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Computation, Volume 9, Issue 2 (February 2021) – 17 articles

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25 pages, 7083 KiB  
Article
Criminal Intention Detection at Early Stages of Shoplifting Cases by Using 3D Convolutional Neural Networks
by Guillermo A. Martínez-Mascorro, José R. Abreu-Pederzini, José C. Ortiz-Bayliss, Angel Garcia-Collantes and Hugo Terashima-Marín
Computation 2021, 9(2), 24; https://doi.org/10.3390/computation9020024 - 23 Feb 2021
Cited by 25 | Viewed by 5043
Abstract
Crime generates significant losses, both human and economic. Every year, billions of dollars are lost due to attacks, crimes, and scams. Surveillance video camera networks generate vast amounts of data, and the surveillance staff cannot process all the information in real-time. Human sight [...] Read more.
Crime generates significant losses, both human and economic. Every year, billions of dollars are lost due to attacks, crimes, and scams. Surveillance video camera networks generate vast amounts of data, and the surveillance staff cannot process all the information in real-time. Human sight has critical limitations. Among those limitations, visual focus is one of the most critical when dealing with surveillance. For example, in a surveillance room, a crime can occur in a different screen segment or on a distinct monitor, and the surveillance staff may overlook it. Our proposal focuses on shoplifting crimes by analyzing situations that an average person will consider as typical conditions, but may eventually lead to a crime. While other approaches identify the crime itself, we instead model suspicious behavior—the one that may occur before the build-up phase of a crime—by detecting precise segments of a video with a high probability of containing a shoplifting crime. By doing so, we provide the staff with more opportunities to act and prevent crime. We implemented a 3DCNN model as a video feature extractor and tested its performance on a dataset composed of daily action and shoplifting samples. The results are encouraging as the model correctly classifies suspicious behavior in most of the scenarios where it was tested. For example, when classifying suspicious behavior, the best model generated in this work obtains precision and recall values of 0.8571 and 1 in one of the test scenarios, respectively. Full article
(This article belongs to the Section Computational Engineering)
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30 pages, 6832 KiB  
Article
Modified ALNS Algorithm for a Processing Application of Family Tourist Route Planning: A Case Study of Buriram in Thailand
by Narisara Khamsing, Kantimarn Chindaprasert, Rapeepan Pitakaso, Worapot Sirirak and Chalermchat Theeraviriya
Computation 2021, 9(2), 23; https://doi.org/10.3390/computation9020023 - 22 Feb 2021
Cited by 17 | Viewed by 3288
Abstract
This research presents a solution to the family tourism route problem by considering daily time windows. To find the best solution for travel routing, the modified adaptive large neighborhood search (MALNS) method, using the four destructions and the four reconstructions approach, is applied [...] Read more.
This research presents a solution to the family tourism route problem by considering daily time windows. To find the best solution for travel routing, the modified adaptive large neighborhood search (MALNS) method, using the four destructions and the four reconstructions approach, is applied here. The solution finding performance of the MALNS method is compared with an exact method running on the Lingo program. As shown by various solutions, the MALNS method can balance travel routing designs, including when many tourist attractions are present in each path. Furthermore, the results of the MALNS method are not significantly different from the results of the exact method for small problem sizes. For medium and large problem sizes, the MALNS method shows a higher performance and a smaller processing time for finding solutions. The values for the average total travel cost and average travel satisfaction rating derived by the MALNS method are approximately 0.18% for a medium problem and 0.05% for a large problem, 0.24% for a medium problem, and 0.21% for a large problem, respectively. The values derived from the exact method are slightly different. Moreover, the MALNS method calculation requires less processing time than the exact method, amounting to approximately 99.95% of the time required for the exact method. In this case study, the MALNS algorithm result shows a suitable balance of satisfaction and number of tourism places in relation to the differences between family members of different ages and genders in terms of satisfaction in tour route planning. The proposed solution methodology presents an effective high-quality solution, suggesting that the MALNS method has the potential to be a great competitive algorithm. According to the empirical results shown here, the MALNS method would be useful for creating route plans for tourism organizations that support travel route selection for family tours in Thailand. Full article
(This article belongs to the Section Computational Engineering)
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15 pages, 325 KiB  
Article
Improved Stability Criteria on Linear Systems with Distributed Interval Time-Varying Delays and Nonlinear Perturbations
by Jitsin Piyawatthanachot, Narongsak Yotha and Kanit Mukdasai
Computation 2021, 9(2), 22; https://doi.org/10.3390/computation9020022 - 21 Feb 2021
Viewed by 1859
Abstract
The problem of delay-range-dependent stability analysis for linear systems with distributed time-varying delays and nonlinear perturbations is studied without using the model transformation and delay-decomposition approach. The less conservative stability criteria are obtained for the systems by constructing a new augmented Lyapunov–Krasovskii functional [...] Read more.
The problem of delay-range-dependent stability analysis for linear systems with distributed time-varying delays and nonlinear perturbations is studied without using the model transformation and delay-decomposition approach. The less conservative stability criteria are obtained for the systems by constructing a new augmented Lyapunov–Krasovskii functional and various inequalities, which are presented in terms of linear matrix inequalities (LMIs). Four numerical examples are demonstrated for the results given to illustrate the effectiveness and improvement over other methods. Full article
22 pages, 2094 KiB  
Article
Modified Fast Inverse Square Root and Square Root Approximation Algorithms: The Method of Switching Magic Constants
by Leonid V. Moroz, Volodymyr V. Samotyy and Oleh Y. Horyachyy
Computation 2021, 9(2), 21; https://doi.org/10.3390/computation9020021 - 17 Feb 2021
Cited by 8 | Viewed by 4872
Abstract
Many low-cost platforms that support floating-point arithmetic, such as microcontrollers and field-programmable gate arrays, do not include fast hardware or software methods for calculating the square root and/or reciprocal square root. Typically, such functions are implemented using direct lookup tables or polynomial approximations, [...] Read more.
Many low-cost platforms that support floating-point arithmetic, such as microcontrollers and field-programmable gate arrays, do not include fast hardware or software methods for calculating the square root and/or reciprocal square root. Typically, such functions are implemented using direct lookup tables or polynomial approximations, with a subsequent application of the Newton–Raphson method. Other, more complex solutions include high-radix digit-recurrence and bipartite or multipartite table-based methods. In contrast, this article proposes a simple modification of the fast inverse square root method that has high accuracy and relatively low latency. Algorithms are given in C/C++ for single- and double-precision numbers in the IEEE 754 format for both square root and reciprocal square root functions. These are based on the switching of magic constants in the initial approximation, depending on the input interval of the normalized floating-point numbers, in order to minimize the maximum relative error on each subinterval after the first iteration—giving 13 correct bits of the result. Our experimental results show that the proposed algorithms provide a fairly good trade-off between accuracy and latency after two iterations for numbers of type float, and after three iterations for numbers of type double when using fused multiply–add instructions—giving almost complete accuracy. Full article
(This article belongs to the Section Computational Engineering)
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15 pages, 502 KiB  
Article
Deep Learning for Fake News Detection in a Pairwise Textual Input Schema
by Despoina Mouratidis, Maria Nefeli Nikiforos and Katia Lida Kermanidis
Computation 2021, 9(2), 20; https://doi.org/10.3390/computation9020020 - 17 Feb 2021
Cited by 22 | Viewed by 5650
Abstract
In the past decade, the rapid spread of large volumes of online information among an increasing number of social network users is observed. It is a phenomenon that has often been exploited by malicious users and entities, which forge, distribute, and reproduce fake [...] Read more.
In the past decade, the rapid spread of large volumes of online information among an increasing number of social network users is observed. It is a phenomenon that has often been exploited by malicious users and entities, which forge, distribute, and reproduce fake news and propaganda. In this paper, we present a novel approach to the automatic detection of fake news on Twitter that involves (a) pairwise text input, (b) a novel deep neural network learning architecture that allows for flexible input fusion at various network layers, and (c) various input modes, like word embeddings and both linguistic and network account features. Furthermore, tweets are innovatively separated into news headers and news text, and an extensive experimental setup performs classification tests using both. Our main results show high overall accuracy performance in fake news detection. The proposed deep learning architecture outperforms the state-of-the-art classifiers, while using fewer features and embeddings from the tweet text. Full article
(This article belongs to the Special Issue Recent Advances in Computation Engineering)
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11 pages, 3546 KiB  
Article
A Power Dissipation Monitoring Circuit for Intrusion Detection and Botnet Prevention on IoT Devices
by Dimitrios Myridakis, Paul Myridakis and Athanasios Kakarountas
Computation 2021, 9(2), 19; https://doi.org/10.3390/computation9020019 - 6 Feb 2021
Cited by 3 | Viewed by 2435
Abstract
Recently, there has been a sharp increase in the production of smart devices and related networks, and consequently the Internet of Things. One concern for these devices, which is constantly becoming more critical, is their protection against attacks due to their heterogeneity and [...] Read more.
Recently, there has been a sharp increase in the production of smart devices and related networks, and consequently the Internet of Things. One concern for these devices, which is constantly becoming more critical, is their protection against attacks due to their heterogeneity and the absence of international standards to achieve this goal. Thus, these devices are becoming vulnerable, with many of them not even showing any signs of malfunction or suspicious behavior. The aim of the present work is to introduce a circuit that is connected in series with the power supply of a smart device, specifically an IP camera, which allows analysis of its behavior. The detection circuit operates in real time (real-time detection), sampling the supply current of the device, processing the sampled values and finally indicating any detection of abnormal activities, based on a comparison to normal operation conditions. By utilizing techniques borrowed by simple power analysis side channel attack, it was possible to detect deviations from the expected operation of the IP camera, as they occurred due to intentional attacks, quarantining the monitored device from the rest of the network. The circuit is analyzed and a low-cost implementation (under 5US$) is illustrated. It achieved 100% success in the test results, showing excellent performance in intrusion detection. Full article
(This article belongs to the Special Issue Recent Advances in Computation Engineering)
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22 pages, 4438 KiB  
Article
Least-Squares Finite Element Method for a Meso-Scale Model of the Spread of COVID-19
by Fleurianne Bertrand and Emilie Pirch
Computation 2021, 9(2), 18; https://doi.org/10.3390/computation9020018 - 5 Feb 2021
Cited by 9 | Viewed by 2920
Abstract
This paper investigates numerical properties of a flux-based finite element method for the discretization of a SEIQRD (susceptible-exposed-infected-quarantined-recovered-deceased) model for the spread of COVID-19. The model is largely based on the SEIRD (susceptible-exposed-infected-recovered-deceased) models developed in recent works, with additional extension by a [...] Read more.
This paper investigates numerical properties of a flux-based finite element method for the discretization of a SEIQRD (susceptible-exposed-infected-quarantined-recovered-deceased) model for the spread of COVID-19. The model is largely based on the SEIRD (susceptible-exposed-infected-recovered-deceased) models developed in recent works, with additional extension by a quarantined compartment of the living population and the resulting first-order system of coupled PDEs is solved by a Least-Squares meso-scale method. We incorporate several data on political measures for the containment of the spread gathered during the course of the year 2020 and develop an indicator that influences the predictions calculated by the method. The numerical experiments conducted show a promising accuracy of predictions of the space-time behavior of the virus compared to the real disease spreading data. Full article
(This article belongs to the Special Issue Computation to Fight SARS-CoV-2 (CoVid-19))
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20 pages, 1281 KiB  
Article
Weighted Consensus Segmentations
by Halima Saker, Rainer Machné, Jörg Fallmann, Douglas B. Murray, Ahmad M. Shahin and Peter F. Stadler
Computation 2021, 9(2), 17; https://doi.org/10.3390/computation9020017 - 5 Feb 2021
Viewed by 2468
Abstract
The problem of segmenting linearly ordered data is frequently encountered in time-series analysis, computational biology, and natural language processing. Segmentations obtained independently from replicate data sets or from the same data with different methods or parameter settings pose the problem of computing an [...] Read more.
The problem of segmenting linearly ordered data is frequently encountered in time-series analysis, computational biology, and natural language processing. Segmentations obtained independently from replicate data sets or from the same data with different methods or parameter settings pose the problem of computing an aggregate or consensus segmentation. This Segmentation Aggregation problem amounts to finding a segmentation that minimizes the sum of distances to the input segmentations. It is again a segmentation problem and can be solved by dynamic programming. The aim of this contribution is (1) to gain a better mathematical understanding of the Segmentation Aggregation problem and its solutions and (2) to demonstrate that consensus segmentations have useful applications. Extending previously known results we show that for a large class of distance functions only breakpoints present in at least one input segmentation appear in the consensus segmentation. Furthermore, we derive a bound on the size of consensus segments. As show-case applications, we investigate a yeast transcriptome and show that consensus segments provide a robust means of identifying transcriptomic units. This approach is particularly suited for dense transcriptomes with polycistronic transcripts, operons, or a lack of separation between transcripts. As a second application, we demonstrate that consensus segmentations can be used to robustly identify growth regimes from sets of replicate growth curves. Full article
(This article belongs to the Special Issue Bioinformatics Tools for ncRNAs)
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15 pages, 961 KiB  
Article
An Elaborate Preprocessing Phase (p3) in Composition and Optimization of Business Process Models
by George Tsakalidis, Kostas Georgoulakos, Dimitris Paganias and Kostas Vergidis
Computation 2021, 9(2), 16; https://doi.org/10.3390/computation9020016 - 4 Feb 2021
Cited by 3 | Viewed by 2424
Abstract
Business process optimization (BPO) has become an increasingly attractive subject in the wider area of business process intelligence and is considered as the problem of composing feasible business process designs with optimal attribute values, such as execution time and cost. Despite the fact [...] Read more.
Business process optimization (BPO) has become an increasingly attractive subject in the wider area of business process intelligence and is considered as the problem of composing feasible business process designs with optimal attribute values, such as execution time and cost. Despite the fact that many approaches have produced promising results regarding the enhancement of attribute performance, little has been done to reduce the computational complexity due to the size of the problem. The proposed approach introduces an elaborate preprocessing phase as a component to an established optimization framework (bpoF) that applies evolutionary multi-objective optimization algorithms (EMOAs) to generate a series of diverse optimized business process designs based on specific process requirements. The preprocessing phase follows a systematic rule-based algorithmic procedure for reducing the library size of candidate tasks. The experimental results on synthetic data demonstrate a considerable reduction of the library size and a positive influence on the performance of EMOAs, which is expressed with the generation of an increasing number of nondominated solutions. An important feature of the proposed phase is that the preprocessing effects are explicitly measured before the EMOAs application; thus, the effects on the library reduction size are directly correlated with the improved performance of the EMOAs in terms of average time of execution and nondominated solution generation. The work presented in this paper intends to pave the way for addressing the abiding optimization challenges related to the computational complexity of the search space of the optimization problem by working on the problem specification at an earlier stage. Full article
(This article belongs to the Section Computational Engineering)
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17 pages, 2362 KiB  
Article
ESTA: Educating Adolescents in Sustainable Travel Urban Behavior through Mobile Applications Using Motivational Features
by Maria Eftychia Angelaki, Theodoros Karvounidis and Christos Douligeris
Computation 2021, 9(2), 15; https://doi.org/10.3390/computation9020015 - 2 Feb 2021
Viewed by 2952
Abstract
This paper proposes the use of motivational features in mobile applications to support adolescents’ education in sustainable travel urban behavior, so that they become more mindful of their environmental impact. To this effect, existing persuasive strategies are adopted, implemented, and integrated into six [...] Read more.
This paper proposes the use of motivational features in mobile applications to support adolescents’ education in sustainable travel urban behavior, so that they become more mindful of their environmental impact. To this effect, existing persuasive strategies are adopted, implemented, and integrated into six simulated screens of a prospective mobile application named ESTA, designed for this purpose through a user-centered design process. These screens are then assessed by secondary education pupils, the outcome of which is analyzed and presented in detail. The analysis takes into consideration the possibility for the daily use of ESTA in order for the adolescents to foster an eco-friendly and healthy transit attitude and make more sustainable mobility choices that will follow them throughout their life. The potential effectiveness of ESTA is demonstrated via two use cases: the “Daily Commuting” case is addressed towards adolescents who want to move within their area of residence or neighborhood following their daily routine and activities, while the “Weekend Entertainment” is addressed towards adolescents who want to move using the available public transport modes, encouraging them to adopt greener weekend travel habits. Full article
(This article belongs to the Special Issue Recent Advances in Computation Engineering)
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10 pages, 3471 KiB  
Article
Dynamic Stability Enhancement of a Hybrid Renewable Energy System in Stand-Alone Applications
by Ezzeddine Touti, Hossem Zayed, Remus Pusca and Raphael Romary
Computation 2021, 9(2), 14; https://doi.org/10.3390/computation9020014 - 1 Feb 2021
Cited by 5 | Viewed by 2509
Abstract
Renewable energy systems have been extensively developed and they are attractive to become widespread in the future because they can deliver energy at a competitive price and generally do not cause environmental pollution. However, stand-alone energy systems may not be practical for satisfying [...] Read more.
Renewable energy systems have been extensively developed and they are attractive to become widespread in the future because they can deliver energy at a competitive price and generally do not cause environmental pollution. However, stand-alone energy systems may not be practical for satisfying the electric load demands, especially in places having unsteady wind speeds with high unpredictability. Hybrid energy systems seem to be a more economically feasible alternative to satisfy the energy demands of several isolated clients worldwide. The combination of these systems makes it possible to guarantee the power stability, efficiency, and reliability. The aim of this paper is to present a comprehensive analysis and to propose a technical solution to integrate a self-excited induction generator in a low power multisource system. Therefore, to avoid the voltage collapsing and the machine demagnetization, the various parameters have to be identified. This procedure allows for the limitation of a safe operating area where the best stability of the machine can be obtained. Hence, the load variation interval is determined. An improvement of the induction generator stability will be analyzed. Simulation results will be validated through experimental tests. Full article
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24 pages, 2208 KiB  
Article
Kinetic Simulations of Compressible Non-Ideal Fluids: From Supercritical Flows to Phase-Change and Exotic Behavior
by Ehsan Reyhanian, Benedikt Dorschner and Ilya Karlin
Computation 2021, 9(2), 13; https://doi.org/10.3390/computation9020013 - 30 Jan 2021
Cited by 4 | Viewed by 2474
Abstract
We investigate a kinetic model for compressible non-ideal fluids. The model imposes the local thermodynamic pressure through a rescaling of the particle’s velocities, which accounts for both long- and short-range effects and hence full thermodynamic consistency. The model is fully Galilean invariant and [...] Read more.
We investigate a kinetic model for compressible non-ideal fluids. The model imposes the local thermodynamic pressure through a rescaling of the particle’s velocities, which accounts for both long- and short-range effects and hence full thermodynamic consistency. The model is fully Galilean invariant and treats mass, momentum, and energy as local conservation laws. The analysis and derivation of the hydrodynamic limit is followed by the assessment of accuracy and robustness through benchmark simulations ranging from the Joule–Thompson effect to a phase-change and high-speed flows. In particular, we show the direct simulation of the inversion line of a van der Waals gas followed by simulations of phase-change such as the one-dimensional evaporation of a saturated liquid, nucleate, and film boiling and eventually, we investigate the stability of a perturbed strong shock front in two different fluid mediums. In all of the cases, we find excellent agreement with the corresponding theoretical analysis and experimental correlations. We show that our model can operate in the entire phase diagram, including super- as well as sub-critical regimes and inherently captures phase-change phenomena. Full article
(This article belongs to the Special Issue Computational Models for Complex Fluid Interfaces across Scales)
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34 pages, 38945 KiB  
Article
The INUS Platform: A Modular Solution for Object Detection and Tracking from UAVs and Terrestrial Surveillance Assets
by Evangelos Maltezos, Athanasios Douklias, Aris Dadoukis, Fay Misichroni, Lazaros Karagiannidis, Markos Antonopoulos, Katerina Voulgary, Eleftherios Ouzounoglou and Angelos Amditis
Computation 2021, 9(2), 12; https://doi.org/10.3390/computation9020012 - 29 Jan 2021
Cited by 9 | Viewed by 4124
Abstract
Situational awareness is a critical aspect of the decision-making process in emergency response and civil protection and requires the availability of up-to-date information on the current situation. In this context, the related research should not only encompass developing innovative single solutions for (real-time) [...] Read more.
Situational awareness is a critical aspect of the decision-making process in emergency response and civil protection and requires the availability of up-to-date information on the current situation. In this context, the related research should not only encompass developing innovative single solutions for (real-time) data collection, but also on the aspect of transforming data into information so that the latter can be considered as a basis for action and decision making. Unmanned systems (UxV) as data acquisition platforms and autonomous or semi-autonomous measurement instruments have become attractive for many applications in emergency operations. This paper proposes a multipurpose situational awareness platform by exploiting advanced on-board processing capabilities and efficient computer vision, image processing, and machine learning techniques. The main pillars of the proposed platform are: (1) a modular architecture that exploits unmanned aerial vehicle (UAV) and terrestrial assets; (2) deployment of on-board data capturing and processing; (3) provision of geolocalized object detection and tracking events; and (4) a user-friendly operational interface for standalone deployment and seamless integration with external systems. Experimental results are provided using RGB and thermal video datasets and applying novel object detection and tracking algorithms. The results show the utility and the potential of the proposed platform, and future directions for extension and optimization are presented. Full article
(This article belongs to the Special Issue Recent Advances in Computation Engineering)
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31 pages, 2649 KiB  
Article
Revisiting the Homogenized Lattice Boltzmann Method with Applications on Particulate Flows
by Robin Trunk, Timo Weckerle, Nicolas Hafen, Gudrun Thäter, Hermann Nirschl and Mathias J. Krause
Computation 2021, 9(2), 11; https://doi.org/10.3390/computation9020011 - 27 Jan 2021
Cited by 13 | Viewed by 3482
Abstract
The simulation of surface resolved particles is a valuable tool to gain more insights in the behaviour of particulate flows in engineering processes. In this work the homogenized lattice Boltzmann method as one approach for such direct numerical simulations is revisited and validated [...] Read more.
The simulation of surface resolved particles is a valuable tool to gain more insights in the behaviour of particulate flows in engineering processes. In this work the homogenized lattice Boltzmann method as one approach for such direct numerical simulations is revisited and validated for different scenarios. Those include a 3D case of a settling sphere for various Reynolds numbers. On the basis of this dynamic case, different algorithms for the calculation of the momentum exchange between fluid and particle are evaluated along with different forcing schemes. The result is an updated version of the method, which is in good agreement with the benchmark values based on simulations and experiments. The method is then applied for the investigation of the tubular pinch effect discovered by Segré and Silberberg and the simulation of hindered settling. For the latter, the computational domain is equipped with periodic boundaries for both fluid and particles. The results are compared to the model by Richardson and Zaki and are found to be in good agreement. As no explicit contact treatment is applied, this leads to the assumption of sufficient momentum transfer between particles via the surrounding fluid. The implementations are based on the open-source C++ lattice Boltzmann library OpenLB. Full article
(This article belongs to the Section Computational Engineering)
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16 pages, 3014 KiB  
Article
The Performance of a Gradient-Based Method to Estimate the Discretization Error in Computational Fluid Dynamics
by Adhika Satyadharma and Harinaldi
Computation 2021, 9(2), 10; https://doi.org/10.3390/computation9020010 - 24 Jan 2021
Cited by 2 | Viewed by 2881
Abstract
Although the grid convergence index is a widely used for the estimation of discretization error in computational fluid dynamics, it still has some problems. These problems are mainly rooted in the usage of the order of a convergence variable within the model which [...] Read more.
Although the grid convergence index is a widely used for the estimation of discretization error in computational fluid dynamics, it still has some problems. These problems are mainly rooted in the usage of the order of a convergence variable within the model which is a fundamental variable that the model is built upon. To improve the model, a new perspective must be taken. By analyzing the behavior of the gradient within simulation data, a gradient-based model was created. The performance of this model is tested on its accuracy, precision, and how it will affect a computational time of a simulation. The testing is conducted on a dataset of 36 simulated variables, simulated using the method of manufactured solutions, with an average of 26.5 meshes/case. The result shows the new gradient based method is more accurate and more precise then the grid convergence index(GCI). This allows for the usage of a coarser mesh for its analysis, thus it has the potential to reduce the overall computational by at least by 25% and also makes the discretization error analysis more available for general usage. Full article
(This article belongs to the Section Computational Engineering)
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15 pages, 1184 KiB  
Article
High-Performance Computation in Residue Number System Using Floating-Point Arithmetic
by Konstantin Isupov
Computation 2021, 9(2), 9; https://doi.org/10.3390/computation9020009 - 21 Jan 2021
Cited by 7 | Viewed by 4805
Abstract
Residue number system (RNS) is known for its parallel arithmetic and has been used in recent decades in various important applications, from digital signal processing and deep neural networks to cryptography and high-precision computation. However, comparison, sign identification, overflow detection, and division are [...] Read more.
Residue number system (RNS) is known for its parallel arithmetic and has been used in recent decades in various important applications, from digital signal processing and deep neural networks to cryptography and high-precision computation. However, comparison, sign identification, overflow detection, and division are still hard to implement in RNS. For such operations, most of the methods proposed in the literature only support small dynamic ranges (up to several tens of bits), so they are only suitable for low-precision applications. We recently proposed a method that supports arbitrary moduli sets with cryptographically sized dynamic ranges, up to several thousands of bits. The practical interest of our method compared to existing methods is that it relies only on very fast standard floating-point operations, so it is suitable for multiple-precision applications and can be efficiently implemented on many general-purpose platforms that support IEEE 754 arithmetic. In this paper, we make further improvements to this method and demonstrate that it can successfully be applied to implement efficient data-parallel primitives operating in the RNS domain, namely finding the maximum element of an array of RNS numbers on graphics processing units. Our experimental results on an NVIDIA RTX 2080 GPU show that for random residues and a 128-moduli set with 2048-bit dynamic range, the proposed implementation reduces the running time by a factor of 39 and the memory consumption by a factor of 13 compared to an implementation based on mixed-radix conversion. Full article
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14 pages, 11943 KiB  
Article
Dam Breach Simulation with the Material Point Method
by Chendi Cao and Mitchell Neilsen
Computation 2021, 9(2), 8; https://doi.org/10.3390/computation9020008 - 20 Jan 2021
Cited by 8 | Viewed by 3114
Abstract
Dam embankment breaches caused by overtopping or internal erosion can impact both life and property downstream. It is important to accurately predict the amount of erosion, peak discharge, and the resulting downstream flow. This paper presents a new model based on the material [...] Read more.
Dam embankment breaches caused by overtopping or internal erosion can impact both life and property downstream. It is important to accurately predict the amount of erosion, peak discharge, and the resulting downstream flow. This paper presents a new model based on the material point method to simulate soil and water interaction and predict failure rate parameters. The model assumes that the dam consists of a homogeneous embankment constructed with cohesive soil, and water inflow is defined by a hydrograph using other readily available reach routing software. The model uses continuum mixture theory to describe each phase where each species individually obeys the conservation of mass and momentum. A two-grid material point method is used to discretize the governing equations. The Drucker–Prager plastic flow model, combined with a Hencky strain-based hyperelasticity model, is used to compute soil stress. Water is modeled as a weakly compressible fluid. Analysis of the model demonstrates the efficacy of our approach for existing examples of overtopping dam breach, dam failures, and collisions. Simulation results from our model are compared with a physical-based breach model, WinDAM C. The new model can capture water and soil interaction at a finer granularity than WinDAM C. The new model gradually removes the granular material during the breach process. The impact of material properties on the dam breach process is also analyzed. Full article
(This article belongs to the Section Computational Engineering)
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