Search results for: computational grid
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2906

Search results for: computational grid

1796 Heat Transfer and Diffusion Modelling

Authors: R. Whalley

Abstract:

The heat transfer modelling for a diffusion process will be considered. Difficulties in computing the time-distance dynamics of the representation will be addressed. Incomplete and irrational Laplace function will be identified as the computational issue. Alternative approaches to the response evaluation process will be provided. An illustration application problem will be presented. Graphical results confirming the theoretical procedures employed will be provided.

Keywords: heat, transfer, diffusion, modelling, computation

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1795 Crop Leaf Area Index (LAI) Inversion and Scale Effect Analysis from Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Data

Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

Abstract:

Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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1794 Experimental Analysis of Control in Electric Vehicle Charging Station Based Grid Tied Photovoltaic-Battery System

Authors: A. Hassoune, M. Khafallah, A. Mesbahi, T. Bouragba

Abstract:

This work presents an improved strategy of control for charging a lithium-ion battery in an electric vehicle charging station using two charger topologies i.e. single ended primary inductor converter (SEPIC) and forward converter. In terms of rapidity and accuracy, the power system consists of a topology/control diagram that would overcome the performance constraints, for instance the power instability, the battery overloading and how the energy conversion blocks would react efficiently to any kind of perturbations. Simulation results show the effectiveness of the proposed topologies operated with a power management algorithm based on voltage/peak current mode controls. In order to provide credible findings, a low power prototype is developed to test the control strategy via experimental evaluations of the converter topology and its controls.

Keywords: battery storage buffer, charging station, electric vehicle, experimental analysis, management algorithm, switches control

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1793 Wind Resource Classification and Feasibility of Distributed Generation for Rural Community Utilization in North Central Nigeria

Authors: O. D. Ohijeagbon, Oluseyi O. Ajayi, M. Ogbonnaya, Ahmeh Attabo

Abstract:

This study analyzed the electricity generation potential from wind at seven sites spread across seven states of the North-Central region of Nigeria. Twenty-one years (1987 to 2007) wind speed data at a height of 10m were assessed from the Nigeria Meteorological Department, Oshodi. The data were subjected to different statistical tests and also compared with the two-parameter Weibull probability density function. The outcome shows that the monthly average wind speeds ranged between 2.2 m/s in November for Bida and 10.1 m/s in December for Jos. The yearly average ranged between 2.1m/s in 1987 for Bida and 11.8 m/s in 2002 for Jos. Also, the power density for each site was determined to range between 29.66 W/m2 for Bida and 864.96 W/m2 for Jos, Two parameters (k and c) of the Weibull distribution were found to range between 2.3 in Lokoja and 6.5 in Jos for k, while c ranged between 2.9 in Bida and 9.9m/s in Jos. These outcomes points to the fact that wind speeds at Jos, Minna, Ilorin, Makurdi and Abuja are compatible with the cut-in speeds of modern wind turbines and hence, may be economically feasible for wind-to-electricity at and above the height of 10 m. The study further assessed the potential and economic viability of standalone wind generation systems for off-grid rural communities located in each of the studied sites. A specific electric load profile was developed to suite hypothetic communities, each consisting of 200 homes, a school and a community health center. Assessment of the design that will optimally meet the daily load demand with a loss of load probability (LOLP) of 0.01 was performed, considering 2 stand-alone applications of wind and diesel. The diesel standalone system (DSS) was taken as the basis of comparison since the experimental locations have no connection to a distribution network. The HOMER® software optimizing tool was utilized to determine the optimal combination of system components that will yield the lowest life cycle cost. Sequel to the analysis for rural community utilization, a Distributed Generation (DG) analysis that considered the possibility of generating wind power in the MW range in order to take advantage of Nigeria’s tariff regime for embedded generation was carried out for each site. The DG design incorporated each community of 200 homes, freely catered for and offset from the excess electrical energy generated above the minimum requirement for sales to a nearby distribution grid. Wind DG systems were found suitable and viable in producing environmentally friendly energy in terms of life cycle cost and levelised value of producing energy at Jos ($0.14/kWh), Minna ($0.12/kWh), Ilorin ($0.09/kWh), Makurdi ($0.09/kWh), and Abuja ($0.04/kWh) at a particluar turbine hub height. These outputs reveal the value retrievable from the project after breakeven point as a function of energy consumed Based on the results, the study demonstrated that including renewable energy in the rural development plan will enhance fast upgrade of the rural communities.

Keywords: wind speed, wind power, distributed generation, cost per kilowatt-hour, clean energy, North-Central Nigeria

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1792 Computational Fluid Dynamics Simulation on Heat Transfer of Hot Air Bubble Injection into Water Column

Authors: Jae-Yeong Choi, Gyu-Mok Jeon, Jong-Chun Park, Yong-Jin Cho, Seok-Tae Yoon

Abstract:

When air flow is injected into water, bubbles are formed in various types inside the water pool along with the air flow rate. The bubbles are floated in equilibrium with forces such as buoyancy, surface tension and shear force. Single bubble generated at low flow rate maintains shape, but bubbles with high flow rate break up to make mixing and turbulence. In addition to this phenomenon, as the hot air bubbles are injected into the water, heat affects the interface of phases. Therefore, the main scope of the present work reveals how to proceed heat transfer between water and hot air bubbles injected into water. In the present study, a series of CFD simulation for the heat transfer of hot bubbles injected through a nozzle near the bottom in a cylindrical water column are performed using a commercial CFD software, STAR-CCM+. The governing equations for incompressible and viscous flow are the continuous and the RaNS (Reynolds- averaged Navier-Stokes) equations and discretized by the FVM (Finite Volume Method) manner. For solving multi-phase flow, the Eulerian multiphase model is employed and the interface is defined by VOF (Volume-of-Fluid) technique. As a turbulence model, the SST k-w model considering the buoyancy effects is introduced. For spatial differencing the 3th-order MUSCL scheme is adopted and the 2nd-order implicit scheme for time integration. As the results, the dynamic behavior of the rising hot bubbles with the flow rate injected and regarding heat transfer mechanism are discussed based on the simulation results.

Keywords: heat transfer, hot bubble injection, eulerian multiphase model, flow rate, CFD (Computational Fluid Dynamics)

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1791 The Effectiveness of Multiphase Flow in Well- Control Operations

Authors: Ahmed Borg, Elsa Aristodemou, Attia Attia

Abstract:

Well control involves managing the circulating drilling fluid within the wells and avoiding kicks and blowouts as these can lead to losses in human life and drilling facilities. Current practices for good control incorporate predictions of pressure losses through computational models. Developing a realistic hydraulic model for a good control problem is a very complicated process due to the existence of a complex multiphase region, which usually contains a non-Newtonian drilling fluid and the miscibility of formation gas in drilling fluid. The current approaches assume an inaccurate flow fluid model within the well, which leads to incorrect pressure loss calculations. To overcome this problem, researchers have been considering the more complex two-phase fluid flow models. However, even these more sophisticated two-phase models are unsuitable for applications where pressure dynamics are important, such as in managed pressure drilling. This study aims to develop and implement new fluid flow models that take into consideration the miscibility of fluids as well as their non-Newtonian properties for enabling realistic kick treatment. furthermore, a corresponding numerical solution method is built with an enriched data bank. The research work considers and implements models that take into consideration the effect of two phases in kick treatment for well control in conventional drilling. In this work, a corresponding numerical solution method is built with an enriched data bank. Software STARCCM+ for the computational studies to study the important parameters to describe wellbore multiphase flow, the mass flow rate, volumetric fraction, and velocity of each phase. Results showed that based on the analysis of these simulation studies, a coarser full-scale model of the wellbore, including chemical modeling established. The focus of the investigations was put on the near drill bit section. This inflow area shows certain characteristics that are dominated by the inflow conditions of the gas as well as by the configuration of the mud stream entering the annulus. Without considering the gas solubility effect, the bottom hole pressure could be underestimated by 4.2%, while the bottom hole temperature is overestimated by 3.2%. and without considering the heat transfer effect, the bottom hole pressure could be overestimated by 11.4% under steady flow conditions. Besides, larger reservoir pressure leads to a larger gas fraction in the wellbore. However, reservoir pressure has a minor effect on the steady wellbore temperature. Also as choke pressure increases, less gas will exist in the annulus in the form of free gas.

Keywords: multiphase flow, well- control, STARCCM+, petroleum engineering and gas technology, computational fluid dynamic

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1790 Evaluating the Methods of Retrofitting and Renovating of the Masonry Schools

Authors: Navid Khayat

Abstract:

This study investigates the retrofitting of schools in Ahvaz City. Three schools, namely, Enghelab, Sherafat, and Golchehreh, in Ahvaz City are initially examined through Schmidt hammer and ultrasonic tests. Given the tests and controls on the structures of these schools, the methods are presented for their reconstruction. The plan is presented for each school by estimating the cost and generally the feasibility and estimated the duration of project reconstruction. After reconstruction, the mentioned tests are re-performed for rebuilt parts and the results indicate a significant improvement in performance of structure because of reconstruction. According to the results, despite the fact that the use of fiber reinforced polymers (FRP) for structure retrofitting is costly, due to the low executive costs and also other benefits of FRP, it is generally considered as one of the most effective ways of retrofitting. Building the concrete coating on walls is another effective method in retrofitting the buildings. According to this method, a grid of horizontal and vertical bars is installed on the wall and then the concrete is poured on it. The use of concrete coating on the concrete and brick structures leads to the useful results and the experience indicates that the poured concrete filled the joints well and provides the appropriate binding and adhesion.

Keywords: renovation, retrofitting, masonry structures, old school

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1789 Artificial Intelligent Methodology for Liquid Propellant Engine Design Optimization

Authors: Hassan Naseh, Javad Roozgard

Abstract:

This paper represents the methodology based on Artificial Intelligent (AI) applied to Liquid Propellant Engine (LPE) optimization. The AI methodology utilized from Adaptive neural Fuzzy Inference System (ANFIS). In this methodology, the optimum objective function means to achieve maximum performance (specific impulse). The independent design variables in ANFIS modeling are combustion chamber pressure and temperature and oxidizer to fuel ratio and output of this modeling are specific impulse that can be applied with other objective functions in LPE design optimization. To this end, the LPE’s parameter has been modeled in ANFIS methodology based on generating fuzzy inference system structure by using grid partitioning, subtractive clustering and Fuzzy C-Means (FCM) clustering for both inferences (Mamdani and Sugeno) and various types of membership functions. The final comparing optimization results shown accuracy and processing run time of the Gaussian ANFIS Methodology between all methods.

Keywords: ANFIS methodology, artificial intelligent, liquid propellant engine, optimization

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1788 Modeling and Simulation of a Hybrid System Solar Panel and Wind Turbine in the Quingeo Heritage Center in Ecuador

Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

Abstract:

In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador

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1787 Instability Index Method and Logistic Regression to Assess Landslide Susceptibility in County Route 89, Taiwan

Authors: Y. H. Wu, Ji-Yuan Lin, Yu-Ming Liou

Abstract:

This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future.

Keywords: instability index method, logistic regression, landslide susceptibility, SRC curve

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1786 Demand Response from Residential Air Conditioning Load Using a Programmable Communication Thermostat

Authors: Saurabh Chanana, Monika Arora

Abstract:

Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand.

Keywords: demand response, home energy management, programmable communicating thermostat, thermostatically controlled appliances

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1785 An Intelligent Search and Retrieval System for Mining Clinical Data Repositories Based on Computational Imaging Markers and Genomic Expression Signatures for Investigative Research and Decision Support

Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

Abstract:

The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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1784 LES Investigation of the Natural Vortex Length in a Small-Scale Gas Cyclone

Authors: Dzmitry Misiulia, Sergiy Antonyuk

Abstract:

Small-scale cyclone separators are widely used in aerosol sampling. The flow field in a cyclone sampler is very complex, especially the vortex behavior. Most of the existing models for calculating cyclone efficiency use the same stable vortex structure while the vortex demonstrates dynamic variations rather than the steady-state picture. It can spontaneously ‘end’ at some point within the body of the separator. Natural vortex length is one of the most critical issues when designing and operating gas cyclones and is crucial to proper cyclone performance. The particle transport along the wall to the grid pot is not effective beyond this point. The flow field and vortex behavior inside the aerosol sampler have been investigated for a wide range of Reynolds numbers using Large Eddy Simulations. Two characteristics types of vortex behavior have been found with simulations. At low flow rates the vortex created in the cyclone dissipates in free space (without attaching to a surface) while at higher flow rates it attaches to the cyclone wall. The effects of the Reynolds number on the natural vortex length and the rotation frequency of the end of the vortex have been revealed.

Keywords: cyclone, flow field, natural vortex length, pressure drop

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1783 Comparative Analysis of Sigmoidal Feedforward Artificial Neural Networks and Radial Basis Function Networks Approach for Localization in Wireless Sensor Networks

Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy

Abstract:

With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m2 grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.

Keywords: localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI, GPS

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1782 Temperature Distribution Inside Hybrid photovoltaic-Thermoelectric Generator Systems and their Dependency on Exposition Angles

Authors: Slawomir Wnuk

Abstract:

Due to widespread implementation of the renewable energy development programs the, solar energy use increasing constantlyacross the world. Accordingly to REN21, in 2020, both on-grid and off-grid solar photovoltaic systems installed capacity reached 760 GWDCand increased by 139 GWDC compared to previous year capacity. However, the photovoltaic solar cells used for primary solar energy conversion into electrical energy has exhibited significant drawbacks. The fundamentaldownside is unstable andlow efficiencythe energy conversion being negatively affected by a rangeof factors. To neutralise or minimise the impact of those factors causing energy losses, researchers have come out withvariedideas. One ofpromising technological solutionsoffered by researchers is PV-MTEG multilayer hybrid system combiningboth photovoltaic cells and thermoelectric generators advantages. A series of experiments was performed on Glasgow Caledonian University laboratory to investigate such a system in operation. In the experiments, the solar simulator Sol3A series was employed as a stable solar irradiation source, and multichannel voltage and temperature data loggers were utilised for measurements. The two layer proposed hybrid systemsimulation model was built up and tested for its energy conversion capability under a variety of the exposure angles to the solar irradiation with a concurrent examination of the temperature distribution inside proposed PV-MTEG structure. The same series of laboratory tests were carried out for a range of various loads, with the temperature and voltage generated being measured and recordedfor each exposure angle and load combination. It was found that increase of the exposure angle of the PV-MTEG structure to an irradiation source causes the decrease of the temperature gradient ΔT between the system layers as well as reduces overall system heating. The temperature gradient’s reduction influences negatively the voltage generation process. The experiments showed that for the exposureangles in the range from 0° to 45°, the ‘generated voltage – exposure angle’ dependence is reflected closely by the linear characteristics. It was also found that the voltage generated by MTEG structures working with the optimal load determined and applied would drop by approximately 0.82% per each 1° degree of the exposure angle increase. This voltage drop occurs at the higher loads applied, getting more steep with increasing the load over the optimal value, however, the difference isn’t significant. Despite of linear character of the generated by MTEG voltage-angle dependence, the temperature reduction between the system structure layers andat tested points on its surface was not linear. In conclusion, the PV-MTEG exposure angle appears to be important parameter affecting efficiency of the energy generation by thermo-electrical generators incorporated inside those hybrid structures. The research revealedgreat potential of the proposed hybrid system. The experiments indicated interesting behaviour of the tested structures, and the results appear to provide valuable contribution into thedevelopment and technological design process for large energy conversion systems utilising similar structural solutions.

Keywords: photovoltaic solar systems, hybrid systems, thermo-electrical generators, renewable energy

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1781 Biomechanical Performance of the Synovial Capsule of the Glenohumeral Joint with a BANKART Lesion through Finite Element Analysis

Authors: Duvert A. Puentes T., Javier A. Maldonado E., Ivan Quintero., Diego F. Villegas

Abstract:

Mechanical Computation is a great tool to study the performance of complex models. An example of it is the study of the human body structure. This paper took advantage of different types of software to make a 3D model of the glenohumeral joint and apply a finite element analysis. The main objective was to study the change in the biomechanical properties of the joint when it presents an injury. Specifically, a BANKART lesion, which consists in the detachment of the anteroinferior labrum from the glenoid. Stress and strain distribution of the soft tissues were the focus of this study. First, a 3D model was made of a joint without any pathology, as a control sample, using segmentation software for the bones with the support of medical imagery and a cadaveric model to represent the soft tissue. The joint was built to simulate a compression and external rotation test using CAD to prepare the model in the adequate position. When the healthy model was finished, it was submitted to a finite element analysis and the results were validated with experimental model data. With the validated model, it was sensitized to obtain the best mesh measurement. Finally, the geometry of the 3D model was changed to imitate a BANKART lesion. Then, the contact zone of the glenoid with the labrum was slightly separated simulating a tissue detachment. With this new geometry, the finite element analysis was applied again, and the results were compared with the control sample created initially. With the data gathered, this study can be used to improve understanding of the labrum tears. Nevertheless, it is important to remember that the computational analysis are approximations and the initial data was taken from an in vitro assay.

Keywords: biomechanics, computational model, finite elements, glenohumeral joint, bankart lesion, labrum

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1780 Aiming at Optimization of Tracking Technology through Seasonally Tilted Sun Trackers: An Indian Perspective

Authors: Sanjoy Mukherjee

Abstract:

Discussions on concepts of Single Axis Tracker (SAT) are becoming more and more apt for developing countries like India not just as an advancement in racking technology but due to the utmost necessity of reaching at the lowest Levelized Cost of Energy (LCOE) targets. With this increasing competition and significant fall in feed-in tariffs of solar PV projects, developers are under constant pressure to secure investment for their projects and eventually earn profits from them. Moreover, being the second largest populated country, India suffers from scarcity of land because of higher average population density. So, to mitigate the risk of this dual edged sword with reducing trend of unit (kWh) cost at one side and utilization of land on the other, tracking evolved as the call of the hour. Therefore, the prime objectives of this paper are not only to showcase how STT proves to be an effective mechanism to get more gain in Global Incidence in collector plane (Ginc) with respect to traditional mounting systems but also to introduce Seasonally Tilted Tracker (STT) technology as a possible option for high latitude locations.

Keywords: tracking system, grid connected solar PV plant, CAPEX reduction, levelized cost of energy

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1779 Solving a Micromouse Maze Using an Ant-Inspired Algorithm

Authors: Rolando Barradas, Salviano Soares, António Valente, José Alberto Lencastre, Paulo Oliveira

Abstract:

This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding.

Keywords: nature inspired algorithms, scratch, micromouse, problem-solving, computational thinking

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1778 Nonlinear Aerodynamic Parameter Estimation of a Supersonic Air to Air Missile by Using Artificial Neural Networks

Authors: Tugba Bayoglu

Abstract:

Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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1777 Optimal Sizes of Energy Storage for Economic Operation Management

Authors: Rohalla Moghimi, Sirus Mohammadi

Abstract:

Batteries for storage of electricity from solar and wind generation farms are a key element in the success of sustainability. In recent years, due to large integration of Renewable Energy Sources (RESs) like wind turbine and photovoltaic unit into the Micro-Grid (MG), the necessity of Battery Energy Storage (BES) has increased dramatically. The BES has several benefits and advantages in the MG-based applications such as short term power supply, power quality improvement, facilitating integration of RES, ancillary service and arbitrage. This paper presents the cost-based formulation to determine the optimal size of the BES in the operation management of MG. Also, some restrictions, i.e. power capacity of Distributed Generators (DGs), power and energy capacity of BES, charge/discharge efficiency of BES, operating reserve and load demand satisfaction should be considered as well. In this paper, a methodology is proposed for the optimal allocation and economic analysis of ESS in MGs on the basis of net present value (NPV). As the optimal operation of an MG strongly depends on the arrangement and allocation of its ESS, economic operation strategies and optimal allocation methods of the ESS devices are required for the MG.

Keywords: microgrid, energy storage system, optimal sizing, net present value

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1776 Load Management Using Multiple Sequential Load Shaping Techniques

Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

Abstract:

Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

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1775 On the Solution of Boundary Value Problems Blended with Hybrid Block Methods

Authors: Kizito Ugochukwu Nwajeri

Abstract:

This paper explores the application of hybrid block methods for solving boundary value problems (BVPs), which are prevalent in various fields such as science, engineering, and applied mathematics. Traditionally, numerical approaches such as finite difference and shooting methods, often encounter challenges related to stability and convergence, particularly in the context of complex and nonlinear BVPs. To address these challenges, we propose a hybrid block method that integrates features from both single-step and multi-step techniques. This method allows for the simultaneous computation of multiple solution points while maintaining high accuracy. Specifically, we employ a combination of polynomial interpolation and collocation strategies to derive a system of equations that captures the behavior of the solution across the entire domain. By directly incorporating boundary conditions into the formulation, we enhance the stability and convergence properties of the numerical solution. Furthermore, we introduce an adaptive step-size mechanism to optimize performance based on the local behavior of the solution. This adjustment allows the method to respond effectively to variations in solution behavior, improving both accuracy and computational efficiency. Numerical tests on a variety of boundary value problems demonstrate the effectiveness of the hybrid block methods. These tests showcase significant improvements in accuracy and computational efficiency compared to conventional methods, indicating that our approach is robust and versatile. The results suggest that this hybrid block method is suitable for a wide range of applications in real-world problems, offering a promising alternative to existing numerical techniques.

Keywords: hybrid block methods, boundary value problem, polynomial interpolation, adaptive step-size control, collocation methods

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1774 Performences of Type-2 Fuzzy Logic Control and Neuro-Fuzzy Control Based on DPC for Grid Connected DFIG with Fixed Switching Frequency

Authors: Fayssal Amrane, Azeddine Chaiba

Abstract:

In this paper, type-2 fuzzy logic control (T2FLC) and neuro-fuzzy control (NFC) for a doubly fed induction generator (DFIG) based on direct power control (DPC) with a fixed switching frequency is proposed for wind generation application. First, a mathematical model of the doubly-fed induction generator implemented in d-q reference frame is achieved. Then, a DPC algorithm approach for controlling active and reactive power of DFIG via fixed switching frequency is incorporated using PID. The performance of T2FLC and NFC, which is based on the DPC algorithm, are investigated and compared to those obtained from the PID controller. Finally, simulation results demonstrate that the NFC is more robust, superior dynamic performance for wind power generation system applications.

Keywords: doubly fed induction generator (DFIG), direct power control (DPC), neuro-fuzzy control (NFC), maximum power point tracking (MPPT), space vector modulation (SVM), type 2 fuzzy logic control (T2FLC)

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1773 Relation between Physical and Mechanical Properties of Concrete Paving Stones Using Neuro-Fuzzy Approach

Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

Abstract:

This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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1772 Patient-Specific Design Optimization of Cardiovascular Grafts

Authors: Pegah Ebrahimi, Farshad Oveissi, Iman Manavi-Tehrani, Sina Naficy, David F. Fletcher, Fariba Dehghani, David S. Winlaw

Abstract:

Despite advances in modern surgery, congenital heart disease remains a medical challenge and a major cause of infant mortality. Cardiovascular prostheses are routinely used in surgical procedures to address congenital malformations, for example establishing a pathway from the right ventricle to the pulmonary arteries in pulmonary valvar atresia. Current off-the-shelf options including human and adult products have limited biocompatibility and durability, and their fixed size necessitates multiple subsequent operations to upsize the conduit to match with patients’ growth over their lifetime. Non-physiological blood flow is another major problem, reducing the longevity of these prostheses. These limitations call for better designs that take into account the hemodynamical and anatomical characteristics of different patients. We have integrated tissue engineering techniques with modern medical imaging and image processing tools along with mathematical modeling to optimize the design of cardiovascular grafts in a patient-specific manner. Computational Fluid Dynamics (CFD) analysis is done according to models constructed from each individual patient’s data. This allows for improved geometrical design and achieving better hemodynamic performance. Tissue engineering strives to provide a material that grows with the patient and mimic the durability and elasticity of the native tissue. Simulations also give insight on the performance of the tissues produced in our lab and reduce the need for costly and time-consuming methods of evaluation of the grafts. We are also developing a methodology for the fabrication of the optimized designs.

Keywords: computational fluid dynamics, cardiovascular grafts, design optimization, tissue engineering

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1771 Neural Network Approach for Solving Integral Equations

Authors: Bhavini Pandya

Abstract:

This paper considers Hη: T2 → T2 the Perturbed Cerbelli-Giona map. That is a family of 2-dimensional nonlinear area-preserving transformations on the torus T2=[0,1]×[0,1]= ℝ2/ ℤ2. A single parameter η varies between 0 and 1, taking the transformation from a hyperbolic toral automorphism to the “Cerbelli-Giona” map, a system known to exhibit multifractal properties. Here we study the multifractal properties of the family of maps. We apply a box-counting method by defining a grid of boxes Bi(δ), where i is the index and δ is the size of the boxes, to quantify the distribution of stable and unstable manifolds of the map. When the parameter is in the range 0.51< η <0.58 and 0.68< η <1 the map is ergodic; i.e., the unstable and stable manifolds eventually cover the whole torus, although not in a uniform distribution. For accurate numerical results we require correspondingly accurate construction of the stable and unstable manifolds. Here we use the piecewise linearity of the map to achieve this, by computing the endpoints of line segments which define the global stable and unstable manifolds. This allows the generalized fractal dimension Dq, and spectrum of dimensions f(α), to be computed with accuracy. Finally, the intersection of the unstable and stable manifold of the map will be investigated, and compared with the distribution of periodic points of the system.

Keywords: feed forward, gradient descent, neural network, integral equation

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1770 A Detailed Computational Investigation into Copper Catalyzed Sonogashira Coupling Reaction

Authors: C. Rajalakshmi, Vibin Ipe Thomas

Abstract:

Sonogashira coupling reactions are widely employed in the synthesis of molecules of biological and pharmaceutical importance. Copper catalyzed Sonogashira coupling reactions are gaining importance owing to the low cost and less toxicity of copper as compared to the palladium catalyst. In the present work, a detailed computational study has been carried out on the Sonogashira coupling reaction between aryl halides and terminal alkynes catalyzed by Copper (I) species with trans-1, 2 Diaminocyclohexane as ligand. All calculations are performed at Density Functional Theory (DFT) level, using the hybrid Becke3LYP functional. Cu and I atoms are described using an effective core potential (LANL2DZ) for the inner electrons and its associated double-ζ basis set for the outer electrons. For all other atoms, 6-311G+* basis set is used. We have identified that the active catalyst species is a neutral 3-coordinate trans-1,2 diaminocyclohexane ligated Cu (I) alkyne complex and found that the oxidative addition and reductive elimination occurs in a single step proceeding through one transition state. This is owing to the ease of reductive elimination involving coupling of Csp2-Csp carbon atoms and the less stable Cu (III) intermediate. This shows the mechanism of copper catalyzed Sonogashira coupling reactions are quite different from those catalyzed by palladium. To gain further insights into the mechanism, substrates containing various functional groups are considered in our study to traverse their effect on the feasibility of the reaction. We have also explored the effect of ligand on the catalytic cycle of the coupling reaction. The theoretical results obtained are in good agreement with the experimental observation. This shows the relevance of a combined theoretical and experimental approach for rationally improving the cross-coupling reaction mechanisms.

Keywords: copper catalysed, density functional theory, reaction mechanism, Sonogashira coupling

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1769 Effect of Process Variables of Wire Electrical Discharge Machining on Surface Roughness for AA-6063 by Response Surface Methodology

Authors: Deepak

Abstract:

WEDM is an amazingly potential electro-wire process for machining of hard metal compounds and metal grid composites without making contact. Wire electrical machining is a developing noncustomary machining process for machining hard to machine materials that are electrically conductive. It is an exceptionally exact, precise, and one of the most famous machining forms in nontraditional machining. WEDM has turned into the fundamental piece of many assembling process ventures, which require precision, variety, and accuracy. In the present examination, AA-6063 is utilized as a workpiece, and execution investigation is done to discover the critical control factors. Impact of different parameters like a pulse on time, pulse off time, servo voltage, peak current, water pressure, wire tension, wire feed upon surface hardness has been researched while machining on AA-6063. RSM has been utilized to advance the yield variable. A variety of execution measures with input factors was demonstrated by utilizing the response surface methodology.

Keywords: AA-6063, response surface methodology, WEDM, surface roughness

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1768 A Robust System for Foot Arch Type Classification from Static Foot Pressure Distribution Data Using Linear Discriminant Analysis

Authors: R. Periyasamy, Deepak Joshi, Sneh Anand

Abstract:

Foot posture assessment is important to evaluate foot type, causing gait and postural defects in all age groups. Although different methods are used for classification of foot arch type in clinical/research examination, there is no clear approach for selecting the most appropriate measurement system. Therefore, the aim of this study was to develop a system for evaluation of foot type as clinical decision-making aids for diagnosis of flat and normal arch based on the Arch Index (AI) and foot pressure distribution parameter - Power Ratio (PR) data. The accuracy of the system was evaluated for 27 subjects with age ranging from 24 to 65 years. Foot area measurements (hind foot, mid foot, and forefoot) were acquired simultaneously from foot pressure intensity image using portable PedoPowerGraph system and analysis of the image in frequency domain to obtain foot pressure distribution parameter - PR data. From our results, we obtain 100% classification accuracy of normal and flat foot by using the linear discriminant analysis method. We observe there is no misclassification of foot types because of incorporating foot pressure distribution data instead of only arch index (AI). We found that the mid-foot pressure distribution ratio data and arch index (AI) value are well correlated to foot arch type based on visual analysis. Therefore, this paper suggests that the proposed system is accurate and easy to determine foot arch type from arch index (AI), as well as incorporating mid-foot pressure distribution ratio data instead of physical area of contact. Hence, such computational tool based system can help the clinicians for assessment of foot structure and cross-check their diagnosis of flat foot from mid-foot pressure distribution.

Keywords: arch index, computational tool, static foot pressure intensity image, foot pressure distribution, linear discriminant analysis

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1767 Evaluating the Methods of Retrofitting and Renovating the Masonry Schools of Ahvaz City

Authors: Navid Khayat, Babak Mombeni

Abstract:

This study investigates the retrofitting of schools in Ahvaz City. Three schools, namely, Enghelab, Sherafat, and Golchehreh, in Ahvaz City, are initially examined through Schmidt hammer and ultrasonic tests. Given the tests and controls on the structures of these schools, the methods are presented for their reconstruction. The plan is presented for each school by estimating the cost and generally the feasibility and estimated the duration of project reconstruction. After reconstruction, the mentioned tests are re-performed for rebuilt parts and the results indicate a significant improvement in performance of structure because of reconstruction. According to the results, despite the fact that the use of fiber reinforced polymers (FRP) for structure retrofitting is costly, due to the low executive costs and also other benefits of FRP, it is generally considered as one of the most effective ways of retrofitting. Building the concrete coating on walls is another effective method in retrofitting the buildings. According to this method, a grid of horizontal and vertical bars is installed on the wall and then the concrete is poured on it. The use of concrete coating on the concrete and brick structures leads to the useful results and the experience indicates that the poured concrete filled the joints well and provides the appropriate bonding and adhesion.

Keywords: renovation, retrofitting, masonry structures, concrete coating

Procedia PDF Downloads 450