Search results for: simulation tools

Authors: Maha Ibrahim Mohamed Khalifa

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Background: Dental fear and anxiety lead to avoidance of dental treatment and deterioration of oral health. Aim of the study: To assess the levels of fear and anxiety among school-age children undergoing dental treatment. Setting: The study was conducted in Outpatient Dental Clinics at Benha Teaching Hospital. Research design: A descriptive research design was utilized to conduct the study. Sample: A purposive sample of 60 school-age children and their mothers attending at the previously mentioned setting was included. Tools: Three tools were used: Tool one: A structured interviewing questionnaire for Personal characteristics of children and their mothers. Tool two: Dental Subscale of Children's Fear Survey Schedule (CFSS-DS). Tool three: Modified Dental Anxiety Scale (MDAS). Results: It was illustrated that more than two-fifths (43.3%) of children had maximum fear and more than half of children (53.3%) had maximal anxiety. Conclusion: Many school-age children undergoing dental treatment suffer from high levels of fear and anxiety. Recommendations: The study recommended further research should be conducted to assess levels of fear and anxiety among children undergoing dental treatments and preferable nursing interventions for reducing their fears and anxieties.

Keywords: fear, anxiety, children, dental treatment

Procedia PDF Downloads 82

Authors: Jingjing Huang, Nengwei Li, Guanghua Wei, Jiabin You, Chao Wang, Junliang Zhang

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In this work, molecular dynamics (MD) simulation is applied to analyze the mass transport process in the cathode of proton exchange membrane fuel cell (PEMFC), of which all types of molecules situated in the cathode is considered. a reasonable and effective MD simulation process is provided, and models were built and compared using both Materials Studio and LAMMPS. The mass transport is one of the key issues in the study of proton exchange membrane fuel cells (PEMFCs). In this report, molecular dynamics (MD) simulation is applied to analyze the influence of Nafion ionomer distribution and Pt nano-particle size on mass transport process in the cathode. It is indicated by the diffusion coefficients calculation that a larger quantity of Nafion, as well as a higher equivalent weight (EW) value, will hinder the transport of oxygen. In addition, medium-sized Pt nano-particles (1.5~2nm) are more advantageous in terms of proton transport compared with other particle sizes (0.94~2.55nm) when the center-to-center distance between two Pt nano-particles is around 5 nm. Then mass transport channels are found to be formed between the hydrophobic backbone and the hydrophilic side chains of Nafion ionomer according to the radial distribution function (RDF) curves. And the morphology of these channels affected by the Pt size is believed to influence the transport of hydronium ions and, consequently the performance of PEMFC.

Keywords: cathode catalytic layer, mass transport, molecular dynamics, proton exchange membrane fuel cell

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Authors: Palash Kumar Mollick, Leire Olazar, Laura Santamaria, Pablo Comendador, Gartzen Lopez, Martin Olazar

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Average calorific value of a mixure of waste plastic is approximately 38 MJ/kg. Present work aims to extract maximum possible energy from a mixure of waste plastic using a DC thermal plasma in a spouted bed reactor. Plasma pyrolysis and steam reforming process has shown a potential to generate hydrogen from plastic with much below of legal limit of producing dioxins and furans as the carcinogenic gases. A spouted bed pyrolysis rector can continuously process plastic beads to produce organic volatiles, which later react with steam in presence of catalyst to results in syngas. lasma being the fourth state of matter, can carry high impact electrons to favour the activation energy of any chemical reactions. Computational Fluid Dynamic (CFD) simulation using COMSOL Multiphysics software has been performed to evaluate performance of a plasma spouted bed reactor in producing contamination free hydrogen as a green energy from waste plastic beads. The simulation results will showcase a design of a plasma spouted bed reactor for converting plastic waste into green hydrogen in a single step process. The high temperature hydrodynamics of spouted bed with plastic beads and the corresponding temperature distribution inside the reaction chamber will be critically examined for it’s near future installation of demonstration plant.

Keywords: green hydrogen, plastic waste, synthetic gas, pyrolysis, steam reforming, spouted bed, reactor design, plasma, dc palsma, cfd simulation

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Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap

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We use modeling and simulation tools, to introduce a novel bias injection attack, named the ’Induced Pulsation Attack’, which targets Cyber Physical Systems with closed-loop controlled Brushless DC (BLDC) motor and Kalman filter driver in the feedback loop. This attack involves engaging a linear function with a constant gradient to distort the coefficient of the injected bias, which falsifies the Kalman filter estimates of the rotor’s angular speed. As a result, this manipulation interaction inside the control system causes periodic pulsations in a form of asymmetric sine wave of both current and voltage in the circuit windings, with a high magnitude. It is shown that by varying the gradient of linear function, one can control both the frequency and structure of the induced pulsations. It is also demonstrated that terminating the attack at any point leads to additional compensating effort from the controller to restore the speed to its equilibrium value. This compensation effort produces an exponentially decaying wave, which we call the ’attack withdrawal syndrome’ wave. The conditions for maximizing or minimizing the impact of the attack withdrawal syndrome are determined. Linking the termination of the attack to the end of the full period of the induced pulsation wave has been shown to nullify the attack withdrawal syndrome wave, thereby improving the attack’s covertness.

Keywords: cyber-attack, induced pulsation, bias injection, Kalman filter, BLDC motor, control system, closed loop, P- controller, PID-controller, saw-function, cyber-physical system

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Authors: Ilhem Ouelhazi, Mouna Elakhdar, Lakdar Kairouani

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A computer simulation model for a combined ejector-vapor compression cycle that uses working fluid R134a. A refrigeration system was developed which combines a basic vapor compression refrigeration cycle with an ejector cooling cycle. A one-dimensional mathematical model was developed using the equations governing the flow and thermodynamics based on the constant area ejector flow model. The effects of the operating parameters on the cooling capacity, the performance coefficient, and the entrainment ratio are studied. The current model is based on the NIST-REFPROP database for refrigerants properties calculations. The simulated performance is compared with the available experimental data from the literature for validation.

Keywords: combined refrigeration cycle, constant area ejector, R134a, ejector-cooling cycle, performance, mathematical simulation, vapor compression cycle

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Ruiyang Bi

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Natural rock masses are cut into rock blocks of different shapes and sizes by intersecting joints. These rock blocks often determine the mechanical properties of the rock mass. In this study, fine sandstone cube specimens were produced, and three intersecting joint cracks were cut inside the specimen. Uniaxial compression tests were conducted using mechanical tests and numerical simulation methods to study the mechanical properties and crack propagation mechanism of triangular blocks within the rock. During the test, the mechanical strength, acoustic emission characteristics and strain field evolution of the specimen were analyzed. Discrete element software was used to study the expansion of microcracks during the specimen failure process, and the crack types were divided. The simulation results show that as the inclination angles of the three joints increase simultaneously, the mechanical strength of the specimen first decreases and then increases, and the crack type is mainly shear. As the inclination angle of a single joint increases, the strength of the specimen gradually decreases. When the inclination angles of the two joints increase at the same time, the strength of the specimen gradually decreases. The research results show that the stability of the rock mass is affected by the joint inclination angle and the size of the cut blocks. The greater the joint dip and block size, the more significant the development of micro-cracks in the rock mass, and the worse the stability.

Keywords: rock joints, uniaxial compression, crack extension, discrete element simulation

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Authors: L. Kiefer, C. Richter, G. Reinhart

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The uprising complexity in production systems due to an increasing amount of variants up to customer innovated products leads to requirements that hierarchical control systems are not able to fulfil. Therefore, factory planners can install autonomous manufacturing systems. The fundamental requirement for an autonomous control is the identification of objects within production systems. In this approach an attribute-based identification is focused for avoiding dose-dependent identification costs. Instead of using an identification mark (ID) like a radio frequency identification (RFID)-Tag, an object type is directly identified by its attributes. To facilitate that it’s recommended to include the identification and the corresponding sensors within handling processes, which connect all manufacturing processes and therefore ensure a high identification rate and reduce blind spots. The presented methodology reduces the individual effort to integrate identification processes in handling systems. First, suitable object attributes and sensor systems for object identification in a production environment are defined. By categorising these sensor systems as well as handling systems, it is possible to match them universal within a compatibility matrix. Based on that compatibility further requirements like identification time are analysed, which decide whether the combination of handling and sensor system is well suited for parallel handling and identification within an autonomous control. By analysing a list of more than thousand possible attributes, first investigations have shown, that five main characteristics (weight, form, colour, amount, and position of subattributes as drillings) are sufficient for an integrable identification. This knowledge limits the variety of identification systems and leads to a manageable complexity within the selection process. Besides the procedure, several tools, as an example a sensor pool are presented. These tools include the generated specific expert knowledge and simplify the selection. The primary tool is a pool of preconfigured identification processes depending on the chosen combination of sensor and handling device. By following the defined procedure and using the created tools, even laypeople out of other scientific fields can choose an appropriate combination of handling devices and sensors which enable parallel handling and identification.

Keywords: agent systems, autonomous control, handling systems, identification

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Authors: Nureni Asafe Yekini, Olawale Nasiru Lawal, Bola Dada, Gabriel Adeyemi Okunlola

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This study is focused on the strengths and challenges associated with using the online social network as a rapidly evolving medium in marketing tourism services and businesses among the youths in Nigeria. The paper examines the Nigerian tourists’ attitude, mainly towards three aspects: application of Internet for travel and tourism; usage of online social networks in sharing travel and tourism experiences; and trust in electronic-media for marketing tourism businesses and services. The aim of this research is to determine the level of application of internet tools in marketing tourism businesses and services in Nigeria. This study reports an empirical analysis based on data obtained from a survey among 1004 Nigerian tourists. The outcome confirms the research hypothesis and points to crucial importance of introducing online social network site for marketing tourism businesses and services in Nigeria, and increasing the awareness for Nigeria as a tourist destination. Moreover, the paper strongly recommends the use of online social network as a tool for marketing tourism businesses and services, and the need for identifying effective framework for application of ICT tools in marketing tourism businesses and services in Nigeria at large.

Keywords: tourism business, internet, online social networks, tourism services, ICT

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Authors: Sajjad Hassanpour, Vicente A. González, Yang Zou, Jiamou Liu

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Earthquakes pose a significant threat to both structural and non-structural elements in buildings, putting human lives at risk. Effective post-earthquake evacuation is critical for ensuring the safety of building occupants. However, current design practices often neglect the integration of post-earthquake evacuation considerations into the early-stage architectural design process. To address this gap, this paper presents a novel automated internal architectural layout generation tool that optimizes post-earthquake evacuation performance. The tool takes an initial plain floor plan as input, along with specific requirements from the user/architect, such as minimum room dimensions, corridor width, and exit lengths. Based on these inputs, firstly, the tool randomly generates different architectural layouts. Secondly, the human post-earthquake evacuation behaviour will be thoroughly assessed for each generated layout using the advanced Agent-Based Building Earthquake Evacuation Simulation (AB2E2S) model. The AB2E2S prototype is a post-earthquake evacuation simulation tool that incorporates variables related to earthquake intensity, architectural layout, and human factors. It leverages a hierarchical agent-based simulation approach, incorporating reinforcement learning to mimic human behaviour during evacuation. The model evaluates different layout options and provides feedback on evacuation flow, time, and possible casualties due to earthquake non-structural damage. By integrating the AB2E2S model into the automated layout generation tool, architects and designers can obtain optimized architectural layouts that prioritize post-earthquake evacuation performance. Through the use of the tool, architects and designers can explore various design alternatives, considering different minimum room requirements, corridor widths, and exit lengths. This approach ensures that evacuation considerations are embedded in the early stages of the design process. In conclusion, this research presents an innovative automated internal architectural layout generation tool that integrates post-earthquake evacuation simulation. By incorporating evacuation considerations into the early-stage design process, architects and designers can optimize building layouts for improved post-earthquake evacuation performance. This tool empowers professionals to create resilient designs that prioritize the safety of building occupants in the face of seismic events.

Keywords: agent-based simulation, automation in design, architectural layout, post-earthquake evacuation behavior

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Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

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Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

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Authors: Meet Patel, Darshan Patel, Nilay Shah

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Excess growth of wind-based renewable energy sources is required to identify the optimal location and damping capacity of doubly fed induction-generator-based (DFIG) wind farms while it penetrates into the transmission network. In this analysis, various ratings of DFIG wind farms are penetrated into the Single Machine Infinite Bus (SMIB ) at a different distance of the transmission line. On the basis of detailed examinations, a prime position is evaluated to maximize the stability of overall systems. A damping controller is designed at an optimum location to mitigate the small oscillations. The proposed model was validated using eigenvalue analysis, calculation of the participation factor, and time-domain simulation.

Keywords: DFIG, small signal stability, eigenvalues, time domain simulation

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Authors: Ji-Seok Hong, Hee-Jang Moon, Hong-Gye Sung

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The details of flow structures and the coupling mechanism between vortex shedding and acoustic excitation in a solid rocket motor with two inhibitors have been investigated using 3D Large Eddy Simulation (LES) and Proper Orthogonal Decomposition (POD) analysis. The oscillation frequencies and vortex shedding periods from two inhibitors compare reasonably well with the experimental data and numerical result. A total of four different locations of the rear inhibitor has been numerically tested to characterize the coupling relation of vortex shedding frequency and acoustic mode. The major source of triggering pressure oscillation in the combustor is the resonance with the acoustic longitudinal half mode. It was observed that the counter-rotating vortices in the nozzle flow produce roll torque.

Keywords: large eddy simulation, proper orthogonal decomposition, SRM instability, flow-acoustic coupling

Procedia PDF Downloads 558

Authors: Mouhamadou Diop, Mohamed I. Hassan

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Molten metallic flow in metallurgical plant is highly turbulent and presents a complex coupling with heat transfer, phase transfer, chemical reaction, momentum transport, etc. Molten silicon flow has significant effect in directional solidification of multicrystalline silicon by affecting the temperature field and the emerging crystallization interface as well as the transport of species and impurities during casting process. Owing to the complexity and limits of reliable measuring techniques, computational models of fluid flow are useful tools to study and quantify these problems. The overall objective of this study is to investigate the potential of a traveling magnetic field for an efficient operating control of the molten metal flow. A multidimensional numerical model will be developed for the calculations of Lorentz force, molten metal flow, and the related phenomenon. The numerical model is implemented in a laboratory-scale silicon crystallization furnace. This study presents the potential of traveling magnetic field approach for an efficient operating control of the molten flow. A numerical model will be used to study the effects of magnetic force applied on the molten flow, and their interdependencies. In this paper, coupled and decoupled, steady and unsteady models of molten flow and crystallization interface will be compared. This study will allow us to retrieve the optimal traveling magnetic field parameter range for crystallization furnaces and the optimal numerical simulations strategy for industrial application.

Keywords: multidimensional, numerical simulation, solidification, multicrystalline, traveling magnetic field

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Authors: Ashwini Umale

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Trajectory planning and optimization is a fundamental problem in articulated robotics. It is often viewed as a two phase problem of initial feasible path planning around obstacles and subsequent optimization of a trajectory satisfying dynamical constraints. An optimized trajectory of multi-axis robot is important and directly influences the Performance of the executing task. Optimal is defined to be the minimum time to transition from the current speed to the set speed. In optimization of trajectory through virtual environment explores the most suitable way to represent robot motion from virtual environment to real environment. This paper aims to review the research of trajectory optimization in virtual environment using simulation software Robcad. Improvements are to be expected in trajectory optimization to generate smooth and collision free trajectories with minimization of overall robot cycle time.

Keywords: trajectory optimization, forward kinematics and reverse kinematics, dynamic constraints, robcad simulation software

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Authors: Md. Fazlul Karim, Ashik Sharfaraz, Aysha Ferdoushi

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Background: Computational medicinal chemistry approaches are used for designing and identifying new drug-like molecules, predicting properties and pharmacological activities, and optimizing lead compounds in drug development. SIRT7, a nicotinamide adenine dinucleotide (NAD+)-dependent deacylase which regulates aging, is an emerging target for cancer therapy with mounting evidence that SIRT7 downregulation plays important roles in reversing cancer phenotypes and suppressing tumor growth. Activation or altered expression of SIRT7 is associated with the progression and invasion of various cancers, including liver, breast, gastric, prostate, and non-small cell lung cancer. Objectives: The goal of this work was to identify potent and selective bioactive candidate inhibitors of SIRT7 by in silico screening of small molecule compounds obtained from Nigella sativa (N. sativa). Methods: SIRT7 structure was retrieved from The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), and its active site was identified using CASTp and metaPocket. Molecular docking simulation was performed with PyRx 0.8 virtual screening software. Drug-likeness properties were tested using SwissADME and pkCSM. In silico toxicity was evaluated by Osiris Property Explorer. Bioactivity was predicted by Molinspiration software. Antitumor activity was screened for Prediction of Activity Spectra for Substances (PASS) using Way2Drug web server. Molecular dynamics (MD) simulation was carried out by Desmond v3.6 package. Results: A total of 159 bioactive compounds from the N. Sativa were screened against the SIRT7 enzyme. Five bioactive compounds: chrysin (CID:5281607), pinocembrin (CID:68071), nigellidine (CID:136828302), nigellicine (CID:11402337), and epicatechin (CID:72276) were identified as potent SIRT7 anti-cancer candidates after docking score evaluation and applying Lipinski's Rule of Five. Finally, MD simulation identified Chrysin as the top SIRT7 anti-cancer candidate molecule. Conclusion: Chrysin, which shows a potential inhibitory effect against SIRT7, can act as a possible anti-cancer drug candidate. This inhibitor warrants further evaluation to check its pharmacokinetics and pharmacodynamics properties both in vitro and in vivo.

Keywords: SIRT7, antitumor, molecular docking, molecular dynamics simulation

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Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno

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Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.

Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index

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Authors: Zineb Ouahdi

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Spirocyclic compound derivatives, with their unique heterocyclic motifs, serve as a continual source of inspiration in the pursuit of developing potential therapeutic agents. These compounds are diverse in their chemical structures; some have fully saturated skeletons, while others are partially unsaturated. Nevertheless, these compounds share a characteristic feature with natural products - the presence of at least one heteroatom in one of their rings. The inclusion of a C = O dipolarophile in pyridazinones imparts an exciting aspect for 1,3-dipolar cycloaddition reactions, the focal point of our study. Our research has involved a detailed theoretical investigation of the reaction between ethyl (Z)-2-bromo-2-(2-(p-tolyl)hydrazono)acetate and 6-methyl-4,5-dihydropyridazine-3(2H)-one. This has been accomplished using the DFT/B3LYP/6-31g(d,p) method, intending to illuminate the chemical pathway of this reaction. The chemical reactivity theories we used for this purpose included FMO, TS, and local and global indices derived from conceptual DFT. The theoretical framework outlined in this study allowed us to propose a reaction mechanism for cycloaddition reactions. It also enabled the identification of the potential activities of the analyzed compounds (P1, P2, P3, P4, P5, and P6) against the major protease of the coronavirus disease (COVID-19). This was achieved using various computational tools, including AutoDock Tools, Autodock Vina, Autodock 4, and PYRX.

Keywords: MEDT, pyridazin, cycloaddition, FMO, DFT, docking

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Authors: T. Nozu, K. Hibi, T. Nishiie

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This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.

Keywords: deflagration, large eddy simulation, turbulent combustion, vented enclosure

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Authors: Mais Wa'ad

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The effect of transmission distance on the performance of hybrid configuration H 10-40 Gb/s with Non-Return to Zero (NRZ) pulse format, 100 GHz channel spacing, and Multiplexer/De-Multiplexer Band width (MUX/DEMUX BW) of 60 GHz has been investigated in this study. The laser Continuous Wave (CW) power launched into the modulator is set to 4 dBm. Eight neighboring DWDM channels are selected around 1550.12 nm carrying different data rates in hybrid optical communication systems travel through the same optical fiber and use the same passive and active optical modules. The simulation has been done using Optiwave Inc Optisys software. Usually, increasing distance will lead to decrease in performance; however this is not always the case, as the simulation conducted in this work, shows different system performance for each channel. This is due to differences in interaction between dispersion and non-linearity, and the differences in residual dispersion for each channel.

Keywords: dispersion and non-linearity interaction, optical hybrid configuration, multiplexer/de multiplexer bandwidth, non-return to zero, optical transmission distance, optisys

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Authors: Meihua Fang, Yipan Guo, Tao Fei, Pengyu Tian

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Space plasma caused spacecraft surface charging is the major space environment hazard. Particle in cell (PIC) method can be used to simulate the interaction between space plasma and spacecraft. It was proved that surface charging level of spacecraft in Jupiter’s orbits was high for its’ electron-heavy plasma environment. In this paper, Jovian plasma environment is modeled and surface charging analysis is carried out by PIC based software Spacecraft Plasma Interaction System (SPIS). The results show that the spacecraft charging potentials exceed 1000V at 2Rj, 15Rj and 25Rj polar orbits in the dark side at worst case plasma model. Furthermore, the simulation results indicate that the large Jovian magnetic field increases the surface charging level for secondary electron gyration.

Keywords: Jupiter, PIC, space plasma, surface charging

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Authors: Laura M. F. Bertens

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There is a long tradition of visually representing the art historical canon, in schematic overviews and diagrams. This is indicative of the desire for scientific, ‘objective’ knowledge of the kind (seemingly) produced in the natural sciences. These diagrams will, however, always retain an element of subjectivity and the modelling methods colour our perception of the represented information. In recent decades visualisations of art historical data, such as hand-drawn diagrams in textbooks, have been extended to include digital, computational tools. These tools significantly increase modelling strength and functionality. As such, they might be used to deconstruct and amend the very problem caused by traditional visualisations of the canon. In this paper, the use of digital tools for modelling the art historical canon is studied, in order to draw attention to the artificial nature of the static models that art historians are presented with in textbooks and lectures, as well as to explore the potential of digital, dynamic tools in creating new models. To study the way diagrams of the canon mediate the represented information, two modelling methods have been used on two case studies of existing diagrams. The tree diagram Stammbaum der neudeutschen Kunst (1823) by Ferdinand Olivier has been translated to a social network using the program Visone, and the famous flow chart Cubism and Abstract Art (1936) by Alfred Barr has been translated to an ontological model using Protégé Ontology Editor. The implications of the modelling decisions have been analysed in an art historical context. The aim of this project has been twofold. On the one hand the translation process makes explicit the design choices in the original diagrams, which reflect hidden assumptions about the Western canon. Ways of organizing data (for instance ordering art according to artist) have come to feel natural and neutral and implicit biases and the historically uneven distribution of power have resulted in underrepresentation of groups of artists. Over the last decades, scholars from fields such as Feminist Studies, Postcolonial Studies and Gender Studies have considered this problem and tried to remedy it. The translation presented here adds to this deconstruction by defamiliarizing the traditional models and analysing the process of reconstructing new models, step by step, taking into account theoretical critiques of the canon, such as the feminist perspective discussed by Griselda Pollock, amongst others. On the other hand, the project has served as a pilot study for the use of digital modelling tools in creating dynamic visualisations of the canon for education and museum purposes. Dynamic computer models introduce functionalities that allow new ways of ordering and visualising the artworks in the canon. As such, they could form a powerful tool in the training of new art historians, introducing a broader and more diverse view on the traditional canon. Although modelling will always imply a simplification and therefore a distortion of reality, new modelling techniques can help us get a better sense of the limitations of earlier models and can provide new perspectives on already established knowledge.

Keywords: canon, ontological modelling, Protege Ontology Editor, social network modelling, Visone

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Authors: L. O. Luengas, E. V. Morales, L. F. G. De Souza, I. S. Bott

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Duplex Stainless Steels are well known for its good mechanical properties, and corrosion resistance. However, when submitted to heating, these features can be lost since the good properties are strongly dependent on the austenite-ferrite phase ratio which has to be approximately 1:1 to keep the phase balance. In a welded joint, the transformation kinetics at the heat affected zone (HAZ) is a function of the cooling rates applied which in turn are dependent on the heat input. The HAZ is usually ferritized at these temperatures, and it has been argued that small variations of the chemical composition can play a role in the solid state transformation sequence of ferrite to austenite during cooling. The δ → γ transformation has been reported to be massive and diffusionless due to the fast cooling rate, but it is also considered a diffusion controlled transformation. The aim of this work is to evaluate the effect of different heat inputs on the HAZ of two duplex stainless steels UNS S32304 and S32750, obtained by physical simulation.

Keywords: duplex stainless steels, HAZ, microstructural characterization, physical simulation

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Authors: Fatma Keskin Arabul, Ibrahim Senol, Ahmet Yigit Arabul, Ali Rifat Boynuegri

Abstract:

On account of the concern of the fossil fuel is depleting and its negative effects on the environment, interest in alternative energy sources is increasing day by day. However, considering the importance of transportation in human life, instead of oil and its derivatives fueled vehicles with internal combustion engines, electric vehicles which are sensitive to the environment and working with electrical energy has begun to develop. In this study, simulation was carried out for providing energy management and recovering regenerative braking in fuel cell-battery hybrid electric vehicle. The main power supply of the vehicle is fuel cell on the other hand not only instantaneous power is supplied by the battery but also the energy generated due to regenerative breaking is stored in the battery. Obtained results of the simulation is analyzed and discussed.

Keywords: electric vehicles, fuel cell, battery, regenerative braking, energy management

Procedia PDF Downloads 710

Authors: Yin-Yann Chen, Jia-Ying Li

Abstract:

Assembly line balancing problems can be categorized into one-sided, two-sided, and multi-manned ones by using the number of operators deployed at workstations. This study explores the balancing problem of a resource-constrained assembly line with multi-manned workstations. Resources include machines or tools in assembly lines such as jigs, fixtures, and hand tools. A mathematical programming model was developed to carry out decision-making and planning in order to minimize the numbers of workstations, resources, and operators for achieving optimal production efficiency. To improve the solution-finding efficiency, a genetic algorithm (GA) and a simulated annealing algorithm (SA) were designed and developed in this study to be combined with a practical case in car making. Results of the GA/SA and mathematics programming were compared to verify their validity. Finally, analysis and comparison were conducted in terms of the target values, production efficiency, and deployment combinations provided by the algorithms in order for the results of this study to provide references for decision-making on production deployment.

Keywords: heuristic algorithms, line balancing, multi-manned workstation, resource-constrained

Procedia PDF Downloads 201

Authors: Sungho Kim, Dae Shik Kim, Jong Min Lee

Abstract:

Fluid catalytic cracking (FCC) process is one of the most important process in modern refinery industry. This paper focuses on the fluid catalytic cracking (FCC) process. As the FCC process is difficult to model well, due to its non linearities and various interactions between its process variables, rigorous process modeling of whole FCC plant is demanded for control and plant-wide optimization of the plant. In this study, a process design for the FCC plant includes riser reactor, main fractionator, and gas processing unit was developed. A reactor model was described based on four-lumped kinetic scheme. Main fractionator, gas processing unit and other process units are designed to simulate real plant data, using a process flow sheet simulator, Aspen PLUS. The custom reactor model was integrated with the process flow sheet simulator to develop an integrated process model.

Keywords: fluid catalytic cracking, simulation, plant data, process design

Procedia PDF Downloads 525

Authors: K. Yahia, A. Titaouine, A. Ghoggal, S. E. Zouzou, F. Benchabane

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), inter-turn short-circuits diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

Procedia PDF Downloads 546

Authors: Tahir Saleem, Mohammad Usman, Nadeem Khan

Abstract:

GPS signals are used for navigation and positioning purposes by a diverse set of users. However, this project intends to utilize the reflected GPS L5 signals for location of target in a region of interest by generating an image that highlights the positions of targets in the area of interest. The principle of bi-static radar is used to detect the targets or any movement or changes. The idea is confirmed by the results obtained during MATLAB simulations. A matched filter based technique is employed in the signal processing to improve the system resolution. The simulation is carried out under different conditions with moving receiver and targets. Noise and attenuation is also induced and atmospheric conditions that affect the direct and reflected GPS signals have been simulated to generate a more practical scenario. A realistic GPS L5 signal has been simulated, the simulation results verify that the detection and imaging of targets is possible by employing reflected GPS using L5 signals and matched filter processing technique with acceptable spatial resolution.

Keywords: GPS, L5 Signal, SAR, spatial resolution

Procedia PDF Downloads 531

Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

Abstract:

Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

Procedia PDF Downloads 183

Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

Abstract:

For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

Procedia PDF Downloads 692