Search results for: computational grid

Authors: Sang-Woo Han, Jong-Shik Shin

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w-Transaminase (w-TA) is broadly used for synthesizing chiral amines with a high enantiopurity. However, the reaction mechanism of w-TA has been not well studied, contrary to a-transaminase (a-TA) such as AspTA. Here, we propose in silico model on the reaction mechanism of w-TA. Based on the modeling results which showed large free energy gaps between external aldimine and quinonoid on deamination (or ketimine and quinonoid on amination), withdrawal of Ca-H seemed as a critical step which determines the reaction rate on both amination and deamination reactions, which is consistent with previous researches. Hyperconjugation was also observed in both external aldimine and ketimine which weakens Ca-H bond to elevate Ca-H abstraction.

Keywords: computational modeling, reaction intermediates, w-transaminase, in silico model

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Authors: Sevil Igit, Merve Meric, Sarp Erturk

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In this paper, it is proposed to improve Daisy descriptor based face recognition using a novel One-Bit Transform (1BT) based pre-registration approach. The 1BT based pre-registration procedure is fast and has low computational complexity. It is shown that the face recognition accuracy is improved with the proposed approach. The proposed approach can facilitate highly accurate face recognition using DAISY descriptor with simple matching and thereby facilitate a low-complexity approach.

Keywords: face recognition, Daisy descriptor, One-Bit Transform, image registration

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Authors: Pyi Phyo Maung

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In the study, the calculations of the permeability coefficient, values of the volume and porosity of a unit cell of a woven fabric before and after deformation based on the geometrical parameters are presented. Two types of carbon woven fabric structures were investigated: standard type, which integrated the filament, has a cross sectional shape of a cylinder and spread tow type, which has a rectangular cross sectional shape. The space antennas reflector, which distinctive feature is the presence of the surface of double curvature, is considered as the object of the research. Modeling of the kinetics of the process of impregnation of the reflector for the two types of carbon fabric’s unit cell structures was performed using software RAM-RTM. This work also investigated the influence of the grid angle between warp and welt of the unit cell on the duration of impregnation process. The results showed that decreasing the angle between warp and welt of the unit cell, the decreasing of the permeability values were occurred. Based on the results of calculation samples of the reflectors, their quality was determined. The comparisons of the theoretical and experimental results have been carried out. Comparison of the two textile structures (standard and spread tow) showed that the standard textiles with circular cross section were impregnated faster than spread tows, which have a rectangular cross section.

Keywords: vacuum assistant resin infusion, impregnation time, shear angle, reflector and modeling

Procedia PDF Downloads 273

Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

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Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: M. A. Rubio, A. Urquia

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Genetic algorithms (GA) are applied to the solution of high-dimensional optimization problems. Additionally, sensitivity analysis (SA) is usually carried out to determine the effect on optimal solutions of changes in parameter values of the objective function. These two analyses (i.e., optimization and sensitivity analysis) are computationally intensive when applied to high-dimensional functions. The approach presented in this paper consists in performing the SA during the GA execution, by statistically analyzing the data obtained of running the GA. The advantage is that in this case SA does not involve making additional evaluations of the objective function and, consequently, this proposed approach requires less computational effort than conducting optimization and SA in two consecutive steps.

Keywords: optimization, sensitivity, genetic algorithms, model calibration

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Authors: Hernández Eva Selene, Reyna Mary Carmen, Rivera Héctor, Barragán Irving

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We propose an approach that jointly addresses the layout of a facility and the scheduling of a sequence of jobs. In real production, these two problems are interrelated. However, they are treated separately in the literature. Our approach is an extension of the job shop problem with transportation delay, where the location of the machines is selected among possible sites. The model minimizes the makespan, using the short processing times rule with two algorithms; the first one considers all the permutations for the location of machines, and the second only a heuristic to select some specific permutations that reduces computational time. Some instances are proved and compared with literature.

Keywords: layout problem, job shop scheduling problem, concurrent scheduling and layout problem, metaheuristic

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Authors: Fofie Kokea Ariane Darolle, Gouet Daniel Hervé, Koumetio Fidèle, Yemele David

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The electrical resistivity method is successfully used in this paper in order to have a clearer picture of the subsurface of the North-East ofFiguil in northern Cameroon. It is worth noting that this method is most often used when the objective of the study is to image the shallow subsoils by considering them as a set of stratified ground layers. The problem to be solved is very often environmental, and in this case, it is necessary to perform an inversion of the data in order to have a complete and accurate picture of the parameters of the said layers. In the case of this work, thirty-three (33) Schlumberger VES have been carried out on an irregular grid to investigate the subsurface of the study area. The 1D inversion applied as a preliminary modeling tool and in correlation with the mechanical drillings results indicates a complex subsurface lithology distribution mainly consisting of marbles and schists. Moreover, the quasi-3D inversion with lateral constraint shows that the misfit between the observed field data and the model response is quite good and acceptable with a value low than 10%. The method also reveals existence of two water bearing in the considered area. The first is the schist or weathering aquifer (unsuitable), and the other is the marble or the fracturing aquifer (suitable). The final quasi 3D inversion results and geological models indicate proper sites for groundwaters prospecting and for mining exploitation, thus allowing the economic development of the study area.

Keywords: electrical resistivity method, 1D inversion, quasi 3D inversion, groundwaters, mining

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Authors: Francielle A. Vargas, Thiago A. S. Pardo

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According to the standard philosophical definition, lying is saying something that you believe to be false with the intent to deceive. For deception detection, the FBI trains its agents in a technique named statement analysis, which attempts to detect deception based on parts of speech (i.e., linguistics style). This method is employed in interrogations, where the suspects are first asked to make a written statement. In this poster, we model false statements using linguistics style. In order to achieve this, we methodically analyze linguistic features in a corpus of fake news in the Portuguese language. The results show that they present substantial lexical, syntactic and semantic variations, as well as punctuation and emotion distinctions.

Keywords: deception detection, linguistics style, computational linguistics, natural language processing

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Authors: Andreas Helwig, John Bell, Wangmo

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Hybrid energy storage systems (HESS) are gaining popularity for grid energy storage (ESS) driven by the increasingly dynamic nature of energy demands, requiring both high energy and high power density. Particularly the ability of energy storage systems via inverters to respond to increasing fluctuation in energy demands, the combination of lithium Iron Phosphate (LFP) battery and supercapacitor (SC) is a particular example of complex electro-chemical devices that may provide benefit to each other for pulse width modulated DC to AC inverter application. This is due to SC’s ability to respond to instantaneous, high-current demands and batteries' long-term energy delivery. However, there is a knowledge gap on the current sharing mechanism within a HESS supplying a load powered by high-frequency pulse-width modulation (PWM) switching to understand the mechanism of aging in such HESS. This paper investigates the prediction of current utilizing various equivalent circuits for SC to investigate sharing between battery and SC in MATLAB/Simulink simulation environment. The findings predict a significant reduction of battery current when the battery is used in a hybrid combination with a supercapacitor as compared to a battery-only model. The impact of PWM inverter carrier switching frequency on current requirements was analyzed between 500Hz and 31kHz. While no clear trend emerged, models predicted optimal frequencies for minimized current needs.

Keywords: hybrid energy storage, carrier frequency, PWM switching, equivalent circuit models

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Authors: Jayaprakash Kar, Daniyal M. Alghazzawi

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The article proposes a novel construction of signcryption scheme with provable security which is most suited to implement on smart card. It is secure in random oracle model and the security relies on Decisional Bilinear Diffie-Hellmann Problem. The proposed scheme is secure against adaptive chosen ciphertext attack (indistiguishbility) and adaptive chosen message attack (unforgebility). Also, it is inspired by zero-knowledge proof. The two most important security goals for smart card are Confidentiality and authenticity. These functions are performed in one logical step in low computational cost.

Keywords: random oracle, provable security, unforgebility, smart card

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Authors: Alireza Abbassi Monjezi, Mohammad Hasan Shaheed

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Flood, caused by excessive rainfall, monsoon, cyclone and tsunami is a common disaster in many countries of the world especially sea connected low-lying countries. A stand-alone self-powered water filtration module for decontamination of floodwater has been designed and modeled. A combination forward osmosis – low pressure reverse osmosis (FO-LPRO) system powered by solar photovoltaic-thermal (PVT) energy is investigated which could overcome the main barriers to water supply for remote areas and ensure off-grid filtration. The proposed system is designed to be small scale and portable to provide on-site potable water to communities that are no longer themselves mobile nor can be reached quickly by the aid agencies. FO is an osmotically driven process that uses osmotic pressure gradients to drive water across a controlled pore membrane from a feed solution (low osmotic pressure) to a draw solution (high osmotic pressure). This drops the demand for high hydraulic pressures and therefore the energy demand. There is also a tendency for lower fouling, easier fouling layer removal and higher water recovery. In addition, the efficiency of the PVT unit will be maximized through freshwater cooling which is integrated into the system. A filtration module with the capacity of 5 m3/day is modeled to treat floodwater and provide drinking water. The module can be used as a tool for disaster relief, particularly in the aftermath of flood and tsunami events.

Keywords: flood resilience, membrane desalination, portable water treatment, solar energy

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Authors: Erich Gomes Schaitza, Antônio Francisco Savi, Glaucia Aparecida Prates

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The penetration of renewable energy into the electricity supply in Brazil is high, one of the highest in the World. Centralized hydroelectric generation is the main source of energy, followed by biomass and wind. Surprisingly, mini and micro-generation are negligible, with less than 2,000 connections to the national grid. In 2015, a new regulatory framework was put in place to change this situation. In the agricultural sector, the framework was complemented by the offer of low interest rate loans to in-farm renewable generation. Brazil proposed to more than double its area of planted forests as part of its INDC- Intended Nationally Determined Contributions to the UNFCCC-U.N. Framework Convention on Climate Change (UNFCCC). This is an ambitious target which will be achieved only if forests are attractive to farmers. Therefore, this paper analyses whether planting forests for in-farm energy generation with a with a woodchip gasifier is economically viable for microgeneration under the new framework and at if they could be an economic driver for forest plantation. At first, a static case was analyzed with data from Eucalyptus plantations in five farms. Then, a broader analysis developed with the use of Monte Carlo technique. Planting short rotation forests to generate energy could be a viable alternative and the low interest loans contribute to that. There are some barriers to such systems such as the inexistence of a mature market for small scale equipment and of a reference network of good practices and examples.

Keywords: biomass, distribuited generation, small-scale, Monte Carlo

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Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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The drug discovery and development process is generally known to be a very lengthy and labor-intensive process. Therefore, in order to be able to deliver prompt and effective responses to cure certain diseases, there is an urgent need to reduce the time and resources needed to design, develop, and optimize potential drugs. Computer-aided drug design (CADD) is able to alleviate this issue by applying computational power in order to streamline the whole drug discovery process, starting from target identification to lead optimization. This drug design approach can be predominantly applied to diseases that cause major public health concerns, such as tuberculosis. Hitherto, there has been no concrete cure for this disease, especially with the continuing emergence of drug resistant strains. In this study, CADD is employed for tuberculosis by first identifying a key enzyme in the mycobacterium’s metabolic pathway that would make a good drug target. One such potential target is the lipoate protein ligase B enzyme (LipB), which is a key enzyme in the M. tuberculosis metabolic pathway involved in the biosynthesis of the lipoic acid cofactor. Its expression is considerably up-regulated in patients with multi-drug resistant tuberculosis (MDR-TB) and it has no known back-up mechanism that can take over its function when inhibited, making it an extremely attractive target. Using cutting-edge computational methods, compounds from AnalytiCon Discovery Natural Derivatives database were screened and docked against the LipB enzyme in order to rank them based on their binding affinities. Compounds which have better binding affinities than LipB’s known inhibitor, decanoic acid, were subjected to in silico toxicity evaluation using the ADMET and TOPKAT protocols. Out of the 31,692 compounds in the database, 112 of these showed better binding energies than decanoic acid. Furthermore, 12 out of the 112 compounds showed highly promising ADMET and TOPKAT properties. Future studies involving in vitro or in vivo bioassays may be done to further confirm the therapeutic efficacy of these 12 compounds, which eventually may then lead to a novel class of anti-tuberculosis drugs.

Keywords: pharmacophore, molecular docking, lipoate protein ligase B (LipB), ADMET, TOPKAT

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Authors: Hassan Manouzi

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We present in this paper a useful strategy to solve stochastic partial differential equations (SPDEs) involving stochastic coefficients. Using the Wick-product of higher order and the Wiener-Itˆo chaos expansion, the SPDEs is reformulated as a large system of deterministic partial differential equations. To reduce the computational complexity of this system, we shall use a decomposition-coordination method. To obtain the chaos coefficients in the corresponding deterministic equations, we use a least square formulation. Once this approximation is performed, the statistics of the numerical solution can be easily evaluated.

Keywords: least squares, wick product, SPDEs, finite element, wiener chaos expansion, gradient method

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: impersonation, image registration, incrimination, object detection, threshold evaluation

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Authors: Ajab G. Majidi, Bilal Bingölbali, Adem Akpınar

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This study aims to investigate the amount of energy (economic wave energy potential) that can be obtained from the existing wave energy converters in the high wave energy potential region of the Black Sea in terms of wave energy potential and their performance at different depths in the region. The data needed for this purpose were obtained using the calibrated nested layered SWAN wave modeling program version 41.01AB, which was forced with Climate Forecast System Reanalysis (CFSR) winds from 1979 to 2009. The wave dataset at a time interval of 2 hours was accumulated for a sub-grid domain for around Karaburun beach in Arnavutkoy, a district of Istanbul city. The annual sea state characteristic matrices for the five different depths along with a vertical line to the coastline were calculated for 31 years. According to the power matrices of different wave energy converter systems and characteristic matrices for each possible installation depth, the probability distribution tables of the specified mean wave period or wave energy period and significant wave height were calculated. Then, by using the relationship between these distribution tables, according to the present wave climate, the energy that the wave energy converter systems at each depth can produce was determined. Thus, the economically feasible potential of the relevant coastal zone was revealed, and the effect of different depths on energy converter systems is presented. The Oceantic at 50, 75 and 100 m depths and Oyster at 5 and 25 m depths presents the best performance. In the 31-year long period 1998 the most and 1989 is the least dynamic year.

Keywords: annual power production, Black Sea, efficiency, power production performance, wave energy converter

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Authors: Anicet Dansou

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Textile reinforced concrete (TRC)is increasingly used nowadays in various fields, in particular civil engineering, where it is mainly used for the reinforcement of damaged reinforced concrete structures. TRC is a composite material composed of multi- or uni-axial textile reinforcements coupled with a fine-grained cementitious matrix. The TRC composite is an alternative solution to the traditional Fiber Reinforcement Polymer (FRP) composite. It has good mechanical performance and better temperature stability but also, it makes it possible to meet the criteria of sustainable development better.TRCs are highly anisotropic composite materials with nonlinear hardening behavior; their macroscopic behavior depends on multi-scale mechanisms. The characterization of these materials through numerical simulation has been the subject of many studies. Since TRCs are multiscale material by definition, numerical multi-scale approaches have emerged as one of the most suitable methods for the simulation of TRCs. They aim to incorporate information pertaining to microscale constitute behavior, mesoscale behavior, and macro-scale structure response within a unified model that enables rapid simulation of structures. The computational costs are hence significantly reduced compared to standard simulation at a fine scale. The fine scale information can be implicitly introduced in the macro scale model: approaches of this type are called non-classical. A representative volume element is defined, and the fine scale information are homogenized over it. Analytical and computational homogenization and nested mesh methods belong to these approaches. On the other hand, in classical approaches, the fine scale information are explicitly introduced in the macro scale model. Such approaches pertain to adaptive mesh refinement strategies, sub-modelling, domain decomposition, and multigrid methods This research presents the main principles of numerical multiscale approaches. Advantages and limitations are identified according to several criteria: the assumptions made (fidelity), the number of input parameters required, the calculation costs (efficiency), etc. A bibliographic study of recent results and advances and of the scientific obstacles to be overcome in order to achieve an effective simulation of textile reinforced concrete in civil engineering is presented. A comparative study is further carried out between several methods for the simulation of TRCs used for the structural reinforcement of reinforced concrete structures.

Keywords: composites structures, multiscale methods, numerical modeling, textile reinforced concrete

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Authors: Ehsan Yari

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In this paper, a numerical study of sheet cavitation has been performed on DTMB4119 and E779A marine propellers with the boundary element method. In propeller design, various parameters of geometry and fluid are incorporated. So a program is needed to solve the flow taking the whole parameters changing into account. The capability of analyzing the wetted and cavitation flow around propellers in steady, unsteady, uniform, and non-uniform conditions while decreasing computational time compared to numerical finite volume methods with acceptable precision are the characteristic features of the present method. Moreover, modifying the position of the detachment point and its corresponding potential value has been considered. Numerical results have been validated with experimental data, showing a good conformation.

Keywords: cavitation, BEM, DTMB4119, E779A

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Authors: Ali Asghar Memon

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A cautious and astute selection of switching devices used in power electronic converters of a switched reluctance (SR) motor is required. It is a matter of choice of best switching devices with respect to their switching ability rather than fulfilling the number of switches. This paper highlights the computational determination of switching losses comprising of switch-on, switch-off and conduction losses respectively by using experimental data in simulation model of a SR machine. The finding of this research is helpful for proper selection of electronic switches and suitable converter topology for switched reluctance motor.

Keywords: converter, operating modes, switched reluctance motor, switching losses

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Authors: Zeinab Yazdanfar, Dilan Robert, Daniel Lester, S. Setunge

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Scour has been identified as the most common threat to bridge stability worldwide. Traditionally, scour around bridge piers is calculated using the empirical approaches that have considerable limitations and are difficult to generalize. The multi-physic nature of scouring which involves turbulent flow, soil mechanics and solid-fluid interactions cannot be captured by simple empirical equations developed based on limited laboratory data. These limitations can be overcome by direct numerical modeling of coupled hydro-mechanical scour process that provides a robust prediction of bridge scour and valuable insights into the scour process. Several numerical models have been proposed in the literature for bridge scour estimation including Eulerian flow models and coupled Euler-Lagrange models incorporating an empirical sediment transport description. However, the contact forces between particles and the flow-particle interaction haven’t been taken into consideration. Incorporating collisional and frictional forces between soil particles as well as the effect of flow-driven forces on particles will facilitate accurate modeling of the complex nature of scour. In this study, a coupled Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) has been developed to simulate the scour process that directly models the hydro-mechanical interactions between the sediment particles and the flowing water. This approach obviates the need for an empirical description as the fundamental fluid-particle, and particle-particle interactions are fully resolved. The sediment bed is simulated as a dense pack of particles and the frictional and collisional forces between particles are calculated, whilst the turbulent fluid flow is modeled using a Reynolds Averaged Navier Stocks (RANS) approach. The CFD-DEM model is validated against experimental data in order to assess the reliability of the CFD-DEM model. The modeling results reveal the criticality of particle impact on the assessment of scour depth which, to the authors’ best knowledge, hasn’t been considered in previous studies. The results of this study open new perspectives to the scour depth and time assessment which is the key to manage the failure risk of bridge infrastructures.

Keywords: bridge scour, discrete element method, CFD-DEM model, multi-phase model

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Authors: Thien X. Dinh, Peter Witt

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A one-dimensional model for the simulation of condensation and solidification of a metallurgical vapor in the mixture of gas during supersonic expansion is presented. In the model, condensation is based on critical nucleation and drop-growth theory. When the temperature falls below the supercooling point, all the formed liquid droplets in the condensation phase are assumed to solidify at an infinite rate. The model was verified with a Computational Fluid Dynamics simulation of magnesium vapor condensation and solidification. The obtained results are in reasonable agreement with CFD data. Therefore, the model is a promising, efficient tool for use in the design process for supersonic nozzles applied in mineral processes since it is faster than the CFD counterpart by an order of magnitude.

Keywords: condensation, metallurgical flow, solidification, supersonic expansion

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Authors: Omar Imine, Mohammed Aounallah, Mustapha Belkadi

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Steady three-dimensional and two free surface waves generated by moving bodies are presented, the flow problem to be simulated is rich in complexity and poses many modeling challenges because of the existence of breaking waves around the ship hull, and because of the interaction of the two-phase flow with the turbulent boundary layer. The results of several simulations are reported. The first study was performed for NACA0012 of hydrofoil with different meshes, this section is analyzed at h/c= 1, 0345 for 2D. In the second simulation, a mathematically defined Wigley hull form is used to investigate the application of a commercial CFD code in prediction of the total resistance and its components from tangential and normal forces on the hull wetted surface. The computed resistance and wave profiles are used to estimate the coefficient of the total resistance for Wigley hull advancing in calm water under steady conditions. The commercial CFD software FLUENT version 12 is used for the computations in the present study. The calculated grid is established using the code computer GAMBIT 2.3.26. The shear stress k-ωSST model is used for turbulence modeling and the volume of the fluid technique is employed to simulate the free-surface motion. The second order upwind scheme is used for discretizing the convection terms in the momentum transport equations, the Modified HRICscheme for VOF discretization. The results obtained compare well with the experimental data.

Keywords: free surface flows, breaking waves, boundary layer, Wigley hull, volume of fluid

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Authors: K. Boumediene, S. E. Belhenniche

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This article presents a numerical analysis of a turbulent flow past DTMB 4119 marine propeller by the means of RANS approach; the propeller designed at David Taylor Model Basin in USA. The purpose of this study is to predict the hydrodynamic performance of the marine propeller, it aims also to compare the results obtained with the experiment carried out in open water tests; a periodical computational domain was created to reduce the unstructured mesh size generated. The standard kw turbulence model for the simulation is selected; the results were in a good agreement. Therefore, the errors were estimated respectively to 1.3% and 5.9% for KT and KQ.

Keywords: propeller flow, CFD simulation, RANS, hydrodynamic performance

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Authors: Dylber Qema

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Driven by recent developments in technology and the growing concern about the sustainability and environmental impact of conventional fuel use, the possibility of producing clean and sustainable energy in significant quantities from renewable energy sources has sparked interest all over the world. Solar energy is one of the sources for the generation of electricity, with no emissions or environmental pollution. The electricity produced by photovoltaics can supply a home or business and can even be sold or exchanged with the grid operator. A very positive effect of using photovoltaic modules is that they do not produce greenhouse gases and do not produce chemical waste, unlike all other forms of energy production. Photovoltaics are becoming one of the largest investments in the field of renewable generating units. Improving the reliability of the electric power system is one of the most important impacts of the installation of photovoltaics (PV). Renewable energy sources are so large that they can meet the energy demands of the whole world, thus enabling sustainable supply as well as reducing local and global atmospheric emissions. Albania is rated by experts as one of the most favorable countries in Europe for the production of electricity from solar panels. But the country currently produces about 1% of its energy from the sun, while the rest of the needs are met by hydropower plants and imports. Albania has very good characteristics in terms of solar radiation (about 1300–1400 kW/m2). Solar energy has great potential and is a permanent source of energy with greater economic efficiency. Photovoltaic energy is also seen as an alternative, as long periods of drought in Albania have produced crises and high costs for securing energy in the foreign market.

Keywords: capacity, ministry of tourism and environment, obstacles, photovoltaic energy, sustainable

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Authors: S. Etaig, R. Hasan, N. Perera

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This paper analyses the heat transfer performance and fluid flow using different nanofluids in a square enclosure. The energy equation and Navier-Stokes equation are solved numerically using finite volume scheme. The effect of volume fraction concentration on the enhancement of heat transfer has been studied icorporating the Brownian motion; the influence of effective thermal conductivity on the enhancement was also investigated for a range of volume fraction concentration. The velocity profile for different Rayleigh number. Water-Cu, water AL2O3 and water-TiO2 were tested.

Keywords: computational fluid dynamics, natural convection, nanofluid and thermal conductivity

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Authors: Sharon-Yasotha Veerayah-Mcgregor, Valipuram Manoranjan

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A backward or inverse problem is known to be an ill-posed problem due to its instability that easily emerges with any slight change within the conditions of the problem. Therefore, only a limited number of numerical approaches are available to solve a backward problem. This paper considers the Nagumo equation, an equation that describes impulse propagation in nerve axons, which also models population growth with the Allee effect. A creative operator splitting numerical scheme is constructed to solve the inverse Nagumo equation. Computational simulations are used to verify that this scheme is stable, accurate, and efficient.

Keywords: inverse/backward equation, operator-splitting, Nagumo equation, ill-posed, finite-difference

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Authors: Prudhvinath Reddy Ankireddy, Narasimha Mangadoddy

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Spiral concentrators are commonly used in various industries, including mineral and coal processing, to efficiently separate materials based on their density and size. In these concentrators, a mixture of solid particles and fluid (usually water) is introduced as feed at the top of a spiral channel. As the mixture flows down the spiral, centrifugal and gravitational forces act on the particles, causing them to stratify based on their density and size. Spiral flows exhibit complex fluid dynamics, and interactions involve multiple phases and components in the process. Understanding the behavior of these phases within the spiral concentrator is crucial for achieving efficient separation. An experimental bi-component particle interaction study is conducted in this work utilizing magnetite (heavier density) and silica (lighter density) with different proportions processed in the spiral concentrator. The observation separation reveals that denser particles accumulate towards the inner region of the spiral trough, while a significant concentration of lighter particles are found close to the outer edge. The 5th turn of the spiral trough is partitioned into five zones to achieve a comprehensive distribution analysis of bicomponent particle segregation. Samples are then gathered from these individual streams using an in-house sample collector, and subsequent analysis is conducted to assess component segregation. Along the trough, there was a decline in the concentration of coarser particles, accompanied by an increase in the concentration of lighter particles. The segregation pattern indicates that the heavier coarse component accumulates in the inner zone, whereas the lighter fine component collects in the outer zone. The middle zone primarily consists of heavier fine particles and lighter coarse particles. The zone-wise results reveal that there is a significant fraction of segregation occurs in inner and middle zones. Finer magnetite and silica particles predominantly accumulate in outer zones with the smallest fraction of segregation. Additionally, numerical simulations are also carried out using the computational fluid dynamics (CFD) model based on the volume of fluid (VOF) approach incorporating the RSM turbulence model. The discrete phase model (DPM) is employed for particle tracking, thereby understanding the particle segregation of magnetite and silica along the spiral trough.

Keywords: spiral concentrator, bi-component particle segregation, computational fluid dynamics, discrete phase model

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Authors: Basil Nkosilathi Dube, Wilson R. Nyemba, Panashe Mandevu

Abstract:

In highway driving, over 50 percent of the power produced by the engine is used to overcome aerodynamic drag, which is a force that opposes a body’s motion through the air. Aerodynamic drag and thus fuel consumption increase rapidly at speeds above 90kph. It is desirable to minimize fuel consumption. Aerodynamic drag reduction in highway driving is the best approach to minimize fuel consumption and to reduce the negative impacts of greenhouse gas emissions on the natural environment. Fuel economy is the ultimate concern of automotive development. This study aims to design and analyze drag-reducing devices for a Mazda T3500 truck, namely, the cab roof and rear (trailer tail) fairings. The aerodynamic effects of adding these append devices were subsequently investigated. To accomplish this, two 3D CAD models of the Mazda truck were designed using the Design Modeler. One, with these, append devices and the other without. The models were exported to ANSYS Fluent for computational fluid dynamics analysis, no wind tunnel tests were performed. A fine mesh with more than 10 million cells was applied in the discretization of the models. The realizable k-ε turbulence model with enhanced wall treatment was used to solve the Reynold’s Averaged Navier-Stokes (RANS) equation. In order to simulate the highway driving conditions, the tests were simulated with a speed of 100 km/h. The effects of these devices were also investigated for low-speed driving. The drag coefficients for both models were obtained from the numerical calculations. By adding the cab roof and rear (trailer tail) fairings, the simulations show a significant reduction in aerodynamic drag at a higher speed. The results show that the greatest drag reduction is obtained when both devices are used. Visuals from post-processing show that the rear fairing minimized the low-pressure region at the rear of the trailer when moving at highway speed. The rear fairing achieved this by streamlining the turbulent airflow, thereby delaying airflow separation. For lower speeds, there were no significant differences in drag coefficients for both models (original and modified). The results show that these devices can be adopted for improving the aerodynamic efficiency of the Mazda T3500 truck at highway speeds.

Keywords: aerodynamic drag, computation fluid dynamics, fluent, fuel consumption

Procedia PDF Downloads 138

Authors: Erick C. Valverde, Wansu Lim

Abstract:

Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

Procedia PDF Downloads 118

Authors: Somveer Singh, Vineet Kumar Singh

Abstract:

We present a new model based on viscoelasticity for the Non-Newtonian fluids.We use a matrix formulated algorithm to approximate solutions of a class of partial integro-differential equations with the given initial and boundary conditions. Some numerical results are presented to simplify application of operational matrix formulation and reduce the computational cost. Convergence analysis, error estimation and numerical stability of the method are also investigated. Finally, some test examples are given to demonstrate accuracy and efficiency of the proposed method.

Keywords: Legendre Wavelets, operational matrices, partial integro-differential equation, viscoelasticity

Procedia PDF Downloads 336