Search results for: hybrid finite element model

Authors: Louis N. Y. Wong

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En-echelon fractures are commonly found in rocks, which appear as a special set of regularly oriented and spaced fractures. By using both experimental and numerical approaches, this study investigates the interaction among them, and how this interaction finally contributes to the development of a shear rupture (fault), especially in brittle natural rocks. Firstly, uniaxial compression tests are conducted on marble specimens containing en-echelon flaws. The latter is cut by using the water abrasive jet into the rock specimens. The fracturing processes of these specimens leading to the formation of a fault are observed in detail by the use of a high speed camera. The influences of the flaw geometry on the production of tensile cracks and shear cracks, which in turn dictate the coalescence patterns of the entire set of en-echelon flaws are comprehensively studied. Secondly, a numerical study based on a recently developed contact model, flat-joint contact model using the discrete element method (DEM) is carried out to model the present laboratory experiments. The numerical results provide a quantitative assessment of the interaction of en-echelon flaws. Particularly, the evolution of the stress field, as well as the characteristics of new crack initiation, propagation and coalescence associated with the generation of an eventual shear rupture are studied in detail. The numerical results are found to agree well with the experimental results obtained in both microscopic and macroscopic observations.

Keywords: discrete element method, en-echelon flaws, fault, marble

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Authors: Rajesh Kumar G

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A challenging aspect of any clinical trial is to carefully plan the study design to meet the study objective in optimum way and to validate the assumptions made during protocol designing. And when it is a pediatric study, there is the added challenge of stringent guidelines and difficulty in recruiting the necessary subjects. Unlike adult trials, there is not much historical data available for pediatrics, which is required to validate assumptions for planning pediatric trials. Typically, pediatric studies are initiated as soon as approval is obtained for a drug to be marketed for adults, so with the adult study historical information and with the available pediatric pilot study data or simulated pediatric data, the pediatric study can be well planned. Generalizing the historical adult study for new pediatric study is a tedious task; however, it is possible by integrating various statistical techniques and utilizing the advantage of hybrid study design, which will help to achieve the study objective in a smoother way even with the presence of many constraints. This research paper will explain how well the hybrid study design can be planned along with integrated technique (SEV) to plan the pediatric study; In brief the SEV technique (Simulation, Estimation (using borrowed adult data and applying Bayesian methods)) incorporates the use of simulating the planned study data and getting the desired estimates to Validate the assumptions.This method of validation can be used to improve the accuracy of data analysis, ensuring that results are as valid and reliable as possible, which allow us to make informed decisions well ahead of study initiation. With professional precision, this technique based on the collected data allows to gain insight into best practices when using data from historical study and simulated data alike.

Keywords: adaptive design, simulation, borrowing data, bayesian model

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Authors: Weiying Wang, Qi Li, Huiwen Deng, Weirong Chen

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The abrupt light change and uneven illumination will make the PV system get rid of constant output power, which will affect the efficiency of the grid connected inverter as well as the stability of the system. To solve this problem, this paper presents a strategy to control the stability of photovoltaic power system under the condition of partial shading of PV array, leading to constant power output, improving the capacity of resisting interferences. Firstly, a photovoltaic cell model considering the partial shading is established, and the backtracking search algorithm is used as the maximum power point to track algorithm under complex illumination. Then, the energy storage system based on the constant power control strategy is used to achieve constant power output. Finally, the effectiveness and correctness of the proposed control method are verified by the joint simulation of MATLAB/Simulink and RTLAB simulation platform.

Keywords: backtracking search algorithm, constant power control, hybrid system, partial shading, stability

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Authors: J. M. Counsell, Y. Khalid, M. J. Stewart

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Achieving nearly zero carbon heating continues to be identified by UK government analysis as an important feature of any lowest cost pathway to reducing greenhouse gas emissions. Heat currently accounts for 48% of UK energy consumption and approximately one third of UK’s greenhouse gas emissions. Heat Networks are being promoted by UK investment policies as one means of supporting hybrid heat pump based solutions. To this effect the RISE (Renewable Integrated and Sustainable Electric) heating system project is investigating how an all-electric heating sourceshybrid configuration could play a key role in long-term decarbonisation of heat.  For the purposes of this study, hybrid systems are defined as systems combining the technologies of an electric driven air source heat pump, electric powered thermal storage, a thermal vessel and micro-heat network as an integrated system.  This hybrid strategy allows for the system to store up energy during periods of low electricity demand from the national grid, turning it into a dynamic supply of low cost heat which is utilized only when required. Currently a prototype of such a system is being tested in a modern house integrated with advanced controls and sensors. This paper presents the virtual performance analysis of the system and its design for a micro heat network with multiple dwelling units. The results show that the RISE system is controllable and can reduce carbon emissions whilst being competitive in running costs with a conventional gas boiler heating system.

Keywords: gas boilers, heat pumps, hybrid heating and thermal storage, renewable integrated and sustainable electric

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Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine

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The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.

Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a promising and cost effective alternative to conventional treatment systems that facilitates direct oxidation of ammonium nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of any external carbon sources. The present study investigates the process kinetics of laboratory scale anammox hybrid reactor (AHR) which combines the dual advantages of attached and suspended growth. The performance & behaviour of AHR was studied under varying hydraulic retention time (HRTs) and nitrogen loading rate (NLRs). The experimental unit consisted of 4 numbers of 5L capacity anammox hybrid reactor inoculated with mixed seed culture containing anoxic and activated sludge. Pseudo steady state (PSS) ammonium and nitrite removal efficiencies of 90.6% and 95.6%, respectively, were achieved during acclimation phase. After establishment of PSS, the performance of AHR was monitored at seven different HRTs of 3.0, 2.5, 2.0, 1.5, 1.0, 0.5 and 0.25 d with increasing NLR from 0.4 to 4.8 kg N/m3d. The results showed that with increase in NLR and decrease in HRT (3.0 to 0.25 d), AHR registered appreciable decline in nitrogen removal efficiency from 92.9% to 67.4 %, respectively. The HRT of 2.0 d was considered optimal to achieve substantial nitrogen removal of 89%, because on further decrease in HRT below 1.5 days, remarkable decline in the values of nitrogen removal efficiency were observed. Analysis of data indicated that attached growth system contributes an additional 15.4 % ammonium removal and reduced the sludge washout rate (additional 29% reduction). This enhanced performance may be attributed to 25% increase in sludge retention time due to the attached growth media. Three kinetic models, namely, first order, Monod and Modified Stover-Kincannon model were applied to assess the substrate removal kinetics of nitrogen removal in AHR. Validation of the models were carried out by comparing experimental set of data with the predicted values obtained from the respective models. For substrate removal kinetics, model validation revealed that Modified Stover-Kincannon is most precise (R2=0.943) and can be suitably applied to predict the kinetics of nitrogen removal in AHR. Lawrence and McCarty model described the kinetics of bacterial growth. The predicted value of yield coefficient and decay constant were in line with the experimentally observed values.

Keywords: anammox, kinetics, modelling, nitrogen removal, sludge wash out rate, AHR

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.

Keywords: distributed algorithms, apache-spark, Hadoop, flexible dynamic job shop scheduling, multi-objective optimization

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Authors: Zeinab Yazdanfar, Dilan Robert, Daniel Lester, S. Setunge

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Scour has been identified as the most common threat to bridge stability worldwide. Traditionally, scour around bridge piers is calculated using the empirical approaches that have considerable limitations and are difficult to generalize. The multi-physic nature of scouring which involves turbulent flow, soil mechanics and solid-fluid interactions cannot be captured by simple empirical equations developed based on limited laboratory data. These limitations can be overcome by direct numerical modeling of coupled hydro-mechanical scour process that provides a robust prediction of bridge scour and valuable insights into the scour process. Several numerical models have been proposed in the literature for bridge scour estimation including Eulerian flow models and coupled Euler-Lagrange models incorporating an empirical sediment transport description. However, the contact forces between particles and the flow-particle interaction haven’t been taken into consideration. Incorporating collisional and frictional forces between soil particles as well as the effect of flow-driven forces on particles will facilitate accurate modeling of the complex nature of scour. In this study, a coupled Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) has been developed to simulate the scour process that directly models the hydro-mechanical interactions between the sediment particles and the flowing water. This approach obviates the need for an empirical description as the fundamental fluid-particle, and particle-particle interactions are fully resolved. The sediment bed is simulated as a dense pack of particles and the frictional and collisional forces between particles are calculated, whilst the turbulent fluid flow is modeled using a Reynolds Averaged Navier Stocks (RANS) approach. The CFD-DEM model is validated against experimental data in order to assess the reliability of the CFD-DEM model. The modeling results reveal the criticality of particle impact on the assessment of scour depth which, to the authors’ best knowledge, hasn’t been considered in previous studies. The results of this study open new perspectives to the scour depth and time assessment which is the key to manage the failure risk of bridge infrastructures.

Keywords: bridge scour, discrete element method, CFD-DEM model, multi-phase model

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Authors: Tomoaki Hashimoto

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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: Xingguo Feng, Hui Zhou, Kaifeng Zhang, Zhao Jiang, Hanjun Hu, Jun Zheng, Hong Hao

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TiN and TiC films have been prepared on Ti6Al4V alloy substrates by plasma-based ion implantation. The effect of N+C and Ti+N hybrid ion implantation at 50 kV, and Ti+C hybrid ion implantation at 20 kV, 35 kV and 50 kV extraction voltages on mechanical properties at a dose of 2×10¹⁷ ions / cm² was studied. The chemical states and microstructures of the implanted samples were investigated using X-ray photoelectron (XPS), and X-ray diffraction (XRD), together with the mechanical and tribological properties of the samples were characterized using nano-indentation and ball-on-disk tribometer. It was found that the modified layer by Ti+C implanted at 50 kV was composed of mainly TiC and Ti-O bond and the layer of Ti+N implanted at 50 kV was observed to be TiN and Ti-O bond. Hardness tests have shown that the hardness values for N+C, Ti+N, and Ti+C hybrid ion implantation samples were much higher than the un-implanted ones. The results of wear tests showed that both Ti+C and Ti+N ion implanted samples had much better wear resistance compared un-implanted sample. The wear rate of Ti+C implanted at 50 kV sample was 6.7×10⁻⁵mm³ / N.m, which was decreased over one order than unimplanted samples.

Keywords: plasma ion implantation, x-ray photoelectron (XPS), hardness, wear

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Authors: Andreas Helwig, John Bell, Wangmo

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Hybrid energy storage systems (HESS) are gaining popularity for grid energy storage (ESS) driven by the increasingly dynamic nature of energy demands, requiring both high energy and high power density. Particularly the ability of energy storage systems via inverters to respond to increasing fluctuation in energy demands, the combination of lithium Iron Phosphate (LFP) battery and supercapacitor (SC) is a particular example of complex electro-chemical devices that may provide benefit to each other for pulse width modulated DC to AC inverter application. This is due to SC’s ability to respond to instantaneous, high-current demands and batteries' long-term energy delivery. However, there is a knowledge gap on the current sharing mechanism within a HESS supplying a load powered by high-frequency pulse-width modulation (PWM) switching to understand the mechanism of aging in such HESS. This paper investigates the prediction of current utilizing various equivalent circuits for SC to investigate sharing between battery and SC in MATLAB/Simulink simulation environment. The findings predict a significant reduction of battery current when the battery is used in a hybrid combination with a supercapacitor as compared to a battery-only model. The impact of PWM inverter carrier switching frequency on current requirements was analyzed between 500Hz and 31kHz. While no clear trend emerged, models predicted optimal frequencies for minimized current needs.

Keywords: hybrid energy storage, carrier frequency, PWM switching, equivalent circuit models

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Authors: Elmahdi Mohammadine, Ahouzi Esmail, Najid Abdellah

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This contribution aims to present a new protected hybrid WDM/TDM PON architecture using Wavelength Selective Switches and Optical Line Protection devices. The objective from using these technologies is to improve flexibility and enhance the protection of GPON networks.

Keywords: Wavlenght Division Multiplexed Passive Optical Network (WDM-PON), Time Division Multiplexed PON (TDM-PON), architecture, Protection, Wavelength Selective Switches (WSS), Optical Line Protection (OLP)

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Syed Talib Abbas Raza, Tahseen Ahmed Jilani, Saleem Abdullah

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This paper presents interval-valued intuitionistic fuzzy soft sets based TOPSIS method for group decision making. The interval-valued intuitionistic fuzzy soft set is a mutation of an interval-valued intuitionistic fuzzy set and soft set. In group decision making problems IVIFSS makes the process much more algebraically elegant. We have used weighted arithmetic averaging operator for aggregating the information and define a new Hybrid Score Function as metric tool for comparison between interval-valued intuitionistic fuzzy values. In an illustrative example we have applied the developed method to a criminological problem. We have developed a group decision making model for integrating the imprecise and hesitant evaluations of multiple law enforcement agencies working on target killing cases in the country.

Keywords: group decision making, interval-valued intuitionistic fuzzy soft set, TOPSIS, score function, criminology

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Authors: Mona Elhelbawy, Mac Gray

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Traditional wired endoscopy is an intrusive process that requires a long flexible tube to be inserted through the patient’s mouth while intravenously sedated. Only images of the upper 4 feet of stomach, colon, and rectum can be captured, leaving the remaining 20 feet of small intestines. Wireless capsule endoscopy offers a painless, non-intrusive, efficient and effective alternative to traditional endoscopy. In wireless capsule endoscopy (WCE), ingestible vitamin-pill-shaped capsules with imaging capabilities, sensors, batteries, and antennas are designed to send images of the gastrointestinal (GI) tract in real time. In this paper, we investigate the radiation performance and specific absorption rate (SAR) of a miniature conformal capsule antenna operating at the Medical Implant Communication Service (MICS) frequency band in the human body. We perform numerical simulations using the finite element method based commercial software, high-frequency structure simulator (HFSS) and the ANSYS human body model (HBM). We also investigate the in-body channel characteristics between the implantable capsule and an external antenna placed on the surface of the human body.

Keywords: IEEE 802.15.6, MICS, SAR, WCE

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: A. Sharma, S. S. Sandhu, A. Shahi, A. Kumar

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The aim of present investigation was to carry out Finite element modeling of distortion in the case of butt weld. 12mm thick AISI 304L plates were butt welded using three different combinations of groove design namely Double U, Double V and Composite. A full simulation of shielded metal arc welding (SMAW) of nonlinear heat transfer is carried out. Aspects like, temperature-dependent thermal properties of AISI stainless steel above liquid phase, the effect of thermal boundary conditions, were included in the model. Since welding heat dissipation characteristics changed due to variable groove design significant changes in the microhardness tensile strength and impact toughness of the joints were observed. The cumulative distortion was found to be least in double V joint followed by the Composite and Double U-joints. All the joints have joint efficiency more than 100%. CVN value of the Double V-groove weld metal was highest. The experimental results and the FEM results were compared and reveal a very good correlation for distortion and weld groove design for a multipass joint with a standard analogy of 83%.

Keywords: AISI 304 L, Butt joint, distortion, FEM, groove design, SMAW

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: aerodynamics, flight control, computational fluid dynamics (CFD), flapping-wing flight

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Authors: Anjali Uday, Yuting Wang, Andres Alfonso Pena Olare

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The Discrete Element Method is a promising approach to modeling microscopic behaviors of granular materials. The quality of the simulations however depends on the model parameters utilized. The present study focuses on calibration and validation of the discrete element parameters for Cuxhaven sand based on the experimental data from triaxial and oedometer tests. A sensitivity analysis was conducted during the sample preparation stage and the shear stage of the triaxial tests. The influence of parameters like rolling resistance, inter-particle friction coefficient, confining pressure and effective modulus were investigated on the void ratio of the sample generated. During the shear stage, the effect of parameters like inter-particle friction coefficient, effective modulus, rolling resistance friction coefficient and normal-to-shear stiffness ratio are examined. The calibration of the parameters is carried out such that the simulations reproduce the macro mechanical characteristics like dilation angle, peak stress, and stiffness. The above-mentioned calibrated parameters are then validated by simulating an oedometer test on the sand. The oedometer test results are in good agreement with experiments, which proves the suitability of the calibrated parameters. In the next step, the calibrated and validated model parameters are applied to forecast the micromechanical behavior including the evolution of contact force chains, buckling of columns of particles, observation of non-coaxiality, and sample inhomogeneity during a simple shear test. The evolution of contact force chains vividly shows the distribution, and alignment of strong contact forces. The changes in coordination number are in good agreement with the volumetric strain exhibited during the simple shear test. The vertical inhomogeneity of void ratios is documented throughout the shearing phase, which shows looser structures in the top and bottom layers. Buckling of columns is not observed due to the small rolling resistance coefficient adopted for simulations. The non-coaxiality of principal stress and strain rate is also well captured. Thus the micromechanical behaviors are well described using the calibrated and validated material parameters.

Keywords: discrete element model, parameter calibration, triaxial test, oedometer test, simple shear test

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Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

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The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

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Authors: Kyung-Suk Choi, Hyung-Joon Kim

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Modular structural systems are constructed using a method that they are assembled with prefabricated unit modular frames on-site. This provides a benefit that can significantly reduce building construction time. Their structural design is usually carried out under the assumption that the load-carrying mechanism is similar to that of a traditional steel moment-resisting system. However, both systems are different in terms of beam-column connection details which may strongly influence the lateral structural behavior. Specially, the presence of access holes in a beam-column joint of a unit modular frame could cause undesirable failure during strong earthquakes. Therefore, this study carried out finite element analyses (FEM) of unit modular frames to investigate the cyclic behavior of beam-column joints with the structural influence of access holes. Analysis results show that the unit modular frames present stable cyclic response with large deformation capacities, and their joints are classified into semi-rigid connections.

Keywords: unit modular frame, steel moment connection, nonlinear analytical model, moment-rotation relation

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Authors: Kim Quy Le, Duan Fei, Jia Wei Chew, Jun Zeng, Maria Fabiola Leyva

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In line with the sustainable development goal, molded fiber products play important roles in reducing plastic-based packaging. To fabricate molded fiber products, besides using conventional meshing tools, 3D printing is employed to manufacture the molded fiber screen. 3D printing technique allows printing molded fiber screens with complex geometry, flexible in pore size and shape. The 3D printed molded fiber screens are in the progress of investigation to improve the de-watering efficiency, fiber collection, mechanical strength, etc. In addition, the fiber distribution on the screen is also necessary to access the quality of the screen. Besides using experimental methods to capture the fiber distribution on screen, simulation also offers using tools to access the uniformity of fiber. In this study, the fiber was simulated using the multi-sphere model to simulate the fibers. The interaction of the fibers was able to mimic by employing the discrete element method. The fiber distribution was captured and compared to the experiment. The simulation results were able to reveal the fiber deposition layer upon layer and explain the formation of uneven thickness on the tilted area of molded fiber screen.

Keywords: 3D printing, multi-jet fusion, molded fiber screen, discrete element method

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Authors: Thomas Yeboah

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Cloud Computing is newly paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). As Cloud Computing is a newly style of computing on the internet. It has many merits along with some crucial issues that need to be resolved in order to improve reliability of cloud environment. These issues are related with the load balancing, fault tolerance and different security issues in cloud environment.In this paper the main concern is to develop an effective load balancing algorithm that gives satisfactory performance to both, cloud users and providers. This proposed algorithm (hybrid Bee Ant Colony algorithm) is a combination of two dynamic algorithms: Ant Colony Optimization and Bees Life algorithm. Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues whiles the Bees Life algorithm is used for optimization of job scheduling in cloud environment. The results of the proposed algorithm shows that the hybrid Bee Ant Colony algorithm outperforms the performances of both Ant Colony algorithm and Bees Life algorithm when evaluated the proposed algorithm performances in terms of Waiting time and Response time on a simulator called CloudSim.

Keywords: ant colony optimization algorithm, bees life algorithm, scheduling algorithm, performance, cloud computing, load balancing

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Authors: Shayem Saleh ALresheedi, Lu Song Feng, Abdulaziz Abdulwahab M. Fatani

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Cloud computing is an emerging concept in the technological sphere. Its development enables many applications to avail information online and on demand. It is becoming an essential element for businesses due to its ability to diminish the costs of IT infrastructure and is being adopted in Saudi Arabia. However, there exist many factors that affect its adoption. Several researchers in the field have ignored the study of the TAM model for identifying the relevant factors and their impact for adopting of cloud computing. This study focuses on evaluating the acceptability of cloud computing and analyzing its impacting factors using Technology Acceptance Model (TAM) of technology adoption in Saudi Arabia. It suggests a model to examine the influential factors of the TAM model along with external factors of technical support in adapting the cloud computing. The proposed model has been tested through the use of multiple hypotheses based on calculation tools and collected data from customers through questionnaires. The findings of the study prove that the TAM model along with external factors can be applied in measuring the expected adoption of cloud computing. The study presents an investigation of influential factors and further recommendation in adopting cloud computing in Saudi Arabia.

Keywords: cloud computing, acceptability, adoption, determinants

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Authors: Atilla Bayram

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This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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Authors: Emmanuel Omokhuale

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A mathematical model is presented to study free convective boundary layer flow in a semi-infinite vertical cylinder with heat sink effect in a porous medium. The governing dimensional governing partial differential equations (PDEs) with corresponding initial and boundary conditions are approximated and solved numerically employing finite difference method (FDM) the implicit type. Stability and convergence of the scheme are also established. Furthermore, the influence of significant physical parameters on the flow characteristics was analysed and shown graphically. The obtained results are benchmarked with previously published works in order to access the accuracy of the numerical method and found to be in good agreement.

Keywords: free convection flow, vertical cylinder, implicit finite difference method, heat sink and porous medium

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Authors: Orose Rugchati, Khumthong Mahawongwiriya

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Dendrobium hybrid cv. Ear-Sakul has become one of the important commercial commodities in Thailand agricultural industry worldwide, either as potted plants or as cut flowers due to the attractive color produced in flower petals. Anthocyanins are the main flower pigments and responsible for the natural attractive display of petal colors. These pigments play an important role in functionality, such as to attract animal pollinators, classification, and grading of these orchids. Dendrobium hybrid cv. Ear-Sakul has been collected from local area farm in different stage flowers (F1, F2-F5, and F6). Anthocyanins pigment were extracted from the fresh flower by solvent extraction (MeOH–TFA 99.5:0.5v/v at 4ºC) and purification with ethyl acetate. The main anthocyanins components are cyanidin, pelargonidin, and delphinidin. Pure anthocyanin contents were analysis by UV-Visible spectroscopy technique at λ max 535, 520 and 546 nm respectively. The anthocyanins contents were converted in term of monomeric anthocyanins pigment (mg/L). The anthocyanins contents of all sample were compared with standard pigments cyanidin, pelargonidin and delphinidin. From this experiment is a simple extraction and analysis anthocyanins content in different stage of flowers results shown that monomeric anthocyanins pigment contents of different stage flowers (F1, F2-F5 and F6 ): cyanidin – 3 – glucoside (mg/l) are 0.85+0.08, 24.22+0.12 and 62.12+0.6; Pelargonidin 3,5-di- glucoside(mg/l) 10.37+0.12, 31.06+0.8 and 81.58+ 0.5; Delphinidin (mg/l) 6.34+0.17, 18.98+0.56 and 49.87+0.7; and the appearance of extraction pure anthocyanins in L(a, b): 2.71(1.38, -0.48), 1.06(0.39,-0.66) and 2.64(2.71,-3.61) respectively. Dendrobium Hybrid cv. Ear-Sakul could be used as a source of anthocyanins by simple solvent extraction and stage of flowers as a guideline for the prediction amount of main anthocyanins components are cyanidin, pelargonidin, and delphinidin could be application and development in quantities, and qualities with the advantage for food pharmaceutical and cosmetic industries.

Keywords: analysis, anthocyanins contents, different stage flowers, Dendrobium Hybrid cv. Ear-Sakul

Procedia PDF Downloads 150

Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

Abstract:

Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

Procedia PDF Downloads 147

Authors: Ahmed Mohammed Alsalama

Abstract:

Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of the current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose a hybrid framework recommendation system to be applied on two-dimensional spaces (User x Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.

Keywords: data mining, association rules, recommendation systems, hybrid systems

Procedia PDF Downloads 453

Authors: Deepa Das, Susmita Das

Abstract:

Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

Procedia PDF Downloads 467