Search results for: applied stochastic model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 23127

Search results for: applied stochastic model

22167 A Framework for Chinese Domain-Specific Distant Supervised Named Entity Recognition

Authors: Qin Long, Li Xiaoge

Abstract:

The Knowledge Graphs have now become a new form of knowledge representation. However, there is no consensus in regard to a plausible and definition of entities and relationships in the domain-specific knowledge graph. Further, in conjunction with several limitations and deficiencies, various domain-specific entities and relationships recognition approaches are far from perfect. Specifically, named entity recognition in Chinese domain is a critical task for the natural language process applications. However, a bottleneck problem with Chinese named entity recognition in new domains is the lack of annotated data. To address this challenge, a domain distant supervised named entity recognition framework is proposed. The framework is divided into two stages: first, the distant supervised corpus is generated based on the entity linking model of graph attention neural network; secondly, the generated corpus is trained as the input of the distant supervised named entity recognition model to train to obtain named entities. The link model is verified in the ccks2019 entity link corpus, and the F1 value is 2% higher than that of the benchmark method. The re-pre-trained BERT language model is added to the benchmark method, and the results show that it is more suitable for distant supervised named entity recognition tasks. Finally, it is applied in the computer field, and the results show that this framework can obtain domain named entities.

Keywords: distant named entity recognition, entity linking, knowledge graph, graph attention neural network

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22166 Genesis of Entrepreneur Business Models in New Ventures

Authors: Arash Najmaei, Jo Rhodes, Peter Lok, Zahra Sadeghinejad

Abstract:

In this article, we endeavor to explore how a new business model comes into existence in the Australian cloud-computing eco-system. Findings from multiple case study methodology reveal that to develop a business model new ventures adopt a three-phase approach. In the first phase, labelled as business model ideation (BMID) various ideas for a viable business model are generated from both internal and external networks of the entrepreneurial team and the most viable one is chosen. Strategic consensus and commitment are generated in the second phase. This phase is a business modelling strategic action phase. We labelled this phase as business model strategic commitment (BMSC) because through commitment and the subsequent actions of executives resources are pooled, coordinated and allocated to the business model. Three complementary sets of resources shape the business model: managerial (MnRs), marketing (MRs) and technological resources (TRs). The third phase is the market-test phase where the business model is reified through the delivery of the intended value to customers and conversion of revenue into profit. We labelled this phase business model actualization (BMAC). Theoretical and managerial implications of these findings will be discussed and several directions for future research will be illuminated.

Keywords: entrepreneur business model, high-tech venture, resources, conversion of revenue

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22165 Using Gaussian Process in Wind Power Forecasting

Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

Abstract:

The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: wind power, Gaussien process, modelling, forecasting

Procedia PDF Downloads 418
22164 Study and Simulation of a Dynamic System Using Digital Twin

Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

Abstract:

Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

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22163 One-Way Electric Vehicle Carsharing in an Urban Area with Vehicle-To-Grid Option

Authors: Cem Isik Dogru, Salih Tekin, Kursad Derinkuyu

Abstract:

Electric vehicle (EV) carsharing is an alternative method to tackle urban transportation problems. This method can be applied by several options. One of the options is the one-way carsharing, which allow an EV to be taken at a designated location and leaving it on another specified location customer desires. Although it may increase users’ satisfaction, the issues, namely, demand dissatisfaction, relocation of EVs and charging schedules, must be dealt with. Also, excessive electricity has to be stored in batteries of EVs. To cope with aforementioned issues, two-step mixed integer programming (MIP) model is proposed. In first step, the integer programming model is used to determine amount of electricity to be sold to the grid in terms of time periods for extra profit. Determined amounts are provided from the batteries of EVs. Also, this step works in day-ahead electricity markets with forecast of periodical electricity prices. In second step, other MIP model optimizes daily operations of one-way carsharing: charging-discharging schedules, relocation of EVs to serve more demand and renting to maximize the profit of EV fleet owner. Due to complexity of the models, heuristic methods are introduced to attain a feasible solution and different price information scenarios are compared.

Keywords: electric vehicles, forecasting, mixed integer programming, one-way carsharing

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22162 Process Simulation of 1-Butene Separation from C4 Mixture by Extractive Distillation

Authors: Muhammad Naeem, Abdulrahman A. Al-Rabiah, Wasif Mughees

Abstract:

Technical mixture of C4 containing 1-butene and n-butane are very close to each other with regard to their boiling points i.e. -6.3°C for 1-butene and -1°C for n-butane. Extractive distillation process is used for the separation of 1-butene from the existing mixture of C4. The solvent is the essential of extractive distillation, and an appropriate solvent plays an important role in the process economy of extractive distillation. Aspen Plus has been applied for the separation of these hydrocarbons as a simulator. Moreover, NRTL activity coefficient model was used in the simulation. This model indicated that the material balances in this separation process were accurate for several solvent flow rates. Mixture of acetonitrile and water used as a solvent and 99% pure 1-butene was separated. This simulation proposed the ratio of the feed to solvent as 1: 7.9 and 15 plates for the solvent recovery column. Previously feed to solvent ratio was more than this and the number of proposed plates were 30, which shows that the separation process can be economized.

Keywords: extractive distillation, 1-butene, aspen plus, ACN solvent

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22161 Model of Multi-Criteria Evaluation for Railway Lines

Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

Abstract:

The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

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22160 Research on Coordination Strategies for Coordinating Supply Chain Based on Auction Mechanisms

Authors: Changtong Wang, Lingyun Wei

Abstract:

The combination of auctions and supply chains is of great significance in improving the supply chain management system and enhancing the efficiency of economic and social operations. To address the gap in research on supply chain strategies under the auction mechanism, a model is developed for the 1-N auction model in a complete information environment, and it is concluded that the two-part contract auction model for retailers in this model can achieve supply chain coordination. The model is validated by substituting the model into the scenario of a fresh-cut flower industry flower auction in exchange for arithmetic examples to further prove the validity of the conclusions.

Keywords: auction mechanism, supply chain coordination strategy, fresh cut flowers industry, supply chain management

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22159 Adaptive Thermal Comfort Model for Air-Conditioned Lecture Halls in Malaysia

Authors: B. T. Chew, S. N. Kazi, A. Amiri

Abstract:

This paper presents an adaptive thermal comfort model study in the tropical country of Malaysia. A number of researchers have been interested in applying the adaptive thermal comfort model to different climates throughout the world, but so far no study has been performed in Malaysia. For the use as a thermal comfort model, which better applies to hot and humid climates, the adaptive thermal comfort model was developed as part of this research by using the collected results from a large field study in six lecture halls with 178 students. The relationship between the operative temperature and behavioral adaptations was determined. In the developed adaptive model, the acceptable indoor neutral temperatures lay within the range of 23.9-26.0 oC, with outdoor temperatures ranging between 27.0–34.6oC. The most comfortable temperature for students in the lecture hall was 25.7 oC.

Keywords: hot and humid, lecture halls, neutral temperature, adaptive thermal comfort model

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22158 Enhanced Flight Dynamics Model to Simulate the Aircraft Response to Gust Encounters

Authors: Castells Pau, Poetsch Christophe

Abstract:

The effect of gust and turbulence encounters on aircraft is a wide field of study which allows different approaches, from high-fidelity multidisciplinary simulations to more simplified models adapted to industrial applications. The typical main goal is to predict the gust loads on the aircraft in order to ensure a safe design and achieve certification. Another topic widely studied is the gust loads reduction through an active control law. The impact of gusts on aircraft handling qualities is of interest as well in the analysis of in-service events so as to evaluate the aircraft response and the performance of the flight control laws. Traditionally, gust loads and handling qualities are addressed separately with different models adapted to the specific needs of each discipline. In this paper, an assessment of the differences between both models is presented and a strategy to better account for the physics of gust encounters in a typical flight dynamics model is proposed based on the model used for gust loads analysis. The applied corrections aim to capture the gust unsteady aerodynamics and propagation as well as the effect of dynamic flexibility at low frequencies. Results from the gust loads model at different flight conditions and measures from real events are used for validation. An assessment of a possible extension of steady aerodynamic nonlinearities to low frequency range is also addressed. The proposed corrections provide meaningful means to evaluate the performance and possible adjustments of the flight control laws.

Keywords: flight dynamics, gust loads, handling qualities, unsteady aerodynamics

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22157 A Model of a Non-expanding Universe

Authors: Yongbai Yin

Abstract:

We propose a non-expanding model of the universe based on the non-changing fine-structure constant and Einstein’s space-time relativity theory. This model consistently explains the Redshift, the ‘expanding’ and the age of the universe without introducing the singularity and inflationary issues that occurred in the ‘Big Bang’ model. It also offers an interpretation of the unexpected ‘accelerated expanding’ universe and the origin of the mystery of ‘Dark matter’. It predicts that the universe began with a ‘cold and peaceful’ rather than ‘extremely hot’ stage which is used to explain consistently the microwave background radiation. It predicts mathematically that galaxies could end in blackholes because blackholes should have the same environmental conditions as those at the beginning of the universe in this model, paving the way to offer a model of the cyclic universes without violating the first law of thermodynamics.

Keywords: big bang, accelerated expanding universe, dark matters, blackholes, microwave background radiation, universe modelling

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22156 Optimal Tamping for Railway Tracks, Reducing Railway Maintenance Expenditures by the Use of Integer Programming

Authors: Rui Li, Min Wen, Kim Bang Salling

Abstract:

For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euros per kilometer per year. In order to reduce such maintenance expenditures, this paper presents a mixed 0-1 linear mathematical model designed to optimize the predictive railway tamping activities for ballast track in the planning horizon of three to four years. The objective function is to minimize the tamping machine actual costs. The approach of the research is using the simple dynamic model for modelling condition-based tamping process and the solution method for finding optimal condition-based tamping schedule. Seven technical and practical aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality recovery on the track quality after tamping operation; (5) Tamping machine operation practices (6) tamping budgets and (7) differentiating the open track from the station sections. A Danish railway track between Odense and Fredericia with 42.6 km of length is applied for a time period of three and four years in the proposed maintenance model. The generated tamping schedule is reasonable and robust. Based on the result from the Danish railway corridor, the total costs can be reduced significantly (50%) than the previous model which is based on optimizing the number of tamping. The different maintenance strategies have been discussed in the paper. The analysis from the results obtained from the model also shows a longer period of predictive tamping planning has more optimal scheduling of maintenance actions than continuous short term preventive maintenance, namely yearly condition-based planning.

Keywords: integer programming, railway tamping, predictive maintenance model, preventive condition-based maintenance

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22155 Using Cyclic Structure to Improve Inference on Network Community Structure

Authors: Behnaz Moradijamei, Michael Higgins

Abstract:

Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

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22154 Agile Software Effort Estimation Using Regression Techniques

Authors: Mikiyas Adugna

Abstract:

Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

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22153 Smaa-Gaia: A Complementary Tool of the Smaa-Promethee Method

Authors: Y. de Smet, J. Hubinont

Abstract:

PROMETHEE and GAIA are well-known Multiple Criteria Decision Aid methods. Given an evaluation table and preference parameters they allow to rank the alternatives, to visualize the problem, to perform sensitivity and robustness analysis, etc. Unfortunately, it is often hard for the Decision Maker (DM) to estimate the precise values of these parameters. Therefore an alternative option is to give ranges of potential values in order to apply Stochastic Multicriteria Acceptability Analysis. This has been recently studied in the context of the SMAA-PROMETHEE method. The aim of this contribution is to propose an SMAA extension of GAIA. We show how this tool can be useful and provide complementary information to SMAA-PROMETHEE. This is illustrated on a pedagogical example.

Keywords: multiple criteria decision making, PROMETHEE, GAIA, SMAA

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22152 Model-Based Control for Piezoelectric-Actuated Systems Using Inverse Prandtl-Ishlinskii Model and Particle Swarm Optimization

Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin

Abstract:

In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.

Keywords: the Bouc-Wen hysteresis model, particle swarm optimization, Prandtl-Ishlinskii model, automation engineering

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22151 Yang-Lee Edge Singularity of the Infinite-Range Ising Model

Authors: Seung-Yeon Kim

Abstract:

The Ising model, consisting magnetic spins, is the simplest system showing phase transitions and critical phenomena at finite temperatures. The Ising model has played a central role in our understanding of phase transitions and critical phenomena. Also, the Ising model explains the gas-liquid phase transitions accurately. However, the Ising model in a nonzero magnetic field has been one of the most intriguing and outstanding unsolved problems. We study analytically the partition function zeros in the complex magnetic-field plane and the Yang-Lee edge singularity of the infinite-range Ising model in an external magnetic field. In addition, we compare the Yang-Lee edge singularity of the infinite-range Ising model with that of the square-lattice Ising model in an external magnetic field.

Keywords: Ising ferromagnet, magnetic field, partition function zeros, Yang-Lee edge singularity

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22150 Risk Assessment Tools Applied to Deep Vein Thrombosis Patients Treated with Warfarin

Authors: Kylie Mueller, Nijole Bernaitis, Shailendra Anoopkumar-Dukie

Abstract:

Background: Vitamin K antagonists particularly warfarin is the most frequently used oral medication for deep vein thrombosis (DVT) treatment and prophylaxis. Time in therapeutic range (TITR) of the international normalised ratio (INR) is widely accepted as a measure to assess the quality of warfarin therapy. Multiple factors can affect warfarin control and the subsequent adverse outcomes including thromboembolic and bleeding events. Predictor models have been developed to assess potential contributing factors and measure the individual risk of these adverse events. These predictive models have been validated in atrial fibrillation (AF) patients, however, there is a lack of literature on whether these can be successfully applied to other warfarin users including DVT patients. Therefore, the aim of the study was to assess the ability of these risk models (HAS BLED and CHADS2) to predict haemorrhagic and ischaemic incidences in DVT patients treated with warfarin. Methods: A retrospective analysis of DVT patients receiving warfarin management by a private pathology clinic was conducted. Data was collected from November 2007 to September 2014 and included demographics, medical and drug history, INR targets and test results. Patients receiving continuous warfarin therapy with an INR reference range between 2.0 and 3.0 were included in the study with mean TITR calculated using the Rosendaal method. Bleeding and thromboembolic events were recorded and reported as incidences per patient. The haemorrhagic risk model HAS BLED and ischaemic risk model CHADS2 were applied to the data. Patients were then stratified into either the low, moderate, or high-risk categories. The analysis was conducted to determine if a correlation existed between risk assessment tool and patient outcomes. Data was analysed using GraphPad Instat Version 3 with a p value of <0.05 considered to be statistically significant. Patient characteristics were reported as mean and standard deviation for continuous data and categorical data reported as number and percentage. Results: Of the 533 patients included in the study, there were 268 (50.2%) female and 265 (49.8%) male patients with a mean age of 62.5 years (±16.4). The overall mean TITR was 78.3% (±12.7) with an overall haemorrhagic incidence of 0.41 events per patient. For the HAS BLED model, there was a haemorrhagic incidence of 0.08, 0.53, and 0.54 per patient in the low, moderate and high-risk categories respectively showing a statistically significant increase in incidence with increasing risk category. The CHADS2 model showed an increase in ischaemic events according to risk category with no ischaemic events in the low category, and an ischaemic incidence of 0.03 in the moderate category and 0.47 high-risk categories. Conclusion: An increasing haemorrhagic incidence correlated to an increase in the HAS BLED risk score in DVT patients treated with warfarin. Furthermore, a greater incidence of ischaemic events occurred in patients with an increase in CHADS2 category. In an Australian population of DVT patients, the HAS BLED and CHADS2 accurately predicts incidences of haemorrhage and ischaemic events respectively.

Keywords: anticoagulant agent, deep vein thrombosis, risk assessment, warfarin

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22149 Design and Implementation a Platform for Adaptive Online Learning Based on Fuzzy Logic

Authors: Budoor Al Abid

Abstract:

Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

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22148 Learners as Consultants: Knowledge Acquisition and Client Organisations-A Student as Producer Case Study

Authors: Barry Ardley, Abi Hunt, Nick Taylor

Abstract:

As a theoretical and practical framework, this study uses the student-as-producer approach to learning in higher education, as adopted by the Lincoln International Business School, University of Lincoln, UK. Students as producer positions learners as skilled and capable agents, able to participate as partners with tutors in live research projects. To illuminate the nature of this approach to learning and to highlight its critical issues, the authors report on two guided student consultancy projects. These were set up with the assistance of two local organisations in the city of Lincoln, UK. Using the student as a producer model to deliver the projects enabled learners to acquire and develop a range of key skills and knowledge not easily accessible in more traditional educational settings. This paper presents a systematic case study analysis of the eight organising principles of the student-as-producer model, as adopted by university tutors. The experience of tutors implementing students as producers suggests that the model can be widely applied to benefit not only the learning and teaching experiences of higher education students and staff but additionally a university’s research programme and its community partners.

Keywords: consultancy, learning, student as producer, research

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22147 Spectral Clustering from the Discrepancy View and Generalized Quasirandomness

Authors: Marianna Bolla

Abstract:

The aim of this paper is to compare spectral, discrepancy, and degree properties of expanding graph sequences. As we can prove equivalences and implications between them and the definition of the generalized (multiclass) quasirandomness of Lovasz–Sos (2008), they can be regarded as generalized quasirandom properties akin to the equivalent quasirandom properties of the seminal Chung-Graham-Wilson paper (1989) in the one-class scenario. Since these properties are valid for deterministic graph sequences, irrespective of stochastic models, the partial implications also justify for low-dimensional embedding of large-scale graphs and for discrepancy minimizing spectral clustering.

Keywords: generalized random graphs, multiway discrepancy, normalized modularity spectra, spectral clustering

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22146 Simulation the Stress Distribution of Wheel/Rail at Contact Region

Authors: Norie A. Akeel, Z. Sajuri, A. K. Ariffin

Abstract:

This paper discusses the effect of different loading analysis on crack initiation life of wheel/rail in the contact region. A simulated three dimensional (3D) elasto plastic model of a wheel/rail contact is modeled using the fine mesh technique in the contact region by using Finite Element Method FEM code ANSYS 11.0 software. Different loads of approximately from 70 to 140 KN was applied on the wheel tread through the running surface on the railhead surface to simulate stress distribution (Von Mises) and a life prediction of the crack initiation under rolling contact motion. Stress analysis is achieved and the fatigue life to the rail head surface is calculated numerically by using a multi-axial fatigue life of crack initiation model. All results obtained from the previous researches are compared with this research.

Keywords: FEM, rolling contact, rail track, stress distribution, fatigue life

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22145 Nonlinear Vibration Analysis of a Functionally Graded Micro-Beam under a Step DC Voltage

Authors: Ali Raheli, Rahim Habibifar, Behzad Mohammadi-Alasti, Mahdi Abbasgholipour

Abstract:

This paper presents vibration behavior of a FGM micro-beam and its pull-in instability under a nonlinear electrostatic pressure. An exponential function has been applied to show the continuous gradation of the properties along thickness. Nonlinear integro-differential-electro-mechanical equation based on Euler–Bernoulli beam theory has been derived. The governing equation in the static analysis has been solved using Step-by-Step Linearization Method and Finite Difference Method. Fixed points or equilibrium positions and singular points have been shown in the state control space. In order to find the response to a step DC voltage, the nonlinear equation of motion has been solved using Galerkin-based reduced-order model and time histories and phase portrait for different applied voltages have been shown. The effects of electrostatic pressure on stability of FGM micro-beams having various amounts of the ceramic constituent have been investigated.

Keywords: FGM, MEMS, nonlinear vibration, electrical, dynamic pull-in voltage

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22144 Reducing Uncertainty of Monte Carlo Estimated Fatigue Damage in Offshore Wind Turbines Using FORM

Authors: Jan-Tore H. Horn, Jørgen Juncher Jensen

Abstract:

Uncertainties related to fatigue damage estimation of non-linear systems are highly dependent on the tail behaviour and extreme values of the stress range distribution. By using a combination of the First Order Reliability Method (FORM) and Monte Carlo simulations (MCS), the accuracy of the fatigue estimations may be improved for the same computational efforts. The method is applied to a bottom-fixed, monopile-supported large offshore wind turbine, which is a non-linear and dynamically sensitive system. Different curve fitting techniques to the fatigue damage distribution have been used depending on the sea-state dependent response characteristics, and the effect of a bi-linear S-N curve is discussed. Finally, analyses are performed on several environmental conditions to investigate the long-term applicability of this multistep method. Wave loads are calculated using state-of-the-art theory, while wind loads are applied with a simplified model based on rotor thrust coefficients.

Keywords: fatigue damage, FORM, monopile, Monte Carlo, simulation, wind turbine

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22143 Simulation-Based Optimization of a Non-Uniform Piezoelectric Energy Harvester with Stack Boundary

Authors: Alireza Keshmiri, Shahriar Bagheri, Nan Wu

Abstract:

This research presents an analytical model for the development of an energy harvester with piezoelectric rings stacked at the boundary of the structure based on the Adomian decomposition method. The model is applied to geometrically non-uniform beams to derive the steady-state dynamic response of the structure subjected to base motion excitation and efficiently harvest the subsequent vibrational energy. The in-plane polarization of the piezoelectric rings is employed to enhance the electrical power output. A parametric study for the proposed energy harvester with various design parameters is done to prepare the dataset required for optimization. Finally, simulation-based optimization technique helps to find the optimum structural design with maximum efficiency. To solve the optimization problem, an artificial neural network is first trained to replace the simulation model, and then, a genetic algorithm is employed to find the optimized design variables. Higher geometrical non-uniformity and length of the beam lowers the structure natural frequency and generates a larger power output.

Keywords: piezoelectricity, energy harvesting, simulation-based optimization, artificial neural network, genetic algorithm

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22142 Validation of a Fluid-Structure Interaction Model of an Aortic Dissection versus a Bench Top Model

Authors: K. Khanafer

Abstract:

The aim of this investigation was to validate the fluid-structure interaction (FSI) model of type B aortic dissection with our experimental results from a bench-top-model. Another objective was to study the relationship between the size of a septectomy that increases the outflow of the false lumen and its effect on the values of the differential of pressure between true lumen and false lumen. FSI analysis based on Galerkin’s formulation was used in this investigation to study flow pattern and hemodynamics within a flexible type B aortic dissection model using boundary conditions from our experimental data. The numerical results of our model were verified against the experimental data for various tear size and location. Thus, CFD tools have a potential role in evaluating different scenarios and aortic dissection configurations.

Keywords: aortic dissection, fluid-structure interaction, in vitro model, numerical

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22141 Applying Napoleoni's 'Shell-State' Concept to Jihadist Organisations's Rise in Mali, Nigeria and Syria/Iraq, 2011-2015

Authors: Francesco Saverio Angiò

Abstract:

The Islamic State of Iraq and the Levant / Syria (ISIL/S), Al-Qaeda in the Islamic Maghreb (AQIM) and People Committed to the Propagation of the Prophet's Teachings and Jihad, also known as ‘Boko Haram’ (BH), have fought successfully against Syria and Iraq, Mali, Nigeria’s government, respectively. According to Napoleoni, the ‘shell-state’ concept can explain the economic dimension and the financing model of the ISIL insurgency. However, she argues that AQIM and BH did not properly plan their financial model. Consequently, her idea would not be suitable to these groups. Nevertheless, AQIM and BH’s economic performances and their (short) territorialisation suggest that their financing models respond to a well-defined strategy, which they were able to adapt to new circumstances. Therefore, Napoleoni’s idea of ‘shell-state’ can be applied to the three jihadist armed groups. In the last five years, together with other similar entities, ISIL/S, AQIM and BH have been fighting against governments with insurgent tactics and terrorism acts, conquering and ruling a quasi-state; a physical space they presented as legitimate territorial entity, thanks to a puritan version of the Islamic law. In these territories, they have exploited the traditional local economic networks. In addition, they have contributed to the development of legal and illegal transnational business activities. They have also established a justice system and created an administrative structure to supply services. Napoleoni’s ‘shell-state’ can describe the evolution of ISIL/S, AQIM and BH, which has switched from an insurgency to a proto or a quasi-state entity, enjoying a significant share of power over territories and populations. Napoleoni first developed and applied the ‘Shell-state’ concept to describe the nature of groups such as the Palestine Liberation Organisation (PLO), before using it to explain the expansion of ISIL. However, her original conceptualisation emphasises on the economic dimension of the rise of the insurgency, focusing on the ‘business’ model and the insurgents’ financing management skills, which permits them to turn into an organisation. However, the idea of groups which use, coordinate and grab some territorial economic activities (at the same time, encouraging new criminal ones), can also be applied to administrative, social, infrastructural, legal and military levels of their insurgency, since they contribute to transform the insurgency to the same extent the economic dimension does. In addition, according to Napoleoni’s view, the ‘shell-state’ prism is valid to understand the ISIL/S phenomenon, because the group has carefully planned their financial steps. Napoleoni affirmed that ISIL/S carries out activities in order to promote their conversion from a group relying on external sponsors to an entity that can penetrate and condition local economies. On the contrary, ‘shell-state’ could not be applied to AQIM or BH, which are acting more like smugglers. Nevertheless, despite its failure to control territories, as ISIL has been able to do, AQIM and BH have responded strategically to their economic circumstances and have defined specific dynamics to ensure a flow of stable funds. Therefore, Napoleoni’s theory is applicable.

Keywords: shell-state, jihadist insurgency, proto or quasi-state entity economic planning, strategic financing

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22140 Structural Behavior of Subsoil Depending on Constitutive Model in Calculation Model of Pavement Structure-Subsoil System

Authors: M. Kadela

Abstract:

The load caused by the traffic movement should be transferred in the road constructions in a harmless way to the pavement as follows: − on the stiff upper layers of the structure (e.g. layers of asphalt: abrading and binding), and − through the layers of principal and secondary substructure, − on the subsoil, directly or through an improved subsoil layer. Reliable description of the interaction proceeding in a system “road construction – subsoil” should be in such case one of the basic requirements of the assessment of the size of internal forces of structure and its durability. Analyses of road constructions are based on: − elements of mechanics, which allows to create computational models, and − results of the experiments included in the criteria of fatigue life analyses. Above approach is a fundamental feature of commonly used mechanistic methods. They allow to use in the conducted evaluations of the fatigue life of structures arbitrarily complex numerical computational models. Considering the work of the system “road construction – subsoil”, it is commonly accepted that, as a result of repetitive loads on the subsoil under pavement, the growth of relatively small deformation in the initial phase is recognized, then this increase disappears, and the deformation takes the character completely reversible. The reliability of calculation model is combined with appropriate use (for a given type of analysis) of constitutive relationships. Phenomena occurring in the initial stage of the system “road construction – subsoil” is unfortunately difficult to interpret in the modeling process. The classic interpretation of the behavior of the material in the elastic-plastic model (e-p) is that elastic phase of the work (e) is undergoing to phase (e-p) by increasing the load (or growth of deformation in the damaging structure). The paper presents the essence of the calibration process of cooperating subsystem in the calculation model of the system “road construction – subsoil”, created for the mechanistic analysis. Calibration process was directed to show the impact of applied constitutive models on its deformation and stress response. The proper comparative base for assessing the reliability of created. This work was supported by the on-going research project “Stabilization of weak soil by application of layer of foamed concrete used in contact with subsoil” (LIDER/022/537/L-4/NCBR/2013) financed by The National Centre for Research and Development within the LIDER Programme. M. Kadela is with the Department of Building Construction Elements and Building Structures on Mining Areas, Building Research Institute, Silesian Branch, Katowice, Poland (phone: +48 32 730 29 47; fax: +48 32 730 25 22; e-mail: m.kadela@ itb.pl). models should be, however, the actual, monitored system “road construction – subsoil”. The paper presents too behavior of subsoil under cyclic load transmitted by pavement layers. The response of subsoil to cyclic load is recorded in situ by the observation system (sensors) installed on the testing ground prepared for this purpose, being a part of the test road near Katowice, in Poland. A different behavior of the homogeneous subsoil under pavement is observed for different seasons of the year, when pavement construction works as a flexible structure in summer, and as a rigid plate in winter. Albeit the observed character of subsoil response is the same regardless of the applied load and area values, this response can be divided into: - zone of indirect action of the applied load; this zone extends to the depth of 1,0 m under the pavement, - zone of a small strain, extending to about 2,0 m.

Keywords: road structure, constitutive model, calculation model, pavement, soil, FEA, response of soil, monitored system

Procedia PDF Downloads 357
22139 Energy Storage in the Future of Ethiopia Renewable Electricity Grid System

Authors: Dawit Abay Tesfamariam

Abstract:

Ethiopia’s Climate- Resilient Green Economy strategy focuses mainly on generating and utilization of Renewable Energy (RE). The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources on the grid from solar and wind energy were only 8 % of the total energy produced. On the other hand, the EEP electricity generation plan in 2030 indicates that 36 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the Energy PLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EPM analysis for two predictive scenarios. The EPM simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Hence, the model’s results are in line with the actual 2016 output. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EPM simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was dominant in all months except in the three rainy months of the year (June, July, and August). Consequently, based on the validated outcomes of EPM indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that; if the excess power is utilized with a storage mechanism that can stabilize the grid system; as a result, the extra RE generated can be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming energy storage system to synchronize with RE potentials that can be generated from RE.

Keywords: renewable energy, storage, wind, energyplan

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22138 Oil Reservoir Asphalting Precipitation Estimating during CO2 Injection

Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

Abstract:

In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

Procedia PDF Downloads 364