PV projects, developers are under constant pressure to secure investment for their projects and eventually earn profits from them. Moreover, being the second largest populated country, India suffers from scarcity of land because of higher average population density. So, to mitigate the risk of this dual edged sword with reducing trend of unit (kWh) cost at one side and utilization of land on the other, tracking evolved as the call of the hour. Therefore, the prime objectives of this paper are not only to showcase how STT proves to be an effective mechanism to get more gain in Global Incidence in collector plane (G_inc) with respect to traditional mounting systems but also to introduce Seasonally Tilted Tracker (STT) technology as a possible option for high latitude locations.

Keywords: tracking system, grid connected solar PV plant, CAPEX reduction, levelized cost of energy

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Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

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Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R-colour component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: feature extraction, remote sensing, image retrieval, chromaticity, water index, spectral library, integrated method

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Authors: Mohamed Barbary, Mohamed H. Abd El-azeem

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Maneuvering non-ellipsoidal extended object tracking (M-NEOT) using high-resolution inverse synthetic aperture radar (ISAR) observations is gaining momentum recently. This work presents a new robust implementation of the Jump Markov (JM) multi-Bernoulli (MB) filter for M-NEOT, where the M-NEOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on an MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, JM-MB-TBD filter

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Authors: Atef Ibrahim, Hamed Elsimary, Abdullah Aljumah, Fayez Gebali

Abstract:

This paper presents a novel semi-systolic array architecture for an optimized parallel sequence alignment algorithm. This architecture has the advantage that it can be modified to be reused for multiple pass processing in order to increase the number of processing elements that can be packed into a single FPGA and to increase the number of sequences that can be aligned in parallel in a single FPGA. This resolves the potential problem of many FPGA resources left unused for designs that have large values of short read length. When using the previously published conventional hardware design. FPGA implementation results show that, for large values of short read lengths (M>128), the proposed design has a slightly higher speed up and FPGA utilization over the the conventional one.

Keywords: bioinformatics, genome sequence alignment, re-sequencing applications, systolic array

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