Search results for: systems modeling

Authors: Ekrem Canli, Thomas Glade

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The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

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Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

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Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

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Authors: Kai Jin, Hua Li, Qing Song

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Homeland security and border safety is an issue for any country. This paper takes the border security of US as an example to discuss the usage and efficiency of simulation tools in the homeland security application. In this study, available resources and different illegal infiltration parameters are defined, including their individual behavior and objective, in order to develop a model that describes border patrol system. A simulation model is created in Arena. This simulation model is used to study the dynamic activities in the border security. Possible factors that may affect the effectiveness of the border patrol system are proposed. Individual and factorial analysis of these factors is conducted and some suggestions are made.

Keywords: resource optimization, simulation, modeling, border security

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Authors: Saritdikhun Somasa

Abstract:

3D printing fabrication has empowered many artists in many fields. Artists who work in stop motion, 3D modeling, toy design, product design, sculpture, and fine arts become one-stop shop operations–where they can design, prototype, and distribute their designs for commercial or fine art purposes. The author has developed a digital sculpting course that fosters digital software, peripheral hardware, and 3D printing with traditional sculpting concept techniques to address the complexities of this multifaceted process, allowing the students to produce complex 3d-printed work. The author will detail the preparation and planning for pre- to post-process 3D printing elements, including software, materials, space, equipment, tools, and schedule consideration for small to medium figurine design statues in a semester-long class. In addition, the author provides insight into teaching challenges in the non-studio space that requires students to work intensively on post-printed models to assemble parts, finish, and refine the 3D printed surface. Even though this paper focuses on the 3D printing processes and techniques for small to medium design statue projects for the Digital Media program, the author hopes the paper will benefit other fields of study such as craft practices, product design, and fine-arts programs. Other schools that might implement 3D printing and fabrication in their programs will find helpful information in this paper, such as a teaching plan, choices of equipment and materials, adaptation for non-studio spaces, and putting together a complete and well-resolved project for students.

Keywords: 3D digital modeling, 3D digital sculpting, 3D modeling, 3D printing, 3D digital fabrication

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Authors: T. Qasim, M. Alqawasmi, M. Hawash, M. Betar, W. Qasim

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Over the last decade, the over population that has happened in urban areas has been reflecting on the services that various local institutions provide to car users in the form of car parks, which is becoming a daily necessity in our lives. This study focuses on car parks at Jordan University of Science and Technology, in Irbid, Jordan, to understand the university parking needs. Data regarding arrival and departure times of cars and the parking utilization were collected, to find various options that the university can implement to solve and develop an efficient car parking system. Arena software was used to simulate a parking model. This model allows measuring the different solutions that solve the parking problem at Jordan University of Science and Technology.

Keywords: car park, simulation, modeling, service time

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Authors: A. Al-Rashidi, A. El-Hamalawi

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In this paper, a performance study was conducted to investigate single and dual-axis PV systems to generate electricity in five different sites in Kuwait. Relevant data were obtained by using two sources for validation purposes. A commercial software, PVsyst, was used to analyse the data, such as metrological data and other input parameters, and compute the performance parameters such as capacity factor (CF) and final yield (YF). The results indicated that single and dual-axis PV systems would be very beneficial to electricity generation in Kuwait as an alternative source to conventional power plants, especially with the increased demand over time. The ranges were also found to be competitive in comparison to leading countries using similar systems. A significant increase in CF and YF values around 24% and 28.8% was achieved related to the use of single and dual systems, respectively.

Keywords: single-axis and dual-axis photovoltaic systems, capacity factor, final yield, Kuwait

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Authors: Mohsin Ali Shaikh, Song Weiguo, Muhammad Kashan Surahio, Usman Shahid, Rehmat Karim

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When the area of a structure that is threatened by a disaster affects personal safety, the effectiveness of disaster prevention, evacuation, and rescue operations can be summarized by three assessment indicators: personal safety, property preservation, and attribution of responsibility. These indicators are applicable regardless of the disaster that affects the building. People need to get out of the hazardous area and to a safe place as soon as possible because there's no other way to respond. The results of the tragedy are thus closely related to how quickly people are advised to evacuate and how quickly they are rescued. This study considers present fire prevention systems to address catastrophes and improve building safety. It proposes the methods of Prevention Level for Deployment in Advance and Spatial Transformation by Human-Machine Collaboration. We present and prototype a real-time fire protection system architecture for building disaster prevention, evacuation, and rescue operations. The design encourages the use of simulations to check the efficacy of evacuation, rescue, and disaster prevention procedures throughout the planning and design phase of the structure.

Keywords: prevention level, building information modeling, quality management system, simulated reality

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Authors: Michael Alsop, Hannah Heitz, Prathiba Natesan Batley, Marion Hambrick, Jason Immekus

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The impacts of cultural engagement on individuals’ health and well-being have been well documented. The purposes of this study were to create an instrument to measure wellbeing constructs, including cultural wellbeing, and explore the relationships between cultural wellbeing and other wellbeing constructs (e.g., emotional, social, physical, spiritual). A sample of 358 participants attending concerts performed by a civic orchestra in the southeastern United States completed a questionnaire designed to measure eight wellbeing constructs. Split-half exploratory, confirmatory factor analyses resulted in the retention of four wellbeing constructs: general, emotional, financial, and cultural. Structural equation modeling showed statistically significant relationships between cultural wellbeing and other wellbeing constructs. In addition to the indirect effect of financial wellbeing on emotional and general wellbeing through cultural wellbeing, there were also direct statistically significant relationships (i.e., moderator). This highlights the importance of removing financial barriers to cultural engagement and the relationship between cultural wellbeing on emotional and general wellbeing. Additionally, the retained cultural wellbeing items focused primarily on community features, indicating the value of community-based cultural engagement opportunities.

Keywords: cultural wellbeing, cultural engagement, factor analysis, structural equation modeling

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Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

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This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

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Authors: Abdullah Eqal Al Mazrooei

Abstract:

In this paper, we introduce a mathematical algorithm which is used for estimating the states in the bilinear systems. This algorithm uses a special linearization of the second-order term by using the best available information about the state of the system. This technique makes our algorithm generalizes the well-known Kalman estimators. The system which is used here is of the bilinear class, the evolution of this model is linear-bilinear in the state of the system. Our algorithm can be used with linear and bilinear systems. We also here introduced a real application for the new algorithm to prove the feasibility and the efficiency for it.

Keywords: estimation algorithm, bilinear systems, Kakman filter, second order linearization

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Authors: Kobi Kutsher

Abstract:

On February 12th 2013, monitoring stations of the Preparatory Commission of the Comprehensive Nuclear Test-Ban Treaty Organization (CTBTO) detected a seismic event with explosion-like underground characteristics in the Democratic People’s Republic of Korea (DPRK). The location was found to be in the vicinity of the two previous announced nuclear tests in 2006 and 2009.The nuclear test was also announced by the government of the DPRK.After an underground nuclear explosion, radioactive fission products (mostly noble gases) can seep through layers of rock and sediment until they escape into the atmosphere. The fission products are dispersed in the atmosphere and may be detected thousands of kilometers downwind from the test site. Indeed, more than 7 weeks after the explosion, unusual detections of noble gases was reported at the radionuclide station in Takasaki, Japan. The radionuclide station is a part of the International Monitoring System, operated to verify the CTBT. This study provides an estimation of the possible source region and the total radioactivity of the release using Atmospheric Transport Modeling.

Keywords: atmospheric transport modeling, CTBTO, nuclear tests, radioactive fission products

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Authors: David Kriebel, Jan Edgar Mehner

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The paper introduces a method to efficiently simulate nonlinear changing electrostatic fields occurring in micro-electromechanical systems (MEMS). Large deflections of the capacitor electrodes usually introduce nonlinear electromechanical forces on the mechanical system. Traditional finite element methods require a time-consuming remeshing process to capture exact results for this physical domain interaction. In order to accelerate the simulation process and eliminate the remeshing process, a formulation of a strongly coupled electromechanical transducer element will be introduced, which uses a combination of finite-element with an advanced mesh morphing technique using radial basis functions (RBF). The RBF allows large geometrical changes of the electric field domain while retaining the high element quality of the deformed mesh. Coupling effects between mechanical and electrical domains are directly included within the element formulation. Fringing field effects are described accurately by using traditional arbitrary shape functions.

Keywords: electromechanical, electric field, transducer, simulation, modeling, finite-element, mesh morphing, radial basis function

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Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

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Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

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Authors: H. Shokouhmand, M. Tajerian

Abstract:

At this paper velocity profile modeling and heat transfer in the micro heat pipes by using electrohydrodynamic (EHD) field at the transient regime have been studied. In the transient flow, one dimensional and two phase fluid flow and heat transfer for micro heat pipes with square cross section, have been studied. At this model Coulomb and dielectrophoretic forces are considered. Coupled, non-linear equations governed on the model (continuity, momentum, and energy equations) have been solved simultaneously by numerical methods. Transient behavior of affecting parameters e.g. substrate temperature, velocity of coolant liquid, radius of curvature and coolant liquid pressure, has been verified. By obtaining and plotting the mentioned parameters, it has been shown that the EHD field enhances the heat transfer process. So, the time required to reach the steady state regime decreases from 16 seconds to 2.4 seconds after applying EHD field. Another result has been observed implicitly that by increasing the heat input the effect of EHD field became more significant. The numerical results of model predict the experimental results available in the literature successfully, and it has been observed there is a good agreement between them.

Keywords: micro heat pipe, transient modeling, electrohydrodynamics, capillary, meniscus

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Authors: Mahmoud Nadir, Adel Ghenaiet

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The main purpose of this study is the thermodynamic modeling, the parametric analysis, and the optimization of three pressure level reheat HRSG (Heat Recovery Steam Generator) using PSO method (Particle Swarm Optimization). In this paper, a parametric analysis followed by a thermodynamic optimization is presented. The chosen objective function is the specific work of the steam cycle that may be, in the case of combined cycle (CC), a good criterion of thermodynamic performance analysis, contrary to the conventional steam turbines in which the thermal efficiency could be also an important criterion. The technologic constraints such as maximal steam cycle temperature, minimal steam fraction at steam turbine outlet, maximal steam pressure, minimal stack temperature, minimal pinch point, and maximal superheater effectiveness are also considered. The parametric analyses permitted to understand the effect of design parameters and the constraints on steam cycle specific work variation. PSO algorithm was used successfully in HRSG optimization, knowing that the achieved results are in accordance with those of the previous studies in which genetic algorithms were used. Moreover, this method is easy to implement comparing with the other methods.

Keywords: combined cycle, HRSG thermodynamic modeling, optimization, PSO, steam cycle specific work

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Authors: K. Jithendra Gowd, Ch. Sai Babu, S. Sivanagaraju

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Electric power systems are daily exposed to service interruption mainly due to faults and human accidental interference. Short circuit currents are responsible for several types of disturbances in power systems. The fault currents are high and the voltages are reduced at the time of fault. This paper presents two suitable methods, consideration of fault resistance and Distributed Generator are implemented and analyzed for the enhancement of voltage profile during fault conditions. Fault resistance is a critical parameter of electric power systems operation due to its stochastic nature. If not considered, this parameter may interfere in fault analysis studies and protection scheme efficiency. The effect of Distributed Generator is also considered. The proposed methods are tested on the IEEE 37 bus test systems and the results are compared.

Keywords: distributed generation, electrical distribution systems, fault resistance

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Authors: B. H. Aitchanov, Sh. K. Aitchanova, O. A. Baimuratov

Abstract:

This paper is focused on dynamic pulse-frequency modulation (DPFM) control systems. Currently, the control law based on DPFM control signals is widely used in direct digital control subsystems introduced in the automated control systems of technological processes. Statistical analysis of automatic control systems is reduced to its construction of functional relationships between the statistical characteristics of the errors processes and input processes. Structural and dynamic Volterra models of digital pulse-frequency control systems can be used to develop methods for generating the dependencies, differing accuracy, requiring the amount of information about the statistical characteristics of input processes and computing labor intensity of their use.

Keywords: digital dynamic pulse-frequency control systems, dynamic pulse-frequency modulation, control object, discrete filter, impulse device, microcontroller

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Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng

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The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.

Keywords: area-based traffic, car-following model, micro-simulation, stochastic modeling

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Authors: Razieh Arian, Hadi Adibi-Asl

Abstract:

This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

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Authors: Keerthi S. Shetty, Annappa Basava

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In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

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Authors: Annie B. V., Anu A. G., Harikumar R.

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Microgrid (MG) is a self-governing miniature section of the power system. Nowadays the majority of loads and energy storage devices are inherently in DC form. This necessitates a greater scope of research in the various types of energy storage devices in DC microgrids. In a modern power system, DC microgrid is a manageable electric power system usually integrated with renewable energy sources (RESs) and DC loads with the help of power electronic converters. The stability of the DC microgrid mainly depends on the power imbalance. Power imbalance due to the presence of intermittent renewable energy resources (RERs) is supplied by energy storage devices. Battery, supercapacitor, flywheel, etc. are some of the commonly used energy storage devices. Owing to the high energy density provided by the batteries, this type of energy storage system is mainly utilized in all sorts of hybrid energy storage systems. To minimize the stability issues, a Supercapacitor (SC) is usually interfaced with the help of a bidirectional DC/DC converter. SC can exchange power during transient conditions due to its high power density. This paper analyses the stability issues of DC microgrids with hybrid energy storage systems (HESSs) arises from a reduction in SC operating voltage due to self-discharge. The stability of DC microgrid and power management is analyzed with different control strategies.

Keywords: DC microgrid, hybrid energy storage system (HESS), power management, small signal modeling, supercapacitor

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Authors: Moqbil S. Alenazi, Magdy. M. Elkhateeb

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A comprehensive photometric study and evolutionary state for the newly discovered Beta Lyr systems V0487 Lac, V0566 Hya, and V0666 Lac were carried out by means of their first photometric observations. New times of minima were estimated from the observed light curves, and first (O-C) curves were established for all systems. A windows interface version of the Wilson and Devinney code (W-D) based on model atmospheres and a pass band prescription have been used for the radiative treatment. The accepted models reveal some absolute parameters for the studied systems, which are used in adopting the spectral type of the system's components and their evolutionary status. Distances to each system were calculated, and physical properties were estimated. Locations of the systems on the theoreticalmass–luminosity and mass–radius relations revealed a good fit for all systems components except for the secondary component of the system V0487 Lac.

Keywords: eclipsing binaries, light curve modelling, evolutionary state

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Authors: Amit R. Bhende, G. K. Awari

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Remaining useful life (RUL) prediction is one of key technologies to realize prognostics and health management that is being widely applied in many industrial systems to ensure high system availability over their life cycles. The present work proposes a data-driven method of RUL prediction based on multiple health state assessment for rolling element bearings. Bearing degradation data at three different conditions from run to failure is used. A RUL prediction model is separately built in each condition. Feed forward back propagation neural network models are developed for prediction modeling.

Keywords: bearing degradation data, remaining useful life (RUL), back propagation, prognosis

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Authors: W. A. Gonçalves, E. P. Souza, C. R. Alcântara

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The ISCCP-Tracking database offers an opportunity to study physical and morphological characteristics of Convective Systems based on geostationary meteorological satellites. This database contains 26 years of tracking of Convective Systems for the entire globe. Then, Tropical Squall Lines which occur in Brazil are certainly within the database. In this study, we propose a methodology for identification of these systems based on the ISCCP-Tracking database. A physical and morphological characterization of these systems is also shown. The proposed methodology is firstly based on the year of 2007. The Squall Lines were subjectively identified by visually analyzing infrared images from GOES-12. Based on this identification, the same systems were identified within the ISCCP-Tracking database. It is known, and it was also observed that the Squall Lines which occur on the north coast of Brazil develop parallel to the coast, influenced by the sea breeze. In addition, it was also observed that the eccentricity of the identified systems was greater than 0.7. Then, a methodology based on the inclination (based on the coast) and eccentricity (greater than 0.7) of the Convective Systems was applied in order to identify and characterize Tropical Squall Lines in Brazil. These thresholds were applied back in the ISCCP-Tracking database for the year of 2007. It was observed that other systems, which were not Squall Lines, were also identified. Then, we decided to call all systems identified by the inclination and eccentricity thresholds as Linear Convective Systems, instead of Squall Lines. After this step, the Linear Convective Systems were identified and characterized for the entire database, from 1983 to 2008. The physical and morphological characteristics of these systems were compared to those systems which did not have the required inclination and eccentricity to be called Linear Convective Systems. The results showed that the convection associated with the Linear Convective Systems seems to be more intense and organized than in the other systems. This affirmation is based on all ISCCP-Tracking variables analyzed. This type of methodology, which explores 26 years of satellite data by an objective analysis, was not previously explored in the literature. The physical and morphological characterization of the Linear Convective Systems based on 26 years of data is of a great importance and should be used in many branches of atmospheric sciences.

Keywords: squall lines, convective systems, linear convective systems, ISCCP-Tracking

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Authors: Sayed M. Soleimani, Nader H. Ghareeb, Nourhan H. Shaker, Muhammad B. Siddiqui

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Honeycomb sandwich panels have been widely used as protective structural elements against blast loading. The main advantages of these panels include their light weight due to the presence of voids, as well as their energy absorption capability. Terrorist activities have imposed new challenges to structural engineers to design protective measures for vital structures. Since blast loading is not usually considered in the load combinations during the design process of a structure, researchers around the world have been motivated to study the behavior of potential elements capable of resisting sudden loads imposed by the detonation of explosive materials. One of the best candidates for this objective is the honeycomb sandwich panel. Studying the effects of explosive materials on the panels requires costly and time-consuming experiments. Moreover, these type of experiments need permission from defense organizations which can become a hurdle. As a result, modeling and simulation using an appropriate tool can be considered as a good alternative. In this research work, the finite element package ABAQUS® is used to study the behavior of hexagonal and squared honeycomb steel sandwich panels under the explosive effects of different amounts of trinitrotoluene (TNT). The results of finite element modeling of a specific honeycomb configuration are initially validated by comparing them with the experimental results from literature. Afterwards, several configurations including different geometrical properties of the honeycomb wall are investigated and the results are compared with the original model. Finally, the effectiveness of the core shape and wall thickness are discussed, and conclusions are made.

Keywords: Abaqus, blast loading, finite element modeling, steel honeycomb sandwich panel

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Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

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Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.

Keywords: COVID-19, modeling, time series, copula function

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Authors: Y. Ruchi, A. Prerna, S. Deepshikha

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Amyotrophic lateral sclerosis (ALS), also known as “Lou Gehrig’s disease”. It is a neurodegenerative disease associated with degeneration of motor neurons in the cerebral cortex, brain stem, and spinal cord characterized by distal muscle weakness, atrophy, normal sensation, pyramidal signs and progressive muscular paralysis reflecting. ALS2 is a juvenile autosomal recessive disorder, slowly progressive, that maps to chromosome 2q33 and is associated with mutations in the alsin gene, a putative GTPase regulator. In this paper we have done homology modeling of alsin2 protein using multiple templates (3KCI_A, 4LIM_A, 402W_A, 4D9S_A, and 4DNV_A) designed using the Prime program in Schrödinger software. Further modeled structure is used to identify effective binding sites on the basis of structural and physical properties using sitemap program in Schrödinger software, structural and function analysis is done by using Prosite and ExPASy server that gives insight into conserved domains and motifs that can be used for protein classification. This paper summarizes the structural, functional and binding site property of alsin2 protein. These binding sites can be potential drug target sites and can be used for docking studies.

Keywords: ALS, binding site, homology modeling, neuronal degeneration

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Authors: Luis Andrey Fajardo Fajardo

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We are immersed in complex systems. The human brain, the galaxies, the snowflakes are examples of complex systems. An area of interest in Complex systems is the chaos theory. This revolutionary field of science presents different ways of study than determinism and reductionism. Here is where in junction with the Nonlinear DSP, chaos theory offer valuable techniques that establish a link between time series and complex theory in terms of complex networks, so that, the study of signals can be explored from the graph theory. Recently, some people had purposed a method to transform time series in graphs, but no one had developed a suitable implementation in Python with signals extracted from Chaotic Systems or Complex systems. That’s why the implementation in Python of an existing method to transform one dimensional chaotic signals from time domain to graph domain and some measures that may reveal information not extracted in the time domain is proposed.

Keywords: Python, complex systems, graph theory, dynamical systems

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Authors: Zakariyya Hassan Abdullahi, Zainab Suleiman Abdullahi, Nuhu Alhaji Muhammad

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In this paper, a thorough review of photovoltaic and photovoltaic thermal systems is done on the basis of its performance based on electrical as well as thermal output. Photovoltaic systems are classified according to their use, i.e., electricity production, and thermal, Photovoltaic systems behave in an extraordinary and useful way, they react to light by transforming part of it into electricity useful way and unique, since photovoltaic and thermal applications along with the electricity production. The application of various photovoltaic systems is also discussed in detail. The performance analysis including all aspects, e.g., electrical, thermal, energy, and energy efficiency are also discussed. A case study for PV and PV/T system based on energetic analysis is presented.

Keywords: photovoltaic, renewable, performance, efficiency, energy

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Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

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The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

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