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Computation, Volume 8, Issue 1 (March 2020) – 21 articles

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Open AccessArticle
Nondimensional Characterization of the Operational Envelope of a Wet Friction Clutch
Computation 2020, 8(1), 21; https://doi.org/10.3390/computation8010021 - 24 Mar 2020
Viewed by 287
Abstract
In recent years, multidisc wet friction clutches are used in demanding powertrains of automatic and dual clutch transmissions targeting high efficiency and smoothness during gearshift. However, the developed flow pattern between the clutch discs is significantly complex and the Computational Fluid Dynamics (CFD) [...] Read more.
In recent years, multidisc wet friction clutches are used in demanding powertrains of automatic and dual clutch transmissions targeting high efficiency and smoothness during gearshift. However, the developed flow pattern between the clutch discs is significantly complex and the Computational Fluid Dynamics (CFD) methods employed are quite demanding in terms of computational cost. To deal with this issue semi-analytical solutions were derived, which are limited, however, to specific problems, in order to obtain handy expressions, while also providing insight to the wet clutch physics. Nevertheless, this lack of global validity is counterbalanced by the fact that the governing equations become analytically solvable at specific operational conditions with satisfactory accuracy, provided that the simplifications rendering the truncated terms inactive hold true. In this work, a quantitative way of determining the relative weight of each term of the Navier-Stokes (NS) equations set is presented, based on the post-processing of CFD results using the Buckingham “π-theorem”. The sets of nondimensional numbers created were used to describe and model the physics of the wet clutch. Full article
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Open AccessArticle
ThunderX2 Performance and Energy-Efficiency for HPC Workloads
Computation 2020, 8(1), 20; https://doi.org/10.3390/computation8010020 - 23 Mar 2020
Viewed by 416
Abstract
In the last years, the energy efficiency of HPC systems is increasingly becoming of paramount importance for environmental, technical, and economical reasons. Several projects have investigated the use of different processors and accelerators in the quest of building systems able to achieve high [...] Read more.
In the last years, the energy efficiency of HPC systems is increasingly becoming of paramount importance for environmental, technical, and economical reasons. Several projects have investigated the use of different processors and accelerators in the quest of building systems able to achieve high energy efficiency levels for data centers and HPC installations. In this context, Arm CPU architecture has received a lot of attention given its wide use in low-power and energy-limited applications, but server grade processors have appeared on the market just recently. In this study, we targeted the Marvell ThunderX2, one of the latest Arm-based processors developed to fit the requirements of high performance computing applications. Our interest is mainly focused on the assessment in the context of large HPC installations, and thus we evaluated both computing performance and energy efficiency, using the ERT benchmark and two HPC production ready applications. We finally compared the results with other processors commonly used in large parallel systems and highlight the characteristics of applications which could benefit from the ThunderX2 architecture, in terms of both computing performance and energy efficiency. Pursuing this aim, we also describe how ERT has been modified and optimized for ThunderX2, and how to monitor power drain while running applications on this processor. Full article
(This article belongs to the Special Issue Energy-Efficient Computing on Parallel Architectures)
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Open AccessArticle
Investigation of the Effect of Geometry Characteristics on Bending Stress of Asymmetric Helical Gears by Using Finite Elements Analysis
Computation 2020, 8(1), 19; https://doi.org/10.3390/computation8010019 - 21 Mar 2020
Viewed by 294
Abstract
Asymmetric helical gears have been under investigation for more than two decades due to their inherent ability to handle greater bending loads than their spur counterparts of comparable size (i.e., the number of teeth and module). For this type of gear, only one [...] Read more.
Asymmetric helical gears have been under investigation for more than two decades due to their inherent ability to handle greater bending loads than their spur counterparts of comparable size (i.e., the number of teeth and module). For this type of gear, only one side of each gear tooth in a geared mechanism is usually loaded (driving/driven side), whereas the other remains mostly unloaded (coast side). Due to the asymmetry of the tooth, a nonlinear model is used. For that reason, a numerical design procedure is introduced involving the geometrical and structural modelling of conjugate helical gear sets. This is accomplished with the tool of Finite Element Analysis (FEA) which is presented to the scientific literature. The basic geometry is initially generated in 2D and thereafter converted to a 3D shape using Boolean operations. The rigid body which is necessary for FEA software is produced from Computer Aided Design (CAD) software (SolidWorks). This paper is focused on the effect analysis of different geometry characteristics on bending loads. The effects on bending stress play a significant role in gear design wherein its magnitude is controlled by the nominal bending stress and the stress concentration due to the geometrical shape of the teeth. The analysis of this effect of the different geometrical characteristics in the load is presented in detail. Moreover, a comparison of the stresses that are developed between pairs with asymmetrical helical teeth by keeping one geometric parameter constant and modifying the values of the other two parameters is presented. Full article
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Open AccessArticle
Simulation-Based EDAs for Stochastic Programming Problems
Computation 2020, 8(1), 18; https://doi.org/10.3390/computation8010018 - 18 Mar 2020
Viewed by 291
Abstract
With the rapid growth of simulation software packages, generating practical tools for simulation-based optimization has attracted a lot of interest over the last decades. In this paper, a modified method of Estimation of Distribution Algorithms (EDAs) is constructed by a combination with variable-sample [...] Read more.
With the rapid growth of simulation software packages, generating practical tools for simulation-based optimization has attracted a lot of interest over the last decades. In this paper, a modified method of Estimation of Distribution Algorithms (EDAs) is constructed by a combination with variable-sample techniques to deal with simulation-based optimization problems. Moreover, a new variable-sample technique is introduced to support the search process whenever the sample sizes are small, especially in the beginning of the search process. The proposed method shows efficient results by simulating several numerical experiments. Full article
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Open AccessArticle
Some New Results on Coincidence Points for Multivalued Suzuki-Type Mappings in Fairly Complete Spaces
Computation 2020, 8(1), 17; https://doi.org/10.3390/computation8010017 - 17 Mar 2020
Cited by 1 | Viewed by 243
Abstract
In this paper, we introduce Suzuki-type ( α , β , γ g ) - generalized and modified proximal contractive mappings. We establish some coincidence and best proximity point results in fairly complete spaces. Also, we provide coincidence and best proximity point results [...] Read more.
In this paper, we introduce Suzuki-type ( α , β , γ g ) - generalized and modified proximal contractive mappings. We establish some coincidence and best proximity point results in fairly complete spaces. Also, we provide coincidence and best proximity point results in partially ordered complete metric spaces for Suzuki-type ( α , β , γ g ) - generalized and modified proximal contractive mappings. Furthermore, some examples are presented in each section to elaborate and explain the usability of the obtained results. As an application, we obtain fixed-point results in metric spaces and in partially ordered metric spaces. The results obtained in this article further extend, modify and generalize the various results in the literature. Full article
Open AccessArticle
On Instability Analysis of Linear Feedback Systems
Computation 2020, 8(1), 16; https://doi.org/10.3390/computation8010016 - 06 Mar 2020
Viewed by 370
Abstract
The numerical approximation of the μ -value is key towards the measurement of instability, stability analysis, robustness, and the performance of linear feedback systems in system theory. The MATLAB function mussv available in MATLAB Control Toolbox efficiently computes both lower and upper bounds [...] Read more.
The numerical approximation of the μ -value is key towards the measurement of instability, stability analysis, robustness, and the performance of linear feedback systems in system theory. The MATLAB function mussv available in MATLAB Control Toolbox efficiently computes both lower and upper bounds of the μ -value. This article deals with the numerical approximations of the lower bounds of μ -values by means of low-rank ordinary differential equation (ODE)-based techniques. The numerical simulation shows that approximated lower bounds of μ -values are much tighter when compared to those obtained by the MATLAB function mussv. Full article
Open AccessReview
Machine-Learning Methods for Computational Science and Engineering
Computation 2020, 8(1), 15; https://doi.org/10.3390/computation8010015 - 03 Mar 2020
Viewed by 603
Abstract
The re-kindled fascination in machine learning (ML), observed over the last few decades, has also percolated into natural sciences and engineering. ML algorithms are now used in scientific computing, as well as in data-mining and processing. In this paper, we provide a review [...] Read more.
The re-kindled fascination in machine learning (ML), observed over the last few decades, has also percolated into natural sciences and engineering. ML algorithms are now used in scientific computing, as well as in data-mining and processing. In this paper, we provide a review of the state-of-the-art in ML for computational science and engineering. We discuss ways of using ML to speed up or improve the quality of simulation techniques such as computational fluid dynamics, molecular dynamics, and structural analysis. We explore the ability of ML to produce computationally efficient surrogate models of physical applications that circumvent the need for the more expensive simulation techniques entirely. We also discuss how ML can be used to process large amounts of data, using as examples many different scientific fields, such as engineering, medicine, astronomy and computing. Finally, we review how ML has been used to create more realistic and responsive virtual reality applications. Full article
(This article belongs to the Special Issue Machine Learning for Computational Science and Engineering)
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Open AccessArticle
Range of Applying the Boundary Condition at Fluid/Porous Interface and Evaluation of Beavers and Joseph’s Slip Coefficient Using Finite Element Method
Computation 2020, 8(1), 14; https://doi.org/10.3390/computation8010014 - 24 Feb 2020
Viewed by 328
Abstract
In this work, Finite Element Method (FEM) is applied to obtain the condition at the boundary of the interface between a channel and a porous medium. The boundary conditions that should be applied to the inhomogeneous interface zone between the two homogeneous regions [...] Read more.
In this work, Finite Element Method (FEM) is applied to obtain the condition at the boundary of the interface between a channel and a porous medium. The boundary conditions that should be applied to the inhomogeneous interface zone between the two homogeneous regions of free fluid and porous medium are derived. The comparison has been performed for porous material characterizations to provide the velocity at the inhomogeneous interface zone with variable permeability between the two homogeneous regions of free fluid and porous medium. Also, the dependence of the slip coefficient on the thickness of the transition zone is established and the values of the thickness are so justified that the numerical results and the numerical results of our proposed technique are found to be in good agreement with experimental results in the literature. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Effect of Structure on the Thermal-Mechanical Performance of Fully Ceramic Microencapsulated Fuel
Computation 2020, 8(1), 13; https://doi.org/10.3390/computation8010013 - 21 Feb 2020
Cited by 1 | Viewed by 287
Abstract
The effect of non-fuel part size on the thermal-mechanical performance of fully ceramic microencapsulated (FCMTM) Fuel was investigated, and the non-fuel part size was selected according to integrity maintaining of non-fuel part and silicon carbide (SiC) layers. The non-fuel part size can affect [...] Read more.
The effect of non-fuel part size on the thermal-mechanical performance of fully ceramic microencapsulated (FCMTM) Fuel was investigated, and the non-fuel part size was selected according to integrity maintaining of non-fuel part and silicon carbide (SiC) layers. The non-fuel part size can affect the FCMTM temperature and stress distribution greatly by changing the distance between tristructural isotropic (TRISO) particles. The maximum temperature of SiC matrix increased from 1220 K to 1450 K with the non-fuel part size increasing from 100 μm to 500 μm, and the matrix temperature of all the samples was lower than the decomposition point of SiC ceramics. The maximum hoop stress decreased with non-fuel part size, but the inner part exhibiteda crosscurrent trend. The inner part of the SiC matrix lost structure integrity because of the large hoop stress caused by the deformation of TRISO particles, however, the non-fuel parts of FCMTM pellet may maintain their integrity when the non-fuel part size was larger than 300 μm. SiC layers hoop stress increased with non-fuel part size, and the failure probability of SiC layer was lower than 2.2 × 10−4 for the FCMTM pellet with small non-fuel part size. The integrity of non-fuel and SiC layers can be maintained for the FCMTM pellet with the non-fuel part size from 300 μm to 400 μm. Full article
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Open AccessArticle
Improved Sampling in Ab Initio Free Energy Calculations of Biomolecules at Solid–Liquid Interfaces: Tight-Binding Assessment of Charged Amino Acids on TiO2 Anatase (101)
Computation 2020, 8(1), 12; https://doi.org/10.3390/computation8010012 - 12 Feb 2020
Viewed by 501
Abstract
Atomistic simulations can complement the scarce experimental data on free energies of molecules at bio-inorganic interfaces. In molecular simulations, adsorption free energy landscapes are efficiently explored with advanced sampling methods, but classical dynamics is unable to capture charge transfer and polarization at the [...] Read more.
Atomistic simulations can complement the scarce experimental data on free energies of molecules at bio-inorganic interfaces. In molecular simulations, adsorption free energy landscapes are efficiently explored with advanced sampling methods, but classical dynamics is unable to capture charge transfer and polarization at the solid–liquid interface. Ab initio simulations do not suffer from this flaw, but only at the expense of an overwhelming computational cost. Here, we introduce a protocol for adsorption free energy calculations that improves sampling on the timescales relevant to ab initio simulations. As a case study, we calculate adsorption free energies of the charged amino acids Lysine and Aspartate on the fully hydrated anatase (101) TiO2 surface using tight-binding forces. We find that the first-principle description of the system significantly contributes to the adsorption free energies, which is overlooked by calculations with previous methods. Full article
(This article belongs to the Section Computational Chemistry)
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Open AccessArticle
Complex Modeling and Design of Catalytic Reactors Using Multiscale Approach—Part 1: Diffusion in Porous Catalyst
Computation 2020, 8(1), 11; https://doi.org/10.3390/computation8010011 - 11 Feb 2020
Viewed by 320
Abstract
The presented work is dedicated to the modeling of catalytic reactors using a multiscale approach, based on the combination of cellular automata and Computational Fluid Dynamics (CFD). This work describes the first step in the development of a complex model of catalytic reactors [...] Read more.
The presented work is dedicated to the modeling of catalytic reactors using a multiscale approach, based on the combination of cellular automata and Computational Fluid Dynamics (CFD). This work describes the first step in the development of a complex model of catalytic reactors and considers the diffusion of components inside a porous structure of an aluminosilicate catalyst. Various cellular automata were used to generate virtual porous structures of catalysts with specific surface areas equal to 250, 500, and 700 m2/g and to calculate the effective diffusion coefficient for the substance transfer inside the catalysts. The obtained effective diffusion coefficient was included in the CFD model of a laboratory scale reactor simulating extraction of aniline from the catalyst with methanol. Results of numerical experiments carried out using the CFD model were compared with the corresponding experimental data. It is shown that the proposed approach is suitable for describing macroscopic and microscopic mass transfer phenomena on consideration of the catalyst’s structure. Full article
(This article belongs to the Section Computational Chemistry)
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Open AccessArticle
Targeted Drug Delivery of Magnetic Nano-Particle in the Specific Lung Region
Computation 2020, 8(1), 10; https://doi.org/10.3390/computation8010010 - 04 Feb 2020
Cited by 1 | Viewed by 488
Abstract
Aerosolized drug inhalation plays an important role in the treatment of respiratory diseases. All of the published in silico, in vivo, and in vitro studies have improved the knowledge of aerosol delivery in the human respiratory system. However, aerosolized magnetic nano-particle (MNP) transport [...] Read more.
Aerosolized drug inhalation plays an important role in the treatment of respiratory diseases. All of the published in silico, in vivo, and in vitro studies have improved the knowledge of aerosol delivery in the human respiratory system. However, aerosolized magnetic nano-particle (MNP) transport and deposition (TD) for the specific position of the human lung are still unavailable in the literature. Therefore, this study is aimed to provide an understanding of the magnetic nano-particle TD in the targeted region by imposing an external magnetic field for the development of future therapeutics. Uniform aerosolized nano-particle TD in the specific position of the lung airways will be modelled by adopting turbulence k–ω low Reynolds number simulation. The Euler–Lagrange (E–L) approach and the magneto hydrodynamics (MHD) model are incorporated in the ANSYS fluent (18.0) solver to investigate the targeted nano-particle TD. The human physical activity conditions of sleeping, resting, light activity and fast breathing are considered in this study. The aerosolized drug particles are navigated to the targeted position under the influence of external magnetic force (EMF), which is applied in two different positions of the two-generation lung airways. A numerical particle tracing model is also developed to predict the magnetic drug targeting behavior in the lung. The numerical results reveal that nano-particle deposition efficiency (DE) in two different magnetic field position is different for various physical activities, which could be helpful for targeted drug delivery to a specific region of the lung after extensive clinical trials. This process will also be cost-effective and will minimize unwanted side effects due to systemic drug distribution in the lung. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
An Incompressible Smoothed Particle Hydrodynamics (ISPH) Model of Direct Laser Interference Patterning
Computation 2020, 8(1), 9; https://doi.org/10.3390/computation8010009 - 30 Jan 2020
Viewed by 664
Abstract
Functional surfaces characterised by periodic microstructures are sought in numerous technological applications. Direct laser interference patterning (DLIP) is a technique that allows the fabrication of microscopic periodic features on different materials, e.g., metals. The mechanisms effective during nanosecond pulsed DLIP of metal surfaces [...] Read more.
Functional surfaces characterised by periodic microstructures are sought in numerous technological applications. Direct laser interference patterning (DLIP) is a technique that allows the fabrication of microscopic periodic features on different materials, e.g., metals. The mechanisms effective during nanosecond pulsed DLIP of metal surfaces are not yet fully understood. In the present investigation, the heat transfer and fluid flow occurring in the metal substrate during the DLIP process are simulated using a smoothed particle hydrodynamics (SPH) methodology. The melt pool convection, driven by surface tension gradients constituting shear stresses according to the Marangoni boundary condition, is solved by an incompressible SPH (ISPH) method. The DLIP simulations reveal a distinct behaviour of the considered substrate materials stainless steel and high-purity aluminium. In particular, the aluminium substrate exhibits a considerably deeper melt pool and remarkable velocity magnitudes of the thermocapillary flow during the patterning process. On the other hand, convection is less pronounced in the processing of stainless steel, whereas the surface temperature is consistently higher. Marangoni convection is therefore a conceivable effective mechanism in the structuring of aluminium at moderate fluences. The different character of the melt pool flow during DLIP of stainless steel and aluminium is confirmed by experimental observations. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Improving Convergence Analysis of the Newton–Kurchatov Method under Weak Conditions
Computation 2020, 8(1), 8; https://doi.org/10.3390/computation8010008 - 26 Jan 2020
Viewed by 373
Abstract
The technique of using the restricted convergence region is applied to study a semilocal convergence of the Newton–Kurchatov method. The analysis is provided under weak conditions for the derivatives and the first order divided differences. Consequently, weaker sufficient convergence criteria and more accurate [...] Read more.
The technique of using the restricted convergence region is applied to study a semilocal convergence of the Newton–Kurchatov method. The analysis is provided under weak conditions for the derivatives and the first order divided differences. Consequently, weaker sufficient convergence criteria and more accurate error estimates are retrieved. A special case of weak conditions is also considered. Full article
Open AccessEditorial
Acknowledgement to Reviewers of Computation in 2019
Computation 2020, 8(1), 7; https://doi.org/10.3390/computation8010007 - 14 Jan 2020
Viewed by 318
Abstract
The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not[...] Full article
Open AccessArticle
Clustering versus Incremental Learning Multi-Codebook Fuzzy Neural Network for Multi-Modal Data Classification
Computation 2020, 8(1), 6; https://doi.org/10.3390/computation8010006 - 13 Jan 2020
Viewed by 382
Abstract
One of the challenges in machine learning is a classification in multi-modal data. The problem needs a customized method as the data has a feature that spreads in several areas. This study proposed a multi-codebook fuzzy neural network classifiers using clustering and incremental [...] Read more.
One of the challenges in machine learning is a classification in multi-modal data. The problem needs a customized method as the data has a feature that spreads in several areas. This study proposed a multi-codebook fuzzy neural network classifiers using clustering and incremental learning approaches to deal with multi-modal data classification. The clustering methods used are K-Means and GMM clustering. Experiment result, on a synthetic dataset, the proposed method achieved the highest performance with 84.76% accuracy. Whereas on the benchmark dataset, the proposed method has the highest performance with 79.94% accuracy. The proposed method has 24.9% and 4.7% improvements in synthetic and benchmark datasets respectively compared to the original version. The proposed classifier has better accuracy compared to a popular neural network with 10% and 4.7% margin in synthetic and benchmark dataset respectively. Full article
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Open AccessArticle
An Evolutionary Computing Model for the Study of Within-Host Evolution
Computation 2020, 8(1), 5; https://doi.org/10.3390/computation8010005 - 09 Jan 2020
Viewed by 429
Abstract
Evolution of an individual within another individual is known as within-host dynamics (WHD). The most common modeling technique to study WHD involves ordinary differential equations (ODEs). In the field of biology, models of this kind assume, for example, that both the number of [...] Read more.
Evolution of an individual within another individual is known as within-host dynamics (WHD). The most common modeling technique to study WHD involves ordinary differential equations (ODEs). In the field of biology, models of this kind assume, for example, that both the number of viruses and the number of mouse cells susceptible to being infected change according to their interaction as stated in the ODE model. However, viruses can undergo mutations and, consequently, evolve inside the mouse, whereas the mouse, in turn, displays evolutionary mechanisms through its immune system (e.g., clonal selection), defending against the invading virus. In this work, as the main novelty, we propose an evolutionary WHD model simulating the coexistence of an evolving invader within a host. In addition, instead of using ODEs we developed an alternative methodology consisting of the hybridization of a genetic algorithm with an artificial immune system. Aside from the model, interest in biology, and its potential clinical use, the proposed WHD model may be useful in those cases where the invader exhibits evolutionary changes, for instance, in the design of anti-virus software, intrusion detection algorithms in a corporation’s computer systems, etc. The model successfully simulates two intruder detection paradigms (i.e., humoral detection, danger detection) in which the intruder represents an evolving invader or guest (e.g., virus, computer program,) that infects a host (e.g., mouse, computer memory). The obtained results open up the possibility of simulating environments in which two entities (guest versus host) compete evolutionarily with each other when occupying the same space (e.g., organ cells, computer memory, network). Full article
(This article belongs to the Section Computational Biology)
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Open AccessArticle
GPU Computing with Python: Performance, Energy Efficiency and Usability
Computation 2020, 8(1), 4; https://doi.org/10.3390/computation8010004 - 09 Jan 2020
Viewed by 496
Abstract
In this work, we examine the performance, energy efficiency, and usability when using Python for developing high-performance computing codes running on the graphics processing unit (GPU). We investigate the portability of performance and energy efficiency between Compute Unified Device Architecture (CUDA) and Open [...] Read more.
In this work, we examine the performance, energy efficiency, and usability when using Python for developing high-performance computing codes running on the graphics processing unit (GPU). We investigate the portability of performance and energy efficiency between Compute Unified Device Architecture (CUDA) and Open Compute Language (OpenCL); between GPU generations; and between low-end, mid-range, and high-end GPUs. Our findings showed that the impact of using Python is negligible for our applications, and furthermore, CUDA and OpenCL applications tuned to an equivalent level can in many cases obtain the same computational performance. Our experiments showed that performance in general varies more between different GPUs than between using CUDA and OpenCL. We also show that tuning for performance is a good way of tuning for energy efficiency, but that specific tuning is needed to obtain optimal energy efficiency. Full article
(This article belongs to the Special Issue Energy-Efficient Computing on Parallel Architectures)
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Open AccessArticle
Heterogeneous Computing (CPU–GPU) for Pollution Dispersion in an Urban Environment
Computation 2020, 8(1), 3; https://doi.org/10.3390/computation8010003 - 07 Jan 2020
Cited by 1 | Viewed by 372
Abstract
The use of Computational Fluid Dynamics (CFD) to assist in air quality studies in urban environments can provide accurate results for the dispersion of pollutants. However, due to the computational resources needed, simulation domain sizes tend to be limited. This study aims to [...] Read more.
The use of Computational Fluid Dynamics (CFD) to assist in air quality studies in urban environments can provide accurate results for the dispersion of pollutants. However, due to the computational resources needed, simulation domain sizes tend to be limited. This study aims to improve the computational efficiency of an emission and dispersion model implemented in a CPU-based solver by migrating it to a CPU–GPU-based one. The migration of the functions that handle boundary conditions and source terms for the pollutants is explained, as well as the main differences present in the solvers used. Once implemented, the model was used to run simulations with both engines on different platforms, enabling the comparison between them and reaching promising time improvements in favor of the use of GPUs. Full article
(This article belongs to the Special Issue Computational Heat, Mass, and Momentum Transfer—II)
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Open AccessArticle
Effect of Mesh Sensitivity and Cohesive Properties on Simulation of Typha Fiber/Epoxy Microbond Test
Computation 2020, 8(1), 2; https://doi.org/10.3390/computation8010002 - 03 Jan 2020
Viewed by 450
Abstract
The microbond test for natural fibers is difficult to conduct experimentally due to several challenges including controlling the gap distance of the blade, the meniscus shape, and the large data spread. In this study, a finite element simulation was performed to investigate the [...] Read more.
The microbond test for natural fibers is difficult to conduct experimentally due to several challenges including controlling the gap distance of the blade, the meniscus shape, and the large data spread. In this study, a finite element simulation was performed to investigate the effects of the bonding characteristics in the interface between the fiber and matrix on the Typha fiber/epoxy microbond test. Our aim was to obtain the accurate mesh and cohesive properties via simulation of the Typha fiber/epoxy microbond test using the cohesive zone model technique. The axisymmetric model was generated to model the microbond test specimen with a cohesive layer between the fiber and matrix. The cohesive parameter and mesh type were varied to determine the appropriate cohesive properties and mesh type. The fine mesh with 61,016 elements and cohesive properties including stiffness coefficients Knn = 2700 N/mm3, Ktt = 2700 N/mm3, and Kss = 2700 N/mm3; fracture energy of 15.15 N/mm; and damage initiation tnn = 270 N/mm2, ttt = 270 N/mm2, and tss = 270 N/mm2 were the most suitable. The cohesive zone model can describe the debonding process in the simulation of the Typha fiber/epoxy microbond test. Therefore, the results of the Typha fiber/epoxy microbond simulation can be used in the simulation of Typha fiber reinforced composites at the macro-scale. Full article
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Open AccessArticle
An Efficient Two-Layer Non-Hydrostatic Model for Investigating Wave Run-Up Phenomena
Computation 2020, 8(1), 1; https://doi.org/10.3390/computation8010001 - 27 Dec 2019
Viewed by 515
Abstract
In this paper, we study the maximum run-up of solitary waves on a sloping beach and over a reef through a non-hydrostatic model. We do a modification on the non-hydrostatic model derived by Stelling and Zijlema. The model is approximated by resolving the [...] Read more.
In this paper, we study the maximum run-up of solitary waves on a sloping beach and over a reef through a non-hydrostatic model. We do a modification on the non-hydrostatic model derived by Stelling and Zijlema. The model is approximated by resolving the vertical fluid depth into two-layer system. In contrast to the two-layer model proposed by Stelling, here, we have a block of a tridiagonal matrix for the hydrodynamic pressure. The equations are then solved by applying a staggered finite volume method with predictor-corrector step. For validation, several test cases are presented. The first test is simulating the propagation of solitary waves over a flat bottom. Good results in amplitude and shape preservation are obtained. Furthermore, run-up simulations are conducted for solitary waves climbing up a sloping beach, following the experimental set-up by Synolakis. In this case, two simulations are performed with solitary waves of small and large amplitude. Again, good agreements are obtained, especially for the prediction of run-up height. Moreover, we validate our numerical scheme for wave run-up simulation over a reef, and the result confirms the experimental data. Full article
(This article belongs to the Section Computational Engineering)
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