Search results for: computational simulations

Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Due to the competitive market in which companies are currently engaged, the constant changes require companies to react quickly regarding the variability of demand and process. The changes are caused by customers, or by demand fluctuations or variations of products, or the need to serve customers within agreed delivery taking into account the continuous search for quality and competitive prices in products. These changes end up influencing directly or indirectly the activities of the Planning and Production Control (PPC), which does business in strategic, tactical and operational levels of production systems. One area of concern for organizations is in the short term (operational level), because this planning stage any error or divergence will cause waste and impact on the delivery of products on time to customers. Thus, this study aims to optimize the efficiency of production scheduling, using different sequencing strategies in an automotive company. Seeking to aim the proposed objective, we used the computer simulation in conjunction with lean manufacturing to build and validate the current model, and subsequently the creation of future scenarios.

Keywords: computational simulation, lean manufacturing, production scheduling, sequencing strategies

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Authors: G. M. Komaki, S. Mobin, E. Teymourian, S. Sheikh

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This paper addresses minimizing the makespan of the distributed permutation flow shop scheduling problem. In this problem, there are several parallel identical factories or flowshops each with series of similar machines. Each job should be allocated to one of the factories and all of the operations of the jobs should be performed in the allocated factory. This problem has recently gained attention and due to NP-Hard nature of the problem, metaheuristic algorithms have been proposed to tackle it. Majority of the proposed algorithms require large computational time which is the main drawback. In this study, a general variable neighborhood search algorithm (GVNS) is proposed where several time-saving schemes have been incorporated into it. Also, the GVNS uses the sophisticated method to change the shaking procedure or perturbation depending on the progress of the incumbent solution to prevent stagnation of the search. The performance of the proposed algorithm is compared to the state-of-the-art algorithms based on standard benchmark instances.

Keywords: distributed permutation flow shop, scheduling, makespan, general variable neighborhood search algorithm

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Authors: Mohammad Moonesun, Ehsan Asadi Asrami, Julia Bodnarchuk

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In the case of Solar Autonomous Underwater Vehicle, which uses photovoltaic panels to provide its required power, due to limitation of energy, accurate estimation of resistance and energy has major sensitivity. In this work, hydrodynamic calculations by numerical method for a solar autonomous underwater vehicle equipped by two 50 W photovoltaic panels has been studied. To evaluate the required power and energy, hull hydrodynamic resistance in several velocities should be taken into account. To do this assessment, the ANSYS FLUENT 18 applied as Computational Fluid Dynamics (CFD) tool that solves Reynolds Average Navier Stokes (RANS) equations around AUV hull, and K-ω SST is used as turbulence model. To validate of solution method and modeling approach, the model of Myring submarine that it’s experimental data was available, is simulated. There is good agreement between numerical and experimental results. Also, these results showed that the K-ω SST Turbulence model is an ideal method to simulate the AUV motion in low velocities.

Keywords: underwater vehicle, hydrodynamic resistance, numerical modelling, CFD, RANS

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Authors: Sameer Jung Karki, Gokhan Saygili

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The allowable bearing capacity of foundation systems is determined by applying a factor of safety to the ultimate bearing capacity. Conventional ultimate bearing capacity calculations routines are based on deterministic input parameters where the nonuniformity and inhomogeneity of soil and site properties are not accounted for. Hence, the laws of mathematics like probability calculus and statistical analysis cannot be directly applied to foundation engineering. It’s assumed that the Factor of Safety, typically as high as 3.0, incorporates the uncertainty of the input parameters. This factor of safety is estimated based on subjective judgement rather than objective facts. It is an ambiguous term. Hence, a probabilistic analysis of the bearing capacity of an isolated footing on a clayey soil is carried out by using the Monte Carlo Simulation method. This simulated model was compared with the traditional discrete model. It was found out that the bearing capacity of soil was found higher for the simulated model compared with the discrete model. This was verified by doing the sensitivity analysis. As the number of simulations was increased, there was a significant % increase of the bearing capacity compared with discrete bearing capacity. The bearing capacity values obtained by simulation was found to follow a normal distribution. While using the traditional value of Factor of safety 3, the allowable bearing capacity had lower probability (0.03717) of occurring in the field compared to a higher probability (0.15866), while using the simulation derived factor of safety of 1.5. This means the traditional factor of safety is giving us bearing capacity that is less likely occurring/available in the field. This shows the subjective nature of factor of safety, and hence probability method is suggested to address the variability of the input parameters in bearing capacity equations.

Keywords: bearing capacity, factor of safety, isolated footing, montecarlo simulation

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Authors: A. Chateauneuf, M. Mostoufi, D. Vyncke

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Monte Carlo (MC) simulation is a technique that provides approximate solutions to a broad range of mathematical problems. A drawback of the method is its high computational cost, especially in a high-dimensional setting, such as estimating the Tail Value-at-Risk for large portfolios or pricing basket options and Asian options. For these types of problems, one can construct an upper bound in the convex order by replacing the copula by the comonotonic copula. This comonotonic upper bound can be computed very quickly, but it gives only a rough approximation. In this paper we introduce the Comonotonic Monte Carlo (CoMC) simulation, by using the comonotonic approximation as a control variate. The CoMC is of broad applicability and numerical results show a remarkable speed improvement. We illustrate the method for estimating Tail Value-at-Risk and pricing basket options and Asian options when the logreturns follow a Black-Scholes model or a variance gamma model.

Keywords: control variate Monte Carlo, comonotonicity, option pricing, scientific computing

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Authors: P. Haldar, P. Ghosh, S. Ghoshdastidar, K. Kargupta

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In polymer electrolyte membrane fuel cells (PEMFC), the membrane electrode assembly (MEA) is consisting of two platinum coated carbon electrodes, sandwiched with one proton conducting phosphoric acid doped polymeric membrane. Due to low mechanical stability, flooding and fuel cell crossover, application of phosphoric acid in polymeric membrane is very critical. Phosphorous and silica based 3D inorganic gel gains the attention in the field of supercapacitors, fuel cells and metal hydrate batteries due to its thermally stable highly proton conductive behavior. Also as a large amount of water molecule and phosphoric acid can easily get trapped in Si-O-Si network cavities, it causes a prevention in the leaching out. In this study, we have performed molecular dynamics (MD) simulation and first principle calculations to understand the structural, electronics and electrochemical and morphological behavior of this inorganic gel at various P to Si ratios. We have used dipole-dipole interactions, H bonding, and van der Waals forces to study the main interactions between the molecules. A 'structure property-performance' mapping is initiated to determine optimum P to Si ratio for best proton conductivity. We have performed the MD simulations at various temperature to understand the temperature dependency on proton conductivity. The observed results will propose a model which fits well with experimental data and other literature values. We have also studied the mechanism behind proton conductivity. And finally we have proposed a structure for the gel paste with optimum P to Si ratio.

Keywords: first principle calculation, molecular dynamics simulation, phosphorous and silica based 3D inorganic gel, polymer electrolyte membrane fuel cells, proton conductivity

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Authors: A. Q. Ahmed, S. Gao

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In this paper, the energy saving and human thermal comfort in a typical office room are investigated. The impact of a combined system of exhaust inlet air with light slots located at the ceiling level in a room served by displacement ventilation system is numerically modelled. Previous experimental data are used to validate the computational fluid dynamic (CFD) model. A case study of simulated office room includes two seating occupants, two computers, two data loggers and four lamps. The combined system is located at the ceiling level above the heat sources. A new method of calculation for the cooling coil load in stratified air distribution (STRAD) system is used in this study. The results show that 47.4 % energy saving of space cooling load can be achieved by combing the exhaust inlet air with light slots at the ceiling level above the heat sources.

Keywords: air conditioning, displacement ventilation, energy saving, thermal comfort

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Nousheen Hashmi, Shoab Ahmad Khan

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Active collaboration among the green energy sources and the load demand leads to serious issues related to power quality and stability. The growing number of green energy resources and Distributed-Generators need newer strategies to be incorporated for their operations to keep the power energy stability among green energy resources and micro-grid/Utility Grid. This paper presents a novel technique for energy power management in Grid-Connected Photovoltaic with energy storage system under set of constraints including weather conditions, Load Shedding Hours, Peak pricing Hours by using rule-based fuzzy smart grid controller to schedule power coming from multiple Power sources (photovoltaic, grid, battery) under the above set of constraints. The technique fuzzifies all the inputs and establishes fuzzify rule set from fuzzy outputs before defuzzification. Simulations are run for 24 hours period and rule base power scheduler is developed. The proposed fuzzy controller control strategy is able to sense the continuous fluctuations in Photovoltaic power generation, Load Demands, Grid (load Shedding patterns) and Battery State of Charge in order to make correct and quick decisions.The suggested Fuzzy Rule-based scheduler can operate well with vague inputs thus doesn’t not require any exact numerical model and can handle nonlinearity. This technique provides a framework for the extension to handle multiple special cases for optimized working of the system.

Keywords: photovoltaic, power, fuzzy logic, distributed generators, state of charge, load shedding, membership functions

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Authors: Shuen-Tai Wang, Yu-Ching Lin

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With more and more workflow systems adopting cloud as their execution environment, it presents various challenges that need to be addressed in order to be utilized efficiently. This paper introduces a method for resource provisioning based on our previous research of dynamic allocation and its pipeline processes. We present an abstraction for workload scheduling in which independent tasks get scheduled among various available processors of distributed computing for optimization. We also propose an integrated web-based workflow designer by taking advantage of the HTML5 technology and chaining together multiple tools. In order to make the combination of multiple pipelines executing on the cloud in parallel, we develop a script translator and an execution engine for workflow management in the cloud. All information is known in advance by the workflow engine and tasks are allocated according to the prior knowledge in the repository. This proposed effort has the potential to provide support for process definition, workflow enactment and monitoring of workflow processes. Users would benefit from the web-based system that allows creation and execution of pipelines without scripting knowledge.

Keywords: workflow systems, resources provisioning, workload scheduling, web-based, workflow engine

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

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Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: acute hepatitis, medical resource cost, artificial neural network, support vector regression

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Authors: Svilen Dimitrov, Manthan Pancholi, Norbert Schmitz, Didier Stricker

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This paper presents the end-to-end development of a wearable motion sensing harness consisting of computational unit and four inertial measurement units to control three smartphone therapeutic games for children. The inertial data is processed in real time to obtain lower body motion information like knee raises, feet taps and squads. By providing a Wi-Fi connection interface the sensor harness acts wireless remote control for smartphone applications. By performing various lower body movements the users provoke corresponding game state changes. In contrary to the current similar offers, like Nintendo Wii Remote, Xbox Kinect and Playstation Move, this product, consisting of the sensor harness and the applications on top of it, are fully wearable, which means they do not rely on the user to be bound to concrete soft- or hardwareequipped space.

Keywords: wearable harness, inertial measurement units, smartphone therapeutic games, motion tracking, lower-body activity monitoring

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Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Joshue Perez, Javier Araluce

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, the following paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for indepth gesture classification. This tandem of MediaPipe's extraction prowess and MPL's analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System (ROS), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: gesture detection, mediapipe, multiperceptron layer, robot operating system

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Authors: Subhamita Chakraborty, Shubhabrata Datta, Sujay Kumar Mukherjea, Partha Protim Chattopadhyay

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Manufacturing of multiphase high strength steel in hot strip mill have drawn significant attention due to the possibility of forming low temperature transformation product of austenite under continuous cooling condition. In such endeavor, reliable prediction of temperature profile of hot strip coil is essential in order to accesses the evolution of microstructure at different location of hot strip coil, on the basis of corresponding Continuous Cooling Transformation (CCT) diagram. Temperature distribution profile of the hot strip coil has been determined by using finite volume method (FVM) vis-à-vis finite difference method (FDM). It has been demonstrated that FVM offer greater computational reliability in estimation of contact pressure distribution and hence the temperature distribution for curved and irregular profiles, owing to the flexibility in selection of grid geometry and discrete point position, Moreover, use of finite volume concept allows enforcing the conservation of mass, momentum and energy, leading to enhanced accuracy of prediction.

Keywords: simulation, modeling, thermal analysis, coil cooling, contact pressure, finite volume method

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Authors: Ronald Collins, Jonathon Coleman, Joel Dasari, George Holt, Carl Metelko, Matthew Murdoch, Alexander Morgan, Yan-Jie Schnellbach, Robert Mills, Gareth Edwards, Alexander Roberts

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At the Wylfa Magnox Power Plant between 2014–2016, the VIDARR prototype anti-neutrino detector was deployed. It is comprised of extruded plastic scintillating bars measuring 4 cm × 1 cm × 152 cm and utilised wavelength shifting fibres (WLS) and multi-pixel photon counters (MPPCs) to detect and quantify radiation. During deployment, it took cosmic muon data in accidental coincidence with the anti-neutrino measurements with the power plant site buildings obscuring the muon sky. Cosmic muons have a significantly higher probability of being attenuated and/or absorbed by denser objects, and so one-sided cosmic muon tomography was utilised to image the reactor site buildings. In order to achieve clear building outlines, a control data set was taken at the University of Liverpool from 2016 – 2018, which had minimal occlusion of the cosmic muon flux by dense objects. By taking the ratio of these two data sets and using GEANT4 simulations, it is possible to perform a one-sided cosmic muon tomography analysis. This analysis can be used to discern specific buildings, building heights, and features at the Wylfa reactor site, including the reactor core/reactor core shielding using ∼ 3 hours worth of cosmic-ray detector live time. This result demonstrates the feasibility of using cosmic muon analysis to determine a segmented detector’s location with respect to surrounding buildings, assisted by aerial photography or satellite imagery.

Keywords: anti-neutrino, GEANT4, muon, tomography, occlusion

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Authors: Leila Jafari, Viliam Makis, G. B. Akram Khaleghei

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In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1, which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM, has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed and illustrated by a numerical example.

Keywords: condition-based maintenance, semi-Markov decision process, multivariate Bayesian control chart, partially observable system, two-unit system

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Authors: Mohan Ramasundaram, Amutha Prabakar Muniyandi

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Remote user authentication is one of the important tasks for any kind of remote server applications. Several remote authentication schemes are proposed by the researcher for Telecare Medicine Information System (TMIS). Most of the existing techniques have limitations, vulnerable to various kind attacks, lack of functionalities, information leakage, no perfect forward security and ineffectiveness. Authentication is a process of user verification mechanism for allows him to access the resources of a server. Nowadays, most of the remote authentication protocols are using two-factor authentications. We have made a survey of several remote authentication schemes using three factors and this survey shows that the most of the schemes are inefficient and subject to several attacks. We observed from the experimental evaluation; the proposed scheme is very secure against various known attacks that include replay attack, man-in-the-middle attack. Furthermore, the analysis based on the communication cost and computational cost estimation of the proposed scheme with related schemes shows that our proposed scheme is efficient.

Keywords: Telecare Medicine Information System, elliptic curve cryptography, three-factor, biometric, random oracle

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Authors: Kizito Ugochukwu Nwajeri

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This paper presents a distinct approach to solving fractional dynamical systems using hybrid block methods (HBMs). Fractional calculus extends the concept of derivatives and integrals to non-integer orders and finds increasing application in fields such as physics, engineering, and finance. However, traditional numerical techniques often struggle to accurately capture the complex behaviors exhibited by these systems. To address this challenge, we develop HBMs that integrate single-step and multi-step methods, enabling the simultaneous computation of multiple solution points while maintaining high accuracy. Our approach employs polynomial interpolation and collocation techniques to derive a system of equations that effectively models the dynamics of fractional systems. We also directly incorporate boundary and initial conditions into the formulation, enhancing the stability and convergence properties of the numerical solution. An adaptive step-size mechanism is introduced to optimize performance based on the local behavior of the solution. Extensive numerical simulations are conducted to evaluate the proposed methods, demonstrating significant improvements in accuracy and efficiency compared to traditional numerical approaches. The results indicate that our hybrid block methods are robust and versatile, making them suitable for a wide range of applications involving fractional dynamical systems. This work contributes to the existing literature by providing an effective numerical framework for analyzing complex behaviors in fractional systems, thereby opening new avenues for research and practical implementation across various disciplines.

Keywords: fractional calculus, numerical simulation, stability and convergence, Adaptive step-size mechanism, collocation methods

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Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

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Authors: Mohd Ritzman Abdul Karim, Zhaohui Huang

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A current focus in seismic engineering practice is the development of seismic design approach that focuses on the performance-based design. Performance-based design aims to design the structures to achieve specified performance based on the damage limit states. This damage limit is more restrictive limit than life safety and needs to be carefully estimated to avoid damage in piers due to failure in transverse reinforcement. In this paper, a different perspective of damage limit states has been explored by integrating two damage control material limit state, concrete and reinforcement by introduced parameters such as expected yield stress of transverse reinforcement where peak tension strain prior to bar buckling is introduced in a recent study. The different perspective of damage limit states with modified yield displacement and the modified plastic-hinge length is used in order to predict damage-control target displacement for reinforced concreate (RC) bridge pier. Three-dimensional (3D) finite element (FE) model has been developed for estimating damage target displacement to validate proposed damage limit states. The result from 3D FE analysis was validated with experimental study found in the literature. The validated model then was applied to predict the damage target displacement for RC bridge pier and to validate the proposed study. The tensile strain on reinforcement and compression on concrete were used to determine the predicted damage target displacement and compared with the proposed study. The result shows that the proposed damage limit states were efficient in predicting damage-control target displacement consistent with FE simulations.

Keywords: damage-control target displacement, damage limit states, reinforced concrete bridge pier, yield displacement

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Authors: Lina Wu, Ye Li

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An equivalent relation between a harmonic form and a closed co-closed form is established on a complete non-compact manifold. This equivalence has been generalized for a differential k-form ω from Lq spaces to non-Lq spaces when q=2 in the context of p-balanced growth where p=2. Especially for a simple differential k-form on a complete non-compact manifold, the equivalent relation has been verified with the extended scope of q for from finite q-energy in Lq spaces to infinite q-energy in non-Lq spaces when with 2-balanced growth. Generalized Hadamard Theorem, Cauchy-Schwarz Inequality, and Calculus skills including Integration by Parts as well as Convergent Series have been applied as estimation techniques to evaluate growth rates for a differential form. In particular, energy growth rates as indicated by an appropriate power range in a selected test function lead to a balance between a harmonic differential form and a closed co-closed differential form. Research ideas and computational methods in this paper could provide an innovative way in the study of broadening Lq spaces to non-Lq spaces with a wide variety of infinite energy growth for a differential form.

Keywords: closed forms, co-closed forms, harmonic forms, L^q spaces, p-balanced growth, simple differential k-forms

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Authors: Shiliang Wu, Huanxin Zhang

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Mercury has been well-known for its negative effects on wildlife, public health as well as the ecosystem. Once emitted into atmosphere, mercury can be transformed into different forms or enter the ecosystem through dry deposition or wet deposition. Some fraction of the mercury will be reemitted back into the atmosphere and be subject to the same cycle. In addition, the relatively long lifetime of elemental mercury in the atmosphere enables it to be transported long distances from source regions to receptor regions. Global change such as climate change and land use/land cover change impose significant challenges for mercury pollution control besides the efforts to regulate mercury anthropogenic emissions. In this study, we use a global chemical transport model (GEOS-Chem) to examine the potential impacts from changes in climate and land use/land cover on the global budget of mercury as well as its atmospheric transport, chemical transformation, and deposition. We carry out a suite of sensitivity model simulations to separate the impacts on atmospheric mercury associated with changes in climate and land use/land cover. Both climate change and land use/land cover change are found to have significant impacts on global mercury budget but through different pathways. Land use/land cover change primarily increase mercury dry deposition in northern mid-latitudes over continental regions and central Africa. Climate change enhances the mobilization of mercury from soil and ocean reservoir to the atmosphere. Also, dry deposition is enhanced over most continental areas while a change in future precipitation dominates the change in mercury wet deposition. We find that 2000-2050 climate change could increase the global atmospheric burden of mercury by 5% and mercury deposition by up to 40% in some regions. Changes in land use and land cover also increase mercury deposition over some continental regions, by up to 40%. The change in the lifetime of atmospheric mercury has important implications for long-range transport of mercury. Our case study shows that changes in climate and land use and cover could significantly affect the source-receptor relationships for mercury.

Keywords: mercury, toxic pollutant, atmospheric transport, deposition, climate change

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Authors: Ranjit Biswas

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The existing subject Algebra is incomplete to support mathematical computations being done by scientists of all areas: Mathematics, Physics, Statistics, Chemistry, Space Science, Cosmology etc. even starting from the era of great Einstein. A huge hidden gap in the subject ‘Algebra’ is unearthed. All the scientists today, including mathematicians, physicists, chemists, statisticians, cosmologists, space scientists, and economists, even starting from the great Einstein, are lucky that they got results without facing any contradictions or without facing computational errors. Most surprising is that the results of all scientists, including Nobel Prize winners, were proved by them by doing experiments too. But in this paper, it is rigorously justified that they all are lucky. An algebraist can define an infinite number of new algebraic structures. The objective of the work in this paper is not just for the sake of defining a distinct algebraic structure, but to recognize and identify a major gap of the subject ‘Algebra’ lying hidden so far in the existing vast literature of it. The objective of this work is to fix the unearthed gap. Consequently, a different algebraic structure called ‘Region’ has been introduced, and its properties are studied.

Keywords: region, ROR, RORR, region algebra

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Authors: Jingde Li, Hong Hao

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Recent oil and gas accidents have reminded us the severe consequences of gas explosion on structure damage and financial loss. In order to protect the structures and personnel, engineers and researchers have been working on numerous different explosion mitigation methods. Amongst, venting is the most economical approach to mitigate gas explosion overpressure. In this paper, venting is used as the overpressure alleviation method. A theoretical method and a numerical technique are presented to predict the internal and external pressure from vented gas explosion in a large enclosure. Under idealized conditions, a number of experiments are used to calibrate the accuracy of the theoretically calculated data. A good agreement between the theoretical results and experimental data is seen. However, for realistic scenarios, the theoretical method over-estimates internal pressures and is incapable of predicting external pressures. Therefore, a CFD simulation procedure is proposed in this study to estimate both the internal and external overpressure from a large-scale vented explosion. Satisfactory agreement between CFD simulation results and experimental data is achieved.

Keywords: vented gas explosion, internal pressure, external pressure, CFD simulation, FLACS, ANSYS Fluent

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Authors: Kazumasa Kitazono, Hiroshi Fukuoka, Nao Kuniyoshi, Minoru Yaga, Eri Ueno, Naoaki Fukuda, Toshio Takiya

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The unsteady supersonic jet formed by a shock tube with a small high-pressure chamber was used as a simple alternative model for pulsed laser ablation. Understanding the vortex ring formed by the shock wave is crucial in clarifying the behavior of unsteady supersonic jet discharged from an elliptical cell. Therefore, this study investigated the behavior of vortex rings and a jet. The experiment and numerical calculation were conducted using the schlieren method and by solving the axisymmetric two-dimensional compressible Navier–Stokes equations, respectively. In both, the calculation and the experiment, laser ablation is conducted for a certain duration, followed by discharge through the exit. Moreover, a parametric study was performed to demonstrate the effect of pressure ratio on the interaction among vortex rings and the supersonic jet. The interaction between the supersonic jet and the vortex rings increased the velocity of the supersonic jet up to the magnitude of the velocity at the center of the vortex rings. The interaction between the vortex rings increased the velocity at the center of the vortex ring.

Keywords: computational fluid dynamics, shock-wave, unsteady jet, vortex ring

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

Procedia PDF Downloads 128

Authors: Abdurrahim Bolukbasi, Hassan Athari, Dogan Ciloglu

Abstract:

The modeling lung respiratory system which has complex anatomy and biophysics presents several challenges including tissue-driven flow patterns and wall motion. Also, the lung pulmonary system because of that they stretch and recoil with each breath, has not static walls and structures. The direct relationship between air flow and tissue motion in the lung structures naturally prefers an FSI simulation technique. Therefore, in order to toward the realistic simulation of pulmonary breathing mechanics the development of a coupled FSI computational model is an important step. A simple but physiologically-relevant three dimensional deep long geometry is designed and fluid-structure interaction (FSI) coupling technique is utilized for simulating the deformation of the lung parenchyma tissue which produces airflow fields. The real understanding of respiratory tissue system as a complex phenomenon have been investigated with respect to respiratory patterns, fluid dynamics and tissue visco-elasticity and tidal breathing period.

Keywords: lung deformation and mechanics; Tissue mechanics; Viscoelasticity; Fluid-structure interactions; ANSYS

Procedia PDF Downloads 321

Authors: A. Ghanbari Mardasi, N. Wu, C. Wu

Abstract:

In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.

Keywords: edge effect, scale optimization, small crack locating, spatial wavelet

Procedia PDF Downloads 356