Open Journal of Modelling and Simulation

Journal Information
ISSN / EISSN : 2327-4018 / 2327-4026
Current Publisher: Scientific Research Publishing, Inc. (10.4236)
Former Publisher:
Total articles ≅ 109
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Latest articles in this journal

Hongwei Zhang, Ahmed Mohamed, Timofei Breikin, Martin Howarth
Open Journal of Modelling and Simulation, Volume 09, pp 26-42; doi:10.4236/ojmsi.2021.91002

Ohmic Heating (OH) is one of the emerging thermal technologies used in food processing which can produce rapid and uniform heating with close to 100% energy transfer efficiency. Although mathematical modelling for OH processes has been studied by many researchers in recent years, systematic simulations of OH have not been developed for model-based control of the processes. In this paper, mathematical model for a Colinear Ohmic Heater is presented, analyzed, and studied based on the selected configuration. A numerical solution for the mathematical equations has been defined and proposed. MATLAB/Simulink model is hence developed and validated against the available data. Simulation results have shown that MATLAB/Simulink model can produce robust outputs at low computational costs with an accuracy of up to 99.6% in comparison to the analytical solution. This model can be used in further studies for analysis of the OH processes and development of advanced controllers.
Jie Wang, Guangzu Zhu, Shiqi Wu, Chunshan Luo
Open Journal of Modelling and Simulation, Volume 09, pp 135-145; doi:10.4236/ojmsi.2021.92009

For decades, safety has been a concern for the construction industry. Helmet detection caught the attention of machine learning, but the problem of identity recognition has been ignored in previous studies, which brings trouble to the subsequent safety education of workers. Although, many scholars have devoted themselves to the study of person re-identification which neglected safety detection. The study of this paper mainly proposes a method based on deep learning, which is different from the previous study of helmet detection and human identity recognition and can carry out helmet detection and identity recognition for construction workers. This paper proposes a computer vision-based worker identity recognition and helmet recognition method. We collected 3000 real-name channel images and constructed a neural network based on the You Only Look Once (YOLO) v3 model to extract the features of the construction worker’s face and helmet, respectively. Experiments show that the method has a high recognition accuracy rate, fast recognition speed, accurate recognition of workers and helmet detection, and solves the problem of poor supervision of real-name channels.
Camila De Andrade Kalil, Maria Clícia Stelling de Castro, Dilson Silva, Célia Martins Cortez
Open Journal of Modelling and Simulation, Volume 09, pp 159-171; doi:10.4236/ojmsi.2021.92011

The aim of the present study is to contribute to the knowledge about the functioning of the neuronal circuits. We built a mathematical-computational model using graph theory for a complex neurophysiological circuit consisting of a reverberating neuronal circuit and a parallel neuronal circuit, which could be coupled. Implementing our model in C++ and applying neurophysiological values found in the literature, we studied the discharge pattern of the reverberant circuit and the parallel circuit separately for the same input signal pattern, examining the influence of the refractory period and the synaptic delay on the respective output signal patterns. Then, the same study was performed for the complete circuit, in which the two circuits were coupled, and the parallel circuit could then influence the functioning of the reverberant. The results showed that the refractory period played an important role in forming the pattern of the output spectrum of a reverberating circuit. The inhibitory action of the parallel circuit was able to regulate the reverberation frequency, suggesting that parallel circuits may be involved in the control of reverberation circuits related to motive activities underlying precision tasks and perhaps underlying neural work processes and immediate memories.
M. Z. I. Bangalee, Mizanur Rahman, M. Ferdows, M. S. Islam
Open Journal of Modelling and Simulation, Volume 09, pp 43-58; doi:10.4236/ojmsi.2021.91003

Flow distribution and the effects of different boundary conditions are achieved for a steady-state conjugate (Conduction & Convection) heat transfer process. A plate fin heat sink with horizontal fin orientation along with a computer chassis is numerically investigated and simulated using software ANSYS CFX. Fin orientation of a heat sink changes the direction of fluid flow inside the chassis. For predicting turbulence of the flow inside the domain, a two-equation based k-ε turbulence model is chosen. The Reynolds number based on inflow velocity and geometry is found 4.2 × 103 that indicates that the flow is turbulent inside the chassis. To get proper thermal cooling, the optimum velocity ratio of inlet/outlet, dimension of inlet/outlet and different positions of outlet on the back sidewall of the chassis are predicted. Aspect velocity ratio between the inlet airflow and the outlet airflow has an effect on the steadiness of the flow. Mass flow rate depends on the dimension of the inlet/outlet. The horizontal fin orientation with 1:1.6 inlet-outlet airflow velocity ratio gives better thermal performance when outlet is located at the top corner of the chassis, near to the inner sidewall. Flow distribution and heat transfer characteristics are also analyzed to obtain the final model.
Angelo Raherinirina, Tsilefa Stefana Fandresena, Aimé Richard Hajalalaina, Haja Rabetafika, Rivo Andry Rakotoarivelo, Fontaine Rafamatanantsoa
Open Journal of Modelling and Simulation, Volume 09, pp 211-230; doi:10.4236/ojmsi.2021.93014

We propose a probabilistic approach to modelling the propagation of the coronavirus disease 2019 (COVID-19) in Madagascar, with all its specificities. With the strategy of the Malagasy state, which consists of isolating all suspected cases and hospitalized confirmed case, we get an epidemic model with seven compartments: susceptible (S), Exposed (E), Infected (I), Asymptomatic (A), Hospitalized (H), Cured (C) and Death (D). In addition to the classical deterministic models used in epidemiology, the stochastic model offers a natural representation of the evolution of the COVID-19 epidemic. We inferred the models with the official data provided by the COVID-19 Command Center (CCO) of Madagascar, between March and August 2020. The basic reproduction number R0 and the other parameters were estimated with a Bayesian approach. We developed an algorithm that allows having a temporal estimate of this number with confidence intervals. The estimated values are slightly lower than the international references. Generally, we were able to obtain a simple but effective model to describe the spread of the disease.
Paul-Antoine Bisgambiglia
Open Journal of Modelling and Simulation, Volume 09, pp 172-197; doi:10.4236/ojmsi.2021.92012

This work proposes a new simulation algorithm to improve message handling in discrete event formalism. We present an approach to minimize simulation execution time. To do this, we propose to reduce the number of exchanged messages between Parallel DEVS (PDEVS) components (simulators and coordinators). We propose three changes from PDEVS: direct coupling, flat structure and local schedule. The goal is the decentralisation of a number of tasks to make the simulators more autonomous and simplify the coordinators to achieve a greater speedup. We propose to compare the simulation results of several models to demonstrate the benefits of our approach.
Hameed K. Ebraheem, Nizar Alkhateeb, Hussein Badran, Ebraheem Sultan
Open Journal of Modelling and Simulation, Volume 09, pp 146-158; doi:10.4236/ojmsi.2021.92010

This paper presents a new modified SIR model which incorporates appropriate delay parameters leading to a more precise prediction of COVID-19 real time data. The efficacy of the newly developed SIR model is proven by comparing its predictions to real data obtained from four counties namely Germany, Italy, Kuwait, and Oman. Two included delay periods for incubation and recovery within the SIR model produce a sensible and more accurate representation of the real time data. In the absence of the two-delay period () the dynamical behavior of the model will not correspond to today’s picture and lag the detection of the epidemic peak. The reproductive number R0 is defined for the model for values of recovery time delay of the infective case. The effect of recovery time may produce second wave, and/or an oscillation which could destabilize the behavior of the system and a periodic oscillation can arise due to Hopf bifurcation phenomenon.
Travis S. Ramsay
Open Journal of Modelling and Simulation, Volume 09, pp 1-25; doi:10.4236/ojmsi.2021.91001

An explicitly coupled two-dimensional (2D) multiphysics finite element method (FEM) framework comprised of thermal, phase field, mechanical and electromagnetic (TPME) equations was developed to simulate the conversion of solid kerogen in oil shale to liquid oil through in-situ pyrolysis by radio frequency heating. Radio frequency heating as a method of in-situ pyrolysis represents a tenable enhanced oil recovery method, whereby an applied electrical potential difference across a target oil shale formation is converted to thermal energy, heating the oil shale and causing it to liquify to become liquid oil. A number of in-situ pyrolysis methods are reviewed but the focus of this work is on the verification of the TPME numerical framework to model radio frequency heating as a potential dielectric heating process for enhanced oil recovery. Very few studies exist which describe production from oil shale; furthermore, there are none that specifically address the verification of numerical models describing radio frequency heating. As a result, the Method of Manufactured Solutions (MMS) was used as an analytical verification method of the developed numerical code. Results show that the multiphysics finite element framework was adequately modeled enabling the simulation of kerogen conversion to oil as a part of the analysis of a TPME numerical model.
Peter A. Hall, Gabor Kiss, Tilman Kuhn, Salissou Moutari, Ellen Patterson, Emily Smith
Open Journal of Modelling and Simulation, Volume 09, pp 91-110; doi:10.4236/ojmsi.2021.92006

In this study, we investigate the dynamics of the COVID-19 epidemic in Northern Ireland from 1st March 2020 up to 25th December 2020, using several copies of a Susceptible-Exposed-Infectious-Recovered (SEIR) compartmental model, and compare it to a detailed publicly available dataset. We split the data into 10 time intervals and fit the models on the consecutive intervals to the cumulative number of confirmed positive cases on each interval. Using the fitted parameter estimates, we also provide estimates of the reproduction number. We also discuss the limitations and possible extensions of the employed model.
Dezhi Chen, Congcong Yan
Open Journal of Modelling and Simulation, Volume 09, pp 198-210; doi:10.4236/ojmsi.2021.92013

It is very important to identify the attribute mastery patterns of the examinee in cognitive diagnosis assessment. There are many methods to classify the attribute mastery patterns and many studies have been done to diagnose what the individuals have mastered and or Montel Carl Computer Simulation is used to study the classification of the attribute mastery patterns by Deep Learning. Four results were found. Firstly, Deep Learning can be used to classify the attribute mastery patterns efficiently. Secondly, the complication of the structures will decrease the accuracy of the classification. The order of the influence is linear, convergent, unstructured and divergent. It means that the divergent is the most complicated, and the accuracy of this structure is the lowest among the four structures. Thirdly, with the increasing rates of the slipping and guessing, the accuracy of the classification decreased in verse, which is the same as the existing research results. At last, the results are influenced by the sample size of the training, and the proper sample size is in need of deeper discussion.
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