Computation

9 pages, 367 KiB

Open AccessArticle

An Improved Approximation Algorithm for the Minimum Power Cover Problem with Submodular Penalty

by Han Dai

Computation 2022, 10(10), 189; https://doi.org/10.3390/computation10100189 - 19 Oct 2022

Cited by 1 | Viewed by 1227

In this paper, we consider the minimum power cover problem with submodular penalty (SPMPC). Given a set U of n users, a set S of m sensors and a penalty function

π : 2^{U} \to R_{+}

on the plane, the relationship [...] Read more.

In this paper, we consider the minimum power cover problem with submodular penalty (SPMPC). Given a set U of n users, a set S of m sensors and a penalty function

π : 2^{U} \to R_{+}

on the plane, the relationship that adjusts the power

p (s)

of each sensor s and its corresponding radius

r (s)

is:

p (s) = c \cdot r {(s)}^{α}

, where

c > 0

and

α \geq 1

. The SPMPC problem is to determine the power assignment on each sensor such that each user

u \in U

is either covered by the sensor or penalized and the sum of the total power consumed by sensors in S plus the penalty of all uncovered users is minimized, the penalty here is determined by the submodular function. Based on the primal dual technique, we design an

O (α)

-approximation algorithm. Full article

(This article belongs to the Special Issue Graph Theory and Its Applications in Computing)

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13 pages, 1058 KiB

Open AccessArticle

Optimizing DSO Requests Management Flexibility for Home Appliances Using CBCC-RDG3

by Mark Bezmaslov, Daniil Belyaev, Vladimir Vasilev, Elizaveta Dolgintseva, Lyubov Yamshchikova and Ovanes Petrosian

Computation 2022, 10(10), 188; https://doi.org/10.3390/computation10100188 - 18 Oct 2022

Cited by 2 | Viewed by 1644

Abstract

This article covers a case study with homes equipped with multiple appliances for energy consumption. The central goal is to provide for aggregators’ flexibility in distribution networks by building an optimal schedule that takes advantage of load flexibility resources. This, in turn, allows [...] Read more.

This article covers a case study with homes equipped with multiple appliances for energy consumption. The central goal is to provide for aggregators’ flexibility in distribution networks by building an optimal schedule that takes advantage of load flexibility resources. This, in turn, allows for the re-scheduling of shifting/real-time home appliances to provision a request from a distribution system operator (DSO). The paper concludes with the consideration of the CBCC-RDG3, HyDE-DF, and genetic algorithms, which were used to find the best schedule that would be highly efficient and meet all the constraints associated with the problem that successfully demonstrate the effectiveness of this particular approach. Full article

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15 pages, 2444 KiB

Open AccessArticle

Global Practical Output Tracking for a Class of Uncertain Inherently Time-Varying Delay Nonlinear Systems by Output Feedback

by Keylan Alimhan, Orken Mamyrbayev, Abilmazhin Adamov, Sandugash Alisheva and Dina Oralbekova

Computation 2022, 10(10), 187; https://doi.org/10.3390/computation10100187 - 13 Oct 2022

Viewed by 1117

Abstract

This article addresses the problem of global practical output tracking by output feedback for a class of uncertain inherently time-varying delay nonlinear systems. Firstly, a homogeneous output-feedback controller is designed for the nominal uncertain inherently system by virtue of adding a power integrator [...] Read more.

This article addresses the problem of global practical output tracking by output feedback for a class of uncertain inherently time-varying delay nonlinear systems. Firstly, a homogeneous output-feedback controller is designed for the nominal uncertain inherently system by virtue of adding a power integrator technique. Then, with the help of an appropriate Lyapunov–Krasovskii functional and reduced-order observer, by using the homogeneous domination approach and adding a power integrator method, an output-feedback controller is successfully developed to guarantee all the states of the closed-loop system remain bounded and simultaneously making the tracking error arbitrarily small. The simulation results of an example verify the proposed approach. Full article

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13 pages, 2377 KiB

Open AccessArticle

A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq

by Ziyad T. Allawi

Computation 2022, 10(10), 186; https://doi.org/10.3390/computation10100186 - 13 Oct 2022

Cited by 5 | Viewed by 1880

Abstract

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories [...] Read more.

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comparison to the actual observational results. ANN simulation gives a clear insight into three crescent moon visibility regions: invisible (I), probably visible (P), and certainly visible (V). The proposed ANN is suitable for building lunar calendars, so it was used to build a four-year calendar on the horizon of Baghdad. The built calendar was compared with the official Hijri calendar in Iraq. Full article

(This article belongs to the Topic Artificial Intelligence and Computational Methods: Modeling, Simulations and Optimization of Complex Systems)

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15 pages, 1123 KiB

Open AccessArticle

Paired Patterns in Logical Analysis of Data for Decision Support in Recognition

by Igor S. Masich, Vadim S. Tyncheko, Vladimir A. Nelyub, Vladimir V. Bukhtoyarov, Sergei O. Kurashkin and Aleksey S. Borodulin

Computation 2022, 10(10), 185; https://doi.org/10.3390/computation10100185 - 12 Oct 2022

Cited by 26 | Viewed by 1397

Abstract

Logical analysis of data (LAD), an approach to data analysis based on Boolean functions, combinatorics, and optimization, can be considered one of the methods of interpretable machine learning. A feature of LAD is that, among many patterns, different types of patterns can be [...] Read more.

Logical analysis of data (LAD), an approach to data analysis based on Boolean functions, combinatorics, and optimization, can be considered one of the methods of interpretable machine learning. A feature of LAD is that, among many patterns, different types of patterns can be identified, for example, prime, strong, spanned, and maximum. This paper proposes a decision-support approach to recognition by sharing different types of patterns to improve the quality of recognition in terms of accuracy, interpretability, and validity. An algorithm was developed to search for pairs of strong patterns (prime and spanned) with the same coverage as the training sample, having the smallest (for the prime pattern) and the largest (for the spanned pattern) number of conditions. The proposed approach leads to a decrease in the number of unrecognized observations (compared with the use of spanned patterns only) by 1.5–2 times (experimental results), to some reduction in recognition errors (compared with the use of prime patterns only) of approximately 1% (depending on the dataset) and makes it possible to assess in more detail the level of confidence of the recognition result due to a refined decision-making scheme that uses the information about the number and type of patterns covering the observation. Full article

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11 pages, 1415 KiB

Open AccessArticle

Numerical Analysis of Deformation Characteristics of Elastic Inhomogeneous Rotational Shells at Arbitrary Displacements and Rotation Angles

by Vladimir G. Dmitriev, Alexander N. Danilin, Anastasiya R. Popova and Natalia V. Pshenichnova

Computation 2022, 10(10), 184; https://doi.org/10.3390/computation10100184 - 11 Oct 2022

Cited by 1 | Viewed by 1258

Abstract

Adequate mathematical models and computational algorithms are developed in this study to investigate specific features of the deformation processes of elastic rotational shells at large displacements and arbitrary rotation angles of the normal line. A finite difference method (FDM) is used to discretize [...] Read more.

Adequate mathematical models and computational algorithms are developed in this study to investigate specific features of the deformation processes of elastic rotational shells at large displacements and arbitrary rotation angles of the normal line. A finite difference method (FDM) is used to discretize the original continuum problem in spatial variables, replacing the differential operators with a second-order finite difference approximation. The computational algorithm for solving the nonlinear boundary value problem is based on a quasi-dynamic form of the ascertainment method with the construction of an explicit two-layer time-difference scheme of second-order accuracy. The influence of physical and mechanical characteristics of isotropic and composite materials on the deformation features of elastic spherical shells under the action of surface loading of “tracking” type is investigated. The results of the studies conducted have shown that the physical and mechanical characteristics of isotropic and composite materials significantly affect the nature of the deformation of the clamped spherical shell in both the subcritical and post-critical domains. The developed mathematical models and computational algorithms can be applied in the future to study shells of rotation made of hyperelastic (non-linearly elastic) materials and soft shells. Full article

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11 pages, 2342 KiB

Open AccessArticle

A Proactive Explainable Artificial Neural Network Model for the Early Diagnosis of Thyroid Cancer

by Sumayh S. Aljameel

Computation 2022, 10(10), 183; https://doi.org/10.3390/computation10100183 - 11 Oct 2022

Cited by 2 | Viewed by 1387

Abstract

Early diagnosis of thyroid cancer can reduce mortality, and can decrease the risk of recurrence, side effects, or the need for lengthy surgery. In this study, an explainable artificial neural network (EANN) model was developed to distinguish between malignant and benign nodules and [...] Read more.

Early diagnosis of thyroid cancer can reduce mortality, and can decrease the risk of recurrence, side effects, or the need for lengthy surgery. In this study, an explainable artificial neural network (EANN) model was developed to distinguish between malignant and benign nodules and to understand the factors that are predictive of malignancy. The study was conducted using the records of 724 patients who were admitted to Shengjing Hospital of China Medical University. The dataset contained the patients’ demographic information, nodule characteristics, blood test findings, and thyroid characteristics. The performance of the model was evaluated using the metrics of accuracy, sensitivity, specificity, F1 score, and area under the curve (AUC). The SMOTEENN combined sampling method was used to correct for a significant imbalance between malignant and benign nodules in the dataset. The proposed model outperformed a baseline study, with an accuracy of 0.99 and an AUC of 0.99. The proposed EANN model can assist health care professionals by enabling them to make effective early cancer diagnoses. Full article

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20 pages, 334 KiB

Open AccessArticle

The Impact of Financial Development and Macroeconomic Fundamentals on Nonperforming Loans among Emerging Countries: An Assessment Using the NARDL Approach

by Aamir Aijaz Syed, Muhammad Abdul Kamal, Simon Grima and Assad Ullah

Computation 2022, 10(10), 182; https://doi.org/10.3390/computation10100182 - 11 Oct 2022

Cited by 5 | Viewed by 1687

Abstract

The relationship between financial development indicators and non-performing loans (NPLs) has garnered significant attention, especially in emerging countries. The puzzle of whether financial sector development increases or decreases Non-performing Loans (NPL)s has not been resolved to the satisfaction of the curious mind. This [...] Read more.

The relationship between financial development indicators and non-performing loans (NPLs) has garnered significant attention, especially in emerging countries. The puzzle of whether financial sector development increases or decreases Non-performing Loans (NPL)s has not been resolved to the satisfaction of the curious mind. This research attempts to answer the above question by studying the asymmetric and symmetric association between financial sector development and NPLs, by utilizing the novel non-linear autoregressive distribution lag (NARDL) and the linear autoregressive distribution lag (ARDL) approach. Moreover, to make the study inclusive, we have added a series of proxies to measure financial sector development and macroeconomic vulnerabilities. Our main findings confirm that financial sector development and NPLs move together in the long run, and there is significant evidence of the asymmetric relationship. We infer that NPLs react differently to the negative and positive shocks of financial development and macroeconomic variables both in the short and long run. In the long-run positive shocks in financial intermediation, banking efficiency, banking depth, banking stability index, and banking non-interest income significantly impact the NPLs in emerging countries. The positive shocks of financial sector development (financial intermediation and size of banks) increase NPLs in emerging countries and vice-versa. Furthermore, regarding the macroeconomic variables, the positive shock of inflation, unemployment, and interest rate positively affect NPLs. The empirical analysis also concludes that in the long-run foreign bank presence is an insignificant factor affecting NPLs in the selected countries. This study emphasizes that, unlike the linear model, the non-linear model provides a more realistic and robust result by highlighting hidden asymmetries, which will help policymakers make appropriate strategic decisions. Full article

(This article belongs to the Special Issue Credit Risk Modelling: Current Practices and Applications)

7 pages, 328 KiB

Open AccessArticle

On the Inverse Symmetric Division Deg Index of Unicyclic Graphs

by Abeer M. Albalahi and Akbar Ali

Computation 2022, 10(10), 181; https://doi.org/10.3390/computation10100181 - 11 Oct 2022

Cited by 1 | Viewed by 1366

Abstract

The symmetric division deg (SDD) index is among the 148 discrete Adriatic indices that were developed about a decade ago. Motivated by the success of the SDD index, Ghorbani et al. in a recent paper proposed the inverse version of this index and [...] Read more.

The symmetric division deg (SDD) index is among the 148 discrete Adriatic indices that were developed about a decade ago. Motivated by the success of the SDD index, Ghorbani et al. in a recent paper proposed the inverse version of this index and called it the inverse symmetric division deg (ISDD) index. In the aforementioned paper, the graphs possessing the maximum and minimum ISDD index over the set of all tree graphs having the given order were found. The present paper addresses the problem of finding the graphs having the largest and smallest ISDD index from the set of all connected unicyclic graphs having the specified order. Full article

(This article belongs to the Special Issue Graph Theory and Its Applications in Computing)

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24 pages, 4805 KiB

Open AccessArticle

Power Loss Minimization and Voltage Profile Improvement by System Reconfiguration, DG Sizing, and Placement

by Mlungisi Ntombela, Kabeya Musasa and Moketjema Clarence Leoaneka

Computation 2022, 10(10), 180; https://doi.org/10.3390/computation10100180 - 10 Oct 2022

Cited by 17 | Viewed by 3305

Abstract

A number of algorithms that aim to reduce power system losses and improve voltage profiles by optimizing distributed generator (DG) location and size have already been proposed, but they are still subject to several limitations. Hence, new algorithms can be developed or existing [...] Read more.

A number of algorithms that aim to reduce power system losses and improve voltage profiles by optimizing distributed generator (DG) location and size have already been proposed, but they are still subject to several limitations. Hence, new algorithms can be developed or existing ones can be improved so that this important issue can be addressed more appropriately and effectively. This study proposes a reconfiguration methodology based on a hybrid optimization algorithm, consisting of a combination of the genetic algorithm (GA) and the improved particle swam optimization (IPSO) algorithm for minimizing active power loss and maintaining the voltage magnitude at about 1 p.u. The buses at which DGs should be injected were identified based on optimal real power loss and reactive power limit. When applying the proposed optimization algorithm for DGs allocation in power system, the search space or number of iterations was reduced, increasing its convergence rate. The proposed reconfiguration methodology was test in an IEEE-30 bus electrical network system with DGs allocations and the simulations were conducted using MATLAB software compared to other optimization algorithms, such as GA, PSO, and IPSO, the combination of GA and IPSO or Hybrid GA & IPSO (HGAIPSO) method has a smaller number of iterations and is more effective in optimization problems. The effectiveness of the proposed HGAIPSO has been tested on IEEE-30 bus network system with DGs allocations, and the obtained test results have been compared to those from other methods (i.e., GA, PSO, and IPSO). The simulation results show that the proposed HGAIPSO can be an efficient and promising optimization algorithm for distribution network reconfiguration problems. The IEEE-30 bus test system with DGs integrated at various location revealed reductions in overall real power loss of 40.7040%, 36.2403%, and 42.9406% for type 1, type 2, and type 3 DGs allocation, respectively. The highest bus voltage profile goes to 1.01 pu in the IEEE-30 bus. Full article

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21 pages, 9316 KiB

Open AccessArticle

Teleoperated Locomotion for Biobot between Japan and Bangladesh

by Mochammad Ariyanto, Chowdhury Mohammad Masum Refat, Xiaofeng Zheng, Kazuyoshi Hirao, Yingzhe Wang and Keisuke Morishima

Computation 2022, 10(10), 179; https://doi.org/10.3390/computation10100179 - 10 Oct 2022

Cited by 7 | Viewed by 2050

Abstract

Biobot-based insects have been investigated so far for various applications such as search and rescue operations, environmental monitoring, and discovering the environment. These applications need a strong international collaboration to complete the tasks. However, during the COVID-19 pandemic, most people could not easily [...] Read more.

Biobot-based insects have been investigated so far for various applications such as search and rescue operations, environmental monitoring, and discovering the environment. These applications need a strong international collaboration to complete the tasks. However, during the COVID-19 pandemic, most people could not easily move from one country to another because of the travel ban. In addition, controlling biobots is challenging because only experts can operate the cockroach behavior with and without stimulated response. In order to solve this issue, we proposed a user-friendly teleoperation user interface (UI) to monitor and control the biobot between Japan and Bangladesh without onsite operation by experts. This study applied Madagascar hissing cockroaches (MHC) as a biobot hybrid robot. A multithreading algorithm was implemented to run multiple parallel computations concurrently on the UI. Virtual network computing (VNC) was implemented on the teleoperation UI as remote communication for streaming real-time video from Japan to Bangladesh and sending remote commands from Bangladesh to Japan. In the experiments, a remote operator successfully steered the biobot to follow a predetermined path through a developed teleoperation UI with a time delay of 275 ms. The proposed interactive and intuitive UI enables a promising and reliable system for teleoperated biobots between two remote countries. Full article

(This article belongs to the Section Computational Engineering)

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15 pages, 4956 KiB

Open AccessArticle

Develop Control Architectures to Enhance Soft Actuator Motion and Force

by Mustafa Hassan, Mohammed Ibrahim Awad and Shady A. Maged

Computation 2022, 10(10), 178; https://doi.org/10.3390/computation10100178 - 09 Oct 2022

Cited by 2 | Viewed by 1872

Abstract

Study: Soft robots can achieve the desired range of motion for finger movement to match their axis of rotation with the axis of rotation of the human hand. The iterative design has been used to achieve data that makes the movement smooth and [...] Read more.

Study: Soft robots can achieve the desired range of motion for finger movement to match their axis of rotation with the axis of rotation of the human hand. The iterative design has been used to achieve data that makes the movement smooth and the range of movement wider, and the validity of the design has been confirmed through practical experiments. Limitation: The challenges facing this research are to reach the most significant inclined angle and increase the force generated by the actuator, which is the most complicated matter while maintaining the desired control accuracy. The motion capture system verifies the actual movement of the soft pneumatic actuator (SPA). A tracking system has been developed for SPA in action by having sensors to know the position and strength of the SPA. Results: The novelty of this research is that it gave better control of soft robots by selecting the proportional, integral, and derivative (PID) controller. The parameters were tuned using three different methods: ZN (Ziegler Nichols Method), GA (Genetic Algorism), and PSO (Particle Swarm Optimization). The optimization techniques were used in Methods 2 and 3 in order to reach the nominal error rate (0.6) and minimum overshoot (0.1%) in the shortest time (2.5 s). Impact: The effect of the proposed system in this study is to provide precise control of the actuator, which helps in medical and industrial applications, the most important of which are the transfer of things from one place to another and the process of medical rehabilitation for patients with muscular dystrophy. A doctor who treats finger muscle insufficiency can monitor a patient’s ability to reach a greater angle of flexion or increase strength by developing three treatment modalities to boost strength: Full Assisted Movement (FAM), Half Assisted Movement (HAM), and Resistance Movement (RM). Full article

(This article belongs to the Special Issue Advanced Information, Computation, and Control Systems for Distributed Environments)

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26 pages, 8902 KiB

Open AccessArticle

A Forecasting Prognosis of the Monkeypox Outbreak Based on a Comprehensive Statistical and Regression Analysis

by Farhana Yasmin, Md. Mehedi Hassan, Sadika Zaman, Si Thu Aung, Asif Karim and Sami Azam

Computation 2022, 10(10), 177; https://doi.org/10.3390/computation10100177 - 09 Oct 2022

Cited by 12 | Viewed by 2491

Abstract

The uncommon illness known as monkeypox is brought on by the monkeypox virus. The Orthopoxvirus genus belongs to the family Poxviridae, which also contains the monkeypox virus. The variola virus, which causes smallpox; the vaccinia virus, which is used in the smallpox vaccine; [...] Read more.

The uncommon illness known as monkeypox is brought on by the monkeypox virus. The Orthopoxvirus genus belongs to the family Poxviridae, which also contains the monkeypox virus. The variola virus, which causes smallpox; the vaccinia virus, which is used in the smallpox vaccine; and the cowpox virus are all members of the Orthopoxvirus genus. There is no relationship between chickenpox and monkeypox. After two outbreaks of a disorder resembling pox, monkeypox was first discovered in colonies of monkeys kept for research in 1958. The illness, also known as “monkeypox”, still has no known cause. However, non-human primates and African rodents can spread the disease to humans (such as monkeys). In 1970, a human was exposed to monkeypox for the first time. Several additional nations in central and western Africa currently have documented cases of monkeypox. Before the 2022 outbreak, almost all instances of monkeypox in people outside of Africa were connected to either imported animals or foreign travel to nations where the illness frequently occurs. In this work, the most recent monkeypox dataset was evaluated and the significant instances were visualized. Additionally, nine different forecasting models were also used, and the prophet model emerged as the most reliable one when compared with all nine models with an MSE value of 41,922.55, an R² score of 0.49, a MAPE value of 16.82, an MAE value of 146.29, and an RMSE value of 204.75, which could be considerable assistance to clinicians treating monkeypox patients and government agencies monitoring the origination and current state of the disease. Full article

(This article belongs to the Special Issue Interpretable Statistical Machine for Decision Making: Modeling, Learning and Application Perspectives)

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0 pages, 5146 KiB

Open AccessArticle

A Regularized Real-Time Integrator for Data-Driven Control of Heating Channels

by Chady Ghnatios, Victor Champaney, Angelo Pasquale and Francisco Chinesta

Computation 2022, 10(10), 176; https://doi.org/10.3390/computation10100176 - 05 Oct 2022

Cited by 4 | Viewed by 1468 | Correction

Abstract

In many contexts of scientific computing and engineering science, phenomena are monitored over time and data are collected as time-series. Plenty of algorithms have been proposed in the field of time-series data mining, many of them based on deep learning techniques. High-fidelity simulations [...] Read more.

In many contexts of scientific computing and engineering science, phenomena are monitored over time and data are collected as time-series. Plenty of algorithms have been proposed in the field of time-series data mining, many of them based on deep learning techniques. High-fidelity simulations of complex scenarios are truly computationally expensive and a real-time monitoring and control could be efficiently achieved by the use of artificial intelligence. In this work we build accurate data-driven models of a two-phase transient flow in a heated channel, as usually encountered in heat exchangers. The proposed methods combine several artificial neural networks architectures, involving standard and transposed deep convolutions. In particular, a very accurate real-time integrator of the system has been developed. Full article

(This article belongs to the Section Computational Engineering)

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17 pages, 2659 KiB

Open AccessArticle

Predicting Successful Throwing Technique in Judo from Factors of Kumite Posture Based on a Machine-Learning Approach

by Satoshi Kato and Shinichi Yamagiwa

Computation 2022, 10(10), 175; https://doi.org/10.3390/computation10100175 - 29 Sep 2022

Cited by 4 | Viewed by 2503

Abstract

Identifying the key points of a movement performed by an expert is required for beginners who want to acquire a motor skill. By repeating a learning cycle, the beginner tries the movement, focusing on the key points. We can find many guiding methods [...] Read more.

Identifying the key points of a movement performed by an expert is required for beginners who want to acquire a motor skill. By repeating a learning cycle, the beginner tries the movement, focusing on the key points. We can find many guiding methods for adopting motor skills in the fields of coaching and training for sports. However, the methods strongly depend on the experience of trainers and coaches, who need to select the appropriate methods for different types of athletes. Although methods based on objective information obtained from videos and sensors applicable to individual movements have been proposed in order to overcome the subjectivity of these approaches, we cannot apply those to movements that include external factors, such as pushing and/or attacks from an opponent, as seen in combat sports. Furthermore, such sports require fast feedback of the analysis to the athletes in order to find the key factors of offensive/defensive techniques at the training site. Focusing on judo throwing techniques, this paper proposes a novel real-time prediction method called RT-XSM (Real-Time Extraction method for Successful Movements) that predicts which throwing technique is most likely to be successful based on Kumite posture just before the throw. The RT-XSM uses logistic regression to analyze datasets consisting of the factors of Kumite posture (a standing posture when both players grip each other) and throwing technique classification. To validate the proposed method, this paper also demonstrates experiments of the RT-XSM using datasets acquired from video scenes of the World Judo Championships. Full article

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16 pages, 1572 KiB

Open AccessArticle

Insurance Premium Determination Model and Innovation for Economic Recovery Due to Natural Disasters in Indonesia

by Kalfin, Sukono, Sudradjat Supian and Mustafa Mamat

Computation 2022, 10(10), 174; https://doi.org/10.3390/computation10100174 - 28 Sep 2022

Cited by 2 | Viewed by 1781

Abstract

Climate change that occurs causes the risk of natural disasters to continue to increase throughout the world. Economic losses are unavoidable, leading to the need for continuous innovation in post-disaster economic recovery efforts. Insurance is one of the offers in providing funding for [...] Read more.

Climate change that occurs causes the risk of natural disasters to continue to increase throughout the world. Economic losses are unavoidable, leading to the need for continuous innovation in post-disaster economic recovery efforts. Insurance is one of the offers in providing funding for the economic recovery that occurs. This study aimed to develop innovations and models for determining natural disaster insurance premiums with a subsidy and tax system. In addition, the developed model considers the disaster risk index in the form of the level of risk distribution, the frequency of events, and economic losses. In this study, the data used were the frequency of events and economic losses obtained from the Indonesian National Disaster Management Agency. The data used were 20 database periods from 2000 to 2019. This study used the collective risk method from the index of natural disaster risk parameters. From the results of the analysis, it was found that the level of distribution of disaster risk affected the determination of insurance premiums. The amount of insurance premiums is increasing along with the increase in the magnitude of the spread of disaster risk. In addition, if taxes and subsidies are reduced, then for high-risk areas, there will be a decrease in the burden of insurance premiums, and for low-risk areas, there will be an increase in the premium burden that must be paid. On the basis of the results of the analysis on the insurance model, it was found that the insurance premiums in each province varied. The results of this study are expected to be a reference for the government and private companies in implementing disaster insurance in Indonesia. In addition, the results of this study can be a means of developing innovations for disaster risk management that occurs. Full article

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12 pages, 3476 KiB

Open AccessArticle

Numerical Study of the Influence of the Geometrical Irregularities on Bodies of Revolution at High Angles of Attack

by José Jiménez-Varona and Gabriel Liaño

Computation 2022, 10(10), 173; https://doi.org/10.3390/computation10100173 - 28 Sep 2022

Viewed by 1363

Abstract

The flow at high angles of attack over axisymmetric configurations is not symmetric. The mechanism that triggers the asymmetry may be a combination of a global or hydrodynamic instability (temporal instability) combined with a convective instability (spatial instability) due to microscopic irregularities of [...] Read more.

The flow at high angles of attack over axisymmetric configurations is not symmetric. The mechanism that triggers the asymmetry may be a combination of a global or hydrodynamic instability (temporal instability) combined with a convective instability (spatial instability) due to microscopic irregularities of the configuration. Poor repeatability of experiments and large differences in the global forces have been obtained with very small changes of the nose tip. In order to study theoretically this phenomenon, numerical simulations have been conducted for an ogive-cylinder configuration at subsonic flow and high angle of attack. For the numerical prediction of the flow about a missile type configuration, an assessment of the effect of structured and unstructured meshes is very important. How the body surface is modelled is very relevant; especially the tip zone of the body. Either configuration resembles a smooth or a rough model. The effect of the turbulence models is also decisive. The analysis has led to the conclusion that only Reynolds stress turbulence models (RSM) combined with Scale Adaptive Simulation (SAS), are the appropriate theoretical tools for the characterization of this flow. The geometrical similarity is very important. There is a roll or orientation angle effect for the unstructured grid, while the structured grid presents a bi-stable solution, one mirror of each other. Full article

(This article belongs to the Special Issue Selected Papers from the 10th International Conference from Scientific Computing to Computational Engineering (IC-SCCE 2022))

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9 pages, 2371 KiB

Open AccessArticle

Solvent Effects in the Regioselective N-Functionalization of Tautomerizable Heterocycles Catalyzed by Methyl Trifluoromethanesulfonate: A Density Functional Theory Study with Implicit Solvent Model

by Nelson H. Morgon, Srijit Biswas, Surajit Duari and Aguinaldo R. de Souza

Computation 2022, 10(10), 172; https://doi.org/10.3390/computation10100172 - 26 Sep 2022

Cited by 1 | Viewed by 1296

Abstract

Methyl trifluoromethanesulfonate was found to catalyze the reaction of the nucleophilic substitution of the hydroxyl group of alcohols by N-heterocycles followed by X- to N- alkyl group migration (X = O, S) to obtain N-functionalized benzoxazolone, benzothiazolethione, indoline, [...] Read more.

Methyl trifluoromethanesulfonate was found to catalyze the reaction of the nucleophilic substitution of the hydroxyl group of alcohols by N-heterocycles followed by X- to N- alkyl group migration (X = O, S) to obtain N-functionalized benzoxazolone, benzothiazolethione, indoline, benzoimidazolethione and pyridinone derivatives. A high degree of solvent dependency on the yield of the products was observed during optimization of the reaction parameters. The yield of the product was found to be 0%, 48% and 70% in acetonitrile, 1,2-dichloroethane and chloroform, respectively. The mechanism of the reaction was established through experiments as well as DFT calculations. The functional B3LYP and 6-311++G(d) basis function sets were used to optimize the molecular geometries. D3 Grimme empiric dispersion with Becke–Johnson dumping was employed, and harmonic vibrational frequencies were calculated to characterize the stationary points on the potential energy surface. To ensure that all the stationary points were smoothly connected to each other, intrinsic reaction coordinate (IRC) analyses were performed. The influence of solvents was considered using the solvation model based on density (SMD). The free energy profiles of the mechanisms were obtained with vibrational unscaled zero-point vibrational energy (ZPE), thermal, enthalpy, entropic and solvent corrections. Full article

(This article belongs to the Special Issue Calculations in Solution)

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13 pages, 2113 KiB

Open AccessTechnical Note

Scrutinizing Dynamic Cumulant Lattice Boltzmann Large Eddy Simulations for Turbulent Channel Flows

by Martin Gehrke and Thomas Rung

Computation 2022, 10(10), 171; https://doi.org/10.3390/computation10100171 - 25 Sep 2022

Cited by 1 | Viewed by 1529

Abstract

This technical paper outlines the predictive performance of a recently published dynamic cumulant lattice Boltzmann method (C-LBM) to model turbulent shear flows at all resolutions. Emphasis is given to a simple strategy that avoids a frequently observed velocity overshoot phenomenon near rigid walls [...] Read more.

This technical paper outlines the predictive performance of a recently published dynamic cumulant lattice Boltzmann method (C-LBM) to model turbulent shear flows at all resolutions. Emphasis is given to a simple strategy that avoids a frequently observed velocity overshoot phenomenon near rigid walls when combining the C-LBM with an all-resolution (universal) wall function. The examples included are confined to turbulent channel flow results for a variety of friction Reynolds numbers within 180 and 50,000, obtained on a sequence of isotropic, homogeneous grids that feature non-dimensional lattice spacings using inner coordinates from 4 to 2200. The results indicate that adjusting the near-wall distance of the first fluid node, i.e., the intersection of the wall with the first lattice edge, to the resolution provides a reasonably simple, robust, and accurate supplement to the all-resolution C-LBM approach. The investigated wall function/C-LBM combination displays a remarkable predictive performance for all investigated resolutions. Full article

(This article belongs to the Special Issue CFD 2022--Recent Advances in Lattice Boltzmann Methods)

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14 pages, 5935 KiB

Open AccessArticle

Naphthenic Acids Aggregation: The Role of Salinity

by Renato D. Cunha, Livia J. Ferreira, Ednilsom Orestes, Mauricio D. Coutinho-Neto, James M. de Almeida, Rogério M. Carvalho, Cleiton D. Maciel, Carles Curutchet and Paula Homem-de-Mello

Computation 2022, 10(10), 170; https://doi.org/10.3390/computation10100170 - 22 Sep 2022

Cited by 3 | Viewed by 1959

Abstract

Naphthenic Acids (NA) are important oil extraction subproducts. These chemical species are one of the leading causes of marine pollution and duct corrosion. For this reason, understanding the behavior of NAs in different saline conditions is one of the challenges in the oil [...] Read more.

Naphthenic Acids (NA) are important oil extraction subproducts. These chemical species are one of the leading causes of marine pollution and duct corrosion. For this reason, understanding the behavior of NAs in different saline conditions is one of the challenges in the oil industry. In this work, we simulated several naphthenic acid species and their mixtures, employing density functional theory calculations with the MST-IEFPCM continuum solvation model, to obtain the octanol–water partition coefficients, together with microsecond classical molecular dynamics. The latter consisted of pure water, low-salinity, and high-salinity environment simulations, to assess the stability of NAs aggregates and their sizes. The quantum calculations have shown that the longer chain acids are more hydrophobic, and the classical simulations corroborated: that the longer the chain, the higher the order of the aggregate. In addition, we observed that larger aggregates are stable at higher salinities for all the studied NAs. This can be one factor in the observed low-salinity-enhanced oil recovery, which is a complex phenomenon. The simulations also show that stabilizing the aggregates induced by the salinity involves a direct interplay of Na⁺ cations with the carboxylic groups of the NAs inside the aggregates. In some cases, the ion/NA organization forms a membrane-like circular structural arrangement, especially for longer chain NAs. Full article

(This article belongs to the Special Issue Calculations in Solution)

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10 pages, 1304 KiB

Open AccessArticle

Theoretical Investigation on the Selective Hydroxyl Radical–Induced Decolorization of Methylene-Blue-Dyed Polymer Films

by Pasika Temeeprasertkij, Michio Iwaoka and Satoru Iwamori

Computation 2022, 10(10), 169; https://doi.org/10.3390/computation10100169 - 21 Sep 2022

Viewed by 1184

Abstract

On the basis of the decolorization caused by the reaction of active oxygen species (AOSs) with methylene blue (MB), our group recently developed colorimetric indicators for hydroxyl radical (OH radical) by embedding MB in polymer thin films made of water-soluble pullulan or sodium [...] Read more.

On the basis of the decolorization caused by the reaction of active oxygen species (AOSs) with methylene blue (MB), our group recently developed colorimetric indicators for hydroxyl radical (OH radical) by embedding MB in polymer thin films made of water-soluble pullulan or sodium alginate. In the present work, to elucidate the reason for the selective decolorization induced by the OH radical compared with other AOSs, such as ozone (O₃) and hydrogen peroxide (H₂O₂), density-functional-theory calculations were performed at the B3LYP/6-31G(d) level for these AOSs and MB and its complexes with pullulan or sodium alginate model molecules. A frontier orbital analysis revealed that the π orbital of MB tends to delocalize on the whole molecule upon complexing with pullulan and sodium alginate, while the energy level is lower than the lowest unoccupied molecular orbital levels of O₃ and H₂O₂ but higher than the singly occupied molecular orbital level of the OH radical. The results support the observation that only the OH radical, as the strongest oxidant, can react with MB in the polymer matrices. The selective decolorization of MB-dyed polymer films by the OH radical is due to not only the steric hindrance in the polymer matrix but also the perturbation of the π orbital of MB through the interaction with the polymer molecules. Full article

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19 pages, 362 KiB

Open AccessArticle

Numerical Treatment of Hybrid Fuzzy Differential Equations Subject to Trapezoidal and Triangular Fuzzy Initial Conditions Using Picard’s and the General Linear Method

by Saed Mallak, Basem Attili and Marah Subuh

Computation 2022, 10(10), 168; https://doi.org/10.3390/computation10100168 - 20 Sep 2022

Cited by 2 | Viewed by 1116

Abstract

We study hybrid fuzzy differential equations (HFDEs) under the Hukuhara derivative numerically using Picard’s and the general linear method (GLM). We use trapezoidal and triangular fuzzy numbers as the initial conditions. To demonstrate the efficiency of the proposed methods, the exact as well [...] Read more.

We study hybrid fuzzy differential equations (HFDEs) under the Hukuhara derivative numerically using Picard’s and the general linear method (GLM). We use trapezoidal and triangular fuzzy numbers as the initial conditions. To demonstrate the efficiency of the proposed methods, the exact as well as the numerical solutions are presented numerically and graphically. In addition, a comparison is made between the results from applying the GLM and those obtained when applying the fifth order Runge–Kutta method as reported in the literature. Full article

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Computation, Volume 10, Issue 10 (October 2022) – 22 articles

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